Musculoskeletal System Ultrasound Examination Data Collection Study for the Development of an Artificial Intelligence Software

Overview

The primary objective of this observational study is to acquire ultrasound images (raw data) encompassing various planes within the musculoskeletal system. This data will be instrumental in the development of artificial intelligence-guided software. The study aims to enlist 300 volunteers, comprising individuals with both healthy musculoskeletal systems and those presenting pathologies. These participants will undergo ultrasound scans administered by two experienced professionals, employing FDA-cleared ultrasound devices. The main question it aims to answer is: -Are the collected ultrasound images of diagnostic quality?

Ultrasound's cost-effective and user-friendly attributes have positioned it as a cornerstone in diagnosing musculoskeletal system disorders. In this single-centered and prospective study, the study aims to enlist 300 volunteers, comprising both individuals with healthy musculoskeletal systems and those with pathologies. The collected ultrasound raw data will be used to train models for the identification and highlighting of key anatomical landmarks on ultrasound images. Participants' gender, age, BMI, and medical history will be considered and reported. All scans will be performed on FDA-cleared general-purpose ultrasound devices. Obtained images will be used to develop artificial intelligence-based medical software by Smart Alfa Teknoloji San. Ve Tic. A.Ş., Ankara, Turkey. Smart Alfa has similarly conducted a study in the field of anesthesia using the same method in Nerveblox artificial intelligence software. The study methodology encompasses the following components: * Specific body views, guided by established protocols, will be scanned from different body planes. The focus areas encompass musculoskeletal structures. * A cohort of 300 volunteers, evenly distributed by gender (150 male, 150 female), will have their demographic data (BMI, gender, age) documented. * To counteract potential biases, the sequence of volunteer participation will be randomized. * Each scan is expected to take 45 minutes.

Conditions