ArticleHistopathology2026
Optimizing breast core needle biopsy biomarker throughput using an AI-based workflow.
Article in Histopathology, 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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Authors and funding
8 authors.
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Abstract
aimsTo evaluate the feasibility, appropriate relevance and impact on turnaround time (TAT) of an AI-supported workflow in which AI, integrated in the Laboratory Information System (LIS) as well as in the daily workflow, autonomously triggers breast biomarker testing (ER, PR, HER2, Ki-67) for breast core needle biopsies with a high AI-based likelihood of invasive breast cancer. METHODS AND
resultsThis retrospective, unicentric implementation study utilized an AI system (IBEX™ Breast) to stratify H&E slides. For cases classified as 'high likelihood for invasive carcinoma', the LIS automatically ordered the standard biomarker panel (ER, PR, HER2 and Ki67), bypassing initial pathologist slide reading. The TAT was measured from the moment of the case assignment to both the availability of IHC staining (TAT
conclusionsIntegrated, LIS-embedded AI in the daily workflow significantly optimizes breast cancer biomarker turnaround time without compromising the diagnostic process of a pathology laboratory. This demonstrates the transformative potential of AI to enhance laboratory efficiency and support more rapid patient-centred oncologic care.
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