HealthyNCT06371859
Human-AI Collaborative Intelligence for Improving Fetal Flow Management
A study testing "XAI feedback on MCA/UA Doppler spectral curves and gate placement suggestions" in people with Healthy, run by Copenhagen University Hospital, Rigshospitalet at 2 sites in Denmark.
Trial summary
This randomized controlled study evaluates the effectiveness of explainable AI (XAI) in improving clinicians' interpretation of Doppler ultrasound images (UA and MCA) in obstetrics. It involves 92 clinicians, randomized into intervention and control groups. Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Healthy
- What is being tested?
- "XAI feedback on MCA/UA Doppler spectral curves and gate placement suggestions"
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 92 participants
- Where
- 2 sitesDenmark
- Study dates
- 29 Apr 2024to 1 Dec 2025
- Phase
- Interventional
- 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 Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Who may be able to join
- The inclusion criterion is the use of ultrasound at least once per week
Who cannot join
- The exclusion criterion is the absence of experience in ultrasound scanning.
Trial locations and contacts
2 sites in 1 country.
Denmark2 sites, 2 recruiting
- Recruiting
Rigshospitalet
Copenhagen, Capital Region of Denmark, 2100
Zahra Bashir, MD
Zahra Bashir, MD
- Recruiting
Slagelse Hospital
Slagelse, Region Sjælland, 4200
Zahra Bashir, MD
Zahra Bashir, MD
About this study
Official title: Human-AI Collaborative Intelligence for Improving Fetal Flow Management: A Randomized Trial
This randomized controlled study evaluates the effectiveness of explainable AI (XAI) in improving clinicians' interpretation of Doppler ultrasound images (UA and MCA) in obstetrics. It involves 92 clinicians, randomized into intervention and control groups. The intervention group receives XAI feedback, aiming to enhance accuracy in ultrasound interpretation and medical decision-making.
Objectives:
- To develop an interpretable model for commonly used Doppler flows, specifically the Pulsatility Index (PI) of the umbilical artery (UA) and middle cerebral artery (MCA), with the aim to provide quality feedback on Doppler spectrum images and suggest potential gate placements.
- To test the effects of providing Explainable AI (XAI)-feedback for clinicians compared with no feedback on their accuracy in ultrasound interpretation and management.
Read the detailed description
Currently, Doppler ultrasound velocimetry serves as a crucial tool in obstetric practice, particularly for assessing the umbilical artery (UA) and middle cerebral artery (MCA) in uteroplacental-fetal circulation. While Doppler ultrasound is valuable for detecting conditions like fetal anemia and placental insufficiency, its accuracy relies on operator expertise. Artificial intelligence (AI) offers potential enhancements, especially in high-risk pregnancies. However, existing AI applications in fetal ultrasound often lack transparency, leading to user distrust. This study aims to address these limitations by developing an explainable AI model to assist clinicians in interpreting Doppler ultrasound images of UA and MCA for improved management of high-risk pregnancies.
The study's objectives are:
- To develop an interpretable model for commonly used Doppler flows, specifically the Pulsatility Index (PI) of the umbilical artery (UA) and middle cerebral artery (MCA), with the aim to provide quality feedback on Doppler spectrum images and suggest potential gate placements.
- To test the effects of providing Explainable AI (XAI)-feedback for clinicians compared with no feedback on their accuracy in ultrasound interpretation and management.
All participants will be instructed to provide gate placement for flow images of the umbilical artery and the MCA, and to evaluate the quality of the resulting flow curves. Each participant will be required to evaluate a total of 40 unique images (10 flow images for UA and MCA, 10 spectral doppler images for UA and MCA, respectively). From the four groups (UA-flow, UA-spectrum, MCA-flow \& MCA-spectrum) the investigators will provide matched sets of 40 images that are provided to participants, who are matched for their level of experience within each hospital (PGY 1-2; PGY 3-5; board certified Obstetricians). For flow images, the participants will be instructed to identify the most appropriate gate placement. For the spectral flow curves, participants will be asked to evaluate whether the flow curves were of sufficient quality to inform medical management decisions.
The inclusions criteria for MCA and UA images will be images taken from the third trimester (>= week 28).
Study Design: Randomized controlled trial
Data Source: 1840 unique ultrasound scans including umbilical artery (UA) and middle cerebral artery (MCA) measurements. The 1840 unique images includes: 460 images of UA-flow images, 460 UA-spectrum images, 460 MCA-flow images and 460 MCA-spectrum images.
Participants: 92 clinicians with varying competence levels across four different university hospitals.
Intervention: XAI feedback on MCA/UA Doppler spectral curves and gate placement suggestions.
Control Group: No XAI feedback.
Procedure: Clinicians will be divided into two groups of 46 each, matched for experience levels across hospitals. The control group will place a gate on MCA/UA images and evaluate the Doppler spectrum without AI feedback, while the intervention group will perform the same tasks with access to AI feedback.
Outcome Measures: The participants' responses in the two groups are reviewed by two fetal medicine sonographers who evaluate the participants' answers independently of each other. In a disagreement, the two sonographers reach a consensus after discussion.
- Conditions
- Healthy
- Being tested
- "XAI feedback on MCA/UA Doppler spectral curves and gate placement suggestions"
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
"XAI feedback on MCA/UA Doppler spectral curves and gate placement suggestions"Behavioural
This study includes 1840 ultrasound images, split into UA and MCA flow and spectrum images, each duplicated for a total of 3680 images to compare explainable AI (XAI) feedback vs. no feedback. The investigators will provide matched sets of 40 images (one for the XAI group and one for the non-XAI group) to participants. Participants are matched based on their level of experience within each hospital (Resident physicians, obstetricians, and gynecologists with obstetric ultrasound experience).
All participants are instructed to place gates on the flow images of the umbilical artery and the middle cerebral artery and to assess the quality of the resulting flow curves. Specifically, for flow images, participants must identify the most appropriate gate placement. For spectral flow curves, they are to decide if the curves are of sufficient quality to guide medical management decisions.
| Study group | Role | What they receive |
|---|---|---|
| "XAI feedback on MCA/UA Doppler spectral curves and gate placement suggestions" | Experimental | The XAI feedback group will place a gate on MCA/UA images and evaluate the Doppler spectrum with AI feedback.
N=46 clinicians (Clinicians will be divided into two groups (XAI feedback \& No XAI feedback groups) of 46 each, matched for experience levels across hospitals) Receives: Behavioral: "XAI feedback on MCA/UA Doppler spectral curves and gate placement suggestions" |
| "No XAI feedback" | No intervention | The control group will place a gate on MCA/UA images and evaluate the Doppler spectrum without AI feedback. N=46 clinicians (Clinicians will be divided into two groups (XAI feedback \& No XAI feedback groups) of 46 each, matched for experience levels across hospitals) |
What is being measured
The primary outcome is the main question the study is designed to answer.
Responses will be reviewed independently by two fetal medicine sonographers, and in case of disagreement between the two experts, a consensus will be reached.
The accuracy in each group (AI-feedback and without AI-feedback group) was defined as the percentage difference in the number of correctly managed flow images between the two groups, assessed by two fetal medicine sonographers.
Correct management was defined as: Correct gate placement (multiple sites possible) AND Correct identification of flow curves that were of adequate quality to allow medical decision-making.
Measured: 1 months
Secondary outcomes (1)
Accuracy of flow image management among competence groups
The secondary outcome is to categorize participants into competence groups (trainees, obstetricians, and gynecologists with obstetric experience) and then examine the percentage difference in the accuracy of flow image management among these competence groups within both the AI-feedback and the non-AI-feedback groups.
Measured: 1 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 Apr 2024
- Study start29 Apr 2024
- Primary completion1 Dec 2024 (estimated)
- Study completion1 Dec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for HealthyStudies of the same condition, open and under way.
- More trials run by Copenhagen University Hospital, RigshospitaletThe 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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- Randomized controlled trial
- Masking
- Double blind
- Who is masked
- Participant, Investigator
- Enrolment
- 92 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Copenhagen University Hospital, Rigshospitalet
- Sponsor type
- University, hospital or other
- Collaborators
- Slagelse Hospital, Technical University of Denmark
- Responsible party
- Principal investigator, Zahra Bashir, Copenhagen University Hospital, Rigshospitalet
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06371859
- Sponsor's protocol ID
- 3-3031-2915/1
- Status last verified
- May 2024
- First submitted
- 9 May 2023
- Last updated
- 6 May 2024
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 6 May 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Human-AI Collaborative Intelligence for Improving Fetal Flow Management: A Randomized Trial
- ClinicalTrials.gov ID
- NCT06371859
- Acronym / sponsor ID
- 3-3031-2915/1
- Conditions
- Healthy
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 92 participants (estimated)
- Lead sponsor
- Copenhagen University Hospital, RigshospitaletUniversity, hospital or other
- Collaborators
- Slagelse Hospital, Technical University of Denmark
- Study start
- 29 Apr 2024 (actual)
- Primary completion
- 1 Dec 2024 (estimated)
- Study completion
- 1 Dec 2025 (estimated)
- First posted
- 17 Apr 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.
This randomized controlled study evaluates the effectiveness of explainable AI (XAI) in improving clinicians' interpretation of Doppler ultrasound images (UA and MCA) in obstetrics. It involves 92 clinicians, randomized into intervention and control groups. The intervention group receives XAI feedback, aiming to enhance accuracy in ultrasound interpretation and medical decision-making.
Objectives:
- To develop an interpretable model for commonly used Doppler flows, specifically the Pulsatility Index (PI) of the umbilical artery (UA) and middle cerebral artery (MCA), with the aim to provide quality feedback on Doppler spectrum images and suggest potential gate placements.
- To test the effects of providing Explainable AI (XAI)-feedback for clinicians compared with no feedback on their accuracy in ultrasound interpretation and management.
Detailed description
Currently, Doppler ultrasound velocimetry serves as a crucial tool in obstetric practice, particularly for assessing the umbilical artery (UA) and middle cerebral artery (MCA) in uteroplacental-fetal circulation. While Doppler ultrasound is valuable for detecting conditions like fetal anemia and placental insufficiency, its accuracy relies on operator expertise. Artificial intelligence (AI) offers potential enhancements, especially in high-risk pregnancies. However, existing AI applications in fetal ultrasound often lack transparency, leading to user distrust. This study aims to address these limitations by developing an explainable AI model to assist clinicians in interpreting Doppler ultrasound images of UA and MCA for improved management of high-risk pregnancies.
The study's objectives are:
- To develop an interpretable model for commonly used Doppler flows, specifically the Pulsatility Index (PI) of the umbilical artery (UA) and middle cerebral artery (MCA), with the aim to provide quality feedback on Doppler spectrum images and suggest potential gate placements.
- To test the effects of providing Explainable AI (XAI)-feedback for clinicians compared with no feedback on their accuracy in ultrasound interpretation and management.
All participants will be instructed to provide gate placement for flow images of the umbilical artery and the MCA, and to evaluate the quality of the resulting flow curves. Each participant will be required to evaluate a total of 40 unique images (10 flow images for UA and MCA, 10 spectral doppler images for UA and MCA, respectively). From the four groups (UA-flow, UA-spectrum, MCA-flow \& MCA-spectrum) the investigators will provide matched sets of 40 images that are provided to participants, who are matched for their level of experience within each hospital (PGY 1-2; PGY 3-5; board certified Obstetricians). For flow images, the participants will be instructed to identify the most appropriate gate placement. For the spectral flow curves, participants will be asked to evaluate whether the flow curves were of sufficient quality to inform medical management decisions.
The inclusions criteria for MCA and UA images will be images taken from the third trimester (>= week 28).
Study Design: Randomized controlled trial
Data Source: 1840 unique ultrasound scans including umbilical artery (UA) and middle cerebral artery (MCA) measurements. The 1840 unique images includes: 460 images of UA-flow images, 460 UA-spectrum images, 460 MCA-flow images and 460 MCA-spectrum images.
Participants: 92 clinicians with varying competence levels across four different university hospitals.
Intervention: XAI feedback on MCA/UA Doppler spectral curves and gate placement suggestions.
Control Group: No XAI feedback.
Procedure: Clinicians will be divided into two groups of 46 each, matched for experience levels across hospitals. The control group will place a gate on MCA/UA images and evaluate the Doppler spectrum without AI feedback, while the intervention group will perform the same tasks with access to AI feedback.
Outcome Measures: The participants' responses in the two groups are reviewed by two fetal medicine sonographers who evaluate the participants' answers independently of each other. In a disagreement, the two sonographers reach a consensus after discussion.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (participant, investigator)
- Number of arms
- 2
- Model description
- Randomized controlled trial
| Arm | Type | Receives |
|---|---|---|
| "XAI feedback on MCA/UA Doppler spectral curves and gate placement suggestions" | Experimental | Behavioral: "XAI feedback on MCA/UA Doppler spectral curves and gate placement suggestions"The XAI feedback group will place a gate on MCA/UA images and evaluate the Doppler spectrum with AI feedback. N=46 clinicians (Clinicians will be divided into two groups (XAI feedback \& No XAI feedback groups) of 46 each, matched for experience levels across hospitals) |
| "No XAI feedback" | No intervention | –The control group will place a gate on MCA/UA images and evaluate the Doppler spectrum without AI feedback. N=46 clinicians (Clinicians will be divided into two groups (XAI feedback \& No XAI feedback groups) of 46 each, matched for experience levels across hospitals) |
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (1 listed)
- The inclusion criterion is the use of ultrasound at least once per week
Key exclusion criteria (1 listed)
- The exclusion criterion is the absence of experience in ultrasound scanning.
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 |
|---|---|---|
| "XAI feedback on MCA/UA Doppler spectral curves and gate placement suggestions"This study includes 1840 ultrasound images, split into UA and MCA flow and spectrum images, each duplicated for a total of 3680 images to compare explainable AI (XAI) feedback vs. no feedback. The investigators will provide matched sets of 40 images (one for the XAI group and one for the non-XAI group) to participants. Participants are matched based on their level of experience within each hospital (Resident physicians, obstetricians, and gynecologists with obstetric ultrasound experience). All participants are instructed to place gates on the flow images of the umbilical artery and the middle cerebral artery and to assess the quality of the resulting flow curves. Specifically, for flow images, participants must identify the most appropriate gate placement. For spectral flow curves, they are to decide if the curves are of sufficient quality to guide medical management decisions. | Behavioural | "XAI feedback on MCA/UA Doppler spectral curves and gate placement suggestions" |
Primary outcome
Responses will be reviewed independently by two fetal medicine sonographers, and in case of disagreement between the two experts, a consensus will be reached.
Time frame: 1 months
The accuracy in each group (AI-feedback and without AI-feedback group) was defined as the percentage difference in the number of correctly managed flow images between the two groups, assessed by two fetal medicine sonographers. Correct management was defined as: Correct gate placement (multiple sites possible) AND Correct identification of flow curves that were of adequate quality to allow medical decision-making.
1 secondary outcome
Accuracy of flow image management among competence groups
Time frame: 1 months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 May 2024.
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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.
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing "XAI feedback on MCA/UA Doppler spectral curves and gate placement suggestions" in people with Healthy, run by Copenhagen University Hospital, Rigshospitalet at 2 sites in Denmark.
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 1 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 6 May 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Denmark. 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?
Contact Zahra Bashir, MD (71871407, zahra.bashir@regionh.dk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Responses will be reviewed independently by two fetal medicine sonographers, and in case of disagreement between the two experts, a consensus will be reached. (time frame: 1 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 6 May 2024.