1
|
Al Darwish FM, Coolen BF, van Kammen CM, Alles LK, de Vos J, Schiffelers RM, Lely TA, Strijkers GJ, Terstappen F. Assessment of feto-placental oxygenation and perfusion in a rat model of placental insufficiency using T2* mapping and 3D dynamic contrast-enhanced MRI. Placenta 2024; 151:19-25. [PMID: 38657321 DOI: 10.1016/j.placenta.2024.04.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 04/05/2024] [Accepted: 04/12/2024] [Indexed: 04/26/2024]
Abstract
INTRODUCTION Placental insufficiency may lead to preeclampsia and fetal growth restriction. There is no cure for placental insufficiency, emphasizing the need for monitoring fetal and placenta health. Current monitoring methods are limited, underscoring the necessity for imaging techniques to evaluate fetal-placental perfusion and oxygenation. This study aims to use MRI to evaluate placental oxygenation and perfusion in the reduced uterine perfusion pressure (RUPP) model of placental insufficiency. METHODS Pregnant rats were randomized to RUPP (n = 11) or sham surgery (n = 8) on gestational day 14. On gestational day 19, rats imaged using a 7T MRI scanner to assess oxygenation and perfusion using T2* mapping and 3D-DCE MRI sequences, respectively. The effect of the RUPP on the feto-placental units were analyzed from the MRI images. RESULTS RUPP surgery led to reduced oxygenation in the labyrinth (24.7 ± 1.8 ms vs. 28.0 ± 2.1 ms, P = 0.002) and junctional zone (7.0 ± 0.9 ms vs. 8.1 ± 1.1 ms, P = 0.04) of the placenta, as indicated by decreased T2* values. However, here were no significant differences in fetal organ oxygenation or placental perfusion between RUPP and sham animals. DISCUSSION The reduced placental oxygenation without a corresponding decrease in perfusion suggests an adaptive response to placental ischemia. While acute reduction in placental perfusion may cause placental hypoxia, persistence of this condition could indicate chronic placental insufficiency after ischemic reperfusion injury. Thus, placental oxygenation may be a more reliable biomarker for assessing fetal condition than perfusion in hypertensive disorders of pregnancies including preeclampsia and FGR.
Collapse
Affiliation(s)
- Fatimah M Al Darwish
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, 1105, AZ, Amsterdam, Netherlands.
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, 1105, AZ, Amsterdam, Netherlands.
| | - Caren M van Kammen
- Department of Obstetrics, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht University, 3584, EA, Utrecht, Netherlands; Department of CDL Research, University Medical Center Utrecht, Utrecht University, 3584, EA, Utrecht, Netherlands.
| | - Lindy K Alles
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, 1105, AZ, Amsterdam, Netherlands.
| | - Judith de Vos
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, 1105, AZ, Amsterdam, Netherlands.
| | - Raymond M Schiffelers
- Department of CDL Research, University Medical Center Utrecht, Utrecht University, 3584, EA, Utrecht, Netherlands.
| | - Titia A Lely
- Department of Obstetrics, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht University, 3584, EA, Utrecht, Netherlands.
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, 1105, AZ, Amsterdam, Netherlands.
| | - Fieke Terstappen
- Department of Obstetrics, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht University, 3584, EA, Utrecht, Netherlands.
| |
Collapse
|
2
|
Groen JA, Crezee J, van Laarhoven HWM, Coolen BF, Strijkers GJ, Bijlsma MF, Kok HP. Robust, planning-based targeted locoregional tumour heating in small animals. Phys Med Biol 2024; 69:085017. [PMID: 38471172 DOI: 10.1088/1361-6560/ad3324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 03/12/2024] [Indexed: 03/14/2024]
Abstract
Objective.To improve hyperthermia in clinical practice, pre-clinical hyperthermia research is essential to investigate hyperthermia effects and assess novel treatment strategies. Translating pre-clinical hyperthermia findings into clinically viable protocols requires laboratory animal treatment techniques similar to clinical hyperthermia techniques. The ALBA micro8 electromagnetic heating system (Med-logix SRL, Rome, Italy) has recently been developed to provide the targeted locoregional tumour heating currently lacking for pre-clinical research. This study evaluates the heat focusing properties of this device and its ability to induce robust locoregional tumour heating under realistic physiological conditions using simulations.Approach.Simulations were performed using the Plan2Heat treatment planning package (Amsterdam UMC, the Netherlands). First, the specific absorption rate (SAR) focus was characterised using a homogeneous phantom. Hereafter, a digital mouse model was used for the characterisation of heating robustness in a mouse. Device settings were optimised for treatment of a pancreas tumour and tested for varying circumstances. The impact of uncertainties in tissue property and perfusion values was evaluated using polynomial chaos expansion. Treatment quality and robustness were evaluated based on SAR and temperature distributions.Main results.The SAR distributions within the phantom are well-focused and can be adjusted to target any specific location. The focus size (full-width half-maximum) is a spheroid with diameters 9 mm (radially) and 20 mm (axially). The mouse model simulations show strong robustness against respiratory motion and intestine and stomach filling (∆T90≤0.14°C).Mouse positioning errors in the cranial-caudal direction lead to∆T90≤0.23°C. Uncertainties in tissue property and perfusion values were found to impact the treatment plan up to 0.56 °C (SD), with a variation onT90of 0.32 °C (1 SD).Significance.Our work shows that the pre-clinical phased-array system can provide adequate and robust locoregional heating of deep-seated target regions in mice. Using our software, robust treatment plans can be generated for pre-clinical hyperthermia research.
Collapse
Affiliation(s)
- Jort A Groen
- Amsterdam UMC location University of Amsterdam, Radiation Oncology, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Cancer biology and immunology, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Treatment and quality of life, Amsterdam, The Netherlands
| | - Johannes Crezee
- Amsterdam UMC location University of Amsterdam, Radiation Oncology, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Cancer biology and immunology, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Treatment and quality of life, Amsterdam, The Netherlands
| | - Hanneke W M van Laarhoven
- Cancer Center Amsterdam, Treatment and quality of life, Amsterdam, The Netherlands
- Amsterdam UMC location University of Amsterdam, Department of Medical Oncology, Amsterdam, The Netherlands
| | - Bram F Coolen
- Amsterdam UMC location University of Amsterdam, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands
| | - Gustav J Strijkers
- Amsterdam UMC location University of Amsterdam, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands
| | - Maarten F Bijlsma
- Cancer Center Amsterdam, Cancer biology and immunology, Amsterdam, The Netherlands
- Amsterdam UMC location University of Amsterdam, Center for Experimental and Molecular Medicine, Laboratory for Experimental Oncology and Radiobiology, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Imaging and biomarkers, Amsterdam, the Netherlands
- Oncode Institute, Amsterdam, The Netherlands
| | - H Petra Kok
- Amsterdam UMC location University of Amsterdam, Radiation Oncology, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Cancer biology and immunology, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Treatment and quality of life, Amsterdam, The Netherlands
| |
Collapse
|
3
|
Sekita A, Unterweger H, Berg S, Ohlmeyer S, Bäuerle T, Zheng KH, Coolen BF, Nederveen AJ, Cabella C, Rossi S, Stroes ESG, Alexiou C, Lyer S, Cicha I. Accumulation of Iron Oxide-Based Contrast Agents in Rabbit Atherosclerotic Plaques in Relation to Plaque Age and Vulnerability Features. Int J Nanomedicine 2024; 19:1645-1666. [PMID: 38406599 PMCID: PMC10893894 DOI: 10.2147/ijn.s430693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 12/14/2023] [Indexed: 02/27/2024] Open
Abstract
Purpose In this study, a detailed characterization of a rabbit model of atherosclerosis was performed to assess the optimal time frame for evaluating plaque vulnerability using superparamagnetic iron oxide nanoparticle (SPION)-enhanced magnetic resonance imaging (MRI). Methods The progression of atherosclerosis induced by ballooning and a high-cholesterol diet was monitored using angiography, and the resulting plaques were characterized using immunohistochemistry and histology. Morphometric analyses were performed to evaluate plaque size and vulnerability features. The accumulation of SPIONs (novel dextran-coated SPIONDex and ferumoxytol) in atherosclerotic plaques was investigated by histology and MRI and correlated with plaque age and vulnerability. Toxicity of SPIONDex was evaluated in rats. Results Weak positive correlations were detected between plaque age and intima thickness, and total macrophage load. A strong negative correlation was observed between the minimum fibrous cap thickness and plaque age as well as the mean macrophage load. The accumulation of SPION in the atherosclerotic plaques was detected by MRI 24 h after administration and was subsequently confirmed by Prussian blue staining of histological specimens. Positive correlations between Prussian blue signal in atherosclerotic plaques, plaque age, and macrophage load were detected. Very little iron was observed in the histological sections of the heart and kidney, whereas strong staining of SPIONDex and ferumoxytol was detected in the spleen and liver. In contrast to ferumoxytol, SPIONDex administration in rabbits was well tolerated without inducing hypersensitivity. The maximum tolerated dose in rat model was higher than 100 mg Fe/kg. Conclusion Older atherosclerotic plaques with vulnerable features in rabbits are a useful tool for investigating iron oxide-based contrast agents for MRI. Based on the experimental data, SPIONDex particles constitute a promising candidate for further clinical translation as a safe formulation that offers the possibility of repeated administration free from the risks associated with other types of magnetic contrast agents.
Collapse
Affiliation(s)
- Alexander Sekita
- ENT-Department, Section of Experimental Oncology Und Nanomedicine (SEON), Else Kröner-Fresenius-Stiftung-Professorship, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Harald Unterweger
- ENT-Department, Section of Experimental Oncology Und Nanomedicine (SEON), Else Kröner-Fresenius-Stiftung-Professorship, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Sonja Berg
- ENT-Department, Section of Experimental Oncology Und Nanomedicine (SEON), Else Kröner-Fresenius-Stiftung-Professorship, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Sabine Ohlmeyer
- Institute of Radiology, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Tobias Bäuerle
- Preclinical Imaging Platform Erlangen (PIPE), Universitätsklinikum Erlangen, Erlangen, Germany
| | - Kang H Zheng
- Department of Vascular Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Claudia Cabella
- Bracco Imaging SpA, Centro Ricerche Bracco, Colleretto Giacosa, Turin, Italy
| | - Silvia Rossi
- Bracco Imaging SpA, Centro Ricerche Bracco, Colleretto Giacosa, Turin, Italy
| | - Erik S G Stroes
- Department of Vascular Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Christoph Alexiou
- ENT-Department, Section of Experimental Oncology Und Nanomedicine (SEON), Else Kröner-Fresenius-Stiftung-Professorship, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Stefan Lyer
- ENT-Department, Section of Experimental Oncology Und Nanomedicine (SEON), Else Kröner-Fresenius-Stiftung-Professorship, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Iwona Cicha
- ENT-Department, Section of Experimental Oncology Und Nanomedicine (SEON), Else Kröner-Fresenius-Stiftung-Professorship, Universitätsklinikum Erlangen, Erlangen, Germany
| |
Collapse
|
4
|
Baas KPA, Vu C, Shen J, Coolen BF, Biemond BJ, Strijkers GJ, Wood JC, Nederveen AJ. Venous Blood Oxygenation Measurements Using TRUST and T2-TRIR MRI During Hypoxic and Hypercapnic Gas Challenges. J Magn Reson Imaging 2023; 58:1903-1914. [PMID: 37092724 DOI: 10.1002/jmri.28744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 03/31/2023] [Accepted: 03/31/2023] [Indexed: 04/25/2023] Open
Abstract
BACKGROUND Oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO2 ) may serve as biomarkers in several diseases. OEF and CMRO2 can be estimated from venous blood oxygenation (Yv ) levels, which in turn can be calculated from venous blood T2 values (T2b ). T2b can be measured using different MRI sequences, including T2-relaxation-under-spin-tagging (TRUST) and T2-prepared-blood-relaxation-imaging-with-inversion-recovery (T2-TRIR). The latter measures both T2b and T1 (T1b ) but was found previously to overestimate T2b compared to TRUST. It remained unclear, however, if this bias is constant across higher and lower oxygen saturations. PURPOSE To compare TRUST and T2-TRIR across a range of O2 saturations using hypoxic and hypercapnic gas challenges. STUDY TYPE Prospective. POPULATION Twelve healthy volunteers (four female, age 36 ± 10 years). FIELD STRENGTH/SEQUENCE A 3T; turbo-field echo-planar-imaging (TFEPI), echo-planar-imaging (EPI), and fast-field-echo (FFE). ASSESSMENT TRUST- and T2-TRIR-derived T2b , Yv , OEF, and CMRO2 were compared across different respiratory challenges. T1b from T2-TRIR was used to estimate Hct (HctTRIR ) and compared with venipuncture (HctVP ). STATISTICAL TESTS Shapiro-Wilk, one-sample and paired-sample t-test, repeated measures ANOVA, Friedman test, Bland-Altman, and correlation analysis. Bonferroni multiple-comparison correction was performed. Significance level was 0.05. RESULTS A significant bias was observed between TRUST- and T2-TRIR-derived T2b , Yv , and OEF values (-13 ± 11 msec, -5.3% ± 3.5% and 5.9 ± 4.1%, respectively). For Yv and OEF, this bias was constant across the range of measured values. T1b was significantly lower during severe hypoxia and hypercapnia compared to baseline (1712 ± 86 msec and 1634 ± 79 msec compared to 1757 ± 90 msec). While no significant bias was found between HctVP and HctTRIR (0.02% ± 0.06%, P = 0.20), the correlation between these Hct values was significant but weak (r = 0.19). DATA CONCLUSION Given the constant bias, TRUST- and T2-TRIR-derived venous T2b values can be used interchangeably to estimate Yv , OEF, and CMRO2 across a broad range of oxygen saturations. Hct from T2-TRIR-derived T1-values only weakly correlated with Hct from venipuncture. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 2.
Collapse
Affiliation(s)
- Koen P A Baas
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Chau Vu
- Biomedical Engineering, University of Southern California, Los Angeles, California, USA
| | - Jian Shen
- Biomedical Engineering, University of Southern California, Los Angeles, California, USA
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands
| | - Bart J Biemond
- Department of Hematology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands
| | - John C Wood
- Biomedical Engineering, University of Southern California, Los Angeles, California, USA
- Division of Cardiology, Children's Hospital Los Angeles, University of Southern California, Los Angeles, California, USA
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| |
Collapse
|
5
|
Huijskes MM, Icardo JM, Coolen BF, Jensen B. Laterality defect of the heart in non-teleost fish. J Anat 2023; 243:1052-1058. [PMID: 37533305 PMCID: PMC10641032 DOI: 10.1111/joa.13933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/04/2023] [Accepted: 07/10/2023] [Indexed: 08/04/2023] Open
Abstract
Dextrocardia is a rare congenital malformation in humans in which most of the heart mass is positioned in the right hemithorax rather than on the left. The heart itself may be normal and dextrocardia is sometimes diagnosed during non-related explorations. A few reports have documented atypical positions of the cardiac chambers in farmed teleost fish. Here, we report the casual finding of a left-right mirrored heart in an 85 cm long wild-caught spiny dogfish (Squalus acanthias) with several organ malformations. Macroscopic observations showed an outflow tract originating from the left side of the ventricular mass, rather than from the right. Internal inspection revealed the expected structures and a looped cavity. The inner curvature of the loop comprised a large trabeculation, the bulboventricular fold, as expected. The junction between the sinus venosus and the atrium appeared normal, only mirrored. MRI data acquired at 0.7 mm isotropic resolution and subsequent 3D-modeling revealed the atrioventricular canal was to the right of the bulboventricular fold, rather than on the left. Spurred by the finding of dextrocardia in the shark, we revisit our previously published material on farmed Adriatic sturgeon (Acipenser naccarii), a non-teleost bony fish. We found several alevins with inverted (left-loop) hearts, amounting to an approximate incidence of 1%-2%. Additionally, an adult sturgeon measuring 90 cm in length showed abnormal topology of the cardiac chambers, but normal position of the abdominal organs. In conclusion, left-right mirrored hearts, a setting that resembles human dextrocardia, can occur in both farmed and wild non-teleost fish.
Collapse
Affiliation(s)
- Myrte M. Huijskes
- Department of Medical Biology, Amsterdam Cardiovascular SciencesUniversity of Amsterdam, Amsterdam UMCAmsterdamthe Netherlands
| | - José M. Icardo
- Department of Anatomy and Cell BiologyUniversity of CantabriaSantanderSpain
| | - Bram F. Coolen
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular SciencesUniversity of Amsterdam, Amsterdam UMCAmsterdamthe Netherlands
| | - Bjarke Jensen
- Department of Medical Biology, Amsterdam Cardiovascular SciencesUniversity of Amsterdam, Amsterdam UMCAmsterdamthe Netherlands
| |
Collapse
|
6
|
Coolen BF. Editorial for "Black-Blood Magnetization Prepared 2 Rapid Acquisition Gradient Echoes: A Fast and Three-dimensional MR Black-blood T1 Mapping Technique for Quantitative Assessment of Atherosclerosis and Venous Thrombosis". J Magn Reson Imaging 2023. [PMID: 38014867 DOI: 10.1002/jmri.29154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 11/02/2023] [Accepted: 11/03/2023] [Indexed: 11/29/2023] Open
Affiliation(s)
- Bram F Coolen
- Biomedical Engineering and Physics, Amsterdam UMC, location University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| |
Collapse
|
7
|
Baas KPA, Everard AJ, Körver S, van Dussen L, Coolen BF, Strijkers GJ, Hollak CEM, Nederveen AJ. Progressive Changes in Cerebral Apparent Diffusion Values in Fabry Disease: A 5-Year Follow-up MRI Study. AJNR Am J Neuroradiol 2023; 44:1157-1164. [PMID: 37770205 PMCID: PMC10549936 DOI: 10.3174/ajnr.a8001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 08/16/2023] [Indexed: 10/03/2023]
Abstract
BACKGROUND AND PURPOSE White matter lesions are commonly found in patients with Fabry disease. Existing studies have shown elevated diffusivity in healthy-appearing brain regions that are commonly associated with white matter lesions, suggesting that DWI could help detect white matter lesions at an earlier stage This study explores whether diffusivity changes precede white matter lesion formation in a cohort of patients with Fabry disease undergoing yearly MR imaging examinations during a 5-year period. MATERIALS AND METHODS T1-weighted anatomic, FLAIR, and DWI scans of 48 patients with Fabry disease (23 women; median age, 44 years; range, 15-69 years) were retrospectively included. White matter lesions and tissue probability maps were segmented and, together with ADC maps, were transformed into standard space. ADC values were determined within lesions before and after detection on FLAIR images and compared with normal-appearing white matter ADC. By means of linear mixed-effects modeling, changes in ADC and ΔADC (relative to normal-appearing white matter) across time were investigated. RESULTS ADC was significantly higher within white matter lesions compared with normal-appearing white matter (P < .01), even before detection on FLAIR images. ADC and ΔADC were significantly affected by sex, showing higher values in men (60.1 [95% CI, 23.8-96.3] ×10-6mm2/s and 35.1 [95% CI, 6.0-64.2] ×10-6mm2/s), respectively. ΔADC increased faster in men compared with women (0.99 [95% CI, 0.27-1.71] ×10-6mm2/s/month). ΔADC increased with time even when only considering data from before detection (0.57 [95% CI, 0.01-1.14] ×10-6mm2/s/month). CONCLUSIONS Our results indicate that in Fabry disease, changes in diffusion precede the formation of white matter lesions and that microstructural changes progress faster in men compared with women. These findings suggest that DWI may be of predictive value for white matter lesion formation in Fabry disease.
Collapse
Affiliation(s)
- Koen P A Baas
- From the Department of Radiology and Nuclear Medicine (K.P.A.B., A.J.N.), Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Albert J Everard
- Faculty of Science (A.J.E.), Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Simon Körver
- Department of Endocrinology and Metabolism (S.K., L.v.D., C.E.M.H.), Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Laura van Dussen
- Department of Endocrinology and Metabolism (S.K., L.v.D., C.E.M.H.), Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics (B.F.C., G.J.S.), Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences (B.F.C., G.J.S.), University of Amsterdam, Amsterdam, the Netherlands
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics (B.F.C., G.J.S.), Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences (B.F.C., G.J.S.), University of Amsterdam, Amsterdam, the Netherlands
| | - Carla E M Hollak
- Department of Endocrinology and Metabolism (S.K., L.v.D., C.E.M.H.), Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Aart J Nederveen
- From the Department of Radiology and Nuclear Medicine (K.P.A.B., A.J.N.), Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| |
Collapse
|
8
|
Al Darwish FM, Meijerink L, Coolen BF, Strijkers GJ, Bekker M, Lely T, Terstappen F. From Molecules to Imaging: Assessment of Placental Hypoxia Biomarkers in Placental Insufficiency Syndromes. Cells 2023; 12:2080. [PMID: 37626890 PMCID: PMC10452979 DOI: 10.3390/cells12162080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 08/04/2023] [Accepted: 08/15/2023] [Indexed: 08/27/2023] Open
Abstract
Placental hypoxia poses significant risks to both the developing fetus and the mother during pregnancy, underscoring the importance of early detection and monitoring. Effectively identifying placental hypoxia and evaluating the deterioration in placental function requires reliable biomarkers. Molecular biomarkers in placental tissue can only be determined post-delivery and while maternal blood biomarkers can be measured over time, they can merely serve as proxies for placental function. Therefore, there is an increasing demand for non-invasive imaging techniques capable of directly assessing the placental condition over time. Recent advancements in imaging technologies, including photoacoustic and magnetic resonance imaging, offer promising tools for detecting and monitoring placental hypoxia. Integrating molecular and imaging biomarkers may revolutionize the detection and monitoring of placental hypoxia, improving pregnancy outcomes and reducing long-term health complications. This review describes current research on molecular and imaging biomarkers of placental hypoxia both in human and animal studies and aims to explore the benefits of an integrated approach throughout gestation.
Collapse
Affiliation(s)
- Fatimah M. Al Darwish
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (B.F.C.); (G.J.S.)
| | - Lotte Meijerink
- Department of Obstetrics, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Utrecht University, 3584 EA Utrecht, The Netherlands; (L.M.); (M.B.); (T.L.); (F.T.)
| | - Bram F. Coolen
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (B.F.C.); (G.J.S.)
| | - Gustav J. Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (B.F.C.); (G.J.S.)
| | - Mireille Bekker
- Department of Obstetrics, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Utrecht University, 3584 EA Utrecht, The Netherlands; (L.M.); (M.B.); (T.L.); (F.T.)
| | - Titia Lely
- Department of Obstetrics, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Utrecht University, 3584 EA Utrecht, The Netherlands; (L.M.); (M.B.); (T.L.); (F.T.)
| | - Fieke Terstappen
- Department of Obstetrics, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Utrecht University, 3584 EA Utrecht, The Netherlands; (L.M.); (M.B.); (T.L.); (F.T.)
| |
Collapse
|
9
|
Grandjean J, Desrosiers-Gregoire G, Anckaerts C, Angeles-Valdez D, Ayad F, Barrière DA, Blockx I, Bortel A, Broadwater M, Cardoso BM, Célestine M, Chavez-Negrete JE, Choi S, Christiaen E, Clavijo P, Colon-Perez L, Cramer S, Daniele T, Dempsey E, Diao Y, Doelemeyer A, Dopfel D, Dvořáková L, Falfán-Melgoza C, Fernandes FF, Fowler CF, Fuentes-Ibañez A, Garin CM, Gelderman E, Golden CEM, Guo CCG, Henckens MJAG, Hennessy LA, Herman P, Hofwijks N, Horien C, Ionescu TM, Jones J, Kaesser J, Kim E, Lambers H, Lazari A, Lee SH, Lillywhite A, Liu Y, Liu YY, López-Castro A, López-Gil X, Ma Z, MacNicol E, Madularu D, Mandino F, Marciano S, McAuslan MJ, McCunn P, McIntosh A, Meng X, Meyer-Baese L, Missault S, Moro F, Naessens DMP, Nava-Gomez LJ, Nonaka H, Ortiz JJ, Paasonen J, Peeters LM, Pereira M, Perez PD, Pompilus M, Prior M, Rakhmatullin R, Reimann HM, Reinwald J, Del Rio RT, Rivera-Olvera A, Ruiz-Pérez D, Russo G, Rutten TJ, Ryoke R, Sack M, Salvan P, Sanganahalli BG, Schroeter A, Seewoo BJ, Selingue E, Seuwen A, Shi B, Sirmpilatze N, Smith JAB, Smith C, Sobczak F, Stenroos PJ, Straathof M, Strobelt S, Sumiyoshi A, Takahashi K, Torres-García ME, Tudela R, van den Berg M, van der Marel K, van Hout ATB, Vertullo R, Vidal B, Vrooman RM, Wang VX, Wank I, Watson DJG, Yin T, Zhang Y, Zurbruegg S, Achard S, Alcauter S, Auer DP, Barbier EL, Baudewig J, Beckmann CF, Beckmann N, Becq GJPC, Blezer ELA, Bolbos R, Boretius S, Bouvard S, Budinger E, Buxbaum JD, Cash D, Chapman V, Chuang KH, Ciobanu L, Coolen BF, Dalley JW, Dhenain M, Dijkhuizen RM, Esteban O, Faber C, Febo M, Feindel KW, Forloni G, Fouquet J, Garza-Villarreal EA, Gass N, Glennon JC, Gozzi A, Gröhn O, Harkin A, Heerschap A, Helluy X, Herfert K, Heuser A, Homberg JR, Houwing DJ, Hyder F, Ielacqua GD, Jelescu IO, Johansen-Berg H, Kaneko G, Kawashima R, Keilholz SD, Keliris GA, Kelly C, Kerskens C, Khokhar JY, Kind PC, Langlois JB, Lerch JP, López-Hidalgo MA, Manahan-Vaughan D, Marchand F, Mars RB, Marsella G, Micotti E, Muñoz-Moreno E, Near J, Niendorf T, Otte WM, Pais-Roldán P, Pan WJ, Prado-Alcalá RA, Quirarte GL, Rodger J, Rosenow T, Sampaio-Baptista C, Sartorius A, Sawiak SJ, Scheenen TWJ, Shemesh N, Shih YYI, Shmuel A, Soria G, Stoop R, Thompson GJ, Till SM, Todd N, Van Der Linden A, van der Toorn A, van Tilborg GAF, Vanhove C, Veltien A, Verhoye M, Wachsmuth L, Weber-Fahr W, Wenk P, Yu X, Zerbi V, Zhang N, Zhang BB, Zimmer L, Devenyi GA, Chakravarty MM, Hess A. Author Correction: A consensus protocol for functional connectivity analysis in the rat brain. Nat Neurosci 2023:10.1038/s41593-023-01328-1. [PMID: 37072562 DOI: 10.1038/s41593-023-01328-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2023]
Affiliation(s)
- Joanes Grandjean
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands.
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
| | - Gabriel Desrosiers-Gregoire
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - Cynthia Anckaerts
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Diego Angeles-Valdez
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Fadi Ayad
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - David A Barrière
- UMR INRAE/CNRS 7247 Physiologie des Comportements et de la Reproduction, Physiologie de la reproduction et des comportements, Centre de recherche INRAE de Nouzilly, Tours, France
| | - Ines Blockx
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Aleksandra Bortel
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Margaret Broadwater
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Beatriz M Cardoso
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Marina Célestine
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Jorge E Chavez-Negrete
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Sangcheon Choi
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Emma Christiaen
- Institute Biomedical Technology (IBiTech), Electronics and Information Systems (ELIS), Ghent University, Gent, Belgium
| | - Perrin Clavijo
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Luis Colon-Perez
- Department of Pharmacology & Neuroscience, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Samuel Cramer
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Tolomeo Daniele
- Centre for Advanced Biomedical Imaging, University College London, London, UK
| | - Elaine Dempsey
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Yujian Diao
- CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Laboratory for Functional and Metabolic Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Arno Doelemeyer
- Musculoskeletal Diseases Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - David Dopfel
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Lenka Dvořáková
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Claudia Falfán-Melgoza
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Francisca F Fernandes
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Caitlin F Fowler
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Antonio Fuentes-Ibañez
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Clément M Garin
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Eveline Gelderman
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Carla E M Golden
- Seaver Autism Center for Research & Treatment, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Chao C G Guo
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Marloes J A G Henckens
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Department of Neuroscience and Pharmacology, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Lauren A Hennessy
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Peter Herman
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | - Nita Hofwijks
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Corey Horien
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Tudor M Ionescu
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Jolyon Jones
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Johannes Kaesser
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Eugene Kim
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Henriette Lambers
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Alberto Lazari
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Sung-Ho Lee
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amanda Lillywhite
- School of Life Sciences, University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
| | - Yikang Liu
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Yanyan Y Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Alejandra López-Castro
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Xavier López-Gil
- Magnetic Imaging Resonance Core Facility, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Zilu Ma
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Eilidh MacNicol
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Dan Madularu
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- Center for Translational Neuroimaging, Northeastern University, Boston, MA, USA
| | - Francesca Mandino
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Sabina Marciano
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Matthew J McAuslan
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Patrick McCunn
- Khokhar Lab, Department of Anatomy and Cell Biology, Western University, London, ON, Canada
| | - Alison McIntosh
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Xianzong Meng
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Lisa Meyer-Baese
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Stephan Missault
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Federico Moro
- Laboratory of Acute Brain Injury and Therapeutic Strategies, Department of NeuroscienceIstituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Daphne M P Naessens
- Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Laura J Nava-Gomez
- Facultad de Medicina, Universidad Autónoma de Querétaro, Querétaro, México
- Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | - Hiroi Nonaka
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Juan J Ortiz
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Jaakko Paasonen
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Lore M Peeters
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Mickaël Pereira
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Pablo D Perez
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Marjory Pompilus
- Febo Laboratory, Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Malcolm Prior
- School of Medicine, University of Nottingham, Nottingham, UK
| | | | - Henning M Reimann
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Jonathan Reinwald
- Translational Imaging, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Rodrigo Triana Del Rio
- Psychiatric neurosciences, Center for Psychiatric Neuroscience, Lausanne University and University Hospital Center, Unicentre, Lausanne, Switzerland
| | - Alejandro Rivera-Olvera
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | | | - Gabriele Russo
- Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Bochum, Germany
| | - Tobias J Rutten
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Rie Ryoke
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Markus Sack
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Piergiorgio Salvan
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Basavaraju G Sanganahalli
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | - Aileen Schroeter
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Bhedita J Seewoo
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- Centre for Microscopy, Characterisation & Analysis, Research Infrastructure Centres, University of Western Australia, Nedlands, WA, Australia
| | | | - Aline Seuwen
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Bowen Shi
- iHuman Institute, ShanghaiTech University, Shanghai, China
| | - Nikoloz Sirmpilatze
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
- Faculty of Biology and Psychology, Georg-August University of Göttingen, Göttingen, Germany
- DFG Research Center for Nanoscale Microscopy and Molecular Physiology of the Brain (CNMPB), Göttingen, Germany
| | - Joanna A B Smith
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Corrie Smith
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Filip Sobczak
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Petteri J Stenroos
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Milou Straathof
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Sandra Strobelt
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Akira Sumiyoshi
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Kengo Takahashi
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Maria E Torres-García
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Raul Tudela
- Group of Biomedical Imaging, Consorcio Centro de Investigación Biomédica en Red (CIBER) de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), University of Barcelona, Barcelona, Spain
| | - Monica van den Berg
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Kajo van der Marel
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Aran T B van Hout
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Roberta Vertullo
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Benjamin Vidal
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Roël M Vrooman
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Victora X Wang
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Isabel Wank
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - David J G Watson
- School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Ting Yin
- Animal Imaging and Technology Section, Center for Biomedical Imaging, École polytechnique fédérale de Lausanne, Lausanne, Switzerland
| | - Yongzhi Zhang
- Focused Ultrasound Laboratory, Department of Radiology Brigham and Women's Hospital, Boston, MA, USA
| | - Stefan Zurbruegg
- Neurosciences Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Sophie Achard
- Inria, University Grenoble Alpes, CNRS, Grenoble, France
| | - Sarael Alcauter
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Dorothee P Auer
- School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Emmanuel L Barbier
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Jürgen Baudewig
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
| | - Christian F Beckmann
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Nicolau Beckmann
- Musculoskeletal Diseases Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | | | - Erwin L A Blezer
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | | | - Susann Boretius
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
- Faculty of Biology and Psychology, Georg-August University of Göttingen, Göttingen, Germany
- DFG Research Center for Nanoscale Microscopy and Molecular Physiology of the Brain (CNMPB), Göttingen, Germany
| | - Sandrine Bouvard
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Eike Budinger
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Joseph D Buxbaum
- Seaver Autism Center for Research & Treatment, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Diana Cash
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Victoria Chapman
- School of Life Sciences, University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Kai-Hsiang Chuang
- Queensland Brain Institute and Centre for Advanced Imaging, University of Queensland, St. Lucia, QLD, Australia
| | | | - Bram F Coolen
- Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jeffrey W Dalley
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Marc Dhenain
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Rick M Dijkhuizen
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Oscar Esteban
- Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Cornelius Faber
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Marcelo Febo
- Febo Laboratory, Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Kirk W Feindel
- Centre for Microscopy, Characterisation & Analysis, Research Infrastructure Centres, University of Western Australia, Nedlands, WA, Australia
| | - Gianluigi Forloni
- Biology of Neurodogenerative Disorders, Department of Neuroscience Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Jérémie Fouquet
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
| | - Eduardo A Garza-Villarreal
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Natalia Gass
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Jeffrey C Glennon
- Conway Institute of Biomedical and Biomolecular Sciences, School of Medicine, University College Dublin, Dublin, Ireland
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Olli Gröhn
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Andrew Harkin
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Arend Heerschap
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Xavier Helluy
- Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Bochum, Germany
- Department of Biopsychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Kristina Herfert
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Arnd Heuser
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Judith R Homberg
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Danielle J Houwing
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Fahmeed Hyder
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | | | - Ileana O Jelescu
- CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Heidi Johansen-Berg
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Gen Kaneko
- School of Arts & Sciences, University of Houston-Victoria, Victoria, TX, USA
| | - Ryuta Kawashima
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Shella D Keilholz
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Georgios A Keliris
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Clare Kelly
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- School of Psychology, Trinity College Dublin, Dublin, Ireland
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Christian Kerskens
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- Trinity Centre for Biomedical Engineering, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Jibran Y Khokhar
- Khokhar Lab, Department of Anatomy and Cell Biology, Western University, London, ON, Canada
| | - Peter C Kind
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
- Centre for Brain Development and Repair, Institute for Stem Cell Biology and Regenerative Medicine, Bangalore, India
| | | | - Jason P Lerch
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- Department of Medical Biophysics, University of Toronto, Toronto, QC, Canada
| | - Monica A López-Hidalgo
- Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | | | - Fabien Marchand
- Université Clermont Auvergne, Inserm U1107 Neuro-Dol, Pharmacologie Fondamentale et Clinique de la Douleur, Clermont-Ferrand, France
| | - Rogier B Mars
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Gerardo Marsella
- Animal Care Unit, Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Edoardo Micotti
- Biology of Neurodogenerative Disorders, Department of Neuroscience Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Emma Muñoz-Moreno
- Magnetic Imaging Resonance Core Facility, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Jamie Near
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, QC, Canada
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- Experimental and Clinical Research Center, A Joint Cooperation Between the Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Willem M Otte
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
- Department of Pediatric Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Patricia Pais-Roldán
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Medical Imaging Physics (INM-4), Institute of Neuroscience and Medicine, Forschungszentrum Juelich, Juelich, Germany
| | - Wen-Ju Pan
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Roberto A Prado-Alcalá
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Gina L Quirarte
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Jennifer Rodger
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Tim Rosenow
- Centre for Microscopy, Characterisation and Analysis, University of Western Australia, Crawley, WA, Australia
| | - Cassandra Sampaio-Baptista
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK
| | - Alexander Sartorius
- Translational Imaging, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Stephen J Sawiak
- Translational Neuroimaging Laboratory, Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - Tom W J Scheenen
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Erwin L. Hahn Institute for MR Imaging, University of Duisburg-Essen, Essen, Germany
| | - Noam Shemesh
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Yen-Yu Ian Shih
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amir Shmuel
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Department of Physiology, McGill University, Montreal, QC, Canada
| | - Guadalupe Soria
- Laboratory of Surgical Neuroanatomy, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Ron Stoop
- Psychiatric neurosciences, Center for Psychiatric Neuroscience, Lausanne University and University Hospital Center, Unicentre, Lausanne, Switzerland
| | | | - Sally M Till
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Nick Todd
- Focused Ultrasound Laboratory, Department of Radiology Brigham and Women's Hospital, Boston, MA, USA
| | - Annemie Van Der Linden
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Annette van der Toorn
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Geralda A F van Tilborg
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Christian Vanhove
- Institute Biomedical Technology (IBiTech), Electronics and Information Systems (ELIS), Ghent University, Gent, Belgium
| | - Andor Veltien
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Marleen Verhoye
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Lydia Wachsmuth
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Wolfgang Weber-Fahr
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Patricia Wenk
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Xin Yu
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Valerio Zerbi
- Neuro-X Institute, School of Engineering (STI), EPFL, Lausanne, Switzerland
- Centre for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Nanyin Zhang
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Baogui B Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Luc Zimmer
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
- CERMEP - Imagerie du vivant, Lyon, France
- Hospices Civils de Lyon, Lyon, France
| | - Gabriel A Devenyi
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Andreas Hess
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| |
Collapse
|
10
|
Grandjean J, Desrosiers-Gregoire G, Anckaerts C, Angeles-Valdez D, Ayad F, Barrière DA, Blockx I, Bortel A, Broadwater M, Cardoso BM, Célestine M, Chavez-Negrete JE, Choi S, Christiaen E, Clavijo P, Colon-Perez L, Cramer S, Daniele T, Dempsey E, Diao Y, Doelemeyer A, Dopfel D, Dvořáková L, Falfán-Melgoza C, Fernandes FF, Fowler CF, Fuentes-Ibañez A, Garin CM, Gelderman E, Golden CEM, Guo CCG, Henckens MJAG, Hennessy LA, Herman P, Hofwijks N, Horien C, Ionescu TM, Jones J, Kaesser J, Kim E, Lambers H, Lazari A, Lee SH, Lillywhite A, Liu Y, Liu YY, López-Castro A, López-Gil X, Ma Z, MacNicol E, Madularu D, Mandino F, Marciano S, McAuslan MJ, McCunn P, McIntosh A, Meng X, Meyer-Baese L, Missault S, Moro F, Naessens DMP, Nava-Gomez LJ, Nonaka H, Ortiz JJ, Paasonen J, Peeters LM, Pereira M, Perez PD, Pompilus M, Prior M, Rakhmatullin R, Reimann HM, Reinwald J, Del Rio RT, Rivera-Olvera A, Ruiz-Pérez D, Russo G, Rutten TJ, Ryoke R, Sack M, Salvan P, Sanganahalli BG, Schroeter A, Seewoo BJ, Selingue E, Seuwen A, Shi B, Sirmpilatze N, Smith JAB, Smith C, Sobczak F, Stenroos PJ, Straathof M, Strobelt S, Sumiyoshi A, Takahashi K, Torres-García ME, Tudela R, van den Berg M, van der Marel K, van Hout ATB, Vertullo R, Vidal B, Vrooman RM, Wang VX, Wank I, Watson DJG, Yin T, Zhang Y, Zurbruegg S, Achard S, Alcauter S, Auer DP, Barbier EL, Baudewig J, Beckmann CF, Beckmann N, Becq GJPC, Blezer ELA, Bolbos R, Boretius S, Bouvard S, Budinger E, Buxbaum JD, Cash D, Chapman V, Chuang KH, Ciobanu L, Coolen BF, Dalley JW, Dhenain M, Dijkhuizen RM, Esteban O, Faber C, Febo M, Feindel KW, Forloni G, Fouquet J, Garza-Villarreal EA, Gass N, Glennon JC, Gozzi A, Gröhn O, Harkin A, Heerschap A, Helluy X, Herfert K, Heuser A, Homberg JR, Houwing DJ, Hyder F, Ielacqua GD, Jelescu IO, Johansen-Berg H, Kaneko G, Kawashima R, Keilholz SD, Keliris GA, Kelly C, Kerskens C, Khokhar JY, Kind PC, Langlois JB, Lerch JP, López-Hidalgo MA, Manahan-Vaughan D, Marchand F, Mars RB, Marsella G, Micotti E, Muñoz-Moreno E, Near J, Niendorf T, Otte WM, Pais-Roldán P, Pan WJ, Prado-Alcalá RA, Quirarte GL, Rodger J, Rosenow T, Sampaio-Baptista C, Sartorius A, Sawiak SJ, Scheenen TWJ, Shemesh N, Shih YYI, Shmuel A, Soria G, Stoop R, Thompson GJ, Till SM, Todd N, Van Der Linden A, van der Toorn A, van Tilborg GAF, Vanhove C, Veltien A, Verhoye M, Wachsmuth L, Weber-Fahr W, Wenk P, Yu X, Zerbi V, Zhang N, Zhang BB, Zimmer L, Devenyi GA, Chakravarty MM, Hess A. A consensus protocol for functional connectivity analysis in the rat brain. Nat Neurosci 2023; 26:673-681. [PMID: 36973511 PMCID: PMC10493189 DOI: 10.1038/s41593-023-01286-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 02/15/2023] [Indexed: 03/29/2023]
Abstract
Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows for comparisons with data modalities collected under invasive or terminal procedures. Currently, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. Here we introduce StandardRat, a consensus rat functional magnetic resonance imaging acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired from rats across 46 centers. We developed a reproducible pipeline for analyzing rat data acquired with diverse protocols and determined experimental and processing parameters associated with the robust detection of functional connectivity across centers. We show that the standardized protocol enhances biologically plausible functional connectivity patterns relative to previous acquisitions. The protocol and processing pipeline described here is openly shared with the neuroimaging community to promote interoperability and cooperation toward tackling the most important challenges in neuroscience.
Collapse
Affiliation(s)
- Joanes Grandjean
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands.
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
| | - Gabriel Desrosiers-Gregoire
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - Cynthia Anckaerts
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Diego Angeles-Valdez
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Fadi Ayad
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - David A Barrière
- UMR INRAE/CNRS 7247 Physiologie des Comportements et de la Reproduction, Physiologie de la reproduction et des comportements, Centre de recherche INRAE de Nouzilly, Tours, France
| | - Ines Blockx
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Aleksandra Bortel
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Margaret Broadwater
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Beatriz M Cardoso
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Marina Célestine
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Jorge E Chavez-Negrete
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Sangcheon Choi
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Emma Christiaen
- Institute Biomedical Technology (IBiTech), Electronics and Information Systems (ELIS), Ghent University, Gent, Belgium
| | - Perrin Clavijo
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Luis Colon-Perez
- Department of Pharmacology & Neuroscience, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Samuel Cramer
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Tolomeo Daniele
- Centre for Advanced Biomedical Imaging, University College London, London, UK
| | - Elaine Dempsey
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Yujian Diao
- CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Laboratory for Functional and Metabolic Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Arno Doelemeyer
- Musculoskeletal Diseases Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - David Dopfel
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Lenka Dvořáková
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Claudia Falfán-Melgoza
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Francisca F Fernandes
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Caitlin F Fowler
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Antonio Fuentes-Ibañez
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Clément M Garin
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Eveline Gelderman
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Carla E M Golden
- Seaver Autism Center for Research & Treatment, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Chao C G Guo
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Marloes J A G Henckens
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Department of Neuroscience and Pharmacology, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Lauren A Hennessy
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Peter Herman
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | - Nita Hofwijks
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Corey Horien
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Tudor M Ionescu
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Jolyon Jones
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Johannes Kaesser
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Eugene Kim
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Henriette Lambers
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Alberto Lazari
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Sung-Ho Lee
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amanda Lillywhite
- School of Life Sciences, University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
| | - Yikang Liu
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Yanyan Y Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Alejandra López-Castro
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Xavier López-Gil
- Magnetic Imaging Resonance Core Facility, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Zilu Ma
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Eilidh MacNicol
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Dan Madularu
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- Center for Translational Neuroimaging, Northeastern University, Boston, MA, USA
| | - Francesca Mandino
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Sabina Marciano
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Matthew J McAuslan
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Patrick McCunn
- Khokhar Lab, Department of Anatomy and Cell Biology, Western University, London, ON, Canada
| | - Alison McIntosh
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Xianzong Meng
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Lisa Meyer-Baese
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Stephan Missault
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Federico Moro
- Laboratory of Acute Brain Injury and Therapeutic Strategies, Department of NeuroscienceIstituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Daphne M P Naessens
- Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Laura J Nava-Gomez
- Facultad de Medicina, Universidad Autónoma de Querétaro, Querétaro, México
- Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | - Hiroi Nonaka
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Juan J Ortiz
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Jaakko Paasonen
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Lore M Peeters
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Mickaël Pereira
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Pablo D Perez
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Marjory Pompilus
- Febo Laboratory, Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Malcolm Prior
- School of Medicine, University of Nottingham, Nottingham, UK
| | | | - Henning M Reimann
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Jonathan Reinwald
- Translational Imaging, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Rodrigo Triana Del Rio
- Psychiatric neurosciences, Center for Psychiatric Neuroscience, Lausanne University and University Hospital Center, Unicentre, Lausanne, Switzerland
| | - Alejandro Rivera-Olvera
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | | | - Gabriele Russo
- Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Bochum, Germany
| | - Tobias J Rutten
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Rie Ryoke
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Markus Sack
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Piergiorgio Salvan
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Basavaraju G Sanganahalli
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | - Aileen Schroeter
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Bhedita J Seewoo
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- Centre for Microscopy, Characterisation & Analysis, Research Infrastructure Centres, University of Western Australia, Nedlands, WA, Australia
| | | | - Aline Seuwen
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Bowen Shi
- iHuman Institute, ShanghaiTech University, Shanghai, China
| | - Nikoloz Sirmpilatze
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
- Faculty of Biology and Psychology, Georg-August University of Göttingen, Göttingen, Germany
- DFG Research Center for Nanoscale Microscopy and Molecular Physiology of the Brain (CNMPB), Göttingen, Germany
| | - Joanna A B Smith
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Corrie Smith
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Filip Sobczak
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Petteri J Stenroos
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Milou Straathof
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Sandra Strobelt
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Akira Sumiyoshi
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Kengo Takahashi
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Maria E Torres-García
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Raul Tudela
- Group of Biomedical Imaging, Consorcio Centro de Investigación Biomédica en Red (CIBER) de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), University of Barcelona, Barcelona, Spain
| | - Monica van den Berg
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Kajo van der Marel
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Aran T B van Hout
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Roberta Vertullo
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Benjamin Vidal
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Roël M Vrooman
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Victora X Wang
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Isabel Wank
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - David J G Watson
- School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Ting Yin
- Animal Imaging and Technology Section, Center for Biomedical Imaging, École polytechnique fédérale de Lausanne, Lausanne, Switzerland
| | - Yongzhi Zhang
- Focused Ultrasound Laboratory, Department of Radiology Brigham and Women's Hospital, Boston, MA, USA
| | - Stefan Zurbruegg
- Neurosciences Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Sophie Achard
- Inria, University Grenoble Alpes, CNRS, Grenoble, France
| | - Sarael Alcauter
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Dorothee P Auer
- School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Emmanuel L Barbier
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Jürgen Baudewig
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
| | - Christian F Beckmann
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Nicolau Beckmann
- Musculoskeletal Diseases Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | | | - Erwin L A Blezer
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | | | - Susann Boretius
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
- Faculty of Biology and Psychology, Georg-August University of Göttingen, Göttingen, Germany
- DFG Research Center for Nanoscale Microscopy and Molecular Physiology of the Brain (CNMPB), Göttingen, Germany
| | - Sandrine Bouvard
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Eike Budinger
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Joseph D Buxbaum
- Seaver Autism Center for Research & Treatment, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Diana Cash
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Victoria Chapman
- School of Life Sciences, University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Kai-Hsiang Chuang
- Queensland Brain Institute and Centre for Advanced Imaging, University of Queensland, St. Lucia, QLD, Australia
| | | | - Bram F Coolen
- Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jeffrey W Dalley
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Marc Dhenain
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Rick M Dijkhuizen
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Oscar Esteban
- Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Cornelius Faber
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Marcelo Febo
- Febo Laboratory, Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Kirk W Feindel
- Centre for Microscopy, Characterisation & Analysis, Research Infrastructure Centres, University of Western Australia, Nedlands, WA, Australia
| | - Gianluigi Forloni
- Biology of Neurodogenerative Disorders, Department of Neuroscience Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Jérémie Fouquet
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
| | - Eduardo A Garza-Villarreal
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Natalia Gass
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Jeffrey C Glennon
- Conway Institute of Biomedical and Biomolecular Sciences, School of Medicine, University College Dublin, Dublin, Ireland
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Olli Gröhn
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Andrew Harkin
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Arend Heerschap
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Xavier Helluy
- Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Bochum, Germany
- Department of Biopsychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Kristina Herfert
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Arnd Heuser
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Judith R Homberg
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Danielle J Houwing
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Fahmeed Hyder
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | | | - Ileana O Jelescu
- CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Heidi Johansen-Berg
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Gen Kaneko
- School of Arts & Sciences, University of Houston-Victoria, Victoria, TX, USA
| | - Ryuta Kawashima
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Shella D Keilholz
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Georgios A Keliris
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Clare Kelly
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- School of Psychology, Trinity College Dublin, Dublin, Ireland
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Christian Kerskens
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- Trinity Centre for Biomedical Engineering, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Jibran Y Khokhar
- Khokhar Lab, Department of Anatomy and Cell Biology, Western University, London, ON, Canada
| | - Peter C Kind
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
- Centre for Brain Development and Repair, Institute for Stem Cell Biology and Regenerative Medicine, Bangalore, India
| | | | - Jason P Lerch
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- Department of Medical Biophysics, University of Toronto, Toronto, QC, Canada
| | - Monica A López-Hidalgo
- Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | | | - Fabien Marchand
- Université Clermont Auvergne, Inserm U1107 Neuro-Dol, Pharmacologie Fondamentale et Clinique de la Douleur, Clermont-Ferrand, France
| | - Rogier B Mars
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Gerardo Marsella
- Animal Care Unit, Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Edoardo Micotti
- Biology of Neurodogenerative Disorders, Department of Neuroscience Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Emma Muñoz-Moreno
- Magnetic Imaging Resonance Core Facility, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Jamie Near
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, QC, Canada
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- Experimental and Clinical Research Center, A Joint Cooperation Between the Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Willem M Otte
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
- Department of Pediatric Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Patricia Pais-Roldán
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Medical Imaging Physics (INM-4), Institute of Neuroscience and Medicine, Forschungszentrum Juelich, Juelich, Germany
| | - Wen-Ju Pan
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Roberto A Prado-Alcalá
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Gina L Quirarte
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Jennifer Rodger
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Tim Rosenow
- Centre for Microscopy, Characterisation and Analysis, University of Western Australia, Crawley, WA, Australia
| | - Cassandra Sampaio-Baptista
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK
| | - Alexander Sartorius
- Translational Imaging, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Stephen J Sawiak
- Translational Neuroimaging Laboratory, Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - Tom W J Scheenen
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Erwin L. Hahn Institute for MR Imaging, University of Duisburg-Essen, Essen, Germany
| | - Noam Shemesh
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Yen-Yu Ian Shih
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amir Shmuel
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Department of Physiology, McGill University, Montreal, QC, Canada
| | - Guadalupe Soria
- Laboratory of Surgical Neuroanatomy, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Ron Stoop
- Psychiatric neurosciences, Center for Psychiatric Neuroscience, Lausanne University and University Hospital Center, Unicentre, Lausanne, Switzerland
| | | | - Sally M Till
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Nick Todd
- Focused Ultrasound Laboratory, Department of Radiology Brigham and Women's Hospital, Boston, MA, USA
| | - Annemie Van Der Linden
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Annette van der Toorn
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Geralda A F van Tilborg
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Christian Vanhove
- Institute Biomedical Technology (IBiTech), Electronics and Information Systems (ELIS), Ghent University, Gent, Belgium
| | - Andor Veltien
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Marleen Verhoye
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Lydia Wachsmuth
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Wolfgang Weber-Fahr
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Patricia Wenk
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Xin Yu
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Valerio Zerbi
- Neuro-X Institute, School of Engineering (STI), EPFL, Lausanne, Switzerland
- Centre for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Nanyin Zhang
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Baogui B Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Luc Zimmer
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
- CERMEP - Imagerie du vivant, Lyon, France
- Hospices Civils de Lyon, Lyon, France
| | - Gabriel A Devenyi
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Andreas Hess
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| |
Collapse
|
11
|
Naessens DMP, de Vos J, Richard E, Wilhelmus MMM, Jongenelen CAM, Scholl ER, van der Wel NN, Heijst JA, Teunissen CE, Strijkers GJ, Coolen BF, VanBavel E, Bakker ENTP. Effect of long-term antihypertensive treatment on cerebrovascular structure and function in hypertensive rats. Sci Rep 2023; 13:3481. [PMID: 36859481 PMCID: PMC9977931 DOI: 10.1038/s41598-023-30515-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 02/24/2023] [Indexed: 03/03/2023] Open
Abstract
Midlife hypertension is an important risk factor for cognitive impairment and dementia, including Alzheimer's disease. We investigated the effects of long-term treatment with two classes of antihypertensive drugs to determine whether diverging mechanisms of blood pressure lowering impact the brain differently. Spontaneously hypertensive rats (SHR) were either left untreated or treated with a calcium channel blocker (amlodipine) or beta blocker (atenolol) until one year of age. The normotensive Wistar Kyoto rat (WKY) was used as a reference group. Both drugs lowered blood pressure equally, while only atenolol decreased heart rate. Cerebrovascular resistance was increased in SHR, which was prevented by amlodipine but not atenolol. SHR showed a larger carotid artery diameter with impaired pulsatility, which was prevented by atenolol. Cerebral arteries demonstrated inward remodelling, stiffening and endothelial dysfunction in SHR. Both treatments similarly improved these parameters. MRI revealed that SHR have smaller brains with enlarged ventricles. In addition, neurofilament light levels were increased in cerebrospinal fluid of SHR. However, neither treatment affected these parameters. In conclusion, amlodipine and atenolol both lower blood pressure, but elicit a different hemodynamic profile. Both medications improve cerebral artery structure and function, but neither drug prevented indices of brain damage in this model of hypertension.
Collapse
Affiliation(s)
- Daphne M. P. Naessens
- grid.509540.d0000 0004 6880 3010Amsterdam UMC Location University of Amsterdam, Biomedical Engineering and Physics, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands ,Amsterdam Cardiovascular Sciences, Microcirculation, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurovascular Disorders, Amsterdam, The Netherlands
| | - Judith de Vos
- grid.509540.d0000 0004 6880 3010Amsterdam UMC Location University of Amsterdam, Biomedical Engineering and Physics, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands ,Amsterdam Cardiovascular Sciences, Microcirculation, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurovascular Disorders, Amsterdam, The Netherlands
| | - Edo Richard
- grid.509540.d0000 0004 6880 3010Amsterdam UMC Location University of Amsterdam, Public and Occupational Health, Amsterdam, The Netherlands ,grid.10417.330000 0004 0444 9382Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Micha M. M. Wilhelmus
- grid.509540.d0000 0004 6880 3010Amsterdam UMC Location Vrije Universiteit Amsterdam, Anatomy and Neurosciences, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Cornelis A. M. Jongenelen
- grid.509540.d0000 0004 6880 3010Amsterdam UMC Location Vrije Universiteit Amsterdam, Anatomy and Neurosciences, Amsterdam, The Netherlands
| | - Edwin R. Scholl
- grid.5650.60000000404654431Amsterdam UMC Location University of Amsterdam, Medical Biology, Electron Microscopy Center Amsterdam, Amsterdam, The Netherlands
| | - Nicole N. van der Wel
- grid.5650.60000000404654431Amsterdam UMC Location University of Amsterdam, Medical Biology, Electron Microscopy Center Amsterdam, Amsterdam, The Netherlands
| | - Johannes A. Heijst
- grid.509540.d0000 0004 6880 3010Amsterdam UMC Location Vrije Universiteit Amsterdam, Neurochemistry Laboratory, Clinical Chemistry, Amsterdam, The Netherlands
| | - Charlotte E. Teunissen
- grid.484519.5Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands ,grid.509540.d0000 0004 6880 3010Amsterdam UMC Location Vrije Universiteit Amsterdam, Neurochemistry Laboratory, Clinical Chemistry, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neuroinfection and -Inflammation, Amsterdam, The Netherlands
| | - Gustav J. Strijkers
- grid.509540.d0000 0004 6880 3010Amsterdam UMC Location University of Amsterdam, Biomedical Engineering and Physics, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Bram F. Coolen
- grid.509540.d0000 0004 6880 3010Amsterdam UMC Location University of Amsterdam, Biomedical Engineering and Physics, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands ,Amsterdam Cardiovascular Sciences, Microcirculation, Amsterdam, The Netherlands
| | - Ed VanBavel
- grid.509540.d0000 0004 6880 3010Amsterdam UMC Location University of Amsterdam, Biomedical Engineering and Physics, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands ,Amsterdam Cardiovascular Sciences, Microcirculation, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurovascular Disorders, Amsterdam, The Netherlands
| | - Erik N. T. P. Bakker
- grid.509540.d0000 0004 6880 3010Amsterdam UMC Location University of Amsterdam, Biomedical Engineering and Physics, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands ,Amsterdam Cardiovascular Sciences, Microcirculation, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurovascular Disorders, Amsterdam, The Netherlands
| |
Collapse
|
12
|
Calcagno C, David JA, Motaal AG, Coolen BF, Beldman T, Corbin A, Kak A, Ramachandran S, Pruzan A, Sridhar A, Soler R, Faries CM, Fayad ZA, Mulder WJM, Strijkers GJ. Self-gated, dynamic contrast-enhanced magnetic resonance imaging with compressed-sensing reconstruction for evaluating endothelial permeability in the aortic root of atherosclerotic mice. NMR Biomed 2023; 36:e4823. [PMID: 36031706 PMCID: PMC10078106 DOI: 10.1002/nbm.4823] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 08/01/2022] [Accepted: 08/21/2022] [Indexed: 05/16/2023]
Abstract
High-risk atherosclerotic plaques are characterized by active inflammation and abundant leaky microvessels. We present a self-gated, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) acquisition with compressed sensing reconstruction and apply it to assess longitudinal changes in endothelial permeability in the aortic root of Apoe-/- atherosclerotic mice during natural disease progression. Twenty-four, 8-week-old, female Apoe-/- mice were divided into four groups (n = 6 each) and imaged with self-gated DCE-MRI at 4, 8, 12, and 16 weeks after high-fat diet initiation, and then euthanized for CD68 immunohistochemistry for macrophages. Eight additional mice were kept on a high-fat diet and imaged longitudinally at the same time points. Aortic-root pseudo-concentration curves were analyzed using a validated piecewise linear model. Contrast agent wash-in and washout slopes (b1 and b2 ) were measured as surrogates of aortic root endothelial permeability and compared with macrophage density by immunohistochemistry. b2 , indicating contrast agent washout, was significantly higher in mice kept on an high-fat diet for longer periods of time (p = 0.03). Group comparison revealed significant differences between mice on a high-fat diet for 4 versus 16 weeks (p = 0.03). Macrophage density also significantly increased with diet duration (p = 0.009). Spearman correlation between b2 from DCE-MRI and macrophage density indicated a weak relationship between the two parameters (r = 0.28, p = 0.20). Validated piecewise linear modeling of the DCE-MRI data showed that the aortic root contrast agent washout rate is significantly different during disease progression. Further development of this technique from a single-slice to a 3D acquisition may enable better investigation of the relationship between in vivo imaging of endothelial permeability and atherosclerotic plaques' genetic, molecular, and cellular makeup in this important model of disease.
Collapse
Affiliation(s)
- Claudia Calcagno
- Biomedical Engineering and Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkUSA
- Department of Diagnostic, Molecular and Interventional RadiologyIcahn School of Medicine at Mount SinaiNew YorkUSA
| | - John A. David
- Amsterdam University Medical Centers, Department of Medical Biochemistry, Amsterdam Cardiovascular SciencesUniversity of AmsterdamAmsterdamThe Netherlands
| | - Abdallah G. Motaal
- Siemens Healthineers, Cardiovascular Care Group, Advanced Therapies BusinessErlangenGermany
| | - Bram F. Coolen
- Amsterdam University Medical Centers, Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular SciencesUniversity of AmsterdamAmsterdamThe Netherlands
| | - Thijs Beldman
- Department of Internal MedicineRadboud University Medical CenterNijmegenThe Netherlands
- Radboud Institute for Molecular Life SciencesRadboud University Medical CenterNijmegenThe Netherlands
| | - Alexandra Corbin
- Biomedical Engineering and Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkUSA
- Department of Diagnostic, Molecular and Interventional RadiologyIcahn School of Medicine at Mount SinaiNew YorkUSA
| | - Arnav Kak
- University of Texas Southwestern Medical CenterDallasTXUSA
| | - Sarayu Ramachandran
- Biomedical Engineering and Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkUSA
- Department of Diagnostic, Molecular and Interventional RadiologyIcahn School of Medicine at Mount SinaiNew YorkUSA
| | - Alison Pruzan
- Biomedical Engineering and Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkUSA
- Department of Diagnostic, Molecular and Interventional RadiologyIcahn School of Medicine at Mount SinaiNew YorkUSA
| | - Arthi Sridhar
- Department of Hematology/OncologyUTHealth McGovern Medical SchoolHoustonTXUSA
| | - Raphael Soler
- CNRS, CRMBMMarseilleFrance
- Department of Vascular and Endovascular SurgeryHôpital Universitaire de la Timone, APHMMarseilleFrance
| | - Christopher M. Faries
- Biomedical Engineering and Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkUSA
- Department of Diagnostic, Molecular and Interventional RadiologyIcahn School of Medicine at Mount SinaiNew YorkUSA
| | - Zahi A. Fayad
- Biomedical Engineering and Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkUSA
- Department of Diagnostic, Molecular and Interventional RadiologyIcahn School of Medicine at Mount SinaiNew YorkUSA
| | - Willem J. M. Mulder
- Biomedical Engineering and Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkUSA
- Department of Diagnostic, Molecular and Interventional RadiologyIcahn School of Medicine at Mount SinaiNew YorkUSA
- Department of Internal MedicineRadboud University Medical CenterNijmegenThe Netherlands
- Radboud Institute for Molecular Life SciencesRadboud University Medical CenterNijmegenThe Netherlands
| | - Gustav J. Strijkers
- Biomedical Engineering and Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkUSA
- Amsterdam University Medical Centers, Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular SciencesUniversity of AmsterdamAmsterdamThe Netherlands
| |
Collapse
|
13
|
Unterweger H, Janko C, Folk T, Cicha I, Kovács N, Gyebnár G, Horváth I, Máthé D, Zheng KH, Coolen BF, Stroes E, Szebeni J, Alexiou C, Dézsi L, Lyer S. Comparative in vitro and in vivo Evaluation of Different Iron Oxide-Based Contrast Agents to Promote Clinical Translation in Compliance with Patient Safety. Int J Nanomedicine 2023; 18:2071-2086. [PMID: 37113796 PMCID: PMC10128873 DOI: 10.2147/ijn.s402320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 03/14/2023] [Indexed: 04/29/2023] Open
Abstract
Introduction One of the major challenges in the clinical translation of nanoparticles is the development of formulations combining favorable efficacy and optimal safety. In the past, iron oxide nanoparticles have been introduced as an alternative for gadolinium-containing contrast agents; however, candidates available at the time were not free from adverse effects. Methods Following the development of a potent iron oxide-based contrast agent SPIONDex, we now performed a systematic comparison of this formulation with the conventional contrast agent ferucarbotran and with ferumoxytol, taking into consideration their physicochemical characteristics, bio- and hemocompatibility in vitro and in vivo, as well as their liver imaging properties in rats. Results The results demonstrated superior in vitro cyto-, hemo- and immunocompatibility of SPIONDex in comparison to the other two formulations. Intravenous administration of ferucarbotran or ferumoxytol induced strong complement activation-related pseudoallergy in pigs. In contrast, SPIONDex did not elicit any hypersensitivity reactions in the experimental animals. In a rat model, comparable liver imaging properties, but a faster clearance was demonstrated for SPIONDex. Conclusion The results indicate that SPIONDex possess an exceptional safety compared to the other two formulations, making them a promising candidate for further clinical translation.
Collapse
Affiliation(s)
- Harald Unterweger
- ENT-Department, Section of Experimental Oncology und Nanomedicine (SEON), Universitätsklinikum Erlangen, Erlangen, Germany
- Correspondence: Harald Unterweger, Universitätsklinikum Erlangen, Glueckstr. 10a, Erlangen, 91054, Germany, Tel +49 9131 85-33142, Fax +49 9131 85-34828, Email
| | - Christina Janko
- ENT-Department, Section of Experimental Oncology und Nanomedicine (SEON), Universitätsklinikum Erlangen, Erlangen, Germany
| | - Tamara Folk
- ENT-Department, Section of Experimental Oncology und Nanomedicine (SEON), Universitätsklinikum Erlangen, Erlangen, Germany
| | - Iwona Cicha
- ENT-Department, Section of Experimental Oncology und Nanomedicine (SEON), Universitätsklinikum Erlangen, Erlangen, Germany
| | - Noémi Kovács
- Hungarian Centre of Excellence for Molecular Medicine, Semmelweis University, Budapest, Hungary
| | - Gyula Gyebnár
- Medical Imaging Centre, Semmelweis University, Budapest, Hungary
| | - Ildikó Horváth
- Department Biophysics and Radiation Biology, Semmelweis University, Budapest, Hungary
| | - Domokos Máthé
- Hungarian Centre of Excellence for Molecular Medicine, Semmelweis University, Budapest, Hungary
- Medical Imaging Centre, Semmelweis University, Budapest, Hungary
| | - Kang H Zheng
- Department of Vascular Medicine, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam, the Netherlands
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam, the Netherlands
| | - Erik Stroes
- Department of Vascular Medicine, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam, the Netherlands
| | - János Szebeni
- Nanomedicine Research and Education Center, Institute of Translational Medicine, Semmelweis University, Budapest, Hungary
- SeroScience Ltd, Budapest, Hungary
| | - Christoph Alexiou
- ENT-Department, Section of Experimental Oncology und Nanomedicine (SEON), Universitätsklinikum Erlangen, Erlangen, Germany
| | - László Dézsi
- Nanomedicine Research and Education Center, Institute of Translational Medicine, Semmelweis University, Budapest, Hungary
- SeroScience Ltd, Budapest, Hungary
| | - Stefan Lyer
- ENT-Department, Section of Experimental Oncology und Nanomedicine (SEON), Universitätsklinikum Erlangen, Erlangen, Germany
| |
Collapse
|
14
|
Jensen B, Petersen SE, Coolen BF. Myocardial perfusion in excessively trabeculated hearts: Insights from imaging and histological studies. J Cardiol 2022; 81:499-507. [PMID: 36481300 DOI: 10.1016/j.jjcc.2022.11.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 10/25/2022] [Accepted: 11/10/2022] [Indexed: 12/12/2022]
Abstract
In gestation, the coronary circulation develops initially in the compact layer and it expands only in fetal development to the trabeculations. Conflicting data have been published as to whether the trabecular layer is hypoperfused relative to the compact wall after birth. If so, this could explain the poor pump function in patients with left ventricular excessive trabeculation, or so-called noncompaction. Here, we review direct and indirect assessments of myocardial perfusion in normal and excessively trabeculated hearts by in vivo imaging by magnetic resonance imaging (MRI), positron emission tomography (PET)/single photon emission computed tomography (SPECT), and echocardiography in addition to histology, injections of labelled microspheres in animals, and electrocardiography. In MRI, PET/SPECT, and echocardiography, flow of blood or myocardial uptake of blood-borne tracer molecules are measured. The imaged trabecular layer comprises trabeculations and blood-filled intertrabecular spaces whereas the compact layer comprises tissue only, and spatio-temporal resolution likely affects measurements of myocardial perfusion differently in the two layers. Overall, studies measuring myocardial uptake of tracers (PET/SPECT) suggest trabecular hypoperfusion. Studies measuring the quantity of blood (echocardiography and MRI) suggest trabecular hyperperfusion. These conflicting results are reconciled if the low uptake from intertrabecular spaces in PET/SPECT and the high signal from intertrabecular spaces in MRI and echocardiography are considered opposite biases. Histology on human hearts reveal a similar capillary density of trabecular and compact myocardium. Injections of labelled microspheres in animals reveal a similar perfusion of trabecular and compact myocardium. In conclusion, trabecular and compact muscle are likely equally perfused in normal hearts and most cases of excessive trabeculation.
Collapse
|
15
|
Zheng KH, Kroon J, Schoormans J, Gurney-Champion O, Meijer SL, Gisbertz SS, Hulshof MC, Vugts DJ, van Dongen GA, Coolen BF, Verberne HJ, Nederveen AJ, Stroes ES, van Laarhoven HW. 89Zr-Labeled High-Density Lipoprotein Nanoparticle PET Imaging Reveals Tumor Uptake in Patients with Esophageal Cancer. J Nucl Med 2022; 63:1880-1886. [PMID: 35738904 PMCID: PMC9730913 DOI: 10.2967/jnumed.121.263330] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 04/18/2022] [Indexed: 01/11/2023] Open
Abstract
Nanomedicine holds promise for the delivery of therapeutic and imaging agents to improve cancer treatment outcomes. Preclinical studies have demonstrated that high-density lipoprotein (HDL) nanoparticles accumulate in tumor tissue on intravenous administration. Whether this HDL-based nanomedicine concept is feasible in patients is unexplored. Using a multimodal imaging approach, we aimed to assess tumor uptake of exogenously administered HDL nanoparticles in patients with esophageal cancer. Methods: The HDL mimetic CER-001 was radiolabeled using 89Zr to allow for PET/CT imaging. Patients with primary esophageal cancer staged T2 and above were recruited for serial 89Zr-HDL PET/CT imaging before starting chemoradiation therapy. In addition, patients underwent routine 18F-FDG PET/CT and 3-T MRI scanning (diffusion-weighted imaging/intravoxel incoherent motion imaging and dynamic contrast-enhanced MRI) to assess tumor glucose metabolism, tumor cellularity and microcirculation perfusion, and tumor vascular permeability. Tumor biopsies were analyzed for the expression of HDL scavenger receptor class B1 and macrophage marker CD68 using immunofluorescence staining. Results: Nine patients with adenocarcinoma or squamous cell carcinoma underwent all study procedures. After injection of 89Zr-HDL (39.2 ± 1.2 [mean ± SD] MBq), blood-pool SUVmean decreased over time (11.0 ± 1.7, 6.5 ± 0.6, and 3.3 ± 0.5 at 1, 24, and 72 h, respectively), whereas liver and spleen SUVmean remained relatively constant (4.1 ± 0.6, 4.0 ± 0.8, and 4.3 ± 0.8 at 1, 24, and 72 h, respectively, for the liver; 4.1 ± 0.3, 3.4 ± 0.3, and 3.1 ± 0.4 at 1, 24, and 72 h, respectively, for the spleen) and kidney SUVmean markedly increased over time (4.1 ± 0.9, 9.3 ± 1.4, and 9.6 ± 2.0 at 1, 24, and 72 h, respectively). Tumor uptake (SUVpeak) increased over time (3.5 ± 1.1 and 5.5 ± 2.1 at 1 and 24 h, respectively [P = 0.016]; 5.7 ± 1.4 at 72 h [P = 0.001]). The effective dose of 89Zr-HDL was 0.523 ± 0.040 mSv/MBq. No adverse events were observed after the administration of 89Zr-HDL. PET/CT and 3-T MRI measures of tumor glucose metabolism, tumor cellularity and microcirculation perfusion, and tumor vascular permeability did not correlate with tumor uptake of 89Zr-HDL, suggesting that a specific mechanism mediated the accumulation of 89Zr-HDL. Immunofluorescence staining of clinical biopsies demonstrated scavenger receptor class B1 and CD68 positivity in tumor tissue, establishing a potential cellular mechanism of action. Conclusion: To our knowledge, this was the first 89Zr-HDL study in human oncology. 89Zr-HDL PET/CT imaging demonstrated that intravenously administered HDL nanoparticles accumulated in tumors of patients with esophageal cancer. The administration of 89Zr-HDL was safe. These findings may support the development of HDL nanoparticles as a clinical delivery platform for drug agents. 89Zr-HDL imaging may guide drug development and serve as a biomarker for individualized therapy.
Collapse
Affiliation(s)
- Kang H. Zheng
- Department of Vascular Medicine, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jeffrey Kroon
- Department of Experimental Vascular Medicine, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jasper Schoormans
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Oliver Gurney-Champion
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Sybren L. Meijer
- Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Suzanne S. Gisbertz
- Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Maarten C.C.M. Hulshof
- Department of Radiotherapy, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Danielle J. Vugts
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, VU University, Amsterdam, The Netherlands; and
| | - Guus A.M.S. van Dongen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, VU University, Amsterdam, The Netherlands; and
| | - Bram F. Coolen
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Hein J. Verberne
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Aart J. Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Erik S.G. Stroes
- Department of Vascular Medicine, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Hanneke W.M. van Laarhoven
- Department of Medical Oncology, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| |
Collapse
|
16
|
Klarenberg H, Gosselink M, Coolen BF, Leiner T, Nederveen AJ, Bakermans AJ, Lamb HJ, Boekholdt SM, Froeling M, Strijkers GJ. A 72-channel receive array coil allows whole-heart cine MRI in two breath holds. Eur Radiol Exp 2022; 6:54. [PMID: 36316525 PMCID: PMC9622972 DOI: 10.1186/s41747-022-00305-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 09/08/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND A new 72-channel receive array coil and sensitivity encoding, compressed (C-SENSE) and noncompressed (SENSE), were investigated to decrease the number of breath-holds (BHs) for cardiac magnetic resonance (CMR). METHODS Three-T CMRs were performed using the 72-channel coil with SENSE-2/4/6 and C-SENSE-2/4/6 accelerated short-axis cine two-dimensional balanced steady-state free precession sequences. A 16-channel coil with SENSE-2 served as reference. Ten healthy subjects were included. BH-time was kept under 15 s. Data were compared in terms of image quality, biventricular function, number of BHs, and scan times. RESULTS BHs decreased from 7 with C-SENSE-2 (scan time 70 s, 2 slices/BH) to 3 with C-SENSE-4 (scan time 42 s, 4-5 slices/BH) and 2 with C-SENSE-6 (scan time 28 s, 7 slices/BH). Compared to reference, image sharpness was similar for SENSE-2/4/6, slightly inferior for C-SENSE-2/4/6. Blood-to-myocardium contrast was unaffected. C-SENSE-4/6 was given lower qualitative median scores, but images were considered diagnostically adequate to excellent, with C-SENSE-6 suboptimal. Biventricular end-diastolic (EDV), end-systolic (ESV) and stroke volumes, ejection fractions (EF), cardiac outputs, and left ventricle (LV)-mass were similar for SENSE-2/4/6 with no systematic bias and clinically appropriate limits of agreements. C-SENSE slightly underestimated LV-EDV (-6.38 ± 6.0 mL, p < 0.047), LV-ESV (-7.94 ± 6.0 mL, p < 0.030) and overestimated LV-EF (3.16 ± 3.10%; p < 0.047) with C-SENSE-4. Bland-Altman analyses revealed minor systematic biases in these variables with C-SENSE-2/4/6 and for LV-mass with C-SENSE-6. CONCLUSIONS Using the 72-channel coil, short-axis CMR for quantifying biventricular function was feasible in two BHs where SENSE slightly outperformed C-SENSE.
Collapse
Affiliation(s)
- Hugo Klarenberg
- grid.7177.60000000084992262Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Mark Gosselink
- grid.7692.a0000000090126352Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Bram F. Coolen
- grid.7177.60000000084992262Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Tim Leiner
- grid.7692.a0000000090126352Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Aart J. Nederveen
- grid.7177.60000000084992262Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Adrianus J. Bakermans
- grid.7177.60000000084992262Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Hildo J. Lamb
- grid.10419.3d0000000089452978Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - S. Matthijs Boekholdt
- grid.7177.60000000084992262Department of Cardiology, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Martijn Froeling
- grid.7692.a0000000090126352Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Gustav J. Strijkers
- grid.7177.60000000084992262Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam, The Netherlands
| |
Collapse
|
17
|
Faber JW, Buijtendijk MFJ, Klarenberg H, Vink AS, Coolen BF, Moorman AFM, Christoffels VM, Clur SA, Jensen B. Fetal Tricuspid Valve Agenesis/Atresia: Testing Predictions of the Embryonic Etiology. Pediatr Cardiol 2022; 43:796-806. [PMID: 34988599 DOI: 10.1007/s00246-021-02789-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 11/20/2021] [Indexed: 11/28/2022]
Abstract
Tricuspid valve agenesis/atresia (TVA) is a congenital cardiac malformation where the tricuspid valve is not formed. It is hypothesized that TVA results from a failure of the normal rightward expansion of the atrioventricular canal (AVC). We tested predictions of this hypothesis by morphometric analyses of the AVC in fetal hearts. We used high-resolution MRI and ultrasonography on a post-mortem fetal heart with TVA and with tricuspid valve stenosis (TVS) to validate the position of measurement landmarks that were to be applied to clinical echocardiograms. This revealed a much deeper right atrioventricular sulcus in TVA than in TVS. Subsequently, serial echocardiograms of in utero fetuses between 12 and 38 weeks of gestation were included (n = 23 TVA, n = 16 TVS, and n = 74 controls) to establish changes in AVC width and ventricular dimensions over time. Ventricular length and width and estimated fetal weight all increased significantly with age, irrespective of diagnosis. Heart rate did not differ between groups. However, in the second trimester, in TVA, the ratio of AVC to ventricular width was significantly lower compared to TVS and controls. This finding supports the hypothesis that TVA is due to a failed rightward expansion of the AVC. Notably, we found in the third trimester that the AVC to ventricular width normalized in TVA fetuses as their mitral valve area was greater than in controls. Hence, TVA associates with a quantifiable under-development of the AVC. This under-development is obscured in the third trimester, likely because of adaptational growth that allows for increased stroke volume of the left ventricle.
Collapse
Affiliation(s)
- Jaeike W Faber
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centres, 1105 AZ, Amsterdam, The Netherlands
| | - Marieke F J Buijtendijk
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centres, 1105 AZ, Amsterdam, The Netherlands
| | - Hugo Klarenberg
- Department of Biomedical Engineering & Physics, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - Arja Suzanne Vink
- Department of Cardiology, Amsterdam University Medical Centres, Amsterdam, The Netherlands.,Department of Paediatric Cardiology, Emma Children's Hospital, Academic Medical Centre, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - Bram F Coolen
- Department of Biomedical Engineering & Physics, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - Antoon F M Moorman
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centres, 1105 AZ, Amsterdam, The Netherlands
| | - Vincent M Christoffels
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centres, 1105 AZ, Amsterdam, The Netherlands
| | - Sally-Ann Clur
- Department of Paediatric Cardiology, Emma Children's Hospital, Academic Medical Centre, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - Bjarke Jensen
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centres, 1105 AZ, Amsterdam, The Netherlands.
| |
Collapse
|
18
|
Blanken CP, Gottwald LM, Westenberg JJ, Peper ES, Coolen BF, Strijkers GJ, Nederveen AJ, Planken RN, Ooij P. Whole‐Heart 4D Flow MRI for Evaluation of Normal and Regurgitant Valvular Flow: A Quantitative Comparison Between Pseudo‐Spiral Sampling and EPI Readout. J Magn Reson Imaging 2022. [DOI: 10.1002/jmri.27710] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
|
19
|
Baas KPA, Coolen BF, Petersen ET, Biemond BJ, Strijkers GJ, Nederveen AJ. Comparative Analysis of Blood T 2 Values Measured by T 2 -TRIR and TRUST. J Magn Reson Imaging 2022; 56:516-526. [PMID: 35077595 DOI: 10.1002/jmri.28066] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 12/24/2021] [Accepted: 12/28/2021] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Venous blood oxygenation (Yv), which can be derived from venous blood T2 (T2 b), combined with oxygen-extraction fraction (OEF) and cerebral metabolic rate of oxygen, is considered indicative for tissue viability and brain functioning and frequently assessed in patients with sickle cell disease. Recently, T2 -Prepared-Blood-Relaxation-Imaging-with-Inversion-Recovery (T2 -TRIR) was introduced allowing for simultaneous measurements of blood T2 and T1 (T1 b), potentially improving Yv estimation by overcoming the need to estimate hematocrit. PURPOSE To optimize and compare T2 -TRIR with T2 -relaxation-under-spin-tagging (TRUST) sequence. STUDY TYPE Prospective. POPULATION A total of 12 healthy volunteers (six female, 27 ± 3 years old) and 7 patients with sickle cell disease (five female, 32 ± 12 years old). FIELD STRENGTH/SEQUENCE 3 T; turbo field echo planar imaging (TFEPI), echo planar imaging (EPI), and fast field echo (FFE). ASSESSMENT T2 b, Yv, and OEF from TRUST and T2 -TRIR were compared and T2 -TRIR-derived T1 b was assessed. Within- and between-session repeatability was quantified in the controls, whereas sensitivity to hemodynamic changes after acetazolamide (ACZ) administration was assessed in the patients. STATISTICAL TESTS Shapiro-Wilk, one-sample and paired-sample t-test, repeated measures ANOVA, mixed linear model, Bland-Altman analysis and correlation analysis. Sidak multiple-comparison correction was performed. Significance level was 0.05. RESULTS In controls, T2 b from T2 -TRIR (70 ± 11 msec) was higher compared to TRUST (60 ± 8 msec). In patients, T2 b values were lower pre- compared to post-ACZ administration (TRUST: 80 ± 15 msec and 106 ± 23 msec and T2 -TRIR: 95 ± 21 msec and 125 ± 36 msec). Consequently, Yv and OEF were lower and higher pre- compared to post-ACZ administration (TRUST Yv: 68% ± 7% and 77% ± 8%, T2 -TRIR Yv: 74% ± 8% and 80% ± 6%, TRUST OEF: 30% ± 7% and 21% ± 8%, and T2 -TRIR OEF: 25% ± 8% and 18% ± 6%). DATA CONCLUSION TRUST and T2 -TRIR are reproducible, but T2 -TRIR-derived T2 b values are significantly higher compared to TRUST, resulting in higher Yv and lower OEF estimates. This bias might be considered when evaluating cerebral oxygen homeostasis. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 2.
Collapse
Affiliation(s)
- Koen P A Baas
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Esben T Petersen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark.,Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Bart J Biemond
- Department of Hematology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam, The Netherlands
| |
Collapse
|
20
|
Daal MRR, Strijkers GJ, Hautemann DJ, Nederveen AJ, Wüst RCI, Coolen BF. Longitudinal CMR assessment of cardiac global longitudinal strain and hemodynamic forces in a mouse model of heart failure. Int J Cardiovasc Imaging 2022; 38:2385-2394. [PMID: 36434328 PMCID: PMC9700588 DOI: 10.1007/s10554-022-02631-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 04/22/2022] [Indexed: 12/14/2022]
Abstract
To longitudinally assess left ventricle (LV) global longitudinal strain (GLS) and hemodynamic forces during the early stages of cardiac dysfunction in a mouse model of heart failure with preserved ejection fraction (HFpEF). Cardiac MRI measurements were performed in control mice (n = 6), and db/db mice (n = 7), whereby animals were scanned four times between the age of 11-15 weeks. After the first scan, the db/db animals received a doxycycline intervention to accelerate progression of HFpEF. Systolic function was evaluated based on a series of prospectively ECG-triggered short-axis CINE images acquired from base to apex. Cardiac GLS and hemodynamic forces values were evaluated based on high frame rate retrospectively gated 2-, 3-, and 4-chamber long-axis CINE images. Ejection fraction (EF) was not different between control and db/db animals, despite that cardiac output, as well as end systolic and end diastolic volume were significantly higher in control animals. Whereas GLS parameters were not significantly different between groups, hemodynamic force root mean square (RMS) values, as well as average hemodynamic forces and the ratio between hemodynamic forces in the inferolateral-anteroseptal and apical-basal direction were lower in db/db mice compared to controls. More importantly, hemodynamic forces parameters showed a significant interaction effect between time and group. Our results indicated that hemodynamic forces parameters were the only functional outcome measure that showed distinct temporal differences between groups. As such, changes in hemodynamic forces reflect early alterations in cardiac function which can be of added value in (pre)clinical research on HFpEF.
Collapse
Affiliation(s)
- Mariah R. R. Daal
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Gustav J. Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | | | - Aart J. Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Rob C. I. Wüst
- Laboratory for Myology, Department of Human Movement Sciences, Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Amsterdam, The Netherlands
| | - Bram F. Coolen
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| |
Collapse
|
21
|
Blanken CPS, Schrauben EM, Peper ES, Gottwald LM, Coolen BF, van Wijk DF, Piek JJ, Strijkers GJ, Planken RN, van Ooij P, Nederveen AJ. Coronary Flow Assessment Using Accelerated 4D Flow MRI With Respiratory Motion Correction. Front Bioeng Biotechnol 2021; 9:725833. [PMID: 34869250 PMCID: PMC8634777 DOI: 10.3389/fbioe.2021.725833] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 08/02/2021] [Indexed: 11/29/2022] Open
Abstract
Magnetic resonance imaging (MRI) can potentially be used for non-invasive screening of patients with stable angina pectoris to identify probable obstructive coronary artery disease. MRI-based coronary blood flow quantification has to date only been performed in a 2D fashion, limiting its clinical applicability. In this study, we propose a framework for coronary blood flow quantification using accelerated 4D flow MRI with respiratory motion correction and compressed sensing image reconstruction. We investigate its feasibility and repeatability in healthy subjects at rest. Fourteen healthy subjects received 8 times-accelerated 4D flow MRI covering the left coronary artery (LCA) with an isotropic spatial resolution of 1.0 mm3. Respiratory motion correction was performed based on 1) lung-liver navigator signal, 2) real-time monitoring of foot-head motion of the liver and LCA by a separate acquisition, and 3) rigid image registration to correct for anterior-posterior motion. Time-averaged diastolic LCA flow was determined, as well as time-averaged diastolic maximal velocity (VMAX) and diastolic peak velocity (VPEAK). 2D flow MRI scans of the LCA were acquired for reference. Scan-rescan repeatability and agreement between 4D flow MRI and 2D flow MRI were assessed in terms of concordance correlation coefficient (CCC) and coefficient of variation (CV). The protocol resulted in good visibility of the LCA in 11 out of 14 subjects (six female, five male, aged 28 ± 4 years). The other 3 subjects were excluded from analysis. Time-averaged diastolic LCA flow measured by 4D flow MRI was 1.30 ± 0.39 ml/s and demonstrated good scan-rescan repeatability (CCC/CV = 0.79/20.4%). Time-averaged diastolic VMAX (17.2 ± 3.0 cm/s) and diastolic VPEAK (24.4 ± 6.5 cm/s) demonstrated moderate repeatability (CCC/CV = 0.52/19.0% and 0.68/23.0%, respectively). 4D flow- and 2D flow-based diastolic LCA flow agreed well (CCC/CV = 0.75/20.1%). Agreement between 4D flow MRI and 2D flow MRI was moderate for both diastolic VMAX and VPEAK (CCC/CV = 0.68/20.3% and 0.53/27.0%, respectively). In conclusion, the proposed framework of accelerated 4D flow MRI equipped with respiratory motion correction and compressed sensing image reconstruction enables repeatable diastolic LCA flow quantification that agrees well with 2D flow MRI.
Collapse
Affiliation(s)
- Carmen P S Blanken
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Eric M Schrauben
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Eva S Peper
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Lukas M Gottwald
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | | | - Jan J Piek
- Department of Cardiology, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - R Nils Planken
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Pim van Ooij
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
| |
Collapse
|
22
|
Riekerk HCE, Coolen BF, J Strijkers G, van der Wal AC, Petersen SE, Sheppard MN, Oostra RJ, Christoffels VM, Jensen B. Higher spatial resolution improves the interpretation of the extent of ventricular trabeculation. J Anat 2021; 240:357-375. [PMID: 34569075 PMCID: PMC8742974 DOI: 10.1111/joa.13559] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 09/07/2021] [Accepted: 09/15/2021] [Indexed: 12/21/2022] Open
Abstract
The ventricular walls of the human heart comprise an outer compact layer and an inner trabecular layer. In the context of an increased pre-test probability, diagnosis left ventricular noncompaction cardiomyopathy is given when the left ventricle is excessively trabeculated in volume (trabecular vol >25% of total LV wall volume) or thickness (trabecular/compact (T/C) >2.3). Here, we investigated whether higher spatial resolution affects the detection of trabeculation and thus the assessment of normal and excessively trabeculated wall morphology. First, we screened left ventricles in 1112 post-natal autopsy hearts. We identified five excessively trabeculated hearts and this low prevalence of excessive trabeculation is in agreement with pathology reports but contrasts the prevalence of approximately 10% of the population found by in vivo non-invasive imaging. Using macroscopy, histology and low- and high-resolution MRI, the five excessively trabeculated hearts were compared with six normal hearts and seven abnormally trabeculated and excessive trabeculation-negative hearts. Some abnormally trabeculated hearts could be considered excessively trabeculated macroscopically because of a trabecular outflow or an excessive number of trabeculations, but they were excessive trabeculation-negative when assessed with MRI-based measurements (T/C <2.3 and vol <25%). The number of detected trabeculations and T/C ratio were positively correlated with higher spatial resolution. Using measurements on high resolution MRI and with histological validation, we could not replicate the correlation between trabeculations of the left and right ventricle that has been previously reported. In conclusion, higher spatial resolution may affect the sensitivity of diagnostic measurements and in addition could allow for novel measurements such as counting of trabeculations.
Collapse
Affiliation(s)
- Hanne C E Riekerk
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Allard C van der Wal
- Department of Pathology, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Steffen E Petersen
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UK
| | - Mary N Sheppard
- Department of Cardiovascular Pathology, Cardiology Clinical Academic Group, Molecular and Clinical Sciences Research Institute, St George's University of London, London, UK
| | - Roelof-Jan Oostra
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Vincent M Christoffels
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Bjarke Jensen
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| |
Collapse
|
23
|
Blanken CPS, Gottwald LM, Westenberg JJM, Peper ES, Coolen BF, Strijkers GJ, Nederveen AJ, Planken RN, van Ooij P. Whole-Heart 4D Flow MRI for Evaluation of Normal and Regurgitant Valvular Flow: A Quantitative Comparison Between Pseudo-Spiral Sampling and EPI Readout. J Magn Reson Imaging 2021; 55:1120-1130. [PMID: 34510612 PMCID: PMC9290924 DOI: 10.1002/jmri.27905] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 08/18/2021] [Accepted: 08/19/2021] [Indexed: 01/23/2023] Open
Abstract
Background Pseudo‐spiral Cartesian sampling with compressed sensing reconstruction has facilitated highly accelerated 4D flow magnetic resonance imaging (MRI) in various cardiovascular structures. However, unlike echo planar imaging (EPI)‐accelerated 4D flow MRI, it has not been validated in whole‐heart applications. Hypothesis Pseudo‐spiral 4D flow MRI (PROUD [PROspective Undersampling in multiple Dimensions]) is comparable to EPI in robustness of valvular flow measurements and remains comparable as the undersampling factor is increased and scan time reduced. Study Type Prospective. Population Twelve healthy subjects and eight patients with valvular regurgitation. Field Strength/Sequence 3.0 T; PROUD and EPI 4D flow sequences, 2D flow and balanced steady‐state free precession sequences. Assessment Valvular blood flow was quantified using valve tracking. PROUD‐ and EPI‐based measurements of aortic (AV) and pulmonary (PV) flow volumes and left and right ventricular stroke volumes were tested for agreement with 2D MRI‐based measurements. PROUD reconstructions with undersampling factors (R) of 9, 14, 28, and 56 were tested for intervalve consistency (per valve, compared to the other valves) and preservation of peak velocities and E/A ratios. Statistical Tests We used repeated measures ANOVA, Bland‐Altman, Wilcoxon signed rank, and intraclass correlation coefficients. P < 0.05 was considered statistically significant. Results PROUD and EPI intervalve consistencies were not significantly different both in healthy subjects (valve‐averaged mean difference [limits of agreement width]: 3.2 ± 0.8 [8.7 ± 1.1] mL/beat for PROUD, 5.5 ± 2.9 [13.7 ± 2.3] mL/beat for EPI, P = 0.07) and in patients with valvular regurgitation (2.3 ± 1.2 [15.3 ± 5.9] mL/beat for PROUD, 0.6 ± 0.6 [19.3 ± 2.9] mL/beat for EPI, P = 0.47). Agreement between EPI and PROUD was higher than between 4D flow (EPI or PROUD) and 2D MRI for forward flow, stroke volumes, and regurgitant volumes. Up to R = 28 in healthy subjects and R = 14 in patients with valvular regurgitation, PROUD intervalve consistency remained comparable to that of EPI. Peak velocities and E/A ratios were preserved up to R = 9. Conclusion PROUD is comparable to EPI in terms of intervalve consistency and may be used with higher undersampling factors to shorten scan times further. Level of Evidence 1 Technical Efficacy Stage 2
Collapse
Affiliation(s)
- Carmen P S Blanken
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location AMC, Amsterdam, The Netherlands
| | - Lukas M Gottwald
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location AMC, Amsterdam, The Netherlands
| | | | - Eva S Peper
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location AMC, Amsterdam, The Netherlands
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics, Amsterdam UMC, Location AMC, Amsterdam, The Netherlands
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam UMC, Location AMC, Amsterdam, The Netherlands
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location AMC, Amsterdam, The Netherlands
| | - R Nils Planken
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location AMC, Amsterdam, The Netherlands
| | - Pim van Ooij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location AMC, Amsterdam, The Netherlands
| |
Collapse
|
24
|
Coolen BF, Schoormans J, Gilbert G, Kooreman ES, de Winter N, Viessmann O, Zwanenburg JJM, Majoie CBLM, Strijkers GJ, Nederveen AJ, Siero JCW. Double delay alternating with nutation for tailored excitation facilitates banding-free isotropic high-resolution intracranial vessel wall imaging. NMR Biomed 2021; 34:e4567. [PMID: 34076305 PMCID: PMC8459252 DOI: 10.1002/nbm.4567] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 04/26/2021] [Accepted: 05/15/2021] [Indexed: 06/12/2023]
Abstract
The purpose of this study was to evaluate the use of a double delay alternating with nutation for tailored excitation (D-DANTE)-prepared sequence for banding-free isotropic high-resolution intracranial vessel wall imaging (IC-VWI) and to compare its performance with regular DANTE in terms of signal-to-noise ratio (SNR) as well as cerebrospinal fluid (CSF) and blood suppression efficiency. To this end, a D-DANTE-prepared 3D turbo spin echo sequence was implemented by interleaving two separate DANTE pulse trains with different RF phase-cycling schemes, but keeping all other DANTE parameters unchanged, including the total number of pulses and total preparation time. This achieved a reduction of the banding distance compared with regular DANTE enabling banding-free imaging up to higher resolutions. Bloch simulations assuming static vessel wall and flowing CSF spins were performed to compare DANTE and D-DANTE in terms of SNR and vessel wall/CSF contrast. Similar image quality measures were assessed from measurements on 13 healthy middle-aged volunteers. Both simulation and in vivo results showed that D-DANTE had only slightly lower vessel wall/CSF and vessel wall/blood contrast-to-noise ratio values compared with regular DANTE, which originated from a 10%-15% reduction in vessel wall SNR but not from reduced CSF or blood suppression efficiency. As anticipated, IC-VWI acquisitions showed that D-DANTE can successfully remove banding artifacts compared with regular DANTE with equal scan time or DANTE preparation length. Moreover, application was demonstrated in a patient with an intracranial aneurysm, indicating improved robustness to slow flow artifacts compared with clinically available 3D turbo spin echo scans. In conclusion, D-DANTE provides banding artifact-free IC-VWI up to higher isotropic resolutions compared with regular DANTE. This allows for a more flexible choice of DANTE preparation parameters in high-resolution IC-VWI protocols.
Collapse
Affiliation(s)
- Bram F. Coolen
- Department of Biomedical Engineering & PhysicsAmsterdam UMCAmsterdamThe Netherlands
| | - Jasper Schoormans
- Department of Biomedical Engineering & PhysicsAmsterdam UMCAmsterdamThe Netherlands
| | | | - Ernst S. Kooreman
- Department of Biomedical Engineering & PhysicsAmsterdam UMCAmsterdamThe Netherlands
- Department of Radiation OncologyThe Netherlands Cancer InstituteAmsterdamThe Netherlands
| | - Naomi de Winter
- Department of Biomedical Engineering & PhysicsAmsterdam UMCAmsterdamThe Netherlands
| | - Olivia Viessmann
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical SchoolMassachusetts General HospitalCharlestownMassachusettsUSA
| | - Jaco J. M. Zwanenburg
- Department of Radiology, University Medical Center UtrechtUtrecht UniversityUtrechtThe Netherlands
| | | | - Gustav J. Strijkers
- Department of Biomedical Engineering & PhysicsAmsterdam UMCAmsterdamThe Netherlands
| | - Aart J. Nederveen
- Department of Radiology & Nuclear MedicineAmsterdam UMCAmsterdamThe Netherlands
| | - Jeroen C. W. Siero
- Department of Radiology, University Medical Center UtrechtUtrecht UniversityUtrechtThe Netherlands
- Spinoza Centre for NeuroimagingAmsterdamThe Netherlands
| |
Collapse
|
25
|
Daal MRR, Strijkers GJ, Calcagno C, Garipov RR, Wüst RCI, Hautemann D, Coolen BF. Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging. J Vis Exp 2021. [PMID: 34096916 DOI: 10.3791/62595] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022] Open
Abstract
Mouse models have contributed significantly to understanding genetic and physiological factors involved in healthy cardiac function, how perturbations result in pathology, and how myocardial diseases may be treated. Cardiovascular magnetic resonance imaging (CMR) has become an indispensable tool for a comprehensive in vivo assessment of cardiac anatomy and function. This protocol shows detailed measurements of mouse heart left ventricular function, myocardial strain, and hemodynamic forces using 7-Tesla CMR. First, animal preparation and positioning in the scanner are demonstrated. Survey scans are performed for planning imaging slices in various short- and long-axis views. A series of prospective ECG-triggered short-axis (SA) movies (or CINE images) are acquired covering the heart from apex to base, capturing end-systolic and end-diastolic phases. Subsequently, single-slice, retrospectively gated CINE images are acquired in a midventricular SA view, and in 2-, 3-, and 4-chamber views, to be reconstructed into high-temporal resolution CINE images using custom-built and open-source software. CINE images are subsequently analyzed using dedicated CMR image analysis software. Delineating endomyocardial and epicardial borders in SA end-systolic and end-diastolic CINE images allows for the calculation of end-systolic and end-diastolic volumes, ejection fraction, and cardiac output. The midventricular SA CINE images are delineated for all cardiac time frames to extract a detailed volume-time curve. Its time derivative allows for the calculation of the diastolic function as the ratio of the early filling and atrial contraction waves. Finally, left ventricular endocardial walls in the 2-, 3-, and 4-chamber views are delineated using feature-tracking, from which longitudinal myocardial strain parameters and left ventricular hemodynamic forces are calculated. In conclusion, this protocol provides detailed in vivo quantification of the mouse cardiac parameters, which can be used to study temporal alterations in cardiac function in various mouse models of heart disease.
Collapse
Affiliation(s)
- Mariah R R Daal
- Department of Biomedical Engineering & Physics, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam;
| | - Gustav J Strijkers
- Department of Biomedical Engineering & Physics, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam; BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai
| | - Claudia Calcagno
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai
| | | | - Rob C I Wüst
- Department of Biomedical Engineering & Physics, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam; Laboratory for Myology, Department of Human Movement Sciences, Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam
| | | | - Bram F Coolen
- Department of Biomedical Engineering & Physics, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam
| |
Collapse
|
26
|
Afzali-Hashemi L, Baas KPA, Schrantee A, Coolen BF, van Osch MJP, Spann SM, Nur E, Wood JC, Biemond BJ, Nederveen AJ. Impairment of Cerebrovascular Hemodynamics in Patients With Severe and Milder Forms of Sickle Cell Disease. Front Physiol 2021; 12:645205. [PMID: 33959037 PMCID: PMC8093944 DOI: 10.3389/fphys.2021.645205] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 03/11/2021] [Indexed: 11/18/2022] Open
Abstract
In patients with sickle cell disease (SCD), cerebral blood flow (CBF) is elevated to counteract anemia and maintain oxygen supply to the brain. This may exhaust the vasodilating capacity of the vessels, possibly increasing the risk of silent cerebral infarctions (SCI). To further investigate cerebrovascular hemodynamics in SCD patients, we assessed CBF, arterial transit time (ATT), cerebrovascular reactivity of CBF and ATT (CVRCBF and CVRATT) and oxygen delivery in patients with different forms of SCD and matched healthy controls. We analyzed data of 52 patients with severe SCD (HbSS and HbSβ0-thal), 20 patients with mild SCD (HbSC and HbSβ+-thal) and 10 healthy matched controls (HbAA and HbAS). Time-encoded arterial spin labeling (ASL) scans were performed before and after a vasodilatory challenge using acetazolamide (ACZ). To identify predictors of CBF and ATT after vasodilation, regression analyses were performed. Oxygen delivery was calculated and associated with hemoglobin and fetal hemoglobin (HbF) levels. At baseline, severe SCD patients showed significantly higher CBF and lower ATT compared to both the mild SCD patients and healthy controls. As CBFpostACZ was linearly related to CBFpreACZ, CVRCBF decreased with disease severity. CVRATT was also significantly affected in severe SCD patients compared to mild SCD patients and healthy controls. Considering all groups, women showed higher CBFpostACZ than men (p < 0.01) independent of baseline CBF. Subsequently, post ACZ oxygen delivery was also higher in women (p < 0.05). Baseline, but not post ACZ, GM oxygen delivery increased with HbF levels. Our data showed that baseline CBF and ATT and CVRCBF and CVRATT are most affected in severe SCD patients and to a lesser extent in patients with milder forms of SCD compared to healthy controls. Cerebrovascular vasoreactivity was mainly determined by baseline CBF, sex and HbF levels. The higher vascular reactivity observed in women could be related to their lower SCI prevalence, which remains an area of future work. Beneficial effects of HbF on oxygen delivery reflect changes in oxygen dissociation affinity from hemoglobin and were limited to baseline conditions suggesting that high HbF levels do not protect the brain upon a hemodynamic challenge, despite its positive effect on hemolysis.
Collapse
Affiliation(s)
- Liza Afzali-Hashemi
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location AMC, Amsterdam, Netherlands
| | - Koen P A Baas
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location AMC, Amsterdam, Netherlands
| | - Anouk Schrantee
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location AMC, Amsterdam, Netherlands
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics, Amsterdam UMC, location AMC, Amsterdam Cardiovascular Sciences, Amsterdam, Netherlands
| | - Matthias J P van Osch
- C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, Netherlands.,Leiden Institute for Brain and Cognition, Leiden University, Leiden, Netherlands
| | - Stefan M Spann
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria
| | - Erfan Nur
- Department of Hematology, Amsterdam UMC, Location AMC, Amsterdam, Netherlands
| | - John C Wood
- Division of Cardiology, Children's Hospital Los Angeles, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Bart J Biemond
- Department of Hematology, Amsterdam UMC, Location AMC, Amsterdam, Netherlands
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location AMC, Amsterdam, Netherlands
| |
Collapse
|
27
|
Wüst RCI, Coolen BF, Held NM, Daal MRR, Alizadeh Tazehkandi V, Baks-te Bulte L, Wiersma M, Kuster DWD, Brundel BJJM, van Weeghel M, Strijkers GJ, Houtkooper RH. The Antibiotic Doxycycline Impairs Cardiac Mitochondrial and Contractile Function. Int J Mol Sci 2021; 22:4100. [PMID: 33921053 PMCID: PMC8071362 DOI: 10.3390/ijms22084100] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 04/08/2021] [Accepted: 04/08/2021] [Indexed: 12/22/2022] Open
Abstract
Tetracycline antibiotics act by inhibiting bacterial protein translation. Given the bacterial ancestry of mitochondria, we tested the hypothesis that doxycycline-which belongs to the tetracycline class-reduces mitochondrial function, and results in cardiac contractile dysfunction in cultured H9C2 cardiomyoblasts, adult rat cardiomyocytes, in Drosophila and in mice. Ampicillin and carbenicillin were used as control antibiotics since these do not interfere with mitochondrial translation. In line with its specific inhibitory effect on mitochondrial translation, doxycycline caused a mitonuclear protein imbalance in doxycycline-treated H9C2 cells, reduced maximal mitochondrial respiration, particularly with complex I substrates, and mitochondria appeared fragmented. Flux measurements using stable isotope tracers showed a shift away from OXPHOS towards glycolysis after doxycycline exposure. Cardiac contractility measurements in adult cardiomyocytes and Drosophila melanogaster hearts showed an increased diastolic calcium concentration, and a higher arrhythmicity index. Systolic and diastolic dysfunction were observed after exposure to doxycycline. Mice treated with doxycycline showed mitochondrial complex I dysfunction, reduced OXPHOS capacity and impaired diastolic function. Doxycycline exacerbated diastolic dysfunction and reduced ejection fraction in a diabetes mouse model vulnerable for metabolic derangements. We therefore conclude that doxycycline impairs mitochondrial function and causes cardiac dysfunction.
Collapse
Affiliation(s)
- Rob C. I. Wüst
- Laboratory Genetic Metabolic Diseases, Amsterdam Gastroenterology, Endocrinology, and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (N.M.H.); (V.A.T.); (M.v.W.)
- Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands; (B.F.C.); (M.R.R.D.); (G.J.S.)
- Laboratory for Myology, Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences, Vrije University Amsterdam, 1081 BT Amsterdam, The Netherlands
| | - Bram F. Coolen
- Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands; (B.F.C.); (M.R.R.D.); (G.J.S.)
| | - Ntsiki M. Held
- Laboratory Genetic Metabolic Diseases, Amsterdam Gastroenterology, Endocrinology, and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (N.M.H.); (V.A.T.); (M.v.W.)
| | - Mariah R. R. Daal
- Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands; (B.F.C.); (M.R.R.D.); (G.J.S.)
| | - Vida Alizadeh Tazehkandi
- Laboratory Genetic Metabolic Diseases, Amsterdam Gastroenterology, Endocrinology, and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (N.M.H.); (V.A.T.); (M.v.W.)
| | - Luciënne Baks-te Bulte
- Department of Physiology, Amsterdam Cardiovascular Sciences, Amsterdam UMC, VU University Medical Center, 1081 HZ Amsterdam, The Netherlands; (L.B.-t.B.); (M.W.); (D.W.D.K.); (B.J.J.M.B.)
| | - Marit Wiersma
- Department of Physiology, Amsterdam Cardiovascular Sciences, Amsterdam UMC, VU University Medical Center, 1081 HZ Amsterdam, The Netherlands; (L.B.-t.B.); (M.W.); (D.W.D.K.); (B.J.J.M.B.)
| | - Diederik W. D. Kuster
- Department of Physiology, Amsterdam Cardiovascular Sciences, Amsterdam UMC, VU University Medical Center, 1081 HZ Amsterdam, The Netherlands; (L.B.-t.B.); (M.W.); (D.W.D.K.); (B.J.J.M.B.)
| | - Bianca J. J. M. Brundel
- Department of Physiology, Amsterdam Cardiovascular Sciences, Amsterdam UMC, VU University Medical Center, 1081 HZ Amsterdam, The Netherlands; (L.B.-t.B.); (M.W.); (D.W.D.K.); (B.J.J.M.B.)
| | - Michel van Weeghel
- Laboratory Genetic Metabolic Diseases, Amsterdam Gastroenterology, Endocrinology, and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (N.M.H.); (V.A.T.); (M.v.W.)
| | - Gustav J. Strijkers
- Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands; (B.F.C.); (M.R.R.D.); (G.J.S.)
- Department of Radiology, Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Riekelt H. Houtkooper
- Laboratory Genetic Metabolic Diseases, Amsterdam Gastroenterology, Endocrinology, and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (N.M.H.); (V.A.T.); (M.v.W.)
| |
Collapse
|
28
|
Gottwald LM, Blanken CPS, Tourais J, Smink J, Planken RN, Boekholdt SM, Meijboom LJ, Coolen BF, Strijkers GJ, Nederveen AJ, van Ooij P. Retrospective Camera-Based Respiratory Gating in Clinical Whole-Heart 4D Flow MRI. J Magn Reson Imaging 2021; 54:440-451. [PMID: 33694310 PMCID: PMC8359364 DOI: 10.1002/jmri.27564] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 02/02/2021] [Accepted: 02/03/2021] [Indexed: 12/17/2022] Open
Abstract
Background Respiratory gating is generally recommended in 4D flow MRI of the heart to avoid blurring and motion artifacts. Recently, a novel automated contact‐less camera‐based respiratory motion sensor has been introduced. Purpose To compare camera‐based respiratory gating (CAM) with liver‐lung‐navigator‐based gating (NAV) and no gating (NO) for whole‐heart 4D flow MRI. Study Type Retrospective. Subjects Thirty two patients with a spectrum of cardiovascular diseases. Field Strength/Sequence A 3T, 3D‐cine spoiled‐gradient‐echo‐T1‐weighted‐sequence with flow‐encoding in three spatial directions. Assessment Respiratory phases were derived and compared against each other by cross‐correlation. Three radiologists/cardiologist scored images reconstructed with camera‐based, navigator‐based, and no respiratory gating with a 4‐point Likert scale (qualitative analysis). Quantitative image quality analysis, in form of signal‐to‐noise ratio (SNR) and liver‐lung‐edge (LLE) for sharpness and quantitative flow analysis of the valves were performed semi‐automatically. Statistical Tests One‐way repeated measured analysis of variance (ANOVA) with Wilks's lambda testing and follow‐up pairwise comparisons. Significance level of P ≤ 0.05. Krippendorff's‐alpha‐test for inter‐rater reliability. Results The respiratory signal analysis revealed that CAM and NAV phases were highly correlated (C = 0.93 ± 0.09, P < 0.01). Image scoring showed poor inter‐rater reliability and no significant differences were observed (P ≥ 0.16). The image quality comparison showed that NAV and CAM were superior to NO with higher SNR (P = 0.02) and smaller LLE (P < 0.01). The quantitative flow analysis showed significant differences between the three respiratory‐gated reconstructions in the tricuspid and pulmonary valves (P ≤ 0.05), but not in the mitral and aortic valves (P > 0.05). Pairwise comparisons showed that reconstructions without respiratory gating were different in flow measurements to either CAM or NAV or both, but no differences were found between CAM and NAV reconstructions. Data Conclusion Camera‐based respiratory gating performed as well as conventional liver‐lung‐navigator‐based respiratory gating. Quantitative image quality analysis showed that both techniques were equivalent and superior to no‐gating‐reconstructions. Quantitative flow analysis revealed local flow differences (tricuspid/pulmonary valves) in images of no‐gating‐reconstructions, but no differences were found between images reconstructed with camera‐based and navigator‐based respiratory gating. Level of Evidence 3 Technical Efficacy Stage 2
Collapse
Affiliation(s)
- Lukas M Gottwald
- Radiology and Nuclear Medicine, Amsterdam, Amsterdam University Medical Centers, location AMC, The Netherlands
| | - Carmen P S Blanken
- Radiology and Nuclear Medicine, Amsterdam, Amsterdam University Medical Centers, location AMC, The Netherlands
| | - João Tourais
- MR R&D-Clinical Science, Philips Healthcare, Best, The Netherlands.,Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.,Magnetic Resonance Systems Lab, Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - Jouke Smink
- MR R&D-Clinical Science, Philips Healthcare, Best, The Netherlands
| | - R Nils Planken
- Cardiology, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | | | - Lilian J Meijboom
- Radiology and Nuclear Medicine, Amsterdam, Amsterdam University Medical Centers, location AMC, The Netherlands
| | - Bram F Coolen
- Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Gustav J Strijkers
- Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Aart J Nederveen
- Radiology and Nuclear Medicine, Amsterdam, Amsterdam University Medical Centers, location AMC, The Netherlands
| | - Pim van Ooij
- Radiology and Nuclear Medicine, Amsterdam, Amsterdam University Medical Centers, location AMC, The Netherlands
| |
Collapse
|
29
|
Moonen RPM, Coolen BF, Sluimer JC, Daemen MJAP, Strijkers GJ. Iron Oxide Nanoparticle Uptake in Mouse Brachiocephalic Artery Atherosclerotic Plaque Quantified by T 2-Mapping MRI. Pharmaceutics 2021; 13:pharmaceutics13020279. [PMID: 33669667 PMCID: PMC7922981 DOI: 10.3390/pharmaceutics13020279] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 02/15/2021] [Accepted: 02/17/2021] [Indexed: 12/29/2022] Open
Abstract
The purpose of our study was to monitor the iron oxide contrast agent uptake in mouse brachiocephalic artery (BCA) atherosclerotic plaques in vivo by quantitative T2-mapping magnetic resonance imaging (MRI). Female ApoE−/− mice (n = 32) on a 15-week Western-type diet developed advanced plaques in the BCA and were injected with ultra-small superparamagnetic iron oxides (USPIOs). Quantitative in vivo MRI at 9.4 T was performed with a Malcolm-Levitt (MLEV) prepared T2-mapping sequence to monitor the nanoparticle uptake in the atherosclerotic plaque. Ex vivo histology and particle electron paramagnetic resonance (pEPR) were used for validation. Longitudinal high-resolution in vivo T2-value maps were acquired with consistent quality. Average T2 values in the plaque decreased from a baseline value of 34.5 ± 0.6 ms to 24.0 ± 0.4 ms one day after injection and partially recovered to an average T2 of 27 ± 0.5 ms after two days. T2 values were inversely related to iron levels in the plaque as determined by ex vivo particle electron paramagnetic resonance (pEPR). We concluded that MRI T2 mapping facilitates a robust quantitative readout for USPIO uptake in atherosclerotic plaques in arteries near the mouse heart.
Collapse
Affiliation(s)
- Rik P. M. Moonen
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, 6229 ER Maastricht, The Netherlands;
- CARIM School for Cardiovascular Diseases, Maastricht University Medical Center, 6229 ER Maastricht, The Netherlands;
| | - Bram F. Coolen
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands;
| | - Judith C. Sluimer
- CARIM School for Cardiovascular Diseases, Maastricht University Medical Center, 6229 ER Maastricht, The Netherlands;
- Department of Pathology, Maastricht University Medical Center, 6229 ER Maastricht, The Netherlands
| | - Mat J. A. P. Daemen
- Department of Pathology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam Cardiovascular Sciences, 1105 AZ Amsterdam, The Netherlands;
| | - Gustav J. Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands;
- Correspondence: ; Tel.: +31-20-566-52-02
| |
Collapse
|
30
|
Kaiser A, Reneman L, Solleveld MM, Coolen BF, Scherder EJA, Knutsson L, Bjørnerud A, van Osch MJP, Wijnen JP, Lucassen PJ, Schrantee A. A Randomized Controlled Trial on the Effects of a 12-Week High- vs. Low-Intensity Exercise Intervention on Hippocampal Structure and Function in Healthy, Young Adults. Front Psychiatry 2021; 12:780095. [PMID: 35126199 PMCID: PMC8814653 DOI: 10.3389/fpsyt.2021.780095] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 12/08/2021] [Indexed: 12/25/2022] Open
Abstract
Physical exercise affects hippocampal structure and function, but the underlying neural mechanisms and the effects of exercise intensity remain incompletely understood. Therefore, we undertook a comprehensive, multi-modal 3T and 7T MRI randomized controlled trial (Netherlands Trial Register - NL5847) in which we randomized 52 young, non-athletic volunteers to a 12-week low- or high-intensity exercise program. Using state-of-the-art methods, we investigated changes in hippocampal volume, as well as changes in vasculature, neuro-metabolites, and peripheral growth factors as potential underpinnings. Cardiorespiratory fitness improved over time (p < 0.001), but no interaction with exercise intensity was found (p = 0.48). Accordingly, we did not observe significant interactions between exercise condition and time on MRI measures (all p > 0.06). However, we found a significant decrease in right hippocampal volume (p < 0.01), an increase in left hippocampal glutathione (p < 0.01), and a decrease of left hippocampal cerebral blood volume (p = 0.01) over time, regardless of exercise condition. Additional exploratory analyses showed that changes in brain-derived neurotrophic factor (p = 0.01), insulin-like growth-factor (p = 0.03), and dorsal anterior cingulate cortex N-acetyl-aspartate levels (p = 0.01) were positively associated with cardiorespiratory fitness changes. Furthermore, a trend toward a positive association of fitness and gray-matter cerebral blood flow (p = 0.06) was found. Our results do not provide evidence for differential effects between high-intensity (aerobic) and low-intensity (toning) exercise on hippocampal structure and function in young adults. However, we show small but significant effects of exercise on hippocampal volume, neurometabolism and vasculature across exercise conditions. Moreover, our exploratory results suggest that exercise might not specifically only benefit hippocampal structure and function, but rather has a more widespread effect. These findings suggest that, in agreement with previous MRI studies demonstrating moderate to strong effects in elderly and diseased populations, but none to only mild effects in young healthy cohorts, the benefits of exercise on the studied brain measures may be age-dependent and restorative rather than stimulatory. Our study highlights the importance of a multi-modal, whole-brain approach to assess macroscopic and microscopic changes underlying exercise-induced brain changes, to better understand the role of exercise as a potential non-pharmacological intervention.
Collapse
Affiliation(s)
- Antonia Kaiser
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands
| | - Liesbeth Reneman
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands
| | - Michelle M Solleveld
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Erik J A Scherder
- Department of Clinical Neuropsychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Linda Knutsson
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Department of Medical Radiation Physics, Lund University, Lund, Sweden.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Atle Bjørnerud
- Department of Diagnostic Physics, Oslo University Hospital, Oslo, Norway.,Department of Physics, University of Oslo, Oslo, Norway
| | | | - Jannie P Wijnen
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Paul J Lucassen
- Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands.,Center for Urban Mental Health, University of Amsterdam, Amsterdam, Netherlands
| | - Anouk Schrantee
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands.,Center for Urban Mental Health, University of Amsterdam, Amsterdam, Netherlands
| |
Collapse
|
31
|
Willemink MJ, Coolen BF, Dyvorne H, Robson PM, Bander I, Ishino S, Pruzan A, Sridhar A, Zhang B, Balchandani P, Mani V, Strijkers GJ, Nederveen AJ, Leiner T, Fayad ZA, Mulder WJM, Calcagno C. Ultra-high resolution, 3-dimensional magnetic resonance imaging of the atherosclerotic vessel wall at clinical 7T. PLoS One 2020; 15:e0241779. [PMID: 33315867 PMCID: PMC7735577 DOI: 10.1371/journal.pone.0241779] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 10/21/2020] [Indexed: 12/11/2022] Open
Abstract
Accurate quantification and characterization of atherosclerotic plaques with MRI requires high spatial resolution acquisitions with excellent image quality. The intrinsically better signal-to-noise ratio (SNR) at high-field clinical 7T compared to the widely employed lower field strengths of 1.5 and 3T may yield significant improvements to vascular MRI. However, 7T atherosclerosis imaging also presents specific challenges, related to local transmit coils and B1 field inhomogeneities, which may overshadow these theoretical gains. We present the development and evaluation of 3D, black-blood, ultra-high resolution vascular MRI on clinical high-field 7T in comparison lower-field 3T. These protocols were applied for in vivo imaging of atherosclerotic rabbits, which are often used for development, testing, and validation of translatable cardiovascular MR protocols. Eight atherosclerotic New Zealand White rabbits were imaged on clinical 7T and 3T MRI scanners using 3D, isotropic, high (0.63 mm3) and ultra-high (0.43 mm3) spatial resolution, black-blood MR sequences with extensive spatial coverage. Following imaging, rabbits were sacrificed for validation using fluorescence imaging and histology. Image quality parameters such as SNR and contrast-to-noise ratio (CNR), as well as morphological and functional plaque measurements (plaque area and permeability) were evaluated at both field strengths. Using the same or comparable imaging parameters, SNR and CNR were in general higher at 7T compared to 3T, with a median (interquartiles) SNR gain of +40.3 (35.3-80.1)%, and a median CNR gain of +68.1 (38.5-95.2)%. Morphological and functional parameters, such as vessel wall area and permeability, were reliably acquired at 7T and correlated significantly with corresponding, widely validated 3T vessel wall MRI measurements. In conclusion, we successfully developed 3D, black-blood, ultra-high spatial resolution vessel wall MRI protocols on a 7T clinical scanner. 7T imaging was in general superior to 3T with respect to image quality, and comparable in terms of plaque area and permeability measurements.
Collapse
Affiliation(s)
- Martin J. Willemink
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Radiology, Stanford University School of Medicine, Stanford, California, United States of America
| | - Bram F. Coolen
- Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Hadrien Dyvorne
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Philip M. Robson
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Ilda Bander
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Seigo Ishino
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Alison Pruzan
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Arthi Sridhar
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Bei Zhang
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Priti Balchandani
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Venkatesh Mani
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Gustav J. Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Aart J. Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Tim Leiner
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Zahi A. Fayad
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Willem J. M. Mulder
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Medical Biochemistry, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands
| | - Claudia Calcagno
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- * E-mail:
| |
Collapse
|
32
|
Jensen B, Coolen BF, Smit TH. Hymenophore configuration of the oak mazegill ( Daedalea quercina). Mycologia 2020; 112:895-907. [PMID: 32716720 DOI: 10.1080/00275514.2020.1785197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
The complex hymenophore configuration of the oak mazegill (Daedalea quercina, Polyporales) is rarely quantified, although quantifications are important analytical tools to assess form and growth. We quantified the hymenophore configuration of the oak mazegill by manual counting of tubes and tubular branches and ends. Complementary measurements were made with the software AngioTool. We found that the number of tubular branches and ends varied substantially between specimens, with a positive correlation with hymenophore area (5-51 cm2). We then measured complexity as tubular branches and ends per area, and complexity was not correlated with the size of the basidiocarps. Basidiocarps from two locations were compared (Hald ege, N = 11; Hvidding krat, N = 7), and the prevalence of branches and that of ends were greater in the Hvidding krat hymenophores (P < 0.001 and P = 0.029, respectively). Additionally, lacunarity, a measure of complexity ("gappiness"), gave a higher score for the Hald ege hymenophores (P = 0.002). Lacunarity analysis of multiple species of Polyporales showed that the oak mazegill hymenophore is comparatively complex. Concerning factors that affect hymenophore complexity of the oak mazegill, we observed that greater hymenophore complexity was associated with abrupt boundaries between growth zones on the pileus surface. Several years of monitoring documented that basidiocarps can remodel to gravitational changes and heal from damage. In conclusion, intra- and interspecies differences of hymenophore configuration can be quantified. In oak mazegill, hymenophore complexity is not dependent on size per se, although abrupt borders between growth zones are associated with increased complexity. Some of the variation between basidiocarps may reflect aspects of the ecology of the individual fungus.
Collapse
Affiliation(s)
- Bjarke Jensen
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam , Meibergdreef 15, 1105 AZ, Amsterdam, The Netherlands
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam , Meibergdreef 15, 1105 AZ, Amsterdam, The Netherlands
| | - Theodoor H Smit
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam , Meibergdreef 15, 1105 AZ, Amsterdam, The Netherlands
| |
Collapse
|
33
|
Naessens DMP, Coolen BF, de Vos J, VanBavel E, Strijkers GJ, Bakker ENTP. Altered brain fluid management in a rat model of arterial hypertension. Fluids Barriers CNS 2020; 17:41. [PMID: 32590994 PMCID: PMC7318739 DOI: 10.1186/s12987-020-00203-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Accepted: 06/18/2020] [Indexed: 12/22/2022] Open
Abstract
Background Proper neuronal function is directly dependent on the composition, turnover, and amount of interstitial fluid that bathes the cells. Most of the interstitial fluid is likely to be derived from ion and water transport across the brain capillary endothelium, a process that may be altered in hypertension due to vascular pathologies as endothelial dysfunction and arterial remodelling. In the current study, we investigated the effects of hypertension on the brain for differences in the water homeostasis. Methods Magnetic resonance imaging (MRI) was performed on a 7T small animal MRI system on male spontaneously hypertensive rats (SHR) and normotensive Wistar Kyoto rats (WKY) of 10 months of age. The MRI protocol consisted of T2-weighted scans followed by quantitative apparent diffusion coefficient (ADC) mapping to measure volumes of different anatomical structures and water diffusion respectively. After MRI, we assessed the spatial distribution of aquaporin 4 expression around blood vessels. Results MRI analysis revealed a significant reduction in overall brain volume and remarkably higher cerebroventricular volume in SHR compared to WKY. Whole brain ADC, as well as ADC values of a number of specific anatomical structures, were significantly lower in hypertensive animals. Additionally, SHR exhibited higher brain parenchymal water content. Immunohistochemical analysis showed a profound expression of aquaporin 4 around blood vessels in both groups, with a significantly larger area of influence around arterioles. Evaluation of specific brain regions revealed a decrease in aquaporin 4 expression around capillaries in the corpus callosum of SHR. Conclusion These results indicate a shift in the brain water homeostasis of adult hypertensive rats.
Collapse
Affiliation(s)
- Daphne M P Naessens
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Judith de Vos
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Ed VanBavel
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Erik N T P Bakker
- Department of Biomedical Engineering and Physics, Amsterdam Cardiovascular Sciences, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands.
| |
Collapse
|
34
|
Gottwald LM, Töger J, Markenroth Bloch K, Peper ES, Coolen BF, Strijkers GJ, van Ooij P, Nederveen AJ. High Spatiotemporal Resolution 4D Flow MRI of Intracranial Aneurysms at 7T in 10 Minutes. AJNR Am J Neuroradiol 2020; 41:1201-1208. [PMID: 32586964 DOI: 10.3174/ajnr.a6603] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Accepted: 04/21/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND AND PURPOSE Patients with intracranial aneurysms may benefit from 4D flow MR imaging because the derived wall shear stress is considered a useful marker for risk assessment and growth of aneurysms. However, long scan times limit the clinical implementation of 4D flow MR imaging. Therefore, this study aimed to investigate whether highly accelerated, high resolution, 4D flow MR imaging at 7T provides reliable quantitative blood flow values in intracranial arteries and aneurysms. MATERIALS AND METHODS We used pseudospiral Cartesian undersampling with compressed sensing reconstruction to achieve high spatiotemporal resolution (0.5 mm isotropic, ∼30 ms) in a scan time of 10 minutes. We analyzed the repeatability of accelerated 4D flow scans and compared flow rates, stroke volume, and the pulsatility index with 2D flow and conventional 4D flow MR imaging in a flow phantom and 15 healthy subjects. Additionally, accelerated 4D flow MR imaging with high spatiotemporal resolution was acquired in 5 patients with aneurysms to derive wall shear stress. RESULTS Flow-rate bias compared with 2D flow was lower for accelerated than for conventional 4D flow MR imaging (0.31 ± 0.13, P = .22, versus 0.79 ± 0.17 mL/s, P < .01). Pulsatility index bias gave similar results. Stroke volume bias showed no difference for accelerated as well as for conventional 4D flow compared to 2D flow MR imaging. Repeatability for accelerated 4D flow was similar to that of 2D flow MR imaging. Increased temporal resolution for wall shear stress measurements in 5 intracranial aneurysms did not show a consistent effect for the wall shear stress but did show an effect for the oscillatory shear index. CONCLUSIONS Highly accelerated high spatiotemporal resolution 4D flow MR imaging at 7T in intracranial arteries and aneurysms provides repeatable and accurate quantitative flow values. Flow rate accuracy is significantly increased compared with conventional 4D flow scans.
Collapse
Affiliation(s)
- L M Gottwald
- From the Departments of Radiology and Nuclear Medicine (L.M.G., E.S.P., P.v.O., A.J.N.)
| | - J Töger
- Department of Diagnostic Radiology (J.T.), Skane University Hospital, Lund, Sweden
| | - K Markenroth Bloch
- Lund University Bioimaging Center (K.M.B.), Lund University, Lund, Sweden
| | - E S Peper
- From the Departments of Radiology and Nuclear Medicine (L.M.G., E.S.P., P.v.O., A.J.N.)
| | - B F Coolen
- Biomedical Engineering and Physics (B.F.C., G.J.S.), Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - G J Strijkers
- Biomedical Engineering and Physics (B.F.C., G.J.S.), Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - P van Ooij
- From the Departments of Radiology and Nuclear Medicine (L.M.G., E.S.P., P.v.O., A.J.N.)
| | - A J Nederveen
- From the Departments of Radiology and Nuclear Medicine (L.M.G., E.S.P., P.v.O., A.J.N.)
| |
Collapse
|
35
|
Gottwald LM, Peper ES, Zhang Q, Coolen BF, Strijkers GJ, Nederveen AJ, van Ooij P. Pseudo-spiral sampling and compressed sensing reconstruction provides flexibility of temporal resolution in accelerated aortic 4D flow MRI: A comparison with k-t principal component analysis. NMR Biomed 2020; 33:e4255. [PMID: 31957927 PMCID: PMC7079056 DOI: 10.1002/nbm.4255] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 12/16/2019] [Accepted: 12/17/2019] [Indexed: 06/10/2023]
Abstract
INTRODUCTION Time-resolved three-dimensional phase contrast MRI (4D flow) of aortic blood flow requires acceleration to reduce scan time. Two established techniques for highly accelerated 4D flow MRI are k-t principal component analysis (k-t PCA) and compressed sensing (CS), which employ either regular or random k-space undersampling. The goal of this study was to gain insights into the quantitative differences between k-t PCA- and CS-derived aortic blood flow, especially for high temporal resolution CS 4D flow MRI. METHODS The scan protocol consisted of both k-t PCA and CS accelerated 4D flow MRI, as well as a 2D flow reference scan through the ascending aorta acquired in 15 subjects. 4D flow scans were accelerated with factor R = 8. For CS accelerated scans, we used a pseudo-spiral Cartesian sampling scheme, which could additionally be reconstructed at higher temporal resolution, resulting in R = 13. 4D flow data were compared with the 2D flow scan in terms of flow, peak flow and stroke volume. A 3D peak systolic voxel-wise velocity and wall shear stress (WSS) comparison between k-t PCA and CS 4D flow was also performed. RESULTS The mean difference in flow/peak flow/stroke volume between the 2D flow scan and the 4D flow CS with R = 8 and R = 13 was 4.2%/9.1%/3.0% and 5.3%/7.1%/1.9%, respectively, whereas for k-t PCA with R = 8 the difference was 9.7%/25.8%/10.4%. In the voxel-by-voxel 4D flow comparison we found 13.6% and 3.5% lower velocity and WSS values of k-t PCA compared with CS with R = 8, and 15.9% and 5.5% lower velocity and WSS values of k-t PCA compared with CS with R = 13. CONCLUSION Pseudo-spiral accelerated 4D flow acquisitions in combination with CS reconstruction provides a flexible choice of temporal resolution. We showed that our proposed strategy achieves better agreement in flow values with 2D reference scans compared with using k-t PCA accelerated acquisitions.
Collapse
Affiliation(s)
- Lukas M. Gottwald
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical CentersUniversity of Amsterdamthe Netherlands
| | - Eva S. Peper
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical CentersUniversity of Amsterdamthe Netherlands
| | - Qinwei Zhang
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical CentersUniversity of Amsterdamthe Netherlands
| | - Bram F. Coolen
- Department of Biomedical Engineering and Physics, Amsterdam University Medical CentersUniversity of Amsterdamthe Netherlands
| | - Gustav J. Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam University Medical CentersUniversity of Amsterdamthe Netherlands
| | - Aart J. Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical CentersUniversity of Amsterdamthe Netherlands
| | - Pim van Ooij
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical CentersUniversity of Amsterdamthe Netherlands
| |
Collapse
|
36
|
Schoormans J, Strijkers GJ, Hansen AC, Nederveen AJ, Coolen BF. Compressed sensing MRI with variable density averaging (CS-VDA) outperforms full sampling at low SNR. ACTA ACUST UNITED AC 2020; 65:045004. [DOI: 10.1088/1361-6560/ab63b7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
|
37
|
Zhang Q, van Houdt PJ, Lambregts DMJ, van Triest B, Kop MPM, Coolen BF, Strijkers GJ, van der Heide UA, Nederveen AJ. Locally advanced rectal cancer: 3D diffusion-prepared stimulated-echo turbo spin-echo versus 2D diffusion-weighted echo-planar imaging. Eur Radiol Exp 2020; 4:9. [PMID: 32030561 PMCID: PMC7005244 DOI: 10.1186/s41747-019-0138-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Accepted: 11/20/2019] [Indexed: 11/10/2022] Open
Abstract
Background Diffusion-weighted imaging (DWI) has shown great value in rectal cancer imaging. However, traditional DWI with echo-planar imaging (DW-EPI) often suffers from geometrical distortions. We applied a three-dimensional diffusion-prepared stimulated-echo turbo spin-echo sequence (DPsti-TSE), allowing geometrically undistorted rectal DWI. We compared DPsti-TSE with DW-EPI for locally advanced rectal cancer DWI. Methods For 33 prior-to-treatment patients, DWI images of the rectum were acquired with DPsti-TSE and DW-EPI at 3 T using b-values of 200 and 1000 s/mm2. Two radiologists conducted a blinded scoring of the images considering nine aspects of image quality and anatomical quality. Tumour apparent diffusion coefficient (ADC) and distortions were compared quantitatively. Results DPsti-TSE scored significantly better than DW-EPI in rectum distortion (p = 0.005) and signal pileup (p = 0.001). DPsti-TSE had better tumour Dice similarity coefficient compared to DW-EPI (0.84 versus 0.80, p = 0.010). Tumour ADC values were higher for DPsti-TSE compared to DW-EPI (1.47 versus 0.86 × 10-3 mm2/s, p < 0.001). Radiologists scored DPsti-TSE significantly lower than DW-EPI on aspects of overall image quality (p = 0.001), sharpness (p < 0.001), quality of fat suppression (p < 0.001), tumour visibility (p = 0.009), tumour conspicuity (p = 0.010) and rectum wall visibility (p = 0.005). Conclusions DPsti-TSE provided geometrically less distorted rectal cancer diffusion-weighted images. However, the image quality of DW-EPI over DPsti-TSE was referred on the basis of several image quality criteria. A significant bias in tumour ADC values from DPsti-TSE was present. Further improvements of DPsti-TSE are needed until it can replace DW-EPI.
Collapse
Affiliation(s)
- Qinwei Zhang
- Amsterdam UMC, Radiology and Nuclear Medicine, University of Amsterdam, Room Z0-178, Meibergdreef 9, 1100 DD, Amsterdam, Netherlands.
| | - Petra J van Houdt
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, Netherlands
| | | | - Baukelien van Triest
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Marnix P M Kop
- Amsterdam UMC, Radiology and Nuclear Medicine, University of Amsterdam, Room Z0-178, Meibergdreef 9, 1100 DD, Amsterdam, Netherlands
| | - Bram F Coolen
- Amsterdam UMC, Biomedical Engineering and Physics, University of Amsterdam, Amsterdam, the Netherlands
| | - Gustav J Strijkers
- Amsterdam UMC, Biomedical Engineering and Physics, University of Amsterdam, Amsterdam, the Netherlands
| | - Uulke A van der Heide
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Aart J Nederveen
- Amsterdam UMC, Radiology and Nuclear Medicine, University of Amsterdam, Room Z0-178, Meibergdreef 9, 1100 DD, Amsterdam, Netherlands
| |
Collapse
|
38
|
Wüst RCI, Calcagno C, Daal MRR, Nederveen AJ, Coolen BF, Strijkers GJ. Emerging Magnetic Resonance Imaging Techniques for Atherosclerosis Imaging. Arterioscler Thromb Vasc Biol 2020; 39:841-849. [PMID: 30917678 DOI: 10.1161/atvbaha.118.311756] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Atherosclerosis is a prevalent disease affecting a large portion of the population at one point in their lives. There is an unmet need for noninvasive diagnostics to identify and characterize at-risk plaque phenotypes noninvasively and in vivo, to improve the stratification of patients with cardiovascular disease, and for treatment evaluation. Magnetic resonance imaging is uniquely positioned to address these diagnostic needs. However, currently available magnetic resonance imaging methods for vessel wall imaging lack sufficient discriminative and predictive power to guide the individual patient needs. To address this challenge, physicists are pushing the boundaries of magnetic resonance atherosclerosis imaging to increase image resolution, provide improved quantitative evaluation of plaque constituents, and obtain readouts of disease activity such as inflammation. Here, we review some of these important developments, with specific focus on emerging applications using high-field magnetic resonance imaging, the use of quantitative relaxation parameter mapping for improved plaque characterization, and novel 19F magnetic resonance imaging technology to image plaque inflammation.
Collapse
Affiliation(s)
- Rob C I Wüst
- From the Biomedical Engineering and Physics (R.C.I.W., M.R.R.D., B.F.C., G.J.S.), Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Claudia Calcagno
- Department of Radiology, Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York (C.C., G.J.S.)
| | - Mariah R R Daal
- From the Biomedical Engineering and Physics (R.C.I.W., M.R.R.D., B.F.C., G.J.S.), Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Aart J Nederveen
- Radiology and Nuclear Medicine (A.J.N.), Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Bram F Coolen
- From the Biomedical Engineering and Physics (R.C.I.W., M.R.R.D., B.F.C., G.J.S.), Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, the Netherlands
| | - Gustav J Strijkers
- From the Biomedical Engineering and Physics (R.C.I.W., M.R.R.D., B.F.C., G.J.S.), Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, the Netherlands.,Department of Radiology, Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York (C.C., G.J.S.)
| |
Collapse
|
39
|
Peper ES, Gottwald LM, Zhang Q, Coolen BF, van Ooij P, Nederveen AJ, Strijkers GJ. Highly accelerated 4D flow cardiovascular magnetic resonance using a pseudo-spiral Cartesian acquisition and compressed sensing reconstruction for carotid flow and wall shear stress. J Cardiovasc Magn Reson 2020; 22:7. [PMID: 31959203 PMCID: PMC6971939 DOI: 10.1186/s12968-019-0582-z] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2019] [Accepted: 10/18/2019] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND 4D flow cardiovascular magnetic resonance (CMR) enables visualization of complex blood flow and quantification of biomarkers for vessel wall disease, such as wall shear stress (WSS). Because of the inherently long acquisition times, many efforts have been made to accelerate 4D flow acquisitions, however, no detailed analysis has been made on the effect of Cartesian compressed sensing accelerated 4D flow CMR at different undersampling rates on quantitative flow parameters and WSS. METHODS We implemented a retrospectively triggered 4D flow CMR acquisition with pseudo-spiral Cartesian k-space filling, which results in incoherent undersampling of k-t space. Additionally, this strategy leads to small jumps in k-space thereby minimizing eddy current related artifacts. The pseudo-spirals were rotated in a tiny golden-angle fashion, which provides optimal incoherence and a variable density sampling pattern with a fully sampled center. We evaluated this 4D flow protocol in a carotid flow phantom with accelerations of R = 2-20, as well as in carotids of 7 healthy subjects (27 ± 2 years, 4 male) for R = 10-30. Fully sampled 2D flow CMR served as a flow reference. Arteries were manually segmented and registered to enable voxel-wise comparisons of both velocity and WSS using a Bland-Altman analysis. RESULTS Magnitude images, velocity images, and pathline reconstructions from phantom and in vivo scans were similar for all accelerations. For the phantom data, mean differences at peak systole for the entire vessel volume in comparison to R = 2 ranged from - 2.3 to - 5.3% (WSS) and - 2.4 to - 2.2% (velocity) for acceleration factors R = 4-20. For the in vivo data, mean differences for the entire vessel volume at peak systole in comparison to R = 10 were - 9.9, - 13.4, and - 16.9% (WSS) and - 8.4, - 10.8, and - 14.0% (velocity), for R = 20, 25, and 30, respectively. Compared to single slice 2D flow CMR acquisitions, peak systolic flow rates of the phantom showed no differences, whereas peak systolic flow rates in the carotid artery in vivo became increasingly underestimated with increasing acceleration. CONCLUSION Acquisition of 4D flow CMR of the carotid arteries can be highly accelerated by pseudo-spiral k-space sampling and compressed sensing reconstruction, with consistent data quality facilitating velocity pathline reconstructions, as well as quantitative flow rate and WSS estimations. At an acceleration factor of R = 20 the underestimation of peak velocity and peak WSS was acceptable (< 10%) in comparison to an R = 10 accelerated 4D flow CMR reference scan. Peak flow rates were underestimated in comparison with 2D flow CMR and decreased systematically with higher acceleration factors.
Collapse
Affiliation(s)
- Eva S Peper
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Lukas M Gottwald
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Qinwei Zhang
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Pim van Ooij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| |
Collapse
|
40
|
Schoormans J, Calcagno C, Daal MR, Wüst RC, Faries C, Maier A, Teunissen AJ, Naidu S, Sanchez‐Gaytan BL, Nederveen AJ, Fayad ZA, Mulder WJ, Coolen BF, Strijkers GJ. An iterative sparse deconvolution method for simultaneous multicolor 19 F-MRI of multiple contrast agents. Magn Reson Med 2020; 83:228-239. [PMID: 31441541 PMCID: PMC6852267 DOI: 10.1002/mrm.27926] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Revised: 07/09/2019] [Accepted: 07/10/2019] [Indexed: 12/11/2022]
Abstract
PURPOSE 19 F-MRI is gaining widespread interest for cell tracking and quantification of immune and inflammatory cells in vivo. Different fluorinated compounds can be discriminated based on their characteristic MR spectra, allowing in vivo imaging of multiple 19 F compounds simultaneously, so-called multicolor 19 F-MRI. We introduce a method for multicolor 19 F-MRI using an iterative sparse deconvolution method to separate different 19 F compounds and remove chemical shift artifacts arising from multiple resonances. METHODS The method employs cycling of the readout gradient direction to alternate the spatial orientation of the off-resonance chemical shift artifacts, which are subsequently removed by iterative sparse deconvolution. Noise robustness and separation was investigated by numerical simulations. Mixtures of fluorinated oils (PFCE and PFOB) were measured on a 7T MR scanner to identify the relation between 19 F signal intensity and compound concentration. The method was validated in a mouse model after intramuscular injection of fluorine probes, as well as after intravascular injection. RESULTS Numerical simulations show efficient separation of 19 F compounds, even at low signal-to-noise ratio. Reliable chemical shift artifact removal and separation of PFCE and PFOB signals was achieved in phantoms and in vivo. Signal intensities correlated excellently to the relative 19 F compound concentrations (r-2 = 0.966/0.990 for PFOB/PFCE). CONCLUSIONS The method requires minimal sequence adaptation and is therefore easily implemented on different MRI systems. Simulations, phantom experiments, and in-vivo measurements in mice showed effective separation and removal of chemical shift artifacts below noise level. We foresee applicability for simultaneous in-vivo imaging of 19 F-containing fluorine probes or for detection of 19 F-labeled cell populations.
Collapse
Affiliation(s)
- Jasper Schoormans
- Department of Biomedical Engineering and PhysicsAmsterdam University Medical CentersUniversity of AmsterdamAmsterdamThe Netherlands
| | - Claudia Calcagno
- Department of RadiologyTranslational and Molecular Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkNew York
| | - Mariah R.R. Daal
- Department of Biomedical Engineering and PhysicsAmsterdam University Medical CentersUniversity of AmsterdamAmsterdamThe Netherlands
| | - Rob C.I. Wüst
- Department of Biomedical Engineering and PhysicsAmsterdam University Medical CentersUniversity of AmsterdamAmsterdamThe Netherlands
| | - Christopher Faries
- Department of RadiologyTranslational and Molecular Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkNew York
| | - Alexander Maier
- Department of RadiologyTranslational and Molecular Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkNew York
| | - Abraham J.P. Teunissen
- Department of RadiologyTranslational and Molecular Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkNew York
| | - Sonum Naidu
- Department of RadiologyTranslational and Molecular Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkNew York
| | - Brenda L. Sanchez‐Gaytan
- Department of RadiologyTranslational and Molecular Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkNew York
| | - Aart J. Nederveen
- Department of Radiology and Nuclear MedicineAmsterdam University Medical CentersUniversity of AmsterdamAmsterdamThe Netherlands
| | - Zahi A. Fayad
- Department of RadiologyTranslational and Molecular Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkNew York
| | - Willem J.M. Mulder
- Department of RadiologyTranslational and Molecular Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkNew York
- Department of Oncological SciencesIcahn School of Medicine at Mount SinaiNew YorkNew York
- Laboratory of Chemical BiologyDepartment of Biomedical Engineering and Institute for Complex Molecular SystemsEindhoven University of TechnologyEindhovenThe Netherlands
- Department of Medical BiochemistryAmsterdam University Medical CentersUniversity of AmsterdamAmsterdamThe Netherlands
| | - Bram F. Coolen
- Department of Biomedical Engineering and PhysicsAmsterdam University Medical CentersUniversity of AmsterdamAmsterdamThe Netherlands
| | - Gustav J. Strijkers
- Department of Biomedical Engineering and PhysicsAmsterdam University Medical CentersUniversity of AmsterdamAmsterdamThe Netherlands
- Department of RadiologyTranslational and Molecular Imaging InstituteIcahn School of Medicine at Mount SinaiNew YorkNew York
| |
Collapse
|
41
|
Peper ES, Leopaldi AM, van Tuijl S, Coolen BF, Strijkers GJ, Baan J, Planken RN, de Weger A, Nederveen AJ, Marquering HA, van Ooij P. An isolated beating pig heart platform for a comprehensive evaluation of intracardiac blood flow with 4D flow MRI: a feasibility study. Eur Radiol Exp 2019; 3:40. [PMID: 31650367 PMCID: PMC6813403 DOI: 10.1186/s41747-019-0114-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Accepted: 07/02/2019] [Indexed: 12/25/2022] Open
Abstract
Background Cardiac magnetic resonance imaging (MRI) in large animals is cumbersome for various reasons, including ethical considerations, costs of housing and maintenance, and need for anaesthesia. Our primary purpose was to show the feasibility of an isolated beating pig heart model for four-dimensional (4D) flow MRI for investigating intracardiac blood flow patterns and flow parameters using slaughterhouse side products. In addition, the feasibility of evaluating transcatheter aortic valve replacement (TAVR) in the model was investigated. Methods Seven slaughterhouse pig hearts were installed in the MRI-compatible isolated beating pig heart platform. First, Langendorff perfusion mode was established; then, the system switched to working mode, in which blood was actively pumped by the left ventricle. A pacemaker ensured a stable HR during 3-T MRI scanning. All hearts were submitted to human physiological conditions of cardiac output and stayed vital for several hours. Aortic flow was measured from which stroke volume, cardiac output, and regurgitation fraction were calculated. Results 4D flow MRI acquisitions were successfully conducted in all hearts. Stroke volume was 31 ± 6 mL (mean ± standard deviation), cardiac output 3.3 ± 0.9 L/min, and regurgitation fraction 16% ± 9%. With 4D flow, intracardiac and coronary flow patterns could be visualised in all hearts. In addition, we could study valve function and regurgitation in two hearts after TAVR. Conclusions The feasibility of 4D flow MRI in an isolated beating pig heart loaded to physiological conditions was demonstrated. The platform is promising for preclinical assessment of cardiac blood flow and function. Electronic supplementary material The online version of this article (10.1186/s41747-019-0114-5) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Eva S Peper
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
| | | | | | - Bram F Coolen
- Department of Biomedical Engineering & Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Gustav J Strijkers
- Department of Biomedical Engineering & Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jan Baan
- Department of Cardiology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - R Nils Planken
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Arend de Weger
- Department of Cardiothoracic Surgery, Leiden University Medical Center, Leiden, The Netherlands
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Henk A Marquering
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.,Department of Biomedical Engineering & Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Pim van Ooij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| |
Collapse
|
42
|
Cornelissen BMW, Leemans EL, Coolen BF, Peper ES, van den Berg R, Marquering HA, Slump CH, Majoie CBLM. Insufficient slow-flow suppression mimicking aneurysm wall enhancement in magnetic resonance vessel wall imaging: a phantom study. Neurosurg Focus 2019; 47:E19. [DOI: 10.3171/2019.4.focus19235] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Accepted: 04/23/2019] [Indexed: 11/06/2022]
Abstract
OBJECTIVEMR vessel wall imaging (VWI) is increasingly performed in clinical settings to support treatment decision-making regarding intracranial aneurysms. Aneurysm wall enhancement after contrast agent injection is expected to be related to aneurysm instability and rupture status. However, the authors hypothesize that slow-flow artifacts mimic aneurysm wall enhancement. Therefore, in this phantom study they assess the effect of slow flow on wall-like enhancement by using different MR VWI techniques.METHODSThe authors developed an MR-compatible aneurysm phantom model, which was connected to a pump to enable pulsatile inflow conditions. For VWI, 3D turbo spin echo sequences—both with and without motion-sensitized driven equilibrium (MSDE) and delay alternating with nutation for tailored excitation (DANTE) preparation pulses—were performed using a 3-T MR scanner. VWI was acquired both before and after Gd contrast agent administration by using two different pulsatile inflow conditions (2.5 ml/sec peak flow at 77 and 48 beats per minute). The intraluminal signal intensity along the aneurysm wall was analyzed to assess the performance of slow-flow suppression.RESULTSThe authors observed wall-like enhancement after contrast agent injection, especially in low pump rate settings. Preparation pulses, in particular the DANTE technique, improved the performance of slow-flow suppression.CONCLUSIONSNear-wall slow flow mimics wall enhancement in VWI protocols. Therefore, VWI should be carefully interpreted. Preparation pulses improve slow-flow suppression, and therefore the authors encourage further development and clinical implementation of these techniques.
Collapse
Affiliation(s)
- Bart M. W. Cornelissen
- 1Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam
- 2Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam; and
- 3MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands
| | - Eva L. Leemans
- 1Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam
- 2Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam; and
| | - Bram F. Coolen
- 2Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam; and
| | - Eva S. Peper
- 1Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam
| | - René van den Berg
- 1Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam
| | - Henk A. Marquering
- 1Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam
- 2Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam; and
| | - Cornelis H. Slump
- 3MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands
| | - Charles B. L. M. Majoie
- 1Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam
| |
Collapse
|
43
|
Zheng KH, Schoormans J, Stiekema LCA, Calcagno C, Cicha I, Alexiou C, Strijkers GJ, Nederveen AJ, Stroes ESG, Coolen BF. Plaque Permeability Assessed With DCE-MRI Associates With USPIO Uptake in Patients With Peripheral Artery Disease. JACC Cardiovasc Imaging 2019; 12:2081-2083. [PMID: 31202746 DOI: 10.1016/j.jcmg.2019.04.014] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2018] [Revised: 04/10/2019] [Accepted: 04/11/2019] [Indexed: 12/14/2022]
|
44
|
Peper ES, Strijkers GJ, Gazzola K, Potters WV, Motaal AG, Luirink IK, Hutten BA, Wiegman A, van Ooij P, van den Born BJH, Nederveen AJ, Coolen BF. Regional assessment of carotid artery pulse wave velocity using compressed sensing accelerated high temporal resolution 2D CINE phase contrast cardiovascular magnetic resonance. J Cardiovasc Magn Reson 2018; 20:86. [PMID: 30567566 PMCID: PMC6300923 DOI: 10.1186/s12968-018-0499-y] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2018] [Accepted: 10/23/2018] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Cardiovascular magnetic resonance (CMR) allows for non-invasive assessment of arterial stiffness by means of measuring pulse wave velocity (PWV). PWV can be calculated from the time shift between two time-resolved flow curves acquired at two locations within an arterial segment. These flow curves can be derived from two-dimensional CINE phase contrast CMR (2D CINE PC CMR). While CMR-derived PWV measurements have proven to be accurate for the aorta, this is more challenging for smaller arteries such as the carotids due to the need for both high spatial and temporal resolution. In this work, we present a novel method that combines retrospectively gated 2D CINE PC CMR, high temporal binning of data and compressed sensing (CS) reconstruction to accomplish a temporal resolution of 4 ms. This enables accurate flow measurements and assessment of PWV in regional carotid artery segments. METHODS Retrospectively gated 2D CINE PC CMR data acquired in the carotid artery was binned into cardiac frames of 4 ms length, resulting in an incoherently undersampled ky-t-space with a mean undersampling factor of 5. The images were reconstructed by a non-linear CS reconstruction using total variation over time as a sparsifying transform. PWV values were calculated from flow curves by using foot-to-foot and cross-correlation methods. Our method was validated against ultrasound measurements in a flow phantom setup representing the carotid artery. Additionally, PWV values of two groups of 23 young (30 ± 3 years, 12 [52%] women) and 10 elderly (62 ± 10 years, 5 [50%] women) healthy subjects were compared using the Wilcoxon rank-sum test. RESULTS Our proposed method produced very similar flow curves as those measured using ultrasound at 1 ms temporal resolution. Reliable PWV estimation proved possible for transit times down to 7.5 ms. Furthermore, significant differences in PWV values between healthy young and elderly subjects were found (4.7 ± 1.0 m/s and 7.9 ± 2.4 m/s, respectively; p < 0.001) in accordance with literature. CONCLUSIONS Retrospectively gated 2D CINE PC CMR with CS allows for high spatiotemporal resolution flow measurements and accurate regional carotid artery PWV calculations. We foresee this technique will be valuable in protocols investigating early development of carotid atherosclerosis.
Collapse
Affiliation(s)
- Eva S Peper
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Katja Gazzola
- Department of Vascular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Wouter V Potters
- Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | | | - Ilse K Luirink
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
- Department of Pediatrics Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Barbara A Hutten
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Albert Wiegman
- Department of Pediatrics Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Pim van Ooij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Bert-Jan H van den Born
- Department of Vascular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.
| |
Collapse
|
45
|
Maier O, Schoormans J, Schloegl M, Strijkers GJ, Lesch A, Benkert T, Block T, Coolen BF, Bredies K, Stollberger R. Rapid T 1 quantification from high resolution 3D data with model-based reconstruction. Magn Reson Med 2018; 81:2072-2089. [PMID: 30346053 PMCID: PMC6588000 DOI: 10.1002/mrm.27502] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Revised: 08/01/2018] [Accepted: 08/02/2018] [Indexed: 12/25/2022]
Abstract
Purpose Magnetic resonance imaging protocols for the assessment of quantitative information suffer from long acquisition times since multiple measurements in a parametric dimension are required. To facilitate the clinical applicability, accelerating the acquisition is of high importance. To this end, we propose a model‐based optimization framework in conjunction with undersampling 3D radial stack‐of‐stars data. Theory and Methods High resolution 3D T1 maps are generated from subsampled data by employing model‐based reconstruction combined with a regularization functional, coupling information from the spatial and parametric dimension, to exploit redundancies in the acquired parameter encodings and across parameter maps. To cope with the resulting non‐linear, non‐differentiable optimization problem, we propose a solution strategy based on the iteratively regularized Gauss‐Newton method. The importance of 3D‐spectral regularization is demonstrated by a comparison to 2D‐spectral regularized results. The algorithm is validated for the variable flip angle (VFA) and inversion recovery Look‐Locker (IRLL) method on numerical simulated data, MRI phantoms, and in vivo data. Results Evaluation of the proposed method using numerical simulations and phantom scans shows excellent quantitative agreement and image quality. T1 maps from accelerated 3D in vivo measurements, e.g. 1.8 s/slice with the VFA method, are in high accordance with fully sampled reference reconstructions. Conclusions The proposed algorithm is able to recover T1 maps with an isotropic resolution of 1 mm3 from highly undersampled radial data by exploiting structural similarities in the imaging volume and across parameter maps.
Collapse
Affiliation(s)
- Oliver Maier
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria.,BioTechMed-Graz, Graz, Austria
| | - Jasper Schoormans
- Department of Biomedical Engineering and Physics, Academic Medical Center, Amsterdam Zuidoost, The Netherlands
| | - Matthias Schloegl
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria.,BioTechMed-Graz, Graz, Austria
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Academic Medical Center, Amsterdam Zuidoost, The Netherlands
| | - Andreas Lesch
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria.,BioTechMed-Graz, Graz, Austria
| | - Thomas Benkert
- Center for Advanced Imaging Innovation and Research, New York University School of Medicine, New York, New York.,Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, New York, New York
| | - Tobias Block
- Center for Advanced Imaging Innovation and Research, New York University School of Medicine, New York, New York.,Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, New York, New York
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics, Academic Medical Center, Amsterdam Zuidoost, The Netherlands
| | - Kristian Bredies
- BioTechMed-Graz, Graz, Austria.,Institute for Mathematics and Scientific Computing, University of Graz, Graz, Austria
| | - Rudolf Stollberger
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria.,BioTechMed-Graz, Graz, Austria
| |
Collapse
|
46
|
Zhang Q, Coolen BF, Nederveen AJ, Strijkers GJ. Three‐dimensional diffusion imaging with spiral encoded navigators from stimulated echoes (3D‐DISPENSE). Magn Reson Med 2018; 81:1052-1065. [DOI: 10.1002/mrm.27470] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Revised: 07/05/2018] [Accepted: 07/06/2018] [Indexed: 01/04/2023]
Affiliation(s)
- Qinwei Zhang
- Amsterdam UMC University of Amsterdam, Radiology and Nuclear Medicine Amsterdam The Netherlands
| | - Bram F. Coolen
- Amsterdam UMC University of Amsterdam, Biomedical Engineering and Physics Amsterdam The Netherlands
| | - Aart J. Nederveen
- Amsterdam UMC University of Amsterdam, Radiology and Nuclear Medicine Amsterdam The Netherlands
| | - Gustav J. Strijkers
- Amsterdam UMC University of Amsterdam, Biomedical Engineering and Physics Amsterdam The Netherlands
| |
Collapse
|
47
|
Mazzoli V, Gottwald LM, Peper ES, Froeling M, Coolen BF, Verdonschot N, Sprengers AM, Ooij P, Strijkers GJ, Nederveen AJ. Accelerated 4
D
phase contrast
MRI
in skeletal muscle contraction. Magn Reson Med 2018; 80:1799-1811. [DOI: 10.1002/mrm.27158] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Revised: 01/15/2018] [Accepted: 02/06/2018] [Indexed: 11/10/2022]
Affiliation(s)
- Valentina Mazzoli
- Department of RadiologyAcademic Medical CenterAmsterdam The Netherlands
- Biomedical NMR, Department of Biomedical EngineeringEindhoven University of TechnologyEindhoven The Netherlands
- Orthopaedic Research LabRadboud UMCNijmegen The Netherlands
| | - Lukas M. Gottwald
- Department of RadiologyAcademic Medical CenterAmsterdam The Netherlands
| | - Eva S. Peper
- Department of RadiologyAcademic Medical CenterAmsterdam The Netherlands
| | - Martijn Froeling
- Department of RadiologyUniversity Medical Center UtrechtUtrecht The Netherlands
| | - Bram F. Coolen
- Biomedical Engineering and PhysicsAcademic Medical CenterAmsterdam The Netherlands
| | - Nico Verdonschot
- Orthopaedic Research LabRadboud UMCNijmegen The Netherlands
- Laboratory for Biomechanical EngineeringUniversity of TwenteEnschede The Netherlands
| | - Andre M. Sprengers
- Orthopaedic Research LabRadboud UMCNijmegen The Netherlands
- Laboratory for Biomechanical EngineeringUniversity of TwenteEnschede The Netherlands
| | - Pim Ooij
- Department of RadiologyAcademic Medical CenterAmsterdam The Netherlands
| | - Gustav J. Strijkers
- Biomedical NMR, Department of Biomedical EngineeringEindhoven University of TechnologyEindhoven The Netherlands
- Biomedical Engineering and PhysicsAcademic Medical CenterAmsterdam The Netherlands
| | - Aart J. Nederveen
- Department of RadiologyAcademic Medical CenterAmsterdam The Netherlands
| |
Collapse
|
48
|
Mazzoli V, Schoormans J, Froeling M, Sprengers AM, Coolen BF, Verdonschot N, Strijkers GJ, Nederveen AJ. Accelerated 4D self-gated MRI of tibiofemoral kinematics. NMR Biomed 2017; 30:e3791. [PMID: 28873255 DOI: 10.1002/nbm.3791] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Revised: 07/17/2017] [Accepted: 07/19/2017] [Indexed: 06/07/2023]
Abstract
Anatomical (static) magnetic resonance imaging (MRI) is the most useful imaging technique for the evaluation and assessment of internal derangement of the knee, but does not provide dynamic information and does not allow the study of the interaction of the different tissues during motion. As knee pain is often only experienced during dynamic tasks, the ability to obtain four-dimensional (4D) images of the knee during motion could improve the diagnosis and provide a deeper understanding of the knee joint. In this work, we present a novel approach for dynamic, high-resolution, 4D imaging of the freely moving knee without the need for external triggering. The dominant knee of five healthy volunteers was scanned during a flexion/extension task. To evaluate the effects of non-uniform motion and poor coordination skills on the quality of the reconstructed images, we performed a comparison between fully free movement and movement instructed by a visual cue. The trigger signal for self-gating was extracted using principal component analysis (PCA), and the images were reconstructed using a parallel imaging and compressed sensing reconstruction pipeline. The reconstructed 4D movies were scored for image quality and used to derive bone kinematics through image registration. Using our method, we were able to obtain 4D high-resolution movies of the knee without the need for external triggering hardware. The movies obtained with and without instruction did not differ significantly in terms of image scoring and quantitative values for tibiofemoral kinematics. Our method showed to be robust for the extraction of the self-gating signal even for uninstructed motion. This can make the technique suitable for patients who, as a result of pain, may find it difficult to comply exactly with instructions. Furthermore, bone kinematics can be derived from accelerated MRI without the need for additional hardware for triggering.
Collapse
Affiliation(s)
- Valentina Mazzoli
- Department of Radiology, Academic Medical Center, Amsterdam, the Netherlands
- Orthopedic Research Laboratory, Radboud University Medical Center, Nijmegen, the Netherlands
- Biomedical NMR, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Jasper Schoormans
- Department of Biomedical Engineering and Physics, Academic Medical Center, Amsterdam, the Netherlands
| | - Martijn Froeling
- Department of Radiology, University Medical Center, Utrecht, the Netherlands
| | - Andre M Sprengers
- Orthopedic Research Laboratory, Radboud University Medical Center, Nijmegen, the Netherlands
- Laboratory for Biomechanical Engineering, University of Twente, Enschede, the Netherlands
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics, Academic Medical Center, Amsterdam, the Netherlands
| | - Nico Verdonschot
- Orthopedic Research Laboratory, Radboud University Medical Center, Nijmegen, the Netherlands
- Laboratory for Biomechanical Engineering, University of Twente, Enschede, the Netherlands
| | - Gustav J Strijkers
- Biomedical NMR, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
- Department of Biomedical Engineering and Physics, Academic Medical Center, Amsterdam, the Netherlands
| | - Aart J Nederveen
- Department of Radiology, Academic Medical Center, Amsterdam, the Netherlands
| |
Collapse
|
49
|
Coolen BF, Calcagno C, van Ooij P, Fayad ZA, Strijkers GJ, Nederveen AJ. Vessel wall characterization using quantitative MRI: what's in a number? MAGMA 2017; 31:201-222. [PMID: 28808823 PMCID: PMC5813061 DOI: 10.1007/s10334-017-0644-x] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/07/2017] [Revised: 07/04/2017] [Accepted: 07/18/2017] [Indexed: 12/15/2022]
Abstract
The past decade has witnessed the rapid development of new MRI technology for vessel wall imaging. Today, with advances in MRI hardware and pulse sequences, quantitative MRI of the vessel wall represents a real alternative to conventional qualitative imaging, which is hindered by significant intra- and inter-observer variability. Quantitative MRI can measure several important morphological and functional characteristics of the vessel wall. This review provides a detailed introduction to novel quantitative MRI methods for measuring vessel wall dimensions, plaque composition and permeability, endothelial shear stress and wall stiffness. Together, these methods show the versatility of non-invasive quantitative MRI for probing vascular disease at several stages. These quantitative MRI biomarkers can play an important role in the context of both treatment response monitoring and risk prediction. Given the rapid developments in scan acceleration techniques and novel image reconstruction, we foresee the possibility of integrating the acquisition of multiple quantitative vessel wall parameters within a single scan session.
Collapse
Affiliation(s)
- Bram F Coolen
- Department of Biomedical Engineering and Physics, Academic Medical Center, PO BOX 22660, 1100 DD, Amsterdam, The Netherlands. .,Department of Radiology, Academic Medical Center, Amsterdam, The Netherlands.
| | - Claudia Calcagno
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pim van Ooij
- Department of Radiology, Academic Medical Center, Amsterdam, The Netherlands
| | - Zahi A Fayad
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Academic Medical Center, PO BOX 22660, 1100 DD, Amsterdam, The Netherlands
| | - Aart J Nederveen
- Department of Radiology, Academic Medical Center, Amsterdam, The Netherlands
| |
Collapse
|
50
|
Gao S, van 't Klooster R, Kitslaar PH, Coolen BF, van den Berg AM, Smits LP, Shahzad R, Shamonin DP, de Koning PJH, Nederveen AJ, van der Geest RJ. Learning-based automated segmentation of the carotid artery vessel wall in dual-sequence MRI using subdivision surface fitting. Med Phys 2017; 44:5244-5259. [PMID: 28715090 DOI: 10.1002/mp.12476] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2017] [Revised: 07/10/2017] [Accepted: 07/10/2017] [Indexed: 01/24/2023] Open
Abstract
PURPOSE The quantification of vessel wall morphology and plaque burden requires vessel segmentation, which is generally performed by manual delineations. The purpose of our work is to develop and evaluate a new 3D model-based approach for carotid artery wall segmentation from dual-sequence MRI. METHODS The proposed method segments the lumen and outer wall surfaces including the bifurcation region by fitting a subdivision surface constructed hierarchical-tree model to the image data. In particular, a hybrid segmentation which combines deformable model fitting with boundary classification was applied to extract the lumen surface. The 3D model ensures the correct shape and topology of the carotid artery, while the boundary classification uses combined image information of 3D TOF-MRA and 3D BB-MRI to promote accurate delineation of the lumen boundaries. The proposed algorithm was validated on 25 subjects (48 arteries) including both healthy volunteers and atherosclerotic patients with 30% to 70% carotid stenosis. RESULTS For both lumen and outer wall border detection, our result shows good agreement between manually and automatically determined contours, with contour-to-contour distance less than 1 pixel as well as Dice overlap greater than 0.87 at all different carotid artery sections. CONCLUSIONS The presented 3D segmentation technique has demonstrated the capability of providing vessel wall delineation for 3D carotid MRI data with high accuracy and limited user interaction. This brings benefits to large-scale patient studies for assessing the effect of pharmacological treatment of atherosclerosis by reducing image analysis time and bias between human observers.
Collapse
Affiliation(s)
- Shan Gao
- Department of Radiology, Division of Image Processing, Leiden University Medical Center, 2300 RC, Leiden, The Netherlands
| | - Ronald van 't Klooster
- Department of Radiology, Division of Image Processing, Leiden University Medical Center, 2300 RC, Leiden, The Netherlands
| | - Pieter H Kitslaar
- Department of Radiology, Division of Image Processing, Leiden University Medical Center, 2300 RC, Leiden, The Netherlands
| | - Bram F Coolen
- Department of Radiology, Academic Medical Center, 1100 DD, Amsterdam, The Netherlands
| | | | - Loek P Smits
- Department of Radiology, Academic Medical Center, 1100 DD, Amsterdam, The Netherlands
| | - Rahil Shahzad
- Department of Radiology, Division of Image Processing, Leiden University Medical Center, 2300 RC, Leiden, The Netherlands
| | - Denis P Shamonin
- Department of Radiology, Division of Image Processing, Leiden University Medical Center, 2300 RC, Leiden, The Netherlands
| | - Patrick J H de Koning
- Department of Radiology, Division of Image Processing, Leiden University Medical Center, 2300 RC, Leiden, The Netherlands
| | - Aart J Nederveen
- Department of Radiology, Academic Medical Center, 1100 DD, Amsterdam, The Netherlands
| | - Rob J van der Geest
- Department of Radiology, Division of Image Processing, Leiden University Medical Center, 2300 RC, Leiden, The Netherlands
| |
Collapse
|