Thyroid NoduleNCT06306599
Human-AI Collaboration for Ultrasound Diagnosis of Thyroid Nodules - a Clinical Trial
A study testing S-Detect for Thyroid in people with Thyroid Nodule, run by Copenhagen University Hospital, Rigshospitalet at 1 site in Denmark.
Trial summary
This is an experimental study wherein groups of medical students and physicians of varying degrees of experience in head-and-neck ultrasound were asked to scan the same five patients each with a thyroid nodule. Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Thyroid Nodule
- What is being tested?
- S-Detect for Thyroid
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 20 participants
- Where
- 1 siteDenmark
- Study dates
- 1 Sep 2023to 4 Nov 2023
- 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
- Last year student
- Doctor enrolled in introductory training as ENT physician.
- Senior ENT registrar doctors
- Doctor enrolled in ENT training.
Who cannot join
- Experience with ultrasound beyond that which is taught at the University of Copenhagen
- Junior ENT registrar doctors
Trial locations and contacts
1 site in 1 country.
About this study
This is an experimental study wherein groups of medical students and physicians of varying degrees of experience in head-and-neck ultrasound were asked to scan the same five patients each with a thyroid nodule.
The study participants did their own ultrasound assessment of the thyroid nodules, as well as using an AI-based ultrasound diagnostics system.
The researchers intended to study two primary outcomes: 1) how varying degrees of experience in ultrasound by the operator might affect the diagnostic performance of the AI-based system, and 2) how the AI-based system influenced the diagnostic performance of the ultrasound operator.
Read the detailed description
This is a prospective clinical study aiming to test how the experience of the ultrasound operator influences the performance of AI-based (artificial intelligence-based) diagnostics when analysing thyroid nodules on ultrasound scans. The investigators set up an experiment with five stations, each with a patient with a thyroid nodule and an ultrasound machine with the deep learning based system S-Detect for Thyroid installed. 20 study participants where recruited: 8 medical students of novice ultrasound skill, 3 junior ENT (ear-nose-throat) registrars of intermediate ultrasound skill, and 9 senior ENT registrars experienced in ultrasound. The participants scanned all the patients and recorded their analyses of the nodules using the EUTIRADS (European thyroid imagining reporting and data system) system in three different ways: a analysis of their own, S-Detect's analysis, and an analysis combining the two previous.
The hypothesis was that the AI system would perform equally well when between the participant groups. In addition, it was expected that the experienced participants would perform better than the students without AI help, and that the doctors would gain little from AI input, but that the students would have their performance improved by AI input.
- Conditions
- Thyroid Nodule
- Being tested
- S-Detect for Thyroid
- Keywords
- Ultrasound, AI, Thyroid cancer
- Medical subject headings
- Thyroid Nodule, Thyroid Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
S-Detect for ThyroidDiagnostic test
Deep learning based program on Samsung ultrasound machines designed to do real-time semi-automated analysis of thyroid nodules. The ultrasound operator freezes a transverse image of the patient's thyroid nodule and activates S-Detect. The operator selects the nodule on the screen, and the program automatically draws a region of interest. Then S-Detect gives a dichotomous diagnosis of either "Possibly benign" and "Possibly malignant". In addition, it measures the nodule and characterises it with a lexicon based on EUTIRADS.
| Study group | Role | What they receive |
|---|---|---|
| Experiment | Experimental | 20 participants ultrasound scan five patients with thyroid nodules, and assess these nodules themselves, then with the AI-program, and at last they give a combined assessment. Receives: Diagnostic Test: S-Detect for Thyroid |
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy of S-Detect diagnosis
Number of correct thyroid nodule malignancy diagnoses out of total malignancy diagnoses by the AI-based ultrasound diagnostic system "S-Detect" on the five patients' thyroid nodules. Gold standard is cytology and histology of the nodules.
Measured: 1 day (day of experiment)
Secondary outcomes (3)
Accuracy of biopsy recommendation
Number of correct biopsy recommendations on the five patients' thyroid nodules. Recommendation is derived from EUTIRADS analyses done by participants with and without AI assistance. Gold standard is biopsy recommendation derived from expert consensus EUTIRADS assessment of the nodules.
Measured: 1 day (day of experiment)
Nodule measurement
Measurement of the five patients' thyroid nodules done by participants and S-Detect. Gold standard are measurements from expert consensus assessment analysis of the nodules.
Measured: 1 day (day of experiment)
OSAUS score
Mean OSAUS (objective structured assessment of ultrasound skills) scores of participants as assessed from their ultrasound scans of the five patients. Assessment are independently by two head-and-neck ultrasound experts.
Measured: 1 day (day of experiment)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted12 Mar 2024
- Study start1 Sep 2023
- Primary completion4 Nov 2023
- Study completion4 Nov 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Thyroid NoduleStudies 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
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- 20 participants scan five patients over the course of fours hour and collect their diagnostics analyses on paper forms.
- Masking
- None (open label)
- Enrolment
- 20 participants (actual)
Sponsor and investigators
- Lead sponsor
- Copenhagen University Hospital, Rigshospitalet
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Axel Bukhave Edström, Copenhagen University Hospital, Rigshospitalet
- Investigators
- Tobias Todsen, Ph.d, Study director, Copenhagen University Hospital, Rigshospitalet
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06306599
- Sponsor's protocol ID
- Thyroid AI US operator exp
- Status last verified
- Nov 2024
- First submitted
- 23 Feb 2024
- Last updated
- 25 Nov 2024
- Results posted
- 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 25 Nov 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Human-AI Collaboration for Ultrasound Diagnosis of Thyroid Nodules - a Clinical Trial
- ClinicalTrials.gov ID
- NCT06306599
- Acronym / sponsor ID
- Thyroid AI US operator exp
- Conditions
- Thyroid Nodule
- Keywords
- Ultrasound, AI, Thyroid cancer
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 20 participants (actual)
- Lead sponsor
- Copenhagen University Hospital, RigshospitaletUniversity, hospital or other
- Study start
- 1 Sep 2023 (actual)
- Primary completion
- 4 Nov 2023 (actual)
- Study completion
- 4 Nov 2023 (actual)
- First posted
- 12 Mar 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 is an experimental study wherein groups of medical students and physicians of varying degrees of experience in head-and-neck ultrasound were asked to scan the same five patients each with a thyroid nodule.
The study participants did their own ultrasound assessment of the thyroid nodules, as well as using an AI-based ultrasound diagnostics system.
The researchers intended to study two primary outcomes: 1) how varying degrees of experience in ultrasound by the operator might affect the diagnostic performance of the AI-based system, and 2) how the AI-based system influenced the diagnostic performance of the ultrasound operator.
Detailed description
This is a prospective clinical study aiming to test how the experience of the ultrasound operator influences the performance of AI-based (artificial intelligence-based) diagnostics when analysing thyroid nodules on ultrasound scans. The investigators set up an experiment with five stations, each with a patient with a thyroid nodule and an ultrasound machine with the deep learning based system S-Detect for Thyroid installed. 20 study participants where recruited: 8 medical students of novice ultrasound skill, 3 junior ENT (ear-nose-throat) registrars of intermediate ultrasound skill, and 9 senior ENT registrars experienced in ultrasound. The participants scanned all the patients and recorded their analyses of the nodules using the EUTIRADS (European thyroid imagining reporting and data system) system in three different ways: a analysis of their own, S-Detect's analysis, and an analysis combining the two previous.
The hypothesis was that the AI system would perform equally well when between the participant groups. In addition, it was expected that the experienced participants would perform better than the students without AI help, and that the doctors would gain little from AI input, but that the students would have their performance improved by AI input.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- 20 participants scan five patients over the course of fours hour and collect their diagnostics analyses on paper forms.
| Arm | Type | Receives |
|---|---|---|
| Experiment | Experimental | Diagnostic Test: S-Detect for Thyroid20 participants ultrasound scan five patients with thyroid nodules, and assess these nodules themselves, then with the AI-program, and at last they give a combined assessment. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (4 listed)
- Last year student
- Doctor enrolled in introductory training as ENT physician.
- Senior ENT registrar doctors
- Doctor enrolled in ENT training.
Key exclusion criteria (2 listed)
- Experience with ultrasound beyond that which is taught at the University of Copenhagen
- Junior ENT registrar doctors
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 |
|---|---|---|
| S-Detect for ThyroidDeep learning based program on Samsung ultrasound machines designed to do real-time semi-automated analysis of thyroid nodules. The ultrasound operator freezes a transverse image of the patient's thyroid nodule and activates S-Detect. The operator selects the nodule on the screen, and the program automatically draws a region of interest. Then S-Detect gives a dichotomous diagnosis of either "Possibly benign" and "Possibly malignant". In addition, it measures the nodule and characterises it with a lexicon based on EUTIRADS. | Diagnostic test | Experiment |
Primary outcome
Accuracy of S-Detect diagnosis
Time frame: 1 day (day of experiment)
Number of correct thyroid nodule malignancy diagnoses out of total malignancy diagnoses by the AI-based ultrasound diagnostic system "S-Detect" on the five patients' thyroid nodules. Gold standard is cytology and histology of the nodules.
3 secondary outcomes
Accuracy of biopsy recommendation
Time frame: 1 day (day of experiment)
Nodule measurement
Time frame: 1 day (day of experiment)
OSAUS score
Time frame: 1 day (day of experiment)
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 25 Nov 2024.
- 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.
Tobias Todsen, Ph.d study director
Copenhagen University Hospital, Rigshospitalet
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing S-Detect for Thyroid in people with Thyroid Nodule, run by Copenhagen University Hospital, Rigshospitalet at 1 site 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 4 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: finished, as of the sponsor's last update on 25 Nov 2024. 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 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?
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?
Accuracy of S-Detect diagnosis (time frame: 1 day (day of experiment)). 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 25 Nov 2024.