Nuclear pleomorphism in canine cutaneous mast cell tumors: Comparison of reproducibility and prognostic relevance between estimates, manual morphometry, and algorithmic morphometry application/pdf eng Text journal article Testo Articolo di rivista Andreas Haghofer Eda Parlak Alexander Bartel Taryn A. Donovan Charles-Antoine Assenmacher Pompei Bolfa Michael J. Dark Andrea Fuchs-Baumgartinger Andrea Klang Kathrin Jäger Robert Klopfleisch Sophie Merz Barbara Richter F. Yvonne Schulman Hannah Janout Jonathan Ganz Josef Scharinger Marc Aubreville Stephan M. Winkler Matti Kiupel Christof A. Bertram Animals Dogs Dog Diseases Pathology Dog Diseases Diagnosis Prognosis Reproducibility of Results Cell Nucleus Pathology Algorithms Skin Neoplasms Veterinary Skin Neoplasms Pathology Skin Neoplasms Diagnosis Male Female Mastocytosis, Cutaneous Veterinary Mastocytosis, Cutaneous Pathology Mastocytosis, Cutaneous Diagnosis Variation in nuclear size and shape is an important criterion of malignancy for many tumor types; however, categorical estimates by pathologists have poor reproducibility. Measurements of nuclear characteristics can improve reproducibility, but current manual methods are time-consuming. The aim of this study was to explore the limitations of estimates and develop alternative morphometric solutions for canine cutaneous mast cell tumors (ccMCTs). We assessed the following nuclear evaluation methods for accuracy, reproducibility, and prognostic utility: (1) anisokaryosis estimates by 11 pathologists; (2) gold standard manual morphometry of at least 100 nuclei; (3) practicable manual morphometry with stratified sampling of 12 nuclei by 9 pathologists; and (4) automated morphometry using deep learning-based segmentation. The study included 96 ccMCTs with available outcome information. Inter-rater reproducibility of anisokaryosis estimates was low (k = 0.226), whereas it was good (intraclass correlation = 0.654) for practicable morphometry of the standard deviation (SD) of nuclear size. As compared with gold standard manual morphometry (area under the ROC curve [AUC] = 0.839, 95% confidence interval [CI] = 0.701-0.977), the prognostic value (tumor-specific survival) of SDs of nuclear area for practicable manual morphometry and automated morphometry were high with an AUC of 0.868 (95% CI = 0.737-0.991) and 0.943 (95% CI = 0.889-0.996), respectively. This study supports the use of manual morphometry with stratified sampling of 12 nuclei and algorithmic morphometry to overcome the poor reproducibility of estimates. Further studies are needed to validate our findings, determine inter-algorithmic reproducibility and algorithmic robustness, and explore tumor heterogeneity of nuclear features in entire tumor sections. Text Wissenschaftlicher Artikel Sage http://creativecommons.org/licenses/by/4.0/ © The Author(s) 2024 open access doi:10.1177/03009858241295399 2024 Veterinary Pathology https://phaidra.vetmeduni.ac.at/o:3989