Interpretable surface-based detection of focal cortical dysplasias:a Multi-centre Epilepsy Lesion Detection study

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy

Cingulate gyrus epilepsy

The cingulate gyrus is located above the corpus callosum and forms part of the limbic system. Cingulate gyrus epilepsy poses a diagnostic challenge, given its diverse and variable seizure semiology. We present two patients with seizures arising in the cingulate gyrus that highlight the electroclinical and imaging features of this rare form of epilepsy. Cingulate seizures can give a wide range of clinical manifestations, which relate to the underlying neuroanatomy and subdivisions of the cingulate cortex. Here, we review the semiology of cingulate epilepsy and how this relates to the location of seizure onset and patterns of propagation

Short-lasting retroorbital pain attacks as a form of ictal epileptic headache: case report

© International Headache Society 2019Background and objectives: Ictal epileptic headache is a rare form of painful seizure, habitually consisting of migrainous or tension-type headache. We describe a case of a patient with short-lasting, severe retroorbital pain attacks caused by frontal lobe epilepsy. Case report: A 25-year-old male patient presented with recurrent attacks of paroxysmal, short-lasting, excruciating left periorbital and facial pain mainly occurring from sleep. After intracranial EEG exploration and resection of a right prefrontal focal cortical dysplasia, long-term seizure and headache remission was obtained. Discussion: Our case extends the clinical and neuroanatomical spectrum of ictal epileptic headache and suggests that long-term remission can be obtained by resective epilepsy surgery. It also reinforces the role of the prefrontal cortex in the pain matrix and pain generation. Conclusion: Despite its rarity, ictal epileptic headache should be suspected in selected patients, particularly those with other ictal symptoms and signs, history of epileptic seizures, or neuroimaging abnormalities.info:eu-repo/semantics/publishedVersio

Quantitative EEG as a Prognostic Tool in Suspected Anti-N-Methyl-D-Aspartate Receptor Antibody Encephalitis

PURPOSE: Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis is a form of autoimmune encephalitis associated with EEG abnormalities. In view of the potentially severe outcomes, there is a need to develop prognostic tools to inform clinical management. The authors explored whether quantitative EEG was able to predict outcomes in patients with suspected anti-NMDAR encephalitis. METHODS: A retrospective, observational study was conducted of patients admitted to a tertiary clinical neuroscience center with suspected anti-NMDAR encephalitis. Peak power and peak frequency within delta (<4 Hz), theta (4-8 Hz), alpha (8 - 13 Hz), and beta (13-30 Hz) frequency bands were calculated for the first clinical EEG recording. Outcome was based on the modified Rankin Scale (mRS) score at 1 year after hospital discharge. Binomial logistic regression using backward elimination was performed with peak frequency and power, anti-NMDAR Encephalitis One-Year Functional Status score, age, and interval from symptom onset to EEG entered as predictors. RESULTS: Twenty patients were included (mean age 48.6 years, 70% female), of which 7 (35%) had a poor clinical outcome (mRS 2-6) at 1 year. There was no association between reported EEG abnormalities and outcome. The final logistic regression model was significant (χ2(1) = 6.35, P < 0.012) with peak frequency in the delta range (<4 Hz) the only retained predictor. The model explained 38% of the variance (Nagelkerke R2) and correctly classified 85% of cases. Higher peak frequency in the delta range was significantly associated (P = 0.04) with an increased likelihood of poor outcome. CONCLUSIONS: In this exploratory study, it was found that quantitative EEG on routinely collected EEG recordings in patients with suspected anti-NMDAR encephalitis was feasible. A higher peak frequency within the delta range was associated with poorer clinical outcome and may indicate anti-NMDAR-mediated synaptic dysfunction. Quantitative EEG may have clinical utility in predicting outcomes in patients with suspected NMDAR antibody encephalitis, thereby serving as a useful adjunct to qualitative EEG assessment; however, given the small sample size, replication in a larger scale is indicated

Preoperative estimation of seizure control after resective surgery for the treatment of epilepsy

AbstractPurposePredicting seizure control after epilepsy surgery is difficult. The objectives of this work are: (a) to estimate the value of surgical procedure, presence of neuroimaging abnormalities, need for intracranial recordings, resection lobe, pathology, durations of epilepsy and follow-up period to predict postsurgical seizure control after epilepsy surgery and (b) to provide empirical estimates of successful outcome after different combinations of the above factors in order to aid clinicians in advising patients presurgically about the likelihood of success under their patients’ individual circumstances.MethodsWe report postsurgical seizure control from all 243 patients who underwent resective surgery for epilepsy at King's College Hospital between 1999 and 2011. Among the 243 patients, 233 had lobar or sub-lobar resections, 8 had multilobar resections and 2 had excision of a hypothalamic hamartoma. We examined the relation between postsurgical seizure control and type of surgical procedure, presence of neuroimaging abnormalities, pathology, resection lobe and the need of intra-cranial electrodes to identify seizure onset.ResultsAmong the 243 patients, 126 (52%) enjoyed outcome grade I, 40 (16%) had grade II, 51 (21%) had grade III and 26 (11%) had grade IV (mean follow-up 41.1 months). Normal neuroimaging or need for intracranial recordings was not associated with poorer outcome. Patients undergoing temporal resections showed better outcome than those with frontal resections, due to the poor outcome seen in frontal patients with normal neuroimaging. Among temporal resections, there was no difference in outcome between patients with and without neuroimaging abnormalities. Among patients with lesions on imaging, temporal and frontal resections showed similar outcomes. Likelihood of favourable outcome under the patient's individual circumstances was estimated by the tables provided. There was an 8–9% decrease in the percentage of grade I between follow-up at 12 and >36 months.ConclusionOverall, nearly 70% of patients undergoing resective surgery enjoy favourable post-surgical seizure control. Normal neuroimaging should not discourage surgery in temporal patients but is a negative prognostic sign in normal MRI frontal patients. There were no statistical differences in outcome between patients with neuroimaging lesions in frontal or temporal lobes