Abdulrasak Mohammed, Hootak Sohail, Mohrag Mostafa, Someili Ali M
Department of Clinical Sciences, Lund University, 22100 Malmo, Sweden.
Department of Gastroenterology and Nutrition, Skane University Hospital, 21428 Malmo, Sweden.
Gastroenterology Res. 2025 Jun;18(3):149-151. doi: 10.14740/gr2040. Epub 2025 Jun 4.
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.
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.
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.
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.
贲门失弛缓症是一种罕见的食管动力障碍性疾病。诊断需基于病史细节及芝加哥分类法(CCv4.0)推荐的高分辨率测压(HRM)结果进行临床怀疑。解读通过HRM获得的数据可能很复杂,尤其是对于新手用户。
因此,我们提出一种基于颜色的算法,涉及“反向红-绿-蓝(RGB)”规则,作为一种基于通过HRM压力传感器获得的颜色来简化诊断的方法。该规则基于对HRM图形中部主要颜色的简单识别,即对于I型(经典型)贲门失弛缓症,蓝色表示最小压力和无蠕动。在II型(全压型)贲门失弛缓症中,绿色表示食管全段压力升高,而在III型(痉挛型)贲门失弛缓症中,红色表示痉挛性收缩。
我们将此规则作为一个概念框架呈现,尚未进行前瞻性验证,它为处理用于诊断贲门失弛缓症的HRM的临床医生提供了一个直观的工具。
需要进一步研究来评估该规则的诊断准确性,以及将此类规则纳入基于人工智能(AI)的食管动力障碍测压诊断模型的可能性。