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Related Experiment Video

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Can AI-assisted microscope facilitate breast HER2 interpretation? A multi-institutional ring study.

Meng Yue1, Jun Zhang2, Xinran Wang1

  • 1Department of Pathology, The Fourth Hospital of Hebei Medical University, No. 12 Jiankang Road, Shijiazhuang, 050011, Hebei, China.

Virchows Archiv : an International Journal of Pathology
|July 19, 2021
PubMed
Summary

An artificial intelligence (AI)-assisted microscope significantly improved human epidermal growth factor receptor-2 (HER2) assessment accuracy in breast cancer. Pathologists showed higher consistency and reliability when using the AI microscope compared to traditional methods.

Keywords:
Artificial intelligence–assisted microscopeBreast cancerHER2

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Area of Science:

  • Oncology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Human epidermal growth factor receptor-2 (HER2) protein and gene expression are crucial for breast cancer prognosis.
  • Visual HER2 staining evaluation by pathologists exhibits significant intraobserver and interobserver variability.
  • Current methods for HER2 assessment lack consistent accuracy and reliability.

Purpose of the Study:

  • To develop and evaluate an artificial intelligence (AI)-assisted microscope for improved HER2 assessment in breast cancer.
  • To enhance the accuracy and reliability of HER2 scoring using AI technology.
  • To reduce variability in HER2 evaluation among pathologists.

Main Methods:

  • An AI-assisted microscope was developed, integrating a cell-level classification HER2 scoring algorithm and an augmented reality module.
  • A three-round ring study involving 33 pathologists from 6 hospitals assessed 50 infiltrating duct carcinoma (NOS) cases.
  • Pathologists' interpretations were compared across three conditions: online whole-slide images (WSIs), conventional microscopy, and the AI-assisted microscope.

Main Results:

  • The AI-assisted microscope significantly improved the consistency and accuracy of HER2 assessment compared to conventional methods (p < 0.001).
  • AI assistance enhanced the precision of immunohistochemistry (IHC) 3+ and 2+ scoring and ensured recall of fluorescent in situ hybridization (FISH)-positive cases in IHC 2+.
  • Pathologists demonstrated a high acceptance rate (0.90) of the AI scoring results, indicating strong agreement.

Conclusions:

  • AI-assisted microscopy offers a substantial improvement in HER2 assessment accuracy and reliability for breast cancer.
  • This technology has the potential to standardize HER2 scoring, leading to better patient prognosis and treatment decisions.
  • The high pathologist acceptance rate suggests the AI microscope is a valuable tool for clinical pathology practice.