Predicting patient response to cancer immunotherapy using quantitative computed tomography based texture analysis.

Abstract

e14536 Background: Immuno-Oncology (I-O) therapies such as PD-L1/PD-1 antibodies disrupt a protective mechanism for tumor cells to evade the host immune system. To minimize toxicity and cost of care, we aim to determine if quantitative texture analysis (QTA) can be used as a predictive biomarker for response to these new drugs. Methods: A pilot study consisting of 20 cancer patients with metastatic disease who received PD-L1/PD-1 antibodies was performed. The subject pool consisted of 10 subjects (NSCLC 3, Urothelial CA 3, TNBC 1, RCC 3) who achieved objective responses to I-O therapy compared to 10 subjects (NSCLC 5, Urothelial CA 2, Ovarian 1, Pancreatic 1, Cervical 1) with primary progression as their best response. Pre-treatment diagnostic CT scans of the chest, abdomen, and pelvis were analyzed using QTA. A minimum of 1 objectively measurable lesion ( > 10 mm in diameter) per study was identified to undergo QTA. Histogram readouts of tumor texture based upon tissue densities per pixel were obtained. Output values from the QTA provided an estimate of tumor signal properties as expressed as the mean pixel density, standard deviation, entropy, kurtosis, skewness, and mean positive pixel value. Results: There was no identifiable signature when examining all of the lesions together. There was statistically significant correlation noted between QTA and RECIST response for lung lesions (n = 14) based on the mean pixel density. A mean pixel density cutoff of 11.91 at a spatial scale factor of 3 predicted response with a sensitivity of 75% and a specificity of 100%. This achieved a Mann-Whitney Z statistic of 2.6 (p = 0.0092). Conclusions: Despite the small number of patients in this pilot study, there were promising findings when examining the mean pixel density of lung lesions, suggesting that quantitative textural analysis can be used to predict response to PD-L1/PD-1 antibodies. Further investigation is warranted in a larger population that can be differentiated by tumor type to validate these results.