Supplementary Material for: Radiomics Correlation to CD68+ Tumor-Associated Macrophages in Clear Cell Renal Cell Carcinoma

Introduction: Renal cell carcinoma (RCC) is the ninth most common cancers worldwide, with clear cell RCC (ccRCC) being the most frequent histological subtype. The tumor immune microenvironment (TIME) of ccRCC is an important factor to guide treatment, but current assessments are tissue-based, which can be time-consuming and resource-intensive. In this study, we used radiomics extracted from clinically performed computed tomography (CT) as a non-invasive surrogate for CD68 tumor-associated macrophages (TAMs), a significant component of ccRCC TIME. Methods: TAM population was measured by CD68+/PanCK+ ratio and tumor-TAM clustering was measured by normalized K function was calculated from multiplex immunofluorescence (mIF). A total of 1,076 regions on mIF slides from 78 patients were included. Radiomic features were extracted from multiphase CT of the ccRCC tumor. Statistical machine learning models, including Random Forest, AdaBoost, and ElasticNet, were used to predicted TAM population and tumor-TAM clustering. Results: The best models achieved an AUROC of 0.81 (95% CI: [0.69, 0.92]) for TAM population and 0.77 (95% CI: [0.66, 0.88]) for tumor-TAM clustering, respectively. Conclusion: Our study demonstrates the potential of using CT radiomics derived imaging markers as a surrogate for assessment of TAM in ccRCC for real time treatment response monitoring and patient selection for targeted therapies and immunotherapies.