Thyroid Nodule
Conditions
Keywords
Ultrasound, AI, Thyroid cancer
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.
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.
Interventions
DIAGNOSTIC_TESTS-Detect for Thyroid
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.
Sponsors
Rigshospitalet, Denmark
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
NONE
Intervention model description
20 participants scan five patients over the course of fours hour and collect their diagnostics analyses on paper forms.
Eligibility
Sex/Gender
ALL
Healthy volunteers
Yes
Inclusion criteria
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Accuracy of S-Detect diagnosis | 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
| Measure | Time frame | Description |
|---|---|---|
| Accuracy of biopsy recommendation | 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. |
| Nodule measurement | 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. |
| OSAUS score | 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. |
Countries
Denmark
Outcome results
None listed