The Reverse Red-Green-Blue Rule : A Color-Coded Approach for Simplified Achalasia Diagnosis via High-Resolution Manometry
Abdulrasak, Mohammed LU
; Hootak, Sohail
; Mohrag, Mostafa
and Someili, Ali M
(2025)
In Gastroenterology research
18(3).
p.149-151
- Abstract
BACKGROUND: Achalasia is a rare motility disorder of the esophagus. The diagnosis involves clinical suspicion based on history details and results of high-resolution manometry (HRM) as recommended by the Chicago classification (CCv4.0). Interpreting data obtained through HRM can be complex especially for the novice user.
METHODS: We propose therefore a color-based algorithm involving the "reversed red-green-blue (RGB)" rule as a simplified way to establish the diagnosis based on colors obtained through the HRM pressure sensors. The rule is based on the simple acknowledgment of the dominant color present in the mid-portion of the HRM figure such that, for type I (classic) achalasia, the blue color illustrates the minimal... (More)
BACKGROUND: Achalasia is a rare motility disorder of the esophagus. The diagnosis involves clinical suspicion based on history details and results of high-resolution manometry (HRM) as recommended by the Chicago classification (CCv4.0). Interpreting data obtained through HRM can be complex especially for the novice user.
METHODS: We propose therefore a color-based algorithm involving the "reversed red-green-blue (RGB)" rule as a simplified way to establish the diagnosis based on colors obtained through the HRM pressure sensors. The rule is based on the simple acknowledgment of the dominant color present in the mid-portion of the HRM figure such that, for type I (classic) achalasia, the blue color illustrates the minimal pressurization and absent peristalsis. In type II (pan-pressurized) achalasia, the green color illustrates pan-esophageal pressurization, while in type III (spastic) achalasia, red color illustrates the spastic contractions.
RESULTS: This rule, which we present as a conceptual framework and has not yet been prospectively validated, provides an intuitive tool for clinicians dealing with HRMs diagnosing achalasia.
CONCLUSION: Further studies are required to assess the diagnostic accuracy of this rule, alongside the potential for incorporating such rules into artificial intelligence (AI)-based models for manometric diagnosis of esophageal motility disorders.
(Less)
- author
- Abdulrasak, Mohammed
LU
; Hootak, Sohail
; Mohrag, Mostafa
and Someili, Ali M
- organization
- publishing date
- 2025-06
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Gastroenterology research
- volume
- 18
- issue
- 3
- pages
- 3 pages
- publisher
- Elmer Press
- external identifiers
-
- pmid:40503192
- ISSN
- 1918-2805
- DOI
- 10.14740/gr2040
- language
- English
- LU publication?
- yes
- additional info
- Copyright 2025 Authors.
- id
- baddcff2-60a3-42be-98b3-d6a3126c9b59
- date added to LUP
- 2025-06-12 18:46:00
- date last changed
- 2025-06-13 08:52:34
@article{baddcff2-60a3-42be-98b3-d6a3126c9b59,
abstract = {{<p>BACKGROUND: Achalasia is a rare motility disorder of the esophagus. The diagnosis involves clinical suspicion based on history details and results of high-resolution manometry (HRM) as recommended by the Chicago classification (CCv4.0). Interpreting data obtained through HRM can be complex especially for the novice user.</p><p>METHODS: We propose therefore a color-based algorithm involving the "reversed red-green-blue (RGB)" rule as a simplified way to establish the diagnosis based on colors obtained through the HRM pressure sensors. The rule is based on the simple acknowledgment of the dominant color present in the mid-portion of the HRM figure such that, for type I (classic) achalasia, the blue color illustrates the minimal pressurization and absent peristalsis. In type II (pan-pressurized) achalasia, the green color illustrates pan-esophageal pressurization, while in type III (spastic) achalasia, red color illustrates the spastic contractions.</p><p>RESULTS: This rule, which we present as a conceptual framework and has not yet been prospectively validated, provides an intuitive tool for clinicians dealing with HRMs diagnosing achalasia.</p><p>CONCLUSION: Further studies are required to assess the diagnostic accuracy of this rule, alongside the potential for incorporating such rules into artificial intelligence (AI)-based models for manometric diagnosis of esophageal motility disorders.</p>}},
author = {{Abdulrasak, Mohammed and Hootak, Sohail and Mohrag, Mostafa and Someili, Ali M}},
issn = {{1918-2805}},
language = {{eng}},
number = {{3}},
pages = {{149--151}},
publisher = {{Elmer Press}},
series = {{Gastroenterology research}},
title = {{The Reverse Red-Green-Blue Rule : A Color-Coded Approach for Simplified Achalasia Diagnosis via High-Resolution Manometry}},
url = {{http://dx.doi.org/10.14740/gr2040}},
doi = {{10.14740/gr2040}},
volume = {{18}},
year = {{2025}},
}