Subcortical alterations in tissue microstructure adjacent to focal cortical dysplasia: detection at diffusion-tensor MR imaging by using magnetoencephalographic dipole cluster localization.
ABSTRACT To determine whether changes at diffusion-tensor magnetic resonance (MR) imaging were present in children with intractable epilepsy and focal cortical dysplasia (FCD) in (a) subcortical white matter subjacent to MR imaging-visible areas of FCD, (b) subcortical white matter beyond the MR imaging-visible abnormality but subjacent to a magnetoencephalographic (MEG) dipole cluster, and (c) deep white matter tracts.
The study protocol had institutional research ethics board approval, and written informed consent was obtained. Fifteen children with FCD and intractable epilepsy (mean age, 11.6 years; range, 3.6-18.3 years) underwent diffusion-tensor MR imaging and MEG. Regions of interest were placed in (a) the subcortical white matter subjacent to the MR imaging-visible abnormality, as well as the contralateral side; (b) the subcortical white matter beyond the MR imaging-visible abnormality but subjacent to a MEG dipole cluster, as well as the contralateral side; and (c) deep white matter tracts projecting to or from the MR imaging-visible FCD, as well as the contralateral side. Fractional anisotropy (FA), mean diffusivity, and eigenvalues (lambda(1), lambda(2), lambda(3)) were evaluated.
Eleven of 15 children had MEG dipole clusters, and four children had MEG scatter. There were significant differences in FA, mean diffusivity, lambda(2), and lambda(3) of the subcortical white matter subjacent to the MR imaging-visible FCD (P < .001 for all), as well as that beyond the MR imaging-visible FCD but subjacent to a MEG dipole cluster (P = .001, P = .036, P < .001, and P = .002, respectively), compared with the contralateral side. There were also significant differences in FA (P < .001), mean diffusivity (P = .008), lambda(2) (P < .001), and lambda(3) (P = .001) of the deep white matter tracts projecting to or from the MR imaging-visible FCD compared with the contralateral side.
With use of MEG dipole clusters to localize the epileptogenic zone, diffusion-tensor imaging can help identify alterations in tissue microstructure beyond the MR imaging-visible FCD.
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ABSTRACT: BACKGROUND: Despite pharmacological and surgical interventions, some children with periventricular nodular heterotopia (PNH) remain refractory to treatment, which suggests more diffuse pathology potentially involving perilesional white matter. OBJECTIVE: The purpose of this study was to evaluate MR diffusion tensor imaging (MRDTI) metrics within perilesional white matter in children with PNH. MATERIALS AND METHODS: Six children with PNH (four boys; average age 3.2 years, range 2 months to 6 years) were studied with MRDTI at 3 T. Fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) were quantified within perilesional white matter at distances of 5 mm, 10 mm, 15 mm, and 20 mm from focal areas of PNH and compared to location-matched ROIs in six healthy control patients (two boys, average age 3.3 years, range 2-6 years). Statistical significance was set at an overall level of α = 0.05, corrected for multiple comparisons. RESULTS: Perilesional white matter showed significantly decreased fractional anisotropy and elevated mean and radial diffusivity at all evaluated distances. No significant differences in axial diffusivity were detected at any distance. CONCLUSION: PNH is associated with microstructural white matter abnormalities as indicated by abnormal perilesional MRDTI metrics detectable at least 20 mm from visible nodular lesions.Pediatric Radiology 03/2013; · 1.57 Impact Factor
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ABSTRACT: Advancements in diffusion-weighted imaging (DWI) over the past decade have led to the utilization of diffusion tensor imaging (DTI) to further characterize the structural integrity of neural tissue and to noninvasively trace neuronal tracts in the brain and spine. This has led to many clinical applications that have aided in surgical planning for brain and spinal cord tumors and has increased the diagnostic potential of magnetic resonance imaging (MRI) in disorders such as multiple sclerosis, Alzheimer disease and traumatic brain injury.World Neurosurgery 08/2013; · 1.77 Impact Factor
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ABSTRACT: INTRODUCTION: The contribution of radial migration lines (RMLs) to the neuroanatomical and neurocognitive phenotype of tuberous sclerosis complex (TSC) is unclear. The aim of this study was to perform a comprehensive evaluation of the neuroradiological phenotype of TSC, distinguishing RMLs from normal-appearing white matter (NAWM) using diffusion tensor imaging (DTI) and volumetric fluid-attenuated inversion recovery imaging. METHODS: Magnetic resonance images of 30 patients with TSC were evaluated. The frequencies of RMLs, tubers, and subependymal nodules (SENs) were determined for every hemispheric lobe. Cerebellar lesions and subependymal giant cell tumors were counted. DTI metrics were obtained from the NAWM of every hemispheric lobe and from the largest RML and tuber. Analyses of variance and correlations were performed to investigate the associations between neuroanatomical characteristics and relationships between RML frequency and neurocognitive outcomes. NAWM DTI metrics were compared with measurements of 16 control patients. RESULTS: A mean of 47 RMLs, 27 tubers, and 10 SENs were found per patient, and the frequencies of these lesions were strongly correlated (p < 0.001). RML fractional anisotropy and mean diffusivity were strongly inversely correlated (p = 0.003). NAWM DTI metrics were similar to the controls (p = 0.26). RML frequency was strongly associated with age of seizure onset (p = 0.003), intelligence outcomes (p = 0.01), and level of autistic features (p = 0.007). CONCLUSION: A detailed neuroradiological phenotype is presented, showing that RMLs are the most frequent neuroanatomical lesion, are responsible for white matter DTI abnormalities, and are strongly associated with age of seizure onset, intelligence outcomes, and level of autistic features.Neuroradiology 05/2013; · 2.70 Impact Factor