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The 1000 Mitoses Project : A Consensus-Based International Collaborative Study on Mitotic Figures Classification

Title: 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.
Contributors: Research Program in Systems Oncology; University of Helsinki; HUS Radiology and Pathology
Publisher Information: SAGE Publications Inc.
Publication Year: 2025
Collection: Helsingfors Universitet: HELDA – Helsingin yliopiston digitaalinen arkisto
Subject Terms: digital pathology; international collaboration; mitotic figure mimics; mitotic figures; social media; Surgery; anesthesiology; intensive care; radiology
Description: 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. ; Peer reviewed
Document Type: article in journal/newspaper
File Description: application/pdf
Language: English
Relation: https://hdl.handle.net/10138/592722; 85190647356; 001204165900001
Availability: https://hdl.handle.net/10138/592722
Rights: cc_by_nc ; info:eu-repo/semantics/openAccess ; openAccess
Accession Number: edsbas.444B83CF
Database: BASE