Francesca De Luca, Jose Carlos Pariente, Sofia González-Ortiz, Estefanía Conde-Blanco, Mar Carreño, Xavier Setoain, Nuria Bargalló
{"title":"Potential role of MELD and MAP18 in patients with structural temporal lobe epilepsy.","authors":"Francesca De Luca, Jose Carlos Pariente, Sofia González-Ortiz, Estefanía Conde-Blanco, Mar Carreño, Xavier Setoain, Nuria Bargalló","doi":"10.1007/s00234-025-03549-6","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>This study compared two image post-processing toolboxes primarily designed for focal cortical dysplasia (FCD): Multi-Centre Epilepsy Lesion Detection (MELD) and Morphometric Analysis Program (MAP18), in identifying temporal lobe epilepsy (TLE) structural lesions on MRI.</p><p><strong>Methods: </strong>This retrospective study examined 79 adults, 58 patients with confirmed TLE, and 21 healthy controls. All participants underwent an elective brain MRI between June 2007 - May 2023 at Hospital Clinic, Barcelona, Spain. All the 3D T1-weighted images were processed using MELD and MAP18 to detect potential epileptogenic lesions. The location (lateral or mesial) and laterality of the reference TLE structural lesion (refTLE) were determined through histopathology or multidisciplinary consensus based on clinical data. Toolboxes' performance was evaluated using descriptive statistics, specificity, and diagnostic accuracy. Additionally, a second-look MRI was conducted for cases where abnormalities detected by MELD and MAP18 did not match the refTLE.</p><p><strong>Results: </strong>MELD and MAP18 demonstrated variability in specificity and diagnostic accuracy. Specificity ranged from 48% to 86%, with ProbMAP (MAP18) achieving the highest values. Global diagnostic accuracy ranged from 7% to 42%, with MELD showing the highest performance. In four patients with visible epileptogenic lesions on MRI, MELD and MAP18 identified additional abnormalities that were previously overlooked. Moreover, MELD detected one TLE lesion in one patient initially classified as MRI-negative (nonlesional).</p><p><strong>Conclusion: </strong>Incorporating tools like MELD and MAP18 into the diagnostic workflow can enhance the detection of TLE-related abnormalities on MRI, potentially improving patient outcomes and aiding in clinical decision-making.</p>","PeriodicalId":19422,"journal":{"name":"Neuroradiology","volume":" ","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuroradiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00234-025-03549-6","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Potential role of MELD and MAP18 in patients with structural temporal lobe epilepsy.
Purpose: This study compared two image post-processing toolboxes primarily designed for focal cortical dysplasia (FCD): Multi-Centre Epilepsy Lesion Detection (MELD) and Morphometric Analysis Program (MAP18), in identifying temporal lobe epilepsy (TLE) structural lesions on MRI.
Methods: This retrospective study examined 79 adults, 58 patients with confirmed TLE, and 21 healthy controls. All participants underwent an elective brain MRI between June 2007 - May 2023 at Hospital Clinic, Barcelona, Spain. All the 3D T1-weighted images were processed using MELD and MAP18 to detect potential epileptogenic lesions. The location (lateral or mesial) and laterality of the reference TLE structural lesion (refTLE) were determined through histopathology or multidisciplinary consensus based on clinical data. Toolboxes' performance was evaluated using descriptive statistics, specificity, and diagnostic accuracy. Additionally, a second-look MRI was conducted for cases where abnormalities detected by MELD and MAP18 did not match the refTLE.
Results: MELD and MAP18 demonstrated variability in specificity and diagnostic accuracy. Specificity ranged from 48% to 86%, with ProbMAP (MAP18) achieving the highest values. Global diagnostic accuracy ranged from 7% to 42%, with MELD showing the highest performance. In four patients with visible epileptogenic lesions on MRI, MELD and MAP18 identified additional abnormalities that were previously overlooked. Moreover, MELD detected one TLE lesion in one patient initially classified as MRI-negative (nonlesional).
Conclusion: Incorporating tools like MELD and MAP18 into the diagnostic workflow can enhance the detection of TLE-related abnormalities on MRI, potentially improving patient outcomes and aiding in clinical decision-making.
期刊介绍:
Neuroradiology aims to provide state-of-the-art medical and scientific information in the fields of Neuroradiology, Neurosciences, Neurology, Psychiatry, Neurosurgery, and related medical specialities. Neuroradiology as the official Journal of the European Society of Neuroradiology receives submissions from all parts of the world and publishes peer-reviewed original research, comprehensive reviews, educational papers, opinion papers, and short reports on exceptional clinical observations and new technical developments in the field of Neuroimaging and Neurointervention. The journal has subsections for Diagnostic and Interventional Neuroradiology, Advanced Neuroimaging, Paediatric Neuroradiology, Head-Neck-ENT Radiology, Spine Neuroradiology, and for submissions from Japan. Neuroradiology aims to provide new knowledge about and insights into the function and pathology of the human nervous system that may help to better diagnose and treat nervous system diseases. Neuroradiology is a member of the Committee on Publication Ethics (COPE) and follows the COPE core practices. Neuroradiology prefers articles that are free of bias, self-critical regarding limitations, transparent and clear in describing study participants, methods, and statistics, and short in presenting results. Before peer-review all submissions are automatically checked by iThenticate to assess for potential overlap in prior publication.