Magnetic resonance imaging findings in Kenyans and South Africans with active convulsive epilepsy: an observational study

Objective: Focal epilepsy is common in low- and middle-income countries. The frequency and nature of possible underlying structural brain abnormalities have, however, not been fully assessed. Methods: We evaluated the possible structural causes of epilepsy in 331 people with epilepsy (240 from Kenya and 91 from South Africa) identified from community surveys of active convulsive epilepsy. Magnetic resonance imaging (MRI) scans were acquired on 1.5-Tesla scanners to determine the frequency and nature of any underlying lesions. We estimated the prevalence of these abnormalities using Bayesian priors (from an earlier pilot study) and observed data (from this study). We used a mixed-effect modified Poisson regression approach with the site as a random effect to determine the clinical features associated with neuropathology. Results: MRI abnormalities were found in 140 of 240 (modeled prevalence = 59%, 95% confidence interval [CI]: 53%–64%) of people with epilepsy in Kenya, and in 62 of 91 (modeled prevalence = 65%, 95% CI: 57%–73%) in South Africa, with a pooled modeled prevalence of 61% (95% CI: 56%–66%). Abnormalities were common in those with a history of adverse perinatal events (15/23 [65%, 95% CI: 43%–84%]), exposure to parasitic infections (83/120 [69%, 95% CI: 60%–77%]) and focal electroencephalographic features (97/142 [68%, 95% CI: 60%–76%]), but less frequent in individuals with generalized electroencephalographic features (44/99 [44%, 95% CI: 34%–55%]). Most abnormalities were potentially epileptogenic (167/202, 82%), of which mesial temporal sclerosis (43%) and gliosis (34%) were the most frequent. Abnormalities were associated with co-occurrence of generalized non-convulsive seizures (relative risk [RR] = 1.12, 95% CI: 1.04–1.25), lack of family history of seizures (RR = 0.91, 0.86–0.96), convulsive status epilepticus (RR = 1.14, 1.08–1.21), frequent seizures (RR = 1.12, 1.04–1.20), and reported use of anti-seizure medication (RR = 1.22, 1.18–1.26). Significance: MRI identified pathologies are common in people with epilepsy in Kenya and South Africa. Mesial temporal sclerosis, the most common abnormality, may be amenable to surgical correction. MRI may have a diagnostic value in rural Africa, but future longitudinal studies should examine the prognostic role

Magnetic resonance imaging findings in Kenyans and South Africans with active convulsive epilepsy: an observational study

Objective: Focal epilepsy is common in low- and middle-income countries. The frequency and nature of possible underlying structural brain abnormalities have, however, not been fully assessed. Methods: We evaluated the possible structural causes of epilepsy in 331 people with epilepsy (240 from Kenya and 91 from South Africa) identified from community surveys of active convulsive epilepsy. Magnetic resonance imaging (MRI) scans were acquired on 1.5-Tesla scanners to determine the frequency and nature of any underlying lesions. We estimated the prevalence of these abnormalities using Bayesian priors (from an earlier pilot study) and observed data (from this study). We used a mixed-effect modified Poisson regression approach with the site as a random effect to determine the clinical features associated with neuropathology. Results: MRI abnormalities were found in 140 of 240 (modeled prevalence = 59%, 95% confidence interval [CI]: 53%–64%) of people with epilepsy in Kenya, and in 62 of 91 (modeled prevalence = 65%, 95% CI: 57%–73%) in South Africa, with a pooled modeled prevalence of 61% (95% CI: 56%–66%). Abnormalities were common in those with a history of adverse perinatal events (15/23 [65%, 95% CI: 43%–84%]), exposure to parasitic infections (83/120 [69%, 95% CI: 60%–77%]) and focal electroencephalographic features (97/142 [68%, 95% CI: 60%–76%]), but less frequent in individuals with generalized electroencephalographic features (44/99 [44%, 95% CI: 34%–55%]). Most abnormalities were potentially epileptogenic (167/202, 82%), of which mesial temporal sclerosis (43%) and gliosis (34%) were the most frequent. Abnormalities were associated with co-occurrence of generalized non-convulsive seizures (relative risk [RR] = 1.12, 95% CI: 1.04–1.25), lack of family history of seizures (RR = 0.91, 0.86–0.96), convulsive status epilepticus (RR = 1.14, 1.08–1.21), frequent seizures (RR = 1.12, 1.04–1.20), and reported use of anti-seizure medication (RR = 1.22, 1.18–1.26). Significance: MRI identified pathologies are common in people with epilepsy in Kenya and South Africa. Mesial temporal sclerosis, the most common abnormality, may be amenable to surgical correction. MRI may have a diagnostic value in rural Africa, but future longitudinal studies should examine the prognostic role

Novel surface features for automated detection of focal cortical dysplasias in paediatric epilepsy.

Focal cortical dysplasia is a congenital abnormality of cortical development and the leading cause of surgically remediable drug-resistant epilepsy in children. Post-surgical outcome is improved by presurgical lesion detection on structural MRI. Automated computational techniques have improved detection of focal cortical dysplasias in adults but have not yet been effective when applied to developing brains. There is therefore a need to develop reliable and sensitive methods to address the particular challenges of a paediatric cohort. We developed a classifier using surface-based features to identify focal abnormalities of cortical development in a paediatric cohort. In addition to established measures, such as cortical thickness, grey-white matter blurring, FLAIR signal intensity, sulcal depth and curvature, our novel features included complementary metrics of surface morphology such as local cortical deformation as well as post-processing methods such as the "doughnut" method - which quantifies local variability in cortical morphometry/MRI signal intensity, and per-vertex interhemispheric asymmetry. A neural network classifier was trained using data from 22 patients with focal epilepsy (mean age = 12.1 ± 3.9, 9 females), after intra- and inter-subject normalisation using a population of 28 healthy controls (mean age = 14.6 ± 3.1, 11 females). Leave-one-out cross-validation was used to quantify classifier sensitivity using established features and the combination of established and novel features. Focal cortical dysplasias in our paediatric cohort were correctly identified with a higher sensitivity (73%) when novel features, based on our approach for detecting local cortical changes, were included, when compared to the sensitivity using only established features (59%). These methods may be applicable to aiding identification of subtle lesions in medication-resistant paediatric epilepsy as well as to the structural analysis of both healthy and abnormal cortical development.This research was supported by the National Institute for Health Research Biomedical Research Centre at Great Ormond Street Hospital for Children NHS Foundation Trust and University College London. SA received funding from the Rosetrees Trust (A711). KW received funding from the James Baird Fund and the Wellcome Trust (WT095692MA). TB from Great Ormond Street Hospital Children's Charity (V1213 and V2416). LR and PCF are funded by the Wellcome Trust and the Bernard Wolfe Health Neuroscience Fund

Post mortem magnetic resonance imaging in the fetus, infant and child: A comparative study with conventional autopsy (MaRIAS Protocol)

<p>Abstract</p> <p>Background</p> <p>Minimally invasive autopsy by post mortem magnetic resonance (MR) imaging has been suggested as an alternative for conventional autopsy in view of the declining consented autopsy rates. However, large prospective studies rigorously evaluating the accuracy of such an approach are lacking. We intend to compare the accuracy of a minimally invasive autopsy approach using post mortem MR imaging with that of conventional autopsy in fetuses, newborns and children for detection of the major pathological abnormalities and/or determination of the cause of death.</p> <p>Methods/Design</p> <p>We recruited 400 consecutive fetuses, newborns and children referred for conventional autopsy to one of the two participating hospitals over a three-year period. We acquired whole body post mortem MR imaging using a 1.5 T MR scanner (Avanto, Siemens Medical Solutions, Enlargen, Germany) prior to autopsy. The total scan time varied between 90 to 120 minutes. Each MR image was reported by a team of four specialist radiologists (paediatric neuroradiology, paediatric cardiology, paediatric chest & abdominal imaging and musculoskeletal imaging), blinded to the autopsy data. Conventional autopsy was performed according to the guidelines set down by the Royal College of Pathologists (UK) by experienced paediatric or perinatal pathologists, blinded to the MR data. The MR and autopsy data were recorded using predefined categorical variables by an independent person.</p> <p>Discussion</p> <p>Using conventional post mortem as the gold standard comparator, the MR images will be assessed for accuracy of the anatomical morphology, associated lesions, clinical usefulness of information and determination of the cause of death. The sensitivities, specificities and predictive values of post mortem MR alone and MR imaging along with other minimally invasive post mortem investigations will be presented for the final diagnosis, broad diagnostic categories and for specific diagnosis of each system.</p> <p>Clinical Trial Registration</p> <p><a href="http://www.clinicaltrials.gov/ct2/show/NCT01417962">NCT01417962</a></p> <p><b>NIHR Portfolio Number: </b>6794</p

Novel surface features for automated detection of focal cortical dysplasias in paediatric epilepsy.

Focal cortical dysplasia is a congenital abnormality of cortical development and the leading cause of surgically remediable drug-resistant epilepsy in children. Post-surgical outcome is improved by presurgical lesion detection on structural MRI. Automated computational techniques have improved detection of focal cortical dysplasias in adults but have not yet been effective when applied to developing brains. There is therefore a need to develop reliable and sensitive methods to address the particular challenges of a paediatric cohort. We developed a classifier using surface-based features to identify focal abnormalities of cortical development in a paediatric cohort. In addition to established measures, such as cortical thickness, grey-white matter blurring, FLAIR signal intensity, sulcal depth and curvature, our novel features included complementary metrics of surface morphology such as local cortical deformation as well as post-processing methods such as the "doughnut" method - which quantifies local variability in cortical morphometry/MRI signal intensity, and per-vertex interhemispheric asymmetry. A neural network classifier was trained using data from 22 patients with focal epilepsy (mean age = 12.1 ± 3.9, 9 females), after intra- and inter-subject normalisation using a population of 28 healthy controls (mean age = 14.6 ± 3.1, 11 females). Leave-one-out cross-validation was used to quantify classifier sensitivity using established features and the combination of established and novel features. Focal cortical dysplasias in our paediatric cohort were correctly identified with a higher sensitivity (73%) when novel features, based on our approach for detecting local cortical changes, were included, when compared to the sensitivity using only established features (59%). These methods may be applicable to aiding identification of subtle lesions in medication-resistant paediatric epilepsy as well as to the structural analysis of both healthy and abnormal cortical development.This research was supported by the National Institute for Health Research Biomedical Research Centre at Great Ormond Street Hospital for Children NHS Foundation Trust and University College London. SA received funding from the Rosetrees Trust (A711). KW received funding from the James Baird Fund and the Wellcome Trust (WT095692MA). TB from Great Ormond Street Hospital Children's Charity (V1213 and V2416). LR and PCF are funded by the Wellcome Trust and the Bernard Wolfe Health Neuroscience Fund

The Anti-Competitive Aspects of Trade Name Protection and the Policy against Consumer Deception

Focal cortical dysplasia is a congenital abnormality of cortical development and the leading cause of surgically remediable drug-resistant epilepsy in children. Post-surgical outcome is improved by presurgical lesion detection on structural MRI. Automated computational techniques have improved detection of focal cortical dysplasias in adults but have not yet been effective when applied to developing brains. There is therefore a need to develop reliable and sensitive methods to address the particular challenges of a paediatric cohort. We developed a classifier using surface-based features to identify focal abnormalities of cortical development in a paediatric cohort. In addition to established measures, such as cortical thickness, grey-white matter blurring, FLAIR signal intensity, sulcal depth and curvature, our novel features included complementary metrics of surface morphology such as local cortical deformation as well as post-processing methods such as the “doughnut” method - which quantifies local variability in cortical morphometry/MRI signal intensity, and per-vertex interhemispheric asymmetry. A neural network classifier was trained using data from 22 patients with focal epilepsy (mean age = 12.1 ± 3.9, 9 females), after intra- and inter-subject normalisation using a population of 28 healthy controls (mean age = 14.6 ± 3.1, 11 females). Leave-one-out cross-validation was used to quantify classifier sensitivity using established features and the combination of established and novel features. Focal cortical dysplasias in our paediatric cohort were correctly identified with a higher sensitivity (73%) when novel features, based on our approach for detecting local cortical changes, were included, when compared to the sensitivity using only established features (59%). These methods may be applicable to aiding identification of subtle lesions in medication-resistant paediatric epilepsy as well as to the structural analysis of both healthy and abnormal cortical development

Towards in vivo focal cortical dysplasia phenotyping using quantitative MRI

Focal cortical dysplasias (FCDs) are a range of malformations of cortical development each with specific histopathological features. Conventional radiological assessment of standard structural MRI is useful for the localization of lesions but is unable to accurately predict the histopathological features. Quantitative MRI offers the possibility to probe tissue biophysical properties in vivo and may bridge the gap between radiological assessment and ex-vivo histology. This review will cover histological, genetic and radiological features of FCD following the ILAE classification and will explain how quantitative voxel- and surface-based techniques can characterise these features. We will provide an overview of the quantitative MRI measures available, their link with biophysical properties and finally the potential application of quantitative MRI to the problem of FCD subtyping. Future research linking quantitative MRI to FCD histological properties should improve clinical protocols, allow better characterisation of lesions in vivo and tailored surgical planning to the individual. Keywords: Focal cortical dysplasia, Biophysical tissue properties, Histology, Radiology, MRI, Quantitative mapping, qMRI, Quantitative MRI, Epilepsy surgery, Malformation of cortical developmen

Muscle "islands": An MRI signature distinguishing neurogenic from myopathic causes of early onset distal weakness

Muscle MRI has an increasing role in diagnosis of inherited neuromuscular diseases, but no features are known which reliably differentiate myopathic and neurogenic conditions. Using patients presenting with early onset distal weakness, we aimed to identify an MRI signature to distinguish myopathic and neurogenic conditions. We identified lower limb MRI scans from patients with either genetically (n = 24) or clinically (n = 13) confirmed diagnoses of childhood onset distal myopathy or distal spinal muscular atrophy. An initial exploratory phase reviewed 11 scans from genetically confirmed patients identifying a single potential discriminatory marker concerning the pattern of fat replacement within muscle, coined "islands". This pattern comprised small areas of muscle tissue with normal signal intensity completely surrounded by areas with similar intensity to subcutaneous fat. In the subsequent validation phase, islands correctly classified scans from all 12 remaining genetically confirmed patients, and 12/13 clinically classified patients. In the genetically confirmed patients MRI classification of neurogenic/myopathic aetiology had 100% accuracy (24/24) compared with 65% accuracy (15/23) for EMG, and 79% accuracy (15/19) for muscle biopsy. Future studies are needed in other clinical contexts, however the presence of islands appears to highly suggestive of a neurogenic aetiology in patients presenting with early onset distal motor weakness. (C) 2021 Elsevier B.V. All rights reserved

Magnetic Resonance Imaging Findings in Kenyans and South Africans with Active Convulsive Epilepsy: An Observational Study

OBJECTIVE: Focal epilepsy is common in low- and middle-income countries. The frequency and nature of possible underlying structural brain abnormalities have, however, not been fully assessed. METHODS: We evaluated the possible structural causes of epilepsy in 331 people with epilepsy (240 from Kenya and 91 from South Africa) identified from community surveys of active convulsive epilepsy. Magnetic Resonance Imaging (MRI) scans were acquired on 1.5-tesla scanners to determine the frequency and nature of underlying lesions. We estimated the prevalence of these abnormalities using Bayesian priors (from an earlier pilot study) and observed data (from this study). We used a mixed-effect modified Poisson regression approach with the site as a random effect to determine the clinical features associated with neuropathology. RESULTS: MRI abnormalities were found in 140/240 (modelled prevalence=59% (95%CI:53%-64%)) of people with epilepsy in Kenya, and in 62/91 (modelled prevalence=65% (95%CI:57%-73%)) in South Africa, with a pooled modelled prevalence of 61% (95%CI:56%-66%). Abnormalities were common in those with a history of adverse perinatal events (15/23 (65% (95%CI:43%-84%))), exposure to parasitic infections (83/120 (69% (95%CI:60%-77%))) and focal electroencephalographic (EEG) features (97/142 (68% (95%CI:60%-76%))), but less frequent in individuals with generalized EEG features (44/99 (44% (95%CI:34%-55%))). Most abnormalities were potentially epileptogenic (167/202 (82%)), of which mesial temporal sclerosis (43%) and gliosis (34%) were most frequent. Abnormalities were associated with co-occurrence of generalised non-convulsive seizures (relative risk (RR)=1.12 (95%CI:1.04-1.25)), lack of family history of seizures (RR=0.91 (0.86-0.96), status epilepticus (RR=1.14 (1.08-1.21)), frequent seizures (RR=1.12 (1.04-1.20)) and reported use of anti-seizure medication (RR=1.22 (1.18-1.26)). SIGNIFICANCE: MRI identified pathologies common in people with epilepsy in Kenya and South Africa. MTS, the most common abnormality, may be amenable to surgical correction. MRI may have a diagnostic value in rural Africa, but future longitudinal studies should examine the prognostic role

Multimodal computational neocortical anatomy in pediatric hippocampal sclerosis

Objective: In contrast to adult cohorts, neocortical changes in epileptic children with hippocampal damage are not well characterized. Here, we mapped multimodal neocortical markers of epilepsy-related structural compromise in a pediatric cohort of temporal lobe epilepsy and explored how they relate to clinical factors. Methods: We measured cortical thickness, gray–white matter intensity contrast and intracortical FLAIR intensity in 22 patients with hippocampal sclerosis (HS) and 30 controls. Surface-based linear models assessed between-group differences in morphological and MR signal intensity markers. Structural integrity of the hippocampus was measured by quantifying atrophy and FLAIR patterns. Linear models were used to evaluate the relationships between hippocampal and neocortical MRI markers and clinical factors. Results: In the hippocampus, patients demonstrated ipsilateral atrophy and bilateral FLAIR hyperintensity. In the neocortex, patients showed FLAIR signal hyperintensities and gray–white matter boundary blurring in the ipsilesional mesial and lateral temporal neocortex. In contrast, cortical thinning was minimal and restricted to a small area of the ipsilesional temporal pole. Furthermore, patients with a history of febrile convulsions demonstrated more pronounced FLAIR hyperintensity in the ipsilesional temporal neocortex. Interpretation: Pediatric HS patients do not yet demonstrate the widespread cortical thinning present in adult cohorts, which may reflect consequences of a protracted disease process. However, pronounced temporal neocortical FLAIR hyperintensity and blurring of the gray–white matter boundary are already detectable, suggesting that alterations in MR signal intensities may reflect a different underlying pathophysiology that is detectable earlier in the disease and more pervasive in patients with a history of febrile convulsions