Conference Agenda

The stomach plays a central role in digestion by accommodating ingested food, mechanically mixing its contents, and chemically breaking down nutrients. These functions are tightly orchestrated by gastric peristalsis—a complex process governed by an intricate electromechanical system that ensures the effective propulsion of food into the intestines. A detailed understanding of the mechanics and regulation of gastric motility is therefore crucial for diagnosing and treating prevalent gastrointestinal disorders such as gastroparesis, gastroesophageal reflux disease (GERD), and functional dyspepsia, all of which can significantly impair quality of life.

Despite its clinical relevance, gastric electromechanics remain poorly understood, even at a fundamental biophysical level. Recent advances in computational modeling offer promising opportunities to investigate gastric function. While experimental studies are indispensable, computational models offer a unique advantage: they enable the exploration of hypothetical physiological configurations and states that are difficult or impossible to replicate in the lab. This makes them powerful tools for efficiently testing and comparing competing biophysical hypotheses.

However, the evaluation of complex models across many different scenarios poses a significant challenge, as the computational cost can become prohibitively high. To address this, we introduce a framework for automated model evaluation in multi-query settings, encompassing parameter studies, sensitivity analysis, uncertainty quantification, and Bayesian parameter identification (i.e., model calibration). We demonstrate how even relatively simple methods—such as structured designs of experiments—can provide valuable insights and enable systematic comparisons of competing hypotheses. A key enabler of more advanced, large-scale studies is the use of surrogate modeling, which dramatically reduces computational costs and facilitates more sophisticated analyses such as global sensitivity analysis.

Using this framework, we for example show that replicating key features of gastric electromechanics—such as the extreme deformations observed experimentally in the fasted stomach—requires very specific conditions. In particular, our results highlight the need for a finely tuned coordination between contractions in the circumferential and longitudinal muscle layers. This emphasizes the critical coupling between electrical excitation and large-scale, nonlinear tissue deformation that underlies normal gastric function.

By integrating multi-query analysis techniques with advanced computational models—such as a patient-specific active-strain electromechanical model of the human stomach—we uncover novel insights into the biomechanics of gastric motility. This approach provides a powerful tool for deepening our understanding of both normal physiology and motility disorders. Ultimately, we envision this work as a bridge between computational modeling and clinical practice, paving the way for model-based diagnostics and treatment planning for disorders such as gastroparesis, GERD, and dyspepsia.

Introduction: Contractions of the smooth muscles throughout the gastrointestinal (GI) tract facilitate digestion. These contractions are coordinated by rhythmic depolarisations of the smooth muscles, known as slow waves. Impairments to these electrical events are associated with a variety of debilitating motility disorders such as gastroparesis and functional dyspepsia. Gastric pacing is a potential therapy to restore normal slow wave function, similar to how cardiac pacemakers regulate heart rhythms. To investigate slow wave physiology and potential treatments, researchers often rely on acute animal studies under anaesthesia, which provide controlled environments for precise physiological measurements. However, different anaesthetic agents may influence gastric slow wave activity in distinct ways, potentially affecting experimental outcomes. Two common anaesthetic agents are: isoflurane, a widely used volatile anaesthetic, and propofol, a newer intravenous agent gaining broader use. This study compares their effects on gastric slow waves and examines how these differences impact the evaluation of gastric pacing as a therapeutic approach.

Methods: With ethical approval, experiments were conducted on pigs anesthetised with either isoflurane or propofol. To study the slow wave response, surface-contact electrode arrays were placed on the mid-corpus of the stomach, covering both the anterior (front-facing) and posterior (back-facing) surfaces (64 electrodes each side, 5 mm inter-electrode spacing). These surfaces are separated by the greater curvature and the lesser curvature. Following a baseline recording period, pacing was applied using a pulse-width of 400 ms and pulse-amplitudes of 5 mA at 1.1 times the intrinsic slow wave frequency. Slow waves were characterised by their period, amplitude, speed, and spatial propagation patterns, while pacing efficacy was assessed by measuring the rate of spatial entrainment under propofol and isoflurane anaesthesia.

Results: Ordered propagation of slow waves in the antegrade direction was observed across both the anterior and posterior surfaces with 86% symmetry under propofol, while isoflurane resulted in more dynamic propagation patterns and significantly less symmetry (25%, p=0.0187). Baseline slow wave period (18.8±5.1 vs 28.1±14.3 s, p=0.016), amplitude (1.5±0.7 vs 0.7±0.4 mV, p=0.002), and speed (4.4±1.1 vs 3.5±0.7 mm/s, p=0.018) differed significantly between propofol and isoflurane groups, respectively. When evaluating the efficacy of pacing under different anaesthesia, pigs anaesthetised with propofol achieved a spatial entrainment success rate of 83% compared to 57% with isoflurane.

Conclusion: Different anaesthetic agents affect gastric slow waves differently. Propofol preserves more regular activity, while isoflurane is associated with a greater proportion of disordered patterns. This contrast likely stems from their distinct mechanisms of action, with propofol providing targeted sedation and isoflurane exerting broader systemic effects, potentially including on the GI tract. Accounting for these differences is crucial when using acute models to study GI electrophysiology. These differences in anaesthetic effects can be leveraged to study diagnostic and therapeutic interventions where propofol provides a model for normal, ordered slow wave activity, while isoflurane can simulate dysrhythmic states, offering valuable insights into disease mechanisms and potential treatments.

Introduction:
Biomechanical and electrochemical computational models of the stomach contraction have advanced significantly over the past two decades, progressing from single-cell simulations to whole-organ ones. More recently, chemo-electromechanical models have emerged, aiming to simulate the relationship between ion concentrations, electric potentials generated by the smooth muscles, and tissue contraction dynamics. The model presented here builds on these foundations by simulating slow wave generation and transmission across an anatomically inspired stomach scaffold, while independently visualizing smooth muscle contractions. A novel aspect of this work is the incorporation of a neural control mechanism that simulates the effect of neurotransmitters such as acetylcholine and nitric oxide on slow wave propagation and muscle contraction across the entire stomach.

Method:
The model couples a tridomain electrophysiological framework with a biomechanical spring-based model. The tridomain equations govern the propagation of slow waves through interstitial cells of Cajal, smooth muscle cells, and a fixed homogenous extracellular domain. Neural regulation pathways affecting specific ionic currents were incorporated based on recent physiological data, modulating excitatory and inhibitory effects through parameters such as Ano1 and NSCC channel conductances. The mechanical behavior was modeled by linking intracellular calcium concentration to tissue tension using Hill-type equations, and displacements were visualized through a damped harmonic oscillator analogy. The anatomical scaffold was derived from fitting CT images obtained from NIH’s SPARC database, and later processed into a finite element mesh in MATLAB, over which the model was solved using isotropic assumptions with Dirichlet and Neumann boundary conditions. Electrophysiological simulations were performed in MATLAB, while scaffold displacements were visualized in Python.

Results:
Simulation results demonstrated realistic propagation of slow waves originating at the gastric pacemaker region, traveling at physiological frequencies (~3 cycles per minute) towards the pylorus, with circumferential conduction velocities approximately double the longitudinal ones. The model also showed the expected frequency and amplitude modulation under neural stimulation: excitatory neural inputs increased wave amplitude by approximately 2.9 mV and raised contraction frequency to 4 cpm, while inhibitory inputs significantly reduced contractile tension by up to 29 kPa. Displacement simulations showed tissue deformations ranging from 0 mm at rest to approximately 2.9 mm during contraction, consistent with physiological observations. Validation was achieved through qualitative comparison with previous computational models of gastric motility, confirming correct slow wave directionality, frequency, and muscle deformation magnitude.

Conclusion and Future Work:

These results highlight the model's capability to simulate gastric motility with neural control on an anatomically inspired scaffold. However, in order for this model to serve as a platform for the design and in-silica testing of pharmaceutical drugs among other clinical applications, it requires further enhancements. Main aspects that will require future attention is the implementation of an anisotropic framework, a more accurate biomechanical model compared to the current Hill model and the incorporation of more neural control pathways.