Inter-transducer variability of ultrasound image quality in obese adults: Qualitative and quantitative comparisons. Academic Article uri icon

Overview

abstract

  • PURPOSE: Acquiring high-quality ultrasound images of deep abdominal organs and vasculatures in obese adults (BMI >30 kg/cm2) is considered challenging. The aim of the study was to assess the inter-transducer variability in B-mode and color Doppler image quality from four commercial ultrasound transducers through qualitative and quantitative analyses. METHODS: Four curvilinear transducers on three ultrasound scanners were used to acquire B-mode and color Doppler images of deep abdominal structures in 15 obesity ≥ class II (BMI >35 kg/cm2) adults. Using visual-qualitative assessment and an offline image processing software, visual-qualitative score and quantitative mean pixel values of B-mode images, and color area ratios of color Doppler images were calculated. Differences in these values among the transducers were analyzed using one-way ANOVA. The intra- and inter-observer reliability of visual-qualitative assessment and offline image processing was tested using the intraclass correlation coefficient (ICC). RESULTS: Differences in visual-qualitative score, mean pixel value of B-mode images, and color area ratio of color Doppler images among the four transducers were significant (p < 0.001). Transducer -4 produced the highest quality of B-mode (45-53% improvement) and color Doppler (22-73% improvement) images among the transducers. Intra-observer repeatability and inter-observer reproducibility were higher with performing offline image processing than visual-qualitative assessment (ICC: 0.97-0.99 versus ICC: 0.76-0.97). CONCLUSION: There was significant image quality variability between different transducers. Transducer -4, a transducer designed specifically for high BMI patients, had the highest quality B-mode and color Doppler images compared to the other transducers lending to improved ultrasonographic visualization in obese patients.

publication date

  • September 29, 2022

Research

keywords

  • Image Processing, Computer-Assisted
  • Transducers

Identity

Scopus Document Identifier

  • 85139307924

Digital Object Identifier (DOI)

  • 10.1016/j.clinimag.2022.09.010

PubMed ID

  • 36208612

Additional Document Info

volume

  • 92