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Digital pathology : elementary, rapid and reliable automated image analysis.

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Bouzin, Caroline [UCL] Lamba Saini, Monika [UCL] Khaing, Kyi Kyi [UCL] Ambroise, Jérôme [UCL] Marbaix, Etienne [UCL] Grégoire, Vincent [UCL] Bol, Vanesa [UCL]

(eng) AIMS: Slide digitalization has brought pathology to a new era, including powerful image analysis possibilities. However, while being a powerful prognostic tool, immunostaining automated analysis on digital images is still not implemented worldwide in routine clinical practice. METHODS AND RESULTS: Digitalized biopsy sections from two independent cohorts of patients, immunostained for membrane or nuclear markers, were quantified with two automated methods. The first was based on stained cell counting through tissue segmentation, while the second relied upon stained area proportion within tissue sections. Different steps of image preparation, such as automated tissue detection, folds exclusion and scanning magnification, were also assessed and validated. Quantification of either stained cells or the stained area was found to be correlated highly for all tested markers. Both methods were also correlated with visual scoring performed by a pathologist. For an equivalent reliability, quantification of the stained area is, however, faster and easier to fine-tune and is therefore more compatible with time constraints for prognosis. CONCLUSIONS: This work provides an incentive for the implementation of automated immunostaining analysis with a stained area method in routine laboratory practice.

Document type Article de périodique (Journal article) – Article de recherche
Access type Accès restreint
Publication date 2015
Language Anglais
Journal information "Histopathology" - Vol. 68, no. 6, p. 888-96 (2016)
Peer reviewed yes
Publisher Wiley-Blackwell Publishing Ltd. (Chichester)
issn 0309-0167
e-issn 1365-2559
Publication status Publié
Affiliations UCL - (SLuc) Service de radiothérapie oncologique
UCL - SSS/DDUV - Institut de Duve
UCL - SSS/IREC/MIRO - Pôle d'imagerie moléculaire, radiothérapie et oncologie
UCL - (SLuc) Service d'anatomie pathologique
Keywords Automation ; Biological markers ; Digital pathology ; Image analysis ; Immunohistochemistry ; Prognosis ; Reproducibility
Links
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Bibliographic reference Bouzin, Caroline ; Lamba Saini, Monika ; Khaing, Kyi Kyi ; Ambroise, Jérôme ; Marbaix, Etienne ; et. al. Digital pathology : elementary, rapid and reliable automated image analysis.. In: Histopathology, Vol. 68, no. 6, p. 888-96 (2016)
Permanent URL http://hdl.handle.net/2078.1/165422