Intratumoral spatial distribution of high-risk prostate cancer patterns: Evaluation on digital pathology.

Abstract

e17123 Background: The most recent guidelines from the European Urology Association (EUA) have recommended implementation of perilesional sampling for prostate biopsies in addition to lesion center sampling during targeted biopsies (TBx). In this study we investigate the spatial distribution of high risk prostate cancer patterns on whole mount digital pathology slides. Methods: 1108 whole mount pathology slides from 316 men were included in this study. Digital slides were annotated by a GU pathologist to reflect intratumoral heterogeneity of morphology patterns. Annotated histology patterns were categorized into three different groups: low (Gleason Grade (GG)1), intermediate (GG2, GG3), and high risk (GG4, GG5, Cribriform). The spatial distribution of patterns within tumor foci was evaluated with respect to 1 and 3mm defined interior edges. The location of a pattern was defined as the ratio from 0 to 1 of the amount of a pattern found within the defined edge and size of the pattern, with higher values indicating pattern proximity to the edge. Tumor regions too small to define an edge sperate from a center and one-pattern regions were excluded. A linear mixed effects model summarized the effects of patient GG, tumor foci size, tumor pattern size, and pattern risk on the edge ratio for 1 and 3mm edges, calculated as pixel ratio with respect to low risk patterns. Results: Median edge ratio values for 1 and 3mm edges were 0.70 and 1.0 for low risk patterns, 0.30 and 0.72 for intermediate risk patterns, and 0.17 and 0.69 for high risk patterns, respectively. Intermediate (β=-0.17, p<0.001) and high risk patterns (β=-0.23, p<0.001) were less localized to both interior edges. Spatial distributions at both edges differed for all paired risk groups. The size of histology patterns (β=-0.06, p<0.001) and tumor foci (β=-0.10, p<0.001) were also associated with less localization towards both interior edges. At the 1mm edge, GG5 patients (n=27) had an increase (β=0.11, p<0.001) in incidence towards the edge, but was fewer than GG4 (n=37) and GG3 (n=53). Conclusions: Our results reveal that high risk patterns are more commonly located at the center of tumors compared to low risk patterns. These results highlight the importance of lesion center sampling approach during TBx to identify more aggressive GG patterns. The effects of patient GG, tumor foci size, pattern size, and pattern risk on the edge ratio for 1 and 3mm edges, calculated as pixel ratio ~ (1|MRN/tumor foci) + high risk pattern + scale (pixels pattern) + scale (pixels tumor foci) + patient GG are summarized. 1mm edge 3 mm edge Predictors β estimates p β estimates p intermediate risk pattern -0.17 <0.001 -0.03 0.102 high risk pattern -0.23 <0.001 -0.09 <0.001 pixels pattern -0.06 <0.001 -0.07 <0.001 pixels tumor foci -0.10 <0.001 -0.09 <0.001 patient GG3 0.01 0.806 -0.00 0.886 patient GG4 0.02 0.309 -0.04 0.109 patient GG5 0.11 <0.001 0.04 0.133