Overall Survival Prediction in Renal Cell Carcinoma Patients Using Computed Tomography Radiomic and Clinical Information

• DOI: 10.1007/s10278-021-00500-y
• Publication Date: 2021-08-11T22:02:24Z
• Authors: Zahra Khodabakhshi; Mehdi Amini; Shayan Mostafaei; Atlas Haddadi Avval; Mostafa Nazari; Mehrdad Oveisi; Isaac Shiri; Habib Zaidi
• Keywords: Kidney cancer

The aim of this work is to investigate the applicability radiomic features alone and in combination with clinical information for prediction renal cell carcinoma (RCC) patients' overall survival after partial or radical nephrectomy. Clinical studies 210 RCC patients from Cancer Imaging Archive (TCIA) who underwent either nephrectomy were included study. Regions interest (ROIs) manually defined on CT images. A total 225 extracted analyzed along 59 features. An elastic net penalized Cox regression was used feature selection. Accelerated failure time (AFT) shared frailty model determine effects selected time. Eleven twelve based their non-zero coefficients. Tumor grade, tumor malignancy, pathology t-stage most significant predictors (OS) among (p < 0.002, 0.02, 0.018, respectively). OS flatness, area density, median 0.05, Along important features, such as heterogeneity imaging biomarkers are significantly correlated patients.