PneumothoraxNCT05963945
Multi-Reader Retrospective Study Examining Carebot AI CXR 2.0.21-v2.01 Implementation in Everyday Radiology Clinical Practice
An observational study of Pneumothorax and Pulmonary Nodule, Solitary, run by Carebot s.r.o. at 1 site in Czechia.
Trial summary
The primary objective is to evaluate the performance parameters of the proposed DLAD (Carebot AI CXR) in comparison to individual radiologists. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Pneumothorax, Pulmonary Nodule, Solitary, Atelectasis
- What is being tested?
- Carebot AI CXR
- Type of treatment
- Injection or infusion, Medical device
- How many people
- 956 participants
- Where
- 1 siteCzechia
- Study dates
- 18 Oct 2022to 21 Mar 2023
- 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
- Adult, Older adult
Study population: Patient's Sex Female: 480 (50.21 %) Male: 474 (49.58 %) Unspecified: 2 (0.21 %) Patient's Age 18-30: 58 (6.07 %) 31-50: 163 (17.05 %) 51-70: 366 38.28 %) 70+: 369 (38.60 %)
Who may be able to join
- Hospital patients > 18 years who were referred for chest radiography October 18th, 2022, and November 17th, 2022 at the Radiodiagnostic Department of the Havířov Hospital, p.o.
Who cannot join
- Patients < 18 years
- Chest X-ray images in lateral positions
- Duplicated chest X-ray images
Trial locations and contacts
1 site in 1 country.
About this study
The primary objective is to evaluate the performance parameters of the proposed DLAD (Carebot AI CXR) in comparison to individual radiologists.
Read the detailed description
In the period between October 18th, 2022, and November 17th, 2022, anonymized chest X-ray images of patients were collected at the Radiodiagnostic Department of the Havířov Hospital, p.o. The collection process involved utilizing the CloudPACS imaging and archiving system provided by OR-CZ spol. s r.o.
The collected X-ray images were subjected to the proposed DLAD (Carebot AI CXR) for analysis. Subsequently, the DLAD's performance was compared with the standard clinical practice, where radiologists assessed the CXR images in the simulated hospital setting with access to standard viewing tools (e.g., pan, zoom, WW/WL) and were given an unlimited amount of time to complete the review. Each radiologist determined the presence or absence of 7 indicated radiological findings, including atelectasis (ATE), consolidation (CON), pleural effusion (EFF), pulmonary lesion (LES), subcutaneous emphysema (SCE), cardiomegaly (CMG), and pneumothorax (PNO).
- Conditions
- Pneumothorax, Pulmonary Nodule, Solitary, Atelectasis, Subcutaneous Emphysema, Cardiomegaly, Consolidation
- Being tested
- Carebot AI CXR
- Keywords
- Artificial Intelligence, Computer-Aided Detection, Deep Learning, Chest X-ray, Radiology
- Medical subject headings
- Pneumothorax, Solitary Pulmonary Nodule, Pulmonary Atelectasis, Subcutaneous Emphysema, Cardiomegaly, Pleural Effusion
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Carebot AI CXRDevice
The proposed DLAD (Carebot AI CXR) is a deep learning-based medical device designed to assist radiologists in interpreting chest X-ray images acquired in anteroposterior (AP) or posteroanterior (PA) projection. By employing advanced deep learning algorithms, this solution enables automatic detection of abnormal findings by analyzing visual patterns associated with specific conditions. The targeted abnormalities include atelectasis (ATE), consolidation (CON), pleural effusion (EFF), pulmonary lesion (LES), subcutaneous emphysema (SCE), cardiomegaly (CMG), and pneumothorax (PNO). The DLAD functions as a prediction algorithm complemented by various application peripherals, such as web-based communication tools, DICOM file conversion capabilities, and storage and reporting libraries supporting both DICOM Structured Report and DICOM Presentation State formats.
| Study group | Role | What they receive |
|---|---|---|
| Retrospective collection for the period October 18th, 2022, and November 17th, 2022 | A total of 1,073 chest X-rays were acquired within the specified period at the department. The data collection remained intact and unaffected throughout the testing phase, ensuring the integrity of the dataset. The collected sample accurately represents the prevalence of findings within the observed population. After excluding ineligible studies such as X-rays from patients under 18 years of age, lateral projection X-rays, and scans of insufficient quality, a total of 956 relevant CXRs were identified for further assessment. Receives: Device: Carebot AI CXR |
What is being measured
The primary outcome is the main question the study is designed to answer.
Performance test
The primary objective is to evaluate the performance parameters of the proposed DLAD (Carebot AI CXR) in comparison to individual radiologists. The performance test includes sensitivity and specificity, positive and negative likelihood ratio, and positive and negative predictive value. The aforementioned parameters are statistically compared using confidence intervals (CI) and p-Values. The comparison procedure consists of two steps: a global hypothesis test is conducted to determine whether there are significant differences between DLAD and radiologists. If the global hypothesis test yields a significant result, individual hypothesis tests are performed. Additionally, multiple comparison methods, such as McNemar with continuity correction for Se and Sp, Holm method for LRs, and weighted generalized score statistics for PVs, are applied to control the overall error rate. All tests are performed as two-tailed tests at the 5% significance level.
Measured: March 2023
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Jul 2023
- Study start18 Oct 2022
- Primary completion17 Nov 2022
- Study completion21 Mar 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for PneumothoraxStudies 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
- 956 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
- NCT05963945
- Sponsor's protocol ID
- CB-CXR-01-HA
- Status last verified
- May 2026
- First submitted
- 12 Jul 2023
- Last updated
- 3 Jun 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
KVAK, Daniel, Anna CHROMCOVÁ, Petra OVESNÁ, Jakub DANDÁR, Marek BIROŠ, Robert HRUBÝ, Daniel DUFEK a Marija PAJDAKOVIĆ. Can Deep Learning Reliably Recognize Abnormality Patterns on Chest X-rays? A Multi-Reader Study Examining One Month of AI Implementation in Everyday Radiology Clinical Practice. arXiv. 2023, 2305.10116, 26 s.
Study at a glance
From the registry record, last updated by the sponsor on 3 Jun 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Multi-Reader Retrospective Study Examining Carebot AI CXR 2.0.21-v2.01 Implementation in Everyday Radiology Clinical Practice
- ClinicalTrials.gov ID
- NCT05963945
- Acronym / sponsor ID
- CB-CXR-01-HA
- Conditions
- Pneumothorax, Pulmonary Nodule, Solitary, Atelectasis, Subcutaneous Emphysema, Cardiomegaly, Consolidation
- Keywords
- Artificial Intelligence, Computer-Aided Detection, Deep Learning, Chest X-ray, Radiology
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 956 participants (actual)
- Lead sponsor
- Carebot s.r.o.Industry (pharma, biotech, devices)
- Study start
- 18 Oct 2022 (actual)
- Primary completion
- 17 Nov 2022 (actual)
- Study completion
- 21 Mar 2023 (actual)
- First posted
- 27 Jul 2023 (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 primary objective is to evaluate the performance parameters of the proposed DLAD (Carebot AI CXR) in comparison to individual radiologists.
Detailed description
In the period between October 18th, 2022, and November 17th, 2022, anonymized chest X-ray images of patients were collected at the Radiodiagnostic Department of the Havířov Hospital, p.o. The collection process involved utilizing the CloudPACS imaging and archiving system provided by OR-CZ spol. s r.o.
The collected X-ray images were subjected to the proposed DLAD (Carebot AI CXR) for analysis. Subsequently, the DLAD's performance was compared with the standard clinical practice, where radiologists assessed the CXR images in the simulated hospital setting with access to standard viewing tools (e.g., pan, zoom, WW/WL) and were given an unlimited amount of time to complete the review. Each radiologist determined the presence or absence of 7 indicated radiological findings, including atelectasis (ATE), consolidation (CON), pleural effusion (EFF), pulmonary lesion (LES), subcutaneous emphysema (SCE), cardiomegaly (CMG), and pneumothorax (PNO).
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Retrospective collection for the period October 18th, 2022, and November 17th, 2022 | – | Device: Carebot AI CXRA total of 1,073 chest X-rays were acquired within the specified period at the department. The data collection remained intact and unaffected throughout the testing phase, ensuring the integrity of the dataset. The collected sample accurately represents the prevalence of findings within the observed population. After excluding ineligible studies such as X-rays from patients under 18 years of age, lateral projection X-rays, and scans of insufficient quality, a total of 956 relevant CXRs were identified for further assessment. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- Patient's Sex Female: 480 (50.21 %) Male: 474 (49.58 %) Unspecified: 2 (0.21 %) Patient's Age 18-30: 58 (6.07 %) 31-50: 163 (17.05 %) 51-70: 366 38.28 %) 70+: 369 (38.60 %)
Key inclusion criteria (1 listed)
- Hospital patients > 18 years who were referred for chest radiography October 18th, 2022, and November 17th, 2022 at the Radiodiagnostic Department of the Havířov Hospital, p.o.
Key exclusion criteria (3 listed)
- Patients < 18 years
- Chest X-ray images in lateral positions
- Duplicated chest X-ray images
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 CXRThe proposed DLAD (Carebot AI CXR) is a deep learning-based medical device designed to assist radiologists in interpreting chest X-ray images acquired in anteroposterior (AP) or posteroanterior (PA) projection. By employing advanced deep learning algorithms, this solution enables automatic detection of abnormal findings by analyzing visual patterns associated with specific conditions. The targeted abnormalities include atelectasis (ATE), consolidation (CON), pleural effusion (EFF), pulmonary lesion (LES), subcutaneous emphysema (SCE), cardiomegaly (CMG), and pneumothorax (PNO). The DLAD functions as a prediction algorithm complemented by various application peripherals, such as web-based communication tools, DICOM file conversion capabilities, and storage and reporting libraries supporting both DICOM Structured Report and DICOM Presentation State formats. | Device | Retrospective collection for the period October 18th, 2022, and November 17th, 2022 |
Primary outcome
Performance test
Time frame: March 2023
The primary objective is to evaluate the performance parameters of the proposed DLAD (Carebot AI CXR) in comparison to individual radiologists. The performance test includes sensitivity and specificity, positive and negative likelihood ratio, and positive and negative predictive value. The aforementioned parameters are statistically compared using confidence intervals (CI) and p-Values. The comparison procedure consists of two steps: a global hypothesis test is conducted to determine whether there are significant differences between DLAD and radiologists. If the global hypothesis test yields a significant result, individual hypothesis tests are performed. Additionally, multiple comparison methods, such as McNemar with continuity correction for Se and Sp, Holm method for LRs, and weighted generalized score statistics for PVs, are applied to control the overall error rate. All tests are performed as two-tailed tests at the 5% significance level.
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 3 Jun 2026.
- Results publicationKVAK, Daniel, Anna CHROMCOVÁ, Petra OVESNÁ, Jakub DANDÁR, Marek BIROŠ, Robert HRUBÝ, Daniel DUFEK a Marija PAJDAKOVIĆ. Can Deep Learning Reliably Recognize Abnormality Patterns on Chest X-rays? A Multi-Reader Study Examining One Month of AI Implementation in Everyday Radiology Clinical Practice. arXiv. 2023, 2305.10116, 26 s.
- 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 Pneumothorax and Pulmonary Nodule, Solitary, 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 3 Jun 2026. 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?
Performance test (time frame: March 2023). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05963945, which also lists 1 linked publication.
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 3 Jun 2026.