Intra-operator Repeatability of Manual Segmentations of the Hip Muscles on Clinical Magnetic Resonance Images

Abstract

The manual segmentation of muscles on magnetic resonance images is the gold standard procedure to reconstruct muscle volumes from medical imaging data and extract critical information for clinical and research purposes. (Semi)automatic methods have been proposed to expedite the otherwise lengthy process. These, however, rely on manual segmentations. Nonetheless, the repeatability of manual muscle volume segmentations performed on clinical MRI data has not been thoroughly assessed. When conducted, volumetric assessments often disregard the hip muscles. Therefore, one trained operator performed repeated manual segmentations (n = 3) of the iliopsoas (n = 34) and gluteus medius (n = 40) muscles on coronal T1-weighted MRI scans, acquired on 1.5 T scanners on a clinical population of patients elected for hip replacement surgery. Reconstructed muscle volumes were divided in sub-volumes and compared in terms of volume variance (normalized variance of volumes – nVV), shape (Jaccard Index—JI) and surface similarity (maximal Hausdorff distance—HD), to quantify intra-operator repeatability. One-way repeated measures ANOVA (or equivalent) tests with Bonferroni corrections for multiple comparisons were conducted to assess statistical significance. For both muscles, repeated manual segmentations were highly similar to one another (nVV: 2–6%, JI > 0.78, HD < 15 mm). However, shape and surface similarity were significantly lower when muscle extremities were included in the segmentations (e.g., iliopsoas: HD –12.06 to 14.42 mm, P < 0.05). Our findings show that the manual segmentation of hip muscle volumes on clinical MRI scans provides repeatable results over time. Nonetheless, extreme care should be taken in the segmentation of muscle extremities.

Automatic segmentation of skeletal muscles from MR images using modified U-Net and a novel data augmentation approach

“…Muscle segmentation is one of the fundamental techniques used to measure the geometrical properties of skeletal muscles that can be associated with the structural functional properties of muscles ( Lareau-Trudel et al, 2015 ; Montefiori et al, 2020 ; Zhu et al, 2021 ). Currently, the common method for measuring relevant muscle characteristics is manual segmentation of relevant areas of interest on MRI slices ( Montefiori et al, 2020 ; Davico et al, 2022 ). However, manual segmentation takes approximately 10 hours for an experienced operator to process thirty-five lower limb muscles and is associated with low inter-operator reproducibility for some of the muscles, with variation above 10% ( Montefiori et al, 2020 ).…”

Towards a comprehensive biomechanical assessment of the elderly combining in vivo data and in silico methods

“…The gold standard measures to quantify the (loss of) muscle volume and the residual muscle force of a person are—respectively—the acquisition of medical imaging data (typically magnetic resonance images, MRI) to extract muscle volumes ( Barnouin et al, 2014 ; Pons et al, 2018 ; Davico et al, 2023 ) and the maximal voluntary isometric contraction (MVIC) test on a dynamometer ( Meldrum et al, 2007 ; O’Brien et al, 2009 ; Harbo et al, 2012 ). Alternatively, the outcome of a hand-grip test may be employed as a surrogate measure of generalized sarcopenia ( Porto et al, 2019 ; Lee and Gong, 2020 ), and bio-impedance devices may be used to estimate the body mass composition ( Khalil et al, 2014 ).…”