학술논문

Stomach Geometry Reconstruction Using Serosal Transmitting Coils and Magnetic Source Localization
Document Type
Periodical
Source
IEEE Transactions on Biomedical Engineering IEEE Trans. Biomed. Eng. Biomedical Engineering, IEEE Transactions on. 70(3):1036-1044 Mar, 2023
Subject
Bioengineering
Computing and Processing
Components, Circuits, Devices and Systems
Communication, Networking and Broadcast Technologies
Coils
Stomach
Magnetic resonance imaging
Magnetic recording
Location awareness
Geometry
Magnetometers
Gastric slow waves
magnetogastrography
electrogastrography
functional gastric motility disorders
source localization
geometry reconstruction
Language
ISSN
0018-9294
1558-2531
Abstract
Objective: Bioelectric slow waves (SWs) are a key regulator of gastrointestinal motility, and disordered SW activity has been linked to motility disorders. There is currently a lack of practical options for the acquisition of the 3D stomach geometry during research studies when medical imaging is challenging. Accurately recording the geometry of the stomach and co-registering electrode and sensor positions would provide context for in-vivo studies and aid the development of non-invasive methods of gastric SW assessment. Methods: A stomach geometry reconstruction method based on the localization of transmitting coils placed on the gastric serosa was developed. The positions and orientations of the coils, which represented boundary points and surface-normal vectors, were estimated using a magnetic source localization algorithm. Coil localization results were then used to generate surface models. The reconstruction method was evaluated against four 3D-printed anatomically realistic human stomach models and applied in a proof of concept in-vivo pig study. Results: Over ten repeated reconstructions, average Hausdorff distance and average surface-normal vector error values were 4.7$\pm$0.2 mm and 18.7$\pm$0.7° for the whole stomach, and 3.6$\pm$0.2 mm and 14.6$\pm$0.6° for the corpus. Furthermore, mean intra-array localization error was 1.4$\pm$1.1 mm for the benchtop experiment and 1.7$\pm$1.6 mm in-vivo. Conclusion and Significance: Results demonstrated that the proposed reconstruction method is accurate and feasible. The stomach models generated by this method, when co-registered with electrode and sensor positions, could enable the investigation and validation of novel inverse analysis techniques.