Abstract
Computed tomography (CT) is the gold standard for analyzing muscle parameters. To clarify sex-specific paraspinal muscle area (PMA), paraspinal muscle index (PMI), and muscle fat infiltration (MFI) percentiles. This was a cross-sectional study of 760 individuals (45% men; age range = 20-92 years; mean age = 53.4 ± 21.1 years) with a body mass index (BMI) in the range of 16.4-38.1 kg/m2. CT scans were retrospectively used to establish PMA, PMI, and MFI at L3 level using a deep-learning (DL) tool. Sex-specific distributions for these parameters were assessed based on associations between age/BMI and individual muscle parameters, after which age- and BMI-specific percentile estimates were determined. The 5th percentile was regarded as the cutoff for PMA/PMI, and the 95th percentile was regarded as the cutoff for MFI. Sex-specific PMA, PMI, and MFI cutoffs in the paraspinal muscles group were 52.9 cm2, 15.0 cm2/m2, and 33.3%, respectively, in men, and 33.2 cm2, 9.5 cm2/m2, and 41.2% in women. Age was moderately negatively correlated with PMA and was strongly negatively correlated with PMI, but age was strongly positively correlated with MFI. BMI was moderately positively correlated with PMA/PMI in men and strongly positively correlated in women; BMI was weakly positively correlated with MFI, thus enabling the establishment of age- and BMI-specific cutoff percentiles. Sex-specific PMA, PMI, and MFI percentiles and age- and BMI-specific cutoff values for these parameters were successfully established for an outpatient population.
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