Search

Background and Objectives: Identification of an epileptogenic lesion on structural neuroimaging in individuals with focal epilepsy is important for management and treatment planning. The objective of this study was to determine the frequency of MRI-identified potentially epileptogenic structural abnormalities in a large multicenter study of adolescent and adult patients with newly diagnosed focal epilepsy., Methods: Patients with a new diagnosis of focal epilepsy enrolled in the Human Epilepsy Project observational cohort study underwent 3 T brain MRI using a standardized protocol. Imaging findings were classified as normal, abnormal, or incidental. Abnormal findings were classified as focal or diffuse and as likely epilepsy-related or of unknown relationship to epilepsy. Fisher exact tests were performed to determine whether abnormal imaging or abnormality type was associated with clinical characteristics., Results: A total of 418 participants were enrolled. Two hundred eighteen participants (59.3%) had no abnormalities detected, 149 (35.6%) had abnormal imaging, and 21 (5.0%) had incidental findings. Seventy-eight participants (18.7%) had abnormalities that were considered epilepsy-related, and 71 (17.0%) had abnormalities of unknown relationship to epilepsy. Older participants were more likely to have imaging abnormalities, while participants with focal and epilepsy-related imaging abnormalities were younger than those without these abnormalities. One hundred thirty-one participants (31.3%) had a family history of epilepsy. Epilepsy-related abnormalities were not associated with participant sex, family history of epilepsy, or seizure type., Discussion: We found that 1 in 5 patients with newly diagnosed focal epilepsy has an MRI finding that is likely causative and may alter treatment options. An additional 1 in 5 patients has abnormalities of unknown significance. This information is important for patient counseling, prognostication, and management., (© 2022 American Academy of Neurology.)

Background and Objective: To test the hypothesis that a multicenter-validated computer deep learning algorithm detects MRI-negative focal cortical dysplasia (FCD)., Methods: We used clinically acquired 3-dimensional (3D) T1-weighted and 3D fluid-attenuated inversion recovery MRI of 148 patients (median age 23 years [range 2-55 years]; 47% female) with histologically verified FCD at 9 centers to train a deep convolutional neural network (CNN) classifier. Images were initially deemed MRI-negative in 51% of patients, in whom intracranial EEG determined the focus. For risk stratification, the CNN incorporated bayesian uncertainty estimation as a measure of confidence. To evaluate performance, detection maps were compared to expert FCD manual labels. Sensitivity was tested in an independent cohort of 23 cases with FCD (13 ± 10 years). Applying the algorithm to 42 healthy controls and 89 controls with temporal lobe epilepsy disease tested specificity., Results: Overall sensitivity was 93% (137 of 148 FCD detected) using a leave-one-site-out cross-validation, with an average of 6 false positives per patient. Sensitivity in MRI-negative FCD was 85%. In 73% of patients, the FCD was among the clusters with the highest confidence; in half, it ranked the highest. Sensitivity in the independent cohort was 83% (19 of 23; average of 5 false positives per patient). Specificity was 89% in healthy and disease controls., Discussion: This first multicenter-validated deep learning detection algorithm yields the highest sensitivity to date in MRI-negative FCD. By pairing predictions with risk stratification, this classifier may assist clinicians in adjusting hypotheses relative to other tests, increasing diagnostic confidence. Moreover, generalizability across age and MRI hardware makes this approach ideal for presurgical evaluation of MRI-negative epilepsy., Classification of Evidence: This study provides Class III evidence that deep learning on multimodal MRI accurately identifies FCD in patients with epilepsy initially diagnosed as MRI negative., (© 2021 American Academy of Neurology.)

Objective: To determine the genetic basis of bottom-of-sulcus dysplasia (BOSD), which is a highly focal and epileptogenic cortical malformation in which the imaging, electrophysiologic, and pathologic abnormalities are maximal at the bottom of sulcus, tapering to a normal gyral crown., Methods: Targeted panel deep sequencing (>500×) was performed on paired blood and brain-derived genomic DNA from 20 operated patients with drug-resistant focal epilepsy and BOSD. Histopathology was assessed using immunohistochemistry., Results: Brain-specific pathogenic somatic variants were found in 6 patients and heterozygous pathogenic germline variants were found in 2. Somatic variants were identified in MTOR and germline variants were identified in DEPDC5 and NPRL3 . Two patients with somatic MTOR variants showed a mutation gradient, with higher mutation load at the bottom of sulcus compared to the gyral crown. Immunohistochemistry revealed an abundance of dysmorphic neurons and balloon cells in the bottom of sulcus but not in the gyral crown or adjacent gyri., Conclusions: BOSD is associated with mTOR pathway dysregulation and shares common genetic etiologies and pathogenic mechanisms with other forms of focal and hemispheric cortical dysplasia, suggesting these disorders are on a genetic continuum., (© 2020 American Academy of Neurology.)

Objective: Patients with temporal lobe epilepsy (TLE) are similar in their epileptology regardless of whether they have a lesion evident on MRI; this study aims to prospectively clarify whether they are also similar in their neuropsychological profiles., Methods: Participants comprised 152 adults: 79 patients with TLE and 73 healthy controls. Patients and controls did not differ in age, sex, or education ( p > 0.05). Sixty-two percent of patients had an MRI-resolvable lesion (39% with presumed hippocampal sclerosis [HS-TLE], 61% with a lesion other than HS [MRI-positive TLE]); the remaining 38% of patients were lesion-negative. Psychometric measures well established in epilepsy were used., Results: Relative to controls, all 3 patient subgroups showed significantly impaired autobiographical, verbal, and visual memory ( p < 0.05-0.001) and significantly more depression and anxiety ( p < 0.05-0.01). Yet, contrary to expectations, the 3 TLE subgroups did not differ in their severity of memory or mood impairment ( p > 0.05). Lower Full-Scale IQ predicted memory impairments across all TLE subtypes, with early age at seizure onset a predictor unique to MRI-negative TLE., Conclusions: MRI-negative TLE is associated with memory and mood dysfunction equivalent to that seen in patients with hippocampal sclerosis and other MRI-resolvable pathologies. As such, neuropsychological impairments in TLE are not contingent on a macroscopic lesion and might be an intrinsic property of the underlying network disease., (Copyright © 2019 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

Objective: To examine associations between ischemic stroke, vascular risk factors, and MRI markers of brain aging., Methods: Eighty-one patients (mean age 67.5 ± 13.1 years, 31 left-sided, 61 men) with confirmed first-ever (n = 66) or recurrent (n = 15) ischemic stroke underwent 3T MRI scanning within 6 weeks of symptom onset (mean 26 ± 9 days). Age-matched controls (n = 40) completed identical testing. Multivariate regression analyses examined associations between group membership and MRI markers of brain aging (cortical thickness, total brain volume, white matter hyperintensity [WMH] volume, hippocampal volume), normalized against intracranial volume, and the effects of vascular risk factors on these relationships., Results: First-ever stroke was associated with smaller hippocampal volume ( p = 0.025) and greater WMH volume ( p = 0.004) relative to controls. Recurrent stroke was in turn associated with smaller hippocampal volume relative to both first-ever stroke ( p = 0.017) and controls ( p = 0.001). These associations remained significant after adjustment for age, sex, education, and, in stroke patients, infarct volume. Total brain volume was not significantly smaller in first-ever stroke patients than in controls ( p = 0.056), but the association became significant after further adjustment for atrial fibrillation ( p = 0.036). Cortical thickness and brain volumes did not differ as a function of stroke type, infarct volume, or etiology., Conclusions: Brain structure is likely to be compromised before ischemic stroke by vascular risk factors. Smaller hippocampal and total brain volumes and increased WMH load represent proxies for underlying vascular brain injury., (Copyright © 2017 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

We assessed performance on selected tests of verbal memory in 48 patients who had undergone either anterior temporal lobectomy or selective amygdalo-hippocampectomy for the relief of pharmacologically intractable epilepsy. We related performance both to the side of surgical excision and to the presence or absence of abnormalities in the contralateral, unoperated, temporal lobe, as revealed by proton magnetic resonance spectroscopy (1H MRS) or T2 relaxometry. There were abnormalities on the unoperated side detected by 1H MRS in 50% of the 34 patients who successfully underwent spectroscopy, and by T2 relaxometry in 33% of the complete series of 48 patients. There was no systematic relationship between seizure outcome and the presence or absence of abnormalities on the unoperated side. Verbal memory deficits were present in patients with left-sided excision, regardless of whether there were abnormalities on the unoperated side. The patients with right-sided excision also had verbal memory deficits, but only in the group with magnetic resonance abnormalities on the contralateral (ie, left) side and only on delayed recall. The study extends previous findings on the role of the temporal lobes in memory and highlights the role of these new magnetic resonance techniques in relating cognitive processes to brain structures.