Abstract Library

Welcome to the open-access search for all ENETS abstracts presented at the Annual ENETS Conferences.

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ENETS Abstract Search

#3654 Digital image analysis of Ki-67 heterogeneity of pancreatic neuroendocrine neoplasms with or without liver metastasis

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.

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,

#3317 Digital image analysis of the Ki67 spatial distribution improves classification and grading in gastroenteropancreatic neuroendocrine neoplasms

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.

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,

#584 KI-67 HETEROGENEITY IN GASTRO-ENTERO-PANCREATIC NEUROENDOCRINE TUMORS

Introduction: The neuroendocrine tumor (NET) proliferation-based grading system (ENETs/WHO) has proved reliable for prognostic stratification, however concerns exist on Ki67 heterogeneity.

Conference:

Presenting Author:

Authors: Grillo F, Albertelli M, Calamaro P, Borra T, Bruno S,

Keywords: neuroendocrine tumor, grade, heterogeneity,