Comparison of ultrasound scanning for scoliosis assessment: Robotic versus manual

Maria Victorova, Heidi Hin Ting Lau, Timothy Tin Yan Lee, David Navarro-Alarcon, Yongping Zheng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)

Abstract

Background: Ultrasound (US) imaging for scoliosis assessment is challenging for a non-experienced operator. The robotic scanning was developed to follow a spinal curvature with deep learning and apply consistent forces to the patient's back. Methods: Twenty three scoliosis patients were scanned with US device both, robotically and manually. Two human raters measured each subject's spinous process angles on robotic and manual coronal images. Results: The robotic method showed high intra- (ICC > 0.85) and inter-rater (ICC > 0.77) reliabilities. Compared with the manual method, the robotic approach showed no significant difference (p < 0.05) when measuring coronal deformity angles. The mean absolute deviation for intra-rater analysis lies within an acceptable range from 0 to 5° for the minimum of 86% and maximum 97% of a total number of the measured angles. Conclusions: This study demonstrated that scoliosis deformity angles measured on ultrasound images obtained with robotic scanning are comparable to those obtained by manual scanning.

Original languageEnglish
Article numbere2468
JournalInternational Journal of Medical Robotics and Computer Assisted Surgery
Volume19
Issue number2
DOIs
Publication statusPublished - Apr 2023

Keywords

  • medical robotics
  • scoliosis
  • spine
  • ultrasound imaging

ASJC Scopus subject areas

  • Surgery
  • Biophysics
  • Computer Science Applications

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