Predicting worsening of pulmonary fibrosis using AI from CT scans

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This observational study aims to predict the progression of idiopathic pulmonary fibrosis (IPF) and non-IP interstitial lung diseases (ILD) by analyzing high-resolution computed tomography (HRCT) scans. Using an artificial intelligence and machine learning approach, the study will derive a Single Time Point Prediction (STP) score from baseline HRCT images to identify patients at risk of worsening disease. Participants will be grouped based on their STP scores, and clinical data such as pulmonary function tests and symptom scores will be collected to validate the predictive capability of the STP score. The study does not involve any intervention and will be conducted at the UCLA ILD Center.

Why it matters

Who can join: the full rules

IPF Inclusion Criteria:

* Established a diagnosis (within 5 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%
* Women of childbearing potential (WOCBP) must be ready and able to use highly effective methods of birth control. WOCBP taking oral contraceptives (OCs) also have to use one barrier method.

Non-IPF ILD Inclusion Criteria:

* Established a diagnosis (within 5 years) of non-IPF ILD by enrolling center.
* Age over or equal to 18 years old
* Presence of chronic fibrosis ILD defined as architectural distortions with reticulation and the presence of traction bronchiectasis by visual assessment: (1) estimating visually \>5% in whole lung, or (2) mild pulmonary fibrosis and \<5% in whole lung (i.e., early non-IPF-ILD identified by a pulmonologist).
* Patients treated with immunosuppressive agents (other than corticosteroids) for an underlying systemic disease need to be on a stable treatment for at least 12 weeks prior to screening
* FVC % predicted \>= 45%
* DLCO % predicted \>=25%
* Women of childbearing potential (WOCBP) must be ready and able to use highly effective methods of birth control. WOCBP taking oral contraceptives (OCs) also have to use one barrier method

Exclusion Criteria:

* Planned to participate in an intervention trial within the next 6 months
* Currently listed for lung transplantation at the time of enrollment
* Malignancy, treated or untreated, other than malignancy unlikely to affect prognosis in the next 3 years such as skin cancer or non-metastatic prostate cancer within the past 5 years
* Any clinically significant co-morbidity, which in the view of investigator, is likely to contribute to mortality or ability to perform PFT's in the next 2 years
* Prebronchodilator Forced Expiratory Volume in 1 second (FEV1)/Forced vital capacity (FVC) \<0.7 at as screening
* 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 for IPF and 5 years for non-IPF ILD (excluding basal cell carcinoma of skin).

HRCT data from subjects with combined pulmonary fibrosis and emphysema (CPFE) can be collected.

Major Discontinuing Criteria in this study

* lung transplant after baseline or death
* withdraw of consent or transition to another care center

Where it's running

• UCLA
  Los Angeles, California, United States Recruiting

Study contacts

• Principal investigator: Samuel Weigt, MD — UCLA Division of Pulmonary, Critical Care, and Hospitals
• Study coordinator: Grace Hyun Kim, PhD
• Email: GraceKim@mednet.ucla.edu
• Phone: (310) 481-7594

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.