Abstracts

Brain Volume Increases Accompany Reductions in Psychogenic Non-epileptic Seizures After Neurobehavioral Therapy

Abstract number : 3.232
Submission category : 5. Neuro Imaging / 5A. Structural Imaging
Year : 2023
Submission ID : 1035
Source : www.aesnet.org
Presentation date : 12/4/2023 12:00:00 AM
Published date :

Authors :
Presenting Author: Ayushe Sharma, PhD – UAB

Adam Goodman, PhD – UAB; Jane Allendorfer, PhD – UAB; W. Curt LaFrance, MD – Brown University; Jerzy Szaflarski, MD, PhD – UAB

Rationale:
Although the etiology of psychogenic nonepileptic seizures (PNES) is still being elucidated, a growing body of neuroimaging evidence suggests that PNES may derive from widespread structural and functional abnormalities. However, no study has investigated whether such abnormalities change after intervention. Among the limited treatments available, neurobehavioral therapy (NBT) has demonstrated effectiveness in a randomized controlled trial, yet its underlying neurobiological mechanisms remain unexplored. Here, we conducted a longitudinal imaging study on PNES patients with prior traumatic brain injury (TBI-PNES) who received NBT, and compared their data to TBI-only and healthy control participants (HCs) scanned twice without intervention.



Methods:
Adults diagnosed with TBI-PNES (N=50), TBI-only (N=50), or HCs (N=33) underwent magnetic resonance imaging (MRI) at 3-Tesla. TBI-PNES were scanned before and after 12 weeks of NBT. TBI-only and HCs were scanned twice, 12 weeks apart. High-resolution T1-weighted structural images were collected using the following magnetization-prepared rapid acquisition with gradient echo sequence parameters: repetition time = 2400 ms, echo time = 2.22 ms, field of view = 24.0 × 25.6 × 16.7 cm, matrix = 256 × 256 mm2, flip angle = 8°, slice thickness = 0.8 mm, isotropic voxels. 

Structural MRI data were analyzed by voxel- and surface-based morphometry using the Computational Anatomy Toolbox 12 (CAT12) in Statistical Parametric Mapping running in MatLab R2020b. The multivariate and repeated measures (MRM) toolbox running in Matlab 2020b was used to compute a repeated measures analysis of variance (rmANOVA) to test changes in gray matter volume (GMV)< between groups over time, with statistical significance at p< 0.05 corrected for multiple comparisons using family-wise error (FWE). 
Neuro Imaging