Unpublished PhD thesis, Rutgers University, 1993/01, , type of study: ,ppt,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,

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Keywords:

biomechanics [69]
low back pain [523]
magnetic resonance imaging [21]
OMT [3924]
osteopathic manipulative treatment [3945]
pretest posttest design [240]

Abstract:

Although there are many treatments offered for Lower Back Pain (LBP), there is no consensus among scientists and physicians as to the treatment and the causes of LBP. The main tools to study the causes of LBP and the effectiveness of treatment on LBP include functional muscle testing, electromyography, and computer models. However, there are conflicting reports about the validity and the reliability of these tools. Thus there is a need to introduce new tools and to improve the existing ones. In this study, first Magnetic Resonance Imaging (MRI) was used to study the muscle spasms. Three groups of subjects (Controls, LBP Patients, and Exercised Subjects) were tested with MRI. Controls and LBP patients were tested before and after a conservative treatment and Exercised subjects were tested before and after they implemented an exercise protocol. When the relaxation parameters of MRI are calculated from the cross-sectional images of the low back muscles at the spinal level of L3/4, it was observed that they were lower for the LBP patients than the controls. After the treatments there was an increase in the relaxation parameters of the patients while there was no change for controls. Exercised subjects showed the same tendency right after the exercise. The lower relaxation parameter is a result of the lower ratio of extracellular to intracellular water concentration in muscle tissue. This suggests that LBP is related to poor blood circulation to the muscle tissue under spasm. Computer models of the spine are developed to study the load distribution among low back muscles. Our computer model is based on a nonlinear optimization algorithm which predicts a range of solutions which contain the possible load distributions among the low back muscles. Based on the predictions of this model, the relation between a particular muscle and the disc compression can be studied. The results predicted that when the force in a particular model is either increased or decreased, it can lead to increased disc compression. With the help of this model we were also able to calculate the disc compression and muscle forces while the spine is resisting an increasing external pure flexion moment. When the results were correlated with the electromyographic activity measurements which were taken from a group of patients before and after the treatment, good agreement was observed.