Inter- and intra-reader reproducibility of shear wave elastography measurements for musculoskeletal soft tissue masses

Skeletal Radiology(2019)

引用 4|浏览9
暂无评分
摘要
Objective To determine inter- and intra-reader reproducibility of shear wave elastography measurements for musculoskeletal soft tissue masses. Materials and methods In all, 64 patients with musculoskeletal soft tissue masses were scanned by two readers prior to biopsy; each taking five measurements of shear wave velocity (m/s) and stiffness (kPa). A single lesion per patient was scanned in transverse and cranio-caudal planes. Depth measurements (cm) and volume (cm 3 ) were recorded for each lesion, for each reader. Linear mixed modelling was performed to assess limits of agreement (LOA), inter- and intra-reader repeatability, including analyses for measured depth and volume. Results Of the 64 lesions scanned, 24 (38%) were malignant. Bland-Altman plots demonstrated negligible bias with wide LOA for all measurements. Transverse velocity was the most reliable measure—intraclass correlation (95% CI) = 0.917 (0.886, 1)—though reader 1 measures could be between 38% lower and 57% higher than reader 2 [ratio-scale bias (95% LOA) = 0.99 (0.64, 1.55)]. Repeatability coefficients indicated most disagreement resulted from poor within-reader reproducibility. LOA between readers calculated from means of five repeated measurements were narrower—transverse velocity ratio-scale bias (95% LOA) = 1.00 (0.74, 1.35). Depth affected both estimated velocity and repeatability; volume also affected repeatability. Conclusion This study found poor repeatability of measurements with wide LOA due mostly to intra-reader variability. Transverse velocity was the most reliable measure; variability may be affected by lesion depth. At least five measurements should be reported with LOA to assist future comparability between shear wave elastography systems in evaluating soft tissue masses.
更多
查看译文
关键词
Elastography,Ultrasound,Muscles,Medical imaging,Reliability
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要