Machine learning-based radiomics analysis in predicting the meningioma grade using multiparametric MRI.

Journal: European journal of radiology

Published Date: Aug 28, 2020

PURPOSE: To investigate the prediction performance of radiomic models based on multiparametric MRI in predicting the meningioma grade.

Jianping Hu

Department of Radiology, The First Affiliated Hospital of Fujian Medical University, 20 ChaZhong Rd, Fuzhou, Fujian, 350005, PR China.
Yijing Zhao

Department of Radiology, The First Affiliated Hospital of Fujian Medical University, 20 ChaZhong Rd, Fuzhou, Fujian, 350005, PR China.
Mengcheng Li

Department of Radiology, The First Affiliated Hospital of Fujian Medical University, 20 ChaZhong Rd, Fuzhou, Fujian, 350005, PR China.
Jianyi Liu

Department of Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
Feng Wang

Department of Oncology, Binzhou Medical University Hospital, Binzhou, Shandong, China.
Qiang Weng

Department of Radiology, The First Affiliated Hospital of Fujian Medical University, 20 ChaZhong Rd, Fuzhou, Fujian, 350005, PR China.
Xingfu Wang

Department of Pathology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Dairong Cao

Department of Radiology, The First Affiliated Hospital of Fujian Medical University, 20 ChaZhong Rd, Fuzhou, Fujian, 350005, PR China. Electronic address: dairongcao@163.com.

Area Under Curve Female Humans Image Interpretation, Computer-Assisted Machine Learning Male Meningeal Neoplasms Meningioma Middle Aged Multiparametric Magnetic Resonance Imaging Neoplasm Grading Predictive Value of Tests Preoperative Care Reproducibility of Results Retrospective Studies ROC Curve

View on PubMed Access via DOI PubMed (32916409)