Digital image analysis of the Ki67 spatial distribution improves classification and grading in gastroenteropancreatic neuroendocrine neoplasms

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Introduction: Ki67 is a reliable grading and prognostic biomarker in gastroenteropancreatic neuroendocrine neoplasms (NENs). Intra-tumor heterogeneity of Ki67, correlated with NENs classification, is a valuable factor requiring robust measurement protocols. Digital image analysis enables high accuracy and reproducibility to evaluate the spatial distribution of Ki67.

Aim(s): This study aims to investigate the utility of digital protocols for the Ki-67 heterogeneity profile in the classification and grading of NENs.

Materials and methods: Resection cases of neuroendocrine tumors (NETs) (G1 n=21; G2 n=25; G3 n=31) and neuroendocrine carcinomas (NECs) (n=25) were selected. Ki-67 index by immunohistochemistry was evaluated in all cases by digital image analysis. Coefficient of variation (CV) and heterogeneity score (HeS), calculated as the difference between the highest score and the lowest score, were assessed in the digital slides. The association between CV/HeS and classification or grading of NENs was determined.

Conference: 18th Annual ENETS Concerence (2021)

Presenting Author: Huang D

Authors: Huang D, Wang X, Tan C, Sheng W,

Keywords: digital image analysis, Ki67, spatial distribution, NEN, classification, grade,