AI-Assisted Chest X-Ray for Misplaced Endotracheal and Nasogastric Tubes and Pneumothorax in Emergency and Critical Care Settings

March 15, 2026 updated by: National Taiwan University Hospital

Clinical Effectiveness and Cost-Effectiveness of Real-Time Chest X-Ray Computer-Aided Detection System for Misplaced Endotracheal and Nasogastric Tubes and Pneumothorax in Emergency and Critical Care Settings

Background Advancements in artificial intelligence (AI) have driven significant breakthroughs in computer-aided detection (CAD) for chest X-ray imaging. National Taiwan University Hospital (NTUH) research team previously developed an AI-based emergency Capstone CXR system (MOST 111-2634-F-002-015-, Capstone project), which led to the creation of a chest X-ray module. This chest X-ray module has an established model supported by extensive research and is ready for direct application in clinical trials without requiring additional model training. This study will utilize three submodules of the system: detection of misplaced endotracheal tubes, detection of misplaced nasogastric tubes, and identification of pneumothorax.

Objective This study aims to apply a real-time chest X-ray CAD system in emergency and critical care settings to evaluate its clinical and economic benefits without requiring additional chest X-ray examinations or altering standard care and procedures. The study will evaluate the CAD system's impact on mortality reduction, post-intubation complications, hospital stay duration, workload, and interpretation time, alongside a cost-effectiveness comparison with standard care.

Methods This study adopts a pilot trial and cluster randomized controlled trial design, with random assignment conducted at the ward level. In the intervention group, units are granted access to AI diagnostic results, while the control group continues standard care practices. Consent will be obtained from attending physicians, residents, and advanced practice nurses in each participating ward. Once consent is secured, these healthcare providers in the intervention group will be authorized to use the CAD system. Intervention units will have access to AI-generated interpretations, whereas control units will maintain routine medical procedures without access to the AI diagnostic outputs.

Results The study was funded in September 2024. Data collection is expected to last from January 2025 to December 2027.

Conclusions This study anticipates that the real-time chest X-ray CAD system will automate the identification and detection of misplaced endotracheal and nasogastric tubes on chest X-rays, as well as assist clinicians in diagnosing pneumothorax. By reducing the workload of physicians, the system is expected to shorten the time required to detect tube misplacement and pneumothorax, decrease patient mortality and hospital stays, and ultimately lower healthcare costs.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Estimated)

10900

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Taiwan
    • Taiwan
      • Taipei, Taiwan, Taiwan, 100225
        • National Taiwan University Hospital
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria for units:

  • Emergency critical care or intensive care units.
  • The units included the patients requiring chest X-rays due to endotracheal intubation, nasogastric tube insertion, or ventilator use with a risk of pneumothorax.

Exclusion Criteria for units:

  • The unit supervisor doesn't agree to participate in the trial.
  • The unit is unable to implement the AI-assisted system (e.g., no data connection or system support).

Inclusion Criteria for Patients:

● Patients who are adults and require chest X-ray due to one of the following conditions: endotracheal intubation, nasogastric intubation, or the use of a ventilator with the potential to cause pneumothorax.

Exclusion Criteria for Patients: Patients in isolation wards or pediatric

  • Patients in isolation wards.
  • Patients in Infant Intensive Care Unit

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Intervention
Other: AI-assisted model
physicians will be authorized to access the AI model's predictions during patient care as an additional decision-making reference. These predictions will be generated in seconds and can help identify issues such as tube misplacement (e.g., nasogastric tube, endotracheal tube) and pneumothorax through AI analysis of CXRs, which will alert the physician to review the images.
No Intervention: standard clinical practice

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
In-hospital Mortality
Time Frame: During the hospital stay, an average of 1 week
The patient's survival is monitored after undergoing a chest X-ray until hospital discharge.
During the hospital stay, an average of 1 week

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Length of Hospital Stay
Time Frame: During the hospital stay, an average of 1 week
The time a patient spends in the hospital from admission to discharge, usually measured in days.
During the hospital stay, an average of 1 week
Misplacement Detection Time
Time Frame: During the hospital stay, an average of 1 week
Evaluates whether the AI system can reduce the time to detect misplaced catheters or pneumothorax, thereby improving the timeliness of clinical intervention.
During the hospital stay, an average of 1 week

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

National Taiwan University Hospital

Collaborators

Min-Sheng General Hospital
National Taiwan University
Fu Jen Catholic University Hospital

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

April 1, 2026

Primary Completion (Estimated)

December 31, 2027

Study Completion (Estimated)

December 31, 2027

Study Registration Dates

First Submitted

February 12, 2025

First Submitted That Met QC Criteria

February 18, 2025

First Posted (Actual)

February 24, 2025

Study Record Updates

Last Update Posted (Actual)

March 17, 2026

Last Update Submitted That Met QC Criteria

March 15, 2026

Last Verified

March 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 202412055DINA

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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