Digital image analysis of Ki-67 heterogeneity of pancreatic neuroendocrine neoplasms with or without liver metastasis

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Introduction: Ki-67 is a reliable grading and prognostic biomarker of gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs). The application of digital image analysis (DIA) enables new digital biomarkers in the assessment of Ki-67 heterogeneity distribution. Our previous study reported that the Morisita-Horn (MH) index, an ecological marker for the measurement of spatial colocalization variants, directly correlated with classification and grading in GEP-NENs and provided prognostic information.

Aim(s): This study aims to investigate the Ki-67 heterogeneity of pancreatic neuroendocrine neoplasms with or without liver metastasis using the MH index and to explore its potential predictive value for liver metastasis.

Materials and methods: A total of 79 resection samples of pancreatic neuroendocrine tumors (panNETs) (G1 n=39; G2 n=38; G3 n=2) were obtained. The DIA algorithm of the MH index was performed in whole-slide images (WSIs) of Ki-67 slides. The association between the MH index and tumor grade as well as liver metastases was determined.

Conference:

Presenting Author: Huang D

Authors: Zhang M, Han X, Ding X, Zhang B, Wang Y,

Keywords: pancreatic, Ki-67 heterogeneity, liver metastasis, Digital image analysis,