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February 19, 2026Clinical Cancer Research

Abstract PD11-10: Optimizing HER2 Diagnostic Pathways: AI Assistance Enriches Gene Amplified Cases in Equivocal Category and Reduces Turnaround Time

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Authors

MVM. VecslerSKS. KrishnamurthySSS. Schnitt

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Overview

Observational study evaluates AI's impact on HER2 scoring accuracy in breast cancer, suggesting enhanced diagnostic workflows.

Key Points

  • This study aims to assess the effectiveness of an AI-assisted HER2 IHC scoring system in improving diagnostic accuracy and reducing turnaround times.
  • Included 2,300 patients' biopsies and excisions from 13 laboratories across US, EU, and UK.
  • 28 pathologists reviewed HER2 IHC slides, both unassisted and with AI assistance.
  • Compared AI scoring against ground truth established by expert breast pathologists using ISH results.
  • AI-assisted pathologists improved overall accuracy from 76.4% to 82.0% (P=0.0000).
  • Accuracy increased across all HER2 categories, from 79.3% to 84.4% with AI help.
  • Proportion of slides requiring ISH testing decreased from 29.0% to 18.6%, implying a 35% reduction in turnaround time.

Cite This Study

Vecsler et al. (2026) studied this question.

synapsesocial.com/papers/6996a957ecb39a600b3f0605https://doi.org/10.1158/1557-3265.sabcs25-pd11-10
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