Pituitary adenoma classification: Tools to improve the current system

Authors

  • William C. McDonald Allina Health Laboratories – Abbott Northwestern Hospital, Minneapolis, MN 55407, USA

DOI:

https://doi.org/10.17879/freeneuropathology-2024-5226

Keywords:

Pituitary, Classification, Machine learning, Statistical learning

Abstract

The World Health Organization classification of pituitary tumors provides a framework for pathologists and researchers to classify pituitary adenomas. From the perspective of a practicing pathologist, this classification can be improved by pooling immunohistochemical data in a more standardized way, and by deliberately distinguishing features that assist in classification from those that do not. This article illustrates one general workflow to examine classification features consisting of immunohistochemical stains for anterior pituitary tumors, in order to promote debate and advance an evidence-based framework for classification.

Metrics

Metrics Loading ...

Downloads

Additional Files

Published

2024-01-10

How to Cite

McDonald, W. C. (2024). Pituitary adenoma classification: Tools to improve the current system. Free Neuropathology, 5, 2. https://doi.org/10.17879/freeneuropathology-2024-5226

Issue

Section

Opinion Pieces