Evaluation of a COVID-19 Pneumonia CXR AI Detection Algorithm

Sponsor

Ensemble Group Holdings, LLC (Industry)

Overall Status

Active, not recruiting

CT.gov ID

NCT04561024

Collaborator

(none)

4,000

Enrollment

Location

Anticipated Duration (Months)

399.2

Patients Per Site Per Month

Study Details

Study Description

Brief Summary

This study investigates the diagnostic performance of an AI algorithm in the detection of COVID-19 pneumonia on chest radiographs.

Condition or Disease	Intervention/Treatment	Phase
Covid19	Diagnostic Test: AI model

Detailed Description

This is an international multi-center study. Chest radiographs (CXR) from different participating centers will be collected to develop an AI algorithm to detect COVID-19 pneumonia. This will be tested on external hold out datasets from different centers using SARS-CoV-2 by Real-Time Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) Assay as ground truth.

Study Design

Study Type:

Observational

Anticipated Enrollment :

4000 participants

Observational Model:

Cohort

Time Perspective:

Retrospective

Official Title:

Evaluation of a Chest X-Ray AI Neural Network (RadGen SARS-CoV2 Detection System) for the Detection of RT-PCR Confirmed SARS-Cov2 Covid-19 Pneumonia

Actual Study Start Date :

Mar 1, 2020

Anticipated Primary Completion Date :

Oct 30, 2020

Anticipated Study Completion Date :

Dec 31, 2020

Arms and Interventions

Arm	Intervention/Treatment
RT-PCR Positive Patients RT-PCR confirmed patients positive for SARS-CoV-2	Diagnostic Test: AI model Deep Learning CNN model
Negative patients RT-PCR confirmed patients negative for SARS-CoV-2 or patients with CXR performed before the emergence of COVID-19 pandemic	Diagnostic Test: AI model Deep Learning CNN model

Arm

Intervention/Treatment

RT-PCR Positive Patients

RT-PCR confirmed patients positive for SARS-CoV-2

Diagnostic Test: AI model

Deep Learning CNN model

Negative patients

RT-PCR confirmed patients negative for SARS-CoV-2 or patients with CXR performed before the emergence of COVID-19 pandemic

Diagnostic Test: AI model

Deep Learning CNN model

Outcome Measures

Primary Outcome Measures

Diagnostic Performance of AI model [9 months]
Performance (accuracy, sensitivity, specificity, false-positive rate (FPR), false-negative rate (FNR), and Area Under the Curve (AUC)) of the AI model in detection of COVID-19 pneumonia on their baseline CXR using RT-PCR and historical controls as gold standard in a multi-center / multi-national cohort.

Eligibility Criteria

Criteria

Ages Eligible for Study:

18 Years to 120 Years

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

Yes

Inclusion Criteria:

All adult patients >18 years of age
Attended any of the participating institutes between February 1, 2020 until September, 2020
Underwent both RT-PCR testing and frontal CXR (within 48 hours of PCR testing) for COVID-19 infection
frontal CXR of patients pre-covid pandemic

Exclusion Criteria:

Unavailability of patient demographics and clinical data
Inconclusive RT-PCR results
CXR considered to be of non-diagnostic quality by the clinical radiology research team at each site
CXR not in a retrievable or processable format for AI inference

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	University of Hong Kong	Hong Kong		Hong Kong

Sponsors and Collaborators

Ensemble Group Holdings, LLC

Investigators

None specified.

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.

Responsible Party:

Ensemble Group Holdings, LLC

ClinicalTrials.gov Identifier:

NCT04561024

Other Study ID Numbers:

EN-092020

First Posted:

Sep 23, 2020

Last Update Posted:

Sep 24, 2020

Last Verified:

Sep 1, 2020

Individual Participant Data (IPD) Sharing Statement:

Plan to Share IPD:

Studies a U.S. FDA-regulated Drug Product:

Studies a U.S. FDA-regulated Device Product:

Additional relevant MeSH terms:

COVID-19

Pneumonia

Study Results

No Results Posted as of Sep 24, 2020