CT texture analysis as a predictor of favorable response to anti-PD1 monoclonal antibodies in metastatic skin melanoma.

Abstract Purpose The purpose of this study was to determine whether texture analysis features on pretreatment contrast-enhanced computed tomography (CT) images and their evolution can predict treatment response of metastatic skin melanoma (SM) treated with anti-PD1 monoclonal antibodies. Materials and methods Sixty patients (29 men, 31 women; median age, 56 years; age range: 27–91 years) with metastatic SM treated with pembrolizumab (43/60; 72%) or nivolumab (17/60; 28%) were included. Texture analysis of SM metastases was performed on baseline and first post-treatment evaluation CT examinations. Mean gray-level, entropy, kurtosis, skewness, and standard deviation values were derived from the pixel distribution histogram before and after spatial filtration at different anatomic scales, ranging from fine to coarse. Lasso penalized Cox regression analyses were performed to identify independent variables associated with favorable response to treatment. Results A total of 127 metastases were analyzed, with a median of two metastases per patient. Skewness at fine texture scale (spatial scale filtration [SSF] = 2; Hazard ratio [HR]: 3.51; 95% CI: 2.08–8.57; P = 0.010), skewness at medium texture scale (SSF = 3; HR: 0.56; 95% CI: 0.11–1.59; P = 0.014), variation of entropy at fine texture scale (SSF = 2; HR: 37.76; 95% CI: 3.48–496.22; P = 0.008) and LDH above the threshold of 248 UI/L (HR: 3.56; 95% CI: 1.78–21.35; P = 0.032] were independent predictors of response to treatment. Conclusion Pretreatment CT texture analysis-derived tumor skewness and variation of entropy between baseline and first control CT examination may be used as predictors of favorable response to anti-PD1 monoclonal antibodies in patients with metastatic SM.