MRI in the diagnosis and management of epileptomas.

High-resolution magnetic resonance imaging (MRI) is invaluable for identifying cerebral tumors that cause epilepsy. Serial voxel-based automated quantitative analyses are more sensitive than visual reading for detecting change in a lesion. Eloquent cortex can be identified with functional MRI (fMRI), with cautions about the precise location and extent of critical cortex. Tractography is useful for delineating critical white matter tracks as are MR venography and computerized tomography (CT) angiography for displaying veins and arteries. These data may be combined into a three-dimensional (3D) multimodal MR data presentation and displayed interoperatively to increase the precision and minimize the risk of neurosurgical treatment, and for the illustrations

Seizure outcomes in people with drug-resistant focal epilepsy evaluated for surgery but do not proceed

Objective: To ascertain seizure outcomes in people with drug-resistant focal epilepsy considered for epilepsy surgery but who did not proceed. // Methods: We identified people discussed at a weekly presurgical epilepsy multi-disciplinary (MDT) meeting from January 2015 to December 2019 and in whom a decision not to proceed to surgery was made. Seizure outcomes were obtained from individuals, primary care physicians and attending neurologists at a minimum of 12 months following the not to proceed decision. // Results: We considered 315 people who did not proceed to surgery after evaluation. Nine died, and 25 were lost to follow-up. We included 281 people with a median follow-up of 2.4 (IQR 1.5–4) years. In total, 83 (30%) people reported that seizures had improved or resolved since the MDT meeting. Thirteen (5%) were seizure-free over the last 12 months of follow-up, 70 (25%) had experienced more than 50% reduction in seizure frequency, 180 (64%) had no meaningful change, and 18 (6%) reported a doubling of seizure frequency. Of the 53 (16%) who had vagal nerve stimulation, 19/53 (37%) reported more than 50% reduction in frequency, including one seizure-free. // Significance: The chances of seizure freedom with further medications and neurostimulation are low for people with drug-resistant focal epilepsy who have been evaluated for surgery and do not proceed, but improvement may still occur. Up to a quarter have a > 50% reduction in seizures, and one in twenty become seizure-free eventually. Trying additional anti-seizure medication and neurostimulation is worthwhile in this population

Reasons for not having epilepsy surgery

Objective: This study was undertaken to determine reasons for adults with drug-resistant focal epilepsy who undergo presurgical evaluation not proceeding with surgery, and to identify predictors of this course. // Methods: We retrospectively analyzed data on 617 consecutive individuals evaluated for epilepsy surgery at a tertiary referral center between January 2015 and December 2019. We compared the characteristics of those in whom a decision not to proceed with surgical treatment was made with those who underwent definitive surgery in the same period. Multivariate logistic regression was performed to identify predictors of not proceeding with surgery. // Results: A decision not to proceed with surgery was reached in 315 (51%) of 617 individuals evaluated. Common reasons for this were an inability to localize the epileptogenic zone (n = 104) and the presence of multifocal epilepsy (n = 74). An individual choice not to proceed with intracranial electroencephalography (icEEG; n = 50) or surgery (n = 39), risk of significant deficit (n = 33), declining noninvasive investigation (n = 12), and coexisting neurological comorbidity (n = 3) accounted for the remainder. Compared to 166 surgically treated patients, those who did not proceed to surgery were more likely to have a learning disability (odds ratio [OR] = 2.35, 95% confidence interval [CI] = 1.07‒5.16), normal magnetic resonance imaging (OR = 4.48, 95% CI = 1.68–11.94), extratemporal epilepsy (OR = 2.93, 95% CI = 1.82‒4.71), bilateral seizure onset zones (OR = 3.05, 95% CI = 1.41‒6.61) and to live in more deprived socioeconomic areas (median deprivation decile = 40%–50% vs. 50%–60%, p < .05). // Significance: Approximately half of those evaluated for surgical treatment of drug-resistant focal epilepsy do not proceed to surgery. Early consideration and discussion of the likelihood of surgical suitability or need for icEEG may help direct referral for presurgical evaluation

The impact of epilepsy surgery on the structural connectome and its relation to outcome

BACKGROUND: Temporal lobe surgical resection brings seizure remission in up to 80% of patients, with long-term complete seizure freedom in 41%. However, it is unclear how surgery impacts on the structural white matter network, and how the network changes relate to seizure outcome. METHODS: We used white matter fibre tractography on preoperative diffusion MRI to generate a structural white matter network, and postoperative T1-weighted MRI to retrospectively infer the impact of surgical resection on this network. We then applied graph theory and machine learning to investigate the properties of change between the preoperative and predicted postoperative networks. RESULTS: Temporal lobe surgery had a modest impact on global network efficiency, despite the disruption caused. This was due to alternative shortest paths in the network leading to widespread increases in betweenness centrality post-surgery. Measurements of network change could retrospectively predict seizure outcomes with 79% accuracy and 65% specificity, which is twice as high as the empirical distribution. Fifteen connections which changed due to surgery were identified as useful for prediction of outcome, eight of which connected to the ipsilateral temporal pole. CONCLUSIONS: Our results suggest that the use of network change metrics may have clinical value for predicting seizure outcome. This approach could be used to prospectively predict outcomes given a suggested resection mask using preoperative data only

Seizure pathways change on circadian and slower timescales in individual patients with focal epilepsy.

Personalized medicine requires that treatments adapt to not only the patient but also changing factors within each individual. Although epilepsy is a dynamic disorder characterized by pathological fluctuations in brain state, surprisingly little is known about whether and how seizures vary in the same patient. We quantitatively compared within-patient seizure network evolutions using intracranial electroencephalographic (iEEG) recordings of over 500 seizures from 31 patients with focal epilepsy (mean 16.5 seizures per patient). In all patients, we found variability in seizure paths through the space of possible network dynamics. Seizures with similar pathways tended to occur closer together in time, and a simple model suggested that seizure pathways change on circadian and/or slower timescales in the majority of patients. These temporal relationships occurred independent of whether the patient underwent antiepileptic medication reduction. Our results suggest that various modulatory processes, operating at different timescales, shape within-patient seizure evolutions, leading to variable seizure pathways that may require tailored treatment approaches

MONDO: Scalable Modelling and Model Management on the Cloud

International audienceAchieving scalability in modelling and MDE involves being able to construct large models and domain-specific languages in a systematic manner, enabling teams of modellers to construct and refine large models in collaboration, advancing the state of the art in model querying and transformations tools so that they can cope with large models (of the scale of millions of model elements), and providing an infrastructure for efficient storage, indexing and retrieval of large models. This paper outlines how MONDO, a collaborative EC-funded project, contributes to tackling some of these scalability-related challenges

Identifying epileptogenic abnormality by decomposing intracranial EEG and MEG power spectra

Identifying abnormal electroencephalographic activity is crucial in diagnosis and treatment of epilepsy. Recent studies showed that decomposing brain activity into periodic (oscillatory) and aperiodic (trend across all frequencies) components may illuminate drivers of changes in spectral activity. Using iEEG data from 234 subjects, we constructed a normative map and compared this with a separate cohort of 63 patients with refractory focal epilepsy being considered for neurosurgery. The normative map was computed using three approaches: (i) relative complete band power, (ii) relative band power with the aperiodic component removed (iii) the aperiodic exponent. Corresponding abnormalities were also calculated for each approach in the separate patient cohort. We investigated the spatial profiles of the three approaches, assessed their localizing ability, and replicated our findings in a separate modality using MEG. The normative maps of relative complete band power and relative periodic band power had similar spatial profiles. In the aperiodic normative map, exponent values were highest in the temporal lobe. Abnormality estimated through the complete band power robustly distinguished between good and bad outcome patients. Neither periodic band power nor aperiodic exponent abnormalities distinguished seizure outcome groups. Combining periodic and aperiodic abnormalities improved performance, similar to the complete band power approach. Our findings suggest that sparing cerebral tissue that generates abnormalities in either periodic or aperiodic activity may lead to a poor surgical outcome. Both periodic and aperiodic abnormalities are necessary to distinguish patient outcomes, with neither sufficient in isolation. Future studies could investigate whether periodic or aperiodic abnormalities are affected by the cerebral location or pathology

A research roadmap towards achieving scalability in model driven engineering

International audienceAs Model-Driven Engineering (MDE) is increasingly applied to larger and more complex systems, the current generation of modelling and model management technologies are being pushed to their limits in terms of capacity and eciency. Additional research and development is imperative in order to enable MDE to remain relevant with industrial practice and to continue delivering its widely recognised productivity , quality, and maintainability benefits. Achieving scalabil-ity in modelling and MDE involves being able to construct large models and domain-specific languages in a systematic manner, enabling teams of modellers to construct and refine large models in a collaborative manner, advancing the state of the art in model querying and transformations tools so that they can cope with large models (of the scale of millions of model elements), and providing an infrastructure for ecient storage, indexing and retrieval of large models. This paper attempts to provide a research roadmap for these aspects of scalability in MDE and outline directions for work in this emerging research area