Morphological characterization of colorectal pits using autofluorescence microscopy images

Autores
Erbes, Luciana Ariadna; Zeitoune, Angel Alberto; Torres, Humberto Maximiliano; Casco, Victor Hugo; Adur, Javier Fernando
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Background: Colorectal cancer (CRC) is one of the most prevalent pathologies. Its prognosis is linked to the early detection and treatment. Currently diagnosis is performed by histological analysis from polyp biopsies, followed by morphological classification. Kudo?s pit pattern classification is frequently used for the differentiation of neoplastic colorectal lesions using hematoxylin-eosin (H&E) stained samples. Few articles have reported this classification with image software processing, using exogenous markers over the samples. The processing of autofluorescence images is an alternative that could allow the characterization of the pits from the crypts of Lieberkühn, bypassing staining techniques. Objective: Processing and analysis of widefield autofluorescence microscopy images obtained by fresh colon tissue samples from a murine model of CRC in order to quantify and characterize the pits morphology by measuring morphology parameters and shape descriptors. Methods: Two-dimensional (2D) segmentation, quantification and morphological characterization of pits by image processing applied using macro programming from FIJI. Results: Type I is the pit morphology prevailing between 53 and 81% in control group weeks. III-L and III-S types were detected in reduced percentages. Between the 33 and 56% of type I was stated as the prevailing morphology for the 4th, 8th and 20th weeks of treated groups, followed by III-L type. For the 16th week, the 39% of the pits was characterized as III-L type, followed by type I. Further, pattern types as IV, III-S and II were also found mainly in that order for almost all of the treated weeks. Conclusion: These preliminaries outcomes could be considered an advance in two-dimensional pit characterization as the whole image processing, comparing to the conventional procedure, takes a few seconds to quantify and characterize non-pathological colon pits as well as to estimate early pathological stages of CRC.
Fil: Erbes, Luciana Ariadna. Universidad Nacional de Entre Ríos. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática; Argentina
Fil: Zeitoune, Angel Alberto. Universidad Nacional de Entre Ríos. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática; Argentina
Fil: Torres, Humberto Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Casco, Victor Hugo. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; Argentina
Fil: Adur, Javier Fernando. Universidad Nacional de Entre Ríos. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática; Argentina
Materia
colorectal
cancer
classification
pattern
autofluorescence
morphology
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/106790
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/106790
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Morphological characterization of colorectal pits using autofluorescence microscopy imagesErbes, Luciana AriadnaZeitoune, Angel AlbertoTorres, Humberto MaximilianoCasco, Victor HugoAdur, Javier Fernandocolorectalcancerclassificationpatternautofluorescencemorphologyhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Background: Colorectal cancer (CRC) is one of the most prevalent pathologies. Its prognosis is linked to the early detection and treatment. Currently diagnosis is performed by histological analysis from polyp biopsies, followed by morphological classification. Kudo?s pit pattern classification is frequently used for the differentiation of neoplastic colorectal lesions using hematoxylin-eosin (H&E) stained samples. Few articles have reported this classification with image software processing, using exogenous markers over the samples. The processing of autofluorescence images is an alternative that could allow the characterization of the pits from the crypts of Lieberkühn, bypassing staining techniques. Objective: Processing and analysis of widefield autofluorescence microscopy images obtained by fresh colon tissue samples from a murine model of CRC in order to quantify and characterize the pits morphology by measuring morphology parameters and shape descriptors. Methods: Two-dimensional (2D) segmentation, quantification and morphological characterization of pits by image processing applied using macro programming from FIJI. Results: Type I is the pit morphology prevailing between 53 and 81% in control group weeks. III-L and III-S types were detected in reduced percentages. Between the 33 and 56% of type I was stated as the prevailing morphology for the 4th, 8th and 20th weeks of treated groups, followed by III-L type. For the 16th week, the 39% of the pits was characterized as III-L type, followed by type I. Further, pattern types as IV, III-S and II were also found mainly in that order for almost all of the treated weeks. Conclusion: These preliminaries outcomes could be considered an advance in two-dimensional pit characterization as the whole image processing, comparing to the conventional procedure, takes a few seconds to quantify and characterize non-pathological colon pits as well as to estimate early pathological stages of CRC.Fil: Erbes, Luciana Ariadna. Universidad Nacional de Entre Ríos. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática; ArgentinaFil: Zeitoune, Angel Alberto. Universidad Nacional de Entre Ríos. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática; ArgentinaFil: Torres, Humberto Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Casco, Victor Hugo. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; ArgentinaFil: Adur, Javier Fernando. Universidad Nacional de Entre Ríos. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática; ArgentinaInstituto Brasileiro de Estudos e Pesquisas de Gastroenterologia e Outras Especialidades2019-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/106790Erbes, Luciana Ariadna; Zeitoune, Angel Alberto; Torres, Humberto Maximiliano; Casco, Victor Hugo; Adur, Javier Fernando; Morphological characterization of colorectal pits using autofluorescence microscopy images; Instituto Brasileiro de Estudos e Pesquisas de Gastroenterologia e Outras Especialidades; Arquivos de Gastroenterologia; 56; 2; 7-2019; 191-1960004-28031678-4219CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1590/s0004-2803.201900000-37info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:11:05Zoai:ri.conicet.gov.ar:11336/106790instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-10 13:11:05.803CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Morphological characterization of colorectal pits using autofluorescence microscopy images
title Morphological characterization of colorectal pits using autofluorescence microscopy images
spellingShingle Morphological characterization of colorectal pits using autofluorescence microscopy images
Erbes, Luciana Ariadna
colorectal
cancer
classification
pattern
autofluorescence
morphology
title_short Morphological characterization of colorectal pits using autofluorescence microscopy images
title_full Morphological characterization of colorectal pits using autofluorescence microscopy images
title_fullStr Morphological characterization of colorectal pits using autofluorescence microscopy images
title_full_unstemmed Morphological characterization of colorectal pits using autofluorescence microscopy images
title_sort Morphological characterization of colorectal pits using autofluorescence microscopy images
dc.creator.none.fl_str_mv Erbes, Luciana Ariadna
Zeitoune, Angel Alberto
Torres, Humberto Maximiliano
Casco, Victor Hugo
Adur, Javier Fernando
author Erbes, Luciana Ariadna
author_facet Erbes, Luciana Ariadna
Zeitoune, Angel Alberto
Torres, Humberto Maximiliano
Casco, Victor Hugo
Adur, Javier Fernando
author_role author
author2 Zeitoune, Angel Alberto
Torres, Humberto Maximiliano
Casco, Victor Hugo
Adur, Javier Fernando
author2_role author
author
author
author
dc.subject.none.fl_str_mv colorectal
cancer
classification
pattern
autofluorescence
morphology
topic colorectal
cancer
classification
pattern
autofluorescence
morphology
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Background: Colorectal cancer (CRC) is one of the most prevalent pathologies. Its prognosis is linked to the early detection and treatment. Currently diagnosis is performed by histological analysis from polyp biopsies, followed by morphological classification. Kudo?s pit pattern classification is frequently used for the differentiation of neoplastic colorectal lesions using hematoxylin-eosin (H&E) stained samples. Few articles have reported this classification with image software processing, using exogenous markers over the samples. The processing of autofluorescence images is an alternative that could allow the characterization of the pits from the crypts of Lieberkühn, bypassing staining techniques. Objective: Processing and analysis of widefield autofluorescence microscopy images obtained by fresh colon tissue samples from a murine model of CRC in order to quantify and characterize the pits morphology by measuring morphology parameters and shape descriptors. Methods: Two-dimensional (2D) segmentation, quantification and morphological characterization of pits by image processing applied using macro programming from FIJI. Results: Type I is the pit morphology prevailing between 53 and 81% in control group weeks. III-L and III-S types were detected in reduced percentages. Between the 33 and 56% of type I was stated as the prevailing morphology for the 4th, 8th and 20th weeks of treated groups, followed by III-L type. For the 16th week, the 39% of the pits was characterized as III-L type, followed by type I. Further, pattern types as IV, III-S and II were also found mainly in that order for almost all of the treated weeks. Conclusion: These preliminaries outcomes could be considered an advance in two-dimensional pit characterization as the whole image processing, comparing to the conventional procedure, takes a few seconds to quantify and characterize non-pathological colon pits as well as to estimate early pathological stages of CRC.
Fil: Erbes, Luciana Ariadna. Universidad Nacional de Entre Ríos. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática; Argentina
Fil: Zeitoune, Angel Alberto. Universidad Nacional de Entre Ríos. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática; Argentina
Fil: Torres, Humberto Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Casco, Victor Hugo. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; Argentina
Fil: Adur, Javier Fernando. Universidad Nacional de Entre Ríos. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática; Argentina
description Background: Colorectal cancer (CRC) is one of the most prevalent pathologies. Its prognosis is linked to the early detection and treatment. Currently diagnosis is performed by histological analysis from polyp biopsies, followed by morphological classification. Kudo?s pit pattern classification is frequently used for the differentiation of neoplastic colorectal lesions using hematoxylin-eosin (H&E) stained samples. Few articles have reported this classification with image software processing, using exogenous markers over the samples. The processing of autofluorescence images is an alternative that could allow the characterization of the pits from the crypts of Lieberkühn, bypassing staining techniques. Objective: Processing and analysis of widefield autofluorescence microscopy images obtained by fresh colon tissue samples from a murine model of CRC in order to quantify and characterize the pits morphology by measuring morphology parameters and shape descriptors. Methods: Two-dimensional (2D) segmentation, quantification and morphological characterization of pits by image processing applied using macro programming from FIJI. Results: Type I is the pit morphology prevailing between 53 and 81% in control group weeks. III-L and III-S types were detected in reduced percentages. Between the 33 and 56% of type I was stated as the prevailing morphology for the 4th, 8th and 20th weeks of treated groups, followed by III-L type. For the 16th week, the 39% of the pits was characterized as III-L type, followed by type I. Further, pattern types as IV, III-S and II were also found mainly in that order for almost all of the treated weeks. Conclusion: These preliminaries outcomes could be considered an advance in two-dimensional pit characterization as the whole image processing, comparing to the conventional procedure, takes a few seconds to quantify and characterize non-pathological colon pits as well as to estimate early pathological stages of CRC.
publishDate 2019
dc.date.none.fl_str_mv 2019-07
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/106790
Erbes, Luciana Ariadna; Zeitoune, Angel Alberto; Torres, Humberto Maximiliano; Casco, Victor Hugo; Adur, Javier Fernando; Morphological characterization of colorectal pits using autofluorescence microscopy images; Instituto Brasileiro de Estudos e Pesquisas de Gastroenterologia e Outras Especialidades; Arquivos de Gastroenterologia; 56; 2; 7-2019; 191-196
0004-2803
1678-4219
CONICET Digital
CONICET
url http://hdl.handle.net/11336/106790
identifier_str_mv Erbes, Luciana Ariadna; Zeitoune, Angel Alberto; Torres, Humberto Maximiliano; Casco, Victor Hugo; Adur, Javier Fernando; Morphological characterization of colorectal pits using autofluorescence microscopy images; Instituto Brasileiro de Estudos e Pesquisas de Gastroenterologia e Outras Especialidades; Arquivos de Gastroenterologia; 56; 2; 7-2019; 191-196
0004-2803
1678-4219
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1590/s0004-2803.201900000-37
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Instituto Brasileiro de Estudos e Pesquisas de Gastroenterologia e Outras Especialidades
publisher.none.fl_str_mv Instituto Brasileiro de Estudos e Pesquisas de Gastroenterologia e Outras Especialidades
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.993085

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