Enhancing Chicago Classification diagnoses with functional lumen imaging probe-mechanics (FLIP-MECH).

BACKGROUND: Esophageal motility disorders can be diagnosed by either high-resolution manometry (HRM) or the functional lumen imaging probe (FLIP) but there is no systematic approach to synergize the measurements of these modalities or to improve the diagnostic metrics that have been developed to analyze them. This work aimed to devise a formal approach to bridge the gap between diagnoses inferred from HRM and FLIP measurements using deep learning and mechanics. METHODS: The "mechanical health" of the esophagus was analyzed in 740 subjects including a spectrum of motility disorder patients and normal subjects. The mechanical health was quantified through a set of parameters including wall stiffness, active relaxation, and contraction pattern. These parameters were used by a variational autoencoder to generate a parameter space called virtual disease landscape (VDL). Finally, probabilities were assigned to each point (subject) on the VDL through linear discriminant analysis (LDA), which in turn was used to compare with FLIP and HRM diagnoses. RESULTS: Subjects clustered into different regions of the VDL with their location relative to each other (and normal) defined by the type and severity of dysfunction. The two major categories that separated best on the VDL were subjects with normal esophagogastric junction (EGJ) opening and those with EGJ obstruction. Both HRM and FLIP diagnoses correlated well within these two groups. CONCLUSION: Mechanics-based parameters effectively estimated esophageal health using FLIP measurements to position subjects in a 3-D VDL that segregated subjects in good alignment with motility diagnoses gleaned from HRM and FLIP studies.

Neurological disorders leading to mechanical dysfunction of the esophagus: an emergent behavior of a neuromechanical dynamical system.

An understanding how neurological disorders lead to mechanical dysfunction of the esophagus requires knowledge of the neural circuit of the enteric nervous system. Historically, this has been elusive. Here, we present an empirically guided neural circuit for the esophagus. It has a chain of unidirectionally coupled relaxation oscillators, receiving excitatory signals from stretch receptors along the esophagus. The resulting neuromechanical model reveals complex patterns and behaviors that emerge from interacting components in the system. A wide variety of clinically observed normal and abnormal esophageal responses to distension are successfully predicted. Specifically, repetitive antegrade contractions (RACs) are conclusively shown to emerge from the coupled neuromechanical dynamics in response to sustained volumetric distension. Normal RACs are shown to have a robust balance between excitatory and inhibitory neuronal populations, and the mechanical input through stretch receptors. When this balance is affected, contraction patterns akin to motility disorders are observed. For example, clinically observed repetitive retrograde contractions emerge due to a hyper stretch sensitive wall. Such neuromechanical insights could be crucial to eventually develop targeted pharmacological interventions.

A Mechanics-Based Perspective on the Function of Human Sphincters During Functional Luminal Imaging Probe Manometry.

Functional luminal imaging probe (FLIP) is used to measure cross-sectional area (CSA) and pressure at sphincters. It consists of a catheter surrounded by a fluid filled cylindrical bag, closed on both ends. Plotting the pressure-CSA hysteresis of a sphincter during a contraction cycle, which is available through FLIP testing, offers information on its functionality, and can provide diagnostic insights. However, limited work has been done to explain the mechanics of these pressure-CSA loops. This work presents a consolidated picture of pressure-CSA loops of different sphincters. Clinical data reveal that although sphincters have a similar purpose (controlling the flow of liquids and solids by opening and closing), two different pressure-CSA loop patterns emerge: negative slope loop (NSL) and positive slope loop (PSL). We show that the loop type is the result of an interplay between (or lack thereof) two mechanical modes: (i) neurogenic mediated relaxation of the sphincter muscle or pulling applied by external forces, and (ii) muscle contraction proximal to the sphincter which causes mechanical distention. We conclude that sphincters which only function through mechanism (i) exhibition NSL whereas sphincters which open as a result of both (i) and (ii) display a PSL. This work provides a fundamental mechanical understanding of human sphincters. This can be used to identify normal and abnormal phenotypes for the different sphincters and help in creating physiomarkers based on work calculation.

Blood-wall fluttering instability as a physiomarker of the progression of thoracic aortic aneurysms.

The diagnosis of aneurysms is informed by empirically tracking their size and growth rate. Here, by analysing the growth of aortic aneurysms from first principles via linear stability analysis of flow through an elastic blood vessel, we show that abnormal aortic dilatation is associated with a transition from stable flow to unstable aortic fluttering. This transition to instability can be described by the critical threshold for a dimensionless number that depends on blood pressure, the size of the aorta, and the shear stress and stiffness of the aortic wall. By analysing data from four-dimensional flow magnetic resonance imaging for 117 patients who had undergone cardiothoracic imaging and for 100 healthy volunteers, we show that the dimensionless number is a physiomarker for the growth of thoracic ascending aortic aneurysms and that it can be used to accurately discriminate abnormal versus natural growth. Further characterization of the transition to blood-wall fluttering instability may aid the understanding of the mechanisms underlying aneurysm progression in patients.

The physical origin of aneurysm growth, dissection, and rupture.

Rupture of aortic aneurysms is by far the most fatal heart disease, with a mortality rate exceeding 80%. There are no reliable clinical protocols to predict growth, dissection, and rupture because the fundamental physics driving aneurysm progression is unknown. Here, via in-vitro experiments, we show that a blood-wall, fluttering instability manifests in synthetic arteries under pulsatile forcing. We establish a phase space to prove that the transition from stable flow to unstable aortic flutter is accurately predicted by a flutter instability parameter derived from first principles. Time resolved strain maps of the evolving system reveal the dynamical characteristics of aortic flutter that drive aneurysm progression. We show that low level instability can trigger permanent aortic growth, even in the absence of material remodeling. Sufficiently large flutter beyond a secondary threshold localizes strain in the walls to the length scale clinically observed in aortic dissection. Lastly, significant physical flutter beyond a tertiary threshold can ultimately induce aneurysm rupture via failure modes reported from necropsy. Resolving the fundamental physics of aneurysm progression directly leads to clinical protocols that forecast growth as well as intercept dissection and rupture by pinpointing their physical origin.

Assessing mechanical function of peristalsis with functional lumen imaging probe panometry: Contraction power and displaced volume.

BACKGROUND AND AIMS: The distal contractile integral (DCI) quantifies the contractile vigor of primary peristalsis on high-resolution manometry (HRM), whereas no such metric exists for secondary peristalsis on functional lumen imaging probe (FLIP) panometry. This study aimed to evaluate novel FLIP metrics of contraction power and displaced volume in asymptomatic controls and a patient cohort. METHODS: Thirty-five asymptomatic controls and adult patients (with normal esophagogastric junction outflow/opening and without spasm) who completed HRM and FLIP panometry were included. The patient group also completed timed barium esophagram (TBE). Contraction power (estimate of esophageal work over time) and displaced volume (estimate of contraction-associated fluid flow) were computed from FLIP. HRM was analyzed per Chicago Classification v4.0. KEY RESULTS: In controls, median (5th-95th percentile) contraction power was 27 mW (10-44) and displaced volume was 43 mL (17-66). 95 patients were included: 72% with normal motility on HRM, 17% with ineffective esophageal motility (IEM), and 12% with absent contractility. Among patients, DCI was significantly correlated with both contraction power (rho = 0.499) and displaced volume (rho = 0.342); p values < 0.001. Both contraction power and displaced volume were greater in patients with normal motility versus IEM or absent contractility, complete versus incomplete bolus transit, and normal versus abnormal retention on TBE; p values < 0.02. CONCLUSIONS: FLIP panometry metrics of contraction power and displaced volume appeared to effectively quantify peristaltic vigor. These novel metrics may enhance evaluation of esophageal motility with FLIP panometry and provide a reliable surrogate to DCI on HRM.

MRI-MECH: mechanics-informed MRI to estimate esophageal health.

Dynamic magnetic resonance imaging (MRI) is a popular medical imaging technique that generates image sequences of the flow of a contrast material inside tissues and organs. However, its application to imaging bolus movement through the esophagus has only been demonstrated in few feasibility studies and is relatively unexplored. In this work, we present a computational framework called mechanics-informed MRI (MRI-MECH) that enhances that capability, thereby increasing the applicability of dynamic MRI for diagnosing esophageal disorders. Pineapple juice was used as the swallowed contrast material for the dynamic MRI, and the MRI image sequence was used as input to the MRI-MECH. The MRI-MECH modeled the esophagus as a flexible one-dimensional tube, and the elastic tube walls followed a linear tube law. Flow through the esophagus was governed by one-dimensional mass and momentum conservation equations. These equations were solved using a physics-informed neural network. The physics-informed neural network minimized the difference between the measurements from the MRI and model predictions and ensured that the physics of the fluid flow problem was always followed. MRI-MECH calculated the fluid velocity and pressure during esophageal transit and estimated the mechanical health of the esophagus by calculating wall stiffness and active relaxation. Additionally, MRI-MECH predicted missing information about the lower esophageal sphincter during the emptying process, demonstrating its applicability to scenarios with missing data or poor image resolution. In addition to potentially improving clinical decisions based on quantitative estimates of the mechanical health of the esophagus, MRI-MECH can also be adapted for application to other medical imaging modalities to enhance their functionality.

A mechanics-based perspective on the function of the esophagogastric junction during functional luminal imaging probe manometry.

The esophagogastric junction (EGJ) is located at the distal end of the esophagus and acts as a valve allowing swallowed food to enter the stomach and preventing acid reflux. Irregular weakening or stiffening of the EGJ muscles results in changes to its opening and closing patterns which can progress into esophageal disorders. Therefore, understanding the physics of the opening and closing cycle of the EGJ can provide mechanistic insights into its function and can help identify the underlying conditions that cause its dysfunction. Using clinical functional lumen imaging probe (FLIP) data, we plotted the pressure-cross-sectional area loops at the EGJ location and distinguished two major loop types-a pressure dominant loop and a tone dominant loop. In this study, we aimed to identify the key characteristics that define each loop type and determine what causes the inversion from one loop to another. To do so, the clinical observations are reproduced using 1D simulations of flow inside a FLIP device located in the esophagus, and the work done by the EGJ wall over time is calculated. This work is decomposed into active and passive components, which reveal the competing mechanisms that dictate the loop type. These mechanisms are esophageal stiffness, fluid viscosity, and the EGJ relaxation pattern.

Inhalation of virus-loaded droplets as a clinically plausible pathway to deep lung infection.

Respiratory viruses, such as SARS-CoV-2, preliminarily infect the nasopharyngeal mucosa. The mechanism of infection spread from the nasopharynx to the deep lung-which may cause a severe infection-is, however, still unclear. We propose a clinically plausible mechanism of infection spread to the deep lung through droplets, present in the nasopharynx, inhaled and transported into the lower respiratory tract. A coupled mathematical model of droplet, virus transport and virus infection kinetics is exercised to demonstrate clinically observed times to deep lung infection. The model predicts, in agreement with clinical observations, that severe infection can develop in the deep lung within 2.5-7 days of initial symptom onset. Results indicate that while fluid dynamics plays an important role in transporting the droplets, infection kinetics and immune responses determine infection growth and resolution. Immune responses, particularly antibodies and T-lymphocytes, are observed to be critically important for preventing infection severity. This reinforces the role of vaccination in preventing severe infection. Managing aerosolization of infected nasopharyngeal mucosa is additionally suggested as a strategy for minimizing infection spread and severity.

The buckling-condensation mechanism driving gas vesicle collapse.

Gas vesicles (GVs) are proteinaceous cylindrical shells found within bacteria or archea growing in aqueous environments and are composed primarily of two proteins, gas vesicle protein A and C (GvpA and GvpC). GVs exhibit strong performance as next-generation ultrasound contrast agents due to their gas-filled interior, tunable collapse pressure, stability in vivo and functionalizable exterior. However, the exact mechanism leading to GV collapse remains inconclusive, which leads to difficulty in predicting collapse pressures for different species of GVs and in extending favorable nonlinear response regimes. Here, we propose a two stage mechanism leading to GV loss of echogenicity and rupture under hydrostatic pressure: elastic buckling of the cylindrical shell coupled with condensation driven weakening of the GV membrane. Our goal is to therefore test whether the final fracture of the GV membrane occurs by the interplay of both mechanisms or purely through buckling failure as previously believed. To do so, we (1) compare the theoretical condensation and buckling pressures with that for experimental GV collapse and (2) describe how condensation can lead to plastic buckling failure. GV shell properties that are necessary input to this theoretical description, such as the elastic moduli and wettability of GvpA, are determined using molecular dynamics simulations of a novel structural model of GvpA that better represents the hydrophobic core. For GVs that are not reinforced by GvpC, this analytical framework shows that the experimentally observed pressures resulting in loss of echogenicity coincide with both the elastic buckling and condensation pressure regimes. We also found that the stress strain curve for GvpA wetted on both the interior and exterior exhibits a loss of mechanical stability compared to GvpA only wetted on the exterior by the bulk solution. We identify a pressure vs. vesicle size regime where condensation can occur prior to buckling, which may preclude nonlinear shell buckling responses in contrast imaging.

Peristaltic regimes in esophageal transport.

A FLIP device gives cross-sectional area along the length of the esophagus and one pressure measurement, both as a function of time. Deducing mechanical properties of the esophagus including wall material properties, contraction strength, and wall relaxation from these data are a challenging inverse problem. Knowing mechanical properties can change how clinical decisions are made because of its potential for in-vivo mechanistic insights. To obtain such information, we conducted a parametric study to identify peristaltic regimes by using a 1D model of peristaltic flow through an elastic tube closed on both ends and also applied it to interpret clinical data. The results gave insightful information about the effect of tube stiffness, fluid/bolus density and contraction strength on the resulting esophagus shape through quantitive representations of the peristaltic regimes. Our analysis also revealed the mechanics of the opening of the contraction area as a function of bolus flow resistance. Lastly, we concluded that peristaltic driven flow displays three modes of peristaltic geometries, but all physiologically relevant flows fall into two peristaltic regimes characterized by a tight contraction.

Virtual disease landscape using mechanics-informed machine learning: Application to esophageal disorders.

Esophageal disorders are related to the mechanical properties and function of the esophageal wall. Therefore, to understand the underlying fundamental mechanisms behind various esophageal disorders, it is crucial to map mechanical behavior of the esophageal wall in terms of mechanics-based parameters corresponding to altered bolus transit and increased intrabolus pressure. We present a hybrid framework that combines fluid mechanics and machine learning to identify the underlying physics of various esophageal disorders (motility disorders, eosinophilic esophagitis, reflux disease, scleroderma esophagus) and maps them onto a parameter space which we call the virtual disease landscape (VDL). A one-dimensional inverse model processes the output from an esophageal diagnostic device called the functional lumen imaging probe (FLIP) to estimate the mechanical "health" of the esophagus by predicting a set of mechanics-based parameters such as esophageal wall stiffness, muscle contraction pattern and active relaxation of esophageal wall. The mechanics-based parameters were then used to train a neural network that consists of a variational autoencoder that generated a latent space and a side network that predicted mechanical work metrics for estimating esophagogastric junction motility. The latent vectors along with a set of discrete mechanics-based parameters define the VDL and formed clusters corresponding to specific esophageal disorders. The VDL not only distinguishes among disorders but also displayed disease progression over time. Finally, we demonstrated the clinical applicability of this framework for estimating the effectiveness of a treatment and tracking patients' condition after a treatment.

Pulmonary drug delivery and retention: A computational study to identify plausible parameters based on a coupled airway-mucus flow model.

Pulmonary drug delivery systems rely on inhalation of drug-laden aerosols produced from aerosol generators such as inhalers, nebulizers etc. On deposition, the drug molecules diffuse in the mucus layer and are also subjected to mucociliary advection which transports the drugs away from the initial deposition site. The availability of the drug at a particular region of the lung is, thus, determined by a balance between these two phenomena. A mathematical analysis of drug deposition and retention in the lungs is developed through a coupled mathematical model of aerosol transport in air as well as drug molecule transport in the mucus layer. The mathematical model is solved computationally to identify suitable conditions for the transport of drug-laden aerosols to the deep lungs. This study identifies the conditions conducive for delivering drugs to the deep lungs which is crucial for achieving systemic drug delivery. The effect of different parameters on drug retention is also characterized for various regions of the lungs, which is important in determining the availability of the inhaled drugs at a target location. Our analysis confirms that drug delivery efficacy remains highest for aerosols in the size range of 1-5 µm. Moreover, it is observed that amount of drugs deposited in the deep lung increases by a factor of 2 when the breathing time period is doubled, with respect to normal breathing, suggesting breath control as a means to increase the efficacy of drug delivery to the deep lung. A higher efficacy also reduces the drug load required to be inhaled to produce the same health effects and hence, can help in minimizing the side effects of a drug.

Normative values of intra-bolus pressure and esophageal compliance based on 4D high-resolution impedance manometry.

BACKGROUND: This study aimed to quantify normative values of phase-specific intra-bolus pressure (IBP) and esophageal distensibility using 4D analysis of high-resolution-impedance manometry (HRIM). METHODS: HRIM studies of supine swallows from 34 normal controls were analyzed with respect to the four phases of bolus transit: (1) accommodation, (2) compartmentalization, (3) peristalsis/esophageal emptying, and (4) ampullary emptying. Phase-specific IBP, bolus volume, and distensibility index (DI) in the esophageal body and esophagogastric junction (EGJ) during phases 1-3 were extracted. RESULTS: The median (5-95th/IQR) IBP values were as follows: phase 1: 4.0 (-2.0-10.4/1.9-5.8) mmHg, phase 2: 5.7 (0.2-14.1/3.6-8.9) mmHg, and phase 3: 11.2 (2.9-19.4/7.7-15.1) mmHg. The median bolus volume calculated by integrating impedance planimetry cross-sectional areas was 4.1 ml during the compartmentalization phase. The EGJ-DI at max EGJ diameter during phase 2 and 3 was 2.8 (1.1-9.5/1.8-3.7) mm2 /mmHg and 6.0 (3.2-20.3/5.1-7.8) mm2 /mmHg, respectively. The phase 3 EGJ-DI values (6.0 (3.2-20.3/5.1-7.8) mm2 /mmHg) were similar to those calculated using functional lumen imaging probe (FLIP) at the 60 ml volume on the same subjects (5.8 [3.5-7.2/5.0-6.4] mm2 /mmHg). CONCLUSIONS AND INFERENCES: 4D-HRIM provides a standardized methodology to track the nadir impedance and provide measurements of IBP during maximal distention across phases 1-3 of bolus transit. Median IBP and delta IBP were different across the phases, supporting the need to define IBP by phase. Additionally, the EGJ-DI calculated during phase 3 was similar to the 60-ml EGJ-DI from FLIP in the same subjects suggesting that 4D-HRIM can quantify EGJ opening during primary peristalsis.

Boiling Transitions During Droplet Contact on Superheated Nano/Micro-Structured Surfaces.

Manipulating surface topography is one of the most promising strategies for increasing the efficiency of numerous industrial processes involving droplet contact with superheated surfaces. In such scenarios, the droplets may immediately boil upon contact, splash and boil, or could levitate on their own vapor in the Leidenfrost state. In this work, we report the outcomes of water droplets coming in gentle contact with designed nano/microtextured surfaces at a wide range of temperatures as observed using high-speed optical and X-ray imaging. We report a paradoxical increase in the Leidenfrost temperature (TLFP) as the texture spacing is reduced below a critical value (∼10 µm) that represents a minima in TLFP. Although droplets on such textured solids appear to boil upon contact, our studies suggest that their behavior is dominated by hydrodynamic instabilities implying that the increase in TLFP may not necessarily lead to enhanced heat transfer. On such surfaces, the droplets display a new regime characterized by splashing accompanied by a vapor jet penetrating through the droplets before they transition to the Leidenfrost state. We provide a comprehensive map of boiling behavior of droplets over a wide range of texture spacings that may have significant implications toward applications such as electronics cooling, spray cooling, nuclear reactor safety, and containment of fire calamities.

Myotomy technique and esophageal contractility impact blown-out myotomy formation in achalasia: an in silico investigation.

We used in silico models to investigate the impact of the dimensions of myotomy, contraction pattern, the tone of the esophagogastric junction (EGJ), and musculature at the myotomy site on esophageal wall stresses potentially leading to the formation of a blown-out myotomy (BOM). We performed three sets of simulations with an in silico esophagus model, wherein the myotomy-influenced region was modeled as an elliptical section devoid of muscle fibers. These sets investigated the effects of the dimensions of myotomy, differing esophageal contraction types, and differing esophagogastric junction (EGJ) tone and wall stiffness at the myotomy affected region on esophageal wall stresses potentially leading to BOM. Longer myotomy was found to be accompanied by a higher bolus volume accumulated at the myotomy site. With respect to esophageal contractions, deformation at the myotomy site was greatest with propagated peristalsis, followed by combined peristalsis and spasm, and pan-esophageal pressurization. Stronger EGJ tone with respect to the wall stiffness at the myotomy site was found to aid in increasing deformation at the myotomy site. In addition, we found that an esophagus with a shorter myotomy performed better at emptying the bolus than that with a longer myotomy. Shorter myotomies decrease the chance of BOM formation. Propagated peristalsis with EGJ outflow obstruction has the highest chance of BOM formation. We also found that abnormal residual EGJ tone may be a co-factor in the development of BOM, whereas remnant muscle fibers at myotomy site reduce the risk of BOM formation.NEW & NOTEWORTHY Blown-out myotomy (BOM) is a complication observed after myotomy, which is performed to treat achalasia. In silico simulations were performed to identify the factors leading to BOM formation. We found that a short myotomy that is not transmural and has some structural architecture intact reduces the risk of BOM formation. In addition, we found that high esophagogastric junction tone due to fundoplication is found to increase the risk of BOM formation.

A fully resolved multiphysics model of gastric peristalsis and bolus emptying in the upper gastrointestinal tract.

Over the past few decades, in silico modeling of organ systems has significantly furthered our understanding of their physiology and biomechanical function. In spite of the relative importance of the digestive system in normal functioning of the human body, there is a scarcity of high-fidelity models for the upper gastrointestinal tract including the esophagus and the stomach. In this work, we present a detailed numerical model of the upper gastrointestinal tract that not only accounts for the fiber architecture of the muscle walls, but also the multiphasic components they help transport during normal digestive function. Construction details for 3D models of representative stomach geometry are presented along with a simple strategy for assigning circular and longitudinal muscle fiber orientations for each layer. We developed a fully resolved model of the stomach to simulate gastric peristalsis by systematically activating muscle fibers embedded in the stomach. Following this, for the first time, we simulate gravity-driven bolus emptying into the stomach due to density differences between ingested contents and fluid contents of the stomach. Finally, we present a case of retrograde flow of fluid from the stomach into the esophagus, resembling the phenomenon of acid reflux. This detailed computational model of the upper gastrointestinal tract provides a foundation for future models to investigate the biomechanics of acid reflux and probe various strategies for gastric bypass surgeries to address the growing problem of obesity.

A mechanics-based perspective on the pressure-cross-sectional area loop within the esophageal body.

Introduction: Plotting the pressure-cross-sectional area (P-CSA) hysteresis loops within the esophagus during a contraction cycle can provide mechanistic insights into esophageal motor function. Pressure and cross-sectional area during secondary peristalsis can be obtained from the functional lumen imaging probe (FLIP). The pressure-cross-sectional area plots at a location within the esophageal body (but away from the sphincter) reveal a horizontal loop shape. The horizontal loop shape has phases that appear similar to those in cardiovascular analyses, whichinclude isometric and isotonic contractions followed by isometric and isotonic relaxations. The aim of this study is to explain the various phases of the pressurecross-sectional area hysteresis loops within the esophageal body. Materials and Methods: We simulate flow inside a FLIP device placed inside the esophagus lumen. We focus on three scenarios: long functional lumen imaging probe bag placed insidethe esophagus but not passing through the lower esophageal sphincter, long functional lumen imaging probe bag that crosses the lower esophageal sphincter, and a short functional lumen imaging probe bag placed in the esophagus body that does not pass through the lower esophageal sphincter. Results and Discussion: Horizontal P-CSA area loop pattern is robust and is reproduced in all three cases with only small differences. The results indicate that the horizontal loop pattern is primarily a product of mechanical conditions rather than any inherently different function of the muscle itself. Thus, the distinct phases of the loop can be explained solely based on mechanics.

Estimation of mechanical work done to open the esophagogastric junction using functional lumen imaging probe panometry.

In this study, we quantify the work done by the esophagus to open the esophagogastric junction (EGJ) and create a passage for bolus flow into the stomach. Work done on the EGJ was computed using functional lumen imaging probe (FLIP) panometry. Eighty-five individuals underwent FLIP panometry with a 16-cm catheter during sedated endoscopy including asymptomatic controls (n = 14), 45 patients with achalasia (n = 15 each, three subtypes), those with gastroesophageal reflux disease (GERD; n = 13), those with eosinophilic esophagitis (EoE; n = 8), and those with systemic sclerosis (SSc; n = 5). Luminal cross-sectional area (CSA) and pressure were measured by the FLIP catheter positioned across the EGJ. Work done on the EGJ (EGJW) was computed (millijoules, mJ) at 40-mL distension. Additionally, a separate method was developed to estimate the "work required" to fully open the EGJ (EGJROW) when it did not open during the procedure. EGJW for controls had a median [interquartile range (IQR)] value of 75 (56-141) mJ. All achalasia subtypes showed low EGJW compared with controls (P < 0.001). Subjects with GERD and EoE had EGJW 54.1 (6.9-96.3) and 65.9 (10.8-102.3) mJ, similar to controls (P < 0.08 and P < 0.4, respectively). The scleroderma group showed low values of EGJW, 12 mJ (P < 0.001). For patients with achalasia, EGJROW was the greatest and had a value of 210.4 (115.2-375.4) mJ. Disease groups with minimal or absent EGJ opening showed low values of EGJW. For patients with achalasia, EGJROW significantly exceeded EGJW values of all other groups, highlighting its unique pathophysiology. Balancing the relationship between EGJW and EGJROW is potentially useful for calibrating achalasia treatments and evaluating treatment response.NEW & NOTEWORTHY Changes in pressure and diameter occur at the EGJ during esophageal emptying. Similar changes can be observed during FLIP panometry. Data from healthy and diseased individuals were used to estimate the mechanical work done on the EGJ during distension-induced relaxation or, in instances of failed opening, work required to open the EGJ. Quantifying these parameters is potentially valuable to calibrate treatments and gauge treatment efficacy for subjects with disorders of EGJ function, especially achalasia.

Mechanics informed fluoroscopy of esophageal transport.

Fluoroscopy is a radiographic procedure for evaluating esophageal disorders such as achalasia, dysphasia and gastroesophageal reflux disease. It performs dynamic imaging of the swallowing process and provides anatomical detail and a qualitative idea of how well swallowed fluid is transported through the esophagus. In this work, we present a method called mechanics informed fluoroscopy (FluoroMech) that derives patient-specific quantitative information about esophageal function. FluoroMech uses a convolutional neural network to perform segmentation of image sequences generated from the fluoroscopy, and the segmented images become input to a one-dimensional model that predicts the flow rate and pressure distribution in fluid transported through the esophagus. We have extended this model to identify and estimate potential physiomarkers such as esophageal wall stiffness and active relaxation ahead of the peristaltic wave in the esophageal musculature. FluoroMech requires minimal computational time and hence can potentially be applied clinically in the diagnosis of esophageal disorders.