Identification of morphological risk factors for sacroiliac joint syndrome using in vivo computed tomography-A comparative study. - Johannes G Dinkel; Christina Wendl; Johanna Ottner; Ekaterina Noeva; Quirin Strotzer; Christian Stroszczynski; Hans-Peter Dinkel; Marco Dollinger; Andreas Schicho (PLoS ONE)
Introduction Sacroiliac joint syndrome (SIJS) is an important cause of lower back pain, constituting a common source of morbidity, especially in today's ageing population. Underlying pathophysiology is complex and likely multifactorial. Previous studies have suggested characteristic morphologies of the sacroiliac joint (SIJ) shape in pain patients. Aim To find morphological markers for SIJS in vivo by evaluating an extensive array of, particularly anatomical, measurements of the SIJ, pelvis and associated musculature using computed tomography (CT) by comparison with non-SIJS control patients. Methods CT scans of 754 patients suffering from SIJS and 116 age-matched control patients were analyzed evaluating anatomy and musculoskeletal degeneration. Combined and gender-grouped T-tests, Mann-Whitney-U-tests and chi-square-tests were conducted. Age correlations were tested using linear regressions. Results Pelvis and SIJ morphology differed significantly in SIJS patients when compared to the control group. Pelves were narrower and deeper, sacra were narrower and there was less sacroiliac depth. True SIJ were deeper at S1 level and less deep at S2 and S3 levels. There was more sagittal angulation of SIJ at S1, S2 and S3 levels. Furthermore, less psoas muscle volume, higher grades of fatty degeneration of the back musculature as well as increased cutis/subcutis thickness were demonstrated in SIJS patients. Grades of SIJ degeneration were higher in all evaluated portions, although moderate in overall extent. Discussion and conclusion Our data suggest a number of morphological markers associated with SIJS, visible in conventional CT imaging. Further studies are needed to evaluate for causality, prognostic value and potential impact of these factors on individual treatment procedure. In a high-risk population, opportunistic analyses might enable targeted preventive measures.