Radiomics evaluates the EGFR mutation status from the brain metastasis: a multi-center study

• Published in: Physics in medicine & biology 2022-06, Vol.67 (12), p.125003
• Main Authors: Cao, Ran, Pang, Ziyan, Wang, Xiaoyu, Du, Zhe, Chen, Huanhuan, Liu, Jiani, Yue, Zhibin, Wang, Huan, Luo, Yahong, Jiang, Xiran
• Format: Article
• Language: English
• Subjects: brain metastasis; EGFR; lung adenocarcinoma; radiomics
• ISSN: 0031-9155; 1361-6560
• DOI: 10.1088/1361-6560/ac7192

To develop and externally validate habitat-based MRI radiomics for preoperative prediction of the EGFR mutation status based on brain metastasis (BM) from primary lung adenocarcinoma (LA). We retrospectively reviewed 150 and 38 patients from hospital 1 and hospital 2 between Jan. 2017 and Dec. 2021 to form a primary and an external validation cohort, respectively. Radiomics features were calculated from the whole tumor (W), tumor active area (TAA) and peritumoral oedema area (POA) in the contrast-enhanced T1-weighted (T1CE) and T2-weighted (T2W) MRI image. The least absolute shrinkage and selection operator (LASSO) was applied to select the most important features and to develop radiomics signatures (RSs) based on W (RS-W), TAA (RS-TAA), POA (RS-POA) and in combination (RS-Com). The area under receiver operating characteristic (ROC) curve (AUC) and accuracy analysis were performed to assess the performance of radiomics models. RS-TAA and RS-POA outperformed RS-W in terms of AUC, ACC and sensitivity. The multi-region combined RS-Com showed the best prediction performance in the primary validation (AUCs, RS-Com vs. RS-W vs. RS-TAA vs. RS-POA, 0.901 vs. 0.699 vs. 0.812 vs. 0.883) and external validation (AUCs, RS-Com vs. RS-W vs. RS-TAA vs. RS-POA, 0.900 vs. 0.637 vs. 0.814 vs. 0.842) cohort. The developed habitat-based radiomics models can accurately detect the EGFR mutation in patients with BM from primary LA, and may provide a preoperative basis for personal treatment planning.