A multimodal epilepsy dataset of paired 3-Tesla and 7-Tesla MRI and intracranial EEG.
Authors
Affiliations (7)
Affiliations (7)
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
- Department of Biostatistics, Epidemiology and Informatics, Philadelphia, USA.
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA. [email protected].
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA. [email protected].
Abstract
There is an increasing need to integrate multimodal datasets in epilepsy research, particularly to correlate electrophysiology with imaging in patients with refractory epilepsy. We present a multimodal paired 3T and 7T MRI dataset acquired from 30 drug-resistant focal epilepsy patients (18 females, 38.8 ± 11.7 years) who underwent T1-weighted (T1w), T2-weighted (T2w), Fluid Attenuated Inversion Recovery (FLAIR), and resting-state functional MRI (rs-fMRI). In addition to the raw data, we release preprocessed anatomical and functional data, along with various quality control and clinical metadata files. For participants who subsequently underwent intracranial EEG (iEEG) (n = 15), curated ictal and interictal epochs are also included. We demonstrate a potential application of this paired 3T and 7T data by training a deep learning model capable of synthesizing high-field 7T T1w MR images from the 3T equivalents. We anticipate that this dataset will facilitate future multiscale analyses in epilepsy.