Generalizing AI-driven Assessment of Immunohistochemistry across Immunostains and Cancer Types: A Universal Immunohistochemistry Analyzer

• URL: http://arxiv.org/abs/2407.20643v1
• Date: Tue, 30 Jul 2024 08:39:30 GMT
• Title: Generalizing AI-driven Assessment of Immunohistochemistry across Immunostains and Cancer Types: A Universal Immunohistochemistry Analyzer
• Authors: Biagio Brattoli, Mohammad Mostafavi, Taebum Lee, Wonkyung Jung, Jeongun Ryu, Seonwook Park, Jongchan Park, Sergio Pereira, Seunghwan Shin, Sangjoon Choi, Hyojin Kim, Donggeun Yoo, Siraj M. Ali, Kyunghyun Paeng, Chan-Young Ock, Soo Ick Cho, Seokhwi Kim,
• Abstract summary: We developed a Universal IHC (UIHC) analyzer, an AI model for interpreting IHC images regardless of tumor or IHC types. This multi-cohort trained model outperforms conventional single-cohort models in interpreting unseen IHCs.
• Score: 12.164507399614347
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Despite advancements in methodologies, immunohistochemistry (IHC) remains the most utilized ancillary test for histopathologic and companion diagnostics in targeted therapies. However, objective IHC assessment poses challenges. Artificial intelligence (AI) has emerged as a potential solution, yet its development requires extensive training for each cancer and IHC type, limiting versatility. We developed a Universal IHC (UIHC) analyzer, an AI model for interpreting IHC images regardless of tumor or IHC types, using training datasets from various cancers stained for PD-L1 and/or HER2. This multi-cohort trained model outperforms conventional single-cohort models in interpreting unseen IHCs (Kappa score 0.578 vs. up to 0.509) and consistently shows superior performance across different positive staining cutoff values. Qualitative analysis reveals that UIHC effectively clusters patches based on expression levels. The UIHC model also quantitatively assesses c-MET expression with MET mutations, representing a significant advancement in AI application in the era of personalized medicine and accumulating novel biomarkers.

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