Staging and Subtyping Disease Evolution in Temporal Lobe Epilepsy
Abstract number :
1.248
Submission category :
5. Neuro Imaging / 5A. Structural Imaging
Year :
2022
Submission ID :
2204249
Source :
www.aesnet.org
Presentation date :
12/3/2022 12:00:00 PM
Published date :
Nov 22, 2022, 05:24 AM
Authors :
Hyo Lee, MSE – Montreal Neurological Institute and Hospital, McGill University; Benoit Caldairou, PhD – Montreal Neurological Institute and Hospital, McGill University; Boris Bernhardt, PhD – Montreal Neurological Institute and Hospital, McGill University; Andrea Bernasconi, MD – Montreal Neurological Institute and Hospital, McGill University; Neda Ladbon-Bernasconi, MD, PhD – Montreal Neurological Institute and Hospital, McGill University
This abstract has been invited to present during the Neuroimaging platform session
Rationale: While ample evidence suggests that drug-resistant temporal lobe epilepsy (TLE) follows a progressive course impacting brain structure and cognitive function,1,2 previous studies have assumed a steady evolution. In addition, by using a group-based design, they largely neglected phenotypic diversity across patients. Novel analytical event-based models estimate distinct stages that capture dynamic patterns of disease evolution from cross-sectional data, which circumvents logistical and financial burdens of a longitudinal design. Here, we applied Subtype and Stage Inference (SuStaIn),3 a computational technique that extends event-based model for simultaneous subtyping and staging.
Methods: Subjects: 82 TLE patients (30 males, 35±10 yrs; 41 MRI-positive and 41 MRI-negative) and 41 healthy controls (18 males, 32±8 yrs) scanned at 3T using T1-weighted, FLAIR and diffusion MRI. Among the 57 who underwent surgery, 43 (75%) were seizure free, 37 (65%) had hippocampal sclerosis and 20 (35%) isolated gliosis.
Feature extraction: We generated surfaces running through the cortical mantle, 2 mm below its boundary and the central paths of hippocampal subfields on which we sampled cortical thickness and hippocampal volume (to model atrophy) and subcortical/hippocampal MD (microstructural damage). Analysis. SuStaIn estimated disease trajectory subtypes and stages by fitting a multi-component piece-wise linear z-score model of progression. Effects of normal aging in healthy controls were subtracted from patients.
Results: SuStaIn identified three disease trajectory subtypes (Figure 1A): (S1) Ipsilateral hippocampal atrophy and gliosis, followed by WM damage; (S2) Bilateral neocortical atrophy, followed by ipsilateral hippocampal atrophy and gliosis; (S3) Bilateral limbic WM damage, followed by bilateral hippocampal gliosis. Patients showed high assignability to their subtypes and stages (Figure 1B). S1 had the highest proportions of patients with early disease onset, febrile convulsions, drug-resistance, a positive MRI, HS and Engel-I outcome, whereas S3 and S2 exhibited the lowest and intermediate proportions, respectively (Table 1).
Conclusions: Disease evolution in TLE follows variable trajectories, each associated with distinct patterns of cortico-subcortical and hippocampal structural alterations. Capturing the progression of subtype-specific MRI biomarkers enables an objective, fine-grained patient stratification, which may identify individuals at risk and help monitoring the effectiveness of potential preventive therapies._x000D_
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References:
1. Caciagli L, et al. Neurology. 2017
2. Marques CM, et al. Epilepsy &and Behavior. 2007
3. Young AL, et al. Nature Comm. 2018
Funding: This work was supported by the Canadian Institutes of Health Research to A.B. and N.B. (CIHR, MOP-57840 and 123520), Epilepsy Canada (Jay and Aiden Barker Breakthrough Grant in Clinical and Basic Sciences to A.B.), Brain Canada and Savoy Foundation for Epilepsy (H.M.L.). B.B. acknowledges research support from the NSERC (Discovery-1304413), the Canadian Institutes of Health Research (CIHR FDN-154298), SickKids Foundation (NI17-039), Azrieli Center for Autism Research (ACAR-TACC), FRQS and the Tier-2 Canada Research Chairs program.
Neuro Imaging