A Novel Ultrasound Probe for Thyroid Imaging and Machine Learning
Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18+
SponsorSound Blade Medical Inc.
About this trial
The objective of the THYMAL 01 pilot study is to evaluate the Sound Blade Imaging System in subjects with benign thyroid nodules undergoing standard-of-care ultrasound imaging.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Participants must be ≥ 18 years of age
Able and willing to sign informed consent
Known thyroid nodule demonstrated on a prior thyroid US and is undergoing active surveillance of the nodule with serial USs
Disqualifiers
Unable to lay flat for 15 minutes
Active neck wounds, dressings, or skin conditions that would interfere with neck US (e.g., preclude transducer placement)
Cervical spine or back disease that would prevent neck extension and would hinder the ability to obtain accurate thyroid US images
Previous thyroid surgeries, radiation of face and neck
Trial design
Design model
Single group
Treatments tested in this trial
Thyroid ultrasound
Diagnostic testPatients who are scheduled for a SOC surveillance Thyroid Nodule Ultrasound will undergo a second ultrasound using the Sound Blade Ultrasound.
Treatment groups
30 Participants
are divided into 1 treatment groupGroup A: Thyroid UltrasoundExperimental treatment 1 intervention
Trial outcomes
Primary outcomes
1
The Ability to Visualization Thyroid Nodules and other key Anatomical Structures
The primary endpoint is to evaluate the ability to visualize thyroid nodules and other key anatomical structures with the investigational device compared to the SOC US imaging device.
Time frame
Day 12
Evaluate the visibility/detection performance of a machine-learning model
A machine-learning model will be created to identify and segment thyroid nodules and key anatomical neck structures. The first outcome will evaluate performance of visibility and detection using standard classification measures
Time frame
Day 13
Evaluate the segmentation performance of a machine-learning model
A machine-learning model will be created to identify and segment thyroid nodules and key anatomical neck structures. The second outcome will evaluate performance on delineable cases.
Time frame
Day 1Sponsors and contacts
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Source ClinicalTrials.gov