External validation of automated focal cortical dysplasia detection using morphometric analysis.

OBJECTIVE: Focal cortical dysplasias (FCDs) are a common cause of drug-resistant focal epilepsy but frequently remain undetected by conventional magnetic resonance imaging (MRI) assessment. The visual detection can be facilitated by morphometric analysis of T1-weighted images, for example, using the Morphometric Analysis Program (v2018; MAP18), which was introduced in 2005, independently validated for its clinical benefits, and successfully integrated in standard presurgical workflows of numerous epilepsy centers worldwide. Here we aimed to develop an artificial neural network (ANN) classifier for robust automated detection of FCDs based on these morphometric maps and probe its generalization performance in a large, independent data set. METHODS: In this retrospective study, we created a feed-forward ANN for FCD detection based on the morphometric output maps of MAP18. The ANN was trained and cross-validated on 113 patients (62 female, mean age ± SD =29.5 ± 13.6 years) with manually segmented FCDs and 362 healthy controls (161 female, mean age ± SD =30.2 ± 9.6 years) acquired on 13 different scanners. In addition, we validated the performance of the trained ANN on an independent, unseen data set of 60 FCD patients (28 female, mean age ± SD =30 ± 15.26 years) and 70 healthy controls (42 females, mean age ± SD = 40.0 ± 12.54 years). RESULTS: In the cross-validation, the ANN achieved a sensitivity of 87.4% at a specificity of 85.4% on the training data set. On the independent validation data set, our method still reached a sensitivity of 81.0% at a comparably high specificity of 84.3%. SIGNIFICANCE: Our method shows a robust automated detection of FCDs and performance generalizability, largely independent of scanning site or MR-sequence parameters. Taken together with the minimal input requirements of a standard T1 image, our approach constitutes a clinically viable and useful tool in the presurgical diagnostic routine for drug-resistant focal epilepsy.

Intra- and interscanner variability of automated voxel-based volumetry based on a 3D probabilistic atlas of human cerebral structures.

The intra- and inter-scanner variability of an automated method for MRI-based volumetry was investigated. Using SPM5 algorithms and predefined masks derived from a probabilistic whole-brain atlas, this method allows to determine the volumes of various brain structures (e.g., hemispheres, lobes, cerebellum, basal ganglia, grey and white matter etc.) in single subjects in an observer-independent fashion. A healthy volunteer was scanned three times at six different MRI scanners (including different vendors and field strengths) to calculate intra- and inter-scanner volumetric coefficients of variation (CV). The mean intra-scanner CV values per brain structure ranged from 0.50% to 4.4% (median, 0.89%), while the inter-scanner CV results varied between 0.66% and 14.7% (median, 4.74%). The overall (=combined intra- and inter-scanner) variability of measurements was only marginally higher, with CV results of 0.87-15.1% (median, 4.80%). Furthermore, the minimum percentage volume difference for detecting a significant volume change between two volume measurements in the same subject was calculated for each substructure. For example, for the total brain volume, mean intra-scanner, inter-scanner, and overall CV results were 0.50%, 3.78%, and 3.80%, respectively, and the cut-offs for significant volume changes between two measurements in the same subject amounted to 1.4% for measurements on the same scanner and 10.5% on different scanners. These findings may be useful for planning and assessing volumetric studies in neurological diseases, for the differentiation of certain patterns of atrophy, or for longitudinal studies monitoring the course of a disease and potential therapeutic effects.

Non-paraneoplastic limbic encephalitis associated with antibodies to potassium channels leading to bilateral hippocampal sclerosis in a pre-pubertal girl.

Limbic encephalitis (LE) is increasingly recognized as a precipitating factor of adult onset temporal lobe epilepsy frequently associated with bilateral hippocampal damage. So far, clinical data in children are rare and only comprise paraneoplastic forms of LE. We describe a 13-year-old pre-pubertal girl in whom non-paraneoplastic LE was diagnosed according to diagnostic criteria proposed by Bien and Elger (2007). The girl presented with a subacute syndrome comprising memory impairment, affective disturbances, and refractory temporal lobe seizures. Serial MRI scans demonstrated an initial temporo-medial swelling with T2/FLAIR signal increase progressing to bilateral hippocampal atrophy within seven months. Two years after onset of symptoms, antibodies to potassium channels were found to be slightly elevated. Immunosuppressive therapy with steroid-pulses was followed by a transient reduction of seizure frequency, even though this was started more than two years after onset of first symptoms. However, extended immunotherapy was refused by the patient's parents, so no full assessment of the treatment response was possible. In conclusion, this case shows that non-paraneoplastic LE leading to mesial temporal lobe epilepsy is not restricted to adult patients. The proposed diagnostic criteria therefore should be adapted for paediatric patients. Patients may profit from immunosuppressive therapy even when it is started at a late stage with already overt hippocampal sclerosis.

Levetiracetam-induced myoclonic status epilepticus in myoclonic-astatic epilepsy: a case report.

We report on a 3-year-old boy with myoclonic-astatic epilepsy who developed myoclonic status epilepticus with continuous twitching of the face and unresponsiveness under monotherapy with levetiracetam. Recently, a nonconvulsive status epilepticus in an adult epilepsy patient has also been described. Our observation points to the possibility of a causal relationship between the induction of myoclonic status by levetiracetam in certain patients with Doose's syndrome. However, a spontaneous evolution cannot be excluded. Levetiracetam is a well-known drug for the control of myoclonic seizures. A controlled study would provide a better understanding of any possible aggravating role in certain forms of myoclonic-astatic epilepsy.

Automatic striatal volumetry allows for identification of patients with chorea-acanthocytosis at single subject level.

Chorea-acanthocytosis (ChAc) is a rare autosomal recessive neurodegenerative disease with erythrocyte membrane dysfunction, progressive hyperkinesia, and neuropsychological abnormalities. Neuropathologic and neuroimaging investigations demonstrate damage to the basal ganglia. Here, a novel automated technique of voxel-based magnetic resonance imaging (MRI) analysis was applied to determine the volumes of caudate nucleus and putamen in nine patients with proven ChAc in comparison with 257 healthy controls. At individual subject level, ChAc patients and controls could be reliably discriminated by the volume of the caudate, using a cut-off of 5 ml, or by a value of -3 in terms of z scores. Putaminal volumes were also significantly reduced in ChAc patients, but showed some overlap with controls. The results indicate that this new automated volumetric MRI analysis offers an objective imaging tool for identification of ChAc patients by quantification of basal ganglia atrophy and lends itself to extension to other basal ganglia diseases.