Tracking Epilepsy-related Gray Matter Atrophy Across the Lifespan: An ENIGMA Study
Abstract number :
1.249
Submission category :
5. Neuro Imaging / 5A. Structural Imaging
Year :
2022
Submission ID :
2204307
Source :
www.aesnet.org
Presentation date :
12/3/2022 12:00:00 PM
Published date :
Nov 22, 2022, 05:24 AM
Authors :
Judy Chen, BHSc – McGill University; Alexander Ngo, BSc – McGIll University; Sara Lariviere, MSc – McGill University; Raul Rodriguez-Cruces, MBBS PhD – McGill University; Reinder Vos de Wael, PhD – McGill University; Nuria Bargallo, MD PhD – Hospital Clínic de Barcelona; Patricia Desmond, MD – University of Melbourne; Orrin Devinsky, MD – New York University; John Duncan, MD – University College London; Renzo Guerrini, MD FRCP FAES – Children's Hospital A. Meyer-University of Florence; Graeme Jackson, MBBS PhD – The Florey; Barbara Kreilkamp, PhD – University Medicine Goettingen; Patrick Kwan, MD PhD – University of Melbourne; Angelo Labate, PhD – University of Messina; Elaine Lui, MD – The Royal Melbourne Hospital; Galovic Marian, MD PhD – University of Zurich; Terence O'Brien, MBBS MD – Monash University; Mark Richardson, BMBCh, PhD, FRCP – King's College London; Lucas Saba, PhD – Università di Cagliari; Pasquale Striano, MD PhD – University of Genova; Rhys Thomas, MD – Newcastle University; Vijay Tiwari, PhD – Queen's University Belfast; Gavin Winston, MD – Queens University; ENIGMA Epilepsy, N/A – ENIGMA-Epilepsy Group; Paul Thompson, PhD – University of Southern California; Sophia Thomopoulos, PhD – University of Southern California; Sanjay Sisodiya, MD PhD – University College London; Carrie McDonald, PhD – University of California San Diego; Lorenzo Caciagli, MD PhD – University of Pennsylvania; Andrea Bernasconi, MD – McGill University; Neda Ladbon-Bernasconi, MD PhD – McGill University; Boris Bernhardt, PhD – McGill University
This abstract is a recipient of the Young Investigator Award
Rationale: Magnetic resonance imaging (MRI) analysis can measure brain atrophy in temporal lobe epilepsy (TLE) and idiopathic generalized epilepsy (IGE).1 Research has mainly focused on linear effects of aging.2,3 We capitalized on categorical and age-window analytics to probe the association between ageing and brain atrophy in the common epilepsies.4 _x000D_
Methods: Participants: As part of ENIGMA-Epilepsy, we analyzed T1w MRI data in 885 healthy individuals (378 male; mean±SD age: 36.0±11.7 years), 769 TLE (314 males; mean±SD: 38.2±11.1 years; 430 left-sided focus) and 113 IGE patients (39 males; mean±SD 31.5±9.7 years)._x000D_
_x000D_
Young and old differences: Participants were divided into young and old cohorts via median age (35 years). Cortical thickness (CT; measured across 68 brain regions) and subcortical volume (SV; measured across 12 subcortical regions and bilateral hippocampi and ventricles) in TLE and IGE patients were compared to controls across both cohorts, while controlling for site, age, and sex. Findings were corrected for multiple comparisons at a false discovery rate (FDR) of p< 0.05._x000D_
_x000D_
Sliding age-window analysis: Using a window range of ± 2 years from the age of interest, yielding a total of five unique ages, the mean values for CT and SV regions were calculated for each age. For example, age of interest of 19 will yield a window from 17 to 21 totalling five unique ages, and the mean CT and SV values for each unique age would be calculated. These mean values were then multiplied by normally distributed weights to yield a weighted average for each brain region. This was repeated for every age of interest sliding across from 19 to 71 years of age for TLE patients, and 19 to 55 years of age for IGE patients._x000D_
Neuro Imaging