Evidence map›Paper›PMID 41845525›Full record

ArticleBreast cancer research : BCR2026

AI-enhanced precision: boosting pathologist confidence in HER2 ultra-low diagnosis through intelligent re-screening.

Xin-Ping Wang, Ying Han, Min Yao, Hong-Wen Gao, Ping-Li Sun

Abstract read
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Article in Breast cancer research : BCR, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xin-Ping WangDepartment of Pathology, The Second Hospital of Jilin University, 4026 Yatai Road, Changchun, 130022, Jilin, China.
Ying HanDepartment of Pathology, Jilin Central General Hospital, Jilin, Jilin, China.
Min YaoDepartment of Pathology, The Second Hospital of Jilin University, 4026 Yatai Road, Changchun, 130022, Jilin, China.
Hong-Wen GaoDepartment of Pathology, The Second Hospital of Jilin University, 4026 Yatai Road, Changchun, 130022, Jilin, China. gaohongwen@jlu.edu.cn.
Ping-Li SunDepartment of Pathology, The Second Hospital of Jilin University, 4026 Yatai Road, Changchun, 130022, Jilin, China. pinglisun@jlu.edu.cn.

Funding

Department of Science and Technology of Jilin Province YDZJ202401451ZYTSJilin Province Key Laboratory 20170622006JCJilin Province Medical and Health Talent Special Project 2024WSZX-A01Jilin Province Medical and Health Talent Special Project 2024WSZX-B06
6 · The paper itself

Abstract

Accurate assessment of Human Epidermal Growth Factor Receptor 2 (HER2) immunohistochemistry (IHC) expression, particularly the precise identification of "HER2 ultra-low" status, is critical for guiding antibody-drug conjugate (ADC) therapies, such as trastuzumab deruxtecan (T-DXd) in breast cancer. Given the difficulty and poor consistency in interpreting HER2 ultra-low expression, this study evaluated an artificial intelligence (AI) tool for assisting pathologists in diagnosing HER2 ultra-low expression in breast cancer. The analysis included 188 breast cancer cases (376 whole-slide images), consisting of 136 matched core needle biopsy (CNB)-surgical excision (SE) pairs from patients without neoadjuvant therapy (NAT) and a separate cohort of 52 matched CNB-post-NAT SE pairs with HER2 IHC scores of 0 or 1+. All slides were scanned using the Roche VENTANA DP 600 scanner. The resulting whole-slide images (WSIs) were subsequently analyzed and scored for HER2 IHC expression using AI assistance via the Roche Navify

Indexed as

Artificial IntelligenceBreast NeoplasmsErb-b2 Receptor Tyrosine KinasesBiomarkers, TumorBiopsy, Large-Core NeedleFemaleHumansImmunohistochemistryIntelligent SystemsPathologistsBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesArtificial intelligenceBreast cancerHER2 ultra-lowImmunohistochemistry

Identifiers

PMID41845525
PMCPMC13113482

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.