Journal of Magnetic Resonance Imaging最新文献

{"title":"Critical Omissions Compromise Internal Validity in Jugular Vein Compression Collar Studies.","authors":"James M Smoliga, Zachary O Binney","doi":"10.1002/jmri.29650","DOIUrl":"https://doi.org/10.1002/jmri.29650","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142558066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial for \"Improving Accuracy and Reproducibility of Cartilage T₂ Mapping in the OAI Dataset Through Extended Phase Graph Modeling\".","authors":"Rong Lu, Kaibo Tang, Weijun Tang","doi":"10.1002/jmri.29647","DOIUrl":"https://doi.org/10.1002/jmri.29647","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142545935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial for \"Repeatability, Reproducibility and Observer Variability of Cortical T1 Mapping for Renal Tissue Characterization\".","authors":"Ravikanth Balaji, Reem Al Mazroui, Rashid Al Sukaiti","doi":"10.1002/jmri.29636","DOIUrl":"https://doi.org/10.1002/jmri.29636","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142545936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial for \"3D Vortex-Energetics in the Left Pulmonary Artery for Differentiating Pulmonary Arterial Hypertension and Pulmonary Venous Hypertension Groups Using 4D Flow MRI\".","authors":"Liwei Hu, Luguang Chen","doi":"10.1002/jmri.29642","DOIUrl":"https://doi.org/10.1002/jmri.29642","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142545934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterization of Brain Abnormalities in Lactational Neurodevelopmental Poly I:C Rat Model of Schizophrenia and Depression Using Machine-Learning and Quantitative MRI.","authors":"Rona Haker, Coral Helft, Emilya Natali Shamir, Moni Shahar, Hadas Solomon, Noam Omer, Tamar Blumenfeld-Katzir, Sharon Zlotzover, Yael Piontkewitz, Ina Weiner, Noam Ben-Eliezer","doi":"10.1002/jmri.29634","DOIUrl":"https://doi.org/10.1002/jmri.29634","url":null,"abstract":"<p><strong>Background: </strong>A recent neurodevelopmental rat model, utilizing lactational exposure to polyriboinosinic-polyribocytidilic acid (Poly I:C) leads to mimics of behavioral phenotypes resembling schizophrenia-like symptoms in male offspring and depression-like symptoms in female offspring.</p><p><strong>Purpose: </strong>To identify mechanisms of neuronal abnormalities in lactational Poly I:C offspring using quantitative MRI (qMRI) tools.</p><p><strong>Study type: </strong>Prospective.</p><p><strong>Animal model: </strong>Twenty Poly I:C rats and 20 healthy control rats, age 130 postnatal day.</p><p><strong>Field strength/sequence: </strong>7 T. Multiflip-angle FLASH protocol for T₁ mapping; multi-echo spin-echo T₂-mapping protocol; echo planar imaging protocol for diffusion tensor imaging.</p><p><strong>Assessment: </strong>Nursing dams were injected with the viral mimic Poly I:C or saline (control group). In adulthood, quantitative maps of T₁, T₂, proton density, and five diffusion metrics were generated for the offsprings. Seven regions of interest (ROIs) were segmented, followed by extracting 10 quantitative features for each ROI.</p><p><strong>Statistical tests: </strong>Random forest machine learning (ML) tool was employed to identify MRI markers of disease and classify Poly I:C rats from healthy controls based on quantitative features.</p><p><strong>Results: </strong>Poly I:C rats were identified from controls with an accuracy of 82.5 ± 25.9% for females and 85.0 ± 24.0% for males. Poly I:C females exhibited differences mainly in diffusion-derived parameters in the thalamus and the medial prefrontal cortex (MPFC), while males displayed changes primarily in diffusion-derived parameters in the corpus callosum and MPFC.</p><p><strong>Data conclusion: </strong>qMRI shows potential for identifying sex-specific brain abnormalities in the Poly I:C model of neurodevelopmental disorders.</p><p><strong>Level of evidence: </strong>NA TECHNICAL EFFICACY: Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142502149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"3D Vortex-Energetics in the Left Pulmonary Artery for Differentiating Pulmonary Arterial Hypertension and Pulmonary Venous Hypertension Groups Using 4D Flow MRI.","authors":"Mohammed S M Elbaz, Melika Shafeghat, Benjamin H Freed, Roberto Sarnari, Zachary Zilber, Ryan Avery, Michael Markl, Bradley D Allen, James Carr","doi":"10.1002/jmri.29635","DOIUrl":"https://doi.org/10.1002/jmri.29635","url":null,"abstract":"<p><strong>Background: </strong>Pulmonary hypertension (PH) is a life-threatening. Differentiation pulmonary arterial hypertension (PAH) from pulmonary venous hypertension (PVH) is important due to distinct treatment protocols. Invasive right heart catheterization (RHC) remains the reference standard but noninvasive alternatives are needed.</p><p><strong>Purpose/hypothesis: </strong>To evaluate 4D Flow MRI-derived 3D vortex energetics in the left pulmonary artery (LPA) for distinguishing PAH from PVH.</p><p><strong>Study type: </strong>Prospective case-control.</p><p><strong>Population/subjects: </strong>Fourteen PAH patients (11 female) and 18 PVH patients (9 female) diagnosed from RHC, 23 healthy controls (9 female).</p><p><strong>Field strength/sequence: </strong>1.5 T; gradient recalled echo 4D flow and balanced steady-state free precession (bSSFP) cardiac cine sequences.</p><p><strong>Assessment: </strong>LPA 3D vortex cores were identified using the lambda2 method. Peak vortex-contained kinetic energy (vortex-KE) and viscous energy loss (vortex-EL) were computed from 4D flow MRI. Left and right ventricular (LV, RV) stroke volume (LVSV, RVSV) and ejection fraction (LVEF, RVEF) were computed from bSSFP. In PH patients, mean pulmonary artery pressure (mPAP), pulmonary capillary wedge pressure (PCWR) and pulmonary vascular resistance (PVR) were determined from RHC.</p><p><strong>Statistical tests: </strong>Mann-Whitney U test for group comparisons, Spearman's rho for correlations, logistic regression for identifying predictors of PAH vs. PVH and develop models, area under the receiver operating characteristic curve (AUC) for model performance. Significance was set at P < 0.05.</p><p><strong>Results: </strong>PAH patients showed significantly lower vortex-KE (37.14 [14.68-78.52] vs. 76.48 [51.07-120.51]) and vortex-EL (9.93 [5.69-25.70] vs. 24.22 [12.20-32.01]) than PVH patients. The combined vortex-KE and LVEF model achieved an AUC of 0.89 for differentiating PAH from PVH. Vortex-EL showed significant negative correlations with mPAP (rho = -0.43), PCWP (rho = 0.37), PVR (rho = -0.64). In the PAH group, PVR was significantly negatively correlated with LPA vortex-KE (rho = -0.73) and vortex-EL (rho = -0.71), and vortex-KE significantly correlated with RVEF (rho = 0.69), RVSV, (rho = 0.70). In the PVH group, vortex-KE (rho = 0.52), vortex-EL significantly correlated with RVSV (rho = 0.58).</p><p><strong>Data conclusion: </strong>These preliminary findings suggest that 4D flow MRI-derived LPA vortex energetics have potential to noninvasively differentiate PAH from PVH and correlate with invasive hemodynamic parameters.</p><p><strong>Evidence level: </strong>1 TECHNICAL EFFICACY: Stage 3.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142522098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial for \"Reproducibility of Cardiac Multifrequency MR Elastography in Assessing Left Ventricular Stiffness and Viscosity\".","authors":"Hichem Sakhi, Virgile Chevance, Arshid Azarine","doi":"10.1002/jmri.29641","DOIUrl":"https://doi.org/10.1002/jmri.29641","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142522099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Influence of Anthropometric Factors on Renal mpMRI: Insights From Regional Analysis.","authors":"Luis Carlos Sanmiguel Serpa, Pieter de Visschere, Marijn Speeckaert, Pim Pullens","doi":"10.1002/jmri.29638","DOIUrl":"https://doi.org/10.1002/jmri.29638","url":null,"abstract":"<p><strong>Background: </strong>Multiparametric MRI (mpMRI) provides detailed insights into renal function, but the impact of anthropometric factors on renal imaging is not fully understood.</p><p><strong>Purpose: </strong>To investigate regional correlations between mpMRI parameters and age, body mass index (BMI), and body surface area (BSA).</p><p><strong>Study type: </strong>Prospective, cross-sectional observational study.</p><p><strong>Population: </strong>Twenty-nine healthy volunteers (44.5 ± 18.3 years, 18 females) without a history of renal disease.</p><p><strong>Field strength/sequence: </strong>3-T, pseudo-continuous arterial spin labeling, multi-echo gradient-recalled echo, diffusion-weighted imaging, T₁ and T₂ mapping.</p><p><strong>Assessment: </strong>Bilateral kidneys were segmented into nine concentric layers (outer cortex to inner regions) and nine equiangular sections (lower to upper pole). Key parameters (renal blood flow [RBF], <math> <semantics> <mrow><msubsup><mi>R</mi> <mn>2</mn> <mo>*</mo></msubsup> </mrow> <annotation>$$ {R}_2^{ast } $$</annotation></semantics> </math> , apparent diffusion coefficient [ADC], T₁ and T₂ maps) were correlated with age, BMI, and BSA. Differences in parameters between age and BMI groups were also evaluated.</p><p><strong>Statistical tests: </strong>Spearman correlation, Mann-Whitney U test, and rank-biserial correlation coefficient for effect size. A P-value <0.05 was considered statistically significant.</p><p><strong>Results: </strong>RBF correlated negatively with age in all regions and BMI in inner layers and lower pole. ADC negatively correlated with BMI (significance was not reached in layers 2, 7, 8; P-value = 0.06-0.12) and BSA in layers 1-7. T₁ negatively correlated with age in inner regions and lower medial pole. Significant positive correlations were found between age and <math> <semantics> <mrow><msubsup><mi>R</mi> <mn>2</mn> <mo>*</mo></msubsup> </mrow> <annotation>$$ {R}_2^{ast } $$</annotation></semantics> </math> (outermost layer, upper pole), age and T₂ (inner and cranial-caudal regions), as well as BMI and T₂ (except upper pole; P-value = 0.06). Significant differences between age groups were observed for RBF (all regions), <math> <semantics> <mrow><msubsup><mi>R</mi> <mn>2</mn> <mo>*</mo></msubsup> </mrow> <annotation>$$ {R}_2^{ast } $$</annotation></semantics> </math> (outermost and second innermost layers, central lateral region), T₁ (innermost layer), and T₂ (upper medial pole). Between BMI groups, ADC (middle layers, upper medial pole) and T₂ (outermost and inner layers, lower pole to lateral region) differed significantly.</p><p><strong>Data conclusion: </strong>Intrarenal variance of mpMRI parameters correlated with age, BMI, and BSA.</p><p><strong>Evidence level: </strong>4 TECHNICAL EFFICACY: Stage 1.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142502154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Repeatability, Reproducibility, and Observer Variability of Cortical T1 Mapping for Renal Tissue Characterization.","authors":"Magdalena Nowak, Markus Henningsson, Tom Davis, Najib Chowdhury, Andrea Dennis, Carolina Fernandes, Helena Thomaides Brears, Matthew D Robson","doi":"10.1002/jmri.29602","DOIUrl":"https://doi.org/10.1002/jmri.29602","url":null,"abstract":"<p><strong>Background: </strong>The global rise in kidney diseases underscores the need for reliable, noninvasive imaging biomarkers. Among these, renal cortical T1 has shown promise but further technical validation is still required.</p><p><strong>Purpose: </strong>To evaluate the repeatability, reproducibility, and observer variability of kidney cortical T1 mapping in human volunteers without known renal disease.</p><p><strong>Study type: </strong>Prospective.</p><p><strong>Subjects: </strong>Three cohorts without renal disease: 1) 25 volunteers (median age 38 [interquartile range, IQR: 28-42] years, female N = 11) for scan-rescan assessments on GE 1.5 T and Siemens 1.5 T; 2) 29 volunteers (median age 29 [IQR: 24-40] years, female N = 15) for scan-rescan assessments on Siemens 3 T; and 3) 16 volunteers (median age 34 [IQR: 31-42] years, female N = 8) for cross-scanner reproducibility.</p><p><strong>Field strength/sequences: </strong>1.5 T and 3 T, a modified Look-Locker imaging (MOLLI) sequence with a balanced steady-state free precession (bSSFP) readout.</p><p><strong>Assessment: </strong>Kidney cortical T1 data was acquired on GE 1.5 T scanner, Siemens 1.5 T and 3 T scanners. Within-scanner repeatability and inter/intra-observer variability: GE 1.5 T and Siemens 1.5 T, and cross-scanner manufacturer reproducibility: Siemens 1.5 T-GE 1.5 T.</p><p><strong>Statistical tests: </strong>Bland Altman analysis, coefficient of variation (CoV), intra-class coefficient (ICC), and repeatability coefficient (RC).</p><p><strong>Results: </strong>Renal cortical T1 mapping showed high repeatability and reliability across scanner field strengths and manufacturers (repeatability: CoV 1.9%-2.8%, ICC 0.79-0.88, pooled RC 73 msec; reproducibility: CoV 3.0%, ICC 0.75, RC 90 msec). The method also showed robust observer variability (CoV 0.6%-1.4%, ICC 0.93-0.98, RC 22-48 msec).</p><p><strong>Data conclusion: </strong>Kidney cortical T1 mapping is a highly repeatable and reproducible method across MRI manufacturers, field strengths, and observer conditions.</p><p><strong>Evidence level: </strong>2 TECHNICAL EFFICACY: Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142522101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving Accuracy and Reproducibility of Cartilage T₂ Mapping in the OAI Dataset Through Extended Phase Graph Modeling.","authors":"Marco Barbieri, Anthony A Gatti, Feliks Kogan","doi":"10.1002/jmri.29646","DOIUrl":"https://doi.org/10.1002/jmri.29646","url":null,"abstract":"<p><strong>Background: </strong>The Osteoarthritis Initiative (OAI) collected extensive imaging data, including Multi-Echo Spin-Echo (MESE) sequences for measuring knee cartilage T₂ relaxation times. Mono-exponential models are used in the OAI for T₂ fitting, which neglects stimulated echoes and B₁ inhomogeneities. Extended Phase Graph (EPG) modeling addresses these limitations but has not been applied to the OAI dataset.</p><p><strong>Purpose: </strong>To assess how different fitting methods, including EPG-based and exponential-based approaches, affect the accuracy and reproducibility of cartilage T₂ in the OAI dataset.</p><p><strong>Study type: </strong>Retrospective.</p><p><strong>Population: </strong>From OAI dataset, 50 subjects, stratified by osteoarthritis (OA) severity using Kellgren-Lawrence grades (KLG), and 50 subjects without OA diagnosis during OAI duration were selected (each group: 25 females, mean ages ~61 years).</p><p><strong>Field strength/sequence: </strong>3-T, two-dimensional (2D) MESE sequence.</p><p><strong>Assessment: </strong>Femoral and tibial cartilages were segmented from DESS images, subdivided into seven sub-regions, and co-registered to MESE. T₂ maps were obtained using three EPG-based methods (nonlinear least squares, dictionary matching, and deep learning) and three mono-exponential approaches (linear least squares, nonlinear least squares, and noise-corrected exponential). Average T₂ values within sub-regions were obtained. Pair-wise agreement among fitting methods was evaluated using the stratified subjects, while reproducibility using healthy subjects. Each method's T₂ accuracy and repeatability varying signal-to-noise ratio (SNR) were assessed with simulations.</p><p><strong>Statistical tests: </strong>Bland-Altman analysis, Lin's concordance coefficient, and coefficient of variation assessed agreement, repeatability, and reproducibility. Statistical significance was set at P-value <0.05.</p><p><strong>Results: </strong>EPG-based methods demonstrated superior T₂ accuracy (mean absolute error below 0.5 msec at SNR > 100) compared to mono-exponential methods (error > 7 msec). EPG-based approaches had better reproducibility, with limits of agreement 1.5-5 msec narrower than exponential-based methods. T₂ values from EPG methods were systematically 10-17 msec lower than those from mono-exponential fitting.</p><p><strong>Data conclusion: </strong>EPG modeling improved agreement and reproducibility of cartilage T₂ mapping in subjects from the OAI dataset.</p><p><strong>Evidence level: </strong>3 TECHNICAL EFFICACY: Stage 1.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142522100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}