Optimal Approaches to Grading Entero-Pancreatic Neuroendocrine Tumors Using Ki-67 Proliferation Index (Hotspot and Whole Slide Digital Quantitative Analysis)

Ibrahim Abukhiran; Azfar Neyaz; Michaela Kop; Ihsan Baroudi; Daniel Christensen; M-Nasan Abdul Baki; Hamdi Surakji; Nuha Shaker; Mariel L Bedell; Judy Jasser; Rayan Rammal; Mustafa Deebajah; Reetesh Pai; Liron Pantanowitz; Andrew Bellizzi

doi:10.1016/j.modpat.2025.100780

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Optimal Approaches to Grading Entero-Pancreatic Neuroendocrine Tumors Using Ki-67 Proliferation Index (Hotspot and Whole Slide Digital Quantitative Analysis)

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Optimal Approaches to Grading Entero-Pancreatic Neuroendocrine Tumors Using Ki-67 Proliferation Index (Hotspot and Whole Slide Digital Quantitative Analysis)

Ibrahim Abukhiran, Azfar Neyaz, Michaela Kop, Ihsan Baroudi, Daniel Christensen, M-Nasan Abdul Baki, Hamdi Surakji, Nuha Shaker, Mariel L Bedell, Judy Jasser, …

Modern pathology, Vol.38(8), 100780

08/2025

DOI: 10.1016/j.modpat.2025.100780

PMID: 40246079

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Abstract

Grading neuroendocrine tumors using Ki-67 PI is essential for prognostic assessment and therapeutic decision-making. However, the absence of standardized guidelines has led to methodological inconsistencies across pathology practices. This study aimed to establish more standardized approaches by evaluating grading methodologies and their impact on clinical outcomes using a large, multi-site dataset. We analyzed 734 tissue sections from 325 patients, applying Hotspot Analysis (HSA) and Whole Slide Analysis (WSA) to determine Ki-67 PI and WHO grade across primary tumors, regional metastases, and distant metastases. Ki-67 PI was quantified using digital image analysis, with WSA capturing the entire tumor proliferation profile and HSA focusing on the highest-proliferating region. A patient-wise analysis was performed to determine the highest-grade site per patient, and each case was assigned dual WHO grades based on HSA and WSA. To evaluate the generalizability of our findings, we analyzed an external validation cohort of 74 patients, which was processed with an independent image analysis software to ensure reproducibility. The analysis revealed that grading based solely on the primary tumor failed to predict clinical outcomes, as the highest-grade site varied among the primary tumor (26.1%), regional metastases (39.1%), and distant metastases (34.8%). Within G2 tumors, survival outcomes differed significantly based on grading methodology, with Diffuse G2 tumors (homogeneous Ki-67 distribution) demonstrating significantly worse survival compared to Focal G2 tumors (84 vs. 136 months, p < 0.01). Cox Proportional Hazards regression identified maximum WSA Ki-67 PI as the sole independent predictor of overall survival, whereas TNM stage and tumor location (pancreatic vs. jejunoileal) were not statistically significant. The external validation cohort reinforced these findings, confirming that Diffuse G2 tumors exhibited significantly worse progression-free survival than Focal G2 tumors. These findings emphasize the necessity of integrating both HSA and WSA for grading neuroendocrine tumors, as well as evaluating all available disease sites to ensure accurate prognostication. Incorporating digital image analysis into grading workflows can provide a more standardized, reproducible approach, improving clinical decision-making and patient outcomes.

digital quantitative analysis

enteropancreatic

grading

hotspot

Ki-67

neuroendocrine tumors

Details

Title: Subtitle: Optimal Approaches to Grading Entero-Pancreatic Neuroendocrine Tumors Using Ki-67 Proliferation Index (Hotspot and Whole Slide Digital Quantitative Analysis)
Creators: Ibrahim Abukhiran - University of Pittsburgh
Azfar Neyaz - University of Pittsburgh
Michaela Kop - University of Hawaiʻi at Mānoa
Ihsan Baroudi - University of Pittsburgh
Daniel Christensen - University of Pittsburgh
M-Nasan Abdul Baki - Allegheny General Hospital
Hamdi Surakji - University of Pittsburgh
Nuha Shaker - University of Pittsburgh
Mariel L Bedell - University of Pittsburgh
Judy Jasser - University of Pittsburgh Medical Center
Rayan Rammal - Memorial Sloan Kettering Cancer Center
Mustafa Deebajah - Cleveland Clinic
Reetesh Pai - University of Pittsburgh
Liron Pantanowitz - University of Pittsburgh
Andrew Bellizzi - University of Iowa Hospitals and Clinics. Electronic address: andrew-bellizzi@uiowa.edu
Resource Type: Journal article
Publication Details: Modern pathology, Vol.38(8), 100780
DOI: 10.1016/j.modpat.2025.100780
PMID: 40246079
NLM abbreviation: Mod Pathol
ISSN: 0893-3952
eISSN: 1530-0285
Publisher: ELSEVIER SCIENCE INC
Grant note: Department of Pathology at the University of IowaDepartment of Pathology at the University of Pittsburgh
This research received no external funding. The study was supported by generous interdepartmental resources from the Department of Pathology at the University of Iowa and the Department of Pathology at the University of Pittsburgh.
Language: English
Electronic publication date: 04/15/2025
Date published: 08/2025
Academic Unit: Pathology
Record Identifier: 9984811217302771

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