Dataset Information

Achalasia subtypes can be identified with functional luminal imaging probe (FLIP) panometry using a supervised machine learning process.

ABSTRACT:

Background

Achalasia subtypes on high-resolution manometry (HRM) prognosticate treatment response and help direct management plan. We aimed to utilize parameters of distension-induced contractility and pressurization on functional luminal imaging probe (FLIP) panometry and machine learning to predict HRM achalasia subtypes.

Methods

One hundred eighty adult patients with treatment-naïve achalasia defined by HRM per Chicago Classification (40 type I, 99 type II, 41 type III achalasia) who underwent FLIP panometry were included: 140 patients were used as the training cohort and 40 patients as the test cohort. FLIP panometry studies performed with 16-cm FLIP assemblies were retrospectively analyzed to assess distensive pressure and distension-induced esophageal contractility. Correlation analysis, single tree, and random forest were adopted to develop classification trees to identify achalasia subtypes.

Key results

Intra-balloon pressure at 60 mL fill volume, and proportions of patients with absent contractile response, repetitive retrograde contractile pattern, occluding contractions, sustained occluding contractions (SOC), contraction-associated pressure changes >10 mm Hg all differed between HRM achalasia subtypes and were used to build the decision tree-based classification model. The model identified spastic (type III) vs non-spastic (types I and II) achalasia with 90% and 78% accuracy in the train and test cohorts, respectively. Achalasia subtypes I, II, and III were identified with 71% and 55% accuracy in the train and test cohorts, respectively.

Conclusions and inferences

Using a supervised machine learning process, a preliminary model was developed that distinguished type III achalasia from non-spastic achalasia with FLIP panometry. Further refinement of the measurements and more experience (data) may improve its ability for clinically relevant application.

SUBMITTER: Carlson DA

PROVIDER: S-EPMC7775338 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Achalasia subtypes can be identified with functional luminal imaging probe (FLIP) panometry using a supervised machine learning process.

Carlson Dustin A DA Kou Wenjun W Rooney Katharine P KP Baumann Alexandra J AJ Donnan Erica E Triggs Joseph R JR Teitelbaum Ezra N EN Holmstrom Amy A Hungness Eric E Sethi Sajiv S Kahrilas Peter J PJ Pandolfino John E JE

Neurogastroenterology and motility 20200701 3

<h4>Background</h4>Achalasia subtypes on high-resolution manometry (HRM) prognosticate treatment response and help direct management plan. We aimed to utilize parameters of distension-induced contractility and pressurization on functional luminal imaging probe (FLIP) panometry and machine learning to predict HRM achalasia subtypes.<h4>Methods</h4>One hundred eighty adult patients with treatment-naïve achalasia defined by HRM per Chicago Classification (40 type I, 99 type II, 41 type III achalasi ...[more]

PMID: 32608147

Similar Datasets

Project description:Background & aimsFunctional luminal imaging probe (FLIP) panometry provides a comprehensive evaluation of esophageal functional at the time of endoscopy, including assessment of esophageal distensibility and distension-induced esophageal contractility. However, the few and inconsistent findings from healthy individuals pose challenges to the application of FLIP to research and clinical practice. We performed FLIP panometry in asymptomatic volunteers.MethodsWe performed a prospective study of 20 asymptomatic volunteers (ages, 23-44; 14 women) who were evaluated with 16-cm FLIP positioned across the esophagogastric junction (EGJ) and distal esophagus (and in 8 subjects also repositioned at the proximal esophagus) during sedated upper endoscopy. FLIP data were analyzed with a customized program that generated FLIP panometry plots and calculated the EGJ-distensibility index (DI) and distensibility plateaus (DP) of distal and proximal esophageal body. Distension-induced esophageal contractility was also assessed.ResultsThe median EGJ-DI was 5.8 mm2/mm Hg (interquartile range [IQR], 4.9-6.7 mm2/mm Hg); all 20 subjects had an EGJ-DI greater than 2.8 mm2/mm Hg. The median DP values from all subjects tested were 20.2 mm (IQR, 19.8-20.8 mm) at the distal body, 21.1 mm (IQR, 20.3-22.9 mm) at the proximal body, and greater than 18 mm at both locations. Repetitive antegrade contractions (RACs) were observed in all 20 subjects; in 19 of 20 (95%) subjects, the RAC pattern persisted for 10 or more consecutive antegrade contractions.ConclusionsNormal parameters of FLIP panometry are EGJ-DI greater than 2.8 mm2/mm Hg, DP greater than 18 mm, and antegrade contractions that occur in a repetitive pattern (RACs)-these can be used as normal findings for esophageal distensibility and distension-induced contractility. These values can be used in comparative studies of esophageal diseases, such as achalasia and eosinophilic esophagitis, and will facilitate application of FLIP panometry to clinical practice.

Project description:Background & aimsA normal esophageal response to distension on functional luminal imaging probe (FLIP) panometry during endoscopy might indicate normal esophageal motor function. We aimed to investigate the correlation of normal FLIP panometry findings with esophageal high-resolution manometry (HRM) and outcomes of discrepant patients.MethodsWe performed a retrospective study using data from a registry of patients who completed FLIP during sedated endoscopy. We identified 111 patients with normal FLIP panometry findings (mean age, 42 y; 69% female) and corresponding HRM data. A normal FLIP panometry was defined as an esophagogastric junction (EGJ) distensibility index greater than 3.0 mm2/mm Hg, an absence of repetitive retrograde contractions, and a repetitive antegrade contraction pattern that met the Rule-of-6s: ≥6 consecutive antegrade contractions of ≥6-cm in length, at a rate of 6 ± 3 contractions per minute. HRM findings were classified by the Chicago classification system version 3.0.ResultsHRM results were classified as normal motility in 78 patients (70%), ineffective esophageal motility in 10 patients (9%), EGJ outflow obstruction in 20 patients (18%), and 3 patients (3%) as other. In patients with EGJ outflow obstruction based on HRM, the integrated relaxation pressure normalized on adjunctive swallows in 16 of 20 patients (80%), and in 8 of 9 patients (88%) who completed a barium esophagram and had normal barium clearance. Thus, although 23 of 111 patients (21%) with normal FLIP panometry had abnormal HRM findings, these HRMs often were considered to be false-positive or equivocal results. All patients with an abnormal result from HRM were treated conservatively.ConclusionsIn a retrospective cohort study, we found that patients with normal FLIP panometry results did not have a clinical impression of a major esophageal motor disorder. Normal FLIP panometry results can exclude esophageal motility disorders at the time of endoscopy, possibly negating the need for HRM in select patients.

Dataset Information

Achalasia subtypes can be identified with functional luminal imaging probe (FLIP) panometry using a supervised machine learning process.

Background

Methods

Key results

Conclusions and inferences

Publications

Achalasia subtypes can be identified with functional luminal imaging probe (FLIP) panometry using a supervised machine learning process.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets