The 1000 Mitoses Project: A Consensus-Based International Collaborative Study on Mitotic Figures Classification
Authors: Lin Sherman , Tran Christopher , Bandari Ela , Romagnoli Tommaso , Li Yueyang , Chu Michael , Amirthakatesan Abinaya S. , Dallmann Adam , Kostiukov Andrii , Panizo Angel , Hodgson Anjelica , Laury Anna R. , Polonia Antonio , Stueck Ashley E. , Menon Aswathy A. , Morini Aurélien , Özamrak Birsen , Cooper Caroline , Trinidad Celestine Marie G. , Eisenlöffel Christian , Suleiman Dauda E. , Suster David , Dorward David A. , Aljufairi Eman A. , Maclean Fiona , Gul Gulen , Sansano Irene , Erana-Rojas Irma E. , Machado Isidro , Kholova Ivana , Karunanithi Jayanthi , Gibier Jean-Baptiste , Schulte Jefree J. , Li Joshua J.X. , Kini Jyoti R. , Collins Katrina , Galea Laurence A. , Muller Louis , Cima Luca , Nova-Camacho Luiz M. , Dabner Marcus , Muscara Matthew J. , Hanna Matthew G. , Agoumi Mehdi , Wiebe Nicholas J. P. , Oswald Nicola K. , Zahra Nusrat , Folaranmi Olaleke O. , Kravtsov Oleksandr , Semerci Orhan , Patil Namrata N. , Muthusamy Sundar Preethi , Charles Prem , Kumaraswamy Rajeswaran Priyadarshini , Zhang Qi , van der Griend Rachael , Pillappa Raghavendra , Perret Raul , Gonzalez Raul S. , Reed Robyn C. , Patil Sachin , Jiang Xiaoyin “Sara” , Qayoom Sumaira , Prendeville Susan , Baskota Swikrity U. , Tran Thanh-Truc , San Thar-Htet , Kukkonen Tiia-Maria , Kendall Timothy J. , Taskin Toros , Rutland Tristan , Manucha Varsha , Cockenpot Vincent , Rosen Yale , Rodriguez-Velandia Yessica P. , Ordulu Zehra , Cecchini Matthew J. 
Published: April 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 mm2 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.