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CHANGING DISTENSIBILITY OF THE ESOPHAGOGASTRIC JUNCTION WITH REPEATED DISTENSIONS IN THE ACHALASIA ESOPHAGUS: HYSTERESIS EFFECT

Date
May 19, 2024


Introduction

Hysteresis is a known property of all materials; it refers to the variability in the relationship between stress force and strain over repeated cycles of loading and unloading, i.e., repeated distension. Hysteresis is known to affect the biomechanical properties of esophageal wall. Our goal was to study the role of hysteresis in determining the distensibility index of the esophagogastric junction (EGJ), which is a critical parameters in assessing the esophageal motility disorders using the functional luminal imaging probe (FLIP). Specifically, we aimed to test, a) whether there is intra-subject variance in the distensibility index (DI) of the EGJ with repeated distensions, and b) the patterns of variance in the DI measurement.

Methods

Consenting adult patients (NCT 04641702) with achalasia esophagus findings on timed barium esophagogram (TBE) were included if they met the following criteria, 1) manometric diagnosis of achalasia or esophagogastric junction outflow obstruction (EGJOO), and 2) absent esophageal contractile response on the FLIP testing. Subjects underwent 3 cycles of inflation and deflation with 60ml bag distension (Figure 1A). FLIP data were analyzed via an open-source software in a blinded fashion. Metrics were measured at the time point of maximal EGJ opening. Univariate statistical analysis and simple linear regression were performed to assess the patterns of variability.

Results

A total of 15 subjects (ages 33-80, female biological sex in 53.3%) were included in the analysis. Manometric patterns were type 1 achalasia (n=4), type 2 achalasia (n=7), type 3 achalasia (n=2), and EGJOO (n=2)]. Measures assessing the intra-subject variance in EGJ measurements are shown in Table 1. High intra-subject variability in the cross-sectional area (and hence the DI) with relative stability in the pressure measurement were noted. Figure 1B and 1C show the trajectory of the DI measurement in the entire studied group, represented as mean % change from the baseline. Based on the DI trajectory, we chose to compare the slope estimates using the simple linear regression model incorporating all 6 ramps (b1=0.156, 95% CI 0.093-0.219) vs when excluding ramp 1 (b1=0.091, 95% CI 0.065-0.117). These slope estimates were different (p value=0.042) using Wilcoxon matched pairs signed-rank test). The repeated DI measurements show a positive linear slope, i.e., an increasing DI with repeated distension. The 1st measurement was the lowest value.

Conclusion

FLIP measurements of the EGJ in achalasia esophagus demonstrate a prominent hysteresis effect, with the lowest DI value during the first inflation. Further studies are needed to determine the clinical implications of our findings with regards to the diagnosis of esophageal motility disorders using FLIP technique.
<b>Table 1. </b>Univariate statistics (from 6 measurements per subject) are provided for 3 variables in 15 subjects. Mean (standard deviation) values are provided. CEV = coefficient of variation.

Table 1. Univariate statistics (from 6 measurements per subject) are provided for 3 variables in 15 subjects. Mean (standard deviation) values are provided. CEV = coefficient of variation.

<b>Figure 1.</b> Distensibility index (DI) trajectory is shown over 6 cycles. Panel A shows the DI measurement protocol during FLIP. Panel B shows the raw DI measurements over the 4-6 cycles in all subjects. Panel C shows the composite trajectory expressed as the % change from the mean DI measurement. Panel C also shows how the slope estimates were derived from the linear regression model (but note these were calculated based on the raw data).

Figure 1. Distensibility index (DI) trajectory is shown over 6 cycles. Panel A shows the DI measurement protocol during FLIP. Panel B shows the raw DI measurements over the 4-6 cycles in all subjects. Panel C shows the composite trajectory expressed as the % change from the mean DI measurement. Panel C also shows how the slope estimates were derived from the linear regression model (but note these were calculated based on the raw data).