Comparison of Radiomic Features in a Diverse Cohort of Patients With Pancreatic Ductal Adenocarcinomas - Permuth, Jennifer B.; Vyas, Shraddha; Li, Jiannong; Chen, Dung-Tsa; Jeong, Daniel; Choi, Jung W. (Frontiers in Oncology, 2021)
Background: Significant racial disparities in pancreatic cancer incidence and mortality rates exist, with the highest rates in African Americans versus Non-Hispanic Whites and Hispanic/Latinx populations. Quantitative imaging or ‘radiomic’ features may serve as noninvasive surrogates for underlying biological factors and heterogeneity that characterize pancreatic tumors from African Americans, yet studies are lacking in this area. The objective of this pilot study was to determine if the radiomic pancreatic tumor profile extracted from pre-treatment computed tomography (CT) images differs between African Americans and other groups. Methods: We evaluated a diverse retrospective cohort of 71 pancreatic cancer cases who underwent pre-treatment CT imaging at Moffitt Cancer Center and Research Institute. Whole lesion semi-automated segmentation was performed on each slice of the lesion on all pretreatment venous phase CT exams using Healthmyne Software to generate a volume of interest. To reduce feature dimensionality, 135 highly relevant non-texture and texture features were extracted from each segmented lesion and analyzed for each volume of interest. Results: Thirty features were identified and significantly associated with race/ethnicity based on Kruskal-Wallis test. Ten of the radiomic features were highly associated with race/ethnicity independent of tumor grade including sphericity, volumetric mean Hounsfield units (HU), minimum HU, coefficient of variation HU, 4 gray level texture features, and 2 wavelet texture features. A radiomic signature summarized by the first principal component partially differentiated African American from non-African American tumors (area underneath the curve=0.80). Poorer survival among African Americans compared to Non-African Americans was observed for tumors with lower volumetric mean CT (HR: 3.90 (95% CI:1.19-12.78), p=0.024), lower GLCM Avg Column Mean (HR:4.75 (95% CI: 1.44,15.37), p=0.010), and higher GLCM Cluster Tendency (HR:3.36 (95% CI: 1.06-10.68), p=0.040), and associations persisted in volumetric mean CT and GLCM Avg Column after adjustment for clinicopathologic factors. Conclusions: This pilot study identified several textural radiomics features associated with poor overall survival among African Americans with PDAC, independent of other prognostic factors. Our findings suggest that CT radiomic features may serve as surrogates for underlying biological factors and add value in predicting clinical outcomes when integrated with other parameters in studies of cancer health disparities.