Evaluation of the Efficacy of Diagnostic Support Algorithms in Chest X-rays- LuAna Trial
NCT06686251 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 1470
Last updated 2026-02-02
Summary
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.
Conditions
- Consolidation
- Lung Injury
- Pleural Effusion
- Pneumothorax
- Cardiomegaly
- Edema Lung
Interventions
- DEVICE
-
App LuAna
Inclusion of chest x-ray images in the LuAna app to receive feedback on lung findings.
Sponsors & Collaborators
-
Hospital Israelita Albert Einstein
lead OTHER
Principal Investigators
-
Joselisa Paiva, PhD · Hospital Israelita Albert Einstein
Study Design
- Allocation
- NA
- Purpose
- OTHER
- Masking
- NONE
- Model
- SINGLE_GROUP
Eligibility
- Min Age
- 18 Years
- Sex
- ALL
- Healthy Volunteers
- No
Timeline & Regulatory
- Start
- 2026-01-05
- Primary Completion
- 2026-06-30
- Completion
- 2026-12-01
Countries
- Brazil
Study Locations
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