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.

翻译：数字组织病理学切片的检索与回取是一项亟待解决的重要任务。在本案例研究中，我们针对三名实体瘤患者，评估了Yottixel、SISH和RetCCL三种最新组织病理学切片搜索引擎的临床就绪性。我们对各模型在提供可靠且对病理学家有价值的检索结果方面的表现进行了定性评估。研究发现，所有三种图像搜索引擎均未能持续生成可靠的结果，且在捕捉恶性肿瘤的细微与隐蔽特征方面存在困难，从而限制了其诊断准确性。基于研究结果，我们还提出了一套最低要求，旨在进一步推动准确可靠的组织病理学图像搜索引擎的开发，以促进其成功应用于临床。