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Purpose <p>MRI detection of subtle focal cortical dysplasia (FCD)-like abnormalities remains challenging in focal epilepsy. Higher signal-to-noise ratio and spatial resolution offered by ultra-high-field 7T MRI and surface-based graph-neural-network (GNN) analysis may improve detection of subtle cortical abnormalities. We evaluated whether combining 7T MRI with a surface-based GNN classifier improves lesion detection in focal epilepsy of suspected structural origin.</p> Methods <p>We analyzed paired 7T and 3T MRI datasets from 87 patients with focal epilepsy (78.1% pediatric) and 10 internal healthy control individuals. We processed T1-weighted and Fluid-Attenuated-Inversion-Recovery MRI using a surface-based framework and a pre-trained GNN classifier developed within the Multi-centre-Epilepsy-Lesion-Detection project. We compared classifier outputs with expert visual MRI assessment, clinical and surface electroencephalography (EEG) localization (all patients), stereo-EEG (ten patients) and histopathological (17 patients) findings. We evaluated diagnostic yield and lesion conspicuity, and performed within-subject comparisons between 7T and 3T.</p> Results <p>Following quality controls, we included 70 patients. The 7T MRI-based classifier identified lesion clusters concordant with visual 3T MRI and electroclinical localization in 25/37 (67.6%) MRI-positive patients, electroclinical-concordant clusters in 15/33 (45.4%) 3T MRI-negatives, stereo-EEG-concordant clusters in 7/10 (70.0%) patients and surgically-concordant clusters in 11/17 (64.7%). Among classifier-positive patients (40/70, 57.1%), 7T allowed detection of previously hidden lesions in 15/40 (37.5%) patients, and improved detection of known lesions in 11/40 (27.5%).</p> Conclusion <p>Combining 7T MRI with surface-based GNN analysis improves detection and characterization of FCD-like abnormalities in focal epilepsy, particularly in patients with unrevealing 3T MRI, supporting the adoption of advanced neuroimaging in presurgical epilepsy assessment.</p>

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Enhanced detection of subtle cortical abnormalities in focal epilepsy using 7 T MRI surface-based models and graph neural networks

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月6日

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  • Matteo Lenge,
  • Simona Fiori,
  • Pietro Cappelletto,
  • Andrea Droghini,
  • Elisa Barbi,
  • Anna Maria Buccoliero,
  • Graziella Donatelli,
  • Michela Tosetti,
  • Flavio Giordano,
  • Carmen Barba,
  • Renzo Guerrini

摘要

Purpose

MRI detection of subtle focal cortical dysplasia (FCD)-like abnormalities remains challenging in focal epilepsy. Higher signal-to-noise ratio and spatial resolution offered by ultra-high-field 7T MRI and surface-based graph-neural-network (GNN) analysis may improve detection of subtle cortical abnormalities. We evaluated whether combining 7T MRI with a surface-based GNN classifier improves lesion detection in focal epilepsy of suspected structural origin.

Methods

We analyzed paired 7T and 3T MRI datasets from 87 patients with focal epilepsy (78.1% pediatric) and 10 internal healthy control individuals. We processed T1-weighted and Fluid-Attenuated-Inversion-Recovery MRI using a surface-based framework and a pre-trained GNN classifier developed within the Multi-centre-Epilepsy-Lesion-Detection project. We compared classifier outputs with expert visual MRI assessment, clinical and surface electroencephalography (EEG) localization (all patients), stereo-EEG (ten patients) and histopathological (17 patients) findings. We evaluated diagnostic yield and lesion conspicuity, and performed within-subject comparisons between 7T and 3T.

Results

Following quality controls, we included 70 patients. The 7T MRI-based classifier identified lesion clusters concordant with visual 3T MRI and electroclinical localization in 25/37 (67.6%) MRI-positive patients, electroclinical-concordant clusters in 15/33 (45.4%) 3T MRI-negatives, stereo-EEG-concordant clusters in 7/10 (70.0%) patients and surgically-concordant clusters in 11/17 (64.7%). Among classifier-positive patients (40/70, 57.1%), 7T allowed detection of previously hidden lesions in 15/40 (37.5%) patients, and improved detection of known lesions in 11/40 (27.5%).

Conclusion

Combining 7T MRI with surface-based GNN analysis improves detection and characterization of FCD-like abnormalities in focal epilepsy, particularly in patients with unrevealing 3T MRI, supporting the adoption of advanced neuroimaging in presurgical epilepsy assessment.