Ilana Klovatch-Podlipsky1, Tomer Gazit2, Firas Fahoum3, Boris Tsirelson4, Svetlana Kipervasser5, Uri Kremer6, Bruria Ben-Zeev7, Hadassah Goldberg-Stern8, Orna Eisenstein9, Yuval Harpaz10, Ory Levy1, Adi Kirschner1, Miriam Y Neufeld5, Itzhak Fried11, Talma Hendler12, Mordekhay Medvedovsky13. 1. Tel-Aviv Center for Brain Functions, Whol Institute for Advance Imaging, Tel Aviv Sourasky Medical Center, Israel. 2. Tel-Aviv Center for Brain Functions, Whol Institute for Advance Imaging, Tel Aviv Sourasky Medical Center, Israel. Electronic address: Tomergazit@gmail.com. 3. EEG and Epilepsy Unit, Department of Neurology, Tel Aviv Sourasky Medical Center, Israel. 4. School of Mathematics, Tel Aviv University, Israel. 5. EEG and Epilepsy Unit, Department of Neurology, Tel Aviv Sourasky Medical Center, Israel; Sackler School of Medicine, Tel Aviv University, Israel. 6. Pediatric Epilepsy Unit, Tel Aviv Sourasky Medical Center, Tel Aviv University, Tel Aviv, Israel. 7. Pediatric Neurology Unit, Edmond and Lilly Safra Children's Hospital, Sheba Medical Center, Ramat-Gan, Israel. 8. Schneider Children's Medical Center of Israel, Petach Tikvah, Israel. 9. Department of Radiology, Tel Aviv Sourasky Medical Center, Israel. 10. Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel. 11. Department of Neurosurgery, David Geffen School of Medicine and Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA; Functional Neurosurgery Unit, Tel-Aviv Medical Center, Israel. 12. Tel-Aviv Center for Brain Functions, Whol Institute for Advance Imaging, Tel Aviv Sourasky Medical Center, Israel; Sackler School of Medicine, Tel Aviv University, Israel; School of Psychological Sciences, Tel-Aviv University, Israel; Sagol School of Neuroscience, Tel-Aviv University, Israel. 13. Tel-Aviv Center for Brain Functions, Whol Institute for Advance Imaging, Tel Aviv Sourasky Medical Center, Israel; Helsinki University Central Hospital, Helsinki, Finland.
Abstract
OBJECTIVE: Although simultaneous recording of EEG and MRI has gained increasing popularity in recent years, the extent of its clinical use remains limited by various technical challenges. Motion interference is one of the major challenges in EEG-fMRI. Here we present an approach which reduces its impact with the aid of an MR compatible dual-array EEG (daEEG) in which the EEG itself is used both as a brain signal recorder and a motion sensor. METHODS: We implemented two arrays of EEG electrodes organized into two sets of nearly orthogonally intersecting wire bundles. The EEG was recorded using referential amplifiers inside a 3T MR-scanner. Virtual bipolar measurements were taken both along bundles (creating a small wire loop and therefore minimizing artifact) and across bundles (creating a large wire loop and therefore maximizing artifact). Independent component analysis (ICA) was applied. The resulting ICA components were classified into brain signal and noise using three criteria: 1) degree of two-dimensional spatial correlation between ICA coefficients along bundles and across bundles; 2) amplitude along bundles vs. across bundles; 3) correlation with ECG. The components which passed the criteria set were transformed back to the channel space. Motion artifact suppression and the ability to detect interictal epileptic spikes following daEEG and Optimal Basis Set (OBS) procedures were compared in 10 patients with epilepsy. RESULTS: The SNR achieved by daEEG was 11.05±3.10 and by OBS was 8.25±1.01 (p<0.00001). In 9 of 10 patients, more spikes were detected after daEEG than after OBS (p<0.05). SIGNIFICANCE: daEEG improves signal quality in EEG-fMRI recordings, expanding its clinical and research potential.
OBJECTIVE: Although simultaneous recording of EEG and MRI has gained increasing popularity in recent years, the extent of its clinical use remains limited by various technical challenges. Motion interference is one of the major challenges in EEG-fMRI. Here we present an approach which reduces its impact with the aid of an MR compatible dual-array EEG (daEEG) in which the EEG itself is used both as a brain signal recorder and a motion sensor. METHODS: We implemented two arrays of EEG electrodes organized into two sets of nearly orthogonally intersecting wire bundles. The EEG was recorded using referential amplifiers inside a 3T MR-scanner. Virtual bipolar measurements were taken both along bundles (creating a small wire loop and therefore minimizing artifact) and across bundles (creating a large wire loop and therefore maximizing artifact). Independent component analysis (ICA) was applied. The resulting ICA components were classified into brain signal and noise using three criteria: 1) degree of two-dimensional spatial correlation between ICA coefficients along bundles and across bundles; 2) amplitude along bundles vs. across bundles; 3) correlation with ECG. The components which passed the criteria set were transformed back to the channel space. Motion artifact suppression and the ability to detect interictal epileptic spikes following daEEG and Optimal Basis Set (OBS) procedures were compared in 10 patients with epilepsy. RESULTS: The SNR achieved by daEEG was 11.05±3.10 and by OBS was 8.25±1.01 (p<0.00001). In 9 of 10 patients, more spikes were detected after daEEG than after OBS (p<0.05). SIGNIFICANCE: daEEG improves signal quality in EEG-fMRI recordings, expanding its clinical and research potential.
Authors: Corey E Cruttenden; Jennifer M Taylor; Mahdi Ahmadi; Yi Zhang; Xiao-Hong Zhu; Wei Chen; Rajesh Rajamani Journal: Biomed Signal Process Control Date: 2021-06-09 Impact factor: 3.880