Evaluation of the Efficacy of Diagnostic Support Algorithms in Chest X-rays- LuAna Trial

This study aims to evaluate whether the use of AI as a physician support tool is associated with an increase in the detection rate of chest radiographic findings in adults with respiratory complaints, compared to diagnosis performed exclusively by doctors, without AI support. This is a cluster-randomized clinical trial, following the stepped wedge design, and adhering to the guidelines of the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT). In this study, the Diagnostic Support Solution for Chest X-rays - LungAnalysis (LuAna), developed by the Hospital Israelita Albert Einstein (HIAE) within the PROADI-SUS Banco de Imagens, was used. The clinical trial will be conducted in multiple centers with a diverse population from the public health system, to ensure that the algorithms are validated across a broad demographic profile. The expected benefits are significant, providing greater security for patients, increasing doctors' confidence in interpreting chest X-rays, promoting efficiency and cost savings for healthcare services, and offering promising prospects for other AI applications in imaging diagnostics.

NCT Number	NCT06686251
Lead Sponsor	Hospital Israelita Albert Einstein
Conditions	Consolidation, Lung Injury, Pleural Effusion, Pneumothorax, Cardiomegaly, Edema Lung
Enrollment	1,470 participants
Start Date	2026-01-05
Primary Completion	2026-06 (estimated)
Study Completion	2026-12-01 (estimated)
Updated on ClinicalTrials.gov	2026-02-02