An investigation into the use of MR imaging to determine the functional cross sectional area of lumbar paraspinal muscles.
The purpose of this study was to investigate the use of magnetic resonance (MR) imaging and image processing software to determine the functional cross-sectional area (FCSA) (the area of muscle isolated from fat) of the lumbar paraspinal muscles. The measurement of the morphology of the lumbar paraspinal muscles has become the focus of several recent investigations into the aetiology of low back pain. However, the reliability and validity of determining the FCSA of the lumbar paraspinal muscles using MR imaging are yet to be reported. T2 axial MR scans at the L1-S1 spinal levels of six subjects were obtained using identical MR systems and scanning parameters. Lean paraspinal muscle, vertebral body bone and intermuscular fat were manually segmented using image analysis software to assign a grey scale range to the MR signal intensity emitted by each tissue type. The resultant grey scale range for muscle was used to determine FCSA measurements for each of the paraspinal muscles, psoas, quadratus lumborum, erector spinae and lumbar multifidus on each scan slice. As various biological, instrument and measurement factors can affect MR signal intensity, a sensitivity analysis was conducted to determine the error associated in calculating FCSA for paraspinal muscle using a discrete grey scale range. Cross-sectional area and FCSA measurements were repeated three times and reliability indices for the FCSA measurements were obtained, showing excellent reliability, intra class correlation coefficient (mean=0.97, range 0.90-0.99) and %SEM (mean=2.6%, range 0.7-4.8%). In addition, the error associated with miscalculation of the grey scale range for the MR signal intensity of muscle was calculated and found to be low with an error of 20 grey scale units at the upper end of the muscle's grey scale range resulting in a very small error in the measured muscle FCSA. The method presented in this paper has a variety of practical applications in areas such as evidence-based rehabilitation, biomechanical modelling and the determination of segmental inertial parameters.
Ranson
Craig A
CA
School of Biomedical and Sports Science, Edith Cowan University, Perth, Western Australia. craig.ranson@ecb.co.uk
Burnett
Angus F
AF
Kerslake
Robert
R
Batt
Mark E
ME
O'Sullivan
Peter B
PB
D000328:Adult; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008161:Lumbosacral Region / Q000033:anatomy & histology; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000706:statistics & numerical data; D008297:Male; D018482:Muscle, Skeletal / Q000033:anatomy & histology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software