Histopathology Slide Indexing and Search: Are We There Yet?

TL;DR

This study evaluates three state-of-the-art histopathology slide search engines, revealing their current limitations in reliability and subtle feature detection, and proposes requirements for clinical readiness.

Contribution

The paper provides a qualitative assessment of existing slide search engines and outlines minimal requirements for improving their clinical applicability.

Findings

All three search engines lack consistent reliability.

Difficulty in capturing subtle features of malignancy.

Limitations hinder diagnostic accuracy.

Abstract

The search and retrieval of digital histopathology slides is an important task that has yet to be solved. In this case study, we investigate the clinical readiness of three state-of-the-art histopathology slide search engines, Yottixel, SISH, and RetCCL, on three patients with solid tumors. We provide a qualitative assessment of each model's performance in providing retrieval results that are reliable and useful to pathologists. We found that all three image search engines fail to produce consistently reliable results and have difficulties in capturing granular and subtle features of malignancy, limiting their diagnostic accuracy. Based on our findings, we also propose a minimal set of requirements to further advance the development of accurate and reliable histopathology image search engines for successful clinical adoption.