Real-time Anatomy Recognition Tool Accuracy Research for Ultrasound-guided PENG and Suprainguinal Fascia Iliaca Blocks
- Conditions
- Nerve BlockArtificial IntelligentUltrasound Therapy; Complications
- Interventions
- Device: ultrasound examination
- Registration Number
- NCT06283485
- Lead Sponsor
- Konya City Hospital
- Brief Summary
Background and rationale: Ultrasound-guided regional anesthesia is a widely used pain control method today. A critical aspect of the procedure is accurate visualization of anatomical structures on ultrasound to precisely define target areas. Distinguishing surrounding tissues with an imaging model that automatically recognizes sonoanatomy in ultrasound images will reduce unintended intraneural injections or injury to other anatomical structures in close proximity and increase patient safety.
Research question; How can we improve the ultrasound images we frequently use in regional blocks by integrating them with artificial intelligence to reduce complications and improve applications? And what is the accuracy of the developed artificial intelligence support during imaging?
Research purpose; This work; We aim to further increase the safety of different regional block positions, minimize the risk of complications, and improve ultrasound visualization by developing an artificial intelligence model (AI Model-Artificial Intelligence) that automatically identifies and segments anatomical landmarks, provides visual guidance for inexperienced colleagues, and improves the performance of the developed model during application. aims to demonstrate its accuracy.
Hypothesis; Numerous studies have shown that the use of ultrasound and neurostimulators in practice increases the success, onset and quality of nerve blocks, but due to the low incidence of major complications and the absence of comparable randomized studies, no definitive statement can be made as to whether ultrasound reduces the overall rate of nerve damage. An imaging model that automatically marks sonoanatomy with artificial intelligence in ultrasound images can reduce unintended intraneural injections or injury to other anatomical structures in close proximity and improve patient safety.
- Detailed Description
Research processes; The study will consist of two stages. Phase 1: PENG, collection of sonoanatomical images of Supraingiuinal Fascia Iliaca block and development of artificial intelligence software (in healthy volunteers without invasive procedures) Stage 2: Conducting validation study with the developed artificial intelligence
Stage 1: Taking ultrasound images from healthy volunteers (150 volunteers) to produce artificial intelligence - How to take PENG and Suprainguinal Fascia Iliaca Block sonoanatomical images is as follows.
1.1) PENG (Pericapsular Nerve Group Block): Images will be taken with both linear and convex probes. Sonoanatomical information will be collected from healthy volunteers and no invasive procedures will be performed. 150 (75 women -75 men) healthy volunteers who agree to have ultrasound images taken will be included.
1.2) Suprainguinal Fascia Iliaca Block: Images will be taken with a linear probe. Sonoanatomical information will be collected from healthy volunteers and no invasive procedures will be performed. 150 (75 female-75 male) healthy volunteers who agree to have ultrasound images taken will be included.
In the first phase of this study, thanks to the PENG and Suprainguinal Fascia Iliaca block images collected from volunteers, the artificial intelligence technology Smart Alfa Teknoloji San. recognizes and marks the anatomical structures of this region. and Tic. Inc. It will be developed by and added to Nerveblox software. After PENG and Suprainguinal Fascia Iliaca blocks are included in the software, Nerveblox software will be used during validation in the second phase of the study.
Phase 2: In the second phase of the study, Smart Alfa Teknoloji San. and Tic. Inc. Artificial intelligence technology called Nerveblox, which was developed with the data received in the first stage with the support of the company, will be used. It is the validation and accuracy study of the artificial intelligence technology developed in the first stage. The accuracy study will be conducted on 40 healthy volunteers. 20 men and 20 women will be included in the study.
Thanks to the Nerveblox artificial intelligence technology developed at this stage, the accuracy of the anatomical structures marked and colored by the regional-specific artificial intelligence; It will be evaluated by 6 experienced anesthesiologists based on ultrasound image scans made by 2nd, 3rd and 4th year assistants (two assistants from each year). The second phase is the validation phase and the validators will be experienced anesthesiologists (at least five years of specialized experience). Validators will score the accuracy of representation of each predefined anatomical landmark using a 5-point scale (1: Very Poor, 2: Poor, 3: Good, 4: Very Good, 5: Excellent); Accuracy is defined as expert opinion on how software-generated landmark labels represent true anatomy in raw ultrasonography images.
Recruitment & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 150
- Agreeing to take ultrasound images
- Healthy - No comorbidities
- Adult individuals between the ages of 18-65
- Those who do not accept ultrasound images
- Individuals under 18 years of age
- with comorbidities
- Pregnancy
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description Male ultrasound examination Phase 1: Creating artificial intelligence from ultrasound scans of 150 healthy volunteers Sonoanatomical PENG and Suprainguinal Fascia Iliaca Block pictures are taken as follows. 1) PENG (Pericapsular Nerve Group Block): Linear and convex probes will be used to collect images. No invasive procedures will be conducted on healthy subjects for sonoanatomical data. 150 healthy volunteers (75 women-75 males) will be ultrasounded. 1.2) Suprainguinal Fascia Iliaca Block: Linear probe images. No invasive procedures will be conducted on healthy subjects for sonoanatomical data. 150 healthy individuals (75 female-75 male) will be ultrasounded. Phase 2: Smart Alfa Teknoloji San. and Tic. Inc. will use Nerveblox, an artificial intelligence system built using data from the first stage, in the second part of the study. First-stage artificial intelligence technology validation and accuracy study. The accuracy study will involve 40 healthy volunteers. 20 men and 20 women will be studied. Female ultrasound examination Phase 1: Creating artificial intelligence from ultrasound scans of 150 healthy volunteers Sonoanatomical PENG and Suprainguinal Fascia Iliaca Block pictures are taken as follows. 1) PENG (Pericapsular Nerve Group Block): Linear and convex probes will be used to collect images. No invasive procedures will be conducted on healthy subjects for sonoanatomical data. 150 healthy volunteers (75 women-75 males) will be ultrasounded. 1.2) Suprainguinal Fascia Iliaca Block: Linear probe images. No invasive procedures will be conducted on healthy subjects for sonoanatomical data. 150 healthy individuals (75 female-75 male) will be ultrasounded.
- Primary Outcome Measures
Name Time Method Artificial intelligence Program size Based, during the ultrasonography. Thanks to the PENG and Suprainguinal Fascia Iliaca block images collected from volunteers in the first phase of this study, the artificial intelligence technology Smart Alfa company recognizes and marks the anatomical structures of these four regions. It will be developed by and added to Nerveblox software.
Score of assessment the pictures After the ultrasonography. In the second phase, thanks to the Nerveblox artificial intelligence technology developed, the accuracy of the anatomical structures marked and colored by the regional-specific artificial intelligence; It will be evaluated based on ultrasound image scans made by 2nd, 3rd and 4th year assistants and by anesthesiologists with at least 5 years of experience.
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
Yasin Tire
🇹🇷Konya, Meram, Turkey