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Importance: Many individuals with drug-resistant epilepsy continue to have seizures after resective surgery. Accurate identification of focal brain abnormalities is essential for successful neurosurgical intervention. Current clinical approaches to identify structural abnormalities for surgical targeting in epilepsy do not use diffusion-weighted MRI (dMRI), despite evidence that dMRI abnormalities are present in epilepsy and may relate to the epileptogenic zone. Objective: To investigate whether surgical resection of diffusion abnormalities relates to post-operative seizure freedom. Design: This retrospective case-control study was conducted between 2009 and 2022. Data were acquired at the National Hospital for Neurology and Neurosurgery, UK. Study participants included 200 individuals with drug-resistant focal epilepsy, who underwent resective surgery, and 97 healthy controls used as a normative baseline. Main Outcomes: Spatial overlap between diffusion abnormality clusters and surgical resection masks, and relation to post-surgical outcome. Results: Surgical resections overlapping with the largest abnormal cluster significantly correlated with sustained seizure freedom at 12 months (83% vs 55%; p<0.0001) and over five years (p<0.0001). Notably, resecting only a small proportion of the largest cluster was associated with better seizure outcomes than cases with no resection of this cluster (p=0.008). Furthermore, sparing the largest cluster but resecting other large clusters still improved seizure freedom rates compared to no overlap (p=0.03). Conclusions: Our results suggest that abnormal clusters, identified using dMRI, are integral to the epileptogenic network, and even a partial removal of such an abnormal cluster is sufficient to achieve seizure freedom. The study highlights the potential of incorporating dMRI into pre-surgical planning to improve outcomes in focal epilepsy.

Status epilepticus (SE) carries risks of morbidity and mortality. Experimental studies have implicated the entorhinal cortex in prolonged seizures; however, studies in large human cohorts are limited. We hypothesised that individuals with temporal lobe epilepsy (TLE) and a history of SE would have more severe entorhinal atrophy compared to others with TLE and no history of SE. 357 individuals with drug resistant temporal lobe epilepsy (TLE) and 100 healthy controls were scanned on a 3T MRI. For all subjects the cortex was segmented, parcellated, and the thickness calculated from the T1-weighted anatomical scan. Subcortical volumes were derived similarly. Cohen's d and Wilcoxon rank-sum tests respectively were used to capture effect sizes and significance. Individuals with TLE and SE had reduced entorhinal thickness compared to those with TLE and no history of SE. The entorhinal cortex was more atrophic ipsilaterally (d=0.51, p<0.001) than contralaterally (d=0.37, p=0.01). Reductions in ipsilateral entorhinal thickness were present in both left TLE (n=22:176, d=0.78, p<0.001), and right TLE (n=19:140, d=0.31, p=0.04), albeit with a smaller effect size in right TLE. Several other regions exhibited atrophy in individuals with TLE, but these did not relate to a history of SE. These findings suggest potential involvement or susceptibility of the entorhinal cortex in prolonged seizures.

Magnetic resonance imaging (MRI) is a crucial tool to identify brain abnormalities in a wide range of neurological disorders. In focal epilepsy MRI is used to identify structural cerebral abnormalities. For covert lesions, machine learning and artificial intelligence algorithms may improve lesion detection if abnormalities are not evident on visual inspection. The success of this approach depends on the volume and quality of training data. Herein, we release an open-source dataset of preprocessed MRI scans from 442 individuals with drug-refractory focal epilepsy who had neurosurgical resections, and detailed demographic information. The MRI scan data includes the preoperative 3D T1 and where available 3D FLAIR, as well as a manually inspected complete surface reconstruction and volumetric parcellations. Demographic information includes age, sex, age of onset of epilepsy, location of surgery, histopathology of resected specimen, occurrence and frequency of focal seizures with and without impairment of awareness, focal to bilateral tonic-clonic seizures, number of anti-seizure medications (ASMs) at time of surgery, and a total of 1764 patient years of post-surgical follow up. Crucially, we also include resection masks delineated from post-surgical imaging. To demonstrate the veracity of our data, we successfully replicated previous studies showing long-term outcomes of seizure freedom in the range of around 50%. Our imaging data replicates findings of group level atrophy in patients compared to controls. Resection locations in the cohort were predominantly in the temporal and frontal lobes. We envisage our dataset, shared openly with the community, will catalyse the development and application of computational methods in clinical neurology.

Background: Understanding healthy human brain function is crucial to identify and map pathological tissue within it. Whilst previous studies have mapped intracranial EEG (icEEG) from non-epileptogenic brain regions, these maps do not consider the effects of age and sex. Further, most existing work on icEEG has often suffered from a small sample size due to the modality's invasive nature. Here, we substantially increase the subject sample size compared to existing literature, to create a multi-centre, normative map of brain activity which additionally considers the effects of age, sex and recording hospital. Methods: Using interictal icEEG recordings from n = 502 subjects originating from 15 centres, we constructed a normative map of non-pathological brain activity by regressing age and sex on relative band power in five frequency bands, whilst accounting for the hospital effect. Results: Recording hospital significantly impacted normative icEEG maps in all frequency bands, and age was a more influential predictor of band power than sex. The age effect varied by frequency band, but no spatial patterns were observed at the region-specific level. Certainty about regression coefficients was also frequency band specific and moderately impacted by sample size. Conclusion: The concept of a normative map is well-established in neuroscience research and particularly relevant to the icEEG modality, which does not allow healthy control baselines. Our key results regarding the hospital site and age effect guide future work utilising normative maps in icEEG.

Delineation of seizure onset regions from EEG is important for effective surgical workup. However, it is unknown if their complete resection is required for seizure freedom, or in other words, if post-surgical seizure recurrence is due to incomplete removal of the seizure onset regions. Retrospective analysis of icEEG recordings from 63 subjects (735 seizures) identified seizure onset regions through visual inspection and algorithmic delineation. We analysed resection of onset regions and correlated this with post-surgical seizure control. Most subjects had over half of onset regions resected (70.7% and 60.5% of subjects for visual and algorithmic methods, respectively). In investigating spatial extent of onset or resection, and presence of diffuse onsets, we found no substantial evidence of association with post-surgical seizure control (all AUC<0.7, p>0.05). Seizure onset regions tends to be at least partially resected, however a less complete resection is not associated with worse post-surgical outcome. We conclude that seizure recurrence after epilepsy surgery is not necessarily a result of failing to completely resect the seizure onset zone, as defined by icEEG. Other network mechanisms must be involved, which are not limited to seizure onset regions alone.