Evidence map›Paper›PMID 34279719›Full record

ArticleVirchows Archiv : an international journal of pathology2021

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

Meng Yue, Jun Zhang, Xinran Wang, Kezhou Yan, Lijing Cai, Kuan Tian, Shuyao Niu, Xiao Han, Yongqiang Yu, Junzhou Huang and 3 more

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Virchows Archiv : an international journal of pathology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 3 pooled it
11.5field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 3 syntheses or guidelines pooled it, 55 citations in OpenAlex.

  1. Pooled it
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  14. Artificial intelligence in breast cancer: application and future perspectives.Journal of cancer research and clinical oncology · 2023
    Review
  15. Review
  16. Article
  17. Article
  18. Review
  19. HER2-Low Breast Cancer: Current Landscape and Future Prospects.Breast cancer (Dove Medical Press) · 2023
    Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 2 institutions in 1 country.

Meng YueDepartment of Pathology, The Fourth Hospital of Hebei Medical University, No. 12 Jiankang Road, Shijiazhuang, 050011, Hebei, China.
Jun ZhangTencent AI Lab, Nanshan District, Tencent Binhai Building, No. 33, Haitian Second Road, Shenzhen, 518054, Guangdong, China.
Xinran WangDepartment of Pathology, The Fourth Hospital of Hebei Medical University, No. 12 Jiankang Road, Shijiazhuang, 050011, Hebei, China.
Kezhou YanTencent AI Lab, Nanshan District, Tencent Binhai Building, No. 33, Haitian Second Road, Shenzhen, 518054, Guangdong, China.
Lijing CaiDepartment of Pathology, The Fourth Hospital of Hebei Medical University, No. 12 Jiankang Road, Shijiazhuang, 050011, Hebei, China.
Kuan TianTencent AI Lab, Nanshan District, Tencent Binhai Building, No. 33, Haitian Second Road, Shenzhen, 518054, Guangdong, China.
Shuyao NiuDepartment of Pathology, The Fourth Hospital of Hebei Medical University, No. 12 Jiankang Road, Shijiazhuang, 050011, Hebei, China.
Xiao HanTencent AI Lab, Nanshan District, Tencent Binhai Building, No. 33, Haitian Second Road, Shenzhen, 518054, Guangdong, China.
Yongqiang YuDepartment of Pathology, The Fourth Hospital of Hebei Medical University, No. 12 Jiankang Road, Shijiazhuang, 050011, Hebei, China.
Junzhou HuangTencent AI Lab, Nanshan District, Tencent Binhai Building, No. 33, Haitian Second Road, Shenzhen, 518054, Guangdong, China.
Dandan HanDepartment of Pathology, The Fourth Hospital of Hebei Medical University, No. 12 Jiankang Road, Shijiazhuang, 050011, Hebei, China.
Jianhua YaoTencent AI Lab, Nanshan District, Tencent Binhai Building, No. 33, Haitian Second Road, Shenzhen, 518054, Guangdong, China. jianhuayao@tencent.com.
Yueping LiuDepartment of Pathology, The Fourth Hospital of Hebei Medical University, No. 12 Jiankang Road, Shijiazhuang, 050011, Hebei, China. annama@163.com.ORCID http://orcid.org/0000-0002-4582-114X
Hebei Medical University · CNTencent (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The level of human epidermal growth factor receptor-2 (HER2) protein and gene expression in breast cancer is an essential factor in judging the prognosis of breast cancer patients. Several investigations have shown high intraobserver and interobserver variability in the evaluation of HER2 staining by visual examination. In this study, we aim to propose an artificial intelligence (AI)-assisted microscope to improve the HER2 assessment accuracy and reliability. Our AI-assisted microscope was equipped with a conventional microscope with a cell-level classification-based HER2 scoring algorithm and an augmented reality module to enable pathologists to obtain AI results in real time. We organized a three-round ring study of 50 infiltrating duct carcinoma not otherwise specified (NOS) cases without neoadjuvant treatment, and recruited 33 pathologists from 6 hospitals. In the first ring study (RS1), the pathologists read 50 HER2 whole-slide images (WSIs) through an online system. After a 2-week washout period, they read the HER2 slides using a conventional microscope in RS2. After another 2-week washout period, the pathologists used our AI microscope for assisted interpretation in RS3. The consistency and accuracy of HER2 assessment by the AI-assisted microscope were significantly improved (p < 0.001) over those obtained using a conventional microscope and online WSI. Specifically, our AI-assisted microscope improved the precision of immunohistochemistry (IHC) 3 + and 2 + scoring while ensuring the recall of fluorescent in situ hybridization (FISH)-positive results in IHC 2 + . Also, the average acceptance rate of AI for all pathologists was 0.90, demonstrating that the pathologists agreed with most AI scoring results.

Indexed as

Artificial IntelligenceImage Interpretation, Computer-AssistedImmunohistochemistryAutomation, LaboratoryBiomarkers, TumorBreast NeoplasmsCarcinoma, Ductal, BreastChinaErb-b2 Receptor Tyrosine KinasesFemaleHumansIn Situ Hybridization, FluorescenceMicroscopyObserver VariationPredictive Value of TestsReproducibility of ResultsBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesArtificial intelligence–assisted microscopeBreast cancerHER2

Identifiers

PMID34279719
OpenAlexW3184786609

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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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.