Novel MR contrasts to reveal more about the brain

Development of a Stand-Alone Independent Graphical User Interface for Neurological Disease Prediction with Automated Extraction and Segmentation of Gray and White Matter in Brain MRI Images

This research presents an independent stand-alone graphical computational tool which functions as a neurological disease prediction framework for diagnosis of neurological disorders to assist neurologists or researchers in the field to perform automatic segmentation of gray and white matter regions in brain MRI images. The tool was built in collaboration with neurologists and neurosurgeons and many of the features are based on their feedback. This tool provides the user automatized functionality to perform automatic segmentation and extract the gray and white matter regions of patient brain image data using an algorithm called adapted fuzzy c-means (FCM) membership-based clustering with preprocessing using the elliptical Hough transform and postprocessing using connected region analysis. Dice coefficients for several patient brain MRI images were calculated to measure the similarity between the manual tracings by experts and automatic segmentations obtained in this research. The average Dice coefficients are 0.86 for gray matter, 0.88 for white matter, and 0.87 for total cortical matter. Dice coefficients of the proposed algorithm were also the highest when compared with previously published standard state-of-the-art brain MRI segmentation algorithms in terms of accuracy in segmenting the gray matter, white matter, and total cortical matter.

Evaluation of quantitative magnetic resonance imaging contrasts in MRI-negative refractory focal epilepsy

PURPOSE

Conventional optimal MRI is unremarkable in 20%-30% of patients with intractable focal epilepsy. These MRI-negative patients are the most challenging in surgical programs. Our aim was to evaluate the yield and utility of quantitative MRI with novel contrasts in MRI-negative patients with refractory focal epilepsy, who were potential surgical candidates.

METHODS

Ninety-three consecutive potential surgical candidates with refractory focal epilepsy, 44 with temporal lobe epilepsy, and 49 with frontal lobe epilepsy as determined with ictal scalp video-EEG; and normal optimal conventional MRI, including hippocampal volumes and T2 measures were investigated with quantitative MRI contrasts. The contrasts comprised fast fluid attenuated inversion recovery based T2 measurement (FFT2), double inversion recovery (DIR), magnetization transfer ratio (MTR), and voxel-based morphometry of gray matter (VBM). Voxel-based analyses of whole brain data were used to compare each patient with a control group.

RESULTS

In patients with a putative single focus on scalp video-EEG telemetry, 16% had concordant FFT2 abnormalities, as did 16% with DIR, 5% with MTR and 9% with VBM. The greatest agreement in the localization of abnormalities was between FFT2 and DIR. Altogether, 31% patients had a focal abnormality with at least one contrast in the lobe of seizure onset. Signal changes outside the lobe of the putative focus were found with FFT2 in 36% patients, with DIR in 42%, with MTR in 6% and with VBM in 7%.

DISCUSSION

Quantitative analysis of MRI contrasts had a low yield of identifying focal abnormalities concordant with putative epileptic foci in patients with unremarkable conventional MRI. Specificity was low for FFT2 and DIR. With the low specificity, data must be interpreted with caution, but in some patients may assist in creating a hypothesis for testing with intracranial electrodes.

Dual inversion recovery MRI helps identifying cortical tubers in tuberous sclerosis

PURPOSE

Dual inversion-recovery imaging (DIR) has been advocated for the diagnosis of cortical lesions in epileptic patients. The role of this sequence, however, is not established in tuberous sclerosis patients.

METHODS

We studied prospectively the interest of DIR sequence in four well-documented consecutive tuberous sclerosis patients with focal epilepsy.

RESULTS

In all patients, the cortical tubers appeared very bright on this sequence and were well outlined compared with high resolution T2 or FLAIR imaging. In two patients, one cortical tuber was missed on T2 weighted images due to signal intensity close to the CSF. These lesions were better depicted on DIR than on FLAIR. Three cortical lesions from two patients were visualized only on DIR.

CONCLUSION

DIR helped to depict cortical tubers and may have a complementary role in the MRI evaluation of tuberous sclerosis patients. There is a need to compare sensitivity of T2, FLAIR and DIR with a larger population of patients with focal epilepsies.