Resting State Functional MRI Based Connectivity Analysis in Infantile Epileptic Spasms Syndrome
Abstract number :
1.215
Submission category :
2. Translational Research / 2C. Biomarkers
Year :
2024
Submission ID :
1296
Source :
www.aesnet.org
Presentation date :
12/7/2024 12:00:00 AM
Published date :
Authors :
Presenting Author: Priyanka Madaan, MD, DM – Amrita Institute of Medical Sciences, Faridabad
Deepti Bathula, BE, PhD – Indian Institute of Technology, Ropar
Pooja Dhir, Phd – PGIMER, Chandigarh
Sandeep Negi, Phd – PGIMER, Chandigarh
Naveen Sankhyan, MD, DM – PGIMER, Chandigarh
Sameer Vyas, MD, DM – PGIMER, Chandigarh
Jitendra Sahu, MD, DM – PGIMER, Chandigarh
Rationale: This study aims to evaluate functional connectivity (FC) analysis using resting-state fMRI in infantile epileptic spasms syndrome (IESS). Functional connectivity and the underlying neural networks for hormonal therapy responders and vigabatrin responders with IESS might be different. The pre-treatment identification of these neural underpinnings in IESS can help identify the best initial treatment for a particular patient, thereby reducing the cost of therapy and risk of drug toxicity.
Methods: This prospective pilot work was done at PGIMER, Chandigarh over three years after ethical clearance (IEC-09/2018-1015). After informed consent, the enrolled treatment-naïve children with IESS (with ongoing epileptic spasms) underwent resting-state functional MRI (fMRI) under triclofos sedation within 7days of standard therapy initiation (adrenocorticotrophic hormone, prednisolone, or vigabatrin) and were followed for 2years. fMRIs were preprocessed with fMRIPrep. Using an automated anatomical labeling (AAL) template, FC analysis was done for 90 regions of interest (ROIs) calculating Pearson’s correlation coefficients between every pair of ROIs. Network parameters were compared between two conditions using a two-tailed two-sample t-test (p< 0.05).
Translational Research