OMG-Octo: Uniformised large scale database of mitotic figures in Haematoxylin and Eosin-Stained Slides

In this study, we established a large uniform database of pan-cancer mitotic figures (MFs) by deploying the Segment Anything Model (SAM), a foundation object detection model, in five open-source datasets (ICPR, TUPAC, CCMCT, CMC, MIDOG++) using a single nuclei mask format. Manual revision of the masks was performed to maximise database quality. Then, we contributed an in-house dataset of human soft tissue tumours (STT) MFs (N=8,400) (Soft-Tissue Mitotic Figures, STMF). Although STT represents a rare tumour group, they comprise over 100 subtypes exhibiting a wide variety of histological appearances and mimic other tumours including common cancers such as melanoma, carcinoma and lymphoma. STT harbours a variable number of MFs and aids in reaching a diagnosis and predicting disease behaviour.  The STMF was initiated by staining WSIs with an anti-phosphorylated histone H3 (pHH3) antibody to target MFs which was expanded and improved by AI-assisted annotations made by pathologists.