Three-dimensional numerical schemes for the segmentation of the psoas muscle in X-ray computed tomography images

BMC Med Imaging. 2024 Sep 19;24(1):251. doi: 10.1186/s12880-024-01423-0.

Abstract

The analysis of the psoas muscle in morphological and functional imaging has proved to be an accurate approach to assess sarcopenia, i.e. a systemic loss of skeletal muscle mass and function that may be correlated to multifactorial etiological aspects. The inclusion of sarcopenia assessment into a radiological workflow would need the implementation of computational pipelines for image processing that guarantee segmentation reliability and a significant degree of automation. The present study utilizes three-dimensional numerical schemes for psoas segmentation in low-dose X-ray computed tomography images. Specifically, here we focused on the level set methodology and compared the performances of two standard approaches, a classical evolution model and a three-dimension geodesic model, with the performances of an original first-order modification of this latter one. The results of this analysis show that these gradient-based schemes guarantee reliability with respect to manual segmentation and that the first-order scheme requires a computational burden that is significantly smaller than the one needed by the second-order approach.

Keywords: Image segmentation; Sarcopenia; Three-dimensional level set methods; X-ray Computed Tomography (CT).

MeSH terms

  • Aged
  • Algorithms
  • Female
  • Humans
  • Imaging, Three-Dimensional* / methods
  • Male
  • Middle Aged
  • Psoas Muscles* / diagnostic imaging
  • Radiographic Image Interpretation, Computer-Assisted / methods
  • Reproducibility of Results
  • Sarcopenia* / diagnostic imaging
  • Tomography, X-Ray Computed* / methods