Thyroid Abnormalities, Thyroid Nodules
Conditions
Keywords
Thyroid Nodule
Brief summary
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.
Interventions
DIAGNOSTIC_TESTThyroid ultrasound
Patients who are scheduled for a SOC surveillance Thyroid Nodule Ultrasound will undergo a second ultrasound using the Sound Blade Ultrasound.
Sponsors
Sound Blade Medical Inc.
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* 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
Exclusion criteria
* 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 * Known inflammatory thyroid diseases or thyroiditis (e.g., Graves, Hashimoto)
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| The Ability to Visualization Thyroid Nodules and other key Anatomical Structures | Day 1 | 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. |
| Evaluate the visibility/detection performance of a machine-learning model | Day 1 | 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 |
| Evaluate the segmentation performance of a machine-learning model | Day 1 | 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. |
Countries
Canada
Contacts
CONTACTDeborah Wright, Project Manager, RN
CONTACTRichard Balys, MD, MD
PRINCIPAL_INVESTIGATORRichard Bayls, MD
Nova Scotia Health Authority
Outcome results
None listed