Automatic method for assessment of proliferation index in digital images of DLBCL tissue section

• Autorzy: Gomolka Ryszard S. , Korzynska Anna , Siemion Krzysztof , Gabor-Siatkowska Karolina , Klonowski Wlodzimierz

Identyfikatory

DOI

10.1016/j.bbe.2018.09.004

• Języki publikacji: EN

Abstrakty

EN

Diffuse large B-cell lymphoma (DLBCL) is a fast-growing and aggressive neoplasm originating from B lymphocytes. Evaluation of proliferation index (PI) based on Ki67 immunohistochemical nuclear staining is used to distinguish proliferating (immunopositive) from nonproliferating (immunonegative) lymphoma cells. Human interpretation of PI varies and is time-consuming, therefore automatic computer-assisted approach may facilitate the performance. Herein we propose a new fully automatic proliferation index estimation (FLAPIE) algorithm, dedicated to detection of immunopositive and immunonegative nuclei, and evaluation of PI in digital microscopy images of DAB&H-stained samples from patients with high-grade DLBCL. FLAPIE performs nuclei detection in original RGB colour space and is independent of image brightness due to its textural-statistical approach. Validation of FLAPIE was performed in 61 non-overlapping whole-slide imagefragments and compared to the results of PI estimation by QuPath open-source software, MetPiKi algorithm and manual evaluation by two independent observers. Interobserver agreement was calculated between the nuclei count and PIs by two observers. High concordance was found between both DAB and H-stained nuclei count, and PIs by two observers. Compared to MetPiKi, FLAPIE presented improved results of DAB and H-stained nuclei detection. In contrary to MetPiKi and QuPath, FLAPIE performed nuclei detection in all images and its results closely matched the number of DAB-stained nuclei evaluated by two observers. No significant difference was found between PIs by all computational methods and observers. FLAPIE achieved good results in PI estimation and prospectively aims to serve as a tool for clinical application in support of patients selection and decision to treatment.

Słowa kluczowe

EN

diffuse large B-cell lymphoma; Ki67; digital histopathology; computer aided diagnosis

PL

chłoniak z limfocytów B; histopatologia cyfrowa; diagnoza wspomagana komputerowo

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2019
• Tom: Vol. 39, no. 1
• Strony: 30--37
• Opis fizyczny: Bibliogr. 40 poz., rys., wykr.

Twórcy

autor

Gomolka Ryszard S.

• Laboratory of Processing and Analysis of Microscopic Images, Hybrid and Analytical Microbiosystems Department, Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland

autor

Korzynska Anna

• Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, 4 Ks. Trojdena st., 02-109 Warsaw, Poland

autor

Siemion Krzysztof

• Laboratory of Processing and Analysis of Microscopic Images, Hybrid and Analytical Microbiosystems Department, Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland; Department of Pathomorphology, Central Clinical Hospital of the Ministry of the Interior and Administration, Warsaw, Poland

autor

Gabor-Siatkowska Karolina

• Laboratory of Processing and Analysis of Microscopic Images, Hybrid and Analytical Microbiosystems Department, Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland

autor

Klonowski Wlodzimierz

• Laboratory of Processing and Analysis of Microscopic Images, Hybrid and Analytical Microbiosystems Department, Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland

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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).