Lung NoduleNCT06597968
Evaluating the Real World Performance of an AI Based Lung Nodule Detection Tool
An observational study of Lung Nodule, run by University Hospitals Cleveland Medical Center at 1 site in United States.
Trial summary
chest x-rays will be analyzed by AI software for a secondary read of lung nodules. Chest x-rays will either be sent to the AI tool to be read or to radiologists to read. If the image is sent to the AI tool, the AI software will generate a report on if it detects a lung nodule or not. Read more about this study
- Who is it for?
- Ages 18 to 89 years
- Conditions the study is for
- Lung Nodule
- What is being tested?
- AI Based CAD Software (qXR-Ln)
- Type of treatment
- Medical device
- How many people
- 44,900 participants
- Where
- 1 siteUnited States
- Study dates
- 24 Jun 2025to 25 Apr 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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 89 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Chest x-rays collected on patients aged 18-89
Who may be able to join
- Chest X-ray images of patients aged 18 - 89 years.
- Modality: CR/DR/DX.
- PA/view
- Lung nodules measuring 6 mm -30 mm (for chest X-ray images where presence of nodules is required).
Who cannot join
- Incomplete view of the chest.
- Lateral view
- Known lung cancer at the time of Chest x-ray images.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Performance Estimation of Triaging Artificial Intelligence Based Computer-Aided Detection Algorithm in Routine Chest Radiography
chest x-rays will be analyzed by AI software for a secondary read of lung nodules. Chest x-rays will either be sent to the AI tool to be read or to radiologists to read. If the image is sent to the AI tool, the AI software will generate a report on if it detects a lung nodule or not. The image will then be sent to a radiologist to determine if there is agreement or disagreement with the AI tool.
Read the detailed description
The study is a prospective study for measuring the performance of an AI software in detecting lung nodules from chest X-rays. Data collected during the study will be analyzed for study purposes after end date of data collection.
There will be two study arms: the control arm and the interventional arm.
Control Arm:
There will be no interruption to the existing standard of care pathway.
Interventional Arm:
Use of AI will occur in parallel to the standard of care pathway.
Consistent with the control Arm, the radiologists or clinicians interpreting the chest x-ray images will proceed as usual based on the existing standard operating procedures of the study site. In addition, the AI software will function as a second reader; meaning images will be processed by the AI software which will generate a report.
In the event that the radiologist and the AI tool do not agree, cases will be reviewed by qualified study team members twice per week.
- Conditions
- Lung Nodule
- Being tested
- AI Based CAD Software (qXR-Ln)
- Keywords
- chest x-ray, CAD software
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI Based CAD Software (qXR-Ln)Device
All x-ray images have already been obtained and will then be run through CAD software for secondary nodule detection
| Study group | Role | What they receive |
|---|---|---|
| Image going through AI tool | these are the images going through the AI tool Receives: Device: AI Based CAD Software (qXR-Ln) | |
| image not going through AI tool | these are the images not going through the AI tool |
What is being measured
The primary outcome is the main question the study is designed to answer.
number of patients with actionable lung nodule as measured by CT scan
Measured: up to one year
total number of patients having chest x-ray
Measured: up to one year
number of patients with high risk lung nodule as measured by CT scan
Measured: up to one year
total number of patients referred for a CT scan
Measured: up to one year
number of lung nodule positive images
Measured: up to one year
number of lung nodule negative images
Measured: up to one year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Sep 2024
- Study start24 Jun 2025
- Primary completion25 Apr 2027 (estimated)
- Study completion25 Apr 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Lung NoduleStudies of the same condition, open and under way.
- More trials run by University Hospitals Cleveland Medical CenterThe sponsor's other registered studies.
- 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
- Prospective
- Enrolment
- 44,900 participants (actual)
Sponsor and investigators
- Lead sponsor
- University Hospitals Cleveland Medical Center
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Amit Gupta, MD, University Hospitals Cleveland Medical Center
- Investigators
- Amit Gupta, MD, Principal investigator, University Hospitals Cleveland Medical Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06597968
- Sponsor's protocol ID
- STUDY20240362
- Status last verified
- Jul 2026
- First submitted
- 12 Sep 2024
- Last updated
- 14 Jul 2026
- 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 14 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Performance Estimation of Triaging Artificial Intelligence Based Computer-Aided Detection Algorithm in Routine Chest Radiography
- ClinicalTrials.gov ID
- NCT06597968
- Acronym / sponsor ID
- STUDY20240362
- Conditions
- Lung Nodule
- Keywords
- chest x-ray, CAD software
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 44,900 participants (actual)
- Lead sponsor
- University Hospitals Cleveland Medical CenterUniversity, hospital or other
- Study start
- 24 Jun 2025 (actual)
- Primary completion
- 25 Apr 2027 (estimated)
- Study completion
- 25 Apr 2027 (estimated)
- First posted
- 19 Sep 2024 (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.
chest x-rays will be analyzed by AI software for a secondary read of lung nodules. Chest x-rays will either be sent to the AI tool to be read or to radiologists to read. If the image is sent to the AI tool, the AI software will generate a report on if it detects a lung nodule or not. The image will then be sent to a radiologist to determine if there is agreement or disagreement with the AI tool.
Detailed description
The study is a prospective study for measuring the performance of an AI software in detecting lung nodules from chest X-rays. Data collected during the study will be analyzed for study purposes after end date of data collection.
There will be two study arms: the control arm and the interventional arm.
Control Arm:
There will be no interruption to the existing standard of care pathway.
Interventional Arm:
Use of AI will occur in parallel to the standard of care pathway.
Consistent with the control Arm, the radiologists or clinicians interpreting the chest x-ray images will proceed as usual based on the existing standard operating procedures of the study site. In addition, the AI software will function as a second reader; meaning images will be processed by the AI software which will generate a report.
In the event that the radiologist and the AI tool do not agree, cases will be reviewed by qualified study team members twice per week.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Image going through AI tool | – | Device: AI Based CAD Software (qXR-Ln)these are the images going through the AI tool |
| image not going through AI tool | – | –these are the images not going through the AI tool |
Who may qualify
- Ages
- 18 to 89 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Chest x-rays collected on patients aged 18-89
Key inclusion criteria (4 listed)
- Chest X-ray images of patients aged 18 - 89 years.
- Modality: CR/DR/DX.
- PA/view
- Lung nodules measuring 6 mm -30 mm (for chest X-ray images where presence of nodules is required).
Key exclusion criteria (3 listed)
- Incomplete view of the chest.
- Lateral view
- Known lung cancer at the time of 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 |
|---|---|---|
| AI Based CAD Software (qXR-Ln)All x-ray images have already been obtained and will then be run through CAD software for secondary nodule detection | Device | Image going through AI tool |
Primary outcome
number of patients with actionable lung nodule as measured by CT scan
Time frame: up to one year
total number of patients having chest x-ray
Time frame: up to one year
number of patients with high risk lung nodule as measured by CT scan
Time frame: up to one year
total number of patients referred for a CT scan
Time frame: up to one year
number of lung nodule positive images
Time frame: up to one year
number of lung nodule negative images
Time frame: up to one year
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 14 Jul 2026.
- 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.
Amit Gupta, MD principal investigator
University Hospitals Cleveland Medical Center
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 Lung Nodule, run by University Hospitals Cleveland Medical Center at 1 site in United States.
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 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: under way, not looking for participants, as of the sponsor's last update on 14 Jul 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 United States. 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?
This study is still under way. Results are not available in the source record yet.
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?
number of patients with actionable lung nodule as measured by CT scan (time frame: up to one year). The study lists 6 primary outcomes in all. 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 14 Jul 2026.