Automated discrimination of brain pathological state attending to complex structural brain network properties: the shiverer mutant mouse case.

Neuroimaging classification procedures between normal and pathological subjects are sparse and highly dependent of an expert's clinical criterion. Here, we aimed to investigate whether possible brain structural network differences in the shiverer mouse mutant, a relevant animal model of myelin...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Yasser Iturria-Medina, Alejandro Pérez Fernández, Pedro Valdés Hernández, Lorna García Pentón, Erick J Canales-Rodríguez, Lester Melie-Garcia, Agustin Lage Castellanos, Marlis Ontivero Ortega
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2011
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/e20e9a1769b14e1fb4779b6b2241f1ca
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:e20e9a1769b14e1fb4779b6b2241f1ca
record_format	dspace
spelling	oai:doaj.org-article:e20e9a1769b14e1fb4779b6b2241f1ca2021-11-18T06:53:05ZAutomated discrimination of brain pathological state attending to complex structural brain network properties: the shiverer mutant mouse case.1932-620310.1371/journal.pone.0019071https://doaj.org/article/e20e9a1769b14e1fb4779b6b2241f1ca2011-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21637753/?tool=EBIhttps://doaj.org/toc/1932-6203Neuroimaging classification procedures between normal and pathological subjects are sparse and highly dependent of an expert's clinical criterion. Here, we aimed to investigate whether possible brain structural network differences in the shiverer mouse mutant, a relevant animal model of myelin related diseases, can reflect intrinsic individual brain properties that allow the automatic discrimination between the shiverer and normal subjects. Common structural networks properties between shiverer (C3Fe.SWV Mbp(shi)/Mbp(shi), n = 6) and background control (C3HeB.FeJ, n = 6) mice are estimated and compared by means of three diffusion weighted MRI (DW-MRI) fiber tractography algorithms and a graph framework. Firstly, we found that brain networks of control group are significantly more clustered, modularized, efficient and optimized than those of the shiverer group, which presented significantly increased characteristic path length. These results are in line with previous structural/functional complex brain networks analysis that have revealed topologic differences and brain network randomization associated to specific states of human brain pathology. In addition, by means of network measures spatial representations and discrimination analysis, we show that it is possible to classify with high accuracy to which group each subject belongs, providing also a probability value of being a normal or shiverer subject as an individual anatomical classifier. The obtained correct predictions (e.g., around 91.6-100%) and clear spatial subdivisions between control and shiverer mice, suggest that there might exist specific network subspaces corresponding to specific brain disorders, supporting also the point of view that complex brain network analyses constitutes promising tools in the future creation of interpretable imaging biomarkers.Yasser Iturria-MedinaAlejandro Pérez FernándezPedro Valdés HernándezLorna García PentónErick J Canales-RodríguezLester Melie-GarciaAgustin Lage CastellanosMarlis Ontivero OrtegaPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 6, Iss 5, p e19071 (2011)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yasser Iturria-Medina Alejandro Pérez Fernández Pedro Valdés Hernández Lorna García Pentón Erick J Canales-Rodríguez Lester Melie-Garcia Agustin Lage Castellanos Marlis Ontivero Ortega Automated discrimination of brain pathological state attending to complex structural brain network properties: the shiverer mutant mouse case.
description	Neuroimaging classification procedures between normal and pathological subjects are sparse and highly dependent of an expert's clinical criterion. Here, we aimed to investigate whether possible brain structural network differences in the shiverer mouse mutant, a relevant animal model of myelin related diseases, can reflect intrinsic individual brain properties that allow the automatic discrimination between the shiverer and normal subjects. Common structural networks properties between shiverer (C3Fe.SWV Mbp(shi)/Mbp(shi), n = 6) and background control (C3HeB.FeJ, n = 6) mice are estimated and compared by means of three diffusion weighted MRI (DW-MRI) fiber tractography algorithms and a graph framework. Firstly, we found that brain networks of control group are significantly more clustered, modularized, efficient and optimized than those of the shiverer group, which presented significantly increased characteristic path length. These results are in line with previous structural/functional complex brain networks analysis that have revealed topologic differences and brain network randomization associated to specific states of human brain pathology. In addition, by means of network measures spatial representations and discrimination analysis, we show that it is possible to classify with high accuracy to which group each subject belongs, providing also a probability value of being a normal or shiverer subject as an individual anatomical classifier. The obtained correct predictions (e.g., around 91.6-100%) and clear spatial subdivisions between control and shiverer mice, suggest that there might exist specific network subspaces corresponding to specific brain disorders, supporting also the point of view that complex brain network analyses constitutes promising tools in the future creation of interpretable imaging biomarkers.
format	article
author	Yasser Iturria-Medina Alejandro Pérez Fernández Pedro Valdés Hernández Lorna García Pentón Erick J Canales-Rodríguez Lester Melie-Garcia Agustin Lage Castellanos Marlis Ontivero Ortega
author_facet	Yasser Iturria-Medina Alejandro Pérez Fernández Pedro Valdés Hernández Lorna García Pentón Erick J Canales-Rodríguez Lester Melie-Garcia Agustin Lage Castellanos Marlis Ontivero Ortega
author_sort	Yasser Iturria-Medina
title	Automated discrimination of brain pathological state attending to complex structural brain network properties: the shiverer mutant mouse case.
title_short	Automated discrimination of brain pathological state attending to complex structural brain network properties: the shiverer mutant mouse case.
title_full	Automated discrimination of brain pathological state attending to complex structural brain network properties: the shiverer mutant mouse case.
title_fullStr	Automated discrimination of brain pathological state attending to complex structural brain network properties: the shiverer mutant mouse case.
title_full_unstemmed	Automated discrimination of brain pathological state attending to complex structural brain network properties: the shiverer mutant mouse case.
title_sort	automated discrimination of brain pathological state attending to complex structural brain network properties: the shiverer mutant mouse case.
publisher	Public Library of Science (PLoS)
publishDate	2011
url	https://doaj.org/article/e20e9a1769b14e1fb4779b6b2241f1ca
work_keys_str_mv	AT yasseriturriamedina automateddiscriminationofbrainpathologicalstateattendingtocomplexstructuralbrainnetworkpropertiestheshiverermutantmousecase AT alejandroperezfernandez automateddiscriminationofbrainpathologicalstateattendingtocomplexstructuralbrainnetworkpropertiestheshiverermutantmousecase AT pedrovaldeshernandez automateddiscriminationofbrainpathologicalstateattendingtocomplexstructuralbrainnetworkpropertiestheshiverermutantmousecase AT lornagarciapenton automateddiscriminationofbrainpathologicalstateattendingtocomplexstructuralbrainnetworkpropertiestheshiverermutantmousecase AT erickjcanalesrodriguez automateddiscriminationofbrainpathologicalstateattendingtocomplexstructuralbrainnetworkpropertiestheshiverermutantmousecase AT lestermeliegarcia automateddiscriminationofbrainpathologicalstateattendingtocomplexstructuralbrainnetworkpropertiestheshiverermutantmousecase AT agustinlagecastellanos automateddiscriminationofbrainpathologicalstateattendingtocomplexstructuralbrainnetworkpropertiestheshiverermutantmousecase AT marlisontiveroortega automateddiscriminationofbrainpathologicalstateattendingtocomplexstructuralbrainnetworkpropertiestheshiverermutantmousecase
_version_	1718424261888049152

Automated discrimination of brain pathological state attending to complex structural brain network properties: the shiverer mutant mouse case.

Ejemplares similares