Musculoskeletal System Ultrasound Examination Data Collection Study for the Development of an Artificial Intelligence Software
NCT ID: NCT06025279
Last Updated: 2024-04-18
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
300 participants
OBSERVATIONAL
2023-08-03
2023-11-29
Brief Summary
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The main question it aims to answer is:
-Are the collected ultrasound images of diagnostic quality?
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Detailed Description
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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
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Study Design
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CASE_ONLY
PROSPECTIVE
Interventions
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Ultrasound Scan
Clinical professionals will conduct non-invasive ultrasound scans from the specified body views and subsequently save the acquired data.
Eligibility Criteria
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Inclusion Criteria
* Able to accept and sign the Informed Consent Form before participating in the study
Exclusion Criteria
* Unwilling to accept or having psychiatric or neurological diseases to sign an Informed Consent Form before participating in the study
* Inability to lie flat
* Anatomical deformity in the area to be scanned
18 Years
ALL
Yes
Sponsors
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Ankara University
OTHER
Smart Alfa Teknoloji San. ve Tic. A.S.
INDUSTRY
Responsible Party
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Locations
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Ankara University School of Medicine
Altındağ, Ankara, Turkey (Türkiye)
Countries
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References
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Gungor I, Gunaydin B, Buyukgebiz Yesil BM, Bagcaz S, Ozdemir MG, Inan G, Oktar SO. Evaluation of the effectiveness of artificial intelligence for ultrasound guided peripheral nerve and plane blocks in recognizing anatomical structures. Ann Anat. 2023 Oct;250:152143. doi: 10.1016/j.aanat.2023.152143. Epub 2023 Aug 11.
Ozcakar L, Tok F, Ricci V, Mezian K, Wu CH, Wu WT, Park GY, Kwon DR, Prieto MG, Dughbaj M, Dogan Y, Aksoz B, Guvener O, Ekiz T, Tiras M, Karacoban L, Menderes Y, Ciftci E, Ilicepinar OF, Kaya U, Kara M, Chang KV. Artificial Intelligence Featuring EURO-MUSCULUS/USPRM Basic Scanning Protocols. Am J Phys Med Rehabil. 2022 Nov 1;101(11):e174-e175. doi: 10.1097/PHM.0000000000002070. Epub 2022 Jul 7. No abstract available.
Other Identifiers
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SMARTALPHA-CURIOUS-1000
Identifier Type: -
Identifier Source: org_study_id
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