Retained Foreign ObjectRFO-AINCT07858162
Prospective Silent Evaluation of AI for Retained Foreign Object Detection
An observational study of Retained Foreign Object, run by University of Colorado, Denver at 1 site in United States.
Trial summary
Retained foreign objects, such as surgical sponges, needles, or instruments, are rare but potentially serious complications of surgery. When there is concern that an object may have been left behind, an intraoperative radiograph may be obtained while the patient is still in the operating room. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Retained Foreign Object
- How many people
- 120 participants
- Where
- 1 siteUnited States
- Study dates
- 1 Feb 2026to 1 Feb 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 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: The study population consists of consecutive adult patients undergoing intraoperative OR count radiography as part of routine clinical care at University of Colorado/UCHealth. Eligible examinations are prospectively identified using institutional OR count imaging protocol labels and processed by the AI system in real time. AI outputs are collected for research purposes only and are not shown to the clinical care team or used to guide patient management.
Who may be able to join
- Age 18 years or older.
- Undergoing intraoperative radiography during routine clinical care for evaluation of a possible retained foreign object.
- Radiographic examination identified using the institutional OR count imaging protocol, including "XR OR COUNT PROTOCOL W/WO POSITIVE CONTROL" or an equivalent institutional protocol label used for OR count imaging during the study period.
Who cannot join
- Radiographic examination lacking usable imaging data.
- Insufficient clinical or imaging information to establish an adequate reference standard for analysis.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United States1 site, 1 recruiting
- Recruiting
University of Colorado Hospital
Aurora, Colorado, 80045
Harrison Bai, 720-516-0637, harrison.bai@cuanschutz.edu
About this study
Official title: Prospective Silent Evaluation of a Real-Time Artificial Intelligence System for Detection of Retained Foreign Objects on Intraoperative Radiographs
Retained foreign objects, such as surgical sponges, needles, or instruments, are rare but potentially serious complications of surgery. When there is concern that an object may have been left behind, an intraoperative radiograph may be obtained while the patient is still in the operating room. These radiographs can be difficult to interpret because of overlapping surgical equipment, patient positioning, and the need for rapid interpretation.
This prospective observational study evaluates an artificial intelligence (AI) system designed to detect retained foreign objects on intraoperative radiographs. Eligible radiographs obtained during routine clinical care will be automatically processed by the AI system in real time for approximately one year. The AI results will not be shown to radiologists, surgeons, or other members of the clinical care team and will not affect patient care.
The study will evaluate how accurately the AI system detects retained foreign objects and how reliably and quickly the system operates in a real-world clinical environment.
Read the detailed description
This is a prospective, non-interventional, silent observational study evaluating the real-world performance and operational feasibility of an artificial intelligence system for detection of retained foreign objects (RFOs) on intraoperative radiographs.
Consecutive eligible OR count radiographs obtained during routine clinical care will be identified using institutional imaging protocol labels and automatically routed from the clinical imaging environment to a secure local research inference system within the institutional firewall. The AI system will process eligible images in real time and generate research outputs, including detection probabilities, localization bounding boxes, and processing timestamps.
The study is conducted in a silent fashion. AI-generated results will not be displayed to interpreting radiologists, surgeons, or other members of the clinical care team and will not be used for clinical decision-making or patient management. No additional imaging, procedure, intervention, or patient contact is required as part of the prospective study.
Reference standards for evaluation of AI performance will be established using available clinical information, including finalized radiology reports, operative documentation, follow-up imaging when available, and expert adjudication of discordant cases when needed.
The study will evaluate standalone AI diagnostic performance using measures including sensitivity, specificity, and area under the receiver operating characteristic curve. Additional measures will evaluate localization performance and operational feasibility, including system latency from image acquisition to availability of the AI output. Exploratory analyses may evaluate performance according to factors such as retained object type, surgical context, and image characteristics.
The prospective evaluation is planned to include approximately 12 months of consecutive eligible examinations and is intended to characterize the performance of the AI system under real-world clinical workflow conditions without influencing clinical care.
- Conditions
- Retained Foreign Object
- Keywords
- Retained Foreign Object, Retained Surgical Item, Retained Foreign Body, Artificial Intelligence, Deep Learning, Object Detection, Intraoperative Radiography, OR Count Radiograph, Surgical Safety
- Medical subject headings
- Foreign Bodies
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Silent AI Analysis of OR Count Radiographs | Eligible OR count radiographs obtained during routine clinical care are automatically processed by an artificial intelligence system designed to detect and localize retained foreign objects. The system generates research outputs including detection probabilities, localization bounding boxes, and processing timestamps. During the prospective silent evaluation, these outputs are not displayed to clinicians and are not used for clinical decision-making or patient management. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Sensitivity of the AI System for Retained Foreign Object Detection
Sensitivity will be calculated as the proportion of reference-standard positive examinations containing a retained foreign object that are correctly identified as positive by the AI system. The reference standard will be established using available clinical information, including finalized radiology reports, operative documentation, follow-up imaging when available, and expert adjudication of discordant cases when needed.
Measured: Through completion of the 12-month prospective study period
Secondary outcomes (4)
Specificity of the AI System for Retained Foreign Object Detection
Specificity will be calculated as the proportion of reference-standard negative examinations without a retained foreign object that are correctly identified as negative by the AI system.
Measured: Through completion of the 12-month prospective study period
Area Under the Receiver Operating Characteristic Curve for RFO Detection
The area under the receiver operating characteristic curve (AUROC) will be calculated using AI-generated detection scores and the reference-standard classification of examinations as positive or negative for a retained foreign object. AUROC ranges from 0 to 1, with higher values indicating greater discrimination between positive and negative examinations.
Measured: Through completion of the 12-month prospective study period
System Latency
System latency will be measured as the elapsed time between availability of an eligible radiographic examination for processing and availability of the corresponding AI output. Latency will be summarized across prospectively processed examinations to evaluate operational feasibility in the real-world clinical workflow.
Measured: Through completion of the 12-month prospective study period
Diagnostic Accuracy of the AI System for Retained Foreign Object Detection
Diagnostic accuracy will be calculated as the proportion of all prospectively evaluated examinations that are correctly classified by the AI system as positive or negative for a retained foreign object compared with the reference standard.
Measured: Through completion of the 12-month prospective study period
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted5 Oct 2026
- Study start1 Feb 2026
- Primary completion1 Feb 2027 (estimated)
- Study completion1 Feb 2027 (estimated)
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 Retained Foreign ObjectStudies of the same condition, open and under way.
- More trials run by University of Colorado, DenverThe 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
- 120 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Colorado, Denver
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07858162
- Sponsor's protocol ID
- 25-2571
- Other IDs
- 25-2571
- Acronym
- RFO-AI
- Status last verified
- Sep 2026
- First submitted
- 29 Sep 2026
- Last updated
- 5 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Hu Y, Wang Y, Acevedo Rodriguez N, et al. SurgRFO: Foundation Model Based Compositional Synthesis of Critical Retained Foreign Objects in Intraoperative Chest X-rays. Medical Image Computing and Computer Assisted Intervention (MICCAI). 2026.
Study at a glance
From the registry record, last updated by the sponsor on 5 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prospective Silent Evaluation of a Real-Time Artificial Intelligence System for Detection of Retained Foreign Objects on Intraoperative Radiographs
- ClinicalTrials.gov ID
- NCT07858162
- Acronym / sponsor ID
- RFO-AI / 25-2571
- Conditions
- Retained Foreign Object
- Keywords
- Retained Foreign Object, Retained Surgical Item, Retained Foreign Body, Artificial Intelligence, Deep Learning, Object Detection, Intraoperative Radiography, OR Count Radiograph
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 120 participants (estimated)
- Lead sponsor
- University of Colorado, DenverUniversity, hospital or other
- Study start
- 1 Feb 2026 (actual)
- Primary completion
- 1 Feb 2027 (estimated)
- Study completion
- 1 Feb 2027 (estimated)
- First posted
- 5 Oct 2026 (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.
Retained foreign objects, such as surgical sponges, needles, or instruments, are rare but potentially serious complications of surgery. When there is concern that an object may have been left behind, an intraoperative radiograph may be obtained while the patient is still in the operating room. These radiographs can be difficult to interpret because of overlapping surgical equipment, patient positioning, and the need for rapid interpretation.
This prospective observational study evaluates an artificial intelligence (AI) system designed to detect retained foreign objects on intraoperative radiographs. Eligible radiographs obtained during routine clinical care will be automatically processed by the AI system in real time for approximately one year. The AI results will not be shown to radiologists, surgeons, or other members of the clinical care team and will not affect patient care.
The study will evaluate how accurately the AI system detects retained foreign objects and how reliably and quickly the system operates in a real-world clinical environment.
Detailed description
This is a prospective, non-interventional, silent observational study evaluating the real-world performance and operational feasibility of an artificial intelligence system for detection of retained foreign objects (RFOs) on intraoperative radiographs.
Consecutive eligible OR count radiographs obtained during routine clinical care will be identified using institutional imaging protocol labels and automatically routed from the clinical imaging environment to a secure local research inference system within the institutional firewall. The AI system will process eligible images in real time and generate research outputs, including detection probabilities, localization bounding boxes, and processing timestamps.
The study is conducted in a silent fashion. AI-generated results will not be displayed to interpreting radiologists, surgeons, or other members of the clinical care team and will not be used for clinical decision-making or patient management. No additional imaging, procedure, intervention, or patient contact is required as part of the prospective study.
Reference standards for evaluation of AI performance will be established using available clinical information, including finalized radiology reports, operative documentation, follow-up imaging when available, and expert adjudication of discordant cases when needed.
The study will evaluate standalone AI diagnostic performance using measures including sensitivity, specificity, and area under the receiver operating characteristic curve. Additional measures will evaluate localization performance and operational feasibility, including system latency from image acquisition to availability of the AI output. Exploratory analyses may evaluate performance according to factors such as retained object type, surgical context, and image characteristics.
The prospective evaluation is planned to include approximately 12 months of consecutive eligible examinations and is intended to characterize the performance of the AI system under real-world clinical workflow conditions without influencing clinical care.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Silent AI Analysis of OR Count Radiographs | – | –Eligible OR count radiographs obtained during routine clinical care are automatically processed by an artificial intelligence system designed to detect and localize retained foreign objects. The system generates research outputs including detection probabilities, localization bounding boxes, and processing timestamps. During the prospective silent evaluation, these outputs are not displayed to clinicians and are not used for clinical decision-making or patient management. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The study population consists of consecutive adult patients undergoing intraoperative OR count radiography as part of routine clinical care at University of Colorado/UCHealth. Eligible examinations are prospectively identified using institutional OR count imaging protocol labels and processed by the AI system in real time. AI outputs are collected for research purposes only and are not shown to the clinical care team or used to guide patient management.
Key inclusion criteria (3 listed)
- Age 18 years or older.
- Undergoing intraoperative radiography during routine clinical care for evaluation of a possible retained foreign object.
- Radiographic examination identified using the institutional OR count imaging protocol, including "XR OR COUNT PROTOCOL W/WO POSITIVE CONTROL" or an equivalent institutional protocol label used for OR count imaging during the study period.
Key exclusion criteria (2 listed)
- Radiographic examination lacking usable imaging data.
- Insufficient clinical or imaging information to establish an adequate reference standard for analysis.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Sensitivity of the AI System for Retained Foreign Object Detection
Time frame: Through completion of the 12-month prospective study period
Sensitivity will be calculated as the proportion of reference-standard positive examinations containing a retained foreign object that are correctly identified as positive by the AI system. The reference standard will be established using available clinical information, including finalized radiology reports, operative documentation, follow-up imaging when available, and expert adjudication of discordant cases when needed.
4 secondary outcomes
Specificity of the AI System for Retained Foreign Object Detection
Time frame: Through completion of the 12-month prospective study period
Area Under the Receiver Operating Characteristic Curve for RFO Detection
Time frame: Through completion of the 12-month prospective study period
System Latency
Time frame: Through completion of the 12-month prospective study period
Diagnostic Accuracy of the AI System for Retained Foreign Object Detection
Time frame: Through completion of the 12-month prospective study period
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 5 Oct 2026.
- BackgroundHu Y, Wang Y, Acevedo Rodriguez N, et al. SurgRFO: Foundation Model Based Compositional Synthesis of Critical Retained Foreign Objects in Intraoperative Chest X-rays. Medical Image Computing and Computer Assisted Intervention (MICCAI). 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.
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 Retained Foreign Object, run by University of Colorado, Denver 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 3 inclusion and 2 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: looking for participants now, as of the sponsor's last update on 5 Oct 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?
Contact Harrison Bai, MD (720-516-0637, harrison.bai@cuanschutz.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Sensitivity of the AI System for Retained Foreign Object Detection (time frame: Through completion of the 12-month prospective study period). 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 NCT07858162, 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 5 Oct 2026.