Background: The imaging assessment of paraspinal muscle morphology and fatty\ninfiltration has gained considerable attention in the past decades, with reports suggesting\nan association between muscle degenerative changes and low back pain (LBP).\nTo date, qualitative and quantitative approaches have been used to assess paraspinal\nmuscle composition. Though highly reliable, manual thresholding techniques are time\nconsuming and not always feasible in a clinical setting. The tedious and rater-dependent\nnature of such manual thresholding techniques provides the impetus for the\ndevelopment of automated or semi-automated segmentation methods. The purpose\nof the present study was to develop and evaluate an automated thresholding algorithm\nfor the assessment of paraspinal muscle composition. The reliability and validity\nof the muscle measurements using the new automated thresholding algorithm were\ninvestigated through repeated measurements and comparison with measurements\nfrom an established, highly reliable manual thresholding technique.\nMethods: Magnetic resonance images of 30 patients with LBP were randomly\nselected cohort of patients participating in a project on commonly diagnosed lumbar\npathologies in patients attending spine surgeon clinics. A series of T2-weighted MR\nimages were used to train the algorithm; preprocessing techniques including adaptive\nhistogram equalization method image adjustment scheme were used to enhance\nthe quality and contrast of the images. All muscle measurements were repeated\ntwice using a manual thresholding technique and the novel automated thresholding\nalgorithm, from axial T2-weigthed images, at least 5 days apart. The rater was blinded\nto all earlier measurements. Inter-method agreement and intra-rater reliability for each\nmeasurement method were assessed. The study did not received external funding and\nthe authors have no disclosures.\nResults: There was excellent agreement between the two methods with intermethod\nreliability coefficients (intraclass correlation coefficients) varying from 0.79\nto 0.99. Bland and Altman plots further confirmed the agreement between the two\nmethods. Intra-rater reliability and standard error of measurements were comparable\nbetween methods, with reliability coefficient varying between 0.95 and 0.99 for the\nmanual thresholding and 0.97ââ?¬â??0.99 for the automated algorithm.\nConclusion: The proposed automated thresholding algorithm to assess paraspinal\nmuscle size and composition measurements was highly reliable, with excellent agreement\nwith the reference manual thresholding method.
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