Autor según el artículo: Marylène Lejeune; Cristina Callau; Anna Korzynska; Marcial García; Gloria Bueno; Ramon Bosch; Joaquín Jaén; Guifré Orero; Teresa Salvadó; Carlos López

Departamento: Ciències Mèdiques Bàsiques

e-ISSN: 1475-925X

Autor/es de la URV: LEJEUNE, MARYLÈNE ; Cristina Callau; Anna Korzynska; Marcial García; Gloria Bueno; Ramon Bosch; Joaquín Jaén; Guifré Orero; Teresa Salvadó; Carlos López

Palabras clave: image processing

Resumen: Background: Digital image (DI) analysis avoids visual subjectivity in interpreting immunohistochemical stains and provides more reproducible results. An automated procedure consisting of two variant methods for quantifying the cytokeratin-19 (CK19) marker in breast cancer tissues is presented. Methods: The first method (A) excludes the holes inside selected CK19 stained areas, and the second (B) includes them. 93 DIs scanned from complete cylinders of tissue microarrays were evaluated visually by two pathologists and by the automated procedures. Results and conclusions: There was good concordance between the two automated methods, both of which tended to identify a smaller CK19-positive area than did the pathologists. The results obtained with method B were more similar to those of the pathologists; probably because it takes into account the entire positive tumoural area, including the holes. However, the pathologists overestimated the positive area of CK19. Further studies are needed to confirm the utility of this automated procedure in prognostic studies.

Grupo de investigación: Patologia Oncològica i Bioinformàtica 2016

Áreas temáticas: Ciències de la salut Ciencias de la salud Health sciences

Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/

Identificador del autor: N/D; N/D; N/D; N/D; N/D; N/D; N/D; N/D; N/D; N/D

Fecha de alta del registro: 2016-07-29

Volumen de revista: 14

Versión del articulo depositado: info:eu-repo/semantics/publishedVersion

Enlace a la fuente original: http://www.biomedical-engineering-online.com/supplements/14/S2.

DOI del artículo: 10.1186/1475-925X-14-S2-S2

Entidad: Universitat Rovira i Virgili

Año de publicación de la revista: 2016

Tipo de publicación: Article Artículo Article