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Completed

NCT Number: NCT06306599

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.

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Key information

Conditions

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

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Rigshospitalet

Copenhagen, 2100, Denmark

About this study

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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

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.

Primary outcomes

  1. 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.

Secondary outcomes

  1. 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.

  2. 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.

  3. 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.

Sponsors and collaborators

Lead sponsor

Rigshospitalet, Denmark

Other

Registry information

Important dates

Study start
2023
Primary completion
2023
Study completion
2023
First posted
Mar 12, 2024
Registry last updated
Nov 25, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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