Journal of magnetic resonance imaging : JMRI
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J Magn Reson Imaging · Oct 2019
Pilot study on longitudinal change in pancreatic proton density fat fraction during a weight-loss surgery program in adults with obesity.
Quantitative-chemical-shift-encoded (CSE)-MRI methods have been applied to the liver. The feasibility and potential utility CSE-MRI in monitoring changes in pancreatic proton density fat fraction (PDFF) have not yet been demonstrated. ⋯ 2 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;50:1092-1102.
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J Magn Reson Imaging · Oct 2019
Multicenter StudyAutomated image quality evaluation of structural brain MRI using an ensemble of deep learning networks.
Deep learning (DL) is a promising methodology for automatic detection of abnormalities in brain MRI. ⋯ 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1260-1267.
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J Magn Reson Imaging · Oct 2019
Comparative StudyDifferentiating axillary lymph node metastasis in invasive breast cancer patients: A comparison of radiomic signatures from multiparametric breast MR sequences.
The axillary lymph node status is critical for breast cancer staging and individualized treatment planning. ⋯ Breast tumor's radiomic signatures from preoperative breast MRI sequences are associated with the ALN metastasis status, where CE2 phase and the contrast enhancement kinetic features lead to the highest classification effect. Level of Evidence 3 Technical Efficacy Stage 2 J. Magn. Reson. Imaging 2019;50:1125-1132.
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J Magn Reson Imaging · Oct 2019
Repeatability and reproducibility of 3D MR fingerprinting relaxometry measurements in normal breast tissue.
The 3D breast magnetic resonance fingerprinting (MRF) technique enables T1 and T2 mapping in breast tissues. Combined repeatability and reproducibility studies on breast T1 and T2 relaxometry are lacking. ⋯ 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1133-1143.
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J Magn Reson Imaging · Oct 2019
Glioma grading using a machine-learning framework based on optimized features obtained from T1 perfusion MRI and volumes of tumor components.
Glioma grading between intermediate grades (Grade II vs. III and Grade III vs. IV) as well as multiclass grades (Grade II vs. III vs. IV) is challenging and needs to be addressed. ⋯ 4 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:1295-1306.