AI in the Identification of Lung Contusions Through Chest Radiological Examination in Blunt Thoracic Trauma

Recruiting now

Conditions studied: Lung Contusion

In brief

The observational study focuses on comparing the interpretation of chest radiological examinations performed using a computer-based system with the standard interpretation conducted by a radiologist. The "LUNIT" system serves as a tool designed to assist radiologists in detecting the 10 most common abnormalities visible on chest radiographs, with proven efficacy in large case series. The investigation addresses the need to evaluate lung injuries resulting from thoracic trauma, which are linked to a higher risk of complications requiring close monitoring to detect potential respiratory failure. The primary aim of the study is to assess the accuracy of the LUNIT system in interpreting chest radiographs for the identification of lung contusions compared to the standard radiologist-based interpretation.

Key facts

Study ID

NCT06777056

Run by

IRCCS Azienda Ospedaliero-Universitaria di Bologna

People needed

135

Starts

2024-12-15

Expected to finish

2025-06-15

Last updated by the study team

2025-01-15

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• Age ≥ 18 years
• Patients presenting to the general Emergency Department of the IRCCS AOU of Bologna between June 1, 2014, and June 1, 2024, for blunt thoracic trauma
• Performance of chest HRCT within 48 hours of standard chest X-ray

You may not qualify if…

• none

Where it is running

• IRCCS Azienda Ospedaliero - Universitaria di Bologna — Bologna, Italy (enrolling)

Full record on ClinicalTrials.gov

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