An In Silico Trial to Evaluate Prospectively the Performance of a Radiomics Algorithm for UIP Compared to Medical Doctors

Maastricht University

Status: Completed

Conditions: Radiomics; Idiopathic Pulmonary Fibrosis; Interstitial Lung Disease

Treatments: Other: Radiomics model to classify between IPF with UIP pattern and ILDs without UIP pattern

Study type: Observational

Funder types: Other

Identifiers

NCT05784207

ISTRU

Details and patient eligibility

About

The purpose of this study is to compare AI performance to doctor's performance in the evaluation of IPF/UIP and ILDs without UIP(proven by biopsy).

Enrollment: 145 patients

Sex: All

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• the availability of non-contrast-enhanced HRCT

Exclusion criteria

• the use of contrast enhancement
• images containing metal or motion artifacts
• Images reconstructed with a slice thickness larger than 1.5 mm

Trial design

145 participants in 4 patient groups

IPF/UIP_CT based

Description:

patients with an ILD and a pathological UIP pattern and a final diagnosis of IPF

Treatment:

Other: Radiomics model to classify between IPF with UIP pattern and ILDs without UIP pattern

IPF/UIP_Biopsy based

Description:

patients with a final diagnosis of IPF but a less typical HRCT pattern( lung biopsy required for the diagnosis)

Treatment:

Other: Radiomics model to classify between IPF with UIP pattern and ILDs without UIP pattern

ILD but not IPF and prove by biopsy not UIP

Description:

patients with an ILD and a pathological non-UIP pattern

Treatment:

Other: Radiomics model to classify between IPF with UIP pattern and ILDs without UIP pattern

Normal

Description:

Normal healthy patients

Treatment:

Other: Radiomics model to classify between IPF with UIP pattern and ILDs without UIP pattern