Journal of Magnetic Resonance Imaging最新文献

{"title":"Free-Breathing Functional Pulmonary Proton MRI: A Novel Approach Using Voxel-Wise Lung Ventilation (VOLVE) Assessment in Healthy Volunteers and Patients With Chronic Obstructive Pulmonary Disease.","authors":"Zachary J T Peggs, Jonathan P Brooke, Charlotte E Bolton, Ian P Hall, Susan T Francis, Penny A Gowland","doi":"10.1002/jmri.29444","DOIUrl":"10.1002/jmri.29444","url":null,"abstract":"<p><strong>Background: </strong>In respiratory medicine, there is a need for sensitive measures of regional lung function that can be performed using standard imaging technology, without the need for inhaled or intravenous contrast agents.</p><p><strong>Purpose: </strong>To describe VOxel-wise Lung VEntilation (VOLVE), a new method for quantifying regional lung ventilation (V) and perfusion (Q) using free-breathing proton MRI, and to evaluate VOLVE in healthy never-smokers, healthy people with smoking history, and people with chronic obstructive pulmonary disease (COPD).</p><p><strong>Study type: </strong>Prospective pilot.</p><p><strong>Population: </strong>Twelve healthy never-smoker participants (age 30.3 ± 12.5 years, five male), four healthy participants with smoking history (>10 pack-years) (age 42.5 ± 18.3 years, one male), and 12 participants with COPD (age 62.8 ± 11.1 years, seven male).</p><p><strong>Field strength/sequence: </strong>Single-slice free-breathing two-dimensional fast field echo sequence at 3 T.</p><p><strong>Assessment: </strong>A novel postprocessing was developed to evaluate the MR signal changes in the lung parenchyma using a linear regression-based approach, which makes use of all the data in the time series for maximum sensitivity. V/Q-weighted maps were produced by computing the cross-correlation, lag and gradient between the respiratory/cardiac phase time course and lung parenchyma signal time courses. A comparison of histogram median and skewness values and spirometry was performed.</p><p><strong>Statistical tests: </strong>Kruskal-Wallis tests with Dunn's multiple comparison tests to compare VOLVE metrics between groups; Spearman correlation to assess the correlation between MRI and spirometry-derived parameters; and Bland-Altman analysis and coefficient of variation to evaluate repeatability were used. A P-value <0.05 was considered significant.</p><p><strong>Results: </strong>Significant differences between the groups were found for ventilation between healthy never-smoker and COPD groups (median XCC_V, Lag_V, and Grad_V) and perfusion (median XCC_Q, Lag_Q, and Grad_Q). Minimal bias and no significant differences between intravisit scans were found (P range = 0.12-0.97).</p><p><strong>Data conclusion: </strong>This preliminary study showed that VOLVE has potential to provide metrics of function quantification.</p><p><strong>Level of evidence: </strong>2 TECHNICAL EFFICACY: Stage 1.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"663-675"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11706312/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141179352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial for \"Parallel CNN-Deep Learning Clinical-Imaging Signature for Assessing Pathologic Grade and Prognosis of Soft Tissue Sarcoma Patients\".","authors":"Pegah Khosravi","doi":"10.1002/jmri.29476","DOIUrl":"10.1002/jmri.29476","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"820-821"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141419500","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 \"Evaluation of Hepatic Glucose and Palmitic Acid Metabolism in Rodents on High-Fat Diet Using Deuterium Metabolic Imaging\".","authors":"Vera B Schrauwen-Hinderling, Ulrich Flögel","doi":"10.1002/jmri.29512","DOIUrl":"10.1002/jmri.29512","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"968-969"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141468578","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":"Preoperative Differentiation of HER2-Zero and HER2-Low from HER2-Positive Invasive Ductal Breast Cancers Using BI-RADS MRI Features and Machine Learning Modeling.","authors":"Jiejie Zhou, Yang Zhang, Haiwei Miao, Ga Young Yoon, Jinhao Wang, Yezhi Lin, Hailing Wang, Yan-Lin Liu, Jeon-Hor Chen, Zhifang Pan, Min-Ying Su, Meihao Wang","doi":"10.1002/jmri.29447","DOIUrl":"10.1002/jmri.29447","url":null,"abstract":"<p><strong>Background: </strong>Accurate determination of human epidermal growth factor receptor 2 (HER2) is important for choosing optimal HER2 targeting treatment strategies. HER2-low is currently considered HER2-negative, but patients may be eligible to receive new anti-HER2 drug conjugates.</p><p><strong>Purpose: </strong>To use breast MRI BI-RADS features for classifying three HER2 levels, first to distinguish HER2-zero from HER2-low/positive (Task-1), and then to distinguish HER2-low from HER2-positive (Task-2).</p><p><strong>Study type: </strong>Retrospective.</p><p><strong>Population: </strong>621 invasive ductal cancer, 245 HER2-zero, 191 HER2-low, and 185 HER2-positive. For Task-1, 488 cases for training and 133 for testing. For Task-2, 294 cases for training and 82 for testing.</p><p><strong>Field strength/sequence: </strong>3.0 T; 3D T1-weighted DCE, short time inversion recovery T2, and single-shot EPI DWI.</p><p><strong>Assessment: </strong>Pathological information and BI-RADS features were compared. Random Forest was used to select MRI features, and then four machine learning (ML) algorithms: decision tree (DT), support vector machine (SVM), k-nearest neighbors (k-NN), and artificial neural nets (ANN), were applied to build models.</p><p><strong>Statistical tests: </strong>Chi-square test, one-way analysis of variance, and Kruskal-Wallis test were performed. The P values <0.05 were considered statistically significant. For ML models, the generated probability was used to construct the ROC curves.</p><p><strong>Results: </strong>Peritumoral edema, the presence of multiple lesions and non-mass enhancement (NME) showed significant differences. For distinguishing HER2-zero from non-zero (low + positive), multiple lesions, edema, margin, and tumor size were selected, and the k-NN model achieved the highest AUC of 0.86 in the training set and 0.79 in the testing set. For differentiating HER2-low from HER2-positive, multiple lesions, edema, and margin were selected, and the DT model achieved the highest AUC of 0.79 in the training set and 0.69 in the testing set.</p><p><strong>Data conclusion: </strong>BI-RADS features read by radiologists from preoperative MRI can be analyzed using more sophisticated feature selection and ML algorithms to build models for the classification of HER2 status and identify HER2-low.</p><p><strong>Level of evidence: 4: </strong></p><p><strong>Technical efficacy: </strong>Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"928-941"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11550260/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140897292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PET-MRI Applications and Future Prospects in Psychiatry.","authors":"Nicole R Zürcher, Jingyuan E Chen, Hsiao-Ying Wey","doi":"10.1002/jmri.29471","DOIUrl":"10.1002/jmri.29471","url":null,"abstract":"<p><p>This article reviews the synergistic application of positron emission tomography-magnetic resonance imaging (PET-MRI) in neuroscience with relevance for psychiatry, particularly examining neurotransmission, epigenetics, and dynamic imaging methodologies. We begin by discussing the complementary insights that PET and MRI modalities provide into neuroreceptor systems, with a focus on dopamine, opioids, and serotonin receptors, and their implications for understanding and treating psychiatric disorders. We further highlight recent PET-MRI studies using a radioligand that enables the quantification of epigenetic enzymes, specifically histone deacetylases, in the brain in vivo. Imaging epigenetics is used to exemplify the impact the quantification of novel molecular targets may have, including new treatment approaches for psychiatric disorders. Finally, we discuss innovative designs involving functional PET using [¹⁸F]FDG (fPET-FDG), which provides detailed information regarding dynamic changes in glucose metabolism. Concurrent acquisitions of fPET-FDG and functional MRI provide a time-resolved approach to studying brain function, yielding simultaneous metabolic and hemodynamic information and thereby opening new avenues for psychiatric research. Collectively, the review underscores the potential of a multimodal PET-MRI approach to advance our understanding of brain structure and function in health and disease, which could improve clinical care based on objective neurobiological features and treatment response monitoring. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"568-578"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11617601/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141261014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial for \"Development and Validation of a Fusion Model Based on Carotid Plaques and White Matter Lesion Burden Imaging Characteristics to Evaluate Ischemic Stroke Severity in Symptomatic Patients\".","authors":"Xiao-Quan Xu, Gao Ma, Fei-Yun Wu","doi":"10.1002/jmri.29441","DOIUrl":"10.1002/jmri.29441","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"661-662"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140957485","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":"Generalizing Diffusion Tensor Imaging of the Physis and Metaphysis.","authors":"Katherine L Luo, Laura Santos, Rumana Tokaria, Sachin Jambawalikar, Phuong T Duong, José G Raya, Sogol Mostoufi-Moab, Diego Jaramillo","doi":"10.1002/jmri.29455","DOIUrl":"10.1002/jmri.29455","url":null,"abstract":"<p><strong>Background: </strong>Current methods to predict height potential are inaccurate. Predicting height by using MRI of the physeal cartilage has shown promise but the applicability of this technique in different imaging setups has not been well-evaluated.</p><p><strong>Purpose: </strong>To assess variability in diffusion tensor imaging of the physis and metaphysis (DTI-P/M) of the distal femur between different scanners, imaging parameters, tractography software, and resolution.</p><p><strong>Study type: </strong>Prospective.</p><p><strong>Population/subjects: </strong>Eleven healthy subjects (five males and six females ages 10-16.94).</p><p><strong>Field strength/sequence: </strong>3 T; DTI single shot echo planar sequences.</p><p><strong>Assessment: </strong>Physeal DTI tract measurements of the distal femur were compared between different scanners, imaging parameters, tractography settings, interpolation correction, and tractography software.</p><p><strong>Statistical tests: </strong>Bland-Altman, Spearman correlation, linear regression, and Shapiro-Wilk tests. Threshold for statistical significance was set at P = 0.05.</p><p><strong>Results: </strong>DTI tract values consistently showed low variability with different imaging and analysis settings. Vendor to vendor comparison exhibited strong correlation (ρ = 0.93) and small but significant bias (bias -5.76, limits of agreement [LOA] -24.31 to 12.78). Strong correlation and no significant difference were seen between technical replicates of the General Electric MRI scanner (ρ = 1, bias 0.17 [LOA -1.5 to 1.2], P = 0.42) and the Siemens MRI scanner (ρ = 0.89, bias = 0.56, P = 0.71). Different voxel sizes (1 × 1 × 2 mm³ vs. 2 × 2 × 3 mm³) did not significantly affect DTI values (bias = 1.4 [LOA -5.7 to 8.4], P = 0.35) but maintained a strong correlation (ρ = 0.82). Gap size (0 mm vs. 0.6 mm) significantly affects tract volume (bias = 1.8 [LOA -5.4 to 1.8]) but maintains a strong correlation (ρ = 0.93). Comparison of tractography algorithms generated significant differences in tract number, length, and volume while maintaining correlation (ρ = 0.86, 0.99, 0.93, respectively). Comparison of interobserver variability between different tractography software also revealed significant differences while maintaining high correlation (ρ = 0.85-0.98).</p><p><strong>Data conclusion: </strong>DTI of the pediatric physis cartilage shows high reproducibility between different imaging and analytic parameters.</p><p><strong>Evidence level: </strong>2 TECHNICAL EFFICACY: Stage 1.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"798-804"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11706308/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140957585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Amide Proton Transfer-Weighted Imaging in Assessing the Aggressive and Proliferative Potential of Bladder Cancer.","authors":"Lingmin Kong, Hui Li, Qian Cai, Wenxin Cao, Yanling Chen, Bei Weng, Meiqin Li, Min Zhang, Long Qian, Yan Guo, Jian Ling, Zhihua Wen, Huanjun Wang","doi":"10.1002/jmri.29464","DOIUrl":"10.1002/jmri.29464","url":null,"abstract":"<p><strong>Background: </strong>Ki-67 and human epidermal growth factor receptor 2 (HER2) are known oncogenes involved in bladder cancer (BCa) patient risk stratification. Preoperative assessment of their expression level can assist in clinical treatment decision-making. Recently, amide proton transfer-weighted (APTw) MRI has shown promising potential in the diagnosis of several malignancies. However, few studies reported the value of APTw imaging in evaluating Ki-67 and HER2 status of BCa.</p><p><strong>Purpose: </strong>To investigate the feasibility of APTw MRI in assessing the aggressive and proliferative potential regarding the expression levels of Ki-67 and HER2 in BCa.</p><p><strong>Study type: </strong>Retrospective.</p><p><strong>Subjects: </strong>114 patients (mean age, 64.78 ± 11.93 [SD] years; 97 men) were studied.</p><p><strong>Field strength/sequence: </strong>APTw MRI acquired by a three-dimensional fast-spin-echo sequence at 3.0 T MRI system.</p><p><strong>Assessment: </strong>Patient pathologic findings, included histologic grade and the expression status of Ki-67 and HER2, were reviewed by one uropathologist. The APTw values of BCa were independently measured by two radiologists and were compared between high-/low-tumor grade group, high-/low-Ki-67 expression group, and high-/low-HER2 expression group.</p><p><strong>Statistical tests: </strong>The interclass correlation coefficient, independent sample t-test, Mann-Whitney U test, Spearman's rank correlation, and receiver operating characteristic curve (ROC) analysis were used. P < 0.05 was considered statistically significant.</p><p><strong>Results: </strong>Significantly higher APTw values were found in high-grade BCa patients (7.72% vs. 4.29%, P < 0.001), high-Ki-67 expression BCa patients (8.40% vs. 3.25%, P < 0.001) and HER2 positive BCa patients (8.24% vs. 5.40%, P = 0.001). APTw values were positively correlated with Ki-67 (r = 0.769) and HER2 (r = 0. 356) expression status. The area under the ROC curve of the APTw values for detecting Ki-67 and HER2 expression status were 0.883 (95% CI: 0.790-0.945) and 0.713 (95% CI: 0.592-0.816), respectively.</p><p><strong>Data conclusions: </strong>APTw MRI is a potential method to assess the biological and proliferation potential of BCa.</p><p><strong>Level of evidence: 4: </strong></p><p><strong>Technical efficacy: </strong>Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"704-712"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141186139","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":"Association Between MRI-Based Radiomics Features and Regional Lymph Node Metastasis in Intrahepatic Cholangiocarcinoma and Its Clinical Outcome.","authors":"Xianling Qian, Xiaoyan Ni, Gengyun Miao, Fang Wang, Changwu Zhou, Peng Huang, Yunfei Zhang, Lei Chen, Chun Yang, Mengsu Zeng","doi":"10.1002/jmri.29477","DOIUrl":"10.1002/jmri.29477","url":null,"abstract":"<p><strong>Background: </strong>Regional lymph node metastasis (LNM) assessment is crucial for predicting intrahepatic cholangiocarcinoma (iCCA) prognosis. However, imaging assessment has limitations for identifying LNM.</p><p><strong>Purpose: </strong>To investigate the association between MRI radiomics features, regional LNM status, and prognosis in iCCA.</p><p><strong>Study type: </strong>Retrospective.</p><p><strong>Subjects: </strong>Two hundred ninety-six patients (male = 197) with surgically confirmed iCCA.</p><p><strong>Field strength/sequence: </strong>1.5 T and 3.0 T. DWI, T2WI, and contrast-enhanced T1WI.</p><p><strong>Assessment: </strong>Clinical information, radiologic, and MRI-based radiomics features associated with LNM status were collected to establish models. Performance of MRI, PET/CT, and the combined LNM models were compared in training (N = 207) and test (N = 89) datasets. Overall survival (OS) was compared based on LNM status.</p><p><strong>Statistical tests: </strong>The independent features were selected by 5-fold cross-validation. The performance of MRI, PET/CT, and the models was evaluated using the area under receiver operating characteristic curve (AUC). Univariable and multivariable Cox regression were used to identify independent variables for OS. Kaplan-Meier curves were compared with the log-rank test between LNM positive and negative groups. P < 0.05 was considered statistically significant.</p><p><strong>Results: </strong>Intrahepatic duct dilatation, enhancement pattern, and CA19-9 were independent clinicoradiologic features. The radiomics model was constructed by the independent radiomics features extracted from T2WI and delay phase T1WI. The combined LNM model showed AUC of 0.888, 0.884, and 0.811 in training, validation, and test cohorts with a positive net benefit. PET/CT exhibited similar sensitivity to the combined LNM model (0.750 vs. 0.733, P > 0.999) while the combined LNM model showed higher specificity (0.703 vs. 0.630, P = 0.039) in the test cohort. High risk of regional LNM was significantly associated with worse OS (median: 24 months) than low risk (median: 30 months, P < 0.0001).</p><p><strong>Data conclusions: </strong>The combined LNM model has the strongest correlation with LNM status for mass-forming iCCA patients.</p><p><strong>Evidence level: </strong>3 TECHNICAL EFFICACY: Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"997-1010"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141457345","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 \"Magnetic Resonance Elastography of Anterior Mediastinal Tumors\".","authors":"James F M Meaney","doi":"10.1002/jmri.29479","DOIUrl":"10.1002/jmri.29479","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":"849-850"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141457406","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}