Concordancia de la volumetría del accidente cerebrovascular isquémico en resonancia magnética mediante herramientas de inteligencia artificial: Bivlab y OLEA versus VES-ADC

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dc.contributor.advisorMantilla García, Daniel Eduardo
dc.contributor.advisorUribe Caputti, Juan Carlos
dc.contributor.apolounabMantilla García, Daniel Eduardo [daniel-eduardo-mantilla-garcía]spa
dc.contributor.authorMeléndez Gomez, Eduardo Andres
dc.contributor.cvlacMelendez Gomez, Eduardo Andres [0001839582]spa
dc.contributor.cvlacMantilla García, Daniel Eduardo [0001437130]spa
dc.contributor.googlescholarMelendez Gomez, Eduardo Andres [SsCm2koAAAAJ]spa
dc.contributor.googlescholarMantilla García, Daniel Eduardo [es&oi=ao]spa
dc.contributor.orcidMelendez Gomez, Eduardo Andres [0000-0001-7685-2160]spa
dc.contributor.orcidMantilla García, Daniel Eduardo [0000-0003-1532-2101]spa
dc.contributor.orcidUribe Caputti, Juan Carlos [0000-0002-6602-1045]spa
dc.contributor.researchgroupGrupo de Investigación en Ciencias y Educación en Saludspa
dc.contributor.researchgroupGrupo de Investigaciones Clínicasspa
dc.coverage.campusUNAB Campus Bucaramangaspa
dc.coverage.spatialFloridablanca (Santander, Colombia)spa
dc.coverage.temporal2025spa
dc.date.accessioned2026-02-16T21:34:10Z
dc.date.available2026-02-16T21:34:10Z
dc.date.issued2026-02-16
dc.degree.nameEspecialistas en Radiología e Imágenes Diagnósticasspa
dc.description.abstractEl accidente cerebrovascular (ACV) isquémico constituye una de las principales causas de mortalidad y discapacidad a nivel mundial. La cuantificación precisa del volumen del tejido cerebral infartado mediante resonancia magnética, particularmente en secuencias DWI y mapas ADC, es determinante para la toma de decisiones terapéuticas y la estimación pronóstica. Sin embargo, la segmentación manual realizada por el radiólogo es un proceso operador-dependiente, dispendioso y con variabilidad interobservador. El presente estudio tuvo como objetivo evaluar la concordancia de la medición volumétrica del ACV isquémico entre dos herramientas de inteligencia artificial (Olea Sphere® y BIVL2ab) y la segmentación realizada por radiólogo experto mediante VES-ADC, considerado como referencia. Se realizó un estudio transversal de evaluación tecnológica en 108 pacientes mayores de 18 años con diagnóstico de ACV isquémico, atendidos en la Fundación Oftalmológica de Santander (FOSCAL) entre 2021 y 2024. Se aplicó la metodología de Bland-Altman y el coeficiente de concordancia de Lin para determinar el grado de acuerdo entre los métodos, complementado con análisis estadísticos no paramétricos. Los resultados evidenciaron que las mediciones presentaron distribución no normal y diferencias estadísticamente significativas entre algunas herramientas. Olea mostró mayor similitud con la medición del radiólogo experto, mientras que BIVL2ab tendió a reportar volúmenes superiores. La concordancia global fue variable entre instrumentos. Se concluye que las herramientas de inteligencia artificial evaluadas presentan diferentes niveles de concordancia frente al método experto, lo cual tiene implicaciones clínicas en la estandarización y posible implementación de tecnologías automatizadas para la cuantificación del volumen isquémico cerebral. Este estudio aporta evidencia local relevante para el fortalecimiento de la investigación en neuroimagen avanzada e inteligencia artificial aplicada al diagnóstico radiológico.spa
dc.description.abstractenglishIschemic stroke is one of the leading causes of death and disability worldwide. Accurate quantification of the volume of infarcted brain tissue using magnetic resonance imaging (MRI), particularly with DWI sequences and ADC maps, is crucial for therapeutic decision-making and prognostic estimation. However, manual segmentation performed by radiologists is an operator-dependent, time-consuming process with interobserver variability. This study aimed to evaluate the agreement between volumetric measurements of ischemic stroke using two artificial intelligence tools (Olea Sphere® and BIVL2ab) and segmentation performed by expert radiologists using VES-ADC, considered the gold standard. A cross-sectional technology assessment study was conducted on 108 patients over 18 years of age diagnosed with ischemic stroke, treated at the Santander Ophthalmological Foundation (FOSCAL) between 2021 and 2024. The Bland-Altman method and Lin's concordance coefficient were applied to determine the degree of agreement between the methods, complemented by non-parametric statistical analyses. The results showed that the measurements had a non-normal distribution and statistically significant differences between some tools. Olea showed greater similarity to the expert radiologist's measurement, while BIVL2ab tended to report higher volumes. Overall agreement was variable among instruments. It is concluded that the artificial intelligence tools evaluated show different levels of agreement with the expert method, which has clinical implications for the standardization and possible implementation of automated technologies for quantifying ischemic brain volume. This study provides relevant local evidence for strengthening research in advanced neuroimaging and artificial intelligence applied to radiological diagnosis.spa
dc.description.degreelevelEspecializaciónspa
dc.description.learningmodalityModalidad Presencialspa
dc.description.tableofcontents1. Introducción…………….. …………………………………………..……….2 2. Planteamiento del problema…………….. …………………………………4 3. Pregunta de Investigación………………….. ……………………………...6 4. Hipótesis Investigativa……………………………….…………...…………6 5. Justificación…………………………………………………...………………6 6. Objetivos general y específicos ……………………………….…...…..….8 7. Marco teórico. ………………………………………………………....…..…9 8. Estado del Arte………………………………..……………………..…..…25 9. Metodología y Plan de Análisis……………………………....………..…31 9.1 Diseño o tipo de estudio…………………………………..…………31 9.2 Criterios de inclusión y exclusión…………………………….…….31 9.3 Tamaño Muestral………………………………….………….….…..32 9.4 Variables y Operación de las variables …………...………………32 9.5 Ejecución del proyecto y recolección de la información…...…….34 9.6 Análisis de datos ……………………………………………………35 10. Consideraciones éticas y legales……………….…………………….…..37 11. Resultados ……………………………………………..…..……………….39 12. Discusión y conclusiones……………………………………………..……56 13. Referencias Bibliográficas………………………………………....………67 14. Anexos ………………………………………………………………………78spa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameinstname:Universidad Autónoma de Bucaramanga - UNABspa
dc.identifier.reponamereponame:Repositorio Institucional UNABspa
dc.identifier.repourlrepourl:https://repository.unab.edu.cospa
dc.identifier.urihttp://hdl.handle.net/20.500.12749/32906
dc.language.isospaspa
dc.publisher.facultyFacultad Ciencias de la Saludspa
dc.publisher.grantorUniversidad Autónoma de Bucaramanga UNABspa
dc.publisher.programEspecialización en Radiología e Imágenes Diagnósticasspa
dc.publisher.programidERAD-272
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dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.creativecommonsAtribución-NoComercial-SinDerivadas 2.5 Colombia*
dc.rights.localAbierto (Texto Completo)spa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/*
dc.subject.keywordsReproducibility of Resultsspa
dc.subject.keywordsDiagnostic Imagingspa
dc.subject.keywordsStroke, ischemicspa
dc.subject.keywordsMagnetic resonance imagingspa
dc.subject.keywordsDiffusion magnetic resonance imagingspa
dc.subject.keywordsArtificial intelligencespa
dc.subject.keywordsImage Processing, çomputer-assistedspa
dc.subject.keywordsMedical sciencesspa
dc.subject.keywordsDigital electronicsspa
dc.subject.keywordsMagnetic fieldsspa
dc.subject.keywordsCerebral ischemiaspa
dc.subject.keywordsScientific instrumentsspa
dc.subject.lembCiencias médicasspa
dc.subject.lembRadiologíaspa
dc.subject.lembDiagnóstico para imágenesspa
dc.subject.lembElectrónica digitalspa
dc.subject.lembCampos magnéticosspa
dc.subject.lembIsquemia cerebralspa
dc.subject.lembInstrumentos científicosspa
dc.subject.proposalAccidente cerebrovascular isquémicospa
dc.subject.proposalImagen por resonancia magnéticaspa
dc.subject.proposalImagen por difusiónspa
dc.subject.proposalInteligencia artificialspa
dc.subject.proposalProcesamiento de imágenes asistido por computadorspa
dc.subject.proposalReproducibilidad de resultadosspa
dc.titleConcordancia de la volumetría del accidente cerebrovascular isquémico en resonancia magnética mediante herramientas de inteligencia artificial: Bivlab y OLEA versus VES-ADCspa
dc.title.translatedConcordance of ischemic stroke volume in magnetic resonance imaging using artificial intelligence tools: Bivlab and OLEA versus VES-ADCspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdcc
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.driverinfo:eu-repo/semantics/masterThesis
dc.type.hasversioninfo:eu-repo/semantics/acceptedVersion
dc.type.localTesisspa
dc.type.redcolhttp://purl.org/redcol/resource_type/TM

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