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

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).

Study Overview

• Status: Completed
• Conditions: Idiopathic Pulmonary Fibrosis; Interstitial Lung Disease; Radiomics
• Intervention / Treatment: Other: Radiomics model to classify between IPF with UIP pattern and ILDs without UIP pattern

• Study Type: Observational
• Enrollment (Actual): 145

Contacts and Locations

Study Locations

• Netherlands
  • Limburg
    • Maastricht, Limburg, Netherlands, 6229ER
      • Maastricht University

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

Patients who had HRCT and shown IPF/UIP in CT images, or patients who is suspected to have IPF based on MMD and proved by lung biopsy.

Description

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

Study Plan

How is the study designed?

Number of groups / cohorts

4

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
IPF/UIP_CT based; patients with an ILD and a pathological UIP pattern and a final diagnosis of IPF	Other: Radiomics model to classify between IPF with UIP pattern and ILDs without UIP pattern; The aim is to evaluate the performance of AI with the performance of doctors
IPF/UIP_Biopsy based; patients with a final diagnosis of IPF but a less typical HRCT pattern( lung biopsy required for the diagnosis)	Other: Radiomics model to classify between IPF with UIP pattern and ILDs without UIP pattern; The aim is to evaluate the performance of AI with the performance of doctors
ILD but not IPF and prove by biopsy not UIP; patients with an ILD and a pathological non-UIP pattern	Other: Radiomics model to classify between IPF with UIP pattern and ILDs without UIP pattern; The aim is to evaluate the performance of AI with the performance of doctors
Normal; Normal healthy patients	Other: Radiomics model to classify between IPF with UIP pattern and ILDs without UIP pattern; The aim is to evaluate the performance of AI with the performance of doctors

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The performance of Radiomics algorithm compared to the ground truth	Reporting the performance measure: accuracy	May 2021

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Comparing the performance of the radiomics algorithm to that of physicians	Correctness of the diagnosis - the most probable thin-section pattern (dichotomous outcome: yes or no)	June 2021

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Comparing the performance of radiomics algorithm to that of individual doctor	Correctness of the diagnosis - the most probable thin-section pattern (dichotomous outcome: yes or no)	June 2021
Comparing the reproducibility of diagnosis between the doctors	Measuring the concordance in diagnosis in between the physicians, and for each physician separately, using the Concordance correlation coefficient.	June 2021

Collaborators and Investigators

• Sponsor: Maastricht University

Study record dates

Study Major Dates

• Study Start (Actual): June 1, 2017
• Primary Completion (Actual): December 30, 2021
• Study Completion (Actual): December 30, 2021

Study Registration Dates

• First Submitted: May 19, 2021
• First Submitted That Met QC Criteria: March 14, 2023
• First Posted (Actual): March 24, 2023

Study Record Updates

• Last Update Posted (Actual): March 24, 2023
• Last Update Submitted That Met QC Criteria: March 14, 2023
• Last Verified: March 1, 2023

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Respiratory Tract Diseases; Lung Diseases; Pulmonary Fibrosis; Idiopathic Pulmonary Fibrosis; Lung Diseases, Interstitial
• Other Study ID Numbers: ISTRU

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No