Computational protocol: Anatomical cross-sectional area of the quadriceps femoris and sit-to-stand test score in middle-aged and elderly population: development of a predictive equation

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[…] A series of cross-sectional images of the right thigh was scanned using MR scanner with a body coil (Signa EXCITE 1.5T; GE Medical Systems, USA). T1-weighted spin-echo transaxial images were collected with the following parameters: echo time, 10 ms; repetition time, 520 ms; slice thickness, 10 mm; gap, 0 mm; matrix, 256 × 192; field of view, 240 mm. Subjects lay supine with their arms and legs fully extended and relaxed in the magnet bore. Scanned MR images were transferred to a computer, and QF ACSA was measured by manually tracing the outline of muscle tissue using software (ImageJ, MIPAV; National Institutes of Health, USA). We took care of excluding visible adipose and connective tissue from individual ACSAs. We selected an image of mid-thigh according to a marker attached at the middle between the great trochanter and lateral condyle of femur, because the peak ACSA of the QF was located at the mid-thigh [, ]. The QF ACSA was denoted absolute (cm2) and adjusted values which were divided by two thirds power of body mass (cm2/mass2/3) []. [...] The difference of absolute and adjusted values of body mass index and QF ACSA, knee extension torque, and leg extension power between males and females was compared using unpaired Student’s t test. Time and power of STS test score were analyzed using a two-way (posture × sex) analysis of variance with repeated measures. Correlation coefficients between QF ACSA and each of the STS time, STS power, knee extension torque, and leg extension power were examined using a Pearson’s correlation analysis. The differences of physical characteristics between the validation and cross-validation groups were compared using unpaired Student’s t test. A stepwise multiple linear regression analysis was performed to create a predictive model of absolute QF ACSA value for the validation group. Sex (males, 0; females, 1), age, and the time and power of STS test score at each posture condition were entered into the stepwise regression as independent variables if they represented a significant contribution to the explained variance (F to enter ≤0.05, F to remove ≥0.10). In the cross-validation group, the difference of the ACSA between measurement and estimated values was compared by paired Student’s t test. A Bland-Altman plot was constructed to determine if there was a systematic error between the measured and estimated values []. The level of significance was set at P < 0.05. Statistical analyses were performed using the IBM SPSS Statistics software (version 22.0; IBM, Japan). […]

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