The 1000 Mitoses Project: A Consensus-Based International Collaborative Study on Mitotic Figures Classification
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. (2024)
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.
2024
INTERNATIONAL JOURNAL OF SURGICAL PATHOLOGY
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202405296412
https://urn.fi/URN:NBN:fi:tuni-202405296412
Kuvaus
Peer reviewed
Tiivistelmä
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.
Kokoelmat
- TUNICRIS-julkaisut [20724]