Single Time Point Prediction as Earlier Diagnosis of Progressive Pulmonary Fibrosis

Description

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.

Conditions

Pulmonary Fibrosis

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Study Overview

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Study Details

Study overview

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.

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

Single Time Point Prediction as Earlier Diagnosis of Progressive Pulmonary Fibrosis

Condition
Pulmonary Fibrosis
Intervention / Treatment

-

Contacts and Locations

Los Angeles

UCLA, Los Angeles, California, United States, 90024

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

For general information about clinical research, read Learn About Studies.

Eligibility Criteria

  • * Established a diagnosis (within 3 years) of IPF by enrolling center as defined by ATS/ERS/JRS/ALAT criteria
  • * Age over or equal to 40 years old
  • * No history of lung transplant
  • * FVC % predicted \>= 45%
  • * DLCO % predicted \>=25%
  • * Planned to participate in an intervention trial within the next 3 months
  • * Currently listed for lung transplantation at the time of enrollment
  • * Malignancy, treated or untreated, other than skin cancer or prostate cancer within the past 5 years
  • * Exclusion of co-morbidities: congestive heart failure (stroke, deep vein thrombosis, pulmonary embolism, myocardial infarction), current virus-associated community acquired pneumonia, smoking-related chronic obstructive lung disease with FEV1 \< 70%, history of lung cancer, history of other cancer treated within the past 4 years (excluding basal cell carcinoma of skin).
  • * lung transplant after baseline or death
  • * withdraw of consent or transition to another care center

Ages Eligible for Study

18 Years to

Sexes Eligible for Study

ALL

Accepts Healthy Volunteers

No

Collaborators and Investigators

University of California, Los Angeles,

Samuel Weigt, MD, PRINCIPAL_INVESTIGATOR, UCLA Division of Pulmonary, Critical Care, and Hospitals

Jonathan Goldin, MD, PRINCIPAL_INVESTIGATOR, Radiological Sciences at the University of California, Los Angeles

Study Record Dates

2028-08-19