Resources / Automated artificial intelligence-based analysis to support clinical assessments of Ki-67 immunohistochemistry-stained neuroendocrine tumors in the routine workflow
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Automated artificial intelligence-based analysis to support clinical assessments of Ki-67 immunohistochemistry-stained neuroendocrine tumors in the routine workflow
Originally presented at PathVisions 2022
Background

Cell proliferation is commonly assessed to grade neuroendocrine tumors (NETs) and aid in the evaluation of patient prognosis and treatment selection. To grade NETs, a proliferation index (PI) is evaluated based on the presence of immunohistochemical staining of the Ki-67 nuclear antigen. In the gastrointestinal tract, grading is performed using WHO criteria for PI as Grade 1-3 (less than 3%, 3%-20%, and greater than 20% respectively). It is recommended to count at least 500 cells followed by calculating the percentage of Ki-67 positive nuclei for cases with the Ki-67 index close to grade cut-offs on eyeballing. Ki 67 proliferation index near cut-offs is a real challenge for practicing pathologists.

Authors and institutions

Vidya Arole MD1*, Jesse Kulewsky1, Jenifer Caldara2, Rachel Scarl DO1, Swati Satturwar MD1, Zaibo Li MD1, Wei Chen MD1, Anil Parwani MD1, Giovanni Lujan MD1

  1. The Ohio State University Wexner Medical Center
  2. Visiopharm Corporation
Topics
Translational US
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