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Automatic Detection of Focal Cortical Dysplasia Using MRI: A Systematic Review

Focal cortical dysplasia (FCD) is a congenital brain malformation that is closely associated with epilepsy. Early and accurate diagnosis is essential for effectively treating and managing FCD. Magnetic resonance imaging (MRI)—one of the most commonly used non-invasive neuroimaging methods for evalua...

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Autores principales: Jiménez-Murillo, David, Castro-Ospina, Andrés Eduardo, Duque-Muñoz, Leonardo, Martínez-Vargas, Juan David, Suárez-Revelo, Jazmín Ximena, Vélez-Arango, Jorge Mario, de la Iglesia-Vayá, Maria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10458261/
https://www.ncbi.nlm.nih.gov/pubmed/37631608
http://dx.doi.org/10.3390/s23167072
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author Jiménez-Murillo, David
Castro-Ospina, Andrés Eduardo
Duque-Muñoz, Leonardo
Martínez-Vargas, Juan David
Suárez-Revelo, Jazmín Ximena
Vélez-Arango, Jorge Mario
de la Iglesia-Vayá, Maria
author_facet Jiménez-Murillo, David
Castro-Ospina, Andrés Eduardo
Duque-Muñoz, Leonardo
Martínez-Vargas, Juan David
Suárez-Revelo, Jazmín Ximena
Vélez-Arango, Jorge Mario
de la Iglesia-Vayá, Maria
author_sort Jiménez-Murillo, David
collection PubMed
description Focal cortical dysplasia (FCD) is a congenital brain malformation that is closely associated with epilepsy. Early and accurate diagnosis is essential for effectively treating and managing FCD. Magnetic resonance imaging (MRI)—one of the most commonly used non-invasive neuroimaging methods for evaluating the structure of the brain—is often implemented along with automatic methods to diagnose FCD. In this review, we define three categories for FCD identification based on MRI: visual, semi-automatic, and fully automatic methods. By conducting a systematic review following the PRISMA statement, we identified 65 relevant papers that have contributed to our understanding of automatic FCD identification techniques. The results of this review present a comprehensive overview of the current state-of-the-art in the field of automatic FCD identification and highlight the progress made and challenges ahead in developing reliable, efficient methods for automatic FCD diagnosis using MRI images. Future developments in this area will most likely lead to the integration of these automatic identification tools into medical image-viewing software, providing neurologists and radiologists with enhanced diagnostic capabilities. Moreover, new MRI sequences and higher-field-strength scanners will offer improved resolution and anatomical detail for precise FCD characterization. This review summarizes the current state of automatic FCD identification, thereby contributing to a deeper understanding and the advancement of FCD diagnosis and management.
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spelling pubmed-104582612023-08-27 Automatic Detection of Focal Cortical Dysplasia Using MRI: A Systematic Review Jiménez-Murillo, David Castro-Ospina, Andrés Eduardo Duque-Muñoz, Leonardo Martínez-Vargas, Juan David Suárez-Revelo, Jazmín Ximena Vélez-Arango, Jorge Mario de la Iglesia-Vayá, Maria Sensors (Basel) Review Focal cortical dysplasia (FCD) is a congenital brain malformation that is closely associated with epilepsy. Early and accurate diagnosis is essential for effectively treating and managing FCD. Magnetic resonance imaging (MRI)—one of the most commonly used non-invasive neuroimaging methods for evaluating the structure of the brain—is often implemented along with automatic methods to diagnose FCD. In this review, we define three categories for FCD identification based on MRI: visual, semi-automatic, and fully automatic methods. By conducting a systematic review following the PRISMA statement, we identified 65 relevant papers that have contributed to our understanding of automatic FCD identification techniques. The results of this review present a comprehensive overview of the current state-of-the-art in the field of automatic FCD identification and highlight the progress made and challenges ahead in developing reliable, efficient methods for automatic FCD diagnosis using MRI images. Future developments in this area will most likely lead to the integration of these automatic identification tools into medical image-viewing software, providing neurologists and radiologists with enhanced diagnostic capabilities. Moreover, new MRI sequences and higher-field-strength scanners will offer improved resolution and anatomical detail for precise FCD characterization. This review summarizes the current state of automatic FCD identification, thereby contributing to a deeper understanding and the advancement of FCD diagnosis and management. MDPI 2023-08-10 /pmc/articles/PMC10458261/ /pubmed/37631608 http://dx.doi.org/10.3390/s23167072 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Jiménez-Murillo, David
Castro-Ospina, Andrés Eduardo
Duque-Muñoz, Leonardo
Martínez-Vargas, Juan David
Suárez-Revelo, Jazmín Ximena
Vélez-Arango, Jorge Mario
de la Iglesia-Vayá, Maria
Automatic Detection of Focal Cortical Dysplasia Using MRI: A Systematic Review
title Automatic Detection of Focal Cortical Dysplasia Using MRI: A Systematic Review
title_full Automatic Detection of Focal Cortical Dysplasia Using MRI: A Systematic Review
title_fullStr Automatic Detection of Focal Cortical Dysplasia Using MRI: A Systematic Review
title_full_unstemmed Automatic Detection of Focal Cortical Dysplasia Using MRI: A Systematic Review
title_short Automatic Detection of Focal Cortical Dysplasia Using MRI: A Systematic Review
title_sort automatic detection of focal cortical dysplasia using mri: a systematic review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10458261/
https://www.ncbi.nlm.nih.gov/pubmed/37631608
http://dx.doi.org/10.3390/s23167072
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