Covid19NCT04561024
Evaluation of a COVID-19 Pneumonia CXR AI Detection Algorithm
An observational study of Covid19, run by Ensemble Group Holdings, LLC at 1 site in Hong Kong.
Trial summary
This study investigates the diagnostic performance of an AI algorithm in the detection of COVID-19 pneumonia on chest radiographs. Read more about this study
- Who is it for?
- Ages 18 to 120 yearsHealthy volunteers can take part
- Conditions the study is for
- Covid19
- What is being tested?
- AI model
- How many people
- 4,000 participants
- Where
- 1 siteHong Kong
- Study dates
- 1 Mar 2020to 31 Dec 2020
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 120 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: There will be three subsets of study population in this study; patients who were 1. RT-PCR confirmed COVID-19 positive 2. RT-PCR confirmed COVID-19 negative 3. either had a diagnosis of pneumonia before the 1st January 2020.
Who may be able to join
- 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
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country.
About this study
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
This study investigates the diagnostic performance of an AI algorithm in the detection of COVID-19 pneumonia on chest radiographs.
Read the 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.
- Conditions
- Covid19
- Being tested
- AI model
- Medical subject headings
- COVID-19
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI modelDiagnostic test
Deep Learning CNN model
| Study group | Role | What they receive |
|---|---|---|
| RT-PCR Positive Patients | RT-PCR confirmed patients positive for SARS-CoV-2 Receives: Diagnostic Test: AI model | |
| Negative patients | RT-PCR confirmed patients negative for SARS-CoV-2 or patients with CXR performed before the emergence of COVID-19 pandemic Receives: Diagnostic Test: AI model |
What is being measured
The primary outcome is the main question the study is designed to answer.
Diagnostic Performance of AI model
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.
Measured: 9 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted23 Sep 2020
- Study start1 Mar 2020
- Primary completion30 Oct 2020 (estimated)
- Study completion31 Dec 2020 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Covid19Studies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 4,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Ensemble Group Holdings, LLC
- Sponsor type
- Industry (pharma, biotech, devices)
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04561024
- Sponsor's protocol ID
- EN-092020
- Status last verified
- Sep 2020
- First submitted
- 22 Sep 2020
- Last updated
- 24 Sep 2020
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 24 Sep 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- 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
- ClinicalTrials.gov ID
- NCT04561024
- Acronym / sponsor ID
- EN-092020
- Conditions
- Covid19
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 4,000 participants (estimated)
- Lead sponsor
- Ensemble Group Holdings, LLCIndustry (pharma, biotech, devices)
- Study start
- 1 Mar 2020 (actual)
- Primary completion
- 30 Oct 2020 (estimated)
- Study completion
- 31 Dec 2020 (estimated)
- First posted
- 23 Sep 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study investigates the diagnostic performance of an AI algorithm in the detection of COVID-19 pneumonia on chest radiographs.
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
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| RT-PCR Positive Patients | – | Diagnostic Test: AI modelRT-PCR confirmed patients positive for SARS-CoV-2 |
| Negative patients | – | Diagnostic Test: AI modelRT-PCR confirmed patients negative for SARS-CoV-2 or patients with CXR performed before the emergence of COVID-19 pandemic |
Who may qualify
- Ages
- 18 to 120 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- There will be three subsets of study population in this study; patients who were 1. RT-PCR confirmed COVID-19 positive 2. RT-PCR confirmed COVID-19 negative 3. either had a diagnosis of pneumonia before the 1st January 2020.
Key inclusion criteria (4 listed)
- 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
Key exclusion criteria (4 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI modelDeep Learning CNN model | Diagnostic test | Negative patients, RT-PCR Positive Patients |
Primary outcome
Diagnostic Performance of AI model
Time frame: 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.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Sep 2020.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Covid19, run by Ensemble Group Holdings, LLC at 1 site in Hong Kong.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 24 Sep 2020. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Hong Kong. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Diagnostic Performance of AI model (time frame: 9 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 Sep 2020.