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Detection and localization of focal cortical dysplasia by voxel-based 3-D MRI analysis
Jan Kassubek1, Hans-Jürgen Huppertz, Joachim Spreer
1Department of Neurology, University Hospital Freiburg, Germany.
Purpose:
Focal cortical dysplasia (FCD) is a frequent cause of partial epilepsy. Its diagnosis by visual evaluation of magnetic resonance images (MRIs) remains difficult. The purpose of this study was to apply a novel automated and observer-independent voxel-based technique for the analysis of 3-dimensional (3-D) MRI to detect and localize FCD.
Methods:
The technique was based on algorithms of the SPM99 software and included the spatial normalization of 3-D MRI data sets to a common stereotaxic space and the segmentation of cortical grey matter. The resulting data sets represented grey-matter density maps where each voxel encoded the grey-matter concentration at the corresponding position in the original MRI. A normal database was set up by calculating and averaging the grey-matter density maps of 30 healthy volunteers. The MRI data sets of seven epilepsy patients with FCD were evaluated retrospectively for dysplastic lesions by voxelwise subtraction of the mean grey-matter density map of the normal database and searching automatically for local and global maxima in the resulting data set.
Results:
In all patients, the results of voxel-based 3-D MRI analysis corresponded both to the location of the dysplastic lesions in conventional MRI and to seizure semiology and EEG findings. In one case, surgery was performed, and the diagnosis FCD was supported by histology.
Conclusions:
The technique of voxel-based 3-D MRI analysis and comparison with a normal database seems to provide a valuable additional screening tool for the detection of FCD.
Insights
A new automated 3D MRI analysis technique accurately detects focal cortical dysplasia (FCD), a common cause of epilepsy. This observer-independent method aids in diagnosing FCD when visual MRI evaluation is challenging.
Area of Science:
- Neuroimaging
- Epileptology
- Medical Image Analysis
Background:
- Focal cortical dysplasia (FCD) is a leading cause of partial epilepsy.
- Diagnosing FCD via visual assessment of magnetic resonance images (MRIs) is often difficult.
- Objective localization of FCD is crucial for effective treatment.
Purpose of the Study:
- To apply a novel automated, observer-independent, voxel-based technique for analyzing 3D MRIs.
- To detect and precisely localize FCD using this advanced imaging analysis.
- To improve diagnostic accuracy for FCD in epilepsy patients.
Main Methods:
- Utilized SPM99 algorithms for spatial normalization and cortical grey matter segmentation of 3D MRI data.
- Created grey-matter density maps to quantify grey matter concentration voxel by voxel.
- Established a normal database from 30 healthy volunteers for comparison.
- Retrospectively analyzed FCD patient MRIs by subtracting the normal database mean density map and identifying maxima.
Main Results:
- The voxel-based 3D MRI analysis successfully identified FCD lesions in all seven epilepsy patients.
- Analysis results correlated with conventional MRI findings, seizure semiology, and EEG data.
- Histological confirmation supported the FCD diagnosis in a surgically treated patient.
Conclusions:
- Voxel-based 3D MRI analysis, compared against a normal database, shows promise as a valuable screening tool for FCD detection.
- This automated technique offers an objective approach to supplement FCD diagnosis.
- Further application of this method could enhance the management of epilepsy caused by FCD.