arXiv AI By Simon Graham, Mostafa Jahanifar, Quoc Dang Vu, Vygante Maskoliunaite, Donatas Petroska, Ruta Barbora Valkiuniene, Ayat Gamal Lashen, Jen Hong Ong, Amede Ogechi Nnorom, Sinclair Couper, Natasha Kardasz, Reshma Agrawal, Brinder Singh Chohan, Jose Luis Solorzano Rendon, Shonali Natu, Arvydas Laurinavicius, Nasir Rajpoot, David Snead

AI-assisted mitotic counting improves reproducibility and efficiency across multiple tumour types

Read the original on arXiv AI →

The study introduces MitPro, an AI tool that guides pathologists to regions with high mitotic activity and highlights mitotic figures, aiming to reduce variability and time in tumour grading. In a retrospective paired reader study of 385 whole‑slide images across seven tumour types, AI assistance raised the intraclass correlation coefficient from 0.589 to 0.949 and cut median assessment time from 286.4 to 127.8 seconds. The tool also produced a slight increase in mitotic counts, aligning with the detection of more active hotspots, while the frequency of score changes matched typical inter‑pathologist variation.

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