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Review
. 2015 Apr;5(2):188-203.
doi: 10.3978/j.issn.2223-4292.2015.01.10.

Post-processing of structural MRI for individualized diagnostics

Pascal Martin  1 , Benjamin Bender  1 , Niels K Focke  1
Affiliations
Review

Post-processing of structural MRI for individualized diagnostics

Pascal Martin et al. Quant Imaging Med Surg. 2015 Apr.

Abstract

Currently, a relevant proportion of all histopathologically proven focal cortical dysplasia (FCD) escape visual detection; this shows the need for additional improvements in analyzing MRI data. A positive MRI is still the strongest prognostic factor for postoperative freedom of seizures. Among several post-processing methods voxel-based morphometry (VBM) of T1- and T2-weighted sequences and T2 relaxometry are routinely applied in pre-surgical diagnostics of cryptogenic epilepsy in epilepsy centers. VBM is superior to conventional visual analysis with 9-15% more identified epileptogenic foci, while T2 relaxometry has its main application in (mesial) temporal lobe epilepsy. Further methods such as surface-based morphometry (SBM) or diffusion tensor imaging are promising but there is a lack of current studies comparing their individual diagnostic value. Post-processing methods represent an important addition to conventional visual analysis but need to be interpreted with expertise and experience so that they should be apprehended as a complementary tool within the context of the multi-modal evaluation of epilepsy patients. This review will give an overview of existing post-processing methods of structural MRI and outline their clinical relevance in detection of epileptogenic structural changes.

Keywords: Epilepsy; post-processing; voxel-based morphometry (VBM).

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Figures

Figure 1
Figure 1
Schematic overview of different VBM processing approaches. (A) Workflow of a “classical” VBM, e.g., in SPM, based on a T1-weighted image. The individual T1-weighted image is spatially normalized, segmented and smoothed. Similar workflows can be applied for magnetization transfer and T2-weighted images; (B) workflow for normalized T2-FLAIR signal intensity mapping. Segmentation and normalization is performed combined with a T1-weighted and T2-FLAIR image (after co-registered). As an additional processing step, intensity normalization of T2-FLAIR needs to be included. The other steps are similar to (A); (C) workflow following the MAP by Huppertz et al., exemplarily shown with the so called “junction map”. Normalization and segmentation are similar to classical VBM above including bias correction. Next, a binary image is created that represents the distribution of voxels with intensities between grey and white matter and then smoothed (convolved image). From the resulting image, the average of equally processed images of a normal population is subtracted and divided by the standard deviation to create a map of z-scores; (D) workflow of SBM, e.g., using Freesurfer, based on a T1-weighted image. As a first step, the boundaries between the gray/white matter and the pial surface are determined on the basis of a brain segmentation. Then the surfaces are tessellated by polygons whose meeting points or vertexes can be characterized by coordinates. To enable comparison between subjects, the brain images are warped into a common space, usually a sphere. On this basis the brains can be spatially normalized to a given template. VBM, voxel-based morphometry; SPM, statistical parametric mapping; MAP, Morphometric Analysis Programme; SBM, surface-based morphometry.
Figure 2
Figure 2
A 14-year-old child with partial (clonuses of the left hand and leg) and secondary generalized seizures since the age of 4. (A) Axial T2-weighted image; (B) axial calculated junction map (window setting −4 to +4 z-score) based on a T1 MPRAGE sequence; (C) axial calculated extension map (window setting −7 to +7 z-score) based on a T1 MPRAGE sequence; (D-F) voxel-based morphometry of FLAIR, using SPM in axial, coronal and sagittal view; (G) SBM using Freesurfer representing left (upper row) and right (lower row) hemisphere. (A) No detectable structural lesion in conventional visual analysis; (B) brighter clusters in the junction map indicating blurring of the grey-white matter junction e.g., due to a focal cortical dysplasia; (C) brighter clusters in the extension map indicating abnormal extension of grey matter into white matter e.g., abnormal gyration; (D-F) colored clusters represent regions with significantly increased FLAIR intensities (P<0.05 FWE corrected); (G) colored vertices show significant increased cortical thickness (P<0.05 FDR corrected) compatible to an MCD. All post-processing methods indicate converging the presence of a lesion in the right frontal and insular cortex. The findings in post-processing methods were congruent with EEG findings. Based on these results the patient was operated, histopathology showed a focal cortical dysplasia type IIa. The patient benefited from the operation in form of a reduction of seizure frequency and intensity. SPM, statistical parametric mapping; SBM, surface-based morphometry; FWE, family wise error correction; FDR, false discovery rate correction; MCD, malformations of cortical development.
Figure 3
Figure 3
Example of an irrelevant finding concerning the epileptological aspect and a true positive finding in a 69-year-old patient with partial seizures since the age of 12 and secondary generalized seizures since the age of 40. (A) Coronal FLAIR image; (B) coronal T2-weighted image; (C,D) coronal calculated junction map based on a T1 MPRAGE sequence; (D,E) voxel-based morphometry of FLAIR, using SPM in axial and coronal view; (G) surface-based morphometry using Freesurfer presenting left (upper row) and right (lower row) hemisphere. (A) Structural lesions due to microangiopathy in subcortical white matter (circle); (B) subtle structural changes in the right temporal lobe with blurring of the grey/white matter junction and increased signal intensity (circle); (C) brighter clusters in the junction map indicating blurring of the grey-white matter junction as often seen in a focal cortical dysplasia, yet in this case due to juxtacortical microangiopathy (false-positive); (D) Z-score increase in the junction map indicating a blurring of the grey-white matter junction concordant to conventional visual analysis in (B); (E,F) suprathreshold cluster representing voxels with significantly increase FLAIR intensities indicating structural lesion (P<0.05 FWE corrected); (G) colored vertices show significant decreased grey/white contrast (P<0.05 FDR corrected) compatible to an MCD. Correlation with (video-) EEG findings shows the epileptogenic region in the right temporal lobe. The left-sided juxtacortical white matter lesions are to be evaluated as false positive finding. This shows the importance of correlation with other diagnostic features and the advantage of multimodal post-processing. SPM, statistical parametric mapping; FWE, family wise error correction; FDR, false discovery rate correction; MCD, malformations of cortical development.
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