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Hall M, Suff N, Slator P, Rutherford M, Shennan A, Hutter J, Story L. Placental multimodal MRI prior to spontaneous preterm birth <32 weeks' gestation: An observational study. BJOG 2024. [PMID: 38956748 DOI: 10.1111/1471-0528.17901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 05/22/2024] [Accepted: 06/20/2024] [Indexed: 07/04/2024]
Abstract
OBJECTIVE To utilise combined diffusion-relaxation MRI techniques to interrogate antenatal changes in the placenta prior to extreme preterm birth among both women with PPROM and membranes intact, and compare this to a control group who subsequently delivered at term. DESIGN Observational study. SETTING Tertiary Obstetric Unit, London, UK. POPULATION Cases: pregnant women who subsequently spontaneously delivered a singleton pregnancy prior to 32 weeks' gestation without any other obstetric complications. CONTROLS pregnant women who delivered an uncomplicated pregnancy at term. METHODS All women consented to an MRI examination. A combined diffusion-relaxation MRI of the placenta was undertaken and analysed using fractional anisotropy, a combined T2*-apparent diffusion coefficient model and a combined T2*-intravoxel incoherent motion model, in order to provide a detailed placental phenotype associated with preterm birth. Subgroup analyses based on whether women in the case group had PPROM or intact membranes at time of scan, and on latency to delivery were performed. MAIN OUTCOME MEASURES Fractional anisotropy, apparent diffusion coefficients and T2* placental values, from two models including a combined T2*-IVIM model separating fast- and slow-flowing (perfusing and diffusing) compartments. RESULTS This study included 23 women who delivered preterm and 52 women who delivered at term. Placental T2* was lower in the T2*-apparent diffusion coefficient model (p < 0.001) and in the fast- and slow-flowing compartments (p = 0.001 and p < 0.001) of the T2*-IVIM model. This reached a higher level of significance in the preterm prelabour rupture of the membranes group than in the membranes intact group. There was a reduced perfusion fraction among the cases with impending delivery. CONCLUSIONS Placental diffusion-relaxation reveals significant changes in the placenta prior to preterm birth with greater effect noted in cases of preterm prelabour rupture of the membranes. Application of this technique may allow clinically valuable interrogation of histopathological changes before preterm birth. In turn, this could facilitate more accurate antenatal prediction of preterm chorioamnionitis and so aid decisions around the safest time of delivery. Furthermore, this technique provides a research tool to improve understanding of the pathological mechanisms associated with preterm birth in vivo.
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Affiliation(s)
- Megan Hall
- Centre for the Developing Brain, St Thomas' Hospital, King's College London, London, UK
- Department of Women and Children's Health, St Thomas' Hospital, King's College London, London, UK
| | - Natalie Suff
- Department of Women and Children's Health, St Thomas' Hospital, King's College London, London, UK
| | - Paddy Slator
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK
- School of Computer Science and Informatics, Cardiff University, Cardiff, UK
| | - Mary Rutherford
- Centre for the Developing Brain, St Thomas' Hospital, King's College London, London, UK
| | - Andrew Shennan
- Department of Women and Children's Health, St Thomas' Hospital, King's College London, London, UK
| | - Jana Hutter
- Centre for the Developing Brain, St Thomas' Hospital, King's College London, London, UK
- Smart Imaging Lab, Radiological Institute, University Hospital Erlangen, Erlangen, Germany
| | - Lisa Story
- Centre for the Developing Brain, St Thomas' Hospital, King's College London, London, UK
- Department of Women and Children's Health, St Thomas' Hospital, King's College London, London, UK
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Zong F, Wang L, Liu H, Xue B, Bai R, Liu Y. A genetic optimisation and iterative reconstruction framework for sparse multi-dimensional diffusion-relaxation correlation MRI. Comput Biol Med 2024; 175:108508. [PMID: 38678941 DOI: 10.1016/j.compbiomed.2024.108508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 04/11/2024] [Accepted: 04/21/2024] [Indexed: 05/01/2024]
Abstract
Multi-dimensional diffusion-relaxation correlation (DRC) magnetic resonance imaging (MRI) techniques have recently been developed to investigate tissue microstructures. Sub-voxel tissue heterogeneity is resolved from the local correlation distributions of relaxation time and molecular diffusivity. However, the implementation of these techniques considerably increases the total acquisition time, and simply reducing the scan time may be at the expense of detailed structural resolution. To overcome these limitations, an optimised framework was proposed for acquiring microstructural maps of the human brain on a clinically feasible timescale. First, the acquisition parameters of the multi-dimensional DRC MRI method were sparsely optimised using a genetic algorithm with a fitness function according to the spectral resolution of the correlation map, hardware requirements, and total scan time. Next, the acquired DRC MRI data were processed using a proposed numerical algorithm based on the dynamic inverse Laplace transform (ILT). Prior knowledge from one-dimensional data was then utilised in the iterative procedure to improve the spectral resolution. Finally, the proposed framework was validated using Monte Carlo simulations and experimental data acquired from healthy participants on an MRI scanner. The results demonstrated that the suggested approach is feasible for offering high-resolution DRC maps that correspond to distinct microstructures with a limited amount of optimised acquisition data from two-dimensional DRC sampling space. By significantly reducing scan time while retaining structural resolution, this approach may enable multi-dimensional DRC MRI to be more widely used for quantitative evaluation in biological and medical settings.
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Affiliation(s)
- Fangrong Zong
- School of Artificial Intelligence, Beijing University of Post and Telecommunication, Beijing, 100876, China.
| | - Lixian Wang
- Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Huabing Liu
- Beijing Limecho Technology Co., Ltd., Beijing, 102200, China
| | - Bing Xue
- School of Engineering and Computer Science, Victoria University of Wellington, Victoria, 6140, New Zealand
| | - Ruiliang Bai
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310020, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, 310030, China
| | - Yong Liu
- School of Artificial Intelligence, Beijing University of Post and Telecommunication, Beijing, 100876, China.
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Cromb D, Slator PJ, Hall M, Price A, Alexander DC, Counsell SJ, Hutter J. Advanced magnetic resonance imaging detects altered placental development in pregnancies affected by congenital heart disease. Sci Rep 2024; 14:12357. [PMID: 38811636 PMCID: PMC11136986 DOI: 10.1038/s41598-024-63087-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 05/24/2024] [Indexed: 05/31/2024] Open
Abstract
Congenital heart disease (CHD) is the most common congenital malformation and is associated with adverse neurodevelopmental outcomes. The placenta is crucial for healthy fetal development and placental development is altered in pregnancy when the fetus has CHD. This study utilized advanced combined diffusion-relaxation MRI and a data-driven analysis technique to test the hypothesis that placental microstructure and perfusion are altered in CHD-affected pregnancies. 48 participants (36 controls, 12 CHD) underwent 67 MRI scans (50 control, 17 CHD). Significant differences in the weighting of two independent placental and uterine-wall tissue components were identified between the CHD and control groups (both pFDR < 0.001), with changes most evident after 30 weeks gestation. A significant trend over gestation in weighting for a third independent tissue component was also observed in the CHD cohort (R = 0.50, pFDR = 0.04), but not in controls. These findings add to existing evidence that placental development is altered in CHD. The results may reflect alterations in placental perfusion or the changes in fetal-placental flow, villous structure and maturation that occur in CHD. Further research is needed to validate and better understand these findings and to understand the relationship between placental development, CHD, and its neurodevelopmental implications.
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Affiliation(s)
- Daniel Cromb
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, SE1 7EH, UK
- Centre for Medical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Paddy J Slator
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
- School of Computer Science and Informatics, Cardiff University, Cardiff, UK
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, UK
| | - Megan Hall
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Anthony Price
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, SE1 7EH, UK
- Centre for Medical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Daniel C Alexander
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, SE1 7EH, UK.
- Centre for Medical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, SE1 7EH, UK
- Centre for Medical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Smart Imaging Lab, Radiological Institute, University Hospital Erlangen, Erlangen, Germany
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Johnson JTE, Irfanoglu MO, Manninen E, Ross TJ, Yang Y, Laun FB, Martin J, Topgaard D, Benjamini D. In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI. Hum Brain Mapp 2024; 45:e26697. [PMID: 38726888 PMCID: PMC11082920 DOI: 10.1002/hbm.26697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 03/28/2024] [Accepted: 04/12/2024] [Indexed: 05/13/2024] Open
Abstract
Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency,ω $$ \omega $$ , in addition to the diffusion tensor,D $$ \mathbf{D} $$ , and relaxation,R 1 $$ {R}_1 $$ ,R 2 $$ {R}_2 $$ , correlations. AD ω - R 1 - R 2 $$ \mathbf{D}\left(\omega \right)-{R}_1-{R}_2 $$ clinical imaging protocol was then introduced, with limited brain coverage and 3 mm3 voxel size, which hinder brain segmentation and future cohort studies. In this study, we introduce an efficient, sparse in vivo MD-MRI acquisition protocol providing whole brain coverage at 2 mm3 voxel size. We demonstrate its feasibility and robustness using a well-defined phantom and repeated scans of five healthy individuals. Additionally, we test different denoising strategies to address the sparse nature of this protocol, and show that efficient MD-MRI encoding design demands a nuanced denoising approach. The MD-MRI framework provides rich information that allows resolving the diffusion frequency dependence into intravoxel components based on theirD ω - R 1 - R 2 $$ \mathbf{D}\left(\omega \right)-{R}_1-{R}_2 $$ distribution, enabling the creation of microstructure-specific maps in the human brain. Our results encourage the broader adoption and use of this new imaging approach for characterizing healthy and pathological tissues.
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Affiliation(s)
- Jessica T. E. Johnson
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIHBaltimoreMarylandUSA
| | - M. Okan Irfanoglu
- Quantitative Medical Imaging Section, National Institute of Biomedical Imaging and Bioengineering, National Institutes of HealthBethesdaMarylandUSA
| | - Eppu Manninen
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIHBaltimoreMarylandUSA
| | - Thomas J. Ross
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of HealthBaltimoreMarylandUSA
| | - Yihong Yang
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of HealthBaltimoreMarylandUSA
| | - Frederik B. Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich‐Alexander‐Universität Erlangen‐Nürnberg (FAU)ErlangenGermany
| | - Jan Martin
- Department of ChemistryLund UniversityLundSweden
| | | | - Dan Benjamini
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIHBaltimoreMarylandUSA
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Hall M, de Marvao A, Schweitzer R, Cromb D, Colford K, Jandu P, O’Regan DP, Ho A, Price A, Chappell LC, Rutherford MA, Story L, Lamata P, Hutter J. Preeclampsia Associated Differences in the Placenta, Fetal Brain, and Maternal Heart Can Be Demonstrated Antenatally: An Observational Cohort Study Using MRI. Hypertension 2024; 81:836-847. [PMID: 38314606 PMCID: PMC7615760 DOI: 10.1161/hypertensionaha.123.22442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 01/02/2024] [Indexed: 02/06/2024]
Abstract
BACKGROUND Preeclampsia is a multiorgan disease of pregnancy that has short- and long-term implications for the woman and fetus, whose immediate impact is poorly understood. We present a novel multiorgan approach to magnetic resonance imaging (MRI) investigation of preeclampsia, with the acquisition of maternal cardiac, placental, and fetal brain anatomic and functional imaging. METHODS An observational study was performed recruiting 3 groups of pregnant women: those with preeclampsia, chronic hypertension, or no medical complications. All women underwent a cardiac MRI, and pregnant women underwent a placental-fetal MRI. Cardiac analysis for structural, morphological, and flow data were undertaken; placenta and fetal brain volumetric and T2* (which describes relative tissue oxygenation) data were obtained. All results were corrected for gestational age. A nonpregnant cohort was identified for inclusion in the statistical shape analysis. RESULTS Seventy-eight MRIs were obtained during pregnancy. Cardiac MRI analysis demonstrated higher left ventricular mass in preeclampsia with 3-dimensional modeling revealing additional specific characteristics of eccentricity and outflow track remodeling. Pregnancies affected by preeclampsia demonstrated lower placental and fetal brain T2*. Within the preeclampsia group, 23% placental T2* results were consistent with controls, these were the only cases with normal placental histopathology. Fetal brain T2* results were consistent with normal controls in 31% of cases. CONCLUSIONS We present the first holistic assessment of the immediate implications of preeclampsia on maternal heart, placenta, and fetal brain. As well as having potential clinical implications for the risk stratification and management of women with preeclampsia, this gives an insight into the disease mechanism.
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Affiliation(s)
- Megan Hall
- Department of Women and Children’s Health (M.H., A.d.M., A.H., L.C.C., L.S.), King’s College London, United Kingdom
- Centre for the Developing Brain (M.H., D.C., K.C., A.H., A.P., M.A.R., L.S., J.H.), King’s College London, United Kingdom
| | - Antonio de Marvao
- Department of Women and Children’s Health (M.H., A.d.M., A.H., L.C.C., L.S.), King’s College London, United Kingdom
- School of Cardiovascular Medicine (A.d.M., R.S.), King’s College London, United Kingdom
- MRC London Institute of Medical Sciences, Imperial College London, United Kingdom (A.d.M., R.S., D.P.O.)
| | - Ronny Schweitzer
- School of Cardiovascular Medicine (A.d.M., R.S.), King’s College London, United Kingdom
- MRC London Institute of Medical Sciences, Imperial College London, United Kingdom (A.d.M., R.S., D.P.O.)
| | - Daniel Cromb
- Centre for the Developing Brain (M.H., D.C., K.C., A.H., A.P., M.A.R., L.S., J.H.), King’s College London, United Kingdom
| | - Kathleen Colford
- Centre for the Developing Brain (M.H., D.C., K.C., A.H., A.P., M.A.R., L.S., J.H.), King’s College London, United Kingdom
| | - Priya Jandu
- GKT School of Medical Education (P.J.), King’s College London, United Kingdom
| | - Declan P O’Regan
- MRC London Institute of Medical Sciences, Imperial College London, United Kingdom (A.d.M., R.S., D.P.O.)
| | - Alison Ho
- Department of Women and Children’s Health (M.H., A.d.M., A.H., L.C.C., L.S.), King’s College London, United Kingdom
- Centre for the Developing Brain (M.H., D.C., K.C., A.H., A.P., M.A.R., L.S., J.H.), King’s College London, United Kingdom
| | - Anthony Price
- Centre for the Developing Brain (M.H., D.C., K.C., A.H., A.P., M.A.R., L.S., J.H.), King’s College London, United Kingdom
- Centre for Medical Engineering (A.P., P.L.), King’s College London, United Kingdom
| | - Lucy C. Chappell
- Department of Women and Children’s Health (M.H., A.d.M., A.H., L.C.C., L.S.), King’s College London, United Kingdom
| | - Mary A. Rutherford
- Centre for the Developing Brain (M.H., D.C., K.C., A.H., A.P., M.A.R., L.S., J.H.), King’s College London, United Kingdom
| | - Lisa Story
- Department of Women and Children’s Health (M.H., A.d.M., A.H., L.C.C., L.S.), King’s College London, United Kingdom
- Centre for the Developing Brain (M.H., D.C., K.C., A.H., A.P., M.A.R., L.S., J.H.), King’s College London, United Kingdom
| | - Pablo Lamata
- Centre for Medical Engineering (A.P., P.L.), King’s College London, United Kingdom
| | - Jana Hutter
- Centre for the Developing Brain (M.H., D.C., K.C., A.H., A.P., M.A.R., L.S., J.H.), King’s College London, United Kingdom
- Smart Imaging Lab, Radiological Institute, University Hospital Erlangen, Germany (J.H.)
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Maiuro A, Ercolani G, Di Stadio F, Antonelli A, Catalano C, Manganaro L, Capuani S. Two-Compartment Perfusion MR IVIM Model to Investigate Normal and Pathological Placental Tissue. J Magn Reson Imaging 2024; 59:879-891. [PMID: 37329218 DOI: 10.1002/jmri.28858] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 05/26/2023] [Accepted: 05/30/2023] [Indexed: 06/18/2023] Open
Abstract
BACKGROUND Perfusion and diffusion coexist in the placenta and can be altered by pathologies. The two-perfusion model, where f1 and, f2 are the perfusion-fraction of the fastest and slowest perfusion compartment, respectively, and D is the diffusion coefficient, may help differentiate between normal and impaired placentas. PURPOSE Investigate the potential of the two-perfusion IVIM model in differentiating between normal and abnormal placentas. STUDY-TYPE Retrospective, case-control. POPULATION 43 normal pregnancy, 9 fetal-growth-restriction (FGR), 6 small-for-gestational-age (SGA), 4 accreta, 1 increta and 2 percreta placentas. FIELD STRENGTH/SEQUENCE Diffusion-weighted-echo planar imaging sequence at 1.5 T. ASSESSMENT Voxel-wise signal-correction and fitting-controls were used to avoid overfitting obtaining that two-perfusion model fitted the observed data better than the IVIM model (Akaike weight: 0.94). The two-perfusion parametric-maps were quantified from ROIs in the fetal and maternal placenta and in the accretion zone of accreta placentas. The diffusion coefficient D was evaluated using a b ≥ 200 sec/mm2 -mono-exponential decay fit. IVIM metrics were quantified to fix f1 + f2 = fIVIM . STATISTICAL-TESTS ANOVA with Dunn-Sidák's post-hoc correction and Cohen's d test were used to compare parameters between groups. Spearman's coefficient was evaluated to study the correlation between variables. A P-value<0.05 indicated a statistically significant difference. RESULTS There was a significant difference in f1 between FGR and SGA, and significant differences in f2 and fIVIM between normal and FGR. The percreta + increta group showed the highest f1 values (Cohen's d = -2.66). The f2 between normal and percreta + increta groups showed Cohen's d = 1.12. Conversely, fIVIM had a small effective size (Cohen's d = 0.32). In the accretion zone, a significant correlation was found between f2 and GA (ρ = 0.90) whereas a significant negative correlation was found between fIVIM and D (ρ = -0.37 in fetal and ρ = -0.56 in maternal side) and f2 and D (ρ = -0.38 in fetal and ρ = -0.51 in maternal side) in normal placentas. CONCLUSION The two-perfusion model provides complementary information to IVIM parameters that may be useful in identifying placenta impairment. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Alessandra Maiuro
- Department of Physics, Sapienza University of Rome, Rome, Italy
- Physics Department Rome, CNR ISC Roma Sapienza, Rome, Italy
| | - Giada Ercolani
- Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, Rome, Italy
| | | | - Amanda Antonelli
- Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, Rome, Italy
| | - Carlo Catalano
- Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, Rome, Italy
| | - Lucia Manganaro
- Department of Radiological, Oncological and Pathological Sciences, Umberto I Hospital, Sapienza University of Rome, Rome, Italy
| | - Silvia Capuani
- Physics Department Rome, CNR ISC Roma Sapienza, Rome, Italy
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Dai Y, Hu W, Wu G, Wu D, Zhu M, Luo Y, Wang J, Zhou Y, Hu P. Grading Clear Cell Renal Cell Carcinoma Grade Using Diffusion Relaxation Correlated MR Spectroscopic Imaging. J Magn Reson Imaging 2024; 59:699-710. [PMID: 37209407 DOI: 10.1002/jmri.28777] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 05/01/2023] [Accepted: 05/02/2023] [Indexed: 05/22/2023] Open
Abstract
BACKGROUND Clear cell renal cell carcinoma (ccRCC) is the most common subtype of RCC, and accurate grading is crucial for prognosis and treatment selection. Biopsy is the reference standard for grading, but MRI methods can improve and complement the grading procedure. PURPOSE Assess the performance of diffusion relaxation correlation spectroscopic imaging (DR-CSI) in grading ccRCC. STUDY TYPE Prospective. SUBJECTS 79 patients (age: 58.1 +/- 11.5 years; 55 male) with ccRCC confirmed by histopathology (grade 1, 7; grade 2, 45; grade 3, 18; grade 4, 9) following surgery. FIELD STRENGTH/SEQUENCE 3.0 T MRI scanner. DR-CSI with a diffusion-weighted echo-planar imaging sequence and T2-mapping with a multi-echo spin echo sequence. ASSESSMENT DR-CSI results were analyzed for the solid tumor regions of interest using spectrum segmentation with five sub-region volume fraction metrics (VA , VB , VC , VD , and VE ). The regulations for spectrum segmentation were determined based on the D-T2 spectra of distinct macro-components. Tumor size, voxel-wise T2, and apparent diffusion coefficient (ADC) values were obtained. Histopathology assessed tumor grade (G1-G4) for each case. STATISTICAL TESTS One-way ANOVA or Kruskal-Wallis test, Spearman's correlation (coefficient, rho), multivariable logistic regression analysis, receiver operating characteristic curve analysis, and DeLong's test. Significance criteria: P < 0.05. RESULTS Significant differences were found in ADC, T2, DR-CSI VB , and VD among the ccRCC grades. Correlations were found for ccRCC grade to tumor size (rho = 0.419), age (rho = 0.253), VB (rho = 0.553) and VD (rho = -0.378). AUC of VB was slightly larger than ADC in distinguishing low-grade (G1-G2) from high-grade (G3-G4) ccRCC (0.801 vs. 0.762, P = 0.406) and G1 from G2 to G4 (0.796 vs. 0.647, P = 0.175), although not significant. Combining VB , VD , and VE had better diagnostic performance than combining ADC and T2 for differentiating G1 from G2-G4 (AUC: 0.814 vs 0.643). DATA CONCLUSION DR-CSI parameters are correlated with ccRCC grades, and may help to differentiate ccRCC grades. EVIDENCE LEVEL 2 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Yongming Dai
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
| | - Wentao Hu
- Department of Radiology, Renji hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Guangyu Wu
- Department of Radiology, Renji hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Dongmei Wu
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China
| | - Mengying Zhu
- Department of Radiology, Renji hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yuansheng Luo
- Department of Radiology, Renji hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jieying Wang
- Clinical Research Center, Renji hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yan Zhou
- Department of Radiology, Renji hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Peng Hu
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
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Cromb D, Slator P, Hall M, Price A, Alexander D, Counsell S, Hutter J. Advanced magnetic resonance imaging detects altered placental development in pregnancies affected by congenital heart disease. RESEARCH SQUARE 2024:rs.3.rs-3873412. [PMID: 38343847 PMCID: PMC10854304 DOI: 10.21203/rs.3.rs-3873412/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/17/2024]
Abstract
Congenital heart disease (CHD) is the most common congenital malformation and is associated with adverse neurodevelopmental outcomes. The placenta is crucial for healthy fetal development and placental development is altered in pregnancy when the fetus has CHD. This study utilized advanced combined diffusion-relaxation MRI and a data-driven analysis technique to test the hypothesis that placental microstructure and perfusion are altered in CHD-affected pregnancies. 48 participants (36 controls, 12 CHD) underwent 67 MRI scans (50 control, 17 CHD). Significant differences in the weighting of two independent placental and uterine-wall tissue components were identified between the CHD and control groups (both pFDR<0.001), with changes most evident after 30 weeks gestation. A Significant trend over gestation in weighting for a third independent tissue component was also observed in the CHD cohort (R = 0.50, pFDR=0.04), but not in controls. These findings add to existing evidence that placental development is altered in CHD. The results may reflect alterations in placental perfusion or the changes in fetal-placental flow, villous structure and maturation that occur in CHD. Further research is needed to validate and better understand these findings and to understand the relationship between placental development, CHD, and its neurodevelopmental implications.
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Jani D, Clark A, Couper S, Thompson JMD, David AL, Melbourne A, Mirjalili A, Lydon AM, Stone PR. The effect of maternal position on placental blood flow and fetoplacental oxygenation in late gestation fetal growth restriction: a magnetic resonance imaging study. J Physiol 2023; 601:5391-5411. [PMID: 37467072 DOI: 10.1113/jp284269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Accepted: 07/03/2023] [Indexed: 07/21/2023] Open
Abstract
Fetal growth restriction (FGR) and maternal supine going-to-sleep position are both risk factors for late stillbirth. This study aimed to use magnetic resonance imaging (MRI) to quantify the effect of maternal supine position on maternal-placental and fetoplacental blood flow, placental oxygen transfer and fetal oxygenation in FGR and healthy pregnancies. Twelve women with FGR and 27 women with healthy pregnancies at 34-38 weeks' gestation underwent MRI in both left lateral and supine positions. Phase-contrast MRI and a functional MRI technique (DECIDE) were used to measure blood flow in the maternal internal iliac arteries (IIAs) and umbilical vein (UV), placental oxygen transfer (placental flux), fetal oxygen saturation (FO2 ), and fetal oxygen delivery (delivery flux). The presence of FGR, compared to healthy pregnancies, was associated with a 7.8% lower FO2 (P = 0.02), reduced placental flux, and reduced delivery flux. Maternal supine positioning caused a 3.8% reduction in FO2 (P = 0.001), and significant reductions in total IIA flow, placental flux, UV flow and delivery flux compared to maternal left lateral position. The effect of maternal supine position on fetal oxygen delivery was independent of FGR pregnancy, meaning that supine positioning has an additive effect of reducing fetal oxygenation further in women with FGR, compared to women with appropriately grown for age pregnancies. Meanwhile, the effect of maternal supine positioning on placental oxygen transfer was not independent of the effect of FGR. Therefore, growth-restricted fetuses, which are chronically hypoxaemic, experience a relatively greater decline in oxygen transfer when mothers lie supine in late gestation compared to appropriately growing fetuses. KEY POINTS: Fetal growth restriction (FGR) is the most common risk factor associated with stillbirth, and early recognition and timely delivery is vital to reduce this risk. Maternal supine going-to-sleep position is found to increase the risk of late stillbirth but when combined with having a FGR pregnancy, maternal supine position leads to 15 times greater odds of stillbirth compared to supine sleeping with appropriately grown for age (AGA) pregnancies. Using MRI, this study quantifies the chronic hypoxaemia experienced by growth-restricted fetuses due to 13.5% lower placental oxygen transfer and 26% lower fetal oxygen delivery compared to AGA fetuses. With maternal supine positioning, there is a 23% reduction in maternal-placental blood flow and a further 14% reduction in fetal oxygen delivery for both FGR and AGA pregnancies, but this effect is proportionally greater for growth-restricted fetuses. This knowledge emphasises the importance of avoiding supine positioning in late pregnancy, particularly for vulnerable FGR pregnancies.
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Affiliation(s)
- Devanshi Jani
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
| | - Alys Clark
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Sophie Couper
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
| | - John M D Thompson
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
- Department of Paediatrics and Child Health, University of Auckland, Auckland, New Zealand
| | - Anna L David
- Elizabeth Garrett Anderson Institute for Women's Health, University College Huntley Street, London, UK
| | - Andrew Melbourne
- School of Biomedical Engineering and Imaging, Kings College London, London, UK
| | - Ali Mirjalili
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
| | - Anna-Maria Lydon
- Centre for Advanced MRI, University of Auckland, Auckland, New Zealand
| | - Peter R Stone
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
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10
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Johnson JT, Irfanoglu MO, Manninen E, Ross TJ, Yang Y, Laun FB, Martin J, Topgaard D, Benjamini D. In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.10.561702. [PMID: 37987005 PMCID: PMC10659440 DOI: 10.1101/2023.10.10.561702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency, ω , in addition to the diffusion tensor, D , and relaxation, R 1 , R 2 , correlations. A D ( ω ) - R 1 - R 2 clinical imaging protocol was then introduced, with limited brain coverage and 3 mm3 voxel size, which hinder brain segmentation and future cohort studies. In this study, we introduce an efficient, sparse in vivo MD-MRI acquisition protocol providing whole brain coverage at 2 mm3 voxel size. We demonstrate its feasibility and robustness using a well-defined phantom and repeated scans of five healthy individuals. Additionally, we test different denoising strategies to address the sparse nature of this protocol, and show that efficient MD-MRI encoding design demands a nuanced denoising approach. The MD-MRI framework provides rich information that allows resolving the diffusion frequency dependence into intravoxel components based on their D ( ω ) - R 1 - R 2 distribution, enabling the creation of microstructure-specific maps in the human brain. Our results encourage the broader adoption and use of this new imaging approach for characterizing healthy and pathological tissues.
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Affiliation(s)
- Jessica T.E. Johnson
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
| | - M. Okan Irfanoglu
- Quantitative Medical Imaging Section, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA
| | - Eppu Manninen
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Thomas J. Ross
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, USA
| | - Yihong Yang
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, USA
| | - Frederik B. Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Jan Martin
- Department of Chemistry, Lund University, Lund, Sweden
| | | | - Dan Benjamini
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
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11
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Kundu S, Barsoum S, Ariza J, Nolan AL, Latimer CS, Keene CD, Basser PJ, Benjamini D. Mapping the individual human cortex using multidimensional MRI and unsupervised learning. Brain Commun 2023; 5:fcad258. [PMID: 37953850 PMCID: PMC10638106 DOI: 10.1093/braincomms/fcad258] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 08/31/2023] [Accepted: 10/05/2023] [Indexed: 11/14/2023] Open
Abstract
Human evolution has seen the development of higher-order cognitive and social capabilities in conjunction with the unique laminar cytoarchitecture of the human cortex. Moreover, early-life cortical maldevelopment has been associated with various neurodevelopmental diseases. Despite these connections, there is currently no noninvasive technique available for imaging the detailed cortical laminar structure. This study aims to address this scientific and clinical gap by introducing an approach for imaging human cortical lamina. This method combines diffusion-relaxation multidimensional MRI with a tailored unsupervised machine learning approach that introduces enhanced microstructural sensitivity. This new imaging method simultaneously encodes the microstructure, the local chemical composition and importantly their correlation within complex and heterogenous tissue. To validate our approach, we compared the intra-cortical layers obtained using our ex vivo MRI-based method with those derived from Nissl staining of postmortem human brain specimens. The integration of unsupervised learning with diffusion-relaxation correlation MRI generated maps that demonstrate sensitivity to areal differences in cytoarchitectonic features observed in histology. Significantly, our observations revealed layer-specific diffusion-relaxation signatures, showing reductions in both relaxation times and diffusivities at the deeper cortical levels. These findings suggest a radial decrease in myelin content and changes in cell size and anisotropy, reflecting variations in both cytoarchitecture and myeloarchitecture. Additionally, we demonstrated that 1D relaxation and high-order diffusion MRI scalar indices, even when aggregated and used jointly in a multimodal fashion, cannot disentangle the cortical layers. Looking ahead, our technique holds the potential to open new avenues of research in human neurodevelopment and the vast array of disorders caused by disruptions in neurodevelopment.
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Affiliation(s)
- Shinjini Kundu
- Department of Radiology, The Johns Hopkins Hospital, Baltimore, MD 21287, USA
- Section on Quantitative Imaging and Tissue Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD 20892, USA
| | - Stephanie Barsoum
- Multiscale Imaging and Integrative Biophysics Unit, Laboratory of Behavioral Neuroscience, National Institute on Aging, NIH, Baltimore, MD 21224, USA
| | - Jeanelle Ariza
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA
| | - Amber L Nolan
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA
| | - Caitlin S Latimer
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA
| | - C Dirk Keene
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA
| | - Peter J Basser
- Section on Quantitative Imaging and Tissue Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD 20892, USA
| | - Dan Benjamini
- Multiscale Imaging and Integrative Biophysics Unit, Laboratory of Behavioral Neuroscience, National Institute on Aging, NIH, Baltimore, MD 21224, USA
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12
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Herrera CL, Kim MJ, Do QN, Owen DM, Fei B, Twickler DM, Spong CY. The human placenta project: Funded studies, imaging technologies, and future directions. Placenta 2023; 142:27-35. [PMID: 37634371 DOI: 10.1016/j.placenta.2023.08.067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 08/16/2023] [Accepted: 08/19/2023] [Indexed: 08/29/2023]
Abstract
The placenta plays a critical role in fetal development. It serves as a multi-functional organ that protects and nurtures the fetus during pregnancy. However, despite its importance, the intricacies of placental structure and function in normal and diseased states have remained largely unexplored. Thus, in 2014, the National Institute of Child Health and Human Development launched the Human Placenta Project (HPP). As of May 2023, the HPP has awarded over $101 million in research funds, resulting in 41 funded studies and 459 publications. We conducted a comprehensive review of these studies and publications to identify areas of funded research, advances in those areas, limitations of current research, and continued areas of need. This paper will specifically review the funded studies by the HPP, followed by an in-depth discussion on advances and gaps within placental-focused imaging. We highlight the progress within magnetic reasonance imaging and ultrasound, including development of tools for the assessment of placental function and structure.
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Affiliation(s)
- Christina L Herrera
- Department of Obstetrics and Gynecology, UT Southwestern Medical Center, and Parkland Health Dallas, Texas, USA; Green Center for Reproductive Biology Sciences, UT Southwestern Medical Center, Dallas, TX, USA.
| | - Meredith J Kim
- University of Texas Southwestern Medical School, Dallas, TX, USA
| | - Quyen N Do
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA
| | - David M Owen
- Department of Obstetrics and Gynecology, UT Southwestern Medical Center, and Parkland Health Dallas, Texas, USA; Green Center for Reproductive Biology Sciences, UT Southwestern Medical Center, Dallas, TX, USA
| | - Baowei Fei
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA; Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA; Department of Bioengineering, University of Texas at Dallas, Dallas, TX, USA
| | - Diane M Twickler
- Department of Obstetrics and Gynecology, UT Southwestern Medical Center, and Parkland Health Dallas, Texas, USA; Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Catherine Y Spong
- Department of Obstetrics and Gynecology, UT Southwestern Medical Center, and Parkland Health Dallas, Texas, USA
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13
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Su CQ, Wang BB, Tang WT, Tao C, Zhao P, Pan MH, Hong XN, Hu WT, Dai YM, Shi HB, Lu SS. Diffusion-relaxation correlation spectrum imaging for predicting tumor consistency and gross total resection in patients with pituitary adenomas: a preliminary study. Eur Radiol 2023; 33:6993-7002. [PMID: 37148353 DOI: 10.1007/s00330-023-09694-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 02/17/2023] [Accepted: 03/09/2023] [Indexed: 05/08/2023]
Abstract
OBJECTIVE To evaluate the ability of diffusion-relaxation correlation spectrum imaging (DR-CSI) to predict the consistency and extent of resection (EOR) of pituitary adenomas (PAs). METHODS Forty-four patients with PAs were prospectively enrolled. Tumor consistency was evaluated at surgery as either soft or hard, followed by histological assessment. In vivo DR-CSI was performed and spectra were segmented following to a peak-based strategy into four compartments, designated A (low ADC), B (mediate ADC, short T2), C (mediate ADC, long T2), and D (high ADC). The corresponding volume fractions ([Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text]) along with the ADC and T2 values were calculated and assessed using univariable analysis for discrimination between hard and soft PAs. Predictors of EOR > 95% were analyzed using logistic regression model and receiver-operating-characteristic analysis. RESULTS Tumor consistency was classified as soft (n = 28) or hard (n = 16). Hard PAs presented higher [Formula: see text] (p = 0.001) and lower [Formula: see text] (p = 0.013) than soft PAs, while no significant difference was found in other parameters. [Formula: see text] significantly correlated with the level of collagen content (r = 0.448, p = 0.002). Knosp grade (odds ratio [OR], 0.299; 95% confidence interval [CI], 0.124-0.716; p = 0.007) and [Formula: see text] (OR, 0.834, per 1% increase; 95% CI, 0.731-0.951; p = 0.007) were independently associated with EOR > 95%. A prediction model based on these variables yielded an AUC of 0.934 (sensitivity, 90.9%; specificity, 90.9%), outperforming the Knosp grade alone (AUC, 0.785; p < 0.05). CONCLUSION DR-CSI may serve as a promising tool to predict the consistency and EOR of PAs. CLINICAL RELEVANCE STATEMENT DR-CSI provides an imaging dimension for characterizing tissue microstructure of PAs and may serve as a promising tool to predict the tumor consistency and extent of resection in patients with PAs. KEY POINTS • DR-CSI provides an imaging dimension for characterizing tissue microstructure of PAs by visualizing the volume fraction and corresponding spatial distribution of four compartments ([Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text]). • [Formula: see text] correlated with the level of collagen content and may be the best DR-CSI parameter for discrimination between hard and soft PAs. • The combination of Knosp grade and [Formula: see text] achieved an AUC of 0.934 for predicting the total or near-total resection, outperforming the Knosp grade alone (AUC, 0.785).
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Affiliation(s)
- Chun-Qiu Su
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guang Zhou Road, Gulou District, Nanjing, 210029, Jiangsu Province, China
| | - Bin-Bin Wang
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, Jiangsu Province, China
| | - Wen-Tian Tang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guang Zhou Road, Gulou District, Nanjing, 210029, Jiangsu Province, China
| | - Chao Tao
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, Jiangsu Province, China
| | - Peng Zhao
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, Jiangsu Province, China
| | - Min-Hong Pan
- Department of Pathology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, Jiangsu Province, China
| | - Xun-Ning Hong
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guang Zhou Road, Gulou District, Nanjing, 210029, Jiangsu Province, China
| | - Wen-Tao Hu
- Central Research Institute, MR Collaboration, United Imaging Healthcare, Shanghai, China
| | - Yong-Ming Dai
- Central Research Institute, MR Collaboration, United Imaging Healthcare, Shanghai, China
- School of Biomedical Engineering, Shanghai Tech University, Shanghai, China
| | - Hai-Bin Shi
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guang Zhou Road, Gulou District, Nanjing, 210029, Jiangsu Province, China.
| | - Shan-Shan Lu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guang Zhou Road, Gulou District, Nanjing, 210029, Jiangsu Province, China.
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14
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Aertsen M, Melbourne A, Couck I, King E, Ourselin S, De Keyzer F, Dymarkowski S, Deprest J, Lewi L. Placental differences between uncomplicated and complicated monochorionic diamniotic pregnancies on diffusion and multicompartment Magnetic Resonance Imaging. Placenta 2023; 142:106-114. [PMID: 37683336 DOI: 10.1016/j.placenta.2023.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 08/28/2023] [Accepted: 09/01/2023] [Indexed: 09/10/2023]
Abstract
INTRODUCTION Twin-twin transfusion syndrome (TTTS) and selective fetal growth restriction (sFGR) are common complications in monochorionic diamniotic (MCDA) pregnancies. The Diffusion-rElaxation Combined Imaging for Detailed Placental Evaluation (DECIDE) model, a placental-specific model, separates the T2 values of the fetal and maternal blood from the background tissue and estimates the fetal blood oxygen saturation. This study investigates diffusion and relaxation differences in uncomplicated MCDA pregnancies and MCDA pregnancies complicated by TTTS and sFGR in mid-pregnancy. METHODS This prospective monocentric cohort study included uncomplicated MCDA pregnancies and pregnancies complicated by TTTS and sFGR. We performed MRI with conventional diffusion-weighted imaging (DWI) and combined relaxometry - DWI-intravoxel incoherent motion. DECIDE analysis was used to quantify different parameters within the placenta related to the fetal, placental, and maternal compartments. RESULTS We included 99 pregnancies, of which 46 were uncomplicated, 12 were complicated by sFGR and 41 by TTTS. Conventional DWI did not find differences between or within cohorts. On DECIDE imaging, fetoplacental oxygen saturation was significantly lower in the smaller member of sFGR (p = 0.07) and in both members of TTTS (p = 0.01 and p = 0.004) compared to the uncomplicated pairs. Additionally, average T2 relaxation time was significantly lower in the smaller twin of the sFGR (p = 0.004) compared to the uncomplicated twins (p = 0.03). CONCLUSION Multicompartment functional MRI showed significant differences in several MRI parameters between the placenta of uncomplicated MCDA pregnancies and those complicated by sFGR and TTTS in mid-pregnancy.
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Affiliation(s)
- M Aertsen
- Department of Radiology, University Hospitals KU Leuven, Leuven, Belgium.
| | - A Melbourne
- School of Biomedical Engineering and Imaging Sciences, King's College London, UK; Medical Physics and Biomedical Engineering, University College London, UK
| | - I Couck
- Department of Obstetrics and Gynaecology, University Hospitals Leuven, Leuven, Belgium
| | - E King
- School of Biomedical Engineering and Imaging Sciences, King's College London, UK
| | - S Ourselin
- School of Biomedical Engineering and Imaging Sciences, King's College London, UK; Medical Physics and Biomedical Engineering, University College London, UK
| | - F De Keyzer
- Department of Radiology, University Hospitals KU Leuven, Leuven, Belgium
| | - S Dymarkowski
- Department of Radiology, University Hospitals KU Leuven, Leuven, Belgium
| | - J Deprest
- Department of Obstetrics and Gynaecology, University Hospitals Leuven, Leuven, Belgium; Department of Development and Regeneration, Cluster Woman and Child, Biomedical Sciences, KU Leuven, Leuven, Belgium; Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, Perinatal Imaging and Health, King's College London, King's Health Partners, St.Thomas' Hospital, 1st Floor South Wing, London, SE1 7EH, UK
| | - L Lewi
- Department of Obstetrics and Gynaecology, University Hospitals Leuven, Leuven, Belgium; Department of Development and Regeneration, Cluster Woman and Child, Biomedical Sciences, KU Leuven, Leuven, Belgium
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15
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Cromb D, Slator PJ, De La Fuente M, Price AN, Rutherford M, Egloff A, Counsell SJ, Hutter J. Assessing within-subject rates of change of placental MRI diffusion metrics in normal pregnancy. Magn Reson Med 2023; 90:1137-1150. [PMID: 37183839 PMCID: PMC10962570 DOI: 10.1002/mrm.29665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 03/14/2023] [Accepted: 03/22/2023] [Indexed: 05/16/2023]
Abstract
PURPOSE Studying placental development informs when development is abnormal. Most placental MRI studies are cross-sectional and do not study the extent of individual variability throughout pregnancy. We aimed to explore how diffusion MRI measures of placental function and microstructure vary in individual healthy pregnancies throughout gestation. METHODS Seventy-nine pregnant, low-risk participants (17 scanned twice and 62 scanned once) were included. T2 -weighted anatomical imaging and a combined multi-echo spin-echo diffusion-weighted sequence were acquired at 3 T. Combined diffusion-relaxometry models were performed using both aT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -ADC and a bicompartmentalT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -intravoxel-incoherent-motion (T 2 * IVIM $$ {\mathrm{T}}_2^{\ast}\;\mathrm{IVIM} $$ ) model fit. RESULTS There was a significant decline in placentalT 2 * $$ {\mathrm{T}}_2^{\ast } $$ and ADC (both P < 0.01) over gestation. These declines are consistent in individuals forT 2 * $$ {\mathrm{T}}_2^{\ast } $$ (covariance = -0.47), but not ADC (covariance = -1.04). TheT 2 * IVIM $$ {\mathrm{T}}_2^{\ast}\;\mathrm{IVIM} $$ model identified a consistent decline in individuals over gestation inT 2 * $$ {\mathrm{T}}_2^{\ast } $$ from both the perfusing and diffusing placental compartments, but not in ADC values from either. The placental perfusing compartment fraction increased over gestation (P = 0.0017), but this increase was not consistent in individuals (covariance = 2.57). CONCLUSION Whole placentalT 2 * $$ {\mathrm{T}}_2^{\ast } $$ and ADC values decrease over gestation, although onlyT 2 * $$ {\mathrm{T}}_2^{\ast } $$ values showed consistent trends within subjects. There was minimal individual variation in rates of change ofT 2 * $$ {\mathrm{T}}_2^{\ast } $$ values from perfusing and diffusing placental compartments, whereas trends in ADC values from these compartments were less consistent. These findings probably relate to the increased complexity of the bicompartmentalT 2 * IVIM $$ {\mathrm{T}}_2^{\ast}\;\mathrm{IVIM} $$ model, and differences in how different placental regions evolve at a microstructural level. These placental MRI metrics from low-risk pregnancies provide a useful benchmark for clinical cohorts.
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Affiliation(s)
- Daniel Cromb
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Paddy J. Slator
- Centre for Medical Image Computing, Department of Computer ScienceUniversity College LondonLondonUK
| | - Miguel De La Fuente
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Anthony N. Price
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- Centre for Medical EngineeringSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
| | - Mary Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- MRC Centre for Neurodevelopmental DisordersKing's College LondonLondonUK
| | - Alexia Egloff
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Serena J. Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- Centre for Medical EngineeringSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
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16
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Hutter J, Al-Wakeel A, Kyriakopoulou V, Matthew J, Story L, Rutherford M. Exploring the role of a time-efficient MRI assessment of the placenta and fetal brain in uncomplicated pregnancies and these complicated by placental insufficiency. Placenta 2023; 139:25-33. [PMID: 37295055 DOI: 10.1016/j.placenta.2023.05.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 02/24/2023] [Accepted: 05/20/2023] [Indexed: 06/12/2023]
Abstract
INTRODUCTION The development of placenta and fetal brain are intricately linked. Placental insufficiency is related to poor neonatal outcomes with impacts on neurodevelopment. This study sought to investigate whether simultaneous fast assessment of placental and fetal brain oxygenation using MRI T2* relaxometry can play a complementary role to US and Doppler US. METHODS This study is a retrospective case-control study with uncomplicated pregnancies (n = 99) and cases with placental insufficiency (PI) (n = 49). Participants underwent placental and fetal brain MRI and contemporaneous ultrasound imaging, resulting in quantitative assessment including a combined MRI score called Cerebro-placental-T2*-Ratio (CPTR). This was assessed in comparison with US-derived Cerebro-Placental-Ratio (CPR), placental histopathology, assessed using the Amsterdam criteria [1], and delivery details. RESULTS Pplacental and fetal brain T2* decreased with increasing gestational age in both low and high risk pregnancies and were corrected for gestational-age alsosignificantly decreased in PI. Both CPR and CPTR score were significantly correlated with gestational age at delivery for the entire cohort. CPTR was, however, also correlated independently with gestational age at delivery in the PI cohort. It furthermore showed a correlation to birth-weight-centile in healthy controls. DISCUSSION This study indicates that MR analysis of the placenta and brain may play a complementary role in the investigation of fetal development. The additional correlation to birth-weight-centile in controls may suggest a role in the determination of placental health even in healthy controls. To our knowledge, this is the first study assessing quantitatively both placental and fetal brain development over gestation in a large cohort of low and high risk pregnancies. Future larger prospective studies will include additional cohorts.
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Affiliation(s)
- Jana Hutter
- Centre for the Developing Brain, King's College London, UK; Centre for Medical Engineering, King's College London, UK.
| | - Ayman Al-Wakeel
- GKT School of Medical Education, King's College London, London, UK
| | - Vanessa Kyriakopoulou
- Centre for the Developing Brain, King's College London, UK; Centre for Medical Engineering, King's College London, UK
| | - Jacqueline Matthew
- Centre for the Developing Brain, King's College London, UK; Centre for Medical Engineering, King's College London, UK
| | - Lisa Story
- Centre for the Developing Brain, King's College London, UK; Institute for Women's and Children's Health, King's College London, UK; Fetal Medicine Unit, St Thomas' Hospital, London, UK
| | - Mary Rutherford
- Centre for the Developing Brain, King's College London, UK; Centre for Medical Engineering, King's College London, UK
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17
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Slator PJ, Verdera JA, Tomi-Tricot R, Hajnal JV, Alexander DC, Hutter J. Low-Field Combined Diffusion-Relaxation MRI for Mapping Placenta Structure and Function. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.06.23290983. [PMID: 37333076 PMCID: PMC10274995 DOI: 10.1101/2023.06.06.23290983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Purpose Demonstrating quantitative multi-parametric mapping in the placenta with combined T 2 ∗ -diffusion MRI at low-field (0.55T). Methods We present 57 placental MRI scans performed on a commercially available 0.55T scanner. We acquired the images using a combined T 2 ∗ -diffusion technique scan that simultaneously acquires multiple diffusion preparations and echo times. We processed the data to produce quantitative T 2 ∗ and diffusivity maps using a combined T 2 ∗ -ADC model. We compared the derived quantitative parameters across gestation in healthy controls and a cohort of clinical cases. Results Quantitative parameter maps closely resemble those from previous experiments at higher field strength, with similar trends in T 2 ∗ and ADC against gestational age observed. Conclusion Combined T 2 ∗ -diffusion placental MRI is reliably achievable at 0.55T. The advantages of lower field strength - such as cost, ease of deployment, increased accessibility and patient comfort due to the wider bore, and increased T 2 ∗ for larger dynamic ranges - can support the widespread roll out of placental MRI as an adjunct to ultrasound during pregnancy.
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Affiliation(s)
- Paddy J Slator
- Centre for Medical Image Computing and Department of Computer Science, University College London, London, United Kingdom
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, UK
- School of Computer Science and Informatics, Cardiff University, Cardiff, UK
| | - Jordina Aviles Verdera
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Raphael Tomi-Tricot
- MR Research Collaborations, Siemens Healthcare Limited, Camberley, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Daniel C Alexander
- Centre for Medical Image Computing and Department of Computer Science, University College London, London, United Kingdom
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
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18
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Luo P, Hu W, Xu R, Wang Y, Li X, Jiang L, Chang S, Wu D, Li G, Dai Y. Enabling early detection of knee osteoarthritis using diffusion-relaxation correlation spectrum imaging. Clin Radiol 2023:S0009-9260(23)00224-6. [PMID: 37336674 DOI: 10.1016/j.crad.2023.05.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 05/11/2023] [Accepted: 05/23/2023] [Indexed: 06/21/2023]
Abstract
AIM To present a technique that enables detection of early stage OA of the knee using diffusion-relaxation correlation spectrum imaging (DR-CSI). MATERIALS AND METHODS Fifty-five early osteoarthritis patients (OA, Kellgren-Lawrence [KL] score 1 to 2; mean age, 56.4 years) and 49 healthy volunteers (mean age, 56.7 years) were underwent magnetic resonance imaging (MRI) with T2-mapping and DR-CSI techniques. Maps of mean apparent diffusion coefficient (ADC), T2 relaxation time and volume fraction Vi for DR-CSI compartment i (A, B, C, D) sensitivity, specificity, and positive and negative likelihood ratio (PLR, NLR) were assessed to determine the diagnostic accuracy for detection of early-stage degeneration of knee articular cartilage. The structural abnormalities of articular cartilage were evaluated using modified Whole-Organ MR Imaging Scores (WORMS). RESULTS All intra- and interobserver agreements for DR-CSI compartment volume fractions and modified WORMS of cartilage were excellent. Early OA versus the controls had higher VC, lower VA and VB (p<0.001), but comparable VD (p>0.05). VA, VB and VC had a moderate association with WORMS. No significant correlation was identified between VD and WORMS. VC had better ability than VA,VB, VD, T2 and ADC to discriminate early OA patients from healthy controls (area under the curve, 0.898). Sensitivity, specificity, PLR, and NLR of VC with a cut-off value of 29.9% were 81.8% (95% confidence interval [CI], 69.1-90.9%), 95.9% (86-99.5%), 20.05% (5.13-78.34%), and 0.19% (0.11-0.33%). CONCLUSIONS DR-CSI compartment volume fractions may be sensitive indicators for detecting early-stage degeneration in knee articular cartilage.
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Affiliation(s)
- P Luo
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - W Hu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - R Xu
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - Y Wang
- Department of Gastroenterology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - X Li
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - L Jiang
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - S Chang
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - D Wu
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronics Science, East China Normal University, Shanghai 200062, China
| | - G Li
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China.
| | - Y Dai
- School of Biomedical Engineering, ShanghaiTech University, Shanghai 201210, China.
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19
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Hall M, de Marvao A, Schweitzer R, Cromb D, Colford K, Jandu P, O'Regan DP, Ho A, Price A, Chappell LC, Rutherford MA, Story L, Lamata P, Hutter J. Characterisation of placental, fetal brain and maternal cardiac structure and function in pre-eclampsia using MRI. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.24.23289069. [PMID: 37163073 PMCID: PMC10168502 DOI: 10.1101/2023.04.24.23289069] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Background Pre-eclampsia is a multiorgan disease of pregnancy that has short- and long-term implications for the woman and fetus, whose immediate impact is poorly understood. We present a novel multi-system approach to MRI investigation of pre-eclampsia, with acquisition of maternal cardiac, placental, and fetal brain anatomical and functional imaging. Methods A prospective study was carried out recruiting pregnant women with pre-eclampsia, chronic hypertension, or no medical complications, and a non-pregnant female cohort. All women underwent a cardiac MRI, and pregnant women underwent a fetal-placental MRI. Cardiac analysis for structural, morphological and flow data was undertaken; placenta and fetal brain volumetric and T2* data were obtained. All results were corrected for gestational age. Results Seventy-eight MRIs were obtained during pregnancy. Pregnancies affected by pre-eclampsia demonstrated lower placental and fetal brain T2*. Within the pre-eclampsia group, three placental T2* results were within the normal range, these were the only cases with normal placental histopathology. Similarly, three fetal brain T2* results were within the normal range; these cases had no evidence of cerebral redistribution on fetal Dopplers. Cardiac MRI analysis demonstrated higher left ventricular mass in pre-eclampsia with 3D modelling revealing additional specific characteristics of eccentricity and outflow track remodelling. Conclusions We present the first holistic assessment of the immediate implications of pre-eclampsia on the placenta, maternal heart, and fetal brain. As well as having potential clinical implications for the risk-stratification and management of women with pre-eclampsia, this gives an insight into disease mechanism.
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Affiliation(s)
- Megan Hall
- Department of Women and Children’s Health, King’s College London, UK
- Centre for the Developing Brain, King’s College London, UK
| | - Antonio de Marvao
- Department of Women and Children’s Health, King’s College London, UK
- School of Cardiovascular Medicine, King’s College London, UK
- MRC London Institute of Medical Sciences, Imperial College London, UK
| | - Ronny Schweitzer
- School of Cardiovascular Medicine, King’s College London, UK
- MRC London Institute of Medical Sciences, Imperial College London, UK
| | - Daniel Cromb
- Centre for the Developing Brain, King’s College London, UK
| | | | - Priya Jandu
- GKT School of Medical Education, King’s College London, UK
| | - Declan P O'Regan
- MRC London Institute of Medical Sciences, Imperial College London, UK
| | - Alison Ho
- Department of Women and Children’s Health, King’s College London, UK
- Centre for the Developing Brain, King’s College London, UK
| | - Anthony Price
- Centre for the Developing Brain, King’s College London, UK
- Centre for Medical Engineering, King’s College London, UK
| | - Lucy C. Chappell
- Department of Women and Children’s Health, King’s College London, UK
| | | | - Lisa Story
- Department of Women and Children’s Health, King’s College London, UK
- Centre for the Developing Brain, King’s College London, UK
| | - Pablo Lamata
- Centre for Medical Engineering, King’s College London, UK
| | - Jana Hutter
- Centre for the Developing Brain, King’s College London, UK
- Centre for Medical Engineering, King’s College London, UK
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20
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Sun K, Dan G, Zhong Z, Zhou XJ. Multi-readout DWI with a reduced FOV for studying the coupling between diffusion and T 2 * relaxation in the prostate. Magn Reson Med 2023; 90:250-258. [PMID: 36932652 DOI: 10.1002/mrm.29636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 02/16/2023] [Accepted: 02/23/2023] [Indexed: 03/19/2023]
Abstract
PURPOSE To develop a DWI sequence with multiple readout echo-trains in a single shot (multi-readout DWI) over a reduced FOV, and to demonstrate its ability to achieve high data acquisition efficiency in the study of coupling between diffusion and relaxation in the human prostate. METHODS The proposed multi-readout DWI sequence plays out multiple EPI readout echo-trains after a Stejskal-Tanner diffusion preparation module. Each EPI readout echo-train corresponded to a distinct effective TE. To maintain a high spatial resolution with a relatively short echo-train for each readout, a 2D RF pulse was used to limit the FOV. Experiments were performed on the prostate of six healthy subjects to acquire a set of images with three b values (0, 500, and 1000 s/mm2 ) and three TEs (63.0, 78.8, and 94.6 ms), producing three ADC maps at different TEs and three T 2 * $$ {T}_2^{\ast } $$ maps at different b values. RESULTS Multi-readout DWI enabled a threefold acceleration without compromising the spatial resolution when compared with a conventional single-readout sequence. Images with three b values and three TEs were obtained in 3 min 40 s with an adequate SNR (≥ 26.9). The ADC values (1.45 ± 0.13, 1.52 ± 0.14, and 1.58 ± 0.15 μm 2 / ms $$ {\upmu \mathrm{m}}^2/\mathrm{ms} $$ ; P < 0.01) exhibited an increasing trend as TEs increased (63.0 ms, 78.8 ms, and 94.6 ms), whereas T 2 * $$ {T}_2^{\ast } $$ values (74.78 ± 13.21, 63.21 ± 7.84, and 56.61 ± 5.05 ms; P < 0.01) decreases as the b values increased (0, 500, and 1000 s/mm2 ). CONCLUSION The multi-readout DWI sequence over a reduced FOV provides a time-efficient technique to study the coupling between diffusion and relaxation times.
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Affiliation(s)
- Kaibao Sun
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Guangyu Dan
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, Illinois, USA.,Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Zheng Zhong
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, Illinois, USA.,Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Xiaohong Joe Zhou
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, Illinois, USA.,Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, Illinois, USA.,Departments of Radiology and Neurosurgery, University of Illinois College of Medicine at Chicago, Chicago, Illinois, USA
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21
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Differentiating between normal and fetal growth restriction-complicated placentas: is T2∗ imaging imaging more accurate than conventional diffusion-weighted imaging? Clin Radiol 2023; 78:362-368. [PMID: 36858925 DOI: 10.1016/j.crad.2023.01.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 01/17/2023] [Accepted: 01/26/2023] [Indexed: 02/18/2023]
Abstract
AIM To compare the performance of T2∗ imaging and apparent diffusion coefficient (ADC) in differentiating normal placentas from those complicated by fetal growth restriction (FGR). MATERIALS AND METHODS This prospective study included 28 control and 30 FGR placentas. Gradient-echo magnetic resonance imaging (MRI) at 16 different echo times and diffusion-weighted imaging (b-value of 0 and 800 s/mm2) were performed on all pregnant women using a 3 T MRI system. RESULTS Both T2∗ imaging Z-score and ADC were significantly lower in the FGR placentas (ADC, (1.69 ± 0.19) × 10-3 versus (1.42 ± 0.28) × 10-3 mm2/s, p<0.001; T2∗ imaging Z-score, -0.004 ± 0.95 versus -2.441 ± 1.48, p<0.001). The area under the curve for T2∗ imaging Z-score and ADC was 0.917 (95% confidence interval [CI] = 0.842-0.991) and 0.788 (95% CI = 0.655-0.887), respectively. The performance of T2∗ imaging in differentiating FGR placentas was significantly better than that of ADC (Z = 2.043, p=0.041). CONCLUSION Placental T2∗ imaging was found to be more reliable than ADC in differentiating between normal and FGR placentas.
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22
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Liu F, Hu W, Sun Y, Shen Y, Zhou W, Dai Y, Gu L, Zhang M, Zhou Y. Exploration of Interstitial Fibrosis in Chronic Kidney Disease by Diffusion‐Relaxation Correlation Spectrum
MR
Imaging: A Preliminary Study. J Magn Reson Imaging 2022. [DOI: 10.1002/jmri.28535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Revised: 11/07/2022] [Accepted: 11/08/2022] [Indexed: 11/23/2022] Open
Affiliation(s)
- Fang Liu
- Department of Radiology Renji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai China
| | - Wentao Hu
- Central Research Institute, United Imaging Healthcare Shanghai China
| | - Yawen Sun
- Department of Radiology Renji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai China
| | - Yiwei Shen
- Department of Nephrology Renji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai China
| | - Wenyan Zhou
- Department of Nephrology Renji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai China
| | - Yongming Dai
- Central Research Institute, United Imaging Healthcare Shanghai China
| | - Leyi Gu
- Department of Nephrology Renji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai China
| | - Minfang Zhang
- Department of Nephrology Renji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai China
| | - Yan Zhou
- Department of Radiology Renji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai China
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23
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Benjamini D, Priemer DS, Perl DP, Brody DL, Basser PJ. Mapping astrogliosis in the individual human brain using multidimensional MRI. Brain 2022; 146:1212-1226. [PMID: 35953450 PMCID: PMC9976979 DOI: 10.1093/brain/awac298] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 06/13/2022] [Accepted: 08/06/2022] [Indexed: 11/14/2022] Open
Abstract
There are currently no non-invasive imaging methods available for astrogliosis assessment or mapping in the central nervous system despite its essential role in the response to many disease states, such as infarcts, neurodegenerative conditions, traumatic brain injury and infection. Multidimensional MRI is an increasingly employed imaging modality that maximizes the amount of encoded chemical and microstructural information by probing relaxation (T1 and T2) and diffusion mechanisms simultaneously. Here, we harness the exquisite sensitivity of this imagining modality to derive a signature of astrogliosis and disentangle it from normative brain at the individual level using machine learning. We investigated ex vivo cerebral cortical tissue specimens derived from seven subjects who sustained blast-induced injuries, which resulted in scar-border forming astrogliosis without being accompanied by other types of neuropathological abnormality, and from seven control brain donors. By performing a combined post-mortem radiology and histopathology correlation study we found that astrogliosis induces microstructural and chemical changes that are robustly detected with multidimensional MRI, and which can be attributed to astrogliosis because no axonal damage, demyelination or tauopathy were histologically observed in any of the cases in the study. Importantly, we showed that no one-dimensional T1, T2 or diffusion MRI measurement can disentangle the microscopic alterations caused by this neuropathology. Based on these findings, we developed a within-subject anomaly detection procedure that generates MRI-based astrogliosis biomarker maps ex vivo, which were significantly and strongly correlated with co-registered histological images of increased glial fibrillary acidic protein deposition (r = 0.856, P < 0.0001; r = 0.789, P < 0.0001; r = 0.793, P < 0.0001, for diffusion-T2, diffusion-T1 and T1-T2 multidimensional data sets, respectively). Our findings elucidate the underpinning of MRI signal response from astrogliosis, and the demonstrated high spatial sensitivity and specificity in detecting reactive astrocytes at the individual level, and if reproduced in vivo, will significantly impact neuroimaging studies of injury, disease, repair and aging, in which astrogliosis has so far been an invisible process radiologically.
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Affiliation(s)
- Dan Benjamini
- Correspondence to: Dan Benjamini, PhD National Institutes of Health (NIH), 251 Bayview Blvd., Baltimore, MD 21224, USA E-mail:
| | - David S Priemer
- Department of Pathology, F. Edward Hébert School of Medicine, Uniformed Services University, Bethesda, MD 20814, USA,The Department of Defense/Uniformed Services, University Brain Tissue Repository, Bethesda, MD 20814, USA,The Henry M. Jackson Foundation for the Advancement of Military Medicine (HJF), Bethesda, MD 20817, USA
| | - Daniel P Perl
- Department of Pathology, F. Edward Hébert School of Medicine, Uniformed Services University, Bethesda, MD 20814, USA,The Department of Defense/Uniformed Services, University Brain Tissue Repository, Bethesda, MD 20814, USA
| | - David L Brody
- Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA,Department of Neurology, F. Edward Hébert School of Medicine, Uniformed Services University, Bethesda, MD 20814, USA,Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD 20892, USA
| | - Peter J Basser
- Section on Quantitative Imaging and Tissue Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD 20891, USA,Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
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24
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Rosenberg JT, Grant SC, Topgaard D. Nonparametric 5D D-R 2 distribution imaging with single-shot EPI at 21.1 T: Initial results for in vivo rat brain. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2022; 341:107256. [PMID: 35753184 PMCID: PMC9339475 DOI: 10.1016/j.jmr.2022.107256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 05/27/2022] [Accepted: 06/10/2022] [Indexed: 06/15/2023]
Abstract
In vivo human diffusion MRI is by default performed using single-shot EPI with greater than 50-ms echo times and associated signal loss from transverse relaxation. The individual benefits of the current trends of increasing B0 to boost SNR and employing more advanced signal preparation schemes to improve the specificity for selected microstructural properties eventually may be cancelled by increased relaxation rates at high B0 and echo times with advanced encoding. Here, initial attempts to translate state-of-the-art diffusion-relaxation correlation methods from 3 T to 21.1 T are made to identify hurdles that need to be overcome to fulfill the promises of both high SNR and readily interpretable microstructural information.
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Affiliation(s)
- Jens T Rosenberg
- National High Magnetic Field Laboratory, Florida State University, Tallahassee FL, United States.
| | - Samuel C Grant
- National High Magnetic Field Laboratory, Florida State University, Tallahassee FL, United States; Chemical and Biomedical Engineering, FAMU-FSU College of Engineering, Florida State University, Tallahassee, FL, United States.
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25
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Bouhrara M, Hutter J, Benjamini D. Editorial: Capturing Biological Complexity and Heterogeneity Using Multidimensional MRI. FRONTIERS IN PHYSICS 2022; 10:950928. [PMID: 38031630 PMCID: PMC10686314 DOI: 10.3389/fphy.2022.950928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/01/2023]
Affiliation(s)
- Mustapha Bouhrara
- Magnetic Resonance Physics of Aging and Dementia Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States
| | - Jana Hutter
- Centre for the Developing Brain, King’s College London, London, United Kingdom
- Biomedical Engineering Department, King’s College London, London, United Kingdom
| | - Dan Benjamini
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States
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26
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Hall M, Hutter J, Suff N, Zampieri CA, Tribe RM, Shennan A, Rutherford M, Story L. Antenatal diagnosis of chorioamnionitis: A review of the potential role of fetal and placental imaging. Prenat Diagn 2022; 42:1049-1058. [PMID: 35670265 PMCID: PMC9543023 DOI: 10.1002/pd.6188] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 05/09/2022] [Accepted: 05/17/2022] [Indexed: 11/12/2022]
Abstract
Chorioamnionitis is present in up to 70% of spontaneous preterm births. It is defined as an acute inflammation of the chorion, with or without involvement of the amnion, and is evidence of a maternal immunological response to infection. A fetal inflammatory response can coexist and is diagnosed on placental histopathology postnatally. Fetal inflammatory response syndrome (FIRS) is associated with poorer fetal and neonatal outcomes. The only antenatal diagnostic test is amniocentesis which carries risks of miscarriage or preterm birth. Imaging of the fetal immune system, in particular the thymus and the spleen, and the placenta may give valuable information antenatally regarding the diagnosis of fetal inflammatory response. While ultrasound is largely limited to structural information, MRI can complement this with functional information that may provide insight into the metabolic activities of the fetal immune system and placenta. This review discusses fetal and placental imaging in pregnancies complicated by chorioamnionitis and their potential future use in achieving non-invasive antenatal diagnosis. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Megan Hall
- Department of Women and Children's Health, St Thomas' Hospital, King's College London, London, UK.,Centre for the Developing Brain, St Thomas' Hospital, King's College London, London, UK
| | - Jana Hutter
- Centre for the Developing Brain, St Thomas' Hospital, King's College London, London, UK
| | - Natalie Suff
- Department of Women and Children's Health, St Thomas' Hospital, King's College London, London, UK
| | - Carla Avena Zampieri
- Centre for the Developing Brain, St Thomas' Hospital, King's College London, London, UK
| | - Rachel M Tribe
- Department of Women and Children's Health, St Thomas' Hospital, King's College London, London, UK
| | - Andrew Shennan
- Department of Women and Children's Health, St Thomas' Hospital, King's College London, London, UK
| | - Mary Rutherford
- Centre for the Developing Brain, St Thomas' Hospital, King's College London, London, UK
| | - Lisa Story
- Department of Women and Children's Health, St Thomas' Hospital, King's College London, London, UK.,Centre for the Developing Brain, St Thomas' Hospital, King's College London, London, UK
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27
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Abulnaga SM, Turk EA, Bessmeltsev M, Grant PE, Solomon J, Golland P. Volumetric Parameterization of the Placenta to a Flattened Template. IEEE TRANSACTIONS ON MEDICAL IMAGING 2022; 41:925-936. [PMID: 34784274 PMCID: PMC9069541 DOI: 10.1109/tmi.2021.3128743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
We present a volumetric mesh-based algorithm for parameterizing the placenta to a flattened template to enable effective visualization of local anatomy and function. MRI shows potential as a research tool as it provides signals directly related to placental function. However, due to the curved and highly variable in vivo shape of the placenta, interpreting and visualizing these images is difficult. We address interpretation challenges by mapping the placenta so that it resembles the familiar ex vivo shape. We formulate the parameterization as an optimization problem for mapping the placental shape represented by a volumetric mesh to a flattened template. We employ the symmetric Dirichlet energy to control local distortion throughout the volume. Local injectivity in the mapping is enforced by a constrained line search during the gradient descent optimization. We validate our method using a research study of 111 placental shapes extracted from BOLD MRI images. Our mapping achieves sub-voxel accuracy in matching the template while maintaining low distortion throughout the volume. We demonstrate how the resulting flattening of the placenta improves visualization of anatomy and function. Our code is freely available at https://github.com/mabulnaga/placenta-flattening.
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28
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Liao Y, Sun T, Jiang L, Zhao Z, Liu T, Qian Z, Sun Y, Zhang Y, Wu D. Detecting abnormal placental microvascular flow in maternal and fetal diseases based on flow-compensated and non-compensated intravoxel incoherent motion imaging. Placenta 2022; 119:17-23. [DOI: 10.1016/j.placenta.2022.01.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 01/07/2022] [Accepted: 01/12/2022] [Indexed: 11/28/2022]
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29
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Dong Z, Wang F, Wald L, Setsompop K. SNR
‐efficient distortion‐free diffusion relaxometry imaging using accelerated echo‐train shifted echo‐planar time‐resolving imaging (
ACE‐EPTI
). Magn Reson Med 2022; 88:164-179. [DOI: 10.1002/mrm.29198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 01/23/2022] [Accepted: 01/24/2022] [Indexed: 11/08/2022]
Affiliation(s)
- Zijing Dong
- Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown Massachusetts USA
- Department of Electrical Engineering and Computer Science MIT Cambridge Massachusetts USA
| | - Fuyixue Wang
- Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown Massachusetts USA
- Harvard‐MIT Health Sciences and Technology, MIT Cambridge Massachusetts USA
| | - Lawrence Wald
- Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown Massachusetts USA
- Harvard‐MIT Health Sciences and Technology, MIT Cambridge Massachusetts USA
| | - Kawin Setsompop
- Department of Radiology Stanford University Stanford California USA
- Department of Electrical Engineering Stanford University Stanford California USA
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Ji Y, Hoge WS, Gagoski B, Westin CF, Rathi Y, Ning L. Accelerating joint relaxation-diffusion MRI by integrating time division multiplexing and simultaneous multi-slice (TDM-SMS) strategies. Magn Reson Med 2022; 87:2697-2709. [PMID: 35092081 DOI: 10.1002/mrm.29160] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 12/01/2021] [Accepted: 12/27/2021] [Indexed: 12/12/2022]
Abstract
PURPOSE To accelerate the acquisition of relaxation-diffusion imaging by integrating time-division multiplexing (TDM) with simultaneous multi-slice (SMS) for EPI and evaluate imaging quality and diffusion measures. METHODS The time-division multiplexing (TDM) technique and SMS method were integrated to achieve a high slice-acceleration (e.g., 6×) factor for acquiring relaxation-diffusion MRI. Two variants of the sequence, referred to as TDM3e-SMS and TDM2s-SMS, were developed to simultaneously acquire slice groups with three distinct TEs and two slice groups with the same TE, respectively. Both sequences were evaluated on a 3T scanner with in vivo human brains and compared with standard single-band (SB) -EPI and SMS-EPI using diffusion measures and tractography results. RESULTS Experimental results showed that the TDM3e-SMS sequence with total slice acceleration of 6 (multiplexing factor (MP) = 3 × multi-band factor (MB) = 2) provided similar image intensity and microstructure measures compared to standard SMS-EPI with MB = 2, and yielded less bias in intensity compared to standard SMS-EPI with MB = 4. The three sequences showed a similar positive correlation between TE and mean kurtosis (MK) and a negative correlation between TE and mean diffusivity (MD) in white matter. Multi-fiber tractography also shows consistency of results in TE-dependent measures between different sequences. The TDM2s-SMS sequence (MP = 2, MB = 2) also provided imaging measures similar to standard SMS-EPI sequences (MB = 2) for single-TE diffusion imaging. CONCLUSIONS The TDM-SMS sequence can provide additional 2× to 3× acceleration to SMS without degrading imaging quality. With the significant reduction in scan time, TDM-SMS makes joint relaxation-diffusion MRI a feasible technique in neuroimaging research to investigate new markers of brain disorders.
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Affiliation(s)
- Yang Ji
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Wellcome Centre for Integrative Neuroimaging, FMRIB Division, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - W Scott Hoge
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Borjan Gagoski
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Carl-Fredrik Westin
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Yogesh Rathi
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Lipeng Ning
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
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HANSEN DN, SINDING M, PETERSEN A, CHRISTIANSEN OB, ULDBJERG N, PETERS MDA, FRØKJÆR JB, SØRENSEN A. T2* weighted placental MRI: A biomarker of placental dysfunction in small-for-gestational-age pregnancies. Am J Obstet Gynecol MFM 2022; 4:100578. [DOI: 10.1016/j.ajogmf.2022.100578] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 01/12/2022] [Accepted: 01/27/2022] [Indexed: 11/27/2022]
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Silletta EV, Velasco MI, Monti GA, Acosta RH. Comparison of experimental times in T 1-D and D-T 2 correlation experiments in single-sided NMR. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2022; 334:107112. [PMID: 34864390 DOI: 10.1016/j.jmr.2021.107112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 11/16/2021] [Accepted: 11/22/2021] [Indexed: 06/13/2023]
Abstract
Diffusion-relaxation correlation experiments in nuclear magnetic resonance are a powerful technique for the characterization of fluid dynamics in confined geometries or soft matter, in which relaxation may be either spin-spin (T2) or spin-lattice (T1). The general approach is to acquire a set of bidimensional data in which diffusion is codified by the evolution of the magnetization with either Hahn or stimulated echoes (STE) in the presence of a constant magnetic field gradient. While T2 is codified by a Carr-Purcell-Meiboom-Gil (CPMG) sequence, T1 is either encoded by saturation or inversion-recovery methods. In this work, we analyse the measurement time of diffusion-relaxation times in single-sided NMR and show that T1-D acquisition is always shorter than D-T2. Depending on the hardware characteristics, this time reduction can be up to an order of magnitude. We present analytical calculations and examples in model porous media saturated with water and in a dairy product.
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Affiliation(s)
- Emilia V Silletta
- Universidad Nacional de Córdoba, Facultad de Matemática, Astronomía, Física y Computación, Córdoba, Argentina; CONICET, Instituto de Física Enrique Gaviola (IFEG), Córdoba, Argentina
| | - Manuel I Velasco
- Universidad Nacional de Córdoba, Facultad de Matemática, Astronomía, Física y Computación, Córdoba, Argentina; CONICET, Instituto de Física Enrique Gaviola (IFEG), Córdoba, Argentina
| | - Gustavo A Monti
- Universidad Nacional de Córdoba, Facultad de Matemática, Astronomía, Física y Computación, Córdoba, Argentina; CONICET, Instituto de Física Enrique Gaviola (IFEG), Córdoba, Argentina
| | - Rodolfo H Acosta
- Universidad Nacional de Córdoba, Facultad de Matemática, Astronomía, Física y Computación, Córdoba, Argentina; CONICET, Instituto de Física Enrique Gaviola (IFEG), Córdoba, Argentina.
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Nonparametric D-R 1-R 2 distribution MRI of the living human brain. Neuroimage 2021; 245:118753. [PMID: 34852278 DOI: 10.1016/j.neuroimage.2021.118753] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 11/17/2021] [Accepted: 11/22/2021] [Indexed: 11/23/2022] Open
Abstract
Diffusion-relaxation correlation NMR can simultaneously characterize both the microstructure and the local chemical composition of complex samples that contain multiple populations of water. Recent developments on tensor-valued diffusion encoding and Monte Carlo inversion algorithms have made it possible to transfer diffusion-relaxation correlation NMR from small-bore scanners to clinical MRI systems. Initial studies on clinical MRI systems employed 5D D-R1 and D-R2 correlation to characterize healthy brain in vivo. However, these methods are subject to an inherent bias that originates from not including R2 or R1 in the analysis, respectively. This drawback can be remedied by extending the concept to 6D D-R1-R2 correlation. In this work, we present a sparse acquisition protocol that records all data necessary for in vivo 6D D-R1-R2 correlation MRI across 633 individual measurements within 25 min-a time frame comparable to previous lower-dimensional acquisition protocols. The data were processed with a Monte Carlo inversion algorithm to obtain nonparametric 6D D-R1-R2 distributions. We validated the reproducibility of the method in repeated measurements of healthy volunteers. For a post-therapy glioblastoma case featuring cysts, edema, and partially necrotic remains of tumor, we present representative single-voxel 6D distributions, parameter maps, and artificial contrasts over a wide range of diffusion-, R1-, and R2-weightings based on the rich information contained in the D-R1-R2 distributions.
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Slator PJ, Palombo M, Miller KL, Westin C, Laun F, Kim D, Haldar JP, Benjamini D, Lemberskiy G, de Almeida Martins JP, Hutter J. Combined diffusion-relaxometry microstructure imaging: Current status and future prospects. Magn Reson Med 2021; 86:2987-3011. [PMID: 34411331 PMCID: PMC8568657 DOI: 10.1002/mrm.28963] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 06/25/2021] [Accepted: 07/20/2021] [Indexed: 12/15/2022]
Abstract
Microstructure imaging seeks to noninvasively measure and map microscopic tissue features by pairing mathematical modeling with tailored MRI protocols. This article reviews an emerging paradigm that has the potential to provide a more detailed assessment of tissue microstructure-combined diffusion-relaxometry imaging. Combined diffusion-relaxometry acquisitions vary multiple MR contrast encodings-such as b-value, gradient direction, inversion time, and echo time-in a multidimensional acquisition space. When paired with suitable analysis techniques, this enables quantification of correlations and coupling between multiple MR parameters-such as diffusivity, T 1 , T 2 , and T 2 ∗ . This opens the possibility of disentangling multiple tissue compartments (within voxels) that are indistinguishable with single-contrast scans, enabling a new generation of microstructural maps with improved biological sensitivity and specificity.
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Affiliation(s)
- Paddy J. Slator
- Centre for Medical Image ComputingDepartment of Computer ScienceUniversity College LondonLondonUK
| | - Marco Palombo
- Centre for Medical Image ComputingDepartment of Computer ScienceUniversity College LondonLondonUK
| | - Karla L. Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | - Carl‐Fredrik Westin
- Department of RadiologyBrigham and Women’s HospitalHarvard Medical SchoolBostonMAUSA
| | - Frederik Laun
- Institute of RadiologyUniversity Hospital ErlangenFriedrich‐Alexander‐Universität Erlangen‐Nürnberg (FAU)ErlangenGermany
| | - Daeun Kim
- Ming Hsieh Department of Electrical and Computer EngineeringUniversity of Southern CaliforniaLos AngelesCAUSA
- Signal and Image Processing InstituteUniversity of Southern CaliforniaLos AngelesCAUSA
| | - Justin P. Haldar
- Ming Hsieh Department of Electrical and Computer EngineeringUniversity of Southern CaliforniaLos AngelesCAUSA
- Signal and Image Processing InstituteUniversity of Southern CaliforniaLos AngelesCAUSA
| | - Dan Benjamini
- The Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentBethesdaMDUSA
- The Center for Neuroscience and Regenerative MedicineUniformed Service University of the Health SciencesBethesdaMDUSA
| | | | - Joao P. de Almeida Martins
- Division of Physical Chemistry, Department of ChemistryLund UniversityLundSweden
- Department of Radiology and Nuclear MedicineSt. Olav’s University HospitalTrondheimNorway
| | - Jana Hutter
- Centre for Biomedical EngineeringSchool of Biomedical Engineering and ImagingKing’s College LondonLondonUK
- Centre for the Developing BrainSchool of Biomedical Engineering and ImagingKing’s College LondonLondonUK
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Andescavage N, Limperopoulos C. Emerging placental biomarkers of health and disease through advanced magnetic resonance imaging (MRI). Exp Neurol 2021; 347:113868. [PMID: 34562472 DOI: 10.1016/j.expneurol.2021.113868] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 09/09/2021] [Accepted: 09/19/2021] [Indexed: 12/12/2022]
Abstract
Placental dysfunction is a major cause of fetal demise, fetal growth restriction, and preterm birth, as well as significant maternal morbidity and mortality. Infant survivors of placental dysfunction are at elevatedrisk for lifelong neuropsychiatric morbidity. However, despite the significant consequences of placental disease, there are no clinical tools to directly and non-invasively assess and measure placental function in pregnancy. In this work, we will review advanced MRI techniques applied to the study of the in vivo human placenta in order to better detail placental structure, architecture, and function. We will discuss the potential of these measures to serve as optimal biomarkers of placental dysfunction and review the evidence of these tools in the discrimination of health and disease in pregnancy. Efforts to advance our understanding of in vivo placental development are necessary if we are to optimize healthy pregnancy outcomes and prevent brain injury in successive generations. Current management of many high-risk pregnancies cannot address placental maldevelopment or injury, given the standard tools available to clinicians. Once accurate biomarkers of placental development and function are constructed, the subsequent steps will be to introduce maternal and fetal therapeutics targeting at optimizing placental function. Applying these biomarkers in future studies will allow for real-time assessments of safety and efficacy of novel interventions aimed at improving maternal-fetal well-being.
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Affiliation(s)
- Nickie Andescavage
- Developing Brain Institute, Department of Radiology, Children's National, Washington DC, USA; Department of Neonatology, Children's National, Washington DC, USA
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Hutter J, Jackson L, Ho A, Avena Zampieri C, Hajnal JV, Al-Adnani M, Nanda S, Shennan AH, Tribe RM, Gibbons D, Rutherford MA, Story L. The use of functional placental magnetic resonance imaging for assessment of the placenta after prolonged preterm rupture of the membranes in vivo: A pilot study. Acta Obstet Gynecol Scand 2021; 100:2244-2252. [PMID: 34546571 DOI: 10.1111/aogs.14267] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 08/18/2021] [Accepted: 08/31/2021] [Indexed: 12/29/2022]
Abstract
INTRODUCTION Preterm prelabor rupture of membranes (PPROM) complicates 3% of pregnancies in the UK. Where delivery does not occur spontaneously, expectant management until 37 weeks of gestation is advocated, unless signs of maternal infection develop. However, clinical presentation of maternal infection can be a late sign and injurious fetal inflammatory responses may already have been activated. There is therefore a need for more sensitive markers to aid optimal timing of interventions. At present there is no non-invasive test in clinical practice to assess for infection in the fetal compartment and definitive diagnosis of chorioamnionitis is by histological assessment of the placenta after delivery. This study presents comprehensive functional placental magnetic resonance imaging (MRI) quantification, already used in other organ systems, to assess for infection/inflammation, in women with and without PPROM aiming to explore its use as a biomarker for inflammation within the feto-placental compartment in vivo. MATERIAL AND METHODS Placental MRI scans were performed in a cohort of 12 women (with one having two scans) with PPROM before 34 weeks of gestation (selected because of their high risk of infection), and in a control group of 87 women. Functional placental assessment was performed with magnetic resonance techniques sensitive to changes in the microstructure (diffusion) and tissue composition (relaxometry), with quantification performed both over the entire organ and in regions of interest between the basal and chorionic plate. Placental histology was analyzed after delivery where available. RESULTS Normative evolution of functional magnetic resonance biomarkers over gestation was studied. Cases of inflammation, as assessed by histological presence of chorioamnionitis, and umbilical cord vasculitis with or without funisitis, were associated with lower T2* (mean T2* at 30 weeks 50 ms compared with 58 ms in controls) and higher fractional anisotropy (mean at 30 weeks 0.55 compared with 0.45 in controls). These differences did not reach significance and there was substantial heterogeneity both in T2* and Apparent Diffusivitiy across the cohort. CONCLUSIONS This first exploration of functional placental assessment in a cohort of women with PPROM demonstrates that functional placental MRI can reveal a range of placental changes associated with inflammatory processes. It is a promising tool to gain information and in the future to identify inflammation in vivo, and could therefore assist in improving optimal timing for interventions designed to prevent fetal injury.
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Affiliation(s)
- Jana Hutter
- Centre for Medical Engineering, King's College London, London, UK
| | - Laurence Jackson
- Centre for Medical Engineering, King's College London, London, UK
| | - Alison Ho
- Centre for Medical Engineering, King's College London, London, UK.,Department of Women and Children's Health, School of Life Course Sciences, King's College London, London, UK
| | - Carla Avena Zampieri
- Centre for Medical Engineering, King's College London, London, UK.,Department of Women and Children's Health, School of Life Course Sciences, King's College London, London, UK
| | - Joseph V Hajnal
- Centre for Medical Engineering, King's College London, London, UK
| | | | - Surabhi Nanda
- Peter Gorer Department of Immunobiology, King's College London, London, UK
| | - Andrew H Shennan
- Department of Women and Children's Health, School of Life Course Sciences, King's College London, London, UK
| | - Rachel M Tribe
- Department of Women and Children's Health, School of Life Course Sciences, King's College London, London, UK
| | - Deena Gibbons
- Peter Gorer Department of Immunobiology, King's College London, London, UK
| | | | - Lisa Story
- Department of Women and Children's Health, School of Life Course Sciences, King's College London, London, UK.,Fetal Medicine Unit, St Thomas' Hospital, London, UK
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Benjamini D, Bouhrara M, Komlosh ME, Iacono D, Perl DP, Brody DL, Basser PJ. Multidimensional MRI for Characterization of Subtle Axonal Injury Accelerated Using an Adaptive Nonlocal Multispectral Filter. FRONTIERS IN PHYSICS 2021; 9:737374. [PMID: 37408700 PMCID: PMC10321473 DOI: 10.3389/fphy.2021.737374] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/07/2023]
Abstract
Multidimensional MRI is an emerging approach that simultaneously encodes water relaxation (T1 and T2) and mobility (diffusion) and replaces voxel-averaged values with subvoxel distributions of those MR properties. While conventional (i.e., voxel-averaged) MRI methods cannot adequately quantify the microscopic heterogeneity of biological tissue, using subvoxel information allows to selectively map a specific T1-T2-diffusion spectral range that corresponds to a group of tissue elements. The major obstacle to the adoption of rich, multidimensional MRI protocols for diagnostic or monitoring purposes is the prolonged scan time. Our main goal in the present study is to evaluate the performance of a nonlocal estimation of multispectral magnitudes (NESMA) filter on reduced datasets to limit the total acquisition time required for reliable multidimensional MRI characterization of the brain. Here we focused and reprocessed results from a recent study that identified potential imaging biomarkers of axonal injury pathology from the joint analysis of multidimensional MRI, in particular voxelwise T1-T2 and diffusion-T2 spectra in human Corpus Callosum, and histopathological data. We tested the performance of NESMA and its effect on the accuracy of the injury biomarker maps, relative to the co-registered histological reference. Noise reduction improved the accuracy of the resulting injury biomarker maps, while permitting data reduction of 35.7 and 59.6% from the full dataset for T1-T2 and diffusion-T2 cases, respectively. As successful clinical proof-of-concept applications of multidimensional MRI are continuously being introduced, reliable and robust noise removal and consequent acquisition acceleration would advance the field towards clinically-feasible diagnostic multidimensional MRI protocols.
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Affiliation(s)
- Dan Benjamini
- Section on Quantitative Imaging and Tissue Sciences, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States
- Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
- The Henry M. Jackson Foundation for the Advancement of Military Medicine (HJF), Bethesda, MD, United States
| | - Mustapha Bouhrara
- Magnetic Resonance Physics of Aging and Dementia Unit, National Institute of Aging, National Institutes of Health, Baltimore, MD, United States
| | - Michal E. Komlosh
- Section on Quantitative Imaging and Tissue Sciences, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States
- Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
- The Henry M. Jackson Foundation for the Advancement of Military Medicine (HJF), Bethesda, MD, United States
| | - Diego Iacono
- Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
- The Henry M. Jackson Foundation for the Advancement of Military Medicine (HJF), Bethesda, MD, United States
- Brain Tissue Repository and Neuropathology Program, Uniformed Services University (USU), Bethesda, MD, United States
- Department of Neurology, F. Edward Hébert School of Medicine, Uniformed Services University, Bethesda, MD, United States
- Department of Pathology, F. Edward Hébert School of Medicine, Uniformed Services University, Bethesda, MD, United States
- Department of Anatomy, Physiology and Genetics, F. Edward Hébert School of Medicine, Uniformed Services University, Bethesda, MD, United States
- Neurodegeneration Disorders Clinic, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Daniel P. Perl
- Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
- Brain Tissue Repository and Neuropathology Program, Uniformed Services University (USU), Bethesda, MD, United States
- Department of Pathology, F. Edward Hébert School of Medicine, Uniformed Services University, Bethesda, MD, United States
| | - David L. Brody
- Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
- Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Peter J. Basser
- Section on Quantitative Imaging and Tissue Sciences, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States
- Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
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Benjamini D, Iacono D, Komlosh ME, Perl DP, Brody DL, Basser PJ. Diffuse axonal injury has a characteristic multidimensional MRI signature in the human brain. Brain 2021; 144:800-816. [PMID: 33739417 DOI: 10.1093/brain/awaa447] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 09/11/2020] [Accepted: 10/11/2020] [Indexed: 02/01/2023] Open
Abstract
Axonal injury is a major contributor to the clinical symptomatology in patients with traumatic brain injury. Conventional neuroradiological tools, such as CT and MRI, are insensitive to diffuse axonal injury (DAI) caused by trauma. Diffusion tensor MRI parameters may change in DAI lesions; however, the nature of these changes is inconsistent. Multidimensional MRI is an emerging approach that combines T1, T2, and diffusion, and replaces voxel-averaged values with distributions, which allows selective isolation of specific potential abnormal components. By performing a combined post-mortem multidimensional MRI and histopathology study, we aimed to investigate T1-T2-diffusion changes linked to DAI and to define their histopathological correlates. Corpora callosa derived from eight subjects who had sustained traumatic brain injury, and three control brain donors underwent post-mortem ex vivo MRI at 7 T. Multidimensional, diffusion tensor, and quantitative T1 and T2 MRI data were acquired and processed. Following MRI acquisition, slices from the same tissue were tested for amyloid precursor protein (APP) immunoreactivity to define DAI severity. A robust image co-registration method was applied to accurately match MRI-derived parameters and histopathology, after which 12 regions of interest per tissue block were selected based on APP density, but blind to MRI. We identified abnormal multidimensional T1-T2, diffusion-T2, and diffusion-T1 components that are strongly associated with DAI and used them to generate axonal injury images. We found that compared to control white matter, mild and severe DAI lesions contained significantly larger abnormal T1-T2 component (P = 0.005 and P < 0.001, respectively), and significantly larger abnormal diffusion-T2 component (P = 0.005 and P < 0.001, respectively). Furthermore, within patients with traumatic brain injury the multidimensional MRI biomarkers differentiated normal-appearing white matter from mild and severe DAI lesions, with significantly larger abnormal T1-T2 and diffusion-T2 components (P = 0.003 and P < 0.001, respectively, for T1-T2; P = 0.022 and P < 0.001, respectively, for diffusion-T2). Conversely, none of the conventional quantitative MRI parameters were able to differentiate lesions and normal-appearing white matter. Lastly, we found that the abnormal T1-T2, diffusion-T1, and diffusion-T2 components and their axonal damage images were strongly correlated with quantitative APP staining (r = 0.876, P < 0.001; r = 0.727, P < 0.001; and r = 0.743, P < 0.001, respectively), while producing negligible intensities in grey matter and in normal-appearing white matter. These results suggest that multidimensional MRI may provide non-invasive biomarkers for detection of DAI, which is the pathological substrate for neurological disorders ranging from concussion to severe traumatic brain injury.
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Affiliation(s)
- Dan Benjamini
- Section on Quantitative Imaging and Tissue Sciences, The Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.,Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, USA.,The Henry M. Jackson Foundation for the Advancement of Military Medicine (HJF), Bethesda, MD, USA
| | - Diego Iacono
- Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, USA.,The Henry M. Jackson Foundation for the Advancement of Military Medicine (HJF), Bethesda, MD, USA.,Department of Neurology, F. Edward Hébert School of Medicine, Uniformed Services University (USU), Bethesda, MD, USA.,Department of Pathology, F. Edward Hébert School of Medicine, Uniformed Services University (USU), Bethesda, MD, USA.,Neuroscience Graduate Program, Department of Anatomy, Physiology, and Genetics, F. Edward Hébert School of Medicine, Uniformed Services University (USU), Bethesda, MD, USA.,Motor Neuron Disorders Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Michal E Komlosh
- Section on Quantitative Imaging and Tissue Sciences, The Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.,Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, USA.,The Henry M. Jackson Foundation for the Advancement of Military Medicine (HJF), Bethesda, MD, USA
| | - Daniel P Perl
- Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, USA.,Department of Pathology, F. Edward Hébert School of Medicine, Uniformed Services University (USU), Bethesda, MD, USA
| | - David L Brody
- Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, USA.,Department of Neurology, F. Edward Hébert School of Medicine, Uniformed Services University (USU), Bethesda, MD, USA.,Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Peter J Basser
- Section on Quantitative Imaging and Tissue Sciences, The Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.,Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
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Pietsch M, Ho A, Bardanzellu A, Zeidan AMA, Chappell LC, Hajnal JV, Rutherford M, Hutter J. APPLAUSE: Automatic Prediction of PLAcental health via U-net Segmentation and statistical Evaluation. Med Image Anal 2021; 72:102145. [PMID: 34229190 PMCID: PMC8350147 DOI: 10.1016/j.media.2021.102145] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Revised: 04/26/2021] [Accepted: 06/21/2021] [Indexed: 02/04/2023]
Abstract
PURPOSE Artificial-intelligence population-based automated quantification of placental maturation and health from a rapid functional Magnetic Resonance scan. The placenta plays a crucial role for any successful human pregnancy. Deviations from the normal dynamic maturation throughout gestation are closely linked to major pregnancy complications. Antenatal assessment in-vivo using T2* relaxometry has shown great promise to inform management and possible interventions but clinical translation is hampered by time consuming manual segmentation and analysis techniques based on comparison against normative curves over gestation. METHODS This study proposes a fully automatic pipeline to predict the biological age and health of the placenta based on a free-breathing rapid (sub-30 second) T2* scan in two steps: Automatic segmentation using a U-Net and a Gaussian process regression model to characterize placental maturation and health. These are trained and evaluated on 108 3T MRI placental data sets, the evaluation included 20 high-risk pregnancies diagnosed with pre-eclampsia and/or fetal growth restriction. An independent cohort imaged at 1.5 T is used to assess the generalization of the training and evaluation pipeline. RESULTS Across low- and high-risk groups, automatic segmentation performs worse than inter-rater performance (mean Dice coefficients of 0.58 and 0.68, respectively) but is sufficient for estimating placental mean T2* (0.986 Pearson Correlation Coefficient). The placental health prediction achieves an excellent ability to differentiate cases of placental insufficiency between 27 and 33 weeks. High abnormality scores correlate with low birth weight, premature birth and histopathological findings. Retrospective application on a different cohort imaged at 1.5 T illustrates the ability for direct clinical translation. CONCLUSION The presented automatic pipeline facilitates a fast, robust and reliable prediction of placental maturation. It yields human-interpretable and verifiable intermediate results and quantifies uncertainties on the cohort-level and for individual predictions. The proposed machine-learning pipeline runs in close to real-time and, deployed in clinical settings, has the potential to become a cornerstone of diagnosis and intervention of placental insufficiency. APPLAUSE generalizes to an independent cohort imaged at 1.5 T, demonstrating robustness to different operational and clinical environments.
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Affiliation(s)
- Maximilian Pietsch
- Centre for Medical Engineering, King's College London, London, UK; Centre for the Developing Brain, King's College London, London, UK.
| | - Alison Ho
- Department of Women and Children's Health, King's College London, London, UK
| | - Alessia Bardanzellu
- Centre for Medical Engineering, King's College London, London, UK; Centre for the Developing Brain, King's College London, London, UK
| | - Aya Mutaz Ahmad Zeidan
- Centre for Medical Engineering, King's College London, London, UK; Centre for the Developing Brain, King's College London, London, UK
| | - Lucy C Chappell
- Department of Women and Children's Health, King's College London, London, UK
| | - Joseph V Hajnal
- Centre for Medical Engineering, King's College London, London, UK; Centre for the Developing Brain, King's College London, London, UK
| | - Mary Rutherford
- Centre for Medical Engineering, King's College London, London, UK; Centre for the Developing Brain, King's College London, London, UK
| | - Jana Hutter
- Centre for Medical Engineering, King's College London, London, UK; Centre for the Developing Brain, King's College London, London, UK
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Srinivasan V, Melbourne A, Oyston C, James JL, Clark AR. Multiscale and multimodal imaging of utero-placental anatomy and function in pregnancy. Placenta 2021; 112:111-122. [PMID: 34329969 DOI: 10.1016/j.placenta.2021.07.290] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Revised: 06/09/2021] [Accepted: 07/19/2021] [Indexed: 12/12/2022]
Abstract
Placental structures at the nano-, micro-, and macro scale each play important roles in contributing to its function. As such, quantifying the dynamic way in which placental structure evolves during pregnancy is critical to both clinical diagnosis of pregnancy disorders, and mechanistic understanding of their pathophysiology. Imaging the placenta, both exvivo and invivo, can provide a wealth of structural and/or functional information. This review outlines how imaging across modalities and spatial scales can ultimately come together to improve our understanding of normal and pathological pregnancies. We discuss how imaging technologies are evolving to provide new insights into placental physiology across disciplines, and how advanced computational algorithms can be used alongside state-of-the-art imaging to obtain a holistic view of placental structure and its associated functions to improve our understanding of placental function in health and disease.
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Affiliation(s)
| | - Andrew Melbourne
- School of Biomedical Engineering & Imaging Sciences, Kings College London, UK
| | - Charlotte Oyston
- Department of Obstetrics and Gynaecology, Faculty of Medical and Health Sciences, University of Auckland, New Zealand
| | - Joanna L James
- Department of Obstetrics and Gynaecology, Faculty of Medical and Health Sciences, University of Auckland, New Zealand
| | - Alys R Clark
- Auckland Bioengineering Institute, University of Auckland, New Zealand
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Hutter J, Ho A, Jackson LH, Slator PJ, Chappell LC, Hajnal JV, Rutherford MA. An efficient and combined placental T 1 -ADC acquisition in pregnancies with and without pre-eclampsia. Magn Reson Med 2021; 86:2684-2691. [PMID: 34268807 DOI: 10.1002/mrm.28809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 03/15/2021] [Accepted: 03/26/2021] [Indexed: 11/07/2022]
Abstract
PURPOSE To provide a new approach to jointly assess microstructural and molecular properties of the human placenta in vivo fast and efficiently and to present initial evidence in cohorts of healthy pregnancies and those affected by pre-eclampsia. METHODS Slice and diffusion preparation shuffling, built on the previously proposed ZEBRA method, is presented as a robust and fast way to obtain T 1 and apparent diffusivity coefficient (ADC) values. Joint modeling and evaluation is performed on a cohort of healthy and pre-eclamptic participants at 3T. RESULTS The datasets show the ability to obtain robust and fast T 1 -ADC measurements. Significant decay over gestation in T 1 (-11 ms/week, P < . 05 ) and a trend toward significance in ADC (-0.23 mm/ s 2 /week, P = .08) values can be observed in a control cohort. Values for the pre-eclamptic pregnancies show a negative trend for both ADC and T 1 . CONCLUSIONS The presented sequence allows the simultaneous acquisition of 2 of the most promising quantitative parameters to study placental insufficiency-identified individually as relevant in previous studies-in under 2 minutes. This allows dynamic assessment of physiological processes, reduced inconsistency in spatial comparisons due to reduced motion artefacts and opens novel avenues for analysis. Initial results in pre-eclamptic placentas, with depicted changes in both ADC and T 1 , illustrate its potential to identify cases of placental insufficiency. Future work will focus on expanding the field-of-view using multi-band acceleration techniques and the expansion to larger and more diverse patient groups.
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Affiliation(s)
- Jana Hutter
- Center for Medical Engineering, King's College London, London, UK
- Center for the Developing Brain, School of Biomedical Engineering and Imaging, King's College London, London, UK
| | - Alison Ho
- Academic Women's Health Department, King's College London, London, UK
| | - Laurence H Jackson
- Center for Medical Engineering, King's College London, London, UK
- Center for the Developing Brain, School of Biomedical Engineering and Imaging, King's College London, London, UK
| | - Paddy J Slator
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Lucy C Chappell
- Academic Women's Health Department, King's College London, London, UK
| | - Joseph V Hajnal
- Center for Medical Engineering, King's College London, London, UK
- Center for the Developing Brain, School of Biomedical Engineering and Imaging, King's College London, London, UK
| | - Mary A Rutherford
- Center for Medical Engineering, King's College London, London, UK
- Center for the Developing Brain, School of Biomedical Engineering and Imaging, King's College London, London, UK
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He J, Chen Z, Chen C, Liu P. Comparative study of placental T2* and intravoxel incoherent motion in the prediction of fetal growth restriction. Placenta 2021; 111:47-53. [PMID: 34157440 DOI: 10.1016/j.placenta.2021.06.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 04/30/2021] [Accepted: 06/13/2021] [Indexed: 11/24/2022]
Abstract
INTRODUCTION Both transverse relaxation time (T2*) and intravoxel incoherent motion (IVIM) on magnetic resonance imaging (MRI) are promising for discriminating fetal growth restriction (FGR). We aimed to compare the utility of these two parameters and their combination in the same cohort. METHODS Twenty-seven FGR and 24 control pregnancies after 28 weeks of gestation in which both T2* and IVIM scans were performed on a 3.0 T MRI were recruited. We compared the T2* Z-score, perfusion fraction (f), diffusion coefficient (D) and pseudodiffusion coefficient (D*) between groups. Binary logistic regression analysis and areas under the curve (AUCs) with receiver operating characteristic (ROC) curve were used to evaluate the diagnostic efficacy of these parameters and their combination. RESULTS Compared with normal pregnancies, T2* Z-score (0.036 ± 0.95 vs. -2.479 ± 1.56, p < 0.001), f (0.2753 ± 0.035 vs. 0.3304 ± 0.035, p < 0.001), D* (48279.82 ± 7497.36 μm2/s vs. 56167.92 ± 8549.87 μm2/s, p = 0.001) and D (1664.32 ± 288.53 μm2/s vs. 1887.15 ± 204.08 μm2/s, p = 0.002) were significantly decreased in FGR pregnancies. However, only AUC(T2* Z-score) (0.903) and AUC(f) (0.873) were good predictors of FGR. The AUC(T2* Z-score-IVIM) (0.937), calculated with the combination of T2* Z-score and f, was similar to AUC(T2* Z-score) and ACU(f). DISCUSSION Both T2* and f were effective in discriminating FGR. However, the combination of the two parameters did not further improve diagnostic efficacy. We suggest that T2* might be more suitable for evaluating placental dysfunction, as it is fast to obtain and easy to measure.
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Affiliation(s)
- Junshen He
- Department of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Zhao Chen
- Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Chunlin Chen
- Department of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
| | - Ping Liu
- Department of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
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Avram AV, Sarlls JE, Basser PJ. Whole-Brain Imaging of Subvoxel T1-Diffusion Correlation Spectra in Human Subjects. Front Neurosci 2021; 15:671465. [PMID: 34177451 PMCID: PMC8232058 DOI: 10.3389/fnins.2021.671465] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 05/14/2021] [Indexed: 12/12/2022] Open
Abstract
T1 relaxation and water mobility generate eloquent MRI tissue contrasts with great diagnostic value in many neuroradiological applications. However, conventional methods do not adequately quantify the microscopic heterogeneity of these important biophysical properties within a voxel, and therefore have limited biological specificity. We describe a new correlation spectroscopic (CS) MRI method for measuring how T1 and mean diffusivity (MD) co-vary in microscopic tissue environments. We develop a clinical pulse sequence that combines inversion recovery (IR) with single-shot isotropic diffusion encoding (IDE) to efficiently acquire whole-brain MRIs with a wide range of joint T1-MD weightings. Unlike conventional diffusion encoding, the IDE preparation ensures that all subvoxel water pools are weighted by their MDs regardless of the sizes, shapes, and orientations of their corresponding microscopic diffusion tensors. Accordingly, IR-IDE measurements are well-suited for model-free, quantitative spectroscopic analysis of microscopic water pools. Using numerical simulations, phantom experiments, and data from healthy volunteers we demonstrate how IR-IDE MRIs can be processed to reconstruct maps of two-dimensional joint probability density functions, i.e., correlation spectra, of subvoxel T1-MD values. In vivo T1-MD spectra show distinct cerebrospinal fluid and parenchymal tissue components specific to white matter, cortical gray matter, basal ganglia, and myelinated fiber pathways, suggesting the potential for improved biological specificity. The one-dimensional marginal distributions derived from the T1-MD correlation spectra agree well with results from other relaxation spectroscopic and quantitative MRI studies, validating the T1-MD contrast encoding and the spectral reconstruction. Mapping subvoxel T1-diffusion correlations in patient populations may provide a more nuanced, comprehensive, sensitive, and specific neuroradiological assessment of the non-specific changes seen on fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted MRIs (DWIs) in cancer, ischemic stroke, or brain injury.
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Affiliation(s)
- Alexandru V Avram
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States.,Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, United States
| | - Joelle E Sarlls
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Peter J Basser
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States
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Reymbaut A, Critchley J, Durighel G, Sprenger T, Sughrue M, Bryskhe K, Topgaard D. Toward nonparametric diffusion- T1 characterization of crossing fibers in the human brain. Magn Reson Med 2021; 85:2815-2827. [PMID: 33301195 PMCID: PMC7898694 DOI: 10.1002/mrm.28604] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Revised: 10/26/2020] [Accepted: 10/27/2020] [Indexed: 12/24/2022]
Abstract
PURPOSE To estimate T 1 for each distinct fiber population within voxels containing multiple brain tissue types. METHODS A diffusion- T 1 correlation experiment was carried out in an in vivo human brain using tensor-valued diffusion encoding and multiple repetition times. The acquired data were inverted using a Monte Carlo algorithm that retrieves nonparametric distributions P ( D , R 1 ) of diffusion tensors and longitudinal relaxation rates R 1 = 1 / T 1 . Orientation distribution functions (ODFs) of the highly anisotropic components of P ( D , R 1 ) were defined to visualize orientation-specific diffusion-relaxation properties. Finally, Monte Carlo density-peak clustering (MC-DPC) was performed to quantify fiber-specific features and investigate microstructural differences between white matter fiber bundles. RESULTS Parameter maps corresponding to P ( D , R 1 ) 's statistical descriptors were obtained, exhibiting the expected R 1 contrast between brain tissue types. Our ODFs recovered local orientations consistent with the known anatomy and indicated differences in R 1 between major crossing fiber bundles. These differences, confirmed by MC-DPC, were in qualitative agreement with previous model-based works but seem biased by the limitations of our current experimental setup. CONCLUSIONS Our Monte Carlo framework enables the nonparametric estimation of fiber-specific diffusion- T 1 features, thereby showing potential for characterizing developmental or pathological changes in T 1 within a given fiber bundle, and for investigating interbundle T 1 differences.
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Affiliation(s)
- Alexis Reymbaut
- Department of Physical ChemistryLund UniversityLundSweden
- Random Walk Imaging ABLundSweden
| | | | | | - Tim Sprenger
- Karolinska InstituteStockholmSweden
- GE HealthcareStockholmSweden
| | | | | | - Daniel Topgaard
- Department of Physical ChemistryLund UniversityLundSweden
- Random Walk Imaging ABLundSweden
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Slator PJ, Hutter J, Marinescu RV, Palombo M, Jackson LH, Ho A, Chappell LC, Rutherford M, Hajnal JV, Alexander DC. Data-Driven multi-Contrast spectral microstructure imaging with InSpect: INtegrated SPECTral component estimation and mapping. Med Image Anal 2021; 71:102045. [PMID: 33934005 PMCID: PMC8543043 DOI: 10.1016/j.media.2021.102045] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 02/08/2021] [Accepted: 03/16/2021] [Indexed: 11/19/2022]
Abstract
Unsupervised learning technique for spectroscopic analysis of quantitative MRI. Shares information across voxels to improve estimation of multi-dimensional or single-dimensional spectra. Spectral maps are dramatically improved compared to existing approaches. Can potentially identify and map tissue environments; in placental diffusion-relaxometry MRI we demonstrate that it identifies components that correspond to distinct tissue types.
We introduce and demonstrate an unsupervised machine learning technique for spectroscopic analysis of quantitative MRI experiments. Our algorithm supports estimation of one-dimensional spectra from single-contrast data, and multidimensional correlation spectra from simultaneous multi-contrast data. These spectrum-based approaches allow model-free investigation of tissue properties, but require regularised inversion of a Laplace transform or Fredholm integral, which is an ill-posed calculation. Here we present a method that addresses this limitation in a data-driven way. The algorithm simultaneously estimates a canonical basis of spectral components and voxelwise maps of their weightings, thereby pooling information across whole images to regularise the ill-posed problem. We show in simulations that our algorithm substantially outperforms current voxelwise spectral approaches. We demonstrate the method on multi-contrast diffusion-relaxometry placental MRI scans, revealing anatomically-relevant sub-structures, and identifying dysfunctional placentas. Our algorithm vastly reduces the data required to reliably estimate spectra, opening up the possibility of quantitative MRI spectroscopy in a wide range of new applications. Our InSpect code is available at github.com/paddyslator/inspect.
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Affiliation(s)
- Paddy J Slator
- Centre for Medical Image Computing, Department of Computer Science, University College London, UK.
| | - Jana Hutter
- Centre for the Developing Brain, Kings College London, London, UK; Biomedical Engineering Department, Kings College London, London, UK
| | - Razvan V Marinescu
- Centre for Medical Image Computing, Department of Computer Science, University College London, UK
| | - Marco Palombo
- Centre for Medical Image Computing, Department of Computer Science, University College London, UK
| | - Laurence H Jackson
- Centre for the Developing Brain, Kings College London, London, UK; Biomedical Engineering Department, Kings College London, London, UK
| | - Alison Ho
- Women's Health Department, King's College London, London, UK
| | - Lucy C Chappell
- Women's Health Department, King's College London, London, UK
| | - Mary Rutherford
- Centre for the Developing Brain, Kings College London, London, UK
| | - Joseph V Hajnal
- Centre for the Developing Brain, Kings College London, London, UK; Biomedical Engineering Department, Kings College London, London, UK
| | - Daniel C Alexander
- Centre for Medical Image Computing, Department of Computer Science, University College London, UK
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de Almeida Martins JP, Tax CMW, Reymbaut A, Szczepankiewicz F, Chamberland M, Jones DK, Topgaard D. Computing and visualising intra-voxel orientation-specific relaxation-diffusion features in the human brain. Hum Brain Mapp 2021; 42:310-328. [PMID: 33022844 PMCID: PMC7776010 DOI: 10.1002/hbm.25224] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 09/04/2020] [Accepted: 09/22/2020] [Indexed: 12/12/2022] Open
Abstract
Diffusion MRI techniques are used widely to study the characteristics of the human brain connectome in vivo. However, to resolve and characterise white matter (WM) fibres in heterogeneous MRI voxels remains a challenging problem typically approached with signal models that rely on prior information and constraints. We have recently introduced a 5D relaxation-diffusion correlation framework wherein multidimensional diffusion encoding strategies are used to acquire data at multiple echo-times to increase the amount of information encoded into the signal and ease the constraints needed for signal inversion. Nonparametric Monte Carlo inversion of the resulting datasets yields 5D relaxation-diffusion distributions where contributions from different sub-voxel tissue environments are separated with minimal assumptions on their microscopic properties. Here, we build on the 5D correlation approach to derive fibre-specific metrics that can be mapped throughout the imaged brain volume. Distribution components ascribed to fibrous tissues are resolved, and subsequently mapped to a dense mesh of overlapping orientation bins to define a smooth orientation distribution function (ODF). Moreover, relaxation and diffusion measures are correlated to each independent ODF coordinate, thereby allowing the estimation of orientation-specific relaxation rates and diffusivities. The proposed method is tested on a healthy volunteer, where the estimated ODFs were observed to capture major WM tracts, resolve fibre crossings, and, more importantly, inform on the relaxation and diffusion features along with distinct fibre bundles. If combined with fibre-tracking algorithms, the methodology presented in this work has potential for increasing the depth of characterisation of microstructural properties along individual WM pathways.
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Affiliation(s)
- João P. de Almeida Martins
- Division of Physical Chemistry, Department of ChemistryLund UniversityLundSweden
- Random Walk Imaging ABLundSweden
| | - Chantal M. W. Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff UniversityCardiffUK
- University Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
| | - Alexis Reymbaut
- Division of Physical Chemistry, Department of ChemistryLund UniversityLundSweden
- Random Walk Imaging ABLundSweden
| | - Filip Szczepankiewicz
- Department of Clinical SciencesLund UniversityLundSweden
- Harvard Medical SchoolBostonMassachusettsUSA
- Radiology, Brigham and Women's HospitalBostonMassachusettsUSA
| | - Maxime Chamberland
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff UniversityCardiffUK
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff UniversityCardiffUK
- Mary MacKillop Institute for Health Research, Australian Catholic UniversityMelbourneAustralia
| | - Daniel Topgaard
- Division of Physical Chemistry, Department of ChemistryLund UniversityLundSweden
- Random Walk Imaging ABLundSweden
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Ho A, Hutter J, Slator P, Jackson L, Seed PT, Mccabe L, Al-Adnani M, Marnerides A, George S, Story L, Hajnal JV, Rutherford M, Chappell LC. Placental magnetic resonance imaging in chronic hypertension: A case-control study. Placenta 2021; 104:138-145. [PMID: 33341490 PMCID: PMC7921773 DOI: 10.1016/j.placenta.2020.12.006] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 11/28/2020] [Accepted: 12/09/2020] [Indexed: 11/21/2022]
Abstract
INTRODUCTION We aimed to explore the use of magnetic resonance imaging (MRI) in vivo as a tool to elucidate the placental phenotype in women with chronic hypertension. METHODS In case-control study, women with chronic hypertension and those with uncomplicated pregnancies were imaged using either a 3T Achieva or 1.5T Ingenia scanner. T2-weighted images, diffusion weighted and T1/T2* relaxometry data was acquired. Placental T2*, T1 and apparent diffusion coefficient (ADC) maps were calculated. RESULTS 129 women (43 with chronic hypertension and 86 uncomplicated pregnancies) were imaged at a median of 27.7 weeks' gestation (interquartile range (IQR) 23.9-32.1) and 28.9 (IQR 26.1-32.9) respectively. Visual analysis of T2-weighted imaging demonstrated placentae to be either appropriate for gestation or to have advanced lobulation in women with chronic hypertension, resulting in a greater range of placental mean T2* values for a given gestation, compared to gestation-matched controls. Both skew and kurtosis (derived from histograms of T2* values across the whole placenta) increased with advancing gestational age at imaging in healthy pregnancies; women with chronic hypertension had values overlapping those in the control group range. Upon visual assessment, the mean ADC declined in the third trimester, with a corresponding decline in placental mean T2* values and showed an overlap of values between women with chronic hypertension and the control group. DISCUSSION A combined placental MR examination including T2 weighted imaging, T2*, T1 mapping and diffusion imaging demonstrates varying placental phenotypes in a cohort of women with chronic hypertension, showing overlap with the control group.
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Affiliation(s)
- Alison Ho
- Department of Women and Children's Health, School of Life Course Sciences, King's College London, London, United Kingdom.
| | - Jana Hutter
- Centre for the Developing Brain, King's College London, London, United Kingdom; Biomedical Engineering Department, King's College London, London, United Kingdom
| | - Paddy Slator
- Centre for Medical Image Computing and Department of Computer Science, University College London, London, United Kingdom
| | - Laurence Jackson
- Centre for the Developing Brain, King's College London, London, United Kingdom; Biomedical Engineering Department, King's College London, London, United Kingdom
| | - Paul T Seed
- Department of Women and Children's Health, School of Life Course Sciences, King's College London, London, United Kingdom
| | - Laura Mccabe
- Centre for the Developing Brain, King's College London, London, United Kingdom
| | - Mudher Al-Adnani
- Department of Cellular Pathology, Guy's and St Thomas' Hospital, London, United Kingdom
| | - Andreas Marnerides
- Department of Cellular Pathology, Guy's and St Thomas' Hospital, London, United Kingdom
| | - Simi George
- Department of Cellular Pathology, Guy's and St Thomas' Hospital, London, United Kingdom
| | - Lisa Story
- Department of Women and Children's Health, School of Life Course Sciences, King's College London, London, United Kingdom
| | - Joseph V Hajnal
- Centre for the Developing Brain, King's College London, London, United Kingdom; Biomedical Engineering Department, King's College London, London, United Kingdom
| | - Mary Rutherford
- Centre for the Developing Brain, King's College London, London, United Kingdom
| | - Lucy C Chappell
- Department of Women and Children's Health, School of Life Course Sciences, King's College London, London, United Kingdom
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Fair MJ, Liao C, Manhard MK, Setsompop K. Diffusion-PEPTIDE: Distortion- and blurring-free diffusion imaging with self-navigated motion-correction and relaxometry capabilities. Magn Reson Med 2020; 85:2417-2433. [PMID: 33314281 DOI: 10.1002/mrm.28579] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 10/11/2020] [Accepted: 10/12/2020] [Indexed: 12/13/2022]
Abstract
PURPOSE To implement the time-resolved relaxometry PEPTIDE technique into a diffusion acquisition to provide self-navigated, distortion- and blurring-free diffusion imaging that is robust to motion, while simultaneously providing T2 and T 2 ∗ mapping. THEORY AND METHODS The PEPTIDE readout was implemented into a spin-echo diffusion acquisition, enabling reconstruction of a time-series of T2 - and T 2 ∗ -weighted images, free from conventional echo planar imaging (EPI) distortion and blurring, for each diffusion-encoding. Robustness of PEPTIDE to motion and shot-to-shot phase variation was examined through a deliberate motion-corrupted diffusion experiment. Two diffusion-relaxometry in vivo brain protocols were also examined: (1)1 × 1 × 3 mm3 across 32 diffusion directions in 20 min, (2)1.5 × 1.5 × 3.0 mm3 across 6 diffusion-weighted images in 3.4 min. T2 , T 2 ∗ , and diffusion parameter maps were calculated from these data. As initial exploration of the rich diffusion-relaxometry data content for use in multi-compartment modeling, PEPTIDE data were acquired of a gadolinium-doped asparagus phantom. These datasets contained two compartments with different relaxation parameters and different diffusion orientation properties, and T2 relaxation variations across these diffusion directions were explored. RESULTS Diffusion-PEPTIDE showed the capability to provide high quality diffusion images and T2 and T 2 ∗ maps from both protocols. The reconstructions were distortion-free, avoided potential resolution losses exceeding 100% in equivalent EPI acquisitions, and showed tolerance to nearly 30° of rotational motion. Expected variation in T2 values as a function of diffusion direction was observed in the two-compartment asparagus phantom (P < .01), demonstrating potential to explore diffusion-PEPTIDE data for multi-compartment modeling. CONCLUSIONS Diffusion-PEPTIDE provides highly robust diffusion and relaxometry data and offers potential for future applications in diffusion-relaxometry multi-compartment modeling.
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Affiliation(s)
- Merlin J Fair
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Congyu Liao
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Mary Kate Manhard
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA.,Harvard-MIT Health Sciences and Technology, MIT, Cambridge, Massachusetts, USA
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49
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Song YQ, Xiao L. Optimization of multidimensional MR data acquisition for relaxation and diffusion. NMR IN BIOMEDICINE 2020; 33:e4238. [PMID: 32012371 DOI: 10.1002/nbm.4238] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 10/17/2019] [Accepted: 11/07/2019] [Indexed: 06/10/2023]
Abstract
Multidimensional MR experiments of relaxation and diffusion have been successful for material characterization and have attracted attention recently for biomedical applications. However, such experiments typically require many scans of data acquisition and are time-consuming. This work discusses a method for systematic optimization of the pulse-sequence parameters to obtain optimal resolution within the experimental conditions, such as the number of acquisitions. Other optimization goals can also be incorporated in this framework.
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Affiliation(s)
- Yi-Qiao Song
- Schlumberger-Doll Research, Cambridge, Massachusetts, USA
| | - Lizhi Xiao
- State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, China
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50
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Zibetti MVW, Helou ES, Sharafi A, Regatte RR. Fast multicomponent 3D-T 1ρ relaxometry. NMR IN BIOMEDICINE 2020; 33:e4318. [PMID: 32359000 PMCID: PMC7606711 DOI: 10.1002/nbm.4318] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 03/10/2020] [Accepted: 04/05/2020] [Indexed: 05/06/2023]
Abstract
NMR relaxometry can provide information about the relaxation of the magnetization in different tissues, increasing our understanding of molecular dynamics and biochemical composition in biological systems. In general, tissues have complex and heterogeneous structures composed of multiple pools. As a result, bulk magnetization returns to its original state with different relaxation times, in a multicomponent relaxation. Recovering the distribution of relaxation times in each voxel is a difficult inverse problem; it is usually unstable and requires long acquisition time, especially on clinical scanners. MRI can also be viewed as an inverse problem, especially when compressed sensing (CS) is used. The solution of these two inverse problems, CS and relaxometry, can be obtained very efficiently in a synergistically combined manner, leading to a more stable multicomponent relaxometry obtained with short scan times. In this paper, we will discuss the details of this technique from the viewpoint of inverse problems.
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Affiliation(s)
- Marcelo V W Zibetti
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, US
| | - Elias S Helou
- Institute of Mathematical Sciences and Computation, University of São Paulo, São Carlos, SP, Brazil
| | - Azadeh Sharafi
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, US
| | - Ravinder R Regatte
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, US
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