Morphological investigation of low back erector spinae muscle: Historical data populations

Abstract

Accurate and reliable low back morphological data such as the cross-sectional area (CSA) of the erector spinae muscle (ESM) is vital for biomechanical modeling of the lumbar spine to estimate spinal loading and enhance the understanding of injury mechanisms. The objective of the present study is to enhance the current database regarding ESM sizes by studying with larger sample sizes, collecting data from live subjects, using high resolution MRI scans, using computerized, reliable, and repeatable measurement techniques, and analyzing data from three inter-vertebral disc (IVD) levels for both genders. A total of 163 subjects (82 males and 81 females) were included in the study. CSAs of both right and left ESMs were measured from axial-oblique MRI scans using architectural design software. The average CSA of the ESM was 23.50, 24.22, and 24.33 cm2 for females and 30.00, 28.28, and 24.60 cm2 for males at the L3/L4, L4/L5, and L5/S1 levels, respectively. Results agree with some studies, but generally larger than most previous studies, possibly due to differences in sampling (sample size, subject characteristics: age, anthropometrics, cadavers, etc.), measurement techniques (scanning technology, scanning plane, scanning posture, different IVD levels), or muscle definitions. Relevance to industryLifting tasks are very common in occupational settings and associated with low back pain. Accurate and reliable low back muscle size data is of importance to produce more efficient low back biomechanical models to better understand the loading mechanism in lifting tasks and to minimize low back pain risk regarding the lifting task. However, available low back muscle size data are quite limited. This study fills part of this gap by providing data from a large sample population of live subjects, multiple levels, both genders, high resolution MRI scans, reliable and repeatable measurement technique. The updated low back muscle size data presented in this paper can be used by biomechanical modelers to improve current low back biomechanical models.