Sovira Tan

Computer Aided Evaluation of Ankylosing Spondylitis Using High-Resolution CT

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 diseases 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).

Quantitative syndesmophyte measurement in ankylosing spondylitis using CT: longitudinal validity and sensitivity to change over 2 years

Objectives Accurate measurement of syndesmophyte development and growth in ankylosing spondylitis (AS) is needed for studies of biomarkers and of treatments to slow spinal fusion. We tested the longitudinal validity and sensitivity to change of quantitative measurement of syndesmophytes using CT. Methods We performed lumbar spine CT scans on 33 patients with AS at baseline, 1 year and 2 years. Volumes and heights of syndesmophytes were computed in four intervertebral disk spaces. We compared the computed changes to a physicians ratings of change based on CT scan inspection. Sensitivity to change of the computed measures was compared with that of the modified Stoke AS Spinal Score (radiography) and a scoring method based on MRI. Results At years 1 and 2, respectively 24 (73%) and 26 (79%) patients had syndesmophyte volume increases by CT. At years 1 and 2, the mean (SD) computed volume increases per patient were, respectively 87 (186) and 201 (366) mm3. Computed volume changes were strongly associated with the physicians visual ratings of change (p<0.0002 and p<0.0001 for changes at years 1 and 2, respectively). The sensitivity to change over 1 year was higher for the CT volume measure (1.84) and the CT height measure (1.22) than either the MRI measure (0.50) or radiography (0.29). Conclusions CT-based syndesmophytes measurements had very good longitudinal validity and better sensitivity to change than radiography or MRI. This method shows promise for longitudinal clinical studies of syndesmophyte development and growth.

Quantitative measurement of syndesmophyte volume and height in ankylosing spondylitis using CT

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.

Computer aided evaluation of ankylosing spondylitis

Ankylosing spondylitis is a disease of the vertebra where abnormal bone structures (syndesmophytes) grow at intervertebral disk spaces. We provide a quantitative measure of the syndesmophytes using high resolution CT images. The first part of our algorithm segments the whole vertebra using a cascade of successive level sets that address the conflicting requirements of robustness to boundary discontinuities and flexibility needed to capture the fine structures caused by the pathology. The second part of the algorithm segments the syndesmophytes from the vertebral body and quantitates them. We use curvature information to locate the rim and end plates of the vertebra from where syndesmophytes develop. The results of our algorithm were validated by comparison with a semi-quantitative evaluation by a medical expert made by visually inspecting 3-D CT scans. Pearson correlation between the two evaluations is 0.898 (p<0.0001), and Spearman correlation is 0.906 (p<0.0001)

Improved precision of syndesmophyte measurement for the evaluation of ankylosing spondylitis using CT: a phantom and patient study

Ankylosing spondylitis is a disease characterized by abnormal bone formation (syndesmophyte) at the margins of inter-vertebral disc spaces. Syndesmophyte growth is currently typically monitored by the visual inspection of radiographs. The limitations inherent to the modality (2D projection of a 3D object) and rater (qualitative human judgment) may compromise sensitivity. With newly available treatments, more precise measures of syndesmophytes are needed to determine whether treatment can slow rates of syndesmophyte growth. We previously presented a computer algorithm measuring syndesmophyte volumes and heights in the 3D space of CT scans. In this study, we present improvements to the original algorithm and evaluate the gain in precision as applied to an anthropomorphic vertebral phantom and patients. Each patient was scanned twice in one day, thus providing two syndesmophyte volume and height measures. The difference between those two measures (ideally zero) determines our algorithms precision. The technical improvements to the algorithm decreased the mean volume difference (standard deviation) between scans from 3.01% (2.83%) to 1.31% (0.95%) and the mean height difference between scans from 3.16% (2.99%) to 1.56% (1.13%). The high precision of the improved algorithm holds promise for application to longitudinal clinical studies.

3D Multi-scale level set segmentation of vertebrae

We present a 3D multi-scale segmentation algorithm for vertebrae based on a cascade of level sets. We validated the performance of the algorithm in terms of accuracy, robustness and speed and compared it with its original single-scale version using a synthetic vertebra and a semi-synthetic one containing natural structured noise. The multi-scale algorithm was found to be 4 to 5 times faster and could be half a voxel more accurate than the single-scale algorithm. Synthetic vertebrae also allowed us to try a large number of level set parameters. Analysis of the results revealed trends about parameter combinations leading to leakage or under segmentation. After selecting a good set of parameters we tested the algorithm on 50 real vertebrae. The success rates were 90% and 80% respectively for the multi-scale and single-scale algorithms.

Syndesmophyte Growth in Ankylosing Spondylitis

Purpose of reviewSyndesmophytes are characteristic components of the spine disorder of ankylosing spondylitis. 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 findingsNew syndesmophytes develop in one-third of patients over 2 years. Consistent clinical predictors are male sex, elevated serum C-reactive protein levels, and preexisting syndesmophytes. Concomitant vertebral inflammation and fat dysplasia on MRI predict future syndesmophytes at the same vertebral location, but most syndesmophytes do not have recognized antecedents. Associations with serum levels of Wingless pathway proteins are inconsistent, as are the results of observational studies of tumor necrosis factor-alpha inhibitors. SummaryAlthough there is better understanding of the frequency of syndesmophyte development, the pathogenesis of syndesmophytes remains unclear.

Colonic fold detection from computed tomographic colonography images using diffusion-FCM and level sets

Colon cancer is the second major cause of cancer related deaths in industrial nations. Computed tomographic colonography (CTC) has emerged in the last decade as a new less invasive colon diagnostic alternative to the usually practiced optical colonoscopy. The overall goal is to increase the effectiveness of virtual endoscopic navigation of the existing computer-aided detection (CAD) system. The colonic/haustral folds serve as important landmarks for various associated tasks in the virtual endoscopic navigation like prone-supine registration, colonic polyp detection and tenia coli extraction. In this paper, we present two different techniques, first in isolation and then in synergism, for the detection of haustral folds. Our input is volumetric computed tomographic colonography (CTC) images. The first method, which uses a combination of heat diffusion and fuzzy c-means algorithm (FCM), has a tendency of over-segmentation. The second method, which employs level sets, suffers from under-segmentation. A synergistic combination, where the output of the first is used as an input for the second, is shown to improve the segmentation quality. Experimental results are presented on digital colon phantoms as well as real patient scans. The combined method has a total erroneous (over-segmentation plus under-segmentation) detection of (6.5+/-2)% of the total number of folds per colon as compared to (12.5+/-5)% for the diffusion-FCM-based method and (11.5+/-3)% for the level set-based method. The p-values obtained from the associated ANOVA tests indicate that the performance improvements are statistically significant.

Quantitation of Circumferential Syndesmophyte Height along the Vertebral Rim in Ankylosing Spondylitis Using Computed Tomography

Objective. Using the 3-D imaging capability of computed tomography (CT), we developed an algorithm quantitating syndesmophyte height along the entire vertebral rim. We investigated its reliability and sensitivity to change, performed a 2-year longitudinal study, and compared it to CT measures of syndesmophyte volume. Methods. We performed thoracolumbar spine CT scans on 33 patients at baseline, Year 1, and Year 2, and computed syndesmophyte height in 4 intervertebral disc spaces (IDS). Height was computed every 5° (72 angular sectors) along the vertebral rim. These 72 measures were summed to form the circumferential height per IDS, and results from 4 IDS were summed to provide results per patient. To assess reliability, we compared results between 2 scans performed on the same day in 9 patients. Validity was assessed by associations with spinal flexibility. Results. Coefficient of variation for circumferential syndesmophyte height was 0.893% per patient, indicating excellent reliability. Based on the Bland-Altman analysis, an increase in circumferential height of more than 3.44% per patient represented a change greater than measurement error. At years 1 and 2, mean (SD) circumferential syndesmophyte height increases were 10.2% (11.7%) and 16.1% (14.0%), respectively. Sensitivity to change was 0.72 and 0.87 at years 1 and 2, respectively. Circumferential syndesmophyte height correlated with the Schober test (r = −0.56, p = 0.0003) and lateral thoracolumbar flexion (r = −0.73, p < 0.0001). Conclusion. CT-based circumferential syndesmophyte height had excellent reliability and good sensitivity to change. It was more highly correlated with spine flexibility than syndesmophyte volume. The algorithm shows promise for longitudinal studies of syndesmophyte growth.

High precision semiautomated computed tomography measurement of lumbar disk and vertebral heights

PURPOSE Evaluation of treatments of many spine disorders requires precise measurement of the heights of vertebral bodies and disk spaces. The authors present a semiautomated computer algorithm measuring those heights from spine computed tomography (CT) scans and evaluate its precision. METHODS Eight patients underwent two spine CT scans in the same day. In each scan, five thoracolumbar vertebral heights and four disk heights were estimated using the algorithm. To assess precision, the authors computed the differences between the height measurements in the two scans, coefficients of variation (CV), and 95% limits of agreement. Intraoperator and interoperator precisions were evaluated. For local vertebral and disk height measurement (anterior, middle, posterior) the algorithm was compared to a manual mid-sagittal plane method. RESULTS The mean (standard deviation) interscan difference was as low as 0.043 (0.031) mm for disk heights and 0.044 (0.043) mm for vertebral heights. The corresponding 95% limits of agreement were [-0.085, 0.11] and [-0.10, 0.12] mm, respectively. Intraoperator and interoperator precision was high, with a maximal CV of 0.30%. For local vertebral and disk heights, the algorithm improved upon the precision of the manual mid-sagittal plane measurement by as much as a factor of 6 and 4, respectively. CONCLUSIONS The authors evaluated the precision of a novel computer algorithm for measuring vertebral body heights and disk heights using short term repeat CT scans of patients. The 95% limits of agreement indicate that the algorithm can detect small height changes of the order of 0.1 mm.