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The goal of this observational study is to assess the accuracy of Artificial Intelligence (AI) software to assist ultrasound scanning prior to peripheral nerve blocks. 40 healthy volunteers are going to be accepted to this study in which ultrasound scanning will be performed for four different block types.
The main questions it aims to answer are:
Participants will be evaluated under four nerve block regions to identify their key anatomical landmarks using ultrasound-guided artificial intelligence software.
Three residents with different levels of Ultrasound-guided Regional Anesthesia(UGRA) experience but eligible to perform UGRA techniques will collect the ultrasound images when the artificial intelligence software scan success fed by ultrasound reached 100%. After collecting US images, each pair of US images(highlighted and raw ) will be evaluated by 2 experts for the accuracy of AI assistance, independently and blindly.
Full description
Ultrasound-guided Regional Anesthesia (UGRA) is currently an effective method for the anesthesiologist. In this single-centered study, we aim to assess the accuracy of artificial intelligence effectiveness. All scans will be performed on an FDA-cleared general-purpose ultrasound device (GE Logiq, Wisconsin, USA) and software setup will be provided by the sponsor also having the software (Nerveblox, Smart Alfa Teknoloji San. Ve Tic. A.S., Ankara, Turkey).
The methodology of the study is that:
Three independent residents, in the 2nd, 3rd, and 4th years of education in the field of anesthesiology and also eligible to perform UGRA, will be recruited for using the artificial intelligence software (Nerveblox v1.0).
40 (20 male and 20 female) volunteers will be recruited for the study and the volunteer's demographic information (body mass index, gender, age) will be considered and recorded.
The order of volunteers will be randomized between participants.
Considered peripheral nerve and plane blocks are:
Each trainee will reach 100% "scan success" on the Nerveblox to record the raw and highlighted images.
Each trainee will scan only 1 time.
On the data analysis:
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Data sourced from clinicaltrials.gov
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