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Schilham MGM, Somford DM, Küsters-Vandevelde HVN, Hermsen R, van Basten JPA, Hoekstra RJ, Scheenen TWJ, Gotthardt M, Sedelaar JPM, Rijpkema M. Prostate-Specific Membrane Antigen-Targeted Radioguided Pelvic Lymph Node Dissection in Newly Diagnosed Prostate Cancer Patients with a Suspicion of Locoregional Lymph Node Metastases: The DETECT Trial. J Nucl Med 2024; 65:423-429. [PMID: 38176721 DOI: 10.2967/jnumed.123.266495] [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: 08/10/2023] [Revised: 11/07/2023] [Accepted: 11/07/2023] [Indexed: 01/06/2024] Open
Abstract
Prostate-specific membrane antigen (PSMA)-targeted radioguided surgery (RGS) aims to optimize the peroperative detection and removal of PSMA-avid lymph node (LN) metastases (LNMs) and has been described in patients with recurrent prostate cancer (PCa). In newly diagnosed PCa patients undergoing pelvic LN dissections, PSMA RGS could guide the urologist toward PSMA-expressing LNMs as identified on preoperative 18F-PSMA PET/CT imaging. The objective was to evaluate the safety and feasibility of 111In-PSMA RGS in primary PCa patients with one or more suggestive LNs on preoperative 18F-PSMA PET/CT. Methods: This prospective, phase I/II study included 20 newly diagnosed PCa patients with at least 1 suggestive LN on preoperative 18F-PSMA PET/CT. PSMA RGS was performed 24 h after 111In-PSMA-I&T administration, and postoperative 18F-PSMA PET/CT was performed to verify successful removal of the suggestive lesions. The primary endpoint was determination of the safety and feasibility of 111In-PSMA RGS. Safety was assessed by monitoring adverse events. Feasibility was described as the possibility to peroperatively detect suggestive LNs as identified on preoperative imaging. Secondary outcomes included the accuracy of 111In-PSMA RGS compared with histopathology, tumor- and lesion-to-background ratios, and biochemical recurrence. Results: No tracer-related adverse events were reported. In 20 patients, 43 of 49 (88%) 18F-PSMA PET-suggestive lesions were successfully removed. 111In-PSMA RGS facilitated peroperative identification and resection of 29 of 49 (59%) RGS-target lesions, of which 28 (97%) contained LNMs. Another 14 of 49 (29%) resected LNs were not detected with 111In-PSMA RGS, of which 2 contained metastases. Conclusion: 111In-PSMA RGS is a safe and feasible procedure that allows peroperative detection of 18F-PSMA PET/CT-suggestive lesions in newly diagnosed PCa patients. The use of a radioactive PSMA tracer and a detection device (γ-probe) during surgery helps in identifying LNs that were suggestive of PCa metastases on the 18F-PSMA PET/CT before surgery and thus may improve the peroperative identification and removal of these LNs.
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Affiliation(s)
- Melline G M Schilham
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands;
- Prosper Prostate Cancer Clinics, Nijmegen/Eindhoven, The Netherlands
- Department of Urology, Canisius Wilhelmina Hospital, Nijmegen, The Netherlands
| | - Diederik M Somford
- Prosper Prostate Cancer Clinics, Nijmegen/Eindhoven, The Netherlands
- Department of Urology, Canisius Wilhelmina Hospital, Nijmegen, The Netherlands
| | | | - Rick Hermsen
- Department of Nuclear Medicine, Canisius Wilhelmina Hospital, Nijmegen, The Netherlands
| | - Jean Paul A van Basten
- Prosper Prostate Cancer Clinics, Nijmegen/Eindhoven, The Netherlands
- Department of Urology, Canisius Wilhelmina Hospital, Nijmegen, The Netherlands
| | - Robert J Hoekstra
- Prosper Prostate Cancer Clinics, Nijmegen/Eindhoven, The Netherlands
- Department of Urology, Catharina Hospital, Eindhoven, The Netherlands; and
| | - Tom W J Scheenen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Martin Gotthardt
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - J P Michiel Sedelaar
- Prosper Prostate Cancer Clinics, Nijmegen/Eindhoven, The Netherlands
- Department of Urology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Mark Rijpkema
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
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Stamatelatou A, Bertinetto CG, Jansen JJ, Postma G, Selnaes KM, Bathen TF, Heerschap A, Scheenen TWJ. A multivariate curve resolution analysis of multicenter proton spectroscopic imaging of the prostate for cancer localization and assessment of aggressiveness. NMR Biomed 2024; 37:e5062. [PMID: 37920145 DOI: 10.1002/nbm.5062] [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] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 09/21/2023] [Accepted: 09/25/2023] [Indexed: 11/04/2023]
Abstract
In this study, we investigated the potential of the multivariate curve resolution alternating least squares (MCR-ALS) algorithm for analyzing three-dimensional (3D) 1 H-MRSI data of the prostate in prostate cancer (PCa) patients. MCR-ALS generates relative intensities of components representing spectral profiles derived from a large training set of patients, providing an interpretable model. Our objectives were to classify magnetic resonance (MR) spectra, differentiating tumor lesions from benign tissue, and to assess PCa aggressiveness. We included multicenter 3D 1 H-MRSI data from 106 PCa patients across eight centers. The patient cohort was divided into a training set (N = 63) and an independent test set (N = 43). Singular value decomposition determined that MR spectra were optimally represented by five components. The profiles of these components were extracted from the training set by MCR-ALS and assigned to specific tissue types. Using these components, MCR-ALS was applied to the test set for a quantitative analysis to discriminate tumor lesions from benign tissue and to assess tumor aggressiveness. Relative intensity maps of the components were reconstructed and compared with histopathology reports. The quantitative analysis demonstrated a significant separation between tumor and benign voxels (t-test, p < 0.001). This result was achieved including voxels with low-quality MR spectra. A receiver operating characteristic analysis of the relative intensity of the tumor component revealed that low- and high-risk tumor lesions could be distinguished with an area under the curve of 0.88. Maps of this component properly identified the extent of tumor lesions. Our study demonstrated that MCR-ALS analysis of 1 H-MRSI of the prostate can reliably identify tumor lesions and assess their aggressiveness. It handled multicenter data with minimal preprocessing and without using prior knowledge or quality control. These findings indicate that MCR-ALS can serve as an automated tool to assess the presence, extent, and aggressiveness of tumor lesions in the prostate, enhancing diagnostic capabilities and treatment planning of PCa patients.
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Affiliation(s)
- Angeliki Stamatelatou
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Jeroen J Jansen
- Department of Analytical Chemistry & Chemometrics, Radboud University, Nijmegen, The Netherlands
| | - Geert Postma
- Department of Analytical Chemistry & Chemometrics, Radboud University, Nijmegen, The Netherlands
| | - Kirsten Margrete Selnaes
- Department of Circulation and Medical Imaging, Norwegian University of Technology and Science, Trondheim, Norway
| | - Tone F Bathen
- Department of Circulation and Medical Imaging, Norwegian University of Technology and Science, Trondheim, Norway
- Department of radiology and nuclear medicine, St. Olavs Hospital - Trondheim University Hospital, Trondheim, Norway
| | - Arend Heerschap
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
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van den Elshout R, Ariëns B, Blaauboer J, Meijer FJA, van der Kolk AG, Esmaeili M, Scheenen TWJ, Henssen DJHA. Quantification of perineural satellitosis in pretreatment glioblastoma with structural MRI and a diffusion tensor imaging template. Neurooncol Adv 2024; 6:vdad168. [PMID: 38196738 PMCID: PMC10776201 DOI: 10.1093/noajnl/vdad168] [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] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2024] Open
Abstract
Background Survival outcomes for glioblastoma (GBM) patients remain unfavorable, and tumor recurrence is often observed. Understanding the radiological growth patterns of GBM could aid in improving outcomes. This study aimed to examine the relationship between contrast-enhancing tumor growth direction and white matter, using an image registration and deformation strategy. Methods In GBM patients 2 pretreatment scans (diagnostic and neuronavigation) were gathered retrospectively, and coregistered to a template and diffusion tensor imaging (DTI) atlas. The GBM lesions were segmented and coregistered to the same space. Growth vectors were derived and divided into vector populations parallel (Φ = 0-20°) and perpendicular (Φ = 70-90°) to white matter. To test for statistical significance between parallel and perpendicular groups, a paired samples Student's t-test was performed. O6-methylguanine-DNA methyltransferase (MGMT) methylation status and its correlation to growth rate were also tested using a one-way ANOVA test. Results For 78 GBM patients (mean age 61 years ± 13 SD, 32 men), the included GBM lesions showed a predominant preference for perineural satellitosis (P < .001), with a mean percentile growth of 30.8% (95% CI: 29.6-32.0%) parallel (0° < |Φ| < 20°) to white matter. Perpendicular tumor growth with respect to white matter microstructure (70° < |Φ| < 90°) showed to be 22.7% (95% CI: 21.3-24.1%) of total tumor growth direction. Conclusions The presented strategy showed that tumor growth direction in pretreatment GBM patients correlated with white matter architecture. Future studies with patient-specific DTI data are required to verify the accuracy of this method prospectively to identify its usefulness as a clinical metric in pre and posttreatment settings.
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Affiliation(s)
- Rik van den Elshout
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Benthe Ariëns
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Joost Blaauboer
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Frederick J A Meijer
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Anja G van der Kolk
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Morteza Esmaeili
- Department of Diagnostic Imaging, Akershus University Hospital, Lørenskog, Norway
- Department of Electrical Engineering and Computer Science, University of Stavanger, Stavanger, Norway
| | - Tom W J Scheenen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Dylan J H A Henssen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
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Tenbergen CJA, Fortuin AS, van Asten JJA, Veltien A, Philips BWJ, Hambrock T, Orzada S, Quick HH, Barentsz JO, Maas MC, Scheenen TWJ. The Potential of Iron Oxide Nanoparticle-Enhanced MRI at 7 T Compared With 3 T for Detecting Small Suspicious Lymph Nodes in Patients With Prostate Cancer. Invest Radiol 2023:00004424-990000000-00184. [PMID: 38157433 DOI: 10.1097/rli.0000000000001056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
BACKGROUND Accurate detection of lymph node (LN) metastases in prostate cancer (PCa) is a challenging but crucial step for disease staging. Ultrasmall superparamagnetic iron oxide (USPIO)-enhanced magnetic resonance imaging (MRI) enables distinction between healthy LNs and nodes suspicious for harboring metastases. When combined with MRI at an ultra-high magnetic field, an unprecedented spatial resolution can be exploited to visualize these LNs. PURPOSE The aim of this study was to explore USPIO-enhanced MRI at 7 T in comparison to 3 T for the detection of small suspicious LNs in the same cohort of patients with PCa. MATERIALS AND METHODS Twenty PCa patients with high-risk primary or recurrent disease were referred to our hospital for an investigational USPIO-enhanced 3 T MRI examination with ferumoxtran-10. With consent, they underwent a 7 T MRI on the same day. Three-dimensional anatomical and T2*-weighted images of both examinations were evaluated blinded, with an interval, by 2 readers who annotated LNs suspicious for metastases. Number, size, and level of suspicion (LoS) of LNs were paired within patients and compared between field strengths. RESULTS At 7 T, both readers annotated significantly more LNs compared with 3 T (474 and 284 vs 344 and 162), with 116 suspicious LNs on 7 T (range, 1-34 per patient) and 79 suspicious LNs on 3 T (range, 1-14 per patient) in 17 patients. For suspicious LNs, the median short axis diameter was 2.6 mm on 7 T (1.3-9.5 mm) and 2.8 mm for 3 T (1.7-10.4 mm, P = 0.05), with large overlap in short axis of annotated LNs between LoS groups. At 7 T, significantly more suspicious LNs had a short axis <2.5 mm compared with 3 T (44% vs 27%). Magnetic resonance imaging at 7 T provided better image quality and structure delineation and a higher LoS score for suspicious nodes. CONCLUSIONS In the same cohort of patients with PCa, more and more small LNs were detected on 7 T USPIO-enhanced MRI compared with 3 T MRI. Suspicious LNs are generally very small, and increased nodal size was not a good indication of suspicion for the presence of metastases. The high spatial resolution of USPIO-enhanced MRI at 7 T improves structure delineation and the visibility of very small suspicious LNs, potentially expanding the in vivo detection limits of pelvic LN metastases in PCa patients.
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Affiliation(s)
- Carlijn J A Tenbergen
- From the Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands (C.J.A.T., A.S.F., J.J.A.v.A., A.V., B.W.J.P., T.H., J.O.B., M.C.M., T.W.J.S.); Department of Radiology, Ziekenhuis Gelderse Vallei, Ede, the Netherlands (A.S.F.); Erwin L. Hahn Institute for MR Imaging, University of Duisburg-Essen, Essen, Germany (S.O., H.H.Q., T.W.J.S.); High-Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany (S.O., H.H.Q.); and Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany (S.O.)
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Nieuwenhuis ER, Mir N, Horstman-van de Loosdrecht MM, Meeuwis APW, de Bakker MGJ, Scheenen TWJ, Alic L. Performance of a Nonlinear Magnetic Handheld Probe for Intraoperative Sentinel Lymph Node Detection: A Phantom Study. Ann Surg Oncol 2023; 30:8735-8742. [PMID: 37661223 PMCID: PMC10625952 DOI: 10.1245/s10434-023-14166-z] [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: 02/03/2023] [Accepted: 07/09/2023] [Indexed: 09/05/2023]
Abstract
OBJECTIVE This study investigates the performance of the DiffMag handheld probe (nonlinear magnetometry), to be used for sentinel lymph node detection. Furthermore, the performance of DiffMag is compared with a gamma probe and a first-order magnetometer (Sentimag®, linear magnetometry). METHODS The performance of all three probes was evaluated based on longitudinal distance, transverse distance, and resolving power for two tracer volumes. A phantom was developed to investigate the performance of the probes for a clinically relevant situation in the floor of the mouth (FOM). RESULTS Considering the longitudinal distance, both DiffMag handheld and Sentimag® probe had comparable performance, while the gamma probe was able to detect at least a factor of 10 deeper. Transverse distances of 13, 11, and 51 mm were measured for the small tracer volume by the DiffMag handheld, Sentimag®, and the gamma probe, respectively. For the large tracer volume this was 21, 18, and 55 mm, respectively. The full width at half maximum, at 7 mm probe height from the phantom surface, was 14, 12, and 18 mm for the small tracer volume and 15, 18, and 25 mm for the large tracer volume with the DiffMag handheld, Sentimag®, and gamma probe, respectively. CONCLUSIONS With a high resolving power but limited longitudinal distance, the DiffMag handheld probe seems suitable for detecting SLNs which are in close proximity to the primary tumor. In this study, comparable results were shown using linear magnetometry. The gamma probe reached 10 times deeper, but has a lower resolving power compared with the DiffMag handheld probe.
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Affiliation(s)
- Eliane R Nieuwenhuis
- Magnetic Detection and Imaging Group, Technical Medical Centre, University of Twente, Enschede, The Netherlands
| | - Nida Mir
- Magnetic Detection and Imaging Group, Technical Medical Centre, University of Twente, Enschede, The Netherlands
| | | | - Antoi P W Meeuwis
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Maarten G J de Bakker
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Lejla Alic
- Magnetic Detection and Imaging Group, Technical Medical Centre, University of Twente, Enschede, The Netherlands.
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Schilham MGM, Somford DM, Veltien A, Zamecnik P, Barentsz JO, Sedelaar MJPM, Kusters-Vandevelde HVN, Gotthardt M, Rijpkema M, Scheenen TWJ. Subnodal Correspondence of PSMA Expression and USPIO-MRI in Metastatic Pelvic Lymph Nodes in Prostate Cancer. Invest Radiol 2023:00004424-990000000-00174. [PMID: 37975702 DOI: 10.1097/rli.0000000000001046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2023]
Abstract
OBJECTIVES Two advanced imaging modalities used to detect lymph node (LN) metastases in prostate cancer patients are prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography and ultrasmall superparamagnetic iron oxide (USPIO)-enhanced magnetic resonance imaging (MRI). As these modalities use different targets, a subnodal comparison is needed to interpret both their correspondence and their differences. The aim of this explorative study was to compare ex vivo 111In-PSMA μSPECT images with high-resolution 7 T USPIO μMR images and histopathology of resected LN specimens from prostate cancer patients to assess the degree of correspondence at subnodal level. MATERIALS AND METHODS Twenty primary prostate cancer patients who underwent pelvic LN dissection were included and received USPIO contrast and 111In-PSMA. A total of 41 LNs of interest (LNOIs) were selected for ex vivo imaging based on γ-probe detection or palpation. μSPECT and μMRI acquisition were performed immediately after resection. Overlay of μSPECT images on MR images was performed, and the level of correspondence (LoC) between μSPECT and μMR findings was assessed according to a 4-point Likert classification scheme. RESULTS Forty-one LNOIs could be matched to an LN on ex vivo μMRI. Coregistration of μSPECT and USPIO-enhanced water-selective multigradient echo MR images was successful for all 41 LNOIs. Ninety percent of the lesions showed excellent correspondence regarding the presence of metastatic tissue and affected subnodal site (LoC 4; 37/41). In only 1 of 41 LNOIs, a small metastasis was misclassified by both techniques. Three LNOIs were classified as LoC 3 (7%) and 1 LNOI as LoC 2. All LoC 2 and LoC 3 lesions had PSMA-expressing metastases on final histopathology. CONCLUSIONS Coregistration of μSPECT and USPIO-μMRI showed excellent subnodal correspondence in the majority (90%) of LNs. Ex vivo imaging may thus help localize small cancer deposits within resected LNs and could contribute to improved interpretation of in vivo imaging of LNs.
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Affiliation(s)
- Melline Gabrielle Maria Schilham
- From the Department of Medical Imaging-Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands (M.G.M.S., A.V., P.Z., J.O.B., M.G., M.R., T.W.J.S.); Prosper Prostate Cancer Clinics, Nijmegen/Eindhoven, the Netherlands (D.M.S., J.P.M.S.); Department of Urology, Canisius Wilhelmina Hospital, Nijmegen, the Netherlands (D.M.S.); Andros Clinics, Medical Imaging, Arnhem, the Netherlands (J.O.B.); Department of Urology, Radboud University Medical Center, Nijmegen, the Netherlands (J.P.M.S.); and Department of Pathology, Canisius Wilhelmina Hospital, Nijmegen, the Netherlands (H.V.N.K.-V.)
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van den Elshout R, Herings SDA, Mannil M, Gijtenbeek AMM, ter Laan M, Smeenk RJ, Meijer FJA, Scheenen TWJ, Henssen DJHA. Apparent Diffusion Coefficient Metrics to Differentiate between Treatment-Related Abnormalities and Tumor Progression in Post-Treatment Glioblastoma Patients: A Retrospective Study. Cancers (Basel) 2023; 15:4990. [PMID: 37894355 PMCID: PMC10605800 DOI: 10.3390/cancers15204990] [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] [Received: 08/30/2023] [Revised: 10/08/2023] [Accepted: 10/10/2023] [Indexed: 10/29/2023] Open
Abstract
Distinguishing treatment-related abnormalities (TRA) from tumor progression (TP) in glioblastoma patients is a diagnostic imaging challenge due to the identical morphology of conventional MR imaging sequences. Diffusion-weighted imaging (DWI) and its derived images of the apparent diffusion coefficient (ADC) have been suggested as diagnostic tools for this problem. The aim of this study is to determine the diagnostic accuracy of different cut-off values of the ADC to differentiate between TP and TRA. In total, 76 post-treatment glioblastoma patients with new contrast-enhancing lesions were selected. Lesions were segmented using a T1-weighted, contrast-enhanced scan. The mean ADC values of the segmentations were compared between TRA and TP groups. Diagnostic accuracy was compared by use of the area under the curve (AUC) and the derived sensitivity and specificity values from cutoff points. Although ADC values in TP (mean = 1.32 × 10-3 mm2/s; SD = 0.31 × 10-3 mm2/s) were significantly different compared to TRA (mean = 1.53 × 10-3 mm2/s; SD = 0.28 × 10-3 mm2/s) (p = 0.003), considerable overlap in their distributions exists. The AUC of ADC values to distinguish TP from TRA was 0.71, with a sensitivity and specificity of 65% and 70%, respectively, at an ADC value of 1.47 × 10-3 mm2/s. These findings therefore indicate that ADC maps should not be used in discerning between TP and TRA at a certain timepoint without information on temporal evolution.
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Affiliation(s)
- Rik van den Elshout
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands; (S.D.A.H.); (F.J.A.M.); (T.W.J.S.); (D.J.H.A.H.)
- Radiologie Radboudumc, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Siem D. A. Herings
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands; (S.D.A.H.); (F.J.A.M.); (T.W.J.S.); (D.J.H.A.H.)
| | - Manoj Mannil
- University Clinic for Radiology, Westfälische Wilhelms-University Muenster and University Hospital Muenster, Albert-Schweitzer-Campus 1, DE-48149 Muenster, Germany;
| | - Anja M. M. Gijtenbeek
- Department of Neurology, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands;
| | - Mark ter Laan
- Department of Neurosurgery, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands;
| | - Robert J. Smeenk
- Department of Radiation Oncology, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands;
| | - Frederick J. A. Meijer
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands; (S.D.A.H.); (F.J.A.M.); (T.W.J.S.); (D.J.H.A.H.)
| | - Tom W. J. Scheenen
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands; (S.D.A.H.); (F.J.A.M.); (T.W.J.S.); (D.J.H.A.H.)
| | - Dylan J. H. A. Henssen
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands; (S.D.A.H.); (F.J.A.M.); (T.W.J.S.); (D.J.H.A.H.)
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Hendriks AD, Veltien A, Voogt IJ, Heerschap A, Scheenen TWJ, Prompers JJ. Glucose versus fructose metabolism in the liver measured with deuterium metabolic imaging. Front Physiol 2023; 14:1198578. [PMID: 37465695 PMCID: PMC10351417 DOI: 10.3389/fphys.2023.1198578] [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] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Accepted: 06/20/2023] [Indexed: 07/20/2023] Open
Abstract
Chronic intake of high amounts of fructose has been linked to the development of metabolic disorders, which has been attributed to the almost complete clearance of fructose by the liver. However, direct measurement of hepatic fructose uptake is complicated by the fact that the portal vein is difficult to access. Here we present a new, non-invasive method to measure hepatic fructose uptake and metabolism with the use of deuterium metabolic imaging (DMI) upon administration of [6,6'-2H2]fructose. Using both [6,6'-2H2]glucose and [6,6'-2H2]fructose, we determined differences in the uptake and metabolism of glucose and fructose in the mouse liver with dynamic DMI. The deuterated compounds were administered either by fast intravenous (IV) bolus injection or by slow IV infusion. Directly after IV bolus injection of [6,6'-2H2]fructose, a more than two-fold higher initial uptake and subsequent 2.5-fold faster decay of fructose was observed in the mouse liver as compared to that of glucose after bolus injection of [6,6'-2H2]glucose. In contrast, after slow IV infusion of fructose, the 2H fructose/glucose signal maximum in liver spectra was lower compared to the 2H glucose signal maximum after slow infusion of glucose. With both bolus injection and slow infusion protocols, deuterium labeling of water was faster with fructose than with glucose. These observations are in line with a higher extraction and faster turnover of fructose in the liver, as compared with glucose. DMI with [6,6'-2H2]glucose and [6,6'-2H2]fructose could potentially contribute to a better understanding of healthy human liver metabolism and aberrations in metabolic diseases.
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Affiliation(s)
- Arjan D. Hendriks
- Center of Image Sciences, University Medical Center Utrecht, Utrecht, Netherlands
| | - Andor Veltien
- Department of Medical Imaging (Radiology), Radboud University Medical Center, Nijmegen, Netherlands
| | | | - Arend Heerschap
- Department of Medical Imaging (Radiology), Radboud University Medical Center, Nijmegen, Netherlands
| | - Tom W. J. Scheenen
- Department of Medical Imaging (Radiology), Radboud University Medical Center, Nijmegen, Netherlands
| | - Jeanine J. Prompers
- Center of Image Sciences, University Medical Center Utrecht, Utrecht, Netherlands
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Stamatelatou A, Sima DM, van Huffel S, van Asten JJA, Heerschap A, Scheenen TWJ. Post-acquisition water-signal removal in 3D water-unsuppressed 1 H-MR spectroscopic imaging of the prostate. Magn Reson Med 2023; 89:1741-1753. [PMID: 36572967 DOI: 10.1002/mrm.29565] [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] [Received: 03/31/2022] [Revised: 11/23/2022] [Accepted: 12/08/2022] [Indexed: 12/28/2022]
Abstract
PURPOSE To develop a robust processing procedure of raw signals from water-unsuppressed MRSI of the prostate for the mapping of absolute tissue concentrations of metabolites. METHODS Water-unsuppressed 3D MRSI data were acquired from a phantom, from healthy volunteers, and a patient with prostate cancer. Signal processing included sequential computation of the modulus of the FID to remove water sidebands, a Hilbert transformation, and k-space Hamming filtering. For the removal of the water signal, we compared Löwner tensor-based blind source separation (BSS) and Hankel Lanczos singular value decomposition techniques. Absolute metabolite levels were quantified with LCModel and the results were statistically analyzed to compare the water removal methods and conventional water-suppressed MRSI. RESULTS The post-processing algorithms successfully removed the water signal and its sidebands without affecting metabolite signals. The best water removal performance was achieved by Löwner tensor-based BSS. Absolute tissue concentrations of citrate in the peripheral zone derived from water-suppressed and unsuppressed 1 H MRSI were the same and as expected from the known physiology of the healthy prostate. Maps for citrate and choline from water-unsuppressed 3D 1 H-MRSI of the prostate showed expected spatial variations in metabolite levels. CONCLUSION We developed a robust relatively simple post-processing method of water-unsuppressed MRSI of the prostate to remove the water signal. Absolute quantification using the water signal, originating from the same location as the metabolite signals, avoids the acquisition of additional reference data.
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Affiliation(s)
- Angeliki Stamatelatou
- Department of Medical Imaging (766), Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands
| | | | - Sabine van Huffel
- STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering (ESAT), Leuven, Belgium
| | - Jack J A van Asten
- Department of Medical Imaging (766), Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands
| | - Arend Heerschap
- Department of Medical Imaging (766), Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Department of Medical Imaging (766), Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands
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10
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Maatman IT, Ypma S, Kachelrieß M, Berker Y, van der Bijl E, Block KT, Hermans JJ, Maas MC, Scheenen TWJ. Single-spoke binning: Reducing motion artifacts in abdominal radial stack-of-stars imaging. Magn Reson Med 2023; 89:1931-1944. [PMID: 36594436 DOI: 10.1002/mrm.29576] [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] [Received: 09/21/2022] [Revised: 11/23/2022] [Accepted: 12/19/2022] [Indexed: 01/04/2023]
Abstract
PURPOSE To increase the effectiveness of respiratory gating in radial stack-of-stars MRI, particularly when imaging at high spatial resolutions or with multiple echoes. METHODS Free induction decay (FID) navigators were integrated into a three-dimensional gradient echo radial stack-of-stars pulse sequence. These navigators provided a motion signal with a high temporal resolution, which allowed single-spoke binning (SSB): each spoke at each phase encode step was sorted individually to the corresponding motion state of the respiratory signal. SSB was compared with spoke-angle binning (SAB), in which all phase encode steps of one projection angle were sorted without the use of additional navigator data. To illustrate the benefit of SSB over SAB, images of a motion phantom and of six free-breathing volunteers were reconstructed after motion-gating using either method. Image sharpness was quantitatively compared using image gradient entropies. RESULTS The proposed method resulted in sharper images of the motion phantom and free-breathing volunteers. Differences in gradient entropy were statistically significant (p = 0.03) in favor of SSB. The increased accuracy of motion-gating led to a decrease of streaking artifacts in motion-gated four-dimensional reconstructions. To consistently estimate respiratory signals from the FID-navigator data, specific types of gradient spoiler waveforms were required. CONCLUSION SSB allowed high-resolution motion-corrected MR imaging, even when acquiring multiple gradient echo signals or large acquisition matrices, without sacrificing accuracy of motion-gating. SSB thus relieves restrictions on the choice of pulse sequence parameters, enabling the use of motion-gated radial stack-of-stars MRI in a broader domain of clinical applications.
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Affiliation(s)
- Ivo T Maatman
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Sjoerd Ypma
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Marc Kachelrieß
- Division of X-Ray Imaging and Computed Tomography, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Yannick Berker
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany.,Clinical Cooperation Unit Pediatric Oncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.,National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany
| | - Erik van der Bijl
- Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Kai Tobias Block
- Department of Radiology, NYU Langone Health, New York, New York, USA
| | - John J Hermans
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Marnix C Maas
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
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11
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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
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12
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Bates S, Dumoulin SO, Folkers PJM, Formisano E, Goebel R, Haghnejad A, Helmich RC, Klomp D, van der Kolk AG, Li Y, Nederveen A, Norris DG, Petridou N, Roell S, Scheenen TWJ, Schoonheim MM, Voogt I, Webb A. A vision of 14 T MR for fundamental and clinical science. MAGMA 2023; 36:211-225. [PMID: 37036574 PMCID: PMC10088620 DOI: 10.1007/s10334-023-01081-3] [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] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 03/20/2023] [Accepted: 03/21/2023] [Indexed: 04/11/2023]
Abstract
OBJECTIVE We outline our vision for a 14 Tesla MR system. This comprises a novel whole-body magnet design utilizing high temperature superconductor; a console and associated electronic equipment; an optimized radiofrequency coil setup for proton measurement in the brain, which also has a local shim capability; and a high-performance gradient set. RESEARCH FIELDS The 14 Tesla system can be considered a 'mesocope': a device capable of measuring on biologically relevant scales. In neuroscience the increased spatial resolution will anatomically resolve all layers of the cortex, cerebellum, subcortical structures, and inner nuclei. Spectroscopic imaging will simultaneously measure excitatory and inhibitory activity, characterizing the excitation/inhibition balance of neural circuits. In medical research (including brain disorders) we will visualize fine-grained patterns of structural abnormalities and relate these changes to functional and molecular changes. The significantly increased spectral resolution will make it possible to detect (dynamic changes in) individual metabolites associated with pathological pathways including molecular interactions and dynamic disease processes. CONCLUSIONS The 14 Tesla system will offer new perspectives in neuroscience and fundamental research. We anticipate that this initiative will usher in a new era of ultra-high-field MR.
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Affiliation(s)
- Steve Bates
- Tesla Engineering Ltd., Water Lane, Storrington, West Sussex, RH20 3EA, UK
| | - Serge O Dumoulin
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
- Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
- Experimental and Applied Psychology, Vrije University Amsterdam, Amsterdam, The Netherlands
- Experimental Psychology, Utrecht University, Utrecht, The Netherlands
| | | | - Elia Formisano
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands
| | | | - Rick C Helmich
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, The Netherlands
- Department of Neurology, Center of Expertise for Parkinson and Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Dennis Klomp
- Radiology Department, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Anja G van der Kolk
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Yi Li
- Independent Researcher, Magdeburg, Germany
| | - Aart Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - David G Norris
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, The Netherlands.
- Erwin L. Hahn Institute for Magnetic Resonance Imaging UNESCO World Cultural Heritage Zollverein, Kokereiallee 7, Building C84, 45141, Essen, Germany.
- Department of Clinical Neurophysiology (CNPH), Faculty Science and Technology, University of Twente, Enschede, The Netherlands.
| | - Natalia Petridou
- Radiology Department, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Stefan Roell
- Neoscan Solutions GmbH, Joseph-von-Fraunhofer-Str. 6, 39106, Magdeburg, Germany
| | - Tom W J Scheenen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Location VUmc, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Ingmar Voogt
- Wavetronica, Padualaan 8, 3584 CH, Utrecht, The Netherlands
| | - Andrew Webb
- Department of Radiology, C.J. Gorter MRI Centre, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands
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13
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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.
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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
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14
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Tenbergen CJA, Ruhm L, Ypma S, Heerschap A, Henning A, Scheenen TWJ. Improving the Effective Spatial Resolution in 1H-MRSI of the Prostate with Three-Dimensional Overdiscretized Reconstructions. Life (Basel) 2023; 13:life13020282. [PMID: 36836640 PMCID: PMC9967259 DOI: 10.3390/life13020282] [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: 12/12/2022] [Revised: 01/12/2023] [Accepted: 01/14/2023] [Indexed: 01/20/2023] Open
Abstract
In in vivo 1H-MRSI of the prostate, small matrix sizes can cause voxel bleeding extending to regions far from a voxel, dispersing a signal of interest outside that voxel and mixing extra-prostatic residual lipid signals into the prostate. To resolve this problem, we developed a three-dimensional overdiscretized reconstruction method. Without increasing the acquisition time from current 3D MRSI acquisition methods, this method is aimed to improve the localization of metabolite signals in the prostate without compromising on SNR. The proposed method consists of a 3D spatial overdiscretization of the MRSI grid, followed by noise decorrelation with small random spectral shifts and weighted spatial averaging to reach a final target spatial resolution. We successfully applied the three-dimensional overdiscretized reconstruction method to 3D prostate 1H-MRSI data at 3T. Both in phantom and in vivo, the method proved to be superior to conventional weighted sampling with Hamming filtering of k-space. Compared with the latter, the overdiscretized reconstructed data with smaller voxel size showed up to 10% less voxel bleed while maintaining higher SNR by a factor of 1.87 and 1.45 in phantom measurements. For in vivo measurements, within the same acquisition time and without loss of SNR compared with weighted k-space sampling and Hamming filtering, we achieved increased spatial resolution and improved localization in metabolite maps.
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Affiliation(s)
- Carlijn J. A. Tenbergen
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
- Correspondence:
| | - Loreen Ruhm
- High-Field MR Center, Max Planck Institute for Biological Cybernetics, 72076 Tübingen, Germany
| | - Sjoerd Ypma
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Arend Heerschap
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Anke Henning
- High-Field MR Center, Max Planck Institute for Biological Cybernetics, 72076 Tübingen, Germany
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Tom W. J. Scheenen
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
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15
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van den Elshout R, Scheenen TWJ, Driessen CML, Smeenk RJ, Meijer FJA, Henssen D. Diffusion imaging could aid to differentiate between glioma progression and treatment-related abnormalities: a meta-analysis. Insights Imaging 2022; 13:158. [PMID: 36194373 PMCID: PMC9532499 DOI: 10.1186/s13244-022-01295-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [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: 04/04/2022] [Accepted: 09/04/2022] [Indexed: 11/10/2022] Open
Abstract
Background In a considerable subgroup of glioma patients treated with (chemo) radiation new lesions develop either representing tumor progression (TP) or treatment-related abnormalities (TRA). Quantitative diffusion imaging metrics such as the Apparent Diffusion Coefficient (ADC) and Fractional Anisotropy (FA) have been reported as potential metrics to noninvasively differentiate between these two phenomena. Variability in performance scores of these metrics and absence of a critical overview of the literature contribute to the lack of clinical implementation. This meta-analysis therefore critically reviewed the literature and meta-analyzed the performance scores. Methods Systematic searching was carried out in PubMed, EMBASE and The Cochrane Library. Using predefined criteria, papers were reviewed. Diagnostic accuracy values of suitable papers were meta-analyzed quantitatively. Results Of 1252 identified papers, 10 ADC papers, totaling 414 patients, and 4 FA papers, with 154 patients were eligible for meta-analysis. Mean ADC values of the patients in the TP/TRA groups were 1.13 × 10−3mm2/s (95% CI 0.912 × 10–3–1.32 × 10−3mm2/s) and 1.38 × 10−3mm2/s (95% CI 1.33 × 10–3–1.45 × 10−3mm2/s, respectively. Mean FA values of TP/TRA was 0.19 (95% CI 0.189–0.194) and 0.14 (95% CI 0.137–0.143) respectively. A significant mean difference between ADC and FA values in TP versus TRA was observed (p = 0.005). Conclusions Quantitative ADC and FA values could be useful for distinguishing TP from TRA on a meta-level. Further studies using serial imaging of individual patients are warranted to determine the role of diffusion imaging in glioma patients.
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Affiliation(s)
- Rik van den Elshout
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands
| | - Chantal M L Driessen
- Department of Medical Oncology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Robert J Smeenk
- Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Frederick J A Meijer
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands
| | - Dylan Henssen
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands.
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16
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Stamatelatou A, Scheenen TWJ, Heerschap A. Developments in proton MR spectroscopic imaging of prostate cancer. MAGMA 2022; 35:645-665. [PMID: 35445307 PMCID: PMC9363347 DOI: 10.1007/s10334-022-01011-9] [Citation(s) in RCA: 5] [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] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 03/04/2022] [Accepted: 03/22/2022] [Indexed: 10/25/2022]
Abstract
In this paper, we review the developments of 1H-MR spectroscopic imaging (MRSI) methods designed to investigate prostate cancer, covering key aspects such as specific hardware, dedicated pulse sequences for data acquisition and data processing and quantification techniques. Emphasis is given to recent advancements in MRSI methodologies, as well as future developments, which can lead to overcome difficulties associated with commonly employed MRSI approaches applied in clinical routine. This includes the replacement of standard PRESS sequences for volume selection, which we identified as inadequate for clinical applications, by sLASER sequences and implementation of 1H MRSI without water signal suppression. These may enable a new evaluation of the complementary role and significance of MRSI in prostate cancer management.
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Affiliation(s)
- Angeliki Stamatelatou
- Department of Medical Imaging (766), Radboud University Medical Center Nijmegen, Geert Grooteplein 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands.
| | - Tom W J Scheenen
- Department of Medical Imaging (766), Radboud University Medical Center Nijmegen, Geert Grooteplein 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands
| | - Arend Heerschap
- Department of Medical Imaging (766), Radboud University Medical Center Nijmegen, Geert Grooteplein 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands
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17
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Tenbergen CJA, Metzger GJ, Scheenen TWJ. Ultra-high-field MR in Prostate cancer: Feasibility and Potential. Magn Reson Mater Phy 2022; 35:631-644. [PMID: 35579785 PMCID: PMC9113077 DOI: 10.1007/s10334-022-01013-7] [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] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 03/31/2022] [Accepted: 04/07/2022] [Indexed: 02/07/2023]
Abstract
Multiparametric MRI of the prostate at clinical magnetic field strengths (1.5/3 Tesla) has emerged as a reliable noninvasive imaging modality for identifying clinically significant cancer, enabling selective sampling of high-risk regions with MRI-targeted biopsies, and enabling minimally invasive focal treatment options. With increased sensitivity and spectral resolution, ultra-high-field (UHF) MRI (≥ 7 Tesla) holds the promise of imaging and spectroscopy of the prostate with unprecedented detail. However, exploiting the advantages of ultra-high magnetic field is challenging due to inhomogeneity of the radiofrequency field and high local specific absorption rates, raising local heating in the body as a safety concern. In this work, we review various coil designs and acquisition strategies to overcome these challenges and demonstrate the potential of UHF MRI in anatomical, functional and metabolic imaging of the prostate and pelvic lymph nodes. When difficulties with power deposition of many refocusing pulses are overcome and the full potential of metabolic spectroscopic imaging is used, UHF MR(S)I may aid in a better understanding of the development and progression of local prostate cancer. Together with large field-of-view and low-flip-angle anatomical 3D imaging, 7 T MRI can be used in its full strength to characterize different tumor stages and help explain the onset and spatial distribution of metastatic spread.
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Affiliation(s)
- Carlijn J A Tenbergen
- Department of Medical Imaging, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands.
| | - Gregory J Metzger
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA
| | - Tom W J Scheenen
- Department of Medical Imaging, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, Essen, Germany
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18
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Nieuwenhuis ER, Kolenaar B, Hof JJ, van Baarlen J, van Bemmel AJM, Christenhusz A, Scheenen TWJ, ten Haken B, de Bree R, Alic L. A Comprehensive Grading System for a Magnetic Sentinel Lymph Node Biopsy Procedure in Head and Neck Cancer Patients. Cancers (Basel) 2022; 14:cancers14030678. [PMID: 35158946 PMCID: PMC8833366 DOI: 10.3390/cancers14030678] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 01/22/2022] [Accepted: 01/26/2022] [Indexed: 02/05/2023] Open
Abstract
Simple Summary With 30% of clinically negative early-stage oral cancer patients harboring occult metastasis, an accurate staging of metastatic lymph nodes (LN) is of utmost importance for treatment planning. A magnetic sentinel lymph node biopsy (SLNB) procedure is offered as an alternative to conventional SLNB in oral oncology, however, a grading system is missing. A proper grading system is preferred to connect the different components of the magnetic SLNB: preoperative imaging, intraoperative detection, and histopathological examination of sentinel lymph nodes (SLNs). This study aims to provide a first grading system based on the distribution of a magnetic tracer, by means of preoperative magnetic resonance imaging (MRI), intraoperative estimation of iron content, and histopathological assessment of resected nodes. Pre- and post-operative MRI and harvested SLNs of eight tongue cancer patients with successful magnetic SLNB procedure were used for analyses. Abstract A magnetic sentinel lymph node biopsy ((SLN)B) procedure has recently been shown feasible in oral cancer patients. However, a grading system is absent for proper identification and classification, and thus for clinical reporting. Based on data from eight complete magnetic SLNB procedures, we propose a provisional grading system. This grading system includes: (1) a qualitative five-point grading scale for MRI evaluation to describe iron uptake by LNs; (2) an ex vivo count of resected SLN with a magnetic probe to quantify iron amount; and (3) a qualitative five-point grading scale for histopathologic examination of excised magnetic SLNs. Most SLNs with iron uptake were identified and detected in level II. In this level, most variance in grading was seen for MRI and histopathology; MRI and medullar sinus were especially highly graded, and cortical sinus was mainly low graded. On average 82 ± 58 µg iron accumulated in harvested SLNs, and there were no significant differences in injected tracer dose (22.4 mg or 11.2 mg iron). In conclusion, a first step was taken in defining a comprehensive grading system to gain more insight into the lymphatic draining system during a magnetic SLNB procedure.
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Affiliation(s)
- Eliane R. Nieuwenhuis
- Magnetic Detection and Imaging Group, Technical Medical Centre, University of Twente, 7522 NB Enschede, The Netherlands; (E.R.N.); (A.C.); (B.t.H.)
- Department of Maxillofacial Surgery—Head and Neck Surgical Oncology, Medisch Spectrum Twente, 7512 KZ Enschede, The Netherlands;
| | - Barry Kolenaar
- Department of Maxillofacial Surgery—Head and Neck Surgical Oncology, Medisch Spectrum Twente, 7512 KZ Enschede, The Netherlands;
| | - Jurrit J. Hof
- Department of Radiology, Medisch Spectrum Twente, 7512 KZ Enschede, The Netherlands;
| | - Joop van Baarlen
- Laboratorium Pathologie Oost Nederland, 7555 BB Hengelo, The Netherlands;
| | - Alexander J. M. van Bemmel
- Department of Otorhinolaryngology—Head and Neck Surgical Oncology, Medisch Spectrum Twente, 7512 KZ Enschede, The Netherlands;
| | - Anke Christenhusz
- Magnetic Detection and Imaging Group, Technical Medical Centre, University of Twente, 7522 NB Enschede, The Netherlands; (E.R.N.); (A.C.); (B.t.H.)
- Department of Surgery, Medisch Spectrum Twente, 7512 KZ Enschede, The Netherlands
| | - Tom W. J. Scheenen
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands;
| | - Bernard ten Haken
- Magnetic Detection and Imaging Group, Technical Medical Centre, University of Twente, 7522 NB Enschede, The Netherlands; (E.R.N.); (A.C.); (B.t.H.)
| | - Remco de Bree
- Department of Head and Neck Surgical Oncology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands;
| | - Lejla Alic
- Magnetic Detection and Imaging Group, Technical Medical Centre, University of Twente, 7522 NB Enschede, The Netherlands; (E.R.N.); (A.C.); (B.t.H.)
- Correspondence: ; Tel.: +31-534-898-731
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19
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Scheenen TWJ. Dual-purpose coils in MRSI of brain tumours. NMR Biomed 2022; 35:e4660. [PMID: 34816524 DOI: 10.1002/nbm.4660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Affiliation(s)
- Tom W J Scheenen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, Essen, Germany
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20
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Privé BM, Janssen MJR, van Oort IM, Muselaers CHJ, Jonker MA, van Gemert WA, de Groot M, Westdorp H, Mehra N, Verzijlbergen JF, Scheenen TWJ, Zámecnik P, Barentsz JO, Gotthardt M, Noordzij W, Vogel WV, Bergman AM, van der Poel HG, Vis AN, Oprea-Lager DE, Gerritsen WR, Witjes JA, Nagarajah J. Update to a randomized controlled trial of lutetium-177-PSMA in Oligo-metastatic hormone-sensitive prostate cancer: the BULLSEYE trial. Trials 2021; 22:768. [PMID: 34736509 PMCID: PMC8566967 DOI: 10.1186/s13063-021-05733-4] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 10/19/2021] [Indexed: 12/09/2022] Open
Abstract
BACKGROUND The BULLSEYE trial is a multicenter, open-label, randomized controlled trial to test the hypothesis if 177Lu-PSMA is an effective treatment in oligometastatic hormone-sensitive prostate cancer (oHSPC) to prolong the progression-free survival (PFS) and postpone the need for androgen deprivation therapy (ADT). The original study protocol was published in 2020. Here, we report amendments that have been made to the study protocol since the commencement of the trial. CHANGES IN METHODS AND MATERIALS Two important changes were made to the original protocol: (1) the study will now use 177Lu-PSMA-617 instead of 177Lu-PSMA-I&T and (2) responding patients with residual disease on 18F-PSMA PET after the first two cycles are eligible to receive additional two cycles of 7.4 GBq 177Lu-PSMA in weeks 12 and 18, summing up to a maximum of 4 cycles if indicated. Therefore, patients receiving 177Lu-PSMA-617 will also receive an interim 18F-PSMA PET scan in week 4 after cycle 2. The title of this study was modified to; "Lutetium-177-PSMA in Oligo-metastatic Hormone Sensitive Prostate Cancer" and is now partly supported by Advanced Accelerator Applications, a Novartis Company. CONCLUSIONS We present an update of the original study protocol prior to the completion of the study. Treatment arm patients that were included and received 177Lu-PSMA-I&T under the previous protocol will be replaced. TRIAL REGISTRATION ClinicalTrials.gov NCT04443062 . First posted: June 23, 2020.
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Affiliation(s)
- Bastiaan M Privé
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
| | - Marcel J R Janssen
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
| | - Inge M van Oort
- Department of Urology, Radboudumc, Nijmegen, The Netherlands
| | | | - Marianne A Jonker
- Department of Health Evidence, Radboudumc, Nijmegen, The Netherlands
| | - Willemijn A van Gemert
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
| | - Michel de Groot
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
| | - Harm Westdorp
- Department of Medical Oncology, Radboudumc, Nijmegen, The Netherlands
| | - Niven Mehra
- Department of Medical Oncology, Radboudumc, Nijmegen, The Netherlands
| | - J Fred Verzijlbergen
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
| | - Patrik Zámecnik
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
| | - Jelle O Barentsz
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
| | - Martin Gotthardt
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
| | - Walter Noordzij
- Department of Radiology and Nuclear Medicine, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Wouter V Vogel
- Department of Radiology and Nuclear Medicine, NKI Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands.,Department of Radiation Oncology, NKI Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Andries M Bergman
- Department of Medical Oncology, NKI Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Henk G van der Poel
- Department of Urology, NKI Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - André N Vis
- Department of Urology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Daniela E Oprea-Lager
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | | | - J Alfred Witjes
- Department of Urology, Radboudumc, Nijmegen, The Netherlands
| | - James Nagarajah
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands.
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21
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Lin M, Breukels V, Scheenen TWJ, Paulusse JMJ. Dynamic Nuclear Polarization of Silicon Carbide Micro- and Nanoparticles. ACS Appl Mater Interfaces 2021; 13:30835-30843. [PMID: 34170657 PMCID: PMC8289227 DOI: 10.1021/acsami.1c07156] [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] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 06/13/2021] [Indexed: 06/13/2023]
Abstract
Two dominant crystalline phases of silicon carbide (SiC): α-SiC and β-SiC, differing in size and chemical composition, were investigated regarding their potential for dynamic nuclear polarization (DNP). 29Si nuclei in α-SiC micro- and nanoparticles with sizes ranging from 650 nm to 2.2 μm and minimal oxidation were successfully hyperpolarized without the use of free radicals, while β-SiC samples did not display appreciable degrees of polarization under the same polarization conditions. Long T1 relaxation times in α-SiC of up to 1600 s (∼27 min) were recorded for the 29Si nuclei after 1 h of polarization at a temperature of 4 K. Interestingly, these promising α-SiC particles allowed for direct hyperpolarization of both 29Si and 13C nuclei, resulting in comparably strong signal amplifications. Moreover, the T1 relaxation time of 13C nuclei in 750 nm-sized α-SiC particles was over 33 min, which far exceeds T1 times of conventional 13C DNP probes with values in the order of 1-2 min. The present work demonstrates the feasibility of DNP on SiC micro- and nanoparticles and highlights their potential as hyperpolarized magnetic resonance imaging agents.
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Affiliation(s)
- Min Lin
- Department
of Biomolecular Nanotechnology, MESA+ Institute for Nanotechnology,
Faculty of Science and Technology, University
of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands
| | - Vincent Breukels
- Department
of Medical Imaging, Radboud University Medical
Center, Nijmegen, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands
| | - Tom W. J. Scheenen
- Department
of Medical Imaging, Radboud University Medical
Center, Nijmegen, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands
| | - Jos M. J. Paulusse
- Department
of Biomolecular Nanotechnology, MESA+ Institute for Nanotechnology,
Faculty of Science and Technology, University
of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands
- Department
of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen,
P.O. Box 30.001, 9700 RB Groningen, The Netherlands
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22
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Privé BM, Peters SMB, Muselaers CHJ, van Oort IM, Janssen MJR, Sedelaar JPM, Konijnenberg MW, Zámecnik P, Uijen MJM, Schilham MGM, Eek A, Scheenen TWJ, Verzijlbergen JF, Gerritsen WR, Mehra N, Kerkmeijer LGW, Smeenk RJ, Somford DM, van Basten JPA, Heskamp S, Barentsz JO, Gotthardt M, Witjes JA, Nagarajah J. Lutetium-177-PSMA-617 in Low-Volume Hormone-Sensitive Metastatic Prostate Cancer: A Prospective Pilot Study. Clin Cancer Res 2021; 27:3595-3601. [PMID: 33883176 DOI: 10.1158/1078-0432.ccr-20-4298] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 03/25/2021] [Accepted: 04/16/2021] [Indexed: 12/09/2022]
Abstract
PURPOSE [177Lu]Lu-PSMA-617 radioligand therapy (177Lu-PSMA) is a novel treatment for metastatic castration-resistant prostate cancer (mCRPC), which could also be applied to patients with metastatic hormone-sensitive prostate cancer (mHSPC) with PSMA expression. In this prospective study (NCT03828838), we analyzed toxicity, radiation doses, and treatment effect of 177Lu-PSMA in pateints with low-volume mHSPC. PATIENTS AND METHODS Ten progressive patients with mHSPC following local treatment, with a maximum of ten metastatic lesions on [68Ga]Ga-PSMA-11 PET/diagnostic-CT imaging (PSMA-PET) and serum PSA doubling time <6 months received two cycles of 177Lu-PSMA. Whole-body single-photon emission CT/CT (SPECT/CT) and blood dosimetry was performed to calculate doses to the tumors and organs at risk (OAR). Adverse events (AE), laboratory values (monitoring response and toxicity), and quality of life were monitored until week 24 after cycle 2, the end of study (EOS). All patients underwent PSMA-PET at screening, 8 weeks after cycle 1, 12 weeks after cycle 2, and at EOS. RESULTS All patients received two cycles of 177Lu-PSMA without complications. No treatment-related grade III-IV adverse events were observed. According to dosimetry, none of the OAR reached threshold doses for radiation-related toxicity. Moreover, all target lesions received a higher radiation dose than the OAR. All 10 patients showed altered PSA kinetics, postponed androgen deprivation therapy, and maintained good quality of life. Half of the patients showed a PSA response of more than 50%. One patient had a complete response on PSMA-PET imaging until EOS and two others had only minimal residual disease. CONCLUSIONS 177Lu-PSMA appeared to be a feasible and safe treatment modality in patients with low-volume mHSPC.
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Affiliation(s)
- Bastiaan M Privé
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands
| | - Steffie M B Peters
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands
| | | | - Inge M van Oort
- Department of Urology, Radboudumc, Nijmegen, the Netherlands
| | - Marcel J R Janssen
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands
| | | | - Mark W Konijnenberg
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands.,Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands
| | - Patrik Zámecnik
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands
| | - Maike J M Uijen
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands
| | - Melline G M Schilham
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands
| | - Annemarie Eek
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands
| | - J Fred Verzijlbergen
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands
| | | | - Niven Mehra
- Department of Medical Oncology, Radboudumc, Nijmegen, the Netherlands
| | | | - Robert J Smeenk
- Department of Radiation Oncology, Radboudumc, Nijmegen, the Netherlands
| | - Diederik M Somford
- Department of Urology, Canisius Wilhelmina Hospital, Nijmegen, the Netherlands
| | | | - Sandra Heskamp
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands
| | - Jelle O Barentsz
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands
| | - Martin Gotthardt
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands
| | - J Alfred Witjes
- Department of Urology, Radboudumc, Nijmegen, the Netherlands
| | - James Nagarajah
- Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands. .,Department of Nuclear Medicine, Technische Universität München, Klinikum rechts der Isar, München, Germany
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Stijns RCH, Philips BWJ, Nagtegaal ID, Polat F, de Wilt JHW, Wauters CAP, Zamecnik P, Fütterer JJ, Scheenen TWJ. USPIO-enhanced MRI of lymph nodes in rectal cancer: A node-to-node comparison with histopathology. Eur J Radiol 2021; 138:109636. [PMID: 33721766 DOI: 10.1016/j.ejrad.2021.109636] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2021] [Revised: 03/04/2021] [Accepted: 03/06/2021] [Indexed: 01/21/2023]
Abstract
PURPOSE To evaluate the initial results of predicting lymph node metastasis in rectal cancer patients detected in-vivo with USPIO-enhanced MRI at 3 T compared on a node-to-node basis with histopathology. METHODS Ten rectal cancer patients of all clinical stages were prospectively included for an in-vivo 0.85 mm3 isotropic 3D MRI after infusion of Ferumoxtran-10. The surgical specimens were examined ex-vivo with an 0.29 mm3 isotropic MRI examination. Two radiologists evaluated in-vivo MR images with a classification scheme to predict lymph node status. Ex-vivo MRI was used for MR-guided pathology and served as a key link between in-vivo MRI and final histopathology for the node-to-node analysis. RESULTS 138 lymph nodes were detected by reader 1 and 255 by reader 2 (p = 0.005) on in-vivo MRI with a median size of 2.6 and 2.4 mm, respectively. Lymph nodes were classified with substantial inter-reader agreement (κ = 0.73). Node-to-node comparison was possible for 55 lymph nodes (median size 3.2 mm; range 1.2-12.3), of which 6 were metastatic on pathology. Low true-positive rates (3/26, 11 % for both readers) and high true negative rates were achieved (14/17, 82 %; 19/22, 86 %). Pathological re-evaluations of 20 lymph nodes with high signal intensity on USPIO-enhanced MRI without lymph node metastases (false positives) did not reveal tumor metastasis but showed benign lymph node tissue with reactive follicles. CONCLUSIONS High resolution MRI visualizes a large number of mesorectal lymph nodes. USPIO-enhanced MRI was not accurate for characterizing small benign versus small tumoral lymph nodes in rectal cancer patients. Suspicious nodes on in-vivo MRI occur as inflammatory as well as metastatic nodes.
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Affiliation(s)
- Rutger C H Stijns
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands; Department of Surgery, Radboud University Medical Center, Nijmegen, the Netherlands.
| | - Bart W J Philips
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Iris D Nagtegaal
- Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Fatih Polat
- Department of Surgery, Canisius-Wilhelmina Hospital, Nijmegen, the Netherlands
| | - Johannes H W de Wilt
- Department of Surgery, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Carla A P Wauters
- Department of Pathology, Canisius-Wilhelmina Hospital, Nijmegen, the Netherlands
| | - Patrik Zamecnik
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Jurgen J Fütterer
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands; Erwin L. Hahn Institute for MR Imaging, University of Duisburg-Essen, Essen, 45141, Germany
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Driessen DAJJ, Dijkema T, Weijs WLJ, Takes RP, Pegge SAH, Zámecnik P, van Engen-van Grunsven ACH, Scheenen TWJ, Kaanders JHAM. Novel Diagnostic Approaches for Assessment of the Clinically Negative Neck in Head and Neck Cancer Patients. Front Oncol 2021; 10:637513. [PMID: 33634033 PMCID: PMC7901951 DOI: 10.3389/fonc.2020.637513] [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: 12/03/2020] [Accepted: 12/21/2020] [Indexed: 02/06/2023] Open
Abstract
In head and neck cancer, the presence of nodal disease is a strong determinant of prognosis and treatment. Despite the use of modern multimodality diagnostic imaging, the prevalence of occult nodal metastases is relatively high. This is why in clinically node negative head and neck cancer the lymphatics are treated “electively” to eradicate subclinical tumor deposits. As a consequence, many true node negative patients undergo surgery or irradiation of the neck and suffer from the associated and unnecessary early and long-term morbidity. Safely tailoring head and neck cancer treatment to individual patients requires a more accurate pre-treatment assessment of nodal status. In this review, we discuss the potential of several innovative diagnostic approaches to guide customized management of the clinically negative neck in head and neck cancer patients.
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Affiliation(s)
- Daphne A J J Driessen
- Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, Netherlands
| | - Tim Dijkema
- Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, Netherlands
| | - Willem L J Weijs
- Department of Oral- and Maxillofacial Surgery and Head and Neck Surgery, Radboud University Medical Center, Nijmegen, Netherlands
| | - Robert P Takes
- Department of Otorhinolaryngology and Head and Neck Surgery, Radboud University Medical Center, Nijmegen, Netherlands
| | - Sjoert A H Pegge
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, Netherlands
| | - Patrik Zámecnik
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, Netherlands
| | | | - Tom W J Scheenen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, Netherlands
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Smits M, Ekici K, Pamidimarri Naga S, van Oort IM, Sedelaar MJP, Schalken JA, Nagarajah J, Scheenen TWJ, Gerritsen WR, Fütterer JJ, Mehra N. Prior PSMA PET-CT Imaging and Hounsfield Unit Impact on Tumor Yield and Success of Molecular Analyses from Bone Biopsies in Metastatic Prostate Cancer. Cancers (Basel) 2020; 12:cancers12123756. [PMID: 33327413 PMCID: PMC7764855 DOI: 10.3390/cancers12123756] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [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: 09/30/2020] [Revised: 12/02/2020] [Accepted: 12/04/2020] [Indexed: 02/06/2023] Open
Abstract
Simple Summary Prostate cancer is currently the fifth leading cause of death in men worldwide. To personalize and guide treatment in prostate cancer, identification of druggable genomic alterations is of major importance. Prostate cancer often metastasizes solely or predominantly to the bones, with molecular analyses on bone biopsies challenging due to technical difficulties to identify and obtain biopsies from high tumor cell containing locations. In our retrospective analysis, we showed a significantly higher success rate in patients where biopsy location was selected by a prior PSMA PET-CT compared to solely CT or MRI. CT-guided biopsies in locations with low Hounsfield units (HUs) and deviation of HUs were associated with a higher proportion of successful histological and molecular biopsies. Based on these results, we designed a simple prediction model for daily clinical practice to increase the success rate of bone biopsies for molecular analyses in prostate cancer to guide precision medicine. Abstract Developing and optimizing targeted therapies in metastatic castration-resistant prostate cancer (mCRPC) necessitates molecular characterization. Obtaining sufficient tumor material for molecular characterization has been challenging. We aimed to identify clinical and imaging variables of imaging-guided bone biopsies in metastatic prostate cancer patients that associate with tumor yield and success in obtaining molecular results, and to design a predictive model: Clinical and imaging data were collected retrospectively from patients with prostate cancer who underwent a bone biopsy for histological and molecular characterization. Clinical characteristics, imaging modalities and imaging variables, were associated with successful biopsy results. In our study, we included a total of 110 bone biopsies. Histological conformation was possible in 84 of all biopsies, of which, in 73 of the 84, successful molecular characterization was performed. Prior use of PSMA PET-CT resulted in higher success rates in histological and molecular successful biopsies compared to CT or MRI. Evaluation of spine biopsies showed more often successful results compared to other locations for both histological and molecular biopsies (p = 0.027 and p = 0.012, respectively). Low Hounsfield units (HUs) and deviation (Dev), taken at CT-guidance, were associated with histological successful biopsies (p = 0.025 and p = 0.023, respectively) and with molecular successful biopsies (p = 0.010 and p = 0.006, respectively). A prediction tool combining low HUs and low Dev resulted in significantly more successful biopsies, histological and molecular (p = 0.023 and p = 0.007, respectively). Based on these results, we concluded that site selection for metastatic tissue biopsies with prior PSMA PET-CT imaging improves the chance of a successful biopsy. Further optimization can be achieved at CT-guidance, by selection of low HU and low Dev lesions. A prediction tool is provided to increase the success rate of bone biopsies in mCRPC patients, which can easily be implemented in daily practice.
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Affiliation(s)
- Minke Smits
- Department of Medical Oncology, Radboud University Medical Center Nijmegen, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands; (K.E.); (S.P.N.); (W.R.G.); (N.M.)
- Correspondence: ; Tel.: +31-24-3618800
| | - Kamer Ekici
- Department of Medical Oncology, Radboud University Medical Center Nijmegen, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands; (K.E.); (S.P.N.); (W.R.G.); (N.M.)
| | - Samhita Pamidimarri Naga
- Department of Medical Oncology, Radboud University Medical Center Nijmegen, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands; (K.E.); (S.P.N.); (W.R.G.); (N.M.)
| | - Inge M. van Oort
- Department of Urology, Radboud University Medical Center Nijmegen, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands; (I.M.v.O.); (M.J.P.S.); (J.A.S.)
| | - Michiel J. P. Sedelaar
- Department of Urology, Radboud University Medical Center Nijmegen, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands; (I.M.v.O.); (M.J.P.S.); (J.A.S.)
| | - Jack A. Schalken
- Department of Urology, Radboud University Medical Center Nijmegen, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands; (I.M.v.O.); (M.J.P.S.); (J.A.S.)
| | - James Nagarajah
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center Nijmegen, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands; (J.N.); (T.W.J.S.); (J.J.F.)
- Department of Nuclear Medicine, Technical University, Arcisstraße 21, 80333 Munich, Germany
| | - Tom W. J. Scheenen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center Nijmegen, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands; (J.N.); (T.W.J.S.); (J.J.F.)
| | - Winald R. Gerritsen
- Department of Medical Oncology, Radboud University Medical Center Nijmegen, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands; (K.E.); (S.P.N.); (W.R.G.); (N.M.)
| | - Jurgen J. Fütterer
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center Nijmegen, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands; (J.N.); (T.W.J.S.); (J.J.F.)
| | - Niven Mehra
- Department of Medical Oncology, Radboud University Medical Center Nijmegen, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands; (K.E.); (S.P.N.); (W.R.G.); (N.M.)
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de Gouw DJJM, Maas MC, Slagt C, Mühling J, Nakamoto A, Klarenbeek BR, Rosman C, Hermans JJ, Scheenen TWJ. Controlled mechanical ventilation to detect regional lymph node metastases in esophageal cancer using USPIO-enhanced MRI; comparison of image quality. Magn Reson Imaging 2020; 74:258-265. [PMID: 32976957 DOI: 10.1016/j.mri.2020.09.020] [Citation(s) in RCA: 4] [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: 05/15/2020] [Revised: 09/08/2020] [Accepted: 09/20/2020] [Indexed: 12/19/2022]
Abstract
BACKGROUND Artifacts caused by respiratory motion or ventilation-induced chest movements are a major problem for thoracic MRI, as they can obscure important anatomical structures such as lymph node metastases. We compared image quality of routine breathhold with intermittent apnea during controlled mechanical ventilation of patients under general anesthesia as the ideal situation without respiratory motion in the detection and characterization of regional lymph nodes in esophageal cancer. METHODS In this prospective study, 10 patients treated for esophageal cancer underwent ultrasmall superparamagnetic iron oxide (USPIO) enhanced MRI scans. Before neoadjuvant therapy, MRI scans were acquired with a routine breathhold technique. After neoadjuvant therapy, patients were scanned under general anesthesia immediately prior to surgery with controlled mechanical ventilation. The image quality was compared using a Likert scale questionnaire based on visibility of anatomical structures and image artifacts. RESULTS MRI with controlled mechanical ventilation and prolonged controlled apnea of 4 min was safe and feasible. All cardio-respiratory monitoring parameters remained stable during the apnea phases. Mediastinal and upper abdominal lymph nodes down to 2 mm in size could be visualized with all sequences. All image quality criteria, including visibility of thoracic structures and regional lymph nodes were scored higher using the controlled ventilation sequences compared to the routine breathhold phase. CONCLUSION USPIO-enhanced MRI with controlled mechanical ventilation is superior to routine breathhold MRI in visualizing lymph nodes, which warrants new motion reduction techniques to use MRI for the detection of lymph node metastases in patients with esophageal cancer.
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Affiliation(s)
- D J J M de Gouw
- Radboud University Medical Center, Department of Surgery, Nijmegen, the Netherlands.
| | - M C Maas
- Radboud University Medical Center, Department of Medical Imaging, Nijmegen, the Netherlands.
| | - C Slagt
- Radboud University Medical Center, Department of Anesthesiology, Pain and Palliative Medicine, Nijmegen, the Netherlands.
| | - J Mühling
- Radboud University Medical Center, Department of Anesthesiology, Pain and Palliative Medicine, Nijmegen, the Netherlands.
| | - A Nakamoto
- Osaka University Graduate School of Medicine, Department of Radiology, Suita, Japan.
| | - B R Klarenbeek
- Radboud University Medical Center, Department of Surgery, Nijmegen, the Netherlands.
| | - C Rosman
- Radboud University Medical Center, Department of Surgery, Nijmegen, the Netherlands.
| | - J J Hermans
- Radboud University Medical Center, Department of Medical Imaging, Nijmegen, the Netherlands.
| | - T W J Scheenen
- Radboud University Medical Center, Department of Medical Imaging, Nijmegen, the Netherlands.
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Privé BM, Janssen MJR, van Oort IM, Muselaers CHJ, Jonker MA, de Groot M, Mehra N, Verzijlbergen JF, Scheenen TWJ, Zámecnik P, Barentsz JO, Gotthardt M, Noordzij W, Vogel WV, Bergman AM, van der Poel HG, Vis AN, Oprea-Lager DE, Gerritsen WR, Witjes JA, Nagarajah J. Lutetium-177-PSMA-I&T as metastases directed therapy in oligometastatic hormone sensitive prostate cancer, a randomized controlled trial. BMC Cancer 2020; 20:884. [PMID: 32928177 PMCID: PMC7490874 DOI: 10.1186/s12885-020-07386-z] [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: 08/15/2020] [Accepted: 09/07/2020] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND In recent years, there is increasing evidence showing a beneficial outcome (e.g. progression free survival; PFS) after metastases-directed therapy (MDT) with external beam radiotherapy (EBRT) or targeted surgery for oligometastatic hormone sensitive prostate cancer (oHSPC). However, many patients do not qualify for these treatments due to prior interventions or tumor location. Such oligometastatic patients could benefit from radioligand therapy (RLT) with 177Lu-PSMA; a novel tumor targeting therapy for end-stage metastatic castration-resistant prostate cancer (mCRPC). Especially because RLT could be more effective in low volume disease, such as the oligometastatic status, due to high uptake of radioligands in smaller lesions. To test the hypothesis that 177Lu-PSMA is an effective treatment in oHSPC to prolong PFS and postpone the need for androgen deprivation therapy (ADT), we initiated a multicenter randomized clinical trial. This is globally, the first prospective study using 177Lu-PSMA-I&T in a randomized multicenter setting. METHODS & DESIGN This study compares 177Lu-PSMA-I&T MDT to the current standard of care (SOC); deferred ADT. Fifty-eight patients with oHSPC (≤5 metastases on PSMA PET) and high PSMA uptake (SUVmax > 15, partial volume corrected) on 18F-PSMA PET after prior surgery and/or EBRT and a PSA doubling time of < 6 months, will be randomized in a 1:1 ratio. The patients randomized to the interventional arm will be eligible for two cycles of 7.4GBq 177Lu-PSMA-I&T at a 6-week interval. After both cycles, patients are monitored every 3 weeks (including adverse events, QoL- and xerostomia questionnaires and laboratory testing) at the outpatient clinic. Twenty-four weeks after cycle two an end of study evaluation is planned together with another 18F-PSMA PET and (whole body) MRI. Patients in the SOC arm are eligible to receive 177Lu-PSMA-I&T after meeting the primary study objective, which is the fraction of patients who show disease progression during the study follow up. A second primary objective is the time to disease progression. Disease progression is defined as a 100% increase in PSA from baseline or clinical progression. DISCUSSION This is the first prospective randomized clinical study assessing the therapeutic efficacy and toxicity of 177Lu-PSMA-I&T for patients with oHSPC. TRIAL REGISTRATION Clinicaltrials.gov identifier: NCT04443062 .
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Affiliation(s)
- Bastiaan M Privé
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
| | - Marcel J R Janssen
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
| | - Inge M van Oort
- Department of Urology, Radboudumc, Nijmegen, The Netherlands
| | | | - Marianne A Jonker
- Department of Health Evidence, Radboudumc, Nijmegen, The Netherlands
| | - Michel de Groot
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
| | - Niven Mehra
- Department of Medical Oncology, Radboudumc, Nijmegen, The Netherlands
| | - J Fred Verzijlbergen
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
| | - Patrik Zámecnik
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
| | - Jelle O Barentsz
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
| | - Martin Gotthardt
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands
| | - Walter Noordzij
- Department of Radiology and Nuclear Medicine, University Medical Center Groningen, Groningen, The Netherlands
| | - Wouter V Vogel
- Department of Radiology and Nuclear Medicine, NKI Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
- Department of Radiation Oncology, NKI Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Andries M Bergman
- Department of Medical Oncology, NKI Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Henk G van der Poel
- Department of Urology, NKI Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - André N Vis
- Department of Urology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Daniela E Oprea-Lager
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | | | - J Alfred Witjes
- Department of Urology, Radboudumc, Nijmegen, The Netherlands
| | - James Nagarajah
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein Zuid 10, 6525, GA, Nijmegen, The Netherlands.
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Fortuin AS, Philips BWJ, van der Leest MMG, Ladd ME, Orzada S, Maas MC, Scheenen TWJ. Magnetic resonance imaging at ultra-high magnetic field strength: An in vivo assessment of number, size and distribution of pelvic lymph nodes. PLoS One 2020; 15:e0236884. [PMID: 32735614 PMCID: PMC7394386 DOI: 10.1371/journal.pone.0236884] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [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: 03/25/2020] [Accepted: 07/15/2020] [Indexed: 01/17/2023] Open
Abstract
Objective The definition of an in vivo nodal anatomical baseline is crucial for validation of representative lymph node dissections and accompanying pathology reports of pelvic cancers, as well as for assessing a potential therapeutic effect of extended lymph node dissections. Therefore the number, size and distribution of lymph nodes in the pelvis were assessed with high-resolution, large field-of-view, 7 Tesla (T) magnetic resonance imaging (MRI) with frequency-selective excitation. Materials and methods We used 7 T MRI for homogeneous pelvic imaging in 11 young healthy volunteers. Frequency-selective imaging of water and lipids was performed to detect nodal structures in the pelvis. Number and size of detected nodes was measured and size distribution per region was assessed. An average volunteer-normalized nodal size distribution was determined. Results In total, 564 lymph nodes were detected in six pelvic regions. Mean number was 51.3 with a wide range of 19–91 lymph nodes per volunteer. Mean diameter was 2.3 mm with a range of 1 to 7 mm. 69% Was 2 mm or smaller. The overall size distribution was very similar to the average volunteer-normalized nodal size distribution. Conclusions The amount of in vivo visible lymph nodes varies largely between subjects, whereas the normalized size distribution of nodes does not. The presence of many small lymph nodes (≤2mm) renders representative or complete removal of pelvic lymph nodes to be very difficult. 7T MRI may shift the in vivo detection limits of lymph node metastases in the future.
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Affiliation(s)
- Ansje S. Fortuin
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Radiology, Ziekenhuis Gelderse Vallei, Ede, The Netherlands
| | - Bart W. J. Philips
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Mark E. Ladd
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Physics and Astronomy and Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, Essen, Germany
| | - Stephan Orzada
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, Essen, Germany
| | - Marnix C. Maas
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Tom W. J. Scheenen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, Essen, Germany
- * E-mail:
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Öz G, Deelchand DK, Wijnen JP, Mlynárik V, Xin L, Mekle R, Noeske R, Scheenen TWJ, Tkáč I. Advanced single voxel 1 H magnetic resonance spectroscopy techniques in humans: Experts' consensus recommendations. NMR Biomed 2020; 34:e4236. [PMID: 31922301 PMCID: PMC7347431 DOI: 10.1002/nbm.4236] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Revised: 10/29/2019] [Accepted: 11/07/2019] [Indexed: 05/06/2023]
Abstract
Conventional proton MRS has been successfully utilized to noninvasively assess tissue biochemistry in conditions that result in large changes in metabolite levels. For more challenging applications, namely, in conditions which result in subtle metabolite changes, the limitations of vendor-provided MRS protocols are increasingly recognized, especially when used at high fields (≥3 T) where chemical shift displacement errors, B0 and B1 inhomogeneities and limitations in the transmit B1 field become prominent. To overcome the limitations of conventional MRS protocols at 3 and 7 T, the use of advanced MRS methodology, including pulse sequences and adjustment procedures, is recommended. Specifically, the semiadiabatic LASER sequence is recommended when TE values of 25-30 ms are acceptable, and the semiadiabatic SPECIAL sequence is suggested as an alternative when shorter TE values are critical. The magnetic field B0 homogeneity should be optimized and RF pulses should be calibrated for each voxel. Unsuppressed water signal should be acquired for eddy current correction and preferably also for metabolite quantification. Metabolite and water data should be saved in single shots to facilitate phase and frequency alignment and to exclude motion-corrupted shots. Final averaged spectra should be evaluated for SNR, linewidth, water suppression efficiency and the presence of unwanted coherences. Spectra that do not fit predefined quality criteria should be excluded from further analysis. Commercially available tools to acquire all data in consistent anatomical locations are recommended for voxel prescriptions, in particular in longitudinal studies. To enable the larger MRS community to take advantage of these advanced methods, a list of resources for these advanced protocols on the major clinical platforms is provided. Finally, a set of recommendations are provided for vendors to enable development of advanced MRS on standard platforms, including implementation of advanced localization sequences, tools for quality assurance on the scanner, and tools for prospective volume tracking and dynamic linear shim corrections.
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Affiliation(s)
- Gülin Öz
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Dinesh K. Deelchand
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Jannie P. Wijnen
- High field MR Research group, Department of Radiology, University Medical Centre Utrecht, Utrecht, the Netherlands
| | - Vladimír Mlynárik
- High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Lijing Xin
- Animal Imaging and Technology Core (AIT), Center for Biomedical Imaging (CIBM), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Ralf Mekle
- Center for Stroke Research Berlin (CSB), Charité Universitätsmedizin Berlin, Berlin, Germany
| | | | - Tom W. J. Scheenen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
- Erwin L Hahn Institute for Magnetic Resonance Imaging, UNESCO World Cultural Heritage Zollverein, Essen, Germany
| | - Ivan Tkáč
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
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van Nuland AJM, den Ouden HEM, Zach H, Dirkx MFM, van Asten JJA, Scheenen TWJ, Toni I, Cools R, Helmich RC. GABAergic changes in the thalamocortical circuit in Parkinson's disease. Hum Brain Mapp 2019; 41:1017-1029. [PMID: 31721369 PMCID: PMC7267977 DOI: 10.1002/hbm.24857] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [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: 03/28/2019] [Revised: 08/31/2019] [Accepted: 10/22/2019] [Indexed: 12/29/2022] Open
Abstract
Parkinson's disease is characterized by bradykinesia, rigidity, and tremor. These symptoms have been related to an increased gamma‐aminobutyric acid (GABA)ergic inhibitory drive from globus pallidus onto the thalamus. However, in vivo empirical evidence for the role of GABA in Parkinson's disease is limited. Some discrepancies in the literature may be explained by the presence or absence of tremor. Specifically, recent functional magnetic resonance imaging (fMRI) findings suggest that Parkinson's tremor is associated with reduced, dopamine‐dependent thalamic inhibition. Here, we tested the hypothesis that GABA in the thalamocortical motor circuit is increased in Parkinson's disease, and we explored differences between clinical phenotypes. We included 60 Parkinson patients with dopamine‐resistant tremor (n = 17), dopamine‐responsive tremor (n = 23), or no tremor (n = 20), and healthy controls (n = 22). Using magnetic resonance spectroscopy, we measured GABA‐to‐total‐creatine ratio in motor cortex, thalamus, and a control region (visual cortex) on two separate days (ON and OFF dopaminergic medication). GABA levels were unaltered by Parkinson's disease, clinical phenotype, or medication. However, motor cortex GABA levels were inversely correlated with disease severity, particularly rigidity and tremor, both ON and OFF medication. We conclude that cortical GABA plays a beneficial rather than a detrimental role in Parkinson's disease, and that GABA depletion may contribute to increased motor symptom expression.
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Affiliation(s)
- Annelies J M van Nuland
- Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands
| | - Hanneke E M den Ouden
- Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands
| | - Heidemarie Zach
- Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Nijmegen, The Netherlands.,Medical University of Vienna, Department of Neurology, Vienna, Austria
| | - Michiel F M Dirkx
- Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Nijmegen, The Netherlands
| | - Jack J A van Asten
- Radboud University Medical Centre, Department of Radiology and Nuclear Medicine, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Radboud University Medical Centre, Department of Radiology and Nuclear Medicine, Nijmegen, The Netherlands
| | - Ivan Toni
- Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands
| | - Roshan Cools
- Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands
| | - Rick C Helmich
- Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands.,Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Nijmegen, The Netherlands
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31
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van Steenbergen TRF, Smits M, Scheenen TWJ, van Oort IM, Nagarajah J, Rovers MM, Mehra N, Fütterer JJ. 68Ga-PSMA-PET/CT and Diffusion MRI Targeting for Cone-Beam CT-Guided Bone Biopsies of Castration-Resistant Prostate Cancer Patients. Cardiovasc Intervent Radiol 2019; 43:147-154. [PMID: 31444628 PMCID: PMC6940314 DOI: 10.1007/s00270-019-02312-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 08/13/2019] [Indexed: 12/19/2022]
Abstract
Introduction Precision medicine expands the treatment options for metastatic castration-resistant prostate cancer (mCRPC) by targeting druggable genetic aberrations. Aberrations can be identified following molecular analysis of metastatic tissue. Bone metastases, commonly present in mCRPC, hinder precision medicine due to a high proportion of biopsies with insufficient tumor cells for next-generation DNA sequencing. We aimed to investigate the feasibility of incorporating advanced target planning and needle guidance in bone biopsies and whether this procedure increases biopsy tumor yield and success rate of molecular analysis as compared to the current standards, utilizing only CT guidance. Materials and Methods In a pilot study, ten mCRPC patients received 68Ga-prostate-specific membrane antigen (PSMA)-PET/CT and diffusion-weighted MRI as biopsy planning images. These datasets were fused for targeting metastatic lesions with high tumor densities. Biopsies were performed under cone-beam CT (CBCT) guidance. Feasibility of target planning and needle guidance was assessed, and success of molecular analysis and tumor yield were reported. Results Fusion target planning and CBCT needle guidance were feasible. Nine out of ten biopsies contained prostate cancer cells, with a median of 39% and 40% tumor cells by two different sequencing techniques. Molecular analysis was successful in eight of ten patients (80%). This exceeds previous reports on CT-guided biopsies that ranged from 33 to 44%. In two patients, important druggable aberrations were found. Discussion A biopsy procedure using advanced target planning and needle guidance is feasible and can increase the success rate of molecular analysis in bone metastases, thereby having the potential of improving treatment outcome for patients with mCRPC. Level of Evidence Level 4, case series.
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Affiliation(s)
- T R F van Steenbergen
- Department of Radiology and Nuclear Medicine, Radboud Institute for Health Sciences, Radboud University Medical Center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands.
| | - M Smits
- Department of Medical Oncology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - T W J Scheenen
- Department of Radiology and Nuclear Medicine, Radboud Institute for Health Sciences, Radboud University Medical Center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands
| | - I M van Oort
- Department of Urology, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - J Nagarajah
- Department of Radiology and Nuclear Medicine, Radboud Institute for Health Sciences, Radboud University Medical Center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands
| | - M M Rovers
- Department of Operating Rooms, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - N Mehra
- Department of Medical Oncology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - J J Fütterer
- Department of Radiology and Nuclear Medicine, Radboud Institute for Health Sciences, Radboud University Medical Center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands
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Wilson M, Andronesi O, Barker PB, Bartha R, Bizzi A, Bolan PJ, Brindle KM, Choi IY, Cudalbu C, Dydak U, Emir UE, Gonzalez RG, Gruber S, Gruetter R, Gupta RK, Heerschap A, Henning A, Hetherington HP, Huppi PS, Hurd RE, Kantarci K, Kauppinen RA, Klomp DWJ, Kreis R, Kruiskamp MJ, Leach MO, Lin AP, Luijten PR, Marjańska M, Maudsley AA, Meyerhoff DJ, Mountford CE, Mullins PG, Murdoch JB, Nelson SJ, Noeske R, Öz G, Pan JW, Peet AC, Poptani H, Posse S, Ratai EM, Salibi N, Scheenen TWJ, Smith ICP, Soher BJ, Tkáč I, Vigneron DB, Howe FA. Methodological consensus on clinical proton MRS of the brain: Review and recommendations. Magn Reson Med 2019; 82:527-550. [PMID: 30919510 PMCID: PMC7179569 DOI: 10.1002/mrm.27742] [Citation(s) in RCA: 226] [Impact Index Per Article: 45.2] [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: 09/28/2018] [Revised: 02/01/2019] [Accepted: 02/25/2019] [Indexed: 12/14/2022]
Abstract
Proton MRS (1 H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good-quality results have been identified as a contributing factor. Considerable progress has been made by the research community to address many of these challenges, and in this paper a consensus is presented on deficiencies in widely available MRS methodology and validated improvements that are currently in routine use at several clinical research institutions. In particular, the localization error for the PRESS localization sequence was found to be unacceptably high at 3 T, and use of the semi-adiabatic localization by adiabatic selective refocusing sequence is a recommended solution. Incorporation of simulated metabolite basis sets into analysis routines is recommended for reliably capturing the full spectral detail available from short TE acquisitions. In addition, the importance of achieving a highly homogenous static magnetic field (B0 ) in the acquisition region is emphasized, and the limitations of current methods and hardware are discussed. Most recommendations require only software improvements, greatly enhancing the capabilities of clinical MRS on existing hardware. Implementation of these recommendations should strengthen current clinical applications and advance progress toward developing and validating new MRS biomarkers for clinical use.
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Affiliation(s)
- Martin Wilson
- Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, England
| | - Ovidiu Andronesi
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Peter B Barker
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Robert Bartha
- Robarts Research Institute, University of Western Ontario, London, Canada
| | - Alberto Bizzi
- U.O. Neuroradiologia, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy
| | - Patrick J Bolan
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota
| | - Kevin M Brindle
- Department of Biochemistry, University of Cambridge, Cambridge, England
| | - In-Young Choi
- Department of Neurology, Hoglund Brain Imaging Center, University of Kansas Medical Center, Kansas City, Kansas
| | - Cristina Cudalbu
- Center for Biomedical Imaging, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| | - Ulrike Dydak
- School of Health Sciences, Purdue University, West Lafayette, Indiana
| | - Uzay E Emir
- School of Health Sciences, Purdue University, West Lafayette, Indiana
| | - Ramon G Gonzalez
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Stephan Gruber
- High Field MR Center, Department of Biomedical imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Rolf Gruetter
- Laboratory for Functional and Metabolic Imaging, Center for Biomedical Imaging, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| | - Rakesh K Gupta
- Fortis Memorial Research Institute, Gurugram, Haryana, India
| | - Arend Heerschap
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Anke Henning
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
| | | | - Petra S Huppi
- Department of Pediatrics, University of Geneva, Geneva, Switzerland
| | - Ralph E Hurd
- Stanford Radiological Sciences Lab, Stanford, California
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | - Risto A Kauppinen
- School of Psychological Science, University of Bristol, Bristol, England
| | | | - Roland Kreis
- Departments of Radiology and Biomedical Research, University of Bern, Bern, Switzerland
| | | | - Martin O Leach
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden Hospital, London, England
| | - Alexander P Lin
- Center for Clinical Spectroscopy, Brigham and Women's Hospital, Harvard University Medical School, Boston, Massachusetts
| | | | - Małgorzata Marjańska
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota
| | | | - Dieter J Meyerhoff
- DVA Medical Center and Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | | | - Paul G Mullins
- Bangor Imaging Unit, School of Psychology, Bangor University, Bangor, Wales
| | | | - Sarah J Nelson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | | | - Gülin Öz
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota
| | - Julie W Pan
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Andrew C Peet
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, England
| | - Harish Poptani
- Centre for Preclinical Imaging, Institute of Translational Medicine, University of Liverpool, Liverpool, England
| | - Stefan Posse
- Department of Neurology, University of New Mexico, Albuquerque, New Mexico
| | - Eva-Maria Ratai
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Nouha Salibi
- MR R&D, Siemens Healthineers, Malvern, Pennsylvania
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | | | - Brian J Soher
- Department of Radiology, Duke University Medical Center, Durham, North Carolina
| | - Ivan Tkáč
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Franklyn A Howe
- Molecular and Clinical Sciences, St George's University of London, London, England
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Philips BWJ, van Uden MJ, Rietsch SHG, Orzada S, Scheenen TWJ. A multitransmit external body array combined with a 1 H and 31 P endorectal coil to enable a multiparametric and multimetabolic MRI examination of the prostate at 7T. Med Phys 2019; 46:3893-3905. [PMID: 31274201 PMCID: PMC6852321 DOI: 10.1002/mp.13696] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [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: 01/23/2019] [Revised: 05/15/2019] [Accepted: 06/21/2019] [Indexed: 12/15/2022] Open
Abstract
Purpose In vivo1H and 31P magnetic resonance spectroscopic imaging (MRSI) provide complementary information on the biology of prostate cancer. In this work we demonstrate the feasibility of performing multiparametric imaging (mpMRI) and 1H and 31P spectroscopic imaging of the prostate using a 31P and 1H endorectal radiofrequency coil (ERC) in combination with a multitransmit body array at 7 Tesla (T). Methods An ERC with a 31P transceiver loop coil and 1H receive (Rx) asymmetric microstrip (31P/1H ERC) was designed, constructed and tested in combination with an external 8‐channel 1H transceiver body array coil (8CH). Electromagnetic field simulations and measurements and in vivo temperature measurements of the ERC were performed for safety validation. In addition, the signal‐to‐noise (SNR) benefit of the 1H microstrip with respect to the 8CH was evaluated. Finally, the feasibility of the setup was tested in one volunteer and three patients with prostate cancer by performing T2‐weighted and diffusion‐weighted imaging in combination with 1H and 31P spectroscopic imaging. Results Electromagnetic field simulations of the 31P loop coil showed no differences in the E‐ and B‐fields of the 31P/1H ERC compared with a previously safety validated ERC without 1H microstrip. The hotspot of the specific absorption rate (SAR) at the feed point of the 31P/1H ERC loop coil was 9.42 W/kg when transmitting on 31P at 1 W. Additional in vivo measurements showed a maximum temperature increase at the SAR hotspot of 0.7°C over 6 min on 31P at 1.9 W transmit (Tx) power, indicating safe maximum power levels. When transmitting with the external 1H body array at 40W for 2:30 min, the temperature increase around the ERC was < 0.3°C. Up to 3.5 cm into the prostate the 1H microstrip of the ERC provided higher SNR than the 8CH. The total coil combination allowed acquisition of an mpMRI protocol and the assessment of 31P and 1H metabolites of the prostate in all test subjects. Conclusion We developed a setup with a 31P transceiver and 1H Rx endorectal coil in combination with an 8‐channel transceiver external body array coil and demonstrated its safety and feasibility for obtaining multiparametric imaging and 1H and 31P MRSI at 7T in patients with prostate cancer within one MR examination.
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Affiliation(s)
- Bart W J Philips
- Department of Radiology and Nuclear Medicine (766), Radboud university medical center, P.O. Box 9101, Nijmegen, The Netherlands
| | - Mark J van Uden
- Department of Radiology and Nuclear Medicine (766), Radboud university medical center, P.O. Box 9101, Nijmegen, The Netherlands
| | - Stefan H G Rietsch
- Erwin L Hahn Institute for Magnetic Resonance Imaging, UNESCO World Cultural, Heritage Zollverein, Kokereiallee 7, Building C84, D-45141, Essen, Germany.,High Field and Hybrid MR Imaging, University Hospital Essen, D-45147, Essen, Germany
| | - Stephan Orzada
- Erwin L Hahn Institute for Magnetic Resonance Imaging, UNESCO World Cultural, Heritage Zollverein, Kokereiallee 7, Building C84, D-45141, Essen, Germany
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine (766), Radboud university medical center, P.O. Box 9101, Nijmegen, The Netherlands.,Erwin L Hahn Institute for Magnetic Resonance Imaging, UNESCO World Cultural, Heritage Zollverein, Kokereiallee 7, Building C84, D-45141, Essen, Germany
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Philips BWJ, Stijns RCH, Rietsch SHG, Brunheim S, Barentsz JO, Fortuin AS, Quick HH, Orzada S, Maas MC, Scheenen TWJ. USPIO-enhanced MRI of pelvic lymph nodes at 7-T: preliminary experience. Eur Radiol 2019; 29:6529-6538. [PMID: 31201525 PMCID: PMC6828641 DOI: 10.1007/s00330-019-06277-7] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [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: 07/05/2018] [Revised: 04/16/2019] [Accepted: 05/17/2019] [Indexed: 02/06/2023]
Abstract
Purpose To evaluate the technical feasibility of high-resolution USPIO-enhanced magnetic resonance imaging of pelvic lymph nodes (LNs) at ultrahigh magnetic field strength. Materials and methods The ethics review board approved this study and written informed consent was obtained from all patients. Three patients with rectal cancer and three selected patients with (recurrent) prostate cancer were examined at 7-T 24–36 h after intravenous ferumoxtran-10 administration; rectal cancer patients also received a 3-T MRI. Pelvic LN imaging was performed using the TIAMO technique in combination with water-selective multi-GRE imaging and lipid-selective GRE imaging with a spatial resolution of 0.66 × 0.66 × 0.66mm3. T2*-weighted images of the water-selective imaging were computed from the multi-GRE images at TE = 0, 8, and 14 ms and used for the assessment of USPIO uptake. Results High-resolution 7-T MR gradient-echo imaging was obtained robustly in all patients without suffering from RF-related signal voids. USPIO signal decay in LNs was visualized using computed TE imaging at TE = 8 ms and an R2* map derived from water-selective imaging. Anatomically, LNs were identified on a combined reading of computed TE = 0 ms images from water-selective scans and images from lipid-selective scans. A range of 3–48 LNs without USPIO signal decay was found per patient. These LNs showed high signal intensity on computed TE = 8 and 14 ms imaging and low R2* (corresponding to high T2*) values on the R2* map. Conclusion USPIO-enhanced MRI of the pelvis at 7-T is technically feasible and offers opportunities for detecting USPIO uptake in normal-sized LNs, due to its high intrinsic signal-to-noise ratio and spatial resolution. Key Points • USPIO-enhanced MRI at 7-T can indicate USPIO uptake in lymph nodes based on computed TE images. • Our method promises a high spatial resolution for pelvic lymph node imaging.
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Affiliation(s)
- Bart W J Philips
- Department of Radiology and Nuclear Medicine (766), Radboud University Medical Center, P.O. Box 9101, Nijmegen, The Netherlands.
| | - Rutger C H Stijns
- Department of Radiology and Nuclear Medicine (766), Radboud University Medical Center, P.O. Box 9101, Nijmegen, The Netherlands
| | - Stefan H G Rietsch
- Erwin L Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, 45141, Essen, Germany.,High-Field and Hybrid MR Imaging, University Hospital Essen, 45147, Essen, Germany
| | - Sascha Brunheim
- Erwin L Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, 45141, Essen, Germany.,High-Field and Hybrid MR Imaging, University Hospital Essen, 45147, Essen, Germany
| | - Jelle O Barentsz
- Department of Radiology and Nuclear Medicine (766), Radboud University Medical Center, P.O. Box 9101, Nijmegen, The Netherlands
| | - Ansje S Fortuin
- Department of Radiology and Nuclear Medicine (766), Radboud University Medical Center, P.O. Box 9101, Nijmegen, The Netherlands.,Department of Radiology, Ziekenhuis Gelderse Vallei, Ede, The Netherlands
| | - Harald H Quick
- Erwin L Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, 45141, Essen, Germany.,High-Field and Hybrid MR Imaging, University Hospital Essen, 45147, Essen, Germany
| | - Stephan Orzada
- Erwin L Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, 45141, Essen, Germany.,High-Field and Hybrid MR Imaging, University Hospital Essen, 45147, Essen, Germany
| | - Marnix C Maas
- Department of Radiology and Nuclear Medicine (766), Radboud University Medical Center, P.O. Box 9101, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine (766), Radboud University Medical Center, P.O. Box 9101, Nijmegen, The Netherlands.,Erwin L Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, 45141, Essen, Germany
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Peeters TH, Kobus T, Breukels V, Lenting K, Veltien A, Heerschap A, Scheenen TWJ. Imaging Hyperpolarized Pyruvate and Lactate after Blood-Brain Barrier Disruption with Focused Ultrasound. ACS Chem Neurosci 2019; 10:2591-2601. [PMID: 30873831 PMCID: PMC6523999 DOI: 10.1021/acschemneuro.9b00085] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [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] [Indexed: 12/12/2022] Open
Abstract
![]()
Imaging of hyperpolarized 13C-labeled substrates has
emerged as an important magnetic resonance (MR) technique to study
metabolic pathways in real time in vivo. Even though
this technique has found its way to clinical trials, in vivo dynamic nuclear polarization is still mostly applied in preclinical
models. Its tremendous increase in signal-to-noise ratio (SNR) overcomes
the intrinsically low MR sensitivity of the 13C nucleus
and allows real-time metabolic imaging in small structures like the
mouse brain. However, applications in brain research are limited as
delivery of hyperpolarized compounds is restrained by the blood–brain
barrier (BBB). A local noninvasive disruption of the BBB could facilitate
delivery of hyperpolarized substrates and create opportunities to
study metabolic pathways in the brain that are generally not within
reach. In this work, we designed a setup to apply BBB disruption in
the mouse brain by MR-guided focused ultrasound (FUS) prior to MR
imaging of 13C-enriched hyperpolarized [1-13C]-pyruvate and its conversion to [1-13C]-lactate. To
overcome partial volume issues, we optimized a fast multigradient-echo
imaging method (temporal resolution of 2.4 s) with an in-plane spatial
resolution of 1.6 × 1.6 mm2, without the need of processing
large amounts of spectroscopic data. We demonstrated the feasibility
to apply 13C imaging in less than 1 h after FUS treatment
and showed a locally disrupted BBB during the time window of the whole
experiment. From detected hyperpolarized pyruvate and lactate signals
in both FUS-treated and untreated mice, we conclude that even at high
spatial resolution, signals from the blood compartment dominate in
the 13C images, leaving the interpretation of hyperpolarized
signals in the mouse brain challenging.
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Affiliation(s)
- Tom H. Peeters
- Department of Radiology and Nuclear Medicine, Radboud university medical center, Nijmegen, The Netherlands
| | - Thiele Kobus
- Department of Radiology and Nuclear Medicine, Radboud university medical center, Nijmegen, The Netherlands
| | - Vincent Breukels
- Department of Radiology and Nuclear Medicine, Radboud university medical center, Nijmegen, The Netherlands
| | - Krissie Lenting
- Department of Biochemistry, Radboud Institute for Molecular Life Sciences, Nijmegen, The Netherlands
| | - Andor Veltien
- Department of Radiology and Nuclear Medicine, Radboud university medical center, Nijmegen, The Netherlands
| | - Arend Heerschap
- Department of Radiology and Nuclear Medicine, Radboud university medical center, Nijmegen, The Netherlands
| | - Tom W. J. Scheenen
- Department of Radiology and Nuclear Medicine, Radboud university medical center, Nijmegen, The Netherlands
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van Uden MJ, Peeters TH, Rijpma A, Rodgers CT, Heerschap A, Scheenen TWJ. An 8-channel receive array for improved 31 P MRSI of the whole brain at 3T. Magn Reson Med 2019; 82:825-832. [PMID: 30900352 PMCID: PMC6520216 DOI: 10.1002/mrm.27736] [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: 09/14/2018] [Revised: 02/21/2019] [Accepted: 02/21/2019] [Indexed: 12/26/2022]
Abstract
PURPOSE To demonstrate a 1 H/31 P whole human brain volume coil configuration for 3 Tesla with separate 31 P transmit and receive components that maintains 1 H MRS performance and delivers optimal 31 P MRSI with 1 H decoupling. METHODS We developed an 8-channel 31 P receive array coil covering the head to be used as an insert for a commercial double-tuned 1 H/31 P birdcage transmit-receive coil. This retains the possibility of using low-power rectangular pulses for 1 H-decoupled 3D 31 P MRSI (nominal resolution 17.6 cm3 ; acquisition duration 13 min) but increases the SNR with the receive sensitivity of 31 P surface coils. The performance of the combined coil setup was evaluated by measuring 1 H and 31 P SNR with and without the 31 P receive array and by assessing the effect of the receive array on the transmit efficiencies of the birdcage coil. RESULTS Compared to the birdcage coil alone, the 31 P insert in combination with the birdcage achieved an average 31 P SNR gain of 1.4 ± 0.4 in a center partition of the brain. The insert did not cause losses in 1 H MRS performance and transmit efficiency, whereas for 31 P approximately 20% more power was needed to achieve the same γB1. CONCLUSION The new coil configuration allows 1 H MRSI and optimal 1 H-decoupled 3D 31 P MRSI, with increased SNR of the human brain without patient repositioning, for clinical and research purposes at 3 Tesla.
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Affiliation(s)
- Mark J van Uden
- Department of Radiology and Nuclear Medicine, Radboud university medical center, Nijmegen, The Netherlands
| | - Tom H Peeters
- Department of Radiology and Nuclear Medicine, Radboud university medical center, Nijmegen, The Netherlands
| | - Anne Rijpma
- Department of Geriatric Medicine, Radboud university medical center, Nijmegen, The Netherlands.,Radboudumc Alzheimer Center, Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, The Netherlands
| | | | - Arend Heerschap
- Department of Radiology and Nuclear Medicine, Radboud university medical center, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine, Radboud university medical center, Nijmegen, The Netherlands.,Erwin L. Hahn Institute, University Hospital Duisburg-Essen, Essen, Germany
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Tayari N, Obels J, Kobus T, Scheenen TWJ, Heerschap A. Simple and broadly applicable automatic quality control for 3D 1 H MR spectroscopic imaging data of the prostate. Magn Reson Med 2018; 81:2887-2895. [PMID: 30506721 DOI: 10.1002/mrm.27616] [Citation(s) in RCA: 4] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2018] [Revised: 10/13/2018] [Accepted: 10/31/2018] [Indexed: 12/17/2022]
Abstract
PURPOSE Quality control (QC) is a prerequisite for clinical MR spectroscopic imaging (MRSI) to avoid that bad spectra hamper data interpretation. The aim of this work was to present a simple automatic QC for prostate 1 H MRSI that can handle data obtained with different commonly used pulse sequences, echo times, field strengths, and MR platforms. METHODS A QC method was developed with a ratio (Qratio) where the numerator and the denominator are functions of several signal heights, logically combined for their positive or negative contribution to spectral quality. This Qratio was tested on 4 data sets obtained at 1.5, 3, and 7T, with and without endorectal coil and different localization sequences and echo times. Spectra of 25,248 voxels in 26 prostates were labeled as acceptable or unacceptable by MRS experts as gold standard. A threshold value was determined for Qratio from a subset of voxels, labeled in consensus by 4 experts, for an optimal accuracy to separate spectra. RESULTS Applying this Qratio threshold to the remaining test voxels, an automatic separation of good and bad spectra was possible with an accuracy of 0.88, similar to manual separation between the 2 classes. Qratio values were used to generate maps representing spectral quality on a binary or continuous scale. CONCLUSION Automated QC of prostate 1 H MRSI by Qratio is fast, simple, easily transferable and more practical than supervised feature extraction methods and therefore easy to integrate into different clinical MR systems. Moreover, quality maps can be generated to read the reliability of spectra in each voxel.
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Affiliation(s)
- Nassim Tayari
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jiri Obels
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Thiele Kobus
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Arend Heerschap
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
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38
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Rietsch SHG, Orzada S, Maderwald S, Brunheim S, Philips BWJ, Scheenen TWJ, Ladd ME, Quick HH. 7T ultra-high field body MR imaging with an 8-channel transmit/32-channel receive radiofrequency coil array. Med Phys 2018; 45:2978-2990. [PMID: 29679498 DOI: 10.1002/mp.12931] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [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: 10/18/2017] [Revised: 03/20/2018] [Accepted: 03/30/2018] [Indexed: 12/11/2022] Open
Abstract
PURPOSE In this work, a combined body coil array with eight transmit/receive (Tx/Rx) meander elements and with 24 receive-only (Rx) loops (8Tx/32Rx) was developed and evaluated in comparison with an 8-channel transmit/receive body array (8Tx/Rx) based on meander elements serving as the reference standard. METHODS Systematic evaluation of the RF array was performed on a body-sized phantom. Body imaging at 7T was performed in six volunteers in the body regions pelvis, abdomen, and heart. Coil characteristics such as signal-to-noise ratio, acceleration capability, g-factors, S-parameters, noise correlation, and B1+ maps were assessed. Safety was ensured by numerical simulations using a coil model validated by dosimetric field measurements. RESULTS Meander elements and loops are intrinsically well decoupled with a maximum coupling value of -20.5 dB. Safe use of the 8Tx/32Rx array could be demonstrated. High gain in signal-to-noise ratio (33% in the subject's center) could be shown for the 8Tx/32Rx array compared to the 8Tx/Rx array. Improvement in acceleration capability in all investigations could be demonstrated. For example, the 8Tx/32Rx array provides lower g-factors in the right-left and anterior-posterior directions with R = 3 undersampling as compared to the 8Tx/Rx array using R = 2. Both arrays are very similar regarding their RF transmit performance. Excellent image quality in the investigated body regions could be achieved with the 8Tx/32Rx array. CONCLUSION In this work, we show that a combination of eight meander elements and 24 loop receive elements is possible without impeding transmit performance. Improved SNR and g-factor performance compared to an RF array without these loops is demonstrated. Body MRI at 7T with the 8Tx/32Rx array could be accomplished in the heart, abdomen, and pelvis with excellent image quality.
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Affiliation(s)
- Stefan H G Rietsch
- Erwin L. Hahn Institute for MR Imaging, University of Duisburg-Essen, 45141, Essen, Germany.,High Field and Hybrid MR Imaging, University Hospital Essen, 45147, Essen, Germany
| | - Stephan Orzada
- Erwin L. Hahn Institute for MR Imaging, University of Duisburg-Essen, 45141, Essen, Germany
| | - Stefan Maderwald
- Erwin L. Hahn Institute for MR Imaging, University of Duisburg-Essen, 45141, Essen, Germany
| | - Sascha Brunheim
- Erwin L. Hahn Institute for MR Imaging, University of Duisburg-Essen, 45141, Essen, Germany.,High Field and Hybrid MR Imaging, University Hospital Essen, 45147, Essen, Germany
| | - Bart W J Philips
- Department of Radiology and Nuclear Medicine, Medical Center, Radboud University, 6525GA, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Erwin L. Hahn Institute for MR Imaging, University of Duisburg-Essen, 45141, Essen, Germany.,Department of Radiology and Nuclear Medicine, Medical Center, Radboud University, 6525GA, Nijmegen, The Netherlands
| | - Mark E Ladd
- Erwin L. Hahn Institute for MR Imaging, University of Duisburg-Essen, 45141, Essen, Germany.,Medical Physics in Radiology, German Cancer Research Center, 69120, Heidelberg, Germany.,Faculty of Physics and Astronomy and Faculty of Medicine, University of Heidelberg, 69120, Heidelberg, Germany
| | - Harald H Quick
- Erwin L. Hahn Institute for MR Imaging, University of Duisburg-Essen, 45141, Essen, Germany.,High Field and Hybrid MR Imaging, University Hospital Essen, 45147, Essen, Germany
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van Veenendaal TM, Backes WH, Tse DHY, Scheenen TWJ, Klomp DW, Hofman PAM, Rouhl RPW, Vlooswijk MCG, Aldenkamp AP, Jansen JFA. High field imaging of large-scale neurotransmitter networks: Proof of concept and initial application to epilepsy. Neuroimage Clin 2018; 19:47-55. [PMID: 30035001 PMCID: PMC6051471 DOI: 10.1016/j.nicl.2018.04.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [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: 06/13/2017] [Revised: 03/22/2018] [Accepted: 04/01/2018] [Indexed: 01/05/2023]
Abstract
The brain can be considered a network, existing of multiple interconnected areas with various functions. MRI provides opportunities to map the large-scale network organization of the brain. We tap into the neurobiochemical dimension of these networks, as neuronal functioning and signal trafficking across distributed brain regions relies on the release and presence of neurotransmitters. Using high-field MR spectroscopic imaging at 7.0 T, we obtained a non-invasive snapshot of the spatial distribution of the neurotransmitters GABA and glutamate, and investigated interregional associations of these neurotransmitters. We demonstrate that interregional correlations of glutamate and GABA concentrations can be conceptualized as networks. Furthermore, patients with epilepsy display an increased number of glutamate and GABA connections and increased average strength of the GABA network. The increased glutamate and GABA connectivity in epilepsy might indicate a disrupted neurotransmitter balance. In addition to epilepsy, the 'neurotransmitter networks' concept might also provide new insights for other neurological diseases.
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Affiliation(s)
- Tamar M van Veenendaal
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center (MUMC+), The Netherlands; School for Mental Health and Neuroscience, Maastricht University, The Netherlands
| | - Walter H Backes
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center (MUMC+), The Netherlands; School for Mental Health and Neuroscience, Maastricht University, The Netherlands
| | - Desmond H Y Tse
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center (MUMC+), The Netherlands; Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, The Netherlands
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Dennis W Klomp
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Paul A M Hofman
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center (MUMC+), The Netherlands; School for Mental Health and Neuroscience, Maastricht University, The Netherlands; Academic Center for Epileptology Kempenhaeghe/MUMC+, Heeze and Maastricht, The Netherlands
| | - Rob P W Rouhl
- School for Mental Health and Neuroscience, Maastricht University, The Netherlands; Academic Center for Epileptology Kempenhaeghe/MUMC+, Heeze and Maastricht, The Netherlands; Department of Neurology, Maastricht University Medical Center, The Netherlands
| | - Marielle C G Vlooswijk
- School for Mental Health and Neuroscience, Maastricht University, The Netherlands; Academic Center for Epileptology Kempenhaeghe/MUMC+, Heeze and Maastricht, The Netherlands; Department of Neurology, Maastricht University Medical Center, The Netherlands
| | - Albert P Aldenkamp
- School for Mental Health and Neuroscience, Maastricht University, The Netherlands; Academic Center for Epileptology Kempenhaeghe/MUMC+, Heeze and Maastricht, The Netherlands; Department of Neurology, Maastricht University Medical Center, The Netherlands
| | - Jacobus F A Jansen
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center (MUMC+), The Netherlands; School for Mental Health and Neuroscience, Maastricht University, The Netherlands.
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40
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van de Bank BL, Maas MC, Bains LJ, Heerschap A, Scheenen TWJ. Is visual activation associated with changes in cerebral high-energy phosphate levels? Brain Struct Funct 2018; 223:2721-2731. [PMID: 29572626 PMCID: PMC5995992 DOI: 10.1007/s00429-018-1656-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [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: 10/07/2017] [Accepted: 03/19/2018] [Indexed: 12/11/2022]
Abstract
Phosphorus magnetic resonance spectroscopy (31P MRS) has been employed before to assess phosphocreatine (PCr) and other high-energy phosphates in the visual cortex during visual stimulation with inconsistent results. We performed functional 31P MRS imaging in the visual cortex and control regions during a visual stimulation paradigm at an unprecedented sensitivity, exploiting a dedicated RF coil design at a 7 T MR system. Visual stimulation in a 3 min 24 s on–off paradigm in eight young healthy adults generated a clear BOLD effect with traditional 1H functional MRI in the visual cortex (average z score 9.9 ± 0.2). However, no significant event-related changes in any of the 31P metabolite concentrations, linewidths (7.9 ± 1.8 vs 7.8 ± 1.9 Hz) or tissue pH (7.07 ± 0.13 vs 7.06 ± 0.07) were detectable. Overall, our study of 31P MRSI in 15 cm3 voxels had a detection threshold for changes in PCr, Pi and γ-ATP between stimulation and rest of 5, 17 and 10%, respectively. In individual subjects, the mean coefficients of variance for PCr and Pi levels of control voxels were 6 ± 3 and 19 ± 8% (three time point average of 3 min 24 s). Altogether this indicates that energy supply for neuronal activation at this temporal resolution does not drain global PCr resources.
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Affiliation(s)
- Bart L van de Bank
- Department of Radiology and Nuclear Medicine (766), Radboud University Medical Center, Geert Grooteplein-zuid 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands
| | - Marnix C Maas
- Department of Radiology and Nuclear Medicine (766), Radboud University Medical Center, Geert Grooteplein-zuid 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands
| | - Lauren J Bains
- Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive Neuroimaging, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Arend Heerschap
- Department of Radiology and Nuclear Medicine (766), Radboud University Medical Center, Geert Grooteplein-zuid 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine (766), Radboud University Medical Center, Geert Grooteplein-zuid 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands. .,Erwin L. Hahn Institute, University Hospital Duisburg-Essen, Essen, Germany.
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41
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Bhogal AA, Schür RR, Houtepen LC, van de Bank B, Boer VO, Marsman A, Barker PB, Scheenen TWJ, Wijnen JP, Vinkers CH, Klomp DWJ. 1 H-MRS processing parameters affect metabolite quantification: The urgent need for uniform and transparent standardization. NMR Biomed 2017; 30:e3804. [PMID: 28915314 DOI: 10.1002/nbm.3804] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [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: 03/22/2017] [Revised: 08/11/2017] [Accepted: 08/14/2017] [Indexed: 06/07/2023]
Abstract
Proton magnetic resonance spectroscopy (1 H-MRS) can be used to quantify in vivo metabolite levels, such as lactate, γ-aminobutyric acid (GABA) and glutamate (Glu). However, there are considerable analysis choices which can alter the accuracy or precision of 1 H-MRS metabolite quantification. It is currently unknown to what extent variations in the analysis pipeline used to quantify 1 H-MRS data affect outcomes. The purpose of this study was to evaluate whether the quantification of identical 1 H-MRS scans across independent and experienced research groups would yield comparable results. We investigated the influence of model parameters and spectral quantification software on fitted metabolite concentration values. Sixty spectra in 30 individuals (repeated measures) were acquired using a 7-T MRI scanner. Data were processed by four independent research groups with the freedom to choose their own individualized and optimal parameter settings using LCModel software. Data were processed a second time in one group using an independent software package (NMRWizard) for an additional comparison with a different post-processing platform. Correlations across research groups of the ratio between the highest and, arguably, the most relevant resonances for neurotransmission [N-acetyl aspartate (NAA), N-acetyl aspartyl glutamate (NAAG) and Glu] over the total creatine [creatine (Cr) + phosphocreatine (PCr)] concentration, using Pearson's product-moment correlation coefficient (r), were calculated. Mean inter-group correlations using LCModel software were 0.87, 0.88 and 0.77 for NAA/Cr + PCr, NAA + NAAG/Cr + PCr and Glu/Cr + PCr, respectively. The mean correlations when comparing NMRWizard results with LCModel fitting results at University Medical Center Utrecht (UMCU) were 0.87, 0.89 and 0.71 for NAA/Cr + PCr, NAA + NAAG/Cr + PCr and Glu/Cr + PCr, respectively. Metabolite quantification using identical 1 H-MRS data was influenced by processing parameters, basis sets and software choice. Locally preferred processing choices affected metabolite quantification, even when using identical software. Our results reinforce the notion that standard practices should be established to regularize outcomes of 1 H-MRS studies, and that basis sets used for processing should be made available to the scientific community.
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Affiliation(s)
- Alex A Bhogal
- Radiology Department, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Remmelt R Schür
- Psychiatry Department, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Lotte C Houtepen
- Psychiatry Department, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Bart van de Bank
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Vincent O Boer
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Anouk Marsman
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Peter B Barker
- Department of Radiology and Radiological Science - Neuroradiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Jannie P Wijnen
- Radiology Department, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Christiaan H Vinkers
- Psychiatry Department, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Dennis W J Klomp
- Radiology Department, University Medical Center Utrecht, Utrecht, the Netherlands
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42
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Vergeldt FJ, Prusova A, Fereidouni F, Amerongen HV, Van As H, Scheenen TWJ, Bader AN. Multi-component quantitative magnetic resonance imaging by phasor representation. Sci Rep 2017; 7:861. [PMID: 28408740 PMCID: PMC5429833 DOI: 10.1038/s41598-017-00864-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2016] [Accepted: 03/20/2017] [Indexed: 12/02/2022] Open
Abstract
Quantitative magnetic resonance imaging (qMRI) is a versatile, non-destructive and non-invasive tool in life, material, and medical sciences. When multiple components contribute to the signal in a single pixel, however, it is difficult to quantify their individual contributions and characteristic parameters. Here we introduce the concept of phasor representation to qMRI to disentangle the signals from multiple components in imaging data. Plotting the phasors allowed for decomposition, unmixing, segmentation and quantification of our in vivo data from a plant stem, a human and mouse brain and a human prostate. In human brain images, we could identify 3 main T2 components and 3 apparent diffusion coefficients; in human prostate 5 main contributing spectral shapes were distinguished. The presented phasor analysis is model-free, fast and accurate. Moreover, we also show that it works for undersampled data.
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Affiliation(s)
- Frank J Vergeldt
- Laboratory of Biophysics, Wageningen University & Research, Wageningen, The Netherlands.,Wageningen NMR Centre, Wageningen University & Research, Wageningen, The Netherlands
| | - Alena Prusova
- Laboratory of Biophysics, Wageningen University & Research, Wageningen, The Netherlands
| | - Farzad Fereidouni
- Department of Pathology and Laboratory Medicine, UC Davis Medical Center, Sacramento, CA, USA
| | - Herbert van Amerongen
- Laboratory of Biophysics, Wageningen University & Research, Wageningen, The Netherlands.,MicroSpectroscopy Centre, Wageningen University and Research, Wageningen, The Netherlands
| | - Henk Van As
- Laboratory of Biophysics, Wageningen University & Research, Wageningen, The Netherlands. .,Wageningen NMR Centre, Wageningen University & Research, Wageningen, The Netherlands.
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Arjen N Bader
- Laboratory of Biophysics, Wageningen University & Research, Wageningen, The Netherlands. .,MicroSpectroscopy Centre, Wageningen University and Research, Wageningen, The Netherlands.
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Fortuin AS, Brüggemann R, van der Linden J, Panfilov I, Israël B, Scheenen TWJ, Barentsz JO. Ultra-small superparamagnetic iron oxides for metastatic lymph node detection: back on the block. Wiley Interdiscip Rev Nanomed Nanobiotechnol 2017; 10. [PMID: 28382713 PMCID: PMC5763341 DOI: 10.1002/wnan.1471] [Citation(s) in RCA: 57] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2016] [Revised: 02/22/2017] [Accepted: 02/25/2017] [Indexed: 12/25/2022]
Abstract
In the past 15 years, encouraging clinical results for the detection of small lymph node metastases was obtained by the use of Combidex‐enhanced MRI (CEM, also known as magnetic resonance lymphography). Withdrawal of the European Medicines Agency approval application by the manufacturer made it impossible for patients to benefit from this agent; a loss, especially for men with prostate cancer. Current conventional imaging techniques are not as accurate as CEM is, thus a surgical diagnostic exploration (extended lymph node dissection) is still the preferred technique to evaluate the lymph nodes, resulting in peri‐ and postoperative complications. In 2013, the Radboud University Medical Center (Radboudumc) obtained all licenses and documentation for the production process of Combidex (ferumoxtran‐10), and manufactured the contrast agent under supervision of the Department of Pharmacy. Since 2014, 310 men with prostate cancer have been examined with CEM in the Radboudumc. Within this cohort, seven minor possibly contrast‐related adverse effects were observed after administration of Combidex. As the contrast agent is now back again in the Netherlands, this review highlights the working mechanism, previous results, observed side effects since the reintroduction, and the future perspectives for Combidex. WIREs Nanomed Nanobiotechnol 2018, 10:e1471. doi: 10.1002/wnan.1471 This article is categorized under:
Diagnostic Tools > In Vivo Nanodiagnostics and Imaging Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease
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Affiliation(s)
- Ansje S Fortuin
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.,Department of Radiology and Nuclear Medicine, Ziekenhuis Gelderse Vallei, Ede, The Netherlands
| | - Roger Brüggemann
- Department of Pharmacy, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Janine van der Linden
- Department of Pharmacy, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Ilia Panfilov
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Bas Israël
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jelle O Barentsz
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
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44
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Philips BWJ, Fortuin AS, Orzada S, Scheenen TWJ, Maas MC. High resolution MR imaging of pelvic lymph nodes at 7 Tesla. Magn Reson Med 2016; 78:1020-1028. [PMID: 27714842 DOI: 10.1002/mrm.26498] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [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: 07/05/2016] [Revised: 08/30/2016] [Accepted: 09/16/2016] [Indexed: 11/06/2022]
Abstract
PURPOSE Pelvic lymph node (PLN) metastases are often smaller than 5 mm and difficult to detect. This work presents a method to perform PLN imaging with ultrahigh-field MRI, using spectrally selective excitation to acquire water and lipid-selective imaging at high spatial resolution. METHODS A 3D water-selective multigradient echo (mGRE) sequence and lipid-selective gradient echo (GRE) sequence were tested in six healthy volunteers on a 7 Tesla (T) MRI system, using time interleaved acquisition of modes (TIAMO) to improve image homogeneity. The size distribution of the first 10 iliac PLNs detected in each volunteer was determined, and the contrast-to-noise ratio (CNR) of these lymph nodes (LNs) was compared with the individual mGRE images, sum-of-squares echo addition, and computed T2*-weighted images derived from the T2* fits. RESULTS LN imaging was acquired robustly at ultrahigh field with high resolution and homogeneous lipid or water-selective contrast. PLNs down to 1.5-mm short axis were detected with mean ± standard error of the mean (SEM) short and long axes of 2.2 ± 0.1 and 3.7 ± 0.2 mm, respectively. Computed T2*-weighted imaging allowed flexibility in T2* contrast while featuring a CNR up to 90% of the sum-of-squares echo addition. CONCLUSION Ultrahigh-field MRI in combination with TIAMO and frequency-selective excitation enables high-resolution, large field-of-view MRI of the lower abdomen, and may ultimately be suitable for detecting small PLN metastases. Magn Reson Med 78:1020-1028, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Bart W J Philips
- Department of Radiology and Nuclear Medicine (766), Radboud University Medical Center, Nijmegen, the Netherlands
| | - Ansje S Fortuin
- Department of Radiology and Nuclear Medicine (766), Radboud University Medical Center, Nijmegen, the Netherlands
| | - Stephan Orzada
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, UNESCO World Cultural Heritage Zollverein, Essen, Germany
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine (766), Radboud University Medical Center, Nijmegen, the Netherlands.,Erwin L. Hahn Institute for Magnetic Resonance Imaging, UNESCO World Cultural Heritage Zollverein, Essen, Germany
| | - Marnix C Maas
- Department of Radiology and Nuclear Medicine (766), Radboud University Medical Center, Nijmegen, the Netherlands
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45
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Steinseifer IK, Philips BWJ, Gagoski B, Weiland E, Scheenen TWJ, Heerschap A. Flexible proton 3D MR spectroscopic imaging of the prostate with low-power adiabatic pulses for volume selection and spiral readout. Magn Reson Med 2016; 77:928-935. [PMID: 26968422 DOI: 10.1002/mrm.26181] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [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: 12/02/2015] [Revised: 01/27/2016] [Accepted: 02/04/2016] [Indexed: 01/28/2023]
Abstract
PURPOSE Cartesian k-space sampling in three-dimensional magnetic resonance spectroscopic imaging (MRSI) of the prostate limits the selection of voxel size and acquisition time. Therefore, large prostates are often scanned at reduced spatial resolutions to stay within clinically acceptable measurement times. Here we present a semilocalized adiabatic selective refocusing (sLASER) sequence with gradient-modulated offset-independent adiabatic (GOIA) refocusing pulses and spiral k-space acquisition (GOIA-sLASER-Spiral) for fast prostate MRSI with enhanced resolution and extended matrix sizes. METHODS MR was performed at 3 tesla with an endorectal receive coil. GOIA-sLASER-Spiral at an echo time (TE) of 90 ms was compared to a point-resolved spectroscopy sequence (PRESS) with weighted, elliptical phase encoding at an TE of 145 ms using simulations and measurements of phantoms and patients (n = 9). RESULTS GOIA-sLASER-Spiral acquisition allows prostate MR spectra to be obtained in ∼5 min with a quality comparable to those acquired with a common Cartesian PRESS protocol in ∼9 min, or at an enhanced spatial resolution showing more precise tissue allocation of metabolites. Extended field of views (FOVs) and matrix sizes for large prostates are possible without compromising spatial resolution or measurement time. CONCLUSION The flexibility of spiral sampling enables prostate MRSI with a wide range of resolutions and FOVs without undesirable increases in acquisition times, as in Cartesian encoding. This approach is suitable for routine clinical exams of prostate metabolites. Magn Reson Med 77:928-935, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Isabell K Steinseifer
- Department of Radiology and Nuclear Medicine (667), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Bart W J Philips
- Department of Radiology and Nuclear Medicine (667), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Borjan Gagoski
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | | | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine (667), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Arend Heerschap
- Department of Radiology and Nuclear Medicine (667), Radboud University Medical Center, Nijmegen, The Netherlands
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Lagemaat MW, van de Bank BL, Sati P, Li S, Maas MC, Scheenen TWJ. Repeatability of (31) P MRSI in the human brain at 7 T with and without the nuclear Overhauser effect. NMR Biomed 2016; 29:256-63. [PMID: 26647020 PMCID: PMC4769102 DOI: 10.1002/nbm.3455] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [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: 02/25/2015] [Revised: 10/18/2015] [Accepted: 11/09/2015] [Indexed: 05/03/2023]
Abstract
An often-employed strategy to enhance signals in (31) P MRS is the generation of the nuclear Overhauser effect (NOE) by saturation of the water resonance. However, NOE allegedly increases the variability of the (31) P data, because variation is reported in NOE enhancements. This would negate the signal-to-noise (SNR) gain it generates. We hypothesized that the variation in NOE enhancement values is not caused by the variability in NOE itself, but is attributable to measurement uncertainties in the values used to calculate the enhancement. If true, the expected increase in SNR with NOE would improve the repeatability of (31) P MRS measurements. To verify this hypothesis, a repeatability study of native and NOE-enhanced (31) P MRSI was performed in the brains of seven healthy volunteers at 7 T. The repeatability coefficient (RC) and the coefficient of variation in repeated measurements (CoVrepeat ) were determined for each method, and the 95% limits of agreement (LoAs) between native and NOE-enhanced signals were calculated. The variation between the methods, defined by the LoA, is at least as great as that predicted by the RC of each method. The sources of variation in NOE enhancements were determined using variance component analysis. In the seven metabolites with a positive NOE enhancement (nine metabolite resonances assessed), CoVrepeat improved, on average, by 15%. The LoAs could be explained by the RCs of the individual methods for the majority of the metabolites, generally confirming our hypothesis. Variation in NOE enhancement was mainly attributable to the factor repeat, but between-voxel effects were also present for phosphoethanolamine and (glycero)phosphocholine. CoVrepeat and fitting error were strongly correlated and improved with positive NOE. Our findings generally indicate that NOE enhances the signal of metabolites, improving the repeatability of metabolite measurements. Additional variability as a result of NOE was minimal. These findings encourage the use of NOE-enhanced (31) P MRSI. Copyright © 2015 John Wiley & Sons, Ltd.
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Affiliation(s)
- Miriam W Lagemaat
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Bart L van de Bank
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Pascal Sati
- Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Shizhe Li
- MRS Core Facility, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Marnix C Maas
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
- Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, Essen, Germany
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van de Bank BL, Orzada S, Smits F, Lagemaat MW, Rodgers CT, Bitz AK, Scheenen TWJ. Optimized (31)P MRS in the human brain at 7 T with a dedicated RF coil setup. NMR Biomed 2015; 28:1570-8. [PMID: 26492089 PMCID: PMC4744789 DOI: 10.1002/nbm.3422] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [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: 03/02/2015] [Revised: 09/02/2015] [Accepted: 09/06/2015] [Indexed: 05/03/2023]
Abstract
The design and construction of a dedicated RF coil setup for human brain imaging ((1)H) and spectroscopy ((31)P) at ultra-high magnetic field strength (7 T) is presented. The setup is optimized for signal handling at the resonance frequencies for (1)H (297.2 MHz) and (31)P (120.3 MHz). It consists of an eight-channel (1)H transmit-receive head coil with multi-transmit capabilities, and an insertable, actively detunable (31)P birdcage (transmit-receive and transmit only), which can be combined with a seven-channel receive-only (31)P array. The setup enables anatomical imaging and (31)P studies without removal of the coil or the patient. By separating transmit and receive channels and by optimized addition of array signals with whitened singular value decomposition we can obtain a sevenfold increase in SNR of (31)P signals in the occipital lobe of the human brain compared with the birdcage alone. These signals can be further enhanced by 30 ± 9% using the nuclear Overhauser effect by B1-shimmed low-power irradiation of water protons. Together, these features enable acquisition of (31)P MRSI at high spatial resolutions (3.0 cm(3) voxel) in the occipital lobe of the human brain in clinically acceptable scan times (~15 min).
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Affiliation(s)
- Bart L van de Bank
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Stephan Orzada
- Erwin L. Hahn Institute, University Hospital Duisburg-Essen, Essen, Germany
| | - Frits Smits
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Miriam W Lagemaat
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Christopher T Rodgers
- Oxford Centre for Clinical Magnetic Resonance Research (OCMR), University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Andreas K Bitz
- Erwin L. Hahn Institute, University Hospital Duisburg-Essen, Essen, Germany
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
- Erwin L. Hahn Institute, University Hospital Duisburg-Essen, Essen, Germany
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Kobus T, van der Laak JAWM, Maas MC, Hambrock T, Bruggink CC, Hulsbergen-van de Kaa CA, Scheenen TWJ, Heerschap A. Contribution of Histopathologic Tissue Composition to Quantitative MR Spectroscopy and Diffusion-weighted Imaging of the Prostate. Radiology 2015; 278:801-11. [PMID: 26418614 DOI: 10.1148/radiol.2015142889] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
PURPOSE To determine associations of metabolite levels derived from magnetic resonance (MR) spectroscopic imaging (ie, hydrogen 1 [(1)H] MR spectroscopic imaging) and apparent diffusion coefficients (ADCs) from diffusion-weighted imaging with prostate tissue composition assessed by digital image analysis of histologic sections. MATERIALS AND METHODS Institutional ethical review board approved this retrospective study and waived informed consent. Fifty-seven prostate cancer patients underwent an MR examination followed by prostatectomy. One hematoxylin and eosin-stained section of the resected prostate per patient was digitized and computationally segmented into nuclei, lumen, and combination of epithelial cytoplasm and stroma. On each stained section, regions of interest (ROIs) were chosen and matched to the corresponding ADC map and (1)H MR spectroscopic imaging voxels. ADC and two metabolite ratios (citrate [Cit], spermine [Spm], and creatine [Cr] to choline [Cho] and Cho to Cr plus Spm) were correlated with percentage areas of nuclei, lumen, and cytoplasm and stroma for peripheral zone (PZ), transition zone (TZ), and tumor tissue in both zones of the prostate by using a linear mixed-effect model and Spearman correlation coefficient (ρ). RESULTS ADC and (Cit + Spm + Cr)/Cho ratio showed positive correlation with percentage area of lumen (ρ = 0.43 and 0.50, respectively) and negative correlation with percentage area of nuclei (ρ = -0.29 and -0.26, respectively). The Cho/(Cr + Spm) ratio showed negative association with percentage area of lumen (ρ = -0.40) and positive association with area of nuclei (ρ = 0.26). Percentage areas of lumen and nuclei, (Cit + Spm + Cr)/Cho ratio, and ADC were significantly different (P < .001) between benign PZ (23.7 and 7.7, 8.83, and 1.58 × 10(-3) mm(2)/sec, respectively) and tumor PZ tissue (11.4 and 12.5, 5.13, and 1.20 × 10(-3) mm(2)/sec, respectively). These parameters were also significantly different between benign TZ (20.0 and 8.2, 6.50, and 1.26 × 10(-3) mm(2)/sec, respectively) and tumor TZ tissue (9.8 and 11.2, 4.36, and 1.03 × 10(-3) mm(2)/sec, respectively). CONCLUSION The observed correlation of (Cit + Spm + Cr)/Cho ratio and ADC of the prostate with its tissue composition indicates that components of this composition, such as percentage luminal area, contribute to the value of these MR parameters.
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Affiliation(s)
- Thiele Kobus
- From the Department of Radiology and Nuclear Medicine (T.K., M.C.M., T.H., C.C.B., T.W.J.S., A.H.) and Department of Pathology (J.A.W.M.v.d.L., C.A.H.v.d.K.), Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Jeroen A W M van der Laak
- From the Department of Radiology and Nuclear Medicine (T.K., M.C.M., T.H., C.C.B., T.W.J.S., A.H.) and Department of Pathology (J.A.W.M.v.d.L., C.A.H.v.d.K.), Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Marnix C Maas
- From the Department of Radiology and Nuclear Medicine (T.K., M.C.M., T.H., C.C.B., T.W.J.S., A.H.) and Department of Pathology (J.A.W.M.v.d.L., C.A.H.v.d.K.), Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Thomas Hambrock
- From the Department of Radiology and Nuclear Medicine (T.K., M.C.M., T.H., C.C.B., T.W.J.S., A.H.) and Department of Pathology (J.A.W.M.v.d.L., C.A.H.v.d.K.), Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Caroline C Bruggink
- From the Department of Radiology and Nuclear Medicine (T.K., M.C.M., T.H., C.C.B., T.W.J.S., A.H.) and Department of Pathology (J.A.W.M.v.d.L., C.A.H.v.d.K.), Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Christina A Hulsbergen-van de Kaa
- From the Department of Radiology and Nuclear Medicine (T.K., M.C.M., T.H., C.C.B., T.W.J.S., A.H.) and Department of Pathology (J.A.W.M.v.d.L., C.A.H.v.d.K.), Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Tom W J Scheenen
- From the Department of Radiology and Nuclear Medicine (T.K., M.C.M., T.H., C.C.B., T.W.J.S., A.H.) and Department of Pathology (J.A.W.M.v.d.L., C.A.H.v.d.K.), Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Arend Heerschap
- From the Department of Radiology and Nuclear Medicine (T.K., M.C.M., T.H., C.C.B., T.W.J.S., A.H.) and Department of Pathology (J.A.W.M.v.d.L., C.A.H.v.d.K.), Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
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Breukels V, Jansen KCFJ, van Heijster FHA, Capozzi A, van Bentum PJM, Schalken JA, Comment A, Scheenen TWJ. Direct dynamic measurement of intracellular and extracellular lactate in small-volume cell suspensions with (13)C hyperpolarised NMR. NMR Biomed 2015; 28:1040-1048. [PMID: 26123400 DOI: 10.1002/nbm.3341] [Citation(s) in RCA: 9] [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: 11/14/2014] [Revised: 04/14/2015] [Accepted: 05/14/2015] [Indexed: 06/04/2023]
Abstract
Hyperpolarised (HP) (13)C NMR allows enzymatic activity to be probed in real time in live biological systems. The use of in vitro models gives excellent control of the cellular environment, crucial in the understanding of enzyme kinetics. The increased conversion of pyruvate to lactate in cancer cells has been well studied with HP (13)C NMR. Unfortunately, the equally important metabolic step of lactate transport out of the cell remains undetected, because intracellular and extracellular lactate are measured as a single resonance. Furthermore, typical experiments must be performed using tens of millions of cells, a large amount which can lead to a costly and sometimes highly challenging growing procedure. We present a relatively simple set-up that requires as little as two million cells with the spectral resolution to separate the intracellular and extracellular lactate resonances. The set-up is tested with suspensions of prostate cancer carcinoma cells (PC3) in combination with HP [1-(13)C]pyruvate. We obtained reproducible pyruvate to lactate label fluxes of 1.2 and 1.7 nmol/s per million cells at 2.5 and 5.0 mM pyruvate concentrations. The existence of a 3-Hz chemical shift difference between intracellular and extracellular lactate enabled us to determine the lactate transport rates in PC3. We deduced a lactate export rate of 0.3 s(-1) and observed a decrease in lactate transport on addition of the lactate transport inhibitor α-cyano-4-hydroxycinnamic acid.
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Affiliation(s)
- Vincent Breukels
- Department of Radiology and Nuclear Medicine, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Kees C F J Jansen
- Department of Urology, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Frits H A van Heijster
- Department of Radiology and Nuclear Medicine, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Andrea Capozzi
- Institute of Physics of Biological Systems, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - P Jan M van Bentum
- Institute for Molecules and Materials, Radboud University, Nijmegen, the Netherlands
| | - Jack A Schalken
- Department of Urology, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Arnaud Comment
- Institute of Physics of Biological Systems, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Centre, Nijmegen, the Netherlands
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Lagemaat MW, Breukels V, Vos EK, Kerr AB, van Uden MJ, Orzada S, Bitz AK, Maas MC, Scheenen TWJ. (1)H MR spectroscopic imaging of the prostate at 7T using spectral-spatial pulses. Magn Reson Med 2015; 75:933-45. [PMID: 25943445 DOI: 10.1002/mrm.25569] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [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: 08/26/2014] [Revised: 11/17/2014] [Accepted: 11/17/2014] [Indexed: 12/16/2022]
Abstract
PURPOSE To assess the feasibility of prostate (1)H MR spectroscopic imaging (MRSI) using low-power spectral-spatial (SPSP) pulses at 7T, exploiting accurate spectral selection and spatial selectivity simultaneously. METHODS A double spin-echo sequence was equipped with SPSP refocusing pulses with a spectral selectivity of 1 ppm. Three-dimensional prostate (1)H-MRSI at 7T was performed with the SPSP-MRSI sequence using an 8-channel transmit array coil and an endorectal receive coil in three patients with prostate cancer and in one healthy subject. No additional water or lipid suppression pulses were used. RESULTS Prostate (1)H-MRSI could be obtained well within specific absorption rate (SAR) limits in a clinically feasible time (10 min). Next to the common citrate signals, the prostate spectra exhibited high spermine signals concealing creatine and sometimes also choline. Residual lipid signals were observed at the edges of the prostate because of limitations in spectral and spatial selectivity. CONCLUSION It is possible to perform prostate (1)H-MRSI at 7T with a SPSP-MRSI sequence while using separate transmit and receive coils. This low-SAR MRSI concept provides the opportunity to increase spatial resolution of MRSI within reasonable scan times.
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Affiliation(s)
- Miriam W Lagemaat
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Vincent Breukels
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Eline K Vos
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Adam B Kerr
- Magnetic Resonance Systems Research Lab, Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Mark J van Uden
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Stephan Orzada
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, Essen, Germany
| | - Andreas K Bitz
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, Essen, Germany.,Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany
| | - Marnix C Maas
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.,Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, Essen, Germany
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