Clinical trial NCT06025279: Musculoskeletal System Ultrasound Examination Data Collection Study for the Development of an Artificial Intelligence Software
Official title: Data Collection Study to Develop an Artificial Intelligence-Based Ultrasound Guidance Software (Curious) for Musculoskeletal Examinations
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Ultrasound Imaging of Anatomical Structures
Musculoskeletal Diseases
Keywords: Artificial Intelligence
Ultrasound Imaging
Musculoskeletal System
Data Collection
Lead sponsor: Smart Alfa Teknoloji San. ve Tic. A.S.
Sponsor class: INDUSTRY
Collaborators: name: Ankara University
First posted: 2023-09-06
Enrollment: 300
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_ONLY
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: A total of 300 participants, divided between genders (150 females and 150 males), will take part in the study. These participants will include both healthy individuals and pathological conditions related to specific views of the musculoskeletal system. Their involvement will be based on informed consent. Pertinent data, such as medical history, body mass index (BMI), age, and gender, will be reported.

The logistical expenses of the volunteers during the study will be covered by the sponsor, Smart Alfa Teknoloji San. ve Tic. A.Ş.

The collection of raw ultrasound data will be undertaken by two experienced clinicians in physical medicine and rehabilitation, and ultrasound scanning. Their expertise ensures accurate data collection.

Brief summary: 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?

Detailed description: 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.

Eligibility criteria: Inclusion Criteria:

* Volunteers over the age of 18
* Able to accept and sign the Informed Consent Form before participating in the study

Exclusion Criteria:

* Volunteers below the age of 18
* 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

Primary outcomes:
measure: Collecting ultrasound data for artificial intelligence software that highlighted structures
timeFrame: 4 months
Secondary outcomes:
measure: Assessment of image quality
timeFrame: 4 months
Other outcomes:
Locations:
city: Altındağ
country: Turkey
facility: Ankara University School of Medicine
state: Ankara
Study officials:
References:
citation: 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.
citation: 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.