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Radiomics can differentiate high-grade glioma from brain metastasis: a systematic review and meta-analysis

Li, Yuanzhen; Liu, Yujie; Liang, Yingying; Wei, Ruili; Zhang, Wanli; Yao, Wang; Luo, Shiwei; Pang, Xinrui; Wang, Ye; Jiang, Xinqing; Lai, Shengsheng*; Yang, Ruimeng*
Science Citation Index Expanded
广东食品药品职业学院

摘要

Objective (1) To evaluate the diagnostic performance of radiomics in differentiating high-grade glioma from brain metastasis and how to improve the model. (2) To assess the methodological quality of radiomics studies and explore ways of embracing the clinical application of radiomics. Methods Studies using radiomics to differentiate high-grade glioma from brain metastasis published by 26 July 2021 were systematically reviewed. Methodological quality and risk of bias were assessed using the Radiomics Quality Score (RQS) system and Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool, respectively. Pooled sensitivity and specificity of the radiomics model were also calculated. Results Seventeen studies combining 1,717 patients were included in the systematic review, of which 10 studies without data leakage suspicion were employed for the quantitative statistical analysis. The average RQS was 5.13 (14.25% of total), with substantial or almost perfect inter-rater agreements. The inclusion of clinical features in the radiomics model was only reported in one study, as was the case for publicly available algorithm code. The pooled sensitivity and specificity were 84% (95% CI, 80-88%) and 84% (95% CI, 81-87%), respectively. The performances of feature extraction from the volume of interest (VOI) or (semi) automatic segmentation in the radiomics models were superior to those of protocols employing region of interest (ROI) or manual segmentation. Conclusion Radiomics can accurately differentiate high-grade glioma from brain metastasis. The adoption of standardized workflow to avoid potential data leakage as well as the integration of clinical features and radiomics are advised to consider in future studies.

关键词

Glioma Brain neoplasms Artificial intelligence Magnetic resonance imaging Quality improvement