Artificial IntelligenceNCT05594485
Retrospective Study of Carebot AI CXR Performance in Preclinical Practice
An observational study of Artificial Intelligence and Lung Diseases, run by Carebot s.r.o. at 1 site in Czechia.
Trial summary
The purpose of this study is to describe the design, methodology and evaluation of the preclinical test of Carebot AI CXR software, and to provide evidence that the investigated medical device meets user requirements in accordance with its intended use. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Artificial Intelligence, Lung Diseases, Pneumothorax
- What is being tested?
- Carebot AI CXR
- Type of treatment
- Injection or infusion, Medical device
- How many people
- 127 participants
- Where
- 1 siteCzechia
- Study dates
- 15 Aug 2022to 20 Oct 2022
- 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 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: To collect the CXR data for retrospective study, we addressed a municipal hospital in the Czech Republic that provides healthcare services to up to 130,000 residents of a medium-sized city (approximately 70,000 inhabitants) and the surrounding area. 127 anonymized CXR images were collected between August 15 and 17, 2022.
Who may be able to join
- Hospital patients who were referred for chest radiography between August 15 and 17, 2022.
Who cannot join
- Pediatric CXR images (under 18 years of age)
- Scans with technical problems (poor image quality, rotation)
- Images in lateral projection
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Chest X-Ray Abnormality Detection Using Artificial Intelligence: Retrospective Study of Carebot AI CXR Performance in Preclinical Practice
The purpose of this study is to describe the design, methodology and evaluation of the preclinical test of Carebot AI CXR software, and to provide evidence that the investigated medical device meets user requirements in accordance with its intended use. Carebot AI CXR is defined as a recommendation system (classification "prediction") based on computer-aided detection. The software can be used in a preclinical deployment at a selected site before interpretation (prioritization, display of all results and heatmaps) or after interpretation (verification of findings) of CXR images, and in accordance with the manufacturer's recommendations. Given this, a retrospective study is performed to test the clinical effectiveness on existing CXRs.
Read the detailed description
The performance of the trained and internally validated Carebot AI CXR software is tested on a set of 127 CXR images from target population. This is compared to common clinical practice, i.e., image assessment by a radiologist in a hospital. Patients may have a variety of findings; at this stage of the evaluation, an abnormal finding is considered to be an abnormality in any of the defined classes. False negative images incorrectly predicted by Carebot AI CXR software result in a clinical impact determination.
To collect the CXR data for retrospective study, investigators addressed a municipal hospital in the Czech Republic that provides healthcare services to up to 130,000 residents of a medium-sized city (approximately 70,000 inhabitants) and the surrounding area. 127 anonymized CXR images were collected between August 15 and 17, 2022, and subsequently submitted to five independent radiologists of varying experience for annotation. The selected radiologists were asked to assess whether the CXR image shows any of the 12 pre-selected abnormalities. Pediatric CXR images (under 18 years of age), scans with technical problems (poor image quality, rotation), and images in lateral projection were excluded from the dataset.
- Conditions
- Artificial Intelligence, Lung Diseases, Pneumothorax, Pleural Effusion, Cardiomegaly, Lung Cancer
- Being tested
- Carebot AI CXR
- Medical subject headings
- Lung Diseases, Pneumothorax, Pleural Effusion, Cardiomegaly, Lung Neoplasms, Pulmonary Edema, Pneumonia, Pulmonary Atelectasis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Carebot AI CXRDevice
Carebot AI CXR is a deep learning-based software that assists radiologists in the interpretation of chest radiographs in posterior-anterior (PA) or anterior-posterior (AP) projections. The solution with artificial intelligence automatically detects abnormality based on visual patterns for the following findings: atelectasis, consolidation, cardiomegaly, mediastinal widening, pneumoperitoneum, pneumothorax, pulmonary edema, pulmonary lesion, bone fracture, hilar enlargement, subcutaneous emphysema, and pleural effusion.
| Study group | Role | What they receive |
|---|---|---|
| Retrospective collection of DICOM patient files for the period 15-17 August | To collect the CXR data for retrospective study, we addressed a municipal hospital in the Czech Republic that provides healthcare services to up to 130,000 residents of a medium-sized city (approximately 70,000 inhabitants) and the surrounding area. 127 anonymized CXR images were collected between August 15 and 17, 2022, and subsequently submitted to five independent radiologists of varying experience for annotation. The selected radiologists were asked to assess whether the CXR image shows any of the 12 abnormalities mentioned above. Pediatric CXR images (under 18 years of age), scans with technical problems (poor image quality, rotation), and images in lateral projection were excluded from the dataset. Receives: Device: Carebot AI CXR |
What is being measured
The primary outcome is the main question the study is designed to answer.
Primary objective
Comparison of the accuracy of radiologist and Carebot AI CXR image assessment.
Measured: 20-10-2022
Secondary outcomes (1)
Secondary objective
Comparison of the accuracy of radiologis with different experience vs. Carebot AI CXR. Weakness assessment of Carebot AI CXR.
Measured: 20-10-2022
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Oct 2022
- Study start15 Aug 2022
- Primary completion17 Aug 2022
- Study completion20 Oct 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Artificial IntelligenceStudies 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
- 127 participants (actual)
Sponsor and investigators
- Lead sponsor
- Carebot s.r.o.
- Sponsor type
- Industry (pharma, biotech, devices)
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05594485
- Sponsor's protocol ID
- 00001
- Status last verified
- Jul 2023
- First submitted
- 21 Oct 2022
- Last updated
- 13 Jul 2023
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: The results of the retrospective study are used to validate the Carebot AI CXR software for the target population prior to deployment in the workplace.
Study at a glance
From the registry record, last updated by the sponsor on 13 Jul 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Chest X-Ray Abnormality Detection Using Artificial Intelligence: Retrospective Study of Carebot AI CXR Performance in Preclinical Practice
- ClinicalTrials.gov ID
- NCT05594485
- Acronym / sponsor ID
- 00001
- Conditions
- Artificial Intelligence, Lung Diseases, Pneumothorax, Pleural Effusion, Cardiomegaly, Lung Cancer
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 127 participants (actual)
- Lead sponsor
- Carebot s.r.o.Industry (pharma, biotech, devices)
- Study start
- 15 Aug 2022 (actual)
- Primary completion
- 17 Aug 2022 (actual)
- Study completion
- 20 Oct 2022 (actual)
- First posted
- 26 Oct 2022 (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.
The purpose of this study is to describe the design, methodology and evaluation of the preclinical test of Carebot AI CXR software, and to provide evidence that the investigated medical device meets user requirements in accordance with its intended use. Carebot AI CXR is defined as a recommendation system (classification "prediction") based on computer-aided detection. The software can be used in a preclinical deployment at a selected site before interpretation (prioritization, display of all results and heatmaps) or after interpretation (verification of findings) of CXR images, and in accordance with the manufacturer's recommendations. Given this, a retrospective study is performed to test the clinical effectiveness on existing CXRs.
Detailed description
The performance of the trained and internally validated Carebot AI CXR software is tested on a set of 127 CXR images from target population. This is compared to common clinical practice, i.e., image assessment by a radiologist in a hospital. Patients may have a variety of findings; at this stage of the evaluation, an abnormal finding is considered to be an abnormality in any of the defined classes. False negative images incorrectly predicted by Carebot AI CXR software result in a clinical impact determination.
To collect the CXR data for retrospective study, investigators addressed a municipal hospital in the Czech Republic that provides healthcare services to up to 130,000 residents of a medium-sized city (approximately 70,000 inhabitants) and the surrounding area. 127 anonymized CXR images were collected between August 15 and 17, 2022, and subsequently submitted to five independent radiologists of varying experience for annotation. The selected radiologists were asked to assess whether the CXR image shows any of the 12 pre-selected abnormalities. Pediatric CXR images (under 18 years of age), scans with technical problems (poor image quality, rotation), and images in lateral projection were excluded from the dataset.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Retrospective collection of DICOM patient files for the period 15-17 August | – | Device: Carebot AI CXRTo collect the CXR data for retrospective study, we addressed a municipal hospital in the Czech Republic that provides healthcare services to up to 130,000 residents of a medium-sized city (approximately 70,000 inhabitants) and the surrounding area. 127 anonymized CXR images were collected between August 15 and 17, 2022, and subsequently submitted to five independent radiologists of varying experience for annotation. The selected radiologists were asked to assess whether the CXR image shows any of the 12 abnormalities mentioned above. Pediatric CXR images (under 18 years of age), scans with technical problems (poor image quality, rotation), and images in lateral projection were excluded from the dataset. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- To collect the CXR data for retrospective study, we addressed a municipal hospital in the Czech Republic that provides healthcare services to up to 130,000 residents of a medium-sized city (approximately 70,000 inhabitants) and the surrounding area. 127 anonymized CXR images were collected between August 15 and 17, 2022.
Key inclusion criteria (1 listed)
- Hospital patients who were referred for chest radiography between August 15 and 17, 2022.
Key exclusion criteria (3 listed)
- Pediatric CXR images (under 18 years of age)
- Scans with technical problems (poor image quality, rotation)
- Images in lateral projection
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 |
|---|---|---|
| Carebot AI CXRCarebot AI CXR is a deep learning-based software that assists radiologists in the interpretation of chest radiographs in posterior-anterior (PA) or anterior-posterior (AP) projections. The solution with artificial intelligence automatically detects abnormality based on visual patterns for the following findings: atelectasis, consolidation, cardiomegaly, mediastinal widening, pneumoperitoneum, pneumothorax, pulmonary edema, pulmonary lesion, bone fracture, hilar enlargement, subcutaneous emphysema, and pleural effusion. | Device | Retrospective collection of DICOM patient files for the period 15-17 August |
Primary outcome
Primary objective
Time frame: 20-10-2022
Comparison of the accuracy of radiologist and Carebot AI CXR image assessment.
1 secondary outcome
Secondary objective
Time frame: 20-10-2022
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Jul 2023.
- Individual participant dataSharing planned: No. The results of the retrospective study are used to validate the Carebot AI CXR software for the target population prior to deployment in the workplace.
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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 Artificial Intelligence and Lung Diseases, run by Carebot s.r.o. at 1 site in Czechia.
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 1 inclusion and 3 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: finished, as of the sponsor's last update on 13 Jul 2023. 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 Czechia. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
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?
Primary objective (time frame: 20-10-2022). 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 13 Jul 2023.