arXiv 2306.170192024-01-04eess.IVcs.CVq-bio.TO

组织病理学切片索引与搜索：我们到了吗？

Histopathology Slide Indexing and Search: Are We There Yet?

Ronald Reagan University of California Los Angeles Medical Center（罗纳德·里根加州大学洛杉矶分校医学中心）；The University of Texas at Arlington（德克萨斯大学阿灵顿分校）

Helen H. Shang, Mohammad Sadegh Nasr, Jai Prakash Veerla, Parisa Boodaghi Malidarreh, MD Jillur Rahman Saurav, Amir Hajighasemi, Manfred Huber, Chace Moleta, Ji… 展开作者

Helen H. Shang, Mohammad Sadegh Nasr, Jai Prakash Veerla, Parisa Boodaghi Malidarreh, MD Jillur Rahman Saurav, Amir Hajighasemi, Manfred Huber, Chace Moleta, Jitin Makker, Jacob M. Luber

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AI总结：

本案例研究评估了Yottixel、SISH和RetCCL三种组织病理学切片搜索引擎在实体瘤患者上的临床就绪程度，发现其检索结果不一致且难以捕捉恶性细微特征，并提出促进临床应用的最低开发要求。

摘要：

数字组织病理学切片的搜索与检索是一项尚未解决的重要任务。在本案例研究中，我们在三名实体瘤患者身上调查了三种最先进的组织病理学切片搜索引擎（Yottixel、SISH和RetCCL）的临床就绪程度。我们对每个模型在提供可靠且对病理学家有用的检索结果方面的性能进行了定性评估。我们发现，这三种图像搜索引擎均未能产生一致可靠的结果，并且在捕捉恶性的细粒度和微妙特征方面存在困难，从而限制了其诊断准确性。基于我们的发现，我们还提出了一组最低要求，以进一步推动准确可靠的组织病理学图像搜索引擎的开发，从而实现成功的临床应用。

英文摘要：

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.

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