Publication Database

Nuclear pleomorphism in canine cutaneous mast cell tumors:
comparison of reproducibility and prognostic relevance between estimates, manual morphometry, and algorithmic morphometry (2025)

Art

Zeitschriftenartikel / wissenschaftlicher Beitrag

Autoren

Haghofer, Andreas

Parlak, Eda

Bartel, Alexander (WE 16)

Donovan, Taryn A.

Assenmacher, Charles-Antoine

Bolfa, Pompei

Dark, Michael J.

Fuchs-Baumgartinger, Andrea

Klang, Andrea

Jäger, Kathrin

Klopfleisch, Robert (WE 12)

Merz, Sophie

Richter, Barbara

Schulman, F. Yvonne

Janout, Hannah

Ganz, Jonathan

Scharinger, Josef

Aubreville, Marc

Winkler, Stephan M.

Kiupel, Matti

Bertram, Christof A.

Quelle

Veterinary pathology : an internat. journal of natural and experimental disease in animals

Bandzählung: 62

Heftzählung: 2

Seiten: 161 – 177

ISSN: 0300-9858

Sprache

Englisch

Verweise

URL (Volltext): https://journals.sagepub.com/doi/10.1177/03009858241295399

DOI: 10.1177/03009858241295399

Pubmed: 39560067

Kontakt

Institut für Veterinär-Epidemiologie und Biometrie

Königsweg 67
14163 Berlin
+49 30 838 56034
epi@vetmed.fu-berlin.de

Abstract / Zusammenfassung

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.