Abstract
To evaluate the potential application of computed tomography (CT) radiomics in the prediction of BRCA1-associated protein 1 (BAP1) mutation status in patients with clear-cell renal cell carcinoma (ccRCC). In this retrospective study, clinical and CT imaging data of 54 patients were retrieved from The Cancer Genome Atlas–Kidney Renal Clear Cell Carcinoma database. Among these, 45 patients had wild-type BAP1 and nine patients had BAP1 mutation. The texture features of tumor images were extracted using the Matlab-based IBEX package. To produce class-balanced data and improve the stability of prediction, we performed data augmentation for the BAP1 mutation group during cross validation. A model to predict BAP1 mutation status was constructed using Random Forest Classification algorithms, and was evaluated using leave-one-out-cross-validation. Random Forest model of predict BAP1 mutation status had an accuracy of 0.83, sensitivity of 0.72, specificity of 0.87, precision of 0.65, AUC of 0.77, F-score of 0.68. CT radiomics is a potential and feasible method for predicting BAP1 mutation status in patients with ccRCC.
Highlights
Clear-cell renal cell carcinoma is the most common kidney cancer in adults, and its pathogenesis is complicated
We evaluated the potential application of the radiomics method in predicting BRCA1-associated protein 1 (BAP1) mutation status in patients with Clear-cell renal cell carcinoma (ccRCC)
Among the features used for model construction, most were extracted from Laplacian of Gaussian (LoG)-filtered images, with a few extracted from the original images
Summary
Clear-cell renal cell carcinoma (ccRCC) is the most common kidney cancer in adults, and its pathogenesis is complicated. Tumor imaging phenotypes are closely associated with their gene expression patterns, protein, or other molecular changes [11]. Liu et al utilized computed tomography (CT) imaging features to predict epidermal growth factor receptor (EGFR) mutations in patients with non-small cell lung cancer. Their results suggest that wild-type EGFR is associated with conditions such as emphysema and airway malformation, while EGFR mutations are associated with ground-glass opacity changes [12]. We evaluated the potential application of the radiomics method in predicting BAP1 mutation status in patients with ccRCC
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