Ultrasound Imaging of Anatomical Structures
Conditions
Keywords
Musculoskeletal, Artificial Intelligence, ultrasound
Brief summary
This study conducted at three locations, aiming to collect ultrasound images from volunteers and assess the performance of an AI software, MSK Go, using these images. The software to be assessed is designed to assist physicians and healthcare professionals in performing ultrasound exams by classifying scan views and identifying key anatomical structures during a musculoskeletal ultrasound examination. The main question the study aims to answer is whether the AI software performs safely and effectively for future clinical use.
Detailed description
This study is designed to validate the performance of the MSK Go software in classifying musculoskeletal ultrasound examination views and segmenting relevant anatomical structures in a U.S. population. Data collection method and analysis: A total of 79 subjects were enrolled and undergone shoulder, elbow, wrist/hand, knee, and foot/ankle scans at three clinical sites. Ultrasound examinations were performed by MSK ultrasound experts without using MSK Go. Each participant spent approximately 30 minutes in the ultrasound scanning session. Demographic data were collected for all subjects. An FDA-cleared, commercially available ultrasound device was used at each location. The collected ultrasound scans are then annotated by healthcare professionals with expertise in musculoskeletal sonography. In a post hoc analysis, the ultrasound clips were processed using the AI software, and the software-generated classifications of views and segmentations of anatomical structures were compared with the reference annotations . Convenience sampling was applied during data collection to ensure that participants represented a balanced distribution across age, gender, BMI, and ethnicity.
Interventions
DEVICEUltrasound Scans
Scanning for musculoskeletal examination views on shoulder, elbow, wrist/hand, knee, and foot/ankle.
Sponsors
Smart Alfa Teknoloji San. ve Tic. A.S.
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
Yes
Inclusion criteria
* Provision of a signed and dated informed consent form * Stated willingness to comply with all study procedures and availability for the duration of the study
Exclusion criteria
* Pregnancy * Inability to lie flat * Open skin lesions or active infection at the scan site * Anatomical deformity in the joints to be scanned
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Rate of spatial (area) overlap of anatomical structure areas on the ultrasound image | Up to 30 days from enrollment | The performance based on the rate of the spatial (area) overlapping of supported structures |
| Rae of correctly classifying the views of the joint | Up to 30 days from enrollment | The performance based on the rate of correctly detecting views of the selected joint |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Rate of correctly assigning anatomical structure completeness level for any scan view of the joint | Up to 30 days from enrollment | The performance based on the completeness rate of detection level of the set of supported anatomical structures by the software |
Countries
United States
Outcome results
None listed