Anatomically Constrained Gastric Slow Wave Localization using Biomagnetic Data.

Detection of dysrhythmic gastric slow wave (SW) activity could have significant clinical utility because dysrhyth-mias have been linked to gastric motility disorders. The elec-trogastrogram (EGG) and magnetogastrogram (MGG) enable the non-invasive assessment of SW activity, but most analysis methods can only resolve frequency and velocity. Improved characterization of dysrhythmic propagation patterns from non-invasive measurements is important for the diagnosis of motility disorders and could allow early treatment stratification. In this study, we demonstrate the use of a penalized linear regression framework to localize SW events on the longitudinal stomach axis using simulated MGG data. Priors relating to spatial sparsity, the organization of wavefronts into complete circumferential rings, and the local distribution of depolar-ization and repolarization phases were used to constrain the inverse solution. This method was applied to MGG computed for a single wavefront case and a multiple wavefront case that were constructed from simulated 3 cycle-per-minute normal SW activity. Propagation patterns along the longitudinal stomach axis were identifiable from reconstructed SW activity for both cases. Localization error was 5.7 ± 0.1 mm and 7.7 ± 0.1 mm for each respective case within the distal stomach when the signal-to-noise ratio was 10 dB. Results indicate that penalized linear regression can successfully localize SW events provided the 3D geometry of the stomach and torso were acquired. Clinical Relevance- This method could help to improve the efficiency and accuracy of diagnosing gastric motility disorders from non-invasive measurements.

Characterizing Spatial Signatures of Gastric Electrical Activity Using Biomagnetic Source Localization.

BACKGROUND: The motility patterns in the gastrointestinal tract are regulated, in part, by bioelectrical events known as slow waves (SWs). Understanding temporal and spatial features of gastric SWs can help reveal the underlying causes of functional motility disorders. OBJECTIVE: This study investigated the ability of source localization techniques to characterize the spatial signatures of SW activity using simulated and experimental magnetogastrography data. METHODS: Two SW propagation patterns (antegrade and retrograde) with two rhythms (normogastric and bradygastric) were used to simulate magnetic fields using 4 anatomically realistic stomach and torso geometries. Source localization was performed utilizing the equivalent current dipole (ECD) and the equivalent magnetic dipole (EMD) models. RESULTS: In the normogastric simulations when compared with the SW activity, the EMD model was capable of identifying the SW propagation in the lateral, antero-posterior, and supero-inferior axes with the median correlation coefficients of 0.66, 0.53, and 0.83, respectively, whereas the ECD model produced lower correlation scores (median: 0.52, 0.44, and 0.44). Moreover, the EMD model resulted in distinct and opposite spatial signatures for the antegrade and retrograde propagation. Similarly, when experimental data was used, the EMD model revealed antegrade-like signatures where the propagation was mostly towards the third quadrant in the supero-inferior (preprandial: 49%, postprandial: 35%) and antero-posterior (preprandial: 49%, postprandial: 50%) axes. CONCLUSION AND SIGNIFICANCE: The EMD model was able to identify and classify the spatial signatures of SW activities, which can help to inform the interpretation of non-invasive recordings of gastric SWs as a biomarker of functional motility disorders.

Effects of magnetogastrography sensor configurations in tracking slow wave propagation.

Magnetogastrography (MGG) is a non-invasive method of assessing gastric slow waves (SWs) by recording the resultant magnetic fields. MGG can capture both SW frequency and propagation, and identify SW dysrhythmias that are associated with motility disorders. However, the impact of the restricted spatial coverage and sensor density on SW propagation tracking performance is unknown. This study simulated MGG using multiple anatomically specific torso geometries and two realistic SW propagation patterns to determine the effect of different sensor configurations on tracking SW propagation. The surface current density mapping and center-of-gravity tracking methods were used to compare four magnetometer array configurations: a reference system currently used in GI research and three hypothetical higher density and coverage arrays. SW propagation patterns identified with two hypothetical arrays (with coverage over at least the anterior of the torso) correlated significantly higher with simulated realistic 3 cycle-per-minute SW activity than the reference array (p = 0.016, p = 0.005). Furthermore, results indicated that most of the magnetic fields that contribute to the performance of SW propagation tracking were located on the anterior of the torso as further increasing the coverage did not significantly increase performance. A 30% decrease in sensor spacing within the same spatial coverage of the reference array also significantly increased correlation values by approximately 0.50 when the signal-to-noise ratio was 5 dB. This study provides evidence that higher density and coverage sensor layouts will improve the utility of MGG. Further work is required to investigate optimum sensor configurations across larger anatomical variations and other SW propagation patterns.

Reconstruction of stomach geometry using magnetic source localization.

Routine diagnosis of gastric motility disorders represents a significant problem to current clinical practice. The non-invasive electrogastrogram (EGG) and magnetogastrogram (MGG) enable the assessment of gastric slow wave (SW) dysrhythmias that are associated with motility disorders. However, both modalities lack standardized methods for reliably detecting patterns of SW activity. Subject-specific anatomical information relating to the geometry of the stomach and its position within the torso have the potential to aid the development of relations between SWs and far-fields. In this study, we demonstrated the feasibility of using magnetic source localization to reconstruct the geometry of an anatomically realistic 3D stomach model. The magnetic fields produced by a small (6.35 × 6.35 mm) N35 neodymium magnet sequentially positioned at 64 positions were recorded by an array of 27 magnetometers. Finally, the magnetic dipole approximation and a particle swarm optimizer were used to estimate the position and orientation of the permanent magnet. Median position and orientation errors of 3.8 mm and 7.3° were achieved. The estimated positions were used to construct a surface mesh, and the Hausdorff Distance and Average Hausdorff Distance dissimilarity metrics for the reconstructed and ground-truth models were 11.6 mm and 2.4 mm, respectively. The results indicate that source localization using the magnetic dipole model can successfully reconstruct the geometry of the stomach.

Computational Reconstruction of 3D Stomach Geometry using Magnetic Field Source Localization.

In this study, we investigated the feasibility of computationally reconstructing the 3D geometry of the stomach by performing source localization of the magnetic field (MF) induced from the stomach surface. Anatomically realistic stomach and torso models of a human participant, reconstructed from the CT images, were used in the computations. First, 128 coils with a radius of 5 mm were positioned on different locations on the stomach model. Next, MF at the sensor positions were computed using Bio-Savart law for the currents of 10 and 100 mA. Then, three noise levels were defined using the biomagnetic data recorded from the same participant and two additional sets of generated white-noise resulting in mean signal to noise ratios (SNR) of 20 and 10 dB. Finally, for each combination of the current and noise level, the magnetic dipole (MDP) approximation was performed to estimate coil positions. The performance of the source localization was assessed by computing the goodness of fit (GOF) values and the distance between the coil and the estimated MDP positions. We obtained GOF values over 98% for all coils and a mean localization error of 0.69±0.08 mm was achieved when 100 mA current was used to induce MF and only biomagnetic data was added. When additional white-noise was added, the GOF values decreased to 95% and the mean localization error increased to around 4 mm. A current of 10 mA was enough to localize the coil positions with a mean error around 8 mm even for the highest noise level we tested but for the few coils furthest from the body surface, the error was around 10 cm. The results indicate that source localization using the MDP approximation can successfully extract spatial information of the stomach.Clinical relevance-Extracting the spatial information of the stomach during the recording of the slow wave activity provides new insights in assessing gastric recordings and relating to disorders.

Simulation-based Analysis of Magnetogastrography Sensor Configurations for Characterizing Gastric Slow Wave Dysrhythmias.

The routine diagnosis of gastric motility disorders represents a significant problem to current clinical practice. Magnetogastrography (MGG) provides a non-invasive option for assessing gastric slow wave (SW) dysrhythmias that are associated with motility disorders. However, its ability to characterize SW propagation is impaired by the limited spatial coverage of existing superconducting quantum interference devices (SQUIDs). Recently developed optically-pumped magnetometers can potentially substitute SQUIDs and enable subject-specific MGG arrays with greater spatial coverage. This study developed simulations of gastric MGG to determine the distribution of the magnetic fields (MFs) generated by SWs above the torso, and investigated the impact of several realistic dysrhythmic patterns of propagation. The distribution of MFs was found to vary significantly for different patterns of SW propagation, with ectopic dysrhythmia displaying the greatest difference from normal. Notably, some important proportion of the MFs lay outside the coverage of an existing experimental SQUID array used in gastrointestinal research for some simulated SW propagation patterns, such as retrograde activity. Results suggest that MGG measurements should be made over the entire frontal face of the torso to capture all of the strongest MFs generated by SWs.Clinical relevance- This provides a guide for the placement of MGG sensors for the capture of both normal and dysrhythmic gastric slow wave propagation.