Distance Between Scalp and SQUID Sensors in Clinical Practice
Abstract number :
2.029
Submission category :
3. Neurophysiology / 3D. MEG
Year :
2022
Submission ID :
2204588
Source :
www.aesnet.org
Presentation date :
12/4/2022 12:00:00 PM
Published date :
Nov 22, 2022, 05:25 AM
Authors :
Teppei Matsubara, MD, PhD – Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; Noam Peled, PhD – Athinoula A. Martinos Center for Biomedical Imaging; Seppo Ahlfors, PhD – Athinoula A. Martinos Center for Biomedical Imaging; Padmavathi Sundaram, PhD – Athinoula A. Martinos Center for Biomedical Imaging; Yoshio Okada, PhD – Boston Children's Hospital; Matti Hämäläinen, PhD – Athinoula A. Martinos Center for Biomedical Imaging; Steven Stufflebeam, MD – Athinoula A. Martinos Center for Biomedical Imaging
Rationale: The distance between the brain and magnetoencephalography (MEG) sensors may be quite large for conventional whole-head MEG systems based on Super Conducting Quantum Interference Devices (SQUIDs). Since the sensors are placed within a single rigid helmet as part of a cryostat, the large distance may significantly diminish the MEG signal depending on the size and shape of the head, especially for the pediatric population. Since there are few studies that have systematically examined this issue, we determined the distance in a large clinical population of epilepsy patients._x000D_
Methods: We determined the distance between the inion (I), the external occipital protuberance, and the nearest MEG sensor (S) of a whole-head MEG system and the distance between I and the nearest cerebellar surface (C) from the individual MRI in a group of patients. The patients who had an MEG scan for presurgical evaluation of epilepsy at Martinos Center between May 2021, and May 2022, were investigated. MEG signals were recorded using a 306-channel MEG system (Elekta Neuromag, VecterView) while lying in a comfortable supine position. MEG measurements were performed along with EEG, electrooculography, and electrocardiography. A 70-channel EEG cap appropriate for the head size was placed on the head. Four head position indicator coils and fiducials were co-digitized with the patient’s head shape using a Polhemus digitizer for subsequent co-registration with individual MRI. The head was placed in the middle of the helmet. Continuous head position monitoring was used. FreeSurfer was used for automatic segmentation and tessellation of scalp, skull, and determining the brain volume from individual MRIs. We used multi-modality visualization tool (MMVT) for the distance measurement. _x000D_
Results: One hundred and fourteen patients (2.1-66 years, average 26.8 years; 57 female) had MEG. Among them, EEG was not collected in 9 patients (5 refusal, 4 large head size). FreeSufer could not complete reconstruction in 13 patients, and 2 MRIs were missing. In the remaining 99 patients, the average distance of IC was 28.7 mm (8.7 mm, standard deviation [SD]), and that of IS was 40.1 mm (7.4 mm SD). The scatter plot (Fig. 1) showed negligible correlation both between age and distance of IC (Pearson correlation efficient 0.24), and between age and distance of IS (Pearson correlation efficient -0.21)._x000D_
Conclusions: The average distance between the inion and the nearest SQUID sensor was 40 mm in patients. Some adult patients with an unsual shape or size or pediatric patients with a smaller head size can have scan limitations using a single rigid helmet. In these patients, on-scalp MEG sensors can be potentially useful._x000D_
Funding: Overseas Research Fellow of Japan Society for the Promotion of Science, NIH 1S10OD030469
Neurophysiology