Estimated Disease Progression Trajectory of White Matter Disruption in Unilateral Temporal Lobe Epilepsy: A Data-driven Machine-learning Approach
Abstract number :
2.29
Submission category :
5. Neuro Imaging / 5A. Structural Imaging
Year :
2024
Submission ID :
764
Source :
www.aesnet.org
Presentation date :
12/8/2024 12:00:00 AM
Published date :
Authors :
Presenting Author: Daichi Sone, MD, PhD – Jikei University School of Medicine
Noriko Sato, MD, PhD – National Center of Neurology and Psychiatry
Yoko Shigemoto, MD, PhD – National Center of Neurology and Psychiatry
Iman Beheshti, PhD – University of Manitoba
Yukio Kimura, MD, PhD – National Center of Neurology and Psychiatry
Hiroshi Matsuda, MD, PhD – National Center of Neurology and Psychiatry
Rationale: Although the involvement of progressive brain alterations in epilepsy was recently suggested, individual patients' trajectories of white matter (WM) disruption are not known. We investigated the disease progression patterns of WM damages and their associations with clinical parameters.
Methods: We analyzed cross-sectional diffusion tensor imaging (DTI) data of 155 patients with unilateral temporal lobe epilepsy (TLE) and 270 age/gender-matched healthy controls, and we then calculated the mean fractional anisotropy (FA) values within 20 WM tracts of the whole brain. We used the Subtype and Stage Inference (SuStaIn) algorithm to identify the progression trajectory of FA changes and investigated its relationship with clinical parameters including onset age, disease duration, drug-responsiveness, and the number of anti-seizure medications (ASMs).
Results: The SuStaIn algorithm identified a single subtype model in which the initial damage occurs in the ipsilateral uncinate fasciculus (UF), followed by damage in the forceps, superior longitudinal fasciculus (SLF), and anterior thalamic radiation (ATR). This pattern was replicated when analyzing TLE with hippocampal sclerosis (n=50) and TLE with no lesions (n=105) separately. Further-progressed stages were associated with longer disease duration (p< 0.001) and greater number of ASMs (p=0.001).
Neuro Imaging