TY - JOUR
T1 - Strength and stability of EEG functional connectivity predict treatment response in infants with epileptic spasms
AU - Shrey, Daniel W.
AU - Kim McManus, Olivia
AU - Rajaraman, Rajsekar
AU - Ombao, Hernando
AU - Hussain, Shaun A.
AU - Lopour, Beth A.
N1 - KAUST Repository Item: Exported on 2021-02-19
Acknowledgements: The authors would like to thank Mary Zupanc, MD, for her mentorship and critical review of the manuscript, as well as Vaibhav Bajaj and Rachel Smith, who contributed preliminary data analysis. This work was supported by a Children’s Hospital of Orange Country (CHOC) PSF Tithe grant and an ICTS CHOC-UC Irvine Collaborative Pilot grant.
PY - 2018/8/4
Y1 - 2018/8/4
N2 - Epileptic spasms (ES) are associated with pathological neuronal networks, which may underlie characteristic EEG patterns such as hypsarrhythmia. Here we evaluate EEG functional connectivity as a quantitative marker of treatment response, in comparison to classic visual EEG features.We retrospectively identified 21 ES patients and 21 healthy controls. EEG data recorded before treatment and after ≥10 days of treatment underwent blinded visual assessment, and functional connectivity was measured using cross-correlation techniques. Short-term treatment response and long-term outcome data were collected.Subjects with ES had stronger, more stable functional networks than controls. After treatment initiation, all responders (defined by cessation of spasms) exhibited decreases in functional connectivity strength, while an increase in connectivity strength occurred only in non-responders. There were six subjects with unusually strong pre-treatment functional connectivity, and all were responders. Visually assessed EEG features were not predictive of treatment response.Changes in network connectivity and stability correlate to treatment response for ES, and high pre-treatment connectivity may predict favorable short-term treatment response. Quantitative measures outperform visual analysis of the EEG.Functional networks may have value as objective markers of treatment response in ES, with potential to facilitate rapid identification of personalized, effective treatments.
AB - Epileptic spasms (ES) are associated with pathological neuronal networks, which may underlie characteristic EEG patterns such as hypsarrhythmia. Here we evaluate EEG functional connectivity as a quantitative marker of treatment response, in comparison to classic visual EEG features.We retrospectively identified 21 ES patients and 21 healthy controls. EEG data recorded before treatment and after ≥10 days of treatment underwent blinded visual assessment, and functional connectivity was measured using cross-correlation techniques. Short-term treatment response and long-term outcome data were collected.Subjects with ES had stronger, more stable functional networks than controls. After treatment initiation, all responders (defined by cessation of spasms) exhibited decreases in functional connectivity strength, while an increase in connectivity strength occurred only in non-responders. There were six subjects with unusually strong pre-treatment functional connectivity, and all were responders. Visually assessed EEG features were not predictive of treatment response.Changes in network connectivity and stability correlate to treatment response for ES, and high pre-treatment connectivity may predict favorable short-term treatment response. Quantitative measures outperform visual analysis of the EEG.Functional networks may have value as objective markers of treatment response in ES, with potential to facilitate rapid identification of personalized, effective treatments.
UR - http://hdl.handle.net/10754/630510
UR - https://www.sciencedirect.com/science/article/pii/S1388245718311787
UR - http://www.scopus.com/inward/record.url?scp=85051410547&partnerID=8YFLogxK
U2 - 10.1016/j.clinph.2018.07.017
DO - 10.1016/j.clinph.2018.07.017
M3 - Article
C2 - 30114662
AN - SCOPUS:85051410547
VL - 129
SP - 2137
EP - 2148
JO - Clinical Neurophysiology
JF - Clinical Neurophysiology
SN - 1388-2457
IS - 10
ER -