A paired comparison of nerve dimensions using B-Mode ultrasound and shear wave elastography during regional anaesthesia

被引:0
|
作者
Lockwood, Heather [1 ]
McLeod, Graeme A. [2 ]
机构
[1] Univ Dundee, Sch Med, Dundee, Scotland
[2] Univ Dundee, Inst Acad Anesthesia, Sch Med, Dundee DD1 9SY, Scotland
关键词
Clinical-physics and engineering; quality assurance-physics and engineering; artificial intelligence; statistics; anaesthesia; ARTIFICIAL-INTELLIGENCE;
D O I
10.1177/1742271X221091726
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Introduction: Shear wave elastography (SWE) presents nerves in colour, but the dimensions of its colour maps have not been validated with paired B-Mode nerve images. Our primary objective was to define the bias and limits of agreement of SWE with B-Mode nerve diameter. Our secondary objectives were to compare nerve area and shape, and provide a clinical standard for future application of new colour imaging technologies such as artificial intelligence. Materials and Methods: Eleven combined ultrasound-guided regional nerve blocks were conducted using a dual-mode transducer. Two raters outlined nerve margins on 110 paired B-Mode and SWE images every second for 20 s before and during injection. Bias and limits of agreement were plotted on Bland-Altman plots. We hypothesized that the bias of nerve diameter would be <2.5% and that the percent limits of agreement would lie +/- 0.67% (2 SD) of the bias. Results: There was no difference in the bias (95% confidence interval (CI) limits of agreement) of nerve diameter measurement, 0.01 (-0.14 to 0.16) cm, P=0.85, equivalent to a 1.4% (-56.6% to 59.5) % difference. The bias and limits of agreement were 0.03 (-0.08 to 0.15) cm(2), P=0.54 for cross-sectional nerve area; and 0.02 (-0.03 to 0.07), P=0.45 for shape. Reliability (ICC) between raters was 0.96 (0.94-0.98) for B-Mode nerve area and 0.91 (0.83-0.95) for SWE nerve area. Conclusions: Nerve diameter measurement from B-Mode and SWE images fell within a priori measures of bias and limits of agreement.
引用
收藏
页码:346 / 354
页数:9
相关论文
共 2 条
  • [1] Dual-mode artificially-intelligent diagnosis of breast tumours in shear-wave elastography and B-mode ultrasound using deep polynomial networks
    Zhang, Qi
    Song, Shuang
    Xiao, Yang
    Chen, Shuai
    Shi, Jun
    Zheng, Hairong
    MEDICAL ENGINEERING & PHYSICS, 2019, 64 : 1 - 6
  • [2] ProCUSNet: Prostate Cancer Detection on B-mode Transrectal Ultrasound Using Artificial Intell igence for Targeting During Prostate Biopsies
    Rusu, Mirabela
    Jahanandish, Hassan
    Vesal, Sulaiman
    Li, Cynthia Xinran
    Bhattacharya, Indrani
    Venkataraman, Rajesh
    Zhou, Steve Ran
    Kornberg, Zachary
    Sommer, Elijah Richard
    Khandwala, Yash Samir
    Hockman, Luke
    Zhou, Zhien
    Choi, Moon Hyung
    Ghanouni, Pejman
    Fan, Richard E.
    Sonn, Geoffrey A.
    EUROPEAN UROLOGY ONCOLOGY, 2025, 8 (02): : 477 - 485