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Cell Oncol (Dordr). 2019 Aug;42(4):555-569. doi: 10.1007/s13402-019-00445-z. Epub 2019 Apr 15.

Deep learning and manual assessment show that the absolute mitotic count does not contain prognostic information in triple negative breast cancer.

Author information

1
Department of Pathology, Radboud University Medical Center, PO Box 9100, 6500, HB, Nijmegen, the Netherlands. maschenka.balkenhol@radboudumc.nl.
2
Department of Pathology, Radboud University Medical Center, PO Box 9100, 6500, HB, Nijmegen, the Netherlands.
3
Department of Pathology, Canisius Wilhelmina Hospital, Nijmegen, the Netherlands.
4
Department of Pathology, Haaglanden Medical Center, 's-Gravenhage, the Netherlands.

Abstract

PURPOSE:

The prognostic value of mitotic count for invasive breast cancer is firmly established. As yet, however, limited studies have been aimed at assessing mitotic counts as a prognostic factor for triple negative breast cancers (TNBC). Here, we assessed the prognostic value of absolute mitotic counts for TNBC, using both deep learning and manual procedures.

METHODS:

A retrospective TNBC cohort (n = 298) was used. The absolute manual mitotic count was assessed by averaging counts from three independent observers. Deep learning was performed using a convolutional neural network on digitized H&E slides. Multivariable Cox regression models for relapse-free survival and overall survival served as baseline models. These were expanded with dichotomized mitotic counts, attempting every possible cut-off value, and evaluated by means of the c-statistic.

RESULTS:

We found that per 2 mm2 averaged manual mitotic counts ranged from 1 to 187 (mean 37.6, SD 23.4), whereas automatic counts ranged from 1 to 269 (mean 57.6; SD 42.2). None of the cut-off values improved the models' baseline c-statistic, for both manual and automatic assessments.

CONCLUSIONS:

Based on our results we conclude that the level of proliferation, as reflected by mitotic count, does not serve as a prognostic factor for TNBC. Therefore, TNBC patient management based on mitotic count should be discouraged.

KEYWORDS:

Artificial intelligence; Mitotic count; Prognosis; Triple negative breast cancer

PMID:
30989469
DOI:
10.1007/s13402-019-00445-z

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