Computer extracted measurements of intra-tumoral heterogeneity on H&E stained tissue images to distinguish short term and long term survivors in patients with non-small cell lung carcinoma.

Abstract

e20052 Background: Molecular and morphologic heterogeneity is an important characteristic of cancer. This spatial and temporal tumor heterogeneity has important implications on tumor behavior and response to therapies. This study aims to evaluate the role of computer extracted features of intra-tumoral heterogeneity (ITH) from digitized whole slide H&E stained images of early stage NSCLC patients treated with surgery as a prognostic marker for survival. Methods: A cohort of 89 early stage NSCLC patients treated with surgery with long term survival data were identified. 28 patients had OS> 3 years from the date of definitive surgery and were defined as long term survivors and 61 patients had OS < 3 years, and were defined as short term survivors. Corresponding H&E stained whole mounted lung tissue images was digitally scanned and a thoracic pathologist marked the primary tumor margins on these images. Our computational approach involved determining the variance in measurements relating to nuclear size, shape, and texture across the tissue section; Each feature was then assigned a morphologic diversity score (MDS) based off the variance; the top predictive MDS features were identified via Wilcoxon Rank Sum Test and then evaluated via a quadratic classifier using 3-fold cross validation. Kaplan-Meier (KM) survival analysis was performed for the ITH features, as well as T- and N-stage. Results: The top ranked MDS features yielded a mean area under the receiver operating characteristic curve (AUC) of 0.66 in discriminating short term from long term survivors. A p=0.00657 (see Table) was obtained for KM-analysis of the ITH features. Conclusions: Computer extracted image features of ITH enabled differentiation of NSCLC patients with short and longer term survival. Large scale multi-site validation will need to be done to establish ITH measurements as a prognostic biomarker for NSCLC patients. [Table: see text]