Radiologist Diagnostic Performance Versus Artificial Intelligence (AI) (RAVIA)

University Hospital Center (CHU)

Status: Completed

Conditions: Painful Hip; Fonctional Impotence After Minor Trauma (Fall)

Treatments: Procedure: hip standard radiography/ CT scan/ MRI

Study type: Observational

Funder types: Other

Identifiers

NCT04304742

RECHMPL20_0126

Details and patient eligibility

About

In France, femoral neck fracture is mainly detected with interpretation of pelvis/hip X-ray imaging (French Health Authority recommandation).

However, up to 10% of fractures are not identified or misdiagnosed, especially in patients admitted to the emergency department.

Indeed, radiologists may be subject to excessive work, wich cause the risk of inaccurate on X-rays diagnosis.

The Artificial intelligence (AI) begins study the detection of fratures on medical imaging.

In this retropective study, this technology developed by GLEAMER company is tested to evaluate the detection rate of hip fracture and specifically femoral neck fracture, compared to the radiologist diagnostic, in eldery patients admitted in emergency department.

AI could optimize the diagnostic performance of radiologists (increase of confidence level) and improve the efficiency of suspected fractures sorting from emergency department.

Enrollment: 1,000 patients

Sex: All

Ages: 60+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Patients aged 60 and older
• Minor trauma
• Admitted in emergency department for painful hip/fonctional impotence after minor trauma
• Takes at least a hip radiography

Exclusion criteria

• Painful before the minor trauma
• Important trauma

Trial design

1,000 participants in 1 patient group

Suspicion of hip fracture

Description:

Suspicion of hip fracture

Treatment:

Procedure: hip standard radiography/ CT scan/ MRI