de Tisi, J. | bioRxiv Science

bioRxiv2023

Patterns of subregional cerebellar atrophy across epilepsy syndromes: An ENIGMA-Epilepsy study

ObjectiveThe intricate neuroanatomical structure of the cerebellum is of longstanding interest in epilepsy, but has been poorly characterized within the current cortico-centric models of this disease. We quantified cross-sectional regional cerebellar lobule volumes using structural MRI in 1,602 adults with epilepsy and 1,022 healthy controls across twenty-two sites from the global ENIGMA-Epilepsy working group. MethodsA state-of-the-art deep learning-based approach was employed that parcellates the cerebellum into 28 neuroanatomical subregions. Linear mixed models compared total and regional cerebellar volume in i) all epilepsies; ii) temporal lobe epilepsy with hippocampal sclerosis (TLE-HS); iii) non-lesional temporal lobe epilepsy (TLE-NL); iv) genetic generalised epilepsy; and (v) extra-temporal focal epilepsy (ETLE). Relationships were examined for cerebellar volume versus age at seizure onset, duration of epilepsy, phenytoin treatment, and cerebral cortical thickness. ResultsAcross all epilepsies, reduced total cerebellar volume was observed (d=0.42). Maximum volume loss was observed in the corpus medullare (dmax=0.49) and posterior lobe grey matter regions, including bilateral lobules VIIB (dmax= 0.47), Crus I/II (dmax= 0.39), VIIIA (dmax=0.45) and VIIIB (dmax=0.40). Earlier age at seizure onset ({eta}{rho}2max=0.05) and longer epilepsy duration ({eta}{rho}2max=0.06) correlated with reduced volume in these regions. Findings were most pronounced in TLE-HS and ETLE with distinct neuroanatomical profiles observed in the posterior lobe. Phenytoin treatment was associated with reduced posterior lobe volume. Cerebellum volume correlated with cerebral cortical thinning more strongly in the epilepsy cohort than in controls. SignificanceWe provide robust evidence of deep cerebellar and posterior lobe subregional grey matter volume loss in patients with chronic epilepsy. Volume loss was maximal for posterior subregions implicated in non-motor functions, relative to motor regions of both the anterior and posterior lobe. Associations between cerebral and cerebellar changes, and variability of neuroanatomical profiles across epilepsy syndromes argue for more precise incorporation of cerebellum subregions into neurobiological models of epilepsy. Key pointsO_LICerebellar involvement in epilepsy is poorly understood within current cortico-centric models of this disease C_LIO_LIWe used a novel, deep learning segmentation tool to parcellate the cerebellum into 28 anatomical subunits using an international MRI dataset of 1,602 individuals with epilepsy (aged between 18 and 65 years old) including temporal lobe epilepsy with hippocampal sclerosis (TLE-HS, n=562), TLE non-lesional (TLE-NL, n=284), generalised genetic epilepsy (GGE, n=186) and extra temporal focal epilepsy (ETLE, n=251) and 1,022 controls. C_LIO_LIAcross all epilepsies (vs. controls) robust changes in the corpus medullare and posterior lobe "non-motor" regions were observed, with maximal differences in bilateral VIIB and Crus II lobules. Lower volume of these regions correlated with longer disease duration. Anterior "motor lobe" regions were relatively spared. C_LIO_LIFindings were most pronounced in TLE-HS and ETLE groups, with distinct neuroanatomical profiles observed. C_LIO_LICortical thinning was associated with pronounced cerebellar volume loss in TLE-HS epilepsy, relative to controls. C_LI ETHICAL PUBLICATION STATEMENTWe confirm that we have read the Journals position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.

neuroscience↗

bioRxiv2019

Node abnormality predicts seizure outcome and relates to long-term relapse after epilepsy surgery

ObjectiveWe assessed pre-operative structural brain networks and clinical characteristics of patients with drug resistant temporal lobe epilepsy (TLE) to identify correlates of post-surgical seizure outcome at 1 year and seizure relapses up to 5 years.\n\nMethodsWe retrospectively examined data from 51 TLE patients who underwent anterior temporal lobe resection (ATLR) and 29 healthy controls. For each patient, using the pre-operative structural, diffusion, and post-operative structural MRI, we generated two networks: pre-surgery network and surgically-spared network. The pre-surgery network is the whole-brain network before surgery and the surgically-spared network is a subnetwork of the pre-surgery network which is expected to remain unaffected by surgery and hence present post-operatively. Standardising these networks with respect to controls, we determined the number of abnormal nodes before surgery and expected to remain after surgery. We incorporated these 2 abnormality measures and 13 commonly acquired clinical data from each patient in a robust machine learning framework to estimate patient-specific chances of seizures persisting after surgery.\n\nResultsPatients with more abnormal nodes had lower chance of seizure freedom at 1 year and even if seizure free at 1 year, were more likely to relapse within five years. In the surgically-spared networks of poor outcome patients, the number of abnormal nodes was greater and their locations more widespread than in good outcome patients. We achieved 0.84 {+/-} 0.06 AUC and 0.89 {+/-} 0.09 specificity in detecting unsuccessful seizure outcomes at 1-year. Moreover, the model-predicted likelihood of seizure relapse was significantly correlated with the grade of surgical outcome at year-one and associated with relapses up-to five years post-surgery.\n\nConclusionNode abnormality offers a personalised non-invasive marker, that can be combined with clinical data, to better estimate the chances of seizure freedom at 1 year, and subsequent relapse up to 5 years after ATLR.

neuroscience↗

bioRxiv2019

Slow changes in seizure pathways in individual patients with focal epilepsy

Personalised medicine requires that treatments adapt to not only the patient, but changing factors within each individual. Although epilepsy is a dynamic disorder that is characterised 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 dynamics using intracranial recordings of over 500 seizures from 31 patients with focal epilepsy (mean 16.5 seizures/patient). In all patients, we found variability in seizure paths through the space of possible network dynamics, producing either a spectrum or clusters of different 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 dynamics, leading to variable seizure pathways that may require tailored treatment approaches.

neuroscience↗