Methodological considerations in region of interest definitions for paraspinal muscles in axial MRIs of the lumbar spine
Berry DB, Padwal J, Johnson S, Parra CL, Ward SR, Shahidi B.
BMC Musculoskelet Disord, 2018 19(1):135.
BMC Musculoskelet Disord, 2018 19(1):135.
Abstract:
BACKGROUND: Magnetic Resonance Imaging (MRI) is commonly used to assess the health of the lumbar spine and supporting structures. Studies have suggested that
fatty infiltration of the posterior lumbar muscles is important in predicting responses to treatment for low back pain. However, methodological differences exist in defining the region of interest (ROI) of a muscle, which limits the ability to compare data between studies. The purpose of this study was to determine reliability and systematic differences within and between two commonly utilized methodologies for ROI definitions of lumbar paraspinal muscle.
METHODS: T2-weighted MRIs of the mid-L4 vertebrae from 37 patients with low back pain who were scheduled for lumbar spine surgery were included from a hospital database. Fatty infiltration for these patients ranged from low to high, based on Kjaer criteria. Two methods were used to define ROI: 1) segmentation of the multifidus and erector spinae based on fascial planes including epimuscular fat, and 2) segmentation of the multifidus and erector spinae based on visible muscle boundaries, which did not include epimuscular fat. Total cross sectional area (tCSA), fat signal fraction (FSF), muscle cross sectional area, and fat cross sectional area were measured. Degree of agreement between raters for each parameter was assessed using intra-class correlation coefficients (ICC) and area fraction of overlapping voxels.
RESULTS: Excellent inter-rater agreement (ICC > 0.75) was observed for all measures for both methods. There was no significant difference between area fraction overlap of ROIs between methods. Method 1 demonstrated a greater tCSA for both the erector spinae (14-15%, p < 0.001) and multifidus (4%, p < 0.016) but a greater FSF only for the erector spinae (11-13%, p < 0.001).
CONCLUSION: The two methods of defining lumbar spine muscle ROIs demonstrated excellent inter-rater reliability, although significant differences exist as method 1 showed larger CSA and FSF values compared to method 2. The results of this study confirm the validity of using either method to measure lumbar paraspinal musculature, and that method should be selected based on the primary outcome variables of interest.
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METHODS: T2-weighted MRIs of the mid-L4 vertebrae from 37 patients with low back pain who were scheduled for lumbar spine surgery were included from a hospital database. Fatty infiltration for these patients ranged from low to high, based on Kjaer criteria. Two methods were used to define ROI: 1) segmentation of the multifidus and erector spinae based on fascial planes including epimuscular fat, and 2) segmentation of the multifidus and erector spinae based on visible muscle boundaries, which did not include epimuscular fat. Total cross sectional area (tCSA), fat signal fraction (FSF), muscle cross sectional area, and fat cross sectional area were measured. Degree of agreement between raters for each parameter was assessed using intra-class correlation coefficients (ICC) and area fraction of overlapping voxels.
RESULTS: Excellent inter-rater agreement (ICC > 0.75) was observed for all measures for both methods. There was no significant difference between area fraction overlap of ROIs between methods. Method 1 demonstrated a greater tCSA for both the erector spinae (14-15%, p < 0.001) and multifidus (4%, p < 0.016) but a greater FSF only for the erector spinae (11-13%, p < 0.001).
CONCLUSION: The two methods of defining lumbar spine muscle ROIs demonstrated excellent inter-rater reliability, although significant differences exist as method 1 showed larger CSA and FSF values compared to method 2. The results of this study confirm the validity of using either method to measure lumbar paraspinal musculature, and that method should be selected based on the primary outcome variables of interest.
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