Evaluating AI-Based Mitosis Detection for Breast Carcinoma in Digital Pathology: A Clinical Study on Routine Practice Integration.

Clara Simmat¹, Loris Guichard², Stéphane Sockeel¹, Nicolas Pozin¹, Rémy Peyret¹, Magali Lacroix-Triki³, Catherine Miquel⁴, Arnaud Gauthier⁵, Marie Sockeel¹, Sophie Prévot²

¹Primaa, 75002 Paris, France.

²Hôpital Bicêtre (AP-HP), Paris-Saclay University, 94270 Kremin-Bicêtre, France.

³Gustave-Roussy Cancer Campus-Grand Paris, 94800 Villejuif, France.

⁴Hôpital Saint-Louis (AP-HP), Paris Cité University, 75010 Paris, France.

⁵Institut Curie, PSL University, 75005 Paris, France.

PubMed PMC DOI PDF

Abstract

Background/Objectives: An accurate assessment of mitotic activity is crucial in the histopathological diagnosis of invasive breast carcinoma. However, this task is time-consuming and labor-intensive, and suffers from high variability between pathologists. Methods: To assist pathologists in routine diagnostics, we developed an artificial intelligence (AI)-based tool that uses whole slide images (WS…

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