Journal of Magnetic Resonance Imaging最新文献

{"title":"Editorial for \"Prognostic Assessment in Patients With Primary Diffuse Large B-Cell Lymphoma of the Central Nervous System Using MRI-Based Radiomics\".","authors":"Durga Udayakumar","doi":"10.1002/jmri.29552","DOIUrl":"https://doi.org/10.1002/jmri.29552","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141855690","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 \"The Association Between Tumor Radiomic Analysis and Peritumor Habitat-Derived Radiomic Analysis on Gadoxetate Disodium-Enhanced MRI With Microvascular Invasion in Hepatocellular Carcinoma\".","authors":"Filippo C Michelotti","doi":"10.1002/jmri.29551","DOIUrl":"https://doi.org/10.1002/jmri.29551","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141855691","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 \"Left Atrial Phasic Function Impairment in Subacute and Chronic Pulmonary Embolism Patients With Different Degrees of Obstruction: An MRI Feature Tracking Study\".","authors":"Danilo T Wada, Gustavo J Volpe, Henrique T Moreira","doi":"10.1002/jmri.29556","DOIUrl":"https://doi.org/10.1002/jmri.29556","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141855689","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":"Letter to Editor Regarding \"Auditory Effects of Acoustic Noise From 3-T Brain MRI in Neonates With Hearing Protection\".","authors":"Michael C Steckner","doi":"10.1002/jmri.29517","DOIUrl":"https://doi.org/10.1002/jmri.29517","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141855692","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 \"Hippocampal Glutamate Levels and Their Correlation With Subregion Volume in School-Aged Children With MRI-Negative Epilepsy: A Preliminary Study\".","authors":"Nishard Abdeen","doi":"10.1002/jmri.29553","DOIUrl":"https://doi.org/10.1002/jmri.29553","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141792643","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":"Deep Learning-Based Techniques in Glioma Brain Tumor Segmentation Using Multi-Parametric MRI: A Review on Clinical Applications and Future Outlooks.","authors":"Delaram J Ghadimi, Amir M Vahdani, Hanie Karimi, Pouya Ebrahimi, Mobina Fathi, Farzan Moodi, Adrina Habibzadeh, Fereshteh Khodadadi Shoushtari, Gelareh Valizadeh, Hanieh Mobarak Salari, Hamidreza Saligheh Rad","doi":"10.1002/jmri.29543","DOIUrl":"https://doi.org/10.1002/jmri.29543","url":null,"abstract":"<p><p>This comprehensive review explores the role of deep learning (DL) in glioma segmentation using multiparametric magnetic resonance imaging (MRI) data. The study surveys advanced techniques such as multiparametric MRI for capturing the complex nature of gliomas. It delves into the integration of DL with MRI, focusing on convolutional neural networks (CNNs) and their remarkable capabilities in tumor segmentation. Clinical applications of DL-based segmentation are highlighted, including treatment planning, monitoring treatment response, and distinguishing between tumor progression and pseudo-progression. Furthermore, the review examines the evolution of DL-based segmentation studies, from early CNN models to recent advancements such as attention mechanisms and transformer models. Challenges in data quality, gradient vanishing, and model interpretability are discussed. The review concludes with insights into future research directions, emphasizing the importance of addressing tumor heterogeneity, integrating genomic data, and ensuring responsible deployment of DL-driven healthcare technologies. EVIDENCE LEVEL: N/A TECHNICAL EFFICACY: Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141792642","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":"High b-Value and Ultra-High b-Value Diffusion Weighted MRI in Stroke.","authors":"Rifeng Jiang, ZhenXiong Wang, Jun Liu, Ting Li, YanChun Lv, Chuanmiao Xie, Changliang Su","doi":"10.1002/jmri.29547","DOIUrl":"https://doi.org/10.1002/jmri.29547","url":null,"abstract":"<p><strong>Purpose: </strong>To explore the application value of high-b-value and ultra-high b-value DWI in noninvasive evaluation of ischemic infarctions.</p><p><strong>Study type: </strong>Prospective.</p><p><strong>Subjects: </strong>Sixty-four patients with clinically diagnosed ischemic lesions based on symptoms and DWI.</p><p><strong>Field strength/sequence: </strong>3.0 T/T2-weighted fast spin-echo, fluid-attenuated inversion recovery, pre-contrast T1-weighted magnetization prepared rapid gradient echo sequence, multi-b-value trace DWI and q-space sampling sequences.</p><p><strong>Assessment: </strong>Lesions were segmented on standard b-value DWI (SB-DWI, 1000 s/mm²), high b-value DWI (HB-DWI, 4000 s/mm²) and ultra-high b-value DWI (UB-DWI, 10,000 s/mm²), and cumulative segmented areas were the final abnormality volumes. Normal white matter (WM) areas were obtained after binarization of segmented brain. In 47 patients, fractional anisotropy (FA) and apparent diffusion coefficients (ADCs) at b values of 1000, 4000, and 10,000 s/mm² were extracted from symmetrical WM masks and lesion masks of contralateral WM (CWM) and lesion-side WM (LWM).</p><p><strong>Statistical tests: </strong>Wilcoxon matched-pairs signed-rank test and Pearson correlation analysis. Two-tailed P-values <0.05 were considered statistically significant.</p><p><strong>Results: </strong>Various signals of HB-/UB-DWI (hypo-, iso- or hyper-intensity) were observed in strokes compared with SB-DWI, and some areas with iso-intensity of SB-DWI manifested with hyper-intensity on HB-/UB-DWI. Abnormality volumes from SB-DWI were significantly smaller than those from HB-DWI and UB-DWI (10.32 ± 16.45 cm³, vs. 12.25 ± 19.71 cm³ and 11.83 ± 19.41 cm³), while no significant difference exist in volume between HB-DWI and UB-DWI (P = 0.32). In CWM, FA significantly correlated with ADC₄₀₀₀ and ADC_10,000 (maximum r = -0.51 and -0.64), but did not significantly correlate with ADC₁₀₀₀ (maximum r = -0.20, P = 0.17). ADC₁₀₀₀ or ADC₄₀₀₀ of LWM not significant correlated with FA of CWM (maximum r = -0.28, P = 0.06), while ADC_10,000 of LWM significantly correlated with FA of CWM (maximum r = -0.46).</p><p><strong>Data conclusion: </strong>HB- and UB-DWI have potential to be supplementary tools for the noninvasive evaluation of stroke lesions in clinics.</p><p><strong>Evidence level: </strong>2 TECHNICAL EFFICACY: Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141792644","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":"Human Brain Deuterium Metabolic Imaging at 7 T: Impact of Different [6,6'-²H₂]Glucose Doses.","authors":"Narjes Ahmadian, Maaike M Konig, Sigrid Otto, Kiki Tesselaar, Pieter van Eijsden, Mark Gosselink, Ayhan Gursan, Dennis W Klomp, Jeanine J Prompers, Evita C Wiegers","doi":"10.1002/jmri.29532","DOIUrl":"https://doi.org/10.1002/jmri.29532","url":null,"abstract":"<p><strong>Background: </strong>Deuterium metabolic imaging (DMI) is an innovative, noninvasive metabolic MR imaging method conducted after administration of ²H-labeled substrates. DMI after [6,6'-²H₂]glucose consumption has been used to investigate brain metabolic processes, but the impact of different [6,6'-²H₂]glucose doses on DMI brain data is not well known.</p><p><strong>Purpose: </strong>To investigate three different [6,6'-²H₂]glucose doses for DMI in the human brain at 7 T.</p><p><strong>Study type: </strong>Prospective.</p><p><strong>Population: </strong>Six healthy participants (age: 28 ± 8 years, male/female: 3/3).</p><p><strong>Field strength/sequence: </strong>7 T, 3D ²H free-induction-decay (FID)-magnetic resonance spectroscopic imaging (MRSI) sequence.</p><p><strong>Assessment: </strong>Three subjects received two different doses (0.25 g/kg, 0.50 g/kg or 0.75 g/kg body weight) of [6,6'-²H₂]glucose on two occasions and underwent consecutive ²H-MRSI scans for 120 minutes. Blood was sampled every 10 minutes during the scan, to determine plasma glucose levels and plasma ²H-Glucose atom percent excess (APE) (part-1). Three subjects underwent the same protocol once after receiving 0.50 g/kg [6,6'-²H₂]glucose (part-2).</p><p><strong>Statistical test: </strong>Mean plasma ²H-Glucose APE and glucose plasma concentrations were compared using one-way ANOVA. Brain ²H-Glc and brain ²H-Glx (part-1) were analyzed with a two-level Linear Mixed Model. In part-2, a General Linear Model was used to compare brain metabolite signals. Statistical significance was set at P < 0.05.</p><p><strong>Results: </strong>Between 60 and 100 minutes after ingesting [6,6'-²H₂]glucose, plasma ²H-Glc APE did not differ between 0.50 g/kg and 0.75 g/kg doses (P = 0.961), but was significantly lower for 0.25 g/kg. Time and doses significantly affected brain ²H-Glucose levels (estimate ± standard error [SE]: 0.89 ± 0.01, 1.09 ± 0.01, and 1.27 ± 0.01, for 0.25 g/kg, 0.50 g/kg, and 0.75 g/kg, respectively) and brain ²H-Glutamate/Glutamine levels (estimate ± SE: 1.91 ± 0.03, 2.27 ± 0.03, and 2.46 ± 0.03, for 0.25 g/kg, 0.50 g/kg, and 0.75 g/kg, respectively). Plasma ²H-Glc APE, brain ²H-Glc, and brain ²H-Glx levels were comparable among subjects receiving 0.50 g/kg [6,6'-²H₂]glucose.</p><p><strong>Data conclusion: </strong>Brain ²H-Glucose and brain ²H-Glutamate/Glutamine showed to be [6,6'-²H₂]glucose dose dependent. A dose of 0.50 g/kg demonstrated comparable, and well-detectable, ²H-Glucose and ²H-Glutamate/Glutamine signals in the brain.</p><p><strong>Evidence level: </strong>1 TECHNICAL EFFICACY: Stage 2.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141759190","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 \"Self-Gated Radial Free-Breathing Liver MR Elastography: Assessment of Technical Performance in Children at 3T\".","authors":"Richard L Ehman","doi":"10.1002/jmri.29542","DOIUrl":"https://doi.org/10.1002/jmri.29542","url":null,"abstract":"","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141759161","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":"Enabling AI-Generated Content for Gadolinium-Free Contrast-Enhanced Breast Magnetic Resonance Imaging.","authors":"Pingping Wang, Hongyu Wang, Pin Nie, Yanli Dang, Rumei Liu, Mingzhu Qu, Jiawei Wang, Gengming Mu, Tianju Jia, Lei Shang, Kaiguo Zhu, Jun Feng, Baoying Chen","doi":"10.1002/jmri.29528","DOIUrl":"https://doi.org/10.1002/jmri.29528","url":null,"abstract":"<p><strong>Background: </strong>There is increasing interest in utilizing AI-generated content for gadolinium-free contrast-enhanced breast MRI.</p><p><strong>Purpose: </strong>To develop a generative model for gadolinium-free contrast-enhanced breast MRI and evaluate the diagnostic utility of the generated scans.</p><p><strong>Study type: </strong>Retrospective.</p><p><strong>Population: </strong>Two hundred seventy-six women with 304 breast MRI examinations (49 ± 13 years, 243/61 for training/testing).</p><p><strong>Field strength/sequence: </strong>ZOOMit diffusion-weighted imaging (DWI), T1-weighted volumetric interpolated breath-hold examination (T1W VIBE), and axial T2 3D SPACE at 3.0 T.</p><p><strong>Assessment: </strong>A generative model was developed to generate contrast-enhanced scans using precontrast T1W VIBE and DWI images. The generated and real images were quantitatively compared using the structural similarity index (SSIM), mean absolute error (MAE), and Dice similarity coefficient. Three radiologists with 8, 5, and 5 years of experience independently rated the image quality and lesion visibility on AI-generated and real images within various subgroups using a five-point scale. Four breast radiologists, with 8, 8, 5, and 5 years of experience, independently and blindly interpreted four reading protocols: unenhanced MRI protocol alone and combined with AI-generated scans, abbreviated MRI protocol, and full-MRI protocol.</p><p><strong>Statistical analysis: </strong>Results were assessed using t-tests and McNemar tests. Using pathology diagnosis as reference standard, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each reading protocol. A P value <0.05 was considered significant.</p><p><strong>Results: </strong>In the test set, the generated images showed similarity to the real images (SSIM: 0.935 ± 0.047 [SD], MAE: 0.015 ± 0.012 [SD], and Dice coefficient: 0.726 ± 0.177 [SD]). No significant difference in lesion visibility was observed between real and AI-generated scans of the mass, non-mass, and benign lesion subgroups. Adding AI-generated scans to the unenhanced MRI protocol slightly improved breast cancer detection (sensitivity: 92.86% vs. 85.71%, NPV: 76.92% vs. 70.00%); achieved non-inferior diagnostic utility compared to the AB-MRI protocol and full-protocol (sensitivity: 92.86%, 95.24%; NPV: 75.00%, 81.82%).</p><p><strong>Data conclusion: </strong>AI-generated gadolinium-free contrast-enhanced breast MRI has potential to improve the sensitivity of unenhanced MRI in detecting breast cancer.</p><p><strong>Evidence level: </strong>4 TECHNICAL EFFICACY: Stage 3.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141759189","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}