Journal of magnetic resonance imaging : JMRI
-
J Magn Reson Imaging · Aug 2021
Multicenter StudyThe Nomogram of MRI-based Radiomics with Complementary Visual Features by Machine Learning Improves Stratification of Glioblastoma Patients: A Multicenter Study.
Glioblastomas (GBMs) represent both the most common and the most highly malignant primary brain tumors. The subjective visual imaging features from MRI make it challenging to predict the overall survival (OS) of GBM. Radiomics can quantify image features objectively as an emerging technique. A pragmatic and objective method in the clinic to assess OS is strongly in need. ⋯ 3 TECHNICAL EFFICACY STAGE: 2.
-
J Magn Reson Imaging · Dec 2020
Multicenter StudyPreoperative Assessment for High-Risk Endometrial Cancer by Developing an MRI- and Clinical-Based Radiomics Nomogram: A Multicenter Study.
High- and low-risk endometrial cancer (EC) differ in whether lymphadenectomy is performed. Assessment of high-risk EC is essential for planning surgery appropriately. ⋯ 4 TECHNICAL EFFICACY STAGE: 2 J. MAGN. RESON. IMAGING 2020;52:1872-1882.
-
J Magn Reson Imaging · May 2020
Multicenter StudyDeep-Learning-Based Neural Tissue Segmentation of MRI in Multiple Sclerosis: Effect of Training Set Size.
The dependence of deep-learning (DL)-based segmentation accuracy of brain MRI on the training size is not known. ⋯ 1 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:1487-1496.
-
J Magn Reson Imaging · Feb 2020
Multicenter StudyRadiomics nomogram based on MRI for predicting white matter hyperintensity progression in elderly adults.
White matter hyperintensity (WMH) is widely observed in aging brain and is associated with various diseases. A pragmatic and handy method in the clinic to assess and follow up white matter disease is strongly in need. ⋯ 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:535-546.
-
J Magn Reson Imaging · Dec 2019
Randomized Controlled Trial Multicenter Study Comparative StudyAdditive value of diffusion-weighted MRI in the I-SPY 2 TRIAL.
The change in apparent diffusion coefficient (ADC) measured from diffusion-weighted imaging (DWI) has been shown to be predictive of pathologic complete response (pCR) for patients with locally invasive breast cancer undergoing neoadjuvant chemotherapy. ⋯ 2 Technical Efficacy Stage: 4 J. Magn. Reson. Imaging 2019;50:1742-1753.