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

Abstract

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.

Keywords: digital pathology; international collaboration; mitotic figure mimics; mitotic figures; social media.

Figure 1.

Demographics of pathologists scoring the mitotic figures dataset. Years of practice among the staff pathologists (A) and location of practice categorized by continent (B).

Figure 2.

Distribution of tumor types used in the 1010 mitotic figures dataset. Abbreviations: GBM, glioblastoma multiforme; H&N SCC, head and neck squamous cell carcinoma; HCC, hepatocellular carcinoma; DLBC, diffuse large B-cell lymphoma; Cervical SCC, cervical squamous cell carcinoma.

Figure 3.

Agreement rates among pathologists across the overall dataset (A). Mitotic figure tiles categorized based on agreement rate from 85 pathologists (B).

Figure 4.

Agreement rates with mitotic figures stratified based on phase of mitosis (A). Representative images of different mitosis phases of high and low agreement (B, 40x magnification).

Figure 5.

Mitotic figures within the dataset characterized by potential mitotic figure mimics (A). Representative microscopy images of mitotic figure mimics observed in the dataset (B).