Bridging radiomics to tumor immune microenvironment assessment in clear cell renal cell carcinoma

Alexander Te-Wei Shieh; Steven Yong Cen; Bino Varghese; Darryl Hwa Hwang; Xiaomeng Lei; Kirthika Gurumurthy; Imran Siddiqi; Manju Aron; Inderbir Gill; William Dean Wallace; Vinay Anant Duddalwar

doi:10.1117/12.2669717

6 March 2023 Bridging radiomics to tumor immune microenvironment assessment in clear cell renal cell carcinoma

Alexander Te-Wei Shieh, Steven Yong Cen, Bino Varghese, Darryl Hwa Hwang, Xiaomeng Lei, Kirthika Gurumurthy, Imran Siddiqi, Manju Aron, Inderbir Gill, William Dean Wallace, Vinay Anant Duddalwar

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Proceedings Volume 12567, 18th International Symposium on Medical Information Processing and Analysis; 1256703 (2023) https://doi.org/10.1117/12.2669717
Event: 18th International Symposium on Medical Information Processing and Analysis, 2022, Valparaíso, Chile

Abstract

Clear cell renal cell carcinoma (ccRCC) is a common cancer and could result in poor prognosis. Understanding individual tumor immune microenvironment (TIME) in ccRCC patients may predict prognosis and response to therapy. In this work, we explore the concept of using radiomic features extracted from computer tomography (CT) imaging to correlate the TIME measurements from multiplex immunohistochemistry (mIHC) analysis. Since CT imaging has long been the standard for evaluation of RCCs, it has the potential to provide noninvasive approximations of the tissue-based mIHC biomarkers. We selected two biomarkers that were grounded by clinical research: PD-L1 expression and CD8⁺PD-1⁺ T cell to CD8⁺ T cell ratio of the tumor epithelium. Then we extracted these two markers from a preliminary set of 52 patients using automated mIHC analysis. We used Random Forest, AdaBoost and ElasticNet to classify each sample as either expressing high or low levels of these markers. We found the radiomic features can correlate tumor epithelium PD-L1 >5%, PD-L1 >10%, and CD8⁺PD1⁺/CD8⁺ >37% with AUROC 0.75, 0.85 and 0.71, respectively.

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Alexander Te-Wei Shieh, Steven Yong Cen, Bino Varghese, Darryl Hwa Hwang, Xiaomeng Lei, Kirthika Gurumurthy, Imran Siddiqi, Manju Aron, Inderbir Gill, William Dean Wallace, and Vinay Anant Duddalwar "Bridging radiomics to tumor immune microenvironment assessment in clear cell renal cell carcinoma", Proc. SPIE 12567, 18th International Symposium on Medical Information Processing and Analysis, 1256703 (6 March 2023); https://doi.org/10.1117/12.2669717

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KEYWORDS

Tumors

Radiomics

Random forests

Cooccurrence matrices

Cancer

Elasticity

Computed tomography

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