The 1000 Mitoses Project: A Consensus-Based International Collaborative Study on Mitotic Figures Classification.
Sherman LinChristopher TranEla BandariTommaso RomagnoliYueyang LiMichael ChuAbinaya S AmirthakatesanAdam DallmannAndrii KostiukovAngel PanizoAnjelica J HodgsonAnna R LauryAntonio PolóniaAshley E StueckAswathy A MenonAurélien MoriniBirsen ÖzamrakCaroline CooperCelestine Marie G TrinidadChristian EisenlöffelDauda E SuleimanDavid SusterDavid A DorwardEman A AljufairiFiona MacleanGulen GulIrene SansanoIrma Elisa Eraña-RojasIsidro MachadoIvana KholovaJayanthi KarunanithiJean-Baptiste GibierJefree J SchulteJoshua Jing Xi LiJyoti R KiniKatrina M CollinsLaurence A GaleaLouis MullerLuca CimaLuiz Miguel Nova-CamachoMarcus DabnerMatthew J MuscaraMatthew G HannaMehdi AgoumiNicholas J P WiebeNicola K OswaldNusrat ZahraOlaleke O FolaranmiOleksandr KravtsovOrhan SemerciNamrata N PatilPreethi Muthusamy SundarPrem CharlesPriyadarshini Kumaraswamy RajeswaranQi ZhangRachael van der GriendRaghavendra PillappaRaul PerretRaul S GonzalezRobyn C ReedSachin PatilXiaoyin Sara JiangSumaira QayoomSusan PrendevilleSwikrity U BaskotaThanh-Truc TranThar-Htet SanTiia-Maria KukkonenTimothy J KendallToros TaskinTristan RutlandVarsha ManuchaVincent CockenpotYale RosenYessica P Rodriguez-VelandiaZehra OrduluMatthew J CecchiniPublished in: International journal of surgical pathology (2024)
Introduction. The identification of mitotic figures is essential for the diagnosis, grading, and classification of various different tumors. Despite its importance, there is a paucity of literature reporting the consistency in interpreting mitotic figures among pathologists. This study leverages publicly accessible datasets and social media to recruit an international group of pathologists to score an image database of more than 1000 mitotic figures collectively. Materials and Methods. Pathologists were instructed to randomly select a digital slide from The Cancer Genome Atlas (TCGA) datasets and annotate 10-20 mitotic figures within a 2 mm 2 area. The first 1010 submitted mitotic figures were used to create an image dataset, with each figure transformed into an individual tile at 40x magnification. The dataset was redistributed to all pathologists to review and determine whether each tile constituted a mitotic figure. Results. Overall pathologists had a median agreement rate of 80.2% (range 42.0%-95.7%). Individual mitotic figure tiles had a median agreement rate of 87.1% and a fair inter-rater agreement across all tiles (kappa = 0.284). Mitotic figures in prometaphase had lower percentage agreement rates compared to other phases of mitosis. Conclusion. This dataset stands as the largest international consensus study for mitotic figures to date and can be utilized as a training set for future studies. The agreement range reflects a spectrum of criteria that pathologists use to decide what constitutes a mitotic figure, which may have potential implications in tumor diagnostics and clinical management.