AI-Assisted Chest X-ray Enhances Diagnosing Achalasia
A new AI-powered approach utilizing plain chest X-rays offers a non-invasive, accurate method for early diagnosis of achalasia, potentially transforming screening and treatment outcomes.
Achalasia is a disorder characterized by impaired movement of the esophagus, leading to symptoms such as difficulty swallowing, food regurgitation, and chest pain. Traditionally, diagnosing this condition involves invasive procedures like upper gastrointestinal endoscopy and high-resolution manometry, which can be uncomfortable for patients.
Recent advancements have introduced the use of plain chest X-ray imaging to identify signs associated with achalasia, such as esophageal dilation, twisting, and fluid retention. However, these radiographic signs are often vague and challenging to interpret accurately.
A groundbreaking development from Osaka Metropolitan University involves an innovative AI model designed to detect achalasia using only standard chest X-rays. Led by Dr. Tadashi Ochiai, Dr. Akinari Sawada, and Associate Professor Daiju Ueda, the research team trained their AI with 207 chest X-rays from 144 patients diagnosed with achalasia and 240 from similar-aged non-achalasia individuals. The model's effectiveness was tested on a separate dataset comprising 17 achalasia and 64 non-achalasia X-rays.
Results demonstrated remarkable accuracy, with the AI achieving an area under the curve (AUC) of 0.964, sensitivity of 94.1%, and specificity of 89.1%. Notably, the AI outperformed experienced physicians in accurately diagnosing the condition based on the same images.
The importance of early diagnosis cannot be overstated, as delays—averaging 6.5 years from symptom onset—can lead to worsening esophageal dilation and reduce treatment effectiveness. In Japan, where chest X-rays are frequently part of routine health checks, this AI tool could serve as a simple, minimally invasive screening method for early detection of achalasia, potentially improving patient outcomes.
The study, published in Clinical Gastroenterology and Hepatology, underscores the potential of AI to revolutionize the diagnostic process for esophageal disorders, facilitating quicker, more accurate, and less invasive diagnoses.
source: https://medicalxpress.com/news/2025-09-achalasia-diagnosis-ai-chest-ray.html
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