To Evaluate the Use of Radiomics to Classify Between Idiopathic Pulmonary Fibrosis and Interstitial Lung Disease

Maastricht University

Status: Completed

Conditions: Usual Interstitial Pneumonia; Idiopathic Pulmonary Fibrosis; Interstitial Lung Disease

Treatments: Diagnostic Test: radiomics

Study type: Observational

Funder types: Other

Identifiers

NCT04430491

RESPIRE_2019

Details and patient eligibility

About

To investigate the ability of machine learning models based on radiomic features extracted from thin-section CT images to differentiate IPF patients from non-IPF interstitial lung diseases.

Enrollment: 300 patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• UIP with final diagnosis in biopsy
• ILDs with final diagnosis in biopsy

Exclusion criteria

• patients with no biopsy confirmation

Trial design

300 participants in 2 patient groups

Training dataset

Description:

No interventions

Treatment:

Diagnostic Test: radiomics

Validation dataset

Description:

No interventions

Treatment:

Diagnostic Test: radiomics