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Automated quantification of steatosis: agreement with stereological point counting
Fraunhofer MEVIS, Germany.
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Gastroentorology.
Fraunhofer MEVIS, Germany.
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Gastroentorology.
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2017 (English)In: Diagnostic Pathology, ISSN 1746-1596, E-ISSN 1746-1596, Vol. 12, article id 80Article in journal (Refereed) Published
Abstract [en]

Background: Steatosis is routinely assessed histologically in clinical practice and research. Automated image analysis can reduce the effort of quantifying steatosis. Since reproducibility is essential for practical use, we have evaluated different analysis methods in terms of their agreement with stereological point counting (SPC) performed by a hepatologist. Methods: The evaluation was based on a large and representative data set of 970 histological images from human patients with different liver diseases. Three of the evaluated methods were built on previously published approaches. One method incorporated a new approach to improve the robustness to image variability. Results: The new method showed the strongest agreement with the expert. At 20x resolution, it reproduced steatosis area fractions with a mean absolute error of 0.011 for absent or mild steatosis and 0.036 for moderate or severe steatosis. At 10x resolution, it was more accurate than and twice as fast as all other methods at 20x resolution. When compared with SPC performed by two additional human observers, its error was substantially lower than one and only slightly above the other observer. Conclusions: The results suggest that the new method can be a suitable automated replacement for SPC. Before further improvements can be verified, it is necessary to thoroughly assess the variability of SPC between human observers.

Place, publisher, year, edition, pages
BIOMED CENTRAL LTD , 2017. Vol. 12, article id 80
Keywords [en]
Steatosis; Histology; Stereology; Stereological point counting; Automated image analysis; Agreement
National Category
Cancer and Oncology
Identifiers
URN: urn:nbn:se:liu:diva-143237DOI: 10.1186/s13000-017-0671-yISI: 000415004000001PubMedID: 29132399OAI: oai:DiVA.org:liu-143237DiVA, id: diva2:1160447
Note

Funding Agencies|Fraunhofer Society, Munich, Germany; Swedish Research Council of Medicine and Health; Swedish Research Council of Science and Engineering; Vinnova

Available from: 2017-11-27 Created: 2017-11-27 Last updated: 2018-01-05

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Nasr, PatrikKechagias, StergiosLundberg, PeterEkstedt, MattiasTreanor, DarrenLundström, Claes
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Division of Cardiovascular MedicineFaculty of Medicine and Health SciencesDepartment of GastroentorologyDivision of Radiological SciencesDepartment of Radiation PhysicsCenter for Medical Image Science and Visualization (CMIV)Division of Neuro and Inflammation ScienceMedia and Information TechnologyFaculty of Science & Engineering
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