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Real-time Anatomy Recognition Tool Accuracy Research for Ultrasound-guided PENG and Suprainguinal Fascia Iliaca Blocks

NCT06283485 · Status: WITHDRAWN · Type: OBSERVATIONAL

Last updated 2025-08-13

No results posted yet for this study

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.

Conditions

  • Artificial Intelligent
  • Ultrasound Therapy; Complications
  • Nerve Block

Interventions

DEVICE

ultrasound examination

Phase 1 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. 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.

Sponsors & Collaborators

  • Betül Afşar

    collaborator UNKNOWN

  • Konya City Hospital

    lead OTHER

Principal Investigators

  • Yasin Tire · Konya City Hospital

  • Betül Afşar · Konya City Hospital

Eligibility

Min Age
18 Years
Max Age
65 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-12-15
Primary Completion
2025-04-15
Completion
2025-04-25

Countries

  • Turkey (Türkiye)

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06283485 on ClinicalTrials.gov