Towards computer aided diagnosis of infective endocarditis in whole-slide images of heart valve tissue using FISH

Autor: Bruns Volker, Franz Daniela, Kuritcyn Petr, Wiesmann Veit, Rathke Magnus, Wittenberg Thomas, Wießner Alexandra, Kursawe Laura, Moter Annette, Kikhney Judith, Münzenmayer Christian
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Current Directions in Biomedical Engineering, Vol 7, Iss 2, Pp 468-471 (2021)
Druh dokumentu: article
ISSN: 2364-5504
2021-2119
DOI: 10.1515/cdbme-2021-2119
Popis: Infective endocarditis (IE) is an infection of the endocardium, and the heart valves associated with high morbidity and mortality. Fluorescence in situ Hybridization (FISH) is a molecular imaging technique used for diagnosis of IE based on histological heart valve tissue sections. FISH allows detection and identification of microorganisms and gives information about their quantity and spatial distribution. This information is important to guide appropriate antibiotic treatment. However, as manual FISH image analysis is time- and costexpensive, an automated image analysis pipeline (consisting of tissue segmentation, bacteria detection, and spot detection modules) is proposed to assist locating potential regions with microorganisms. The proposed approach was evaluated in a study, where five observers manually assessed a set of 171 fields-of-view (FoVs) captured in 400-fold magnification from 10 randomly chosen WSI for the presence of microorganisms, morphologically detected by the nucleic acid stain DAPI. The task of the observers was to mark the presented image using a 2-class score (‘positive/questionable’ or ‘negative’). The human assessment was compared to the results suggested by the algorithm. The proposed algorithm locates and ranks potential regions with microorganisms in heart valve sections so that experts can validate them in higher power FoVs for the presence of bacteria and identify their species. The automated system for preselecting and recommending adequate FoVs is thus a starting point to support experts and save human resources. It is now ready to be further developed for the detection of bacteria by FISH.
Databáze: Directory of Open Access Journals
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