Radiomics nomogram for differentiating between benign and malignant soft‐tissue masses of the extremities

作者：Hexiang Wang, Pei Nie, Yujian Wang, Wenjian Xu, Shaofeng Duan, Haisong Chen, Dapeng Hao, Jihua Liu · 发表于：Journal of Magnetic Resonance Imaging · 年份：2019 · DOI：10.1002/jmri.26818 · 被引用次数：60 · 研究领域：Sarcoma Diagnosis and Treatment、Musculoskeletal synovial abnormalities and treatments、Colorectal and Anal Carcinomas

Background Preoperative differentiation between malignant and benign tumors is important for treatment decisions. Purpose/Hypothesis To investigate/validate a radiomics nomogram for preoperative differentiation between malignant and benign masses. Study Type Retrospective. Population Imaging data of 91 patients. Field Strength/Sequence T 1 ‐weighted images (570 msec repetition time [TR]; 17.9 msec echo time [TE], 200–400 mm field of view [FOV], 208–512 × 208–512 matrix), fat‐suppressed fast‐spin‐echo (FSE) T 2 ‐weighted images (T 2 WIs) (4331 msec TR; 87.9 msec TE, 200–400 mm FOV, 312 × 312 matrix), slice thickness 4 mm, and slice spacing 1 mm. Assessment Fat‐suppressed FSE T 2 WIs were selected for extraction of features. Radiomics features were extracted from fat‐suppressed T 2 WIs. A radiomics signature was generated from the training dataset using least absolute shrinkage and selection operator algorithms. Independent risk factors were identified by multivariate logistic regression analysis and a radiomics nomogram was constructed. Nomogram capability was evaluated in the training dataset and validated in the validation dataset. Performance of the nomogram, radiomics signature, and clinical model were compared. Statistical Tests 1) Independent t ‐test or Mann–Whitney U ‐test: for continuous variables. Fisher's exact test or χ 2 test: comparing categorical variables between two groups. Univariate analysis: evaluating associations between clinical/morphological characterist...