Human-AI Collaboration for Ultrasound Diagnosis of Thyroid Nodules - a Clinical Trial

NCT06306599 | Completed

• 1 other identifier: Thyroid AI US operator exp
• Study Type: interventional
• Target: 20
• Locations: 1 country
• Sites: 1

Brief 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. 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.

Conditions

Thyroid Nodule

Keywords

Ultrasound; AI; Thyroid cancer

Outcome Measures

Primary Outcomes (1)

• 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.

  1 day (day of experiment)

Secondary Outcomes (3)

• Accuracy of biopsy recommendation

  1 day (day of experiment)

• Nodule measurement

  1 day (day of experiment)

• OSAUS score

  1 day (day of experiment)

Study Arms (1)

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.

Diagnostic Test: S-Detect for Thyroid

Interventions

S-Detect for Thyroid DIAGNOSTIC_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.

Experiment

Eligibility Criteria

• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• Last year student

You may not qualify if:

• Experience with ultrasound beyond that which is taught at the University of Copenhagen
• Junior ENT registrar doctors
• Doctor enrolled in introductory training as ENT physician.
• Senior ENT registrar doctors
• Doctor enrolled in ENT training.

Sponsors & Collaborators

• Rigshospitalet, Denmark: lead

Study Sites (1)

Rigshospitalet

Copenhagen, 2100, Denmark

Location

MeSH Terms

Conditions

Thyroid Nodule; Thyroid Neoplasms

Condition Hierarchy (Ancestors)

Endocrine Gland Neoplasms; Neoplasms by Site; Neoplasms; Head and Neck Neoplasms; Endocrine System Diseases; Thyroid Diseases

Study Officials

• Tobias Todsen, Ph.d

  Rigshospitalet, Denmark

  STUDY DIRECTOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Model Details: 20 participants scan five patients over the course of fours hour and collect their diagnostics analyses on paper forms.

Study Record Dates

• First Submitted: February 23, 2024
• First Posted: March 12, 2024
• Study Start: September 1, 2023
• Primary Completion: November 4, 2023
• Study Completion: November 4, 2023
• Last Updated: November 25, 2024

Record last verified: 2024-11

Data Sharing

• IPD Sharing: Will not share

Locations

DK (1)