Authors :
Presenting Author: Fernando Cendes, MD, PhD – University of Campinas - UNICAMP
Benjamin Sinclair, Postdoctoral Research Fellow – Department of Neuroscience, Central Clinical School – Monash University; Amanda Santos, MD – Epilepsy Fellow, Neurology, University of Campinas - UNICAMP; Rafael João, MD – Epilepsy Fellow, Neurology, University of Campinas - UNICAMP; Lenise Valler, MD – PhD Student, Neurology, University of Campinas - UNICAMP; Brunno De Campos, PhD – Research Assistant, Neurology, University of Campinas - UNICAMP; Lucas Scardua, MD – Researcher, Neurology, University of Campinas - UNICAMP; Marina Alvim, MD, PhD – Neurologist Assistant, Neurology, University of Campinas - UNICAMP; Nishant Mishra, MD – Neurology – Yale University; Guernot Hlauschek, MD – Oslo University Hospital National Centre for Epilepsy; John-Paul Nicolo, MD – Neurology – Monash University; Meng Law, MD – Radiology – Monash University; Patrick Kwan, MD, PhD – Professor, Neurology, Monash University; Fernando Cendes, MD, PhD – Professor, Neurology, University of Campinas - UNICAMP
Rationale:
Although seizures occur in approximately ten percent of patients after stroke, the pathophysiology of post-stroke epilepsy (PSE) is still unclear. In this preliminary analysis, we aimed to investigate patterns of grey matter atrophy (GMA) in individuals with PSE compared to subjects with stroke without epilepsy (PS-without-Epilepsy) and healthy controls using Voxel-Based Morphometry (VBM).Methods:
We compared 26 PSE patients (12 women, median age of 61.5 years), 30 PS-without-Epilepsy patients (13 women; median of 62 years), and 30 healthy controls (19 women, median age of 61 years). We flipped the MRIs with right-sided stroke lesions to increase the statistical power. We combined CAT12 and lesion_gnb toolboxes running on SPM12/Matlab2019 to segment the 3T 3D-T1 MRI scans into grey and white matter maps. The lesion_gnb allowed us to create individual masks for stroke lesions which were combined and used to exclude the lesioned areas from statistical analyses. We used the full-factorial design from CAT12/SPM12 (including sex, age, and intracranial volume as covariates) for statistical analyses to investigate patterns of GMA between patients and controls, including region-of-interest analysis (with Holm-Bonferroni correction). Clinical data were analyzed with SPSS23.Results:
Patients and controls were balanced for age (p=0.96), sex (p=0.25), diagnosis of diabetes (p=0.1), atrial fibrillation (p=1) and dyslipidemia (p=0.7). However, hypertension was more frequent in patients (p=0.04). Although PSE and PS-without-Epilepsy groups were well-adjusted for most of the risk factors, dyslipidemia was less frequent in PSE (62%) compared to the PS-without-Epilepsy group (90%) (p=0.03). PSE and PS-without-Epilepsy groups were balanced in terms of NIHSS-scale (at stroke admission, p=0.7), use of thrombolytic therapy (p=0.9); type of stroke (cortical, subcortical or both, p=0.14), side of stroke (left, right or bilateral, p=0.18) and the interval between acute stroke and MRI acquisition (p=0.17). Late-onset Seizures occurred in 80%, with a median interval of 88 days after stroke (range 0-2833 days).
In Figure 1, we show the statistical maps of GMA resultant from the comparisons between each group and the controls. The PSE group showed a more widespread GMA pattern than the PS-without-Epilepsy group (Figure 1). While both groups exhibited atrophy in basal ganglia (including putamen and caudate), we identified limbic atrophy in the PSE involving bilateral hippocampi (p< 0.03) and ipsilateral cingulum (p< 0.001). Other areas of bilateral GMA were observed in the PSE group.