Heath R Pardoe1, James H Cole2, Karen Blackmon3, Thomas Thesen3, Ruben Kuzniecky3. 1. Comprehensive Epilepsy Center, Department of Neurology, New York University School of Medicine, 223 East 34th St, New York City, NY 10016, USA. Electronic address: heath.pardoe@nyumc.org. 2. Computational, Clinical, and Cognitive Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, United Kingdom. 3. Comprehensive Epilepsy Center, Department of Neurology, New York University School of Medicine, 223 East 34th St, New York City, NY 10016, USA.
Abstract
OBJECTIVE: We used whole brain T1-weighted MRI to estimate the age of individuals with medically refractory focal epilepsy, and compared with individuals with newly diagnosed focal epilepsy and healthy controls. The difference between neuroanatomical age and chronological age was compared between the three groups. METHODS: Neuroanatomical age was estimated using a machine learning-based method that was trained using structural MRI scans from a large independent healthy control sample (N=2001). The prediction model was then used to estimate age from MRI scans obtained from newly diagnosed focal epilepsy patients (N=42), medically refractory focal epilepsy patients (N=94) and healthy controls (N=74). RESULTS: Individuals with medically refractory epilepsy had a difference between predicted brain age and chronological age that was on average 4.5 years older than healthy controls (p=4.6×10-5). No significant differences were observed in newly diagnosed focal epilepsy. Earlier age of onset was associated with an increased brain age difference in the medically refractory group (p=0.034). SIGNIFICANCE: Medically refractory focal epilepsy is associated with structural brain changes that resemble premature brain aging.
OBJECTIVE: We used whole brain T1-weighted MRI to estimate the age of individuals with medically refractory focal epilepsy, and compared with individuals with newly diagnosed focal epilepsy and healthy controls. The difference between neuroanatomical age and chronological age was compared between the three groups. METHODS: Neuroanatomical age was estimated using a machine learning-based method that was trained using structural MRI scans from a large independent healthy control sample (N=2001). The prediction model was then used to estimate age from MRI scans obtained from newly diagnosed focal epilepsypatients (N=42), medically refractory focal epilepsypatients (N=94) and healthy controls (N=74). RESULTS: Individuals with medically refractory epilepsy had a difference between predicted brain age and chronological age that was on average 4.5 years older than healthy controls (p=4.6×10-5). No significant differences were observed in newly diagnosed focal epilepsy. Earlier age of onset was associated with an increased brain age difference in the medically refractory group (p=0.034). SIGNIFICANCE: Medically refractory focal epilepsy is associated with structural brain changes that resemble premature brain aging.
Authors: Ivan I Kirov; Ruben Kuzniecky; Hoby P Hetherington; Brian J Soher; Matthew S Davitz; James S Babb; Heath R Pardoe; Jullie W Pan; Oded Gonen Journal: Epilepsy Res Date: 2017-12-02 Impact factor: 3.045
Authors: Sarah Gourmaud; Haochang Shou; David J Irwin; Kimberly Sansalone; Leah M Jacobs; Timothy H Lucas; Eric D Marsh; Kathryn A Davis; Frances E Jensen; Delia M Talos Journal: Brain Date: 2020-01-01 Impact factor: 13.501
Authors: Patrick H Luckett; Luigi Maccotta; John J Lee; Ki Yun Park; Nico U F Dosenbach; Beau M Ances; Robert Edward Hogan; Joshua S Shimony; Eric C Leuthardt Journal: Epilepsia Date: 2022-04-01 Impact factor: 6.740
Authors: Jacob Hogan; Haoqi Sun; Luis Paixao; Mike Westmeijer; Pooja Sikka; Jing Jin; Ryan Tesh; Madalena Cardoso; Sydney S Cash; Oluwaseun Akeju; Robert Thomas; M Brandon Westover Journal: Clin Neurophysiol Date: 2020-10-29 Impact factor: 3.708
Authors: Ann-Marie G de Lange; Melis Anatürk; Sana Suri; Tobias Kaufmann; James H Cole; Ludovica Griffanti; Enikő Zsoldos; Daria E A Jensen; Nicola Filippini; Archana Singh-Manoux; Mika Kivimäki; Lars T Westlye; Klaus P Ebmeier Journal: Neuroimage Date: 2020-08-21 Impact factor: 6.556
Authors: Obada Al Zoubi; Chung Ki Wong; Rayus T Kuplicki; Hung-Wen Yeh; Ahmad Mayeli; Hazem Refai; Martin Paulus; Jerzy Bodurka Journal: Front Aging Neurosci Date: 2018-07-02 Impact factor: 5.750