Ankylosing Spondylitis is a disease characterized by abnormal bone structures (syndesmophytes) growing at intervertebral disk spaces. Because this growth is so slow as to be undetectable on plain radiographs taken over years, it is desirable to resort to computerized techniques to complement qualitative human judgment with precise quantitative measures. We developed an algorithm with minimal user intervention that provides such measures using high-resolution computed tomography (CT) images. To the best of our knowledge it is the first time that determination of the disease’s status is attempted by direct measurement of the syndesmophytes. The first part of our algorithm segments the whole vertebral body using a 3-D multiscale cascade of successive level sets. The second part extracts the continuous ridgeline of the vertebral body where syndesmophytes are located. For that we designed a novel level set implementation capable of evolving on the isosurface of an object represented by a triangular mesh using curvature features. The third part of the algorithm segments the syndesmophytes from the vertebral body using local cutting planes and quantitates them. We present experimental work done with 10 patients from each of which we processed five vertebrae. The results of our algorithm were validated by comparison with a semi-quantitative evaluation made by a medical expert who visually inspected the CT scans. Correlation between the two evaluations was found to be 0.936 (p < 10−18).
Purpose of review Syndesmophytes are characteristic components of the spine pathology of ankylosing spondylitis (AS). Understanding their growth may reveal insights to pathogenesis and potential treatment. We review recent studies on rates of development of syndesmophytes, patient characteristics associated with more rapid syndesmophyte growth, local vertebral abnormalities that precede syndesmophytes, systemic biomarkers of syndesmophytes, and studies of medications. Recent findings New syndesmophytes develop in one-third of patients over two years. Consistent clinical predictors are male gender, elevated serum C-reactive protein levels, and pre-existing syndesmophytes. Concomitant vertebral inflammation and fat dysplasia on magnetic resonance imaging predict future syndesmophytes at the same vertebral location, but most syndesmophytes do not have recognized antecedents. Associations with serum levels of Wnt pathway proteins are inconsistent, as are the results of observational studies of tumor necrosis factor-alpha inhibitors. Summary Although there is better understanding of the frequency of syndesmophyte development, the pathogenesis of syndesmophytes remains unclear.
Objective Syndesmophyte growth in ankylosing spondylitis can be difficult to measure using radiographs because of poor visualisation and semiquantitative scoring methods. We developed and tested the reliability and validity of a new computer-based method that fully quantifies syndesmophyte volumes and heights on CT scans. Methods In this developmental study, we performed lumbar spine CT scans on 38 patients and used our algorithm to compute syndesmophyte volume and height in four intervertebral disk spaces. To assess reliability, we compared results between two scans performed on the same day in nine patients. To assess validity, we compared computed measures to visual ratings of syndesmophyte volume and height on both CT scans and radiographs by two physician readers. Results Coefficients of variation for syndesmophyte volume and height, based on repeat scans, were 2.05% and 2.40%, respectively. Based on Bland–Altman analysis, an increase in syndesmophyte volume of more than 4% or in height of more than 0.20 mm represented a change greater than measurement error. Computed volumes and heights were strongly associated with physician ratings of syndesmophyte volume and height on visual examination of both the CT scans (p<0.0001) and plain radiographs (p<0.002). Syndesmophyte volumes correlated with the Schober test (r=−0.48) and lateral thoracolumbar flexion (r=−0.60). Conclusions This new CT-based method that fully quantifies syndesmophytes in three-dimensional space had excellent reliability and face and construct validity. Given its high precision, this method shows promise for longitudinal clinical studies of syndesmophyte development and growth.
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