Evidence map›Paper›PMID 42233975›Full record

ArticleEpilepsia2026

Comparison of volume- and surface-based magnetic resonance imaging morphometry algorithms in the detection of focal cortical dysplasia.

Lara Bücheler, Marco Reisert, Theo Demerath, Florian Mayer, Christian Moeller, Joshua Reß, Yiwen Li Hegner, Dirk-Matthias Altenmüller, Victoria San Antonio-Arce, Christian Scheiwe and 8 more

Abstract readComparative Study
In one paragraph

Article in Epilepsia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Lara BüchelerEpilepsy Center, Medical Center, member of the European Reference Network for Rare and Complex Epilepsies EpiCARE, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Marco ReisertDepartment of Radiology, Medical Physics, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID https://orcid.org/0000-0003-2742-1940
Theo DemerathDepartment of Neuroradiology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID https://orcid.org/0000-0002-5869-1110
Florian MayerDepartment of Pediatrics and Adolescent Medicine, Medical University of Vienna, member of European Reference Network for Rare and Complex Epilepsies EpiCARE, Vienna, Austria.ORCID https://orcid.org/0009-0007-1271-3314
Christian MoellerNeurocenter, IT-Service, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Joshua ReßNeurocenter, IT-Service, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Yiwen Li HegnerDepartment of Neurology and Epileptology, member of European Reference Network for Rare and Complex Epilepsies EpiCARE, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.ORCID https://orcid.org/0000-0001-9960-6958
Dirk-Matthias AltenmüllerEpilepsy Center, Medical Center, member of the European Reference Network for Rare and Complex Epilepsies EpiCARE, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID https://orcid.org/0000-0001-8610-2216
Victoria San Antonio-ArceEpilepsy Center, Medical Center, member of the European Reference Network for Rare and Complex Epilepsies EpiCARE, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID https://orcid.org/0000-0002-2780-6560
Christian ScheiweDepartment of Neurosurgery, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID https://orcid.org/0000-0003-1695-8689
Mukesch ShahDepartment of Neurosurgery, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID https://orcid.org/0000-0002-7224-9185
Jürgen BeckDepartment of Neurosurgery, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID https://orcid.org/0000-0002-7687-6098
Soroush DoostkamInstitute of Neuropathology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Thomas BastEpilepsy Center Kork, Kehl-Kork, Germany.
Bernhard J SteinhoffEpilepsy Center Kork, Kehl-Kork, Germany.ORCID https://orcid.org/0000-0001-5995-5862
Andreas Schulze-BonhageEpilepsy Center, Medical Center, member of the European Reference Network for Rare and Complex Epilepsies EpiCARE, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID https://orcid.org/0000-0003-2382-0506
Horst UrbachDepartment of Neuroradiology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID https://orcid.org/0000-0001-7264-4807
Marcel HeersEpilepsy Center, Medical Center, member of the European Reference Network for Rare and Complex Epilepsies EpiCARE, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID https://orcid.org/0000-0001-5545-7014

Funding

Deutsche Forschungsgemeinschaft 468174690Deutsche Forschungsgemeinschaft HE6844/3-1Deutsche Forschungsgemeinschaft LI1904/2-1
6 · The paper itself

Abstract

objectiveDetection of focal cortical dysplasia (FCD) remains a major challenge in presurgical epilepsy diagnostics. Magnetic resonance imaging (MRI) morphometry increasingly improves lesion detection and postsurgical outcomes. The volume-based Morphometric Analysis Program, version 2018 (MAP18) with integrated artificial neural network and surface-based Multi-centre Epilepsy Lesion Detection (MELD; MELD Graph) MRI morphometry algorithms have demonstrated diagnostic utility, but their performance has not been directly compared within a single cohort of surgically treated patients with histopathologically confirmed FCD.

methodsWe retrospectively analyzed 3-T MRIs of 32 FCD patients who underwent epilepsy surgery. MAP18 was applied to MP2RAGE (magnetization-prepared 2 rapid gradient echo) sequences and MELD to T1MPRAGE (magnetization-prepared rapid gradient echo) and three-dimensional FLAIR (fluid-attenuated inversion recovery) sequences. Binary lesion masks served as ground truth for evaluating detection accuracy, precision, and recall at cluster and voxel levels. Clinical correlation analysis assessed spatial concordance with seizure onset zone (SOZ) and irritative zone (IZ) from video-electroencephalography (EEG) and postoperative outcome.

resultsThe cohort included 34 histopathologically proven FCD lesions (91.2% FCD II, 5.8% mild malformation of cortical development, 2.9% unspecified). MELD identified 32 of 34 lesions (94.1%), and MAP18 identified 33 of 34 lesions (97.1%), with concordance in 32 of 34 lesions (94.1%). At the cluster level, MELD showed significantly higher precision (p < .001) and fewer false positive clusters per patient (median 0 vs. 3, p < .001). Voxelwise analysis revealed that MELD demonstrated significantly higher precision than MAP18 (.42 vs. .13, p < .0001) and recall (.44 vs. .23, p < .01). Lobar concordance with SOZ reached 90.6% and with IZ reached 87.5%. Among invasive EEG patients, overlap with SOZ and IZ was 100%. Seizure freedom (Engel I) was achieved in 87.5% of patients. SIGNIFICANCE: Under standardized high-resolution 3-T MRI, both algorithms achieved high detection rates with strong concordance. Combined application may enhance presurgical lesion detection, with results limited to surgically treated patients.

Indexed as

AlgorithmsFocal Cortical DysplasiaMagnetic Resonance ImagingAdolescentAdultChildDetection AlgorithmsElectroencephalographyEpilepsyFemaleHumansMaleRetrospective StudiesYoung Adultautomated lesion detectionepilepsy surgeryfocal cortical dysplasiamachine learningMRI morphometry

Identifiers

PMID42233975
PMCPMC13592473

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