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RECRUITING
NCT06162884

Single Time Point Prediction as Earlier Diagnosis of Progressive Pulmonary Fibrosis

Sponsor: University of California, Los Angeles

View on ClinicalTrials.gov

Summary

This study is a prospective observational study for subjects with idiopathic pulmonary fibrosis (IPF) or non-IPF interstitial lung diseases (ILD). The purpose of this study is to compare whether imaging patterns from high-resolution computed tomography (HRCT) at baseline can predict worsening. Single Time point Prediction (STP) is a score derived from an artificial intelligenc/ machine learning (AI/ML) using the radiomic features from a HRCT scan that quantifies the imaging patterns of short-term predictive worsening.

Official title: Imaging Signature of Progressive Pulmonary Fibrosis in Idiopathic Pulmonary Fibrosis and Non-IPF Interstitial Lung Diseases

Key Details

Gender

All

Age Range

18 Years - Any

Study Type

OBSERVATIONAL

Enrollment

200

Start Date

2024-11-06

Completion Date

2028-08-19

Last Updated

2025-06-15

Healthy Volunteers

No

Locations (1)

UCLA

Los Angeles, California, United States