Mechanics informed fluoroscopy of esophageal transport

Anatomy-derived 3D Aortic Hemodynamics Using Fluid Physics-informed Deep Learning

Background Four-dimensional (4D) flow MRI provides assessment of thoracic aorta hemodynamic measures that are increasingly recognized as important biomarkers for risk assessment. However, long acquisition times and cumbersome data analysis limit widespread availability. Purpose To evaluate the feasibility and accuracy of a generative artificial intelligence (AI) approach (fluid physics-informed cycle generative adversarial network [FPI-CycleGAN]) in quantifying aorta hemodynamics directly from anatomic input as an alternative to 4D flow MRI. Materials and Methods Patients were retrospectively identified from a dataset of clinical cardiothoracic MRI examinations performed between November 2011 and July 2020. All patients underwent aortic 4D flow MRI, which served as a reference standard for training and testing of FPI-CycleGANs. A three-dimensional (3D) segmentation of the aortic geometry was used as the only input to predict systolic aortic hemodynamics, with separate networks for bicuspid aortic valve (BAV) (994 in the training set and 248 in the test set) and tricuspid aortic valve (TAV) (419 in the training set and 104 in the test set). Voxel-by-voxel and regional analyses were used to quantify and compare (AI vs the reference standard, 4D flow) systolic velocity vector fields, peak velocity, wall shear stress (WSS), and classification of aortic valve stenosis. Results In total, 1765 patients (median age, 53 years [IQR, 41-63 years]; 1242 patients had BAV and 523 had TAV) were included. Mean AI computation time was 0.15 second ± 0.11 (SD), and total training was 1500 and 3600 minutes for the TAV and BAV networks, respectively. The FPI-CycleGAN predicted systolic 3D velocity vector fields accurately, with low bias (<0.01 m/sec) and excellent limits of agreements (±0.06-0.08 m/sec). For peak velocities and WSS, there was strong agreement between FPI-CycleGAN and 4D flow (r2 = 0.930-0.957 [P < .001], with relative differences of 6.2%-9.8%). AI accurately classified aortic valve stenosis severity in 85.8% of patients (302 of 352) (κ = 0.80 [95% CI: 0.71, 0.89]). The FPI-CycleGAN was robust to one- and two-voxel dilation and erosion (bias, -0.05 to 0.1 m/sec) and ±5° rotation (bias, -0.02 to 0.03 m/sec) of the input data. The application of the trained FPI-CycleGAN in an external test set with contrast-enhanced MR angiography (n = 60 patients) as AI input data demonstrated strong to excellent performance for peak velocities and WSS (r2 = 0.944-0.965 [P < .001], with relative differences of 6.2%-9.2%). Conclusion Aorta 3D hemodynamics can be derived from anatomic input in less than 1 second using an FPI-CycleGAN and demonstrate strong agreement with in vivo 4D flow MRI systolic hemodynamics. © RSNA, 2025 Supplemental material is available for this article.

Ex-vivo mechano-structural characterization of fresh diseased human esophagus

The esophagus, the tube-like organ responsible for transporting food from the pharynx to the stomach, operates as a highly mechanical structure, exhibiting complex contraction and distension patterns triggered by neurological impulses. Despite the critical role of mechanics in its function and the need for high-fidelity models of esophageal transport, mechanical characterization studies of human esophagus remain relatively scarce. In addition to the paucity of studies in human specimens, the available results are often scattered in terms of methodology and scope, making it difficult to compare findings across studies and thereby limiting their use in computational models. In this work, we present a detailed passive-mechanical and structural characterization of the esophageal muscular layers, excised from short esophageal segments obtained from live patients with varied clinical presentations. Specifically, we conducted uniaxial and planar biaxial extension tests on the smooth muscle layers, complemented by pre- and post-testing structural characterization via histological imaging. Unlike existing studies, our experimental results on passive behavior are discussed in the context of physiological relevance (e.g., physiological stretches, and activity-inhibiting pathologies), providing valuable insights that guide the subsequent modeling of the esophagus' mechanical response. As such, this work provides new insights into the passive properties of the fresh human esophagus, expands the existing database of mechanical parameters for computational modeling, and lays the foundation for future studies on active mechanical properties. STATEMENT OF SIGNIFICANCE: Understanding the mechanical properties of the esophagus is crucial for developing accurate models of its function and suitable replacements. This study provides insights into the passive mechanical behavior of fresh human esophageal tissue, enhancing our understanding of how it responds to stretching under physiological conditions. By characterizing the properties of different esophageal layers, obtained from esophagectomy specimens with various presentations, and considering their relevance to both normal and abnormal functioning, this work addresses the gap in ex-vivo human esophagus studies. The findings emphasize the importance of contextually analyzing experimental results within physiological parameters and suggest avenues for future research to further refine our understanding of esophageal mechanics, paving the way for improved diagnostic and therapeutic approaches in managing esophageal disorders.

Recent advancements and future directions in automatic swallowing analysis via videofluoroscopy: A review

Videofluoroscopic swallowing studies (VFSS) capture the complex anatomy and physiology contributing to bolus transport and airway protection during swallowing. While clinical assessment of VFSS can be affected by evaluators subjectivity and variability in evaluation protocols, many efforts have been dedicated to developing methods to ensure consistent measures and reliable analyses of swallowing physiology using advanced computer-assisted methods. Latest advances in computer vision, pattern recognition, and deep learning technologies provide new paradigms to explore and extract information from VFSS recordings. The literature search was conducted on four bibliographic databases with exclusive focus on automatic videofluoroscopic analyses. We identified 46 studies that employ state-of-the-art image processing techniques to solve VFSS analytical tasks including anatomical structure detection, bolus contrast segmentation, and kinematic event recognition. Advanced computer vision and deep learning techniques have enabled fully automatic swallowing analysis and abnormality detection, resulting in improved accuracy and unprecedented efficiency in swallowing assessment. By establishing this review of image processing techniques applied to automatic swallowing analysis, we intend to demonstrate the current challenges in VFSS analyses and provide insight into future directions in developing more accurate and clinically explainable algorithms.

A Software Framework for the Functional Lumen Imaging Probe-Mechanics (MechView)

BACKGROUND

The functional lumen imaging probe (FLIP) has proven to be a versatile device for diagnosing esophageal motility disorders and estimating esophageal wall compliance, but there is a lack of viable software for quantitative assessment of FLIP measurements.

METHODS

A Python-based web framework was developed for a unified assessment of FLIP measurements including clinical metrics such as esophagogastric junction (EGJ) distensibility index (DI), maximum EGJ opening diameter, mechanics-based metrics for estimating strength, and effectiveness of contractions, such as contraction power and displaced volume, and machine learning-based clustering and predictive algorithms such as the virtual disease landscape (VDL) and EGJ obstruction probability. The clinical and VDL probability metrics were then validated using FLIP data from 121 subjects constituting different categories of EGJ opening which were diagnosed by expert clinicians.

RESULTS

The clinical metrics estimated by the framework matched the manual diagnosis of the clinicians. Misclassifications were minimal and were mostly between neighboring groups, that is, normal and borderline normal or borderline normal and borderline reduced EGJ opening. Similar results were also obtained for the VDL probability metrics. The misclassifications were further analyzed by clinicians and approved.

CONCLUSION

The FLIP web framework was developed and validated to reliably estimate various clinical, mechanical, and machine learning-based metrics for diagnosing esophageal motility disorders.

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.

Oesophageal fluoroscopy in adults-when and why?

Oesophageal fluoroscopy is a radiological procedure that uses dynamic recording of the swallowing process to evaluate morphology and function simultaneously, a characteristic not found in other clinical tests. It enables a comprehensive evaluation of the entire upper gastrointestinal tract, from the oropharynx to oesophagogastric bolus transport. The number of fluoroscopies of the oesophagus and the oropharynx has increased in recent decades, while the overall use of gastrointestinal fluoroscopic examinations has declined. Radiologists performing fluoroscopies need a good understanding of the appropriate clinical questions and the methodological advantages and limitations to adjust the examination to the patient's symptoms and clinical situation. This review provides an overview of the indications for oesophageal fluoroscopy and the various pathologies it can identify, ranging from motility disorders to structural abnormalities and assessment in the pre- and postoperative care. The strengths and weaknesses of this modality and its future role within different clinical scenarios in the adult population are discussed. We conclude that oesophageal fluoroscopy remains a valuable tool in diagnostic radiology for the evaluation of oesophageal disorders.

Automatic three-dimensional reconstruction of the oesophagus in achalasia patients undergoing POEM: an innovative approach for evaluating treatment outcomes

BACKGROUND AND AIMS

Peroral endoscopic myotomy (POEM) is a standard treatment option for achalasia patients. Treatment response varies due to factors such as achalasia type, degree of dilatation, pressure and distensibility indices. We present an innovative approach for treatment response prediction based on an automatic three-dimensional (3-D) reconstruction of the tubular oesophagus (TE) and the lower oesophageal sphincter (LES) in patients undergoing POEM for achalasia.

METHODS

A software was developed, integrating data from high-resolution manometry, timed barium oesophagogram and endoscopic images to automatically generate 3-D reconstructions of the TE and LES. Novel normative indices for TE (volume×pressure) and LES (volume/pressure) were automatically integrated, facilitating pre-POEM and post-POEM comparisons. Treatment response was evaluated by changes in volumetric and pressure indices for the TE and the LES before as well as 3 and 12 months after POEM. In addition, these values were compared with normal value indices of non-achalasia patients.

RESULTS

50 treatment-naive achalasia patients were enrolled prospectively. The mean TE index decreased significantly (p<0.0001) and the mean LES index increased significantly 3 months post-POEM (p<0.0001). In the 12-month follow-up, no further significant change of value indices between 3 and 12 months post-POEM was seen. 3 months post-POEM mean LES index approached the mean LES of the healthy control group (p=0.077).

CONCLUSION

3-D reconstruction provides an interactive, dynamic visualisation of the oesophagus, serving as a comprehensive tool for evaluating treatment response. It may contribute to refining our approach to achalasia treatment and optimising treatment outcomes.

TRIAL REGISTRATION NUMBER

22-0149.

Investigating biomechanical alterations and emptying patterns after various gastrojejunostomy strategy

Gastrojejunostomy is a prominent approach in managing distal gastric cancer that is unresectable due to gastric outlet obstruction (GOO). Research has demonstrated that stomach-partitioning gastrojejunostomy (SPGJ) exhibits superior clinical efficacy compared to conventional gastrojejunostomy (CGJ), however, the underlying mechanism of this phenomenon remains elusive. This study constructed 3D models of the SPGJ and CGJ based on the computed tomography (CT) images obtained from a patient diagnosed with distal gastric cancer. The biomechanical patterns of these procedures in the digestive system were subsequently compared through numerical simulations and in vitro experiments. The results of the numerical simulation demonstrated that the model following SPGJ promoted the discharge of food through the anastomotic orifice and into the lower jejunum. Furthermore, a decrease in passage size after partitioning, the low-level velocity of esophageal, and an increase in contents viscosity effectively inhibited the flow through the passage to the pylorus, ultimately reducing stimulation to tumor. The study also revealed that favorable gastric emptying is associated with a smaller passage and faster inlet velocity, and that lower contents viscosity. ​The experimental findings conducted in vitro demonstrated that SPGJ exhibited superior efficacy in obstructing the flow near the pylorus in comparison to CGJ. Moreover, a decrease in passage size correlates with a reduction in fluid flow towards the pylorus. These results provide the foundation of theory and practice for the surgical management of patients with GOO resulting from unresectable distal gastric cancer, and have potential implications for clinical interventions.

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.

Esophageal diverticula: from diagnosis to therapeutic management-narrative review

BACKGROUND AND OBJECTIVE

Esophageal diverticulum (ED) is a relatively rare condition, characterized by high etio- and pathophysiological versatility, with an uncommon clinical impact, consequently requiring a complete and complex diagnostic evaluation, so that the therapeutic decision is "appropriate" to a specific case. The aim of the paper is, therefore, a reassessment of the diagnostic possibilities underlying the establishment of the therapeutic protocol and the available therapeutic resources, making a review of the literature, and a non-statistical retrospective analysis of cases hospitalized and operated in a tertiary center.

METHODS

Thus, classical investigations (upper digestive endoscopy, barium swallow) need to be correlated with complex, manometric, and imaging evaluations with direct implications in therapeutic management. Moreover, in the absence of a precise etiology, the operative indication needs to be established sparingly, with the imposition of the identification and interception of the pathophysiological mechanisms through the therapeutic gesture.

KEY CONTENT AND FINDINGS

The identification of the pathophysiological mechanisms is mandatory for the management of diverticular disease, the result obtained-restoring swallowing and comfort/good quality of life in the postoperative period-is directly related to the chosen therapeutic procedure. In addition, management appears to be a difficult goal in the context of the low incidence of ED but also of the results that emphasize important differences in the reports in the medical literature. Although ED is a benign condition, surgical techniques are demanding, impacted by significant morbidity and mortality. The causes of these results are multiple: possible localizations anywhere in the esophagus, diverticulum size/volume from a few millimeters to an impressive one, over 10-12 cm, metabolic impact in direct relation to the alteration swallowing, numerous diverticular complications but, perhaps most importantly, alteration of the quality of the diverticular wall by inflammatory phenomena, with an impact on the quality of the suture.

CONCLUSIONS

The accumulation of cases in a tertiary profile center, with volume/hospital, respectively volume/surgeon + gastroenterologist could be a solution in improving the results. One consequence would be the identification of alternative solutions to open surgical techniques, a series of minimally invasive or endoscopic variants can refine these results.

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.

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.

Esophageal wall compliance/stiffness during peristalsis in patients with functional dysphagia and high-amplitude esophageal contractions

Recent studies that utilized distension/contraction plots to study peristalsis reveal poor distension of the esophagus in patients with functional dysphagia and high-amplitude contractions [high-amplitude esophageal contractions (HAECs)] even though the contraction phase of peristalsis is normal in these patients. Our goal was to determine biomechanical properties of the esophageal wall and bolus flow characteristics in patients with functional dysphagia and HAEC during primary peristalsis. Studies were performed on 30 healthy subjects, 30 patients with functional dysphagia, and 25 patients with HAEC. Subjects swallowed 10 mL, 0.5 N saline bolus in the Trendelenburg position to study primary peristalsis. A custom-built software (Dplots) determined peak distension from the impedance measurements, pressure at peak distension, wall tension (pressure × radius), wall distensibility [cross-sectional area (CSA)/pressure], and bolus flow (cm3/s) in four segments of esophagus (between upper and lower esophageal sphincter). Luminal CSA of distal esophagus was smaller, and average bolus flow rate was faster in patients with functional dysphagia and HAEC. Esophageal wall distensibility, a measure of esophageal wall compliance was lower and wall tension was higher in the distal esophagus of both patient groups compared with normal subjects. Ultrasound imaging confirmed poor distension of the esophagus. A trend toward greater wall thickness at the peak of distension was found in patients with functional dysphagia compared with normal subjects. A stiffer or noncompliant esophageal wall is the reason for poor distension of the esophagus during primary peristalsis in patients with functional dysphagia and HAEC.NEW & NOTEWORTHY We studied healthy asymptomatic subject, patients with functional dysphagia (FD), and patients with high-amplitude esophageal contractions (HAEC). Our data show that in patients with HAEC and functional dysphagia, luminal distension is smaller (low luminal CSA at peak distension), intraluminal pressure is higher, and liquid bolus travels faster through the esophagus as compared with normal subjects. We conclude that patients with functional dysphagia and HAEC have a stiffer distal esophageal wall during bolus transport related to primary peristalsis.

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.

Assessment of esophageal body peristaltic work using functional lumen imaging probe panometry

The goal of this study was to conceptualize and compute measures of "mechanical work" done by the esophagus using data generated during functional lumen imaging probe (FLIP) panometry and compare work done during secondary peristalsis among patients and controls. Eighty-five individuals were evaluated with a 16-cm FLIP during sedated endoscopy, including asymptomatic controls (n = 14) and those with achalasia subtypes I, II, and III (n = 15, each); gastroesophageal reflux disease (GERD; n = 13); eosinophilic esophagitis (EoE; n = 9); and systemic sclerosis (SSc; n = 5). The FLIP catheter was positioned to have its distal segment straddling the esophagogastric junction (EGJ) during stepwise distension. Two metrics of work were assessed: "active work" (during bag volumes ≤ 40 mL where contractility generates substantial changes in lumen area) and "work capacity" (for bag volumes ≥ 60 mL when contractility cannot substantially alter the lumen area). Controls showed median [interquartile range (IQR)] of 7.3 (3.6-9.2) mJ of active work and 268.6 (225.2-332.3) mJ of work capacity. Patients with all achalasia subtypes, GERD, and SSc showed lower active work done than controls (P ≤ 0.003). Patients with achalasia subtypes I and II, GERD, and SSc had lower work capacity compared with controls (P < 0.001, 0.004, 0.04, and 0.001, respectively). Work capacity was similar between controls and patients with achalasia type III and EoE. Mechanical work of the esophagus differs between healthy controls and patient groups with achalasia, EoE, SSc, and GERD. Further studies are needed to fully explore the utility of this approach, but these work metrics would be valuable for device design (artificial esophagus), to measure the efficacy of peristalsis, to gauge the physiological state of the esophagus, and to comment on its pumping effectiveness.NEW & NOTEWORTHY Functional lumen imaging probe (FLIP) panometry assesses esophageal response to distension and provides a simultaneous assessment of pressure and dimension during contractility. This enables an objective assessment of "mechanical work" done by the esophagus. Eighty-five individuals were evaluated, and two work metrics were computed for each subject. Controls showed greater values of work compared with individuals with achalasia, gastroesophageal reflux disease (GERD), and systemic sclerosis (SSc). These values can quantify the mechanical behavior of the distal esophagus and assist in the estimation of muscular integrity.