Human-AI Collaboration for Ultrasound Diagnosis of Thyroid Nodules - a Clinical Trial
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.
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
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 Type
Study Type
Enrollment (Actual)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Locations
-
-
-
Copenhagen, Denmark, 2100
- Rigshospitalet
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
Description
Medical students
Inclusion Criteria:
- Last year student
Exclusion Criteria:
- Experience with ultrasound beyond that which is taught at the University of Copenhagen
Junior ENT registrar doctors
Inclusion Criteria:
- Doctor enrolled in introductory training as ENT physician.
Senior ENT registrar doctors
Inclusion Criteria:
- Doctor enrolled in ENT training.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: N/A
- Interventional Model: Single Group Assignment
- Masking: None (Open Label)
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Experimental: Experiment
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.
|
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.
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
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.
|
1 day (day of experiment)
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Accuracy of biopsy recommendation
Time Frame: 1 day (day of experiment)
|
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.
|
1 day (day of experiment)
|
|
Nodule measurement
Time Frame: 1 day (day of experiment)
|
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.
|
1 day (day of experiment)
|
|
OSAUS score
Time Frame: 1 day (day of experiment)
|
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.
|
1 day (day of experiment)
|
Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Study Director: Tobias Todsen, Ph.d, Rigshospitalet, Denmark
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Estimated)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- Thyroid AI US operator exp
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
Clinical Trials on Thyroid Nodule
-
NCT06225765RecruitingBenign Thyroid Nodule | Suspicious Malignant Thyroid Nodule
-
NCT07255482Active, not recruitingThyroid Cancer | Thyroid Nodule (Benign) | Thyroid Nodule (Diagnosis)
-
NCT07237373RecruitingBenign Thyroid Nodule
-
NCT07235605Not yet recruiting
-
NCT07625865CompletedBenign Thyroid Nodule
-
NCT05142904TerminatedRadiofrequency Ablation | Thyroid Nodule, Toxic or With Hyperthyroidism | Autonomous Thyroid Function | Thyroid Nodule; Hyperthyroidism | Iodine Hyperthyroidism | Iodine Adverse Reaction
-
NCT05132478CompletedThyroid Cancer | Thyroid Nodule | Benign Thyroid Nodule
-
NCT05758038Not yet recruitingThyroid Nodule (Benign)
-
NCT06014229Active, not recruitingBenign Thyroid Nodule
Clinical Trials on S-Detect for Thyroid
-
NCT02225509UnknownThyroid Cancer | Thyroid Nodule
-
NCT03706534UnknownBreast Cancer | Breast Lesions | Breast Mass
-
NCT05958654RecruitingElder Abuse | Elder Mistreatment
-
NCT02736552Withdrawn
-
NCT07054229RecruitingPapillary Thyroid Microcarcinoma | Microwave Ablation | Contrast-enhanced Ultrasound | Genetic and Molecular Diagnostics
-
NCT05029232Not yet recruitingDuchenne Muscular Dystrophy
-
NCT04313101UnknownICU Acquired Weakness | Thyroid Abnormalities
-
NCT05780047CompletedEnvironmental Exposure | Survey | Health Literacy | Endocrine Disrupting Chemicals | Phthalate Exposure | Bisphenol A
-
NCT06179121Enrolling by invitationCeliac Disease in Children
-
NCT06235814CompletedPapillary Thyroid Cancer