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Published online before print September 11, 2006, 10.1148/radiol.2412050781
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(Radiology 2006;241:603-608.)
© RSNA, 2006


Vascular and Interventional Radiology

Vessel Wall Calcifications at Multi–Detector Row CT Angiography in Patients with Peripheral Arterial Disease: Effect on Clinical Utility and Clinical Predictors1

Rody Ouwendijk, MD, PhD, Marc C. J. M. Kock, MD, MSc, Lukas C. van Dijk, MD, PhD, Marc R. H. M. van Sambeek, MD, PhD, Theo Stijnen, PhD and M. G. Myriam Hunink, MD, PhD

1 From the Program for the Assessment of Radiological Technology (ART Program) and the Departments of Radiology (R.O., M.C.J.M.K., L.C.v.D., M.G.M.H.), Epidemiology and Biostatistics (R.O., T.S., M.G.M.H.), and Vascular Surgery (M.R.H.M.v.S.), Erasmus MC Rotterdam, Dr Molewaterplein 50, Room Ee 21-40a, 3015 GE Rotterdam, the Netherlands; and the Department of Health Policy and Management, Harvard School of Public Health, Boston, Mass (M.G.M.H.). Received May 7, 2005; revision requested July 6; revision received September 4; accepted September 22; final version accepted January 25, 2006. Supported by grants 945-01-039 from ZonMw, Netherlands Organisation for Health Research and Development, The Hague, the Netherlands, and 904-66-091 from the Netherlands Organization for Scientific Research, The Hague, the Netherlands. Address correspondence to M.G.M.H. (e-mail: m.hunink{at}erasmusmc.nl).


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ADVANCES IN KNOWLEDGE
 References
 
Purpose: To evaluate retrospectively the effect of vessel wall calcifications on the clinical utility of multi–detector row computed tomographic (CT) angiography performed in patients with peripheral arterial disease and to identify clinical predictors for the presence of vessel wall calcifications.

Materials and Methods: The study was approved by the hospital institutional review board, and informed consent was obtained from all patients. For this study the authors included patients from two randomized controlled trials that measured the costs and effects of diagnostic imaging in patients with peripheral arterial disease. All patients underwent CT angiography and were followed up for 6 months. Clinical utility was measured on the basis of therapeutic confidence (rated on a 10-point scale) in the results of initial CT angiography and the need for additional vascular imaging. Univariable and multivariable logistic and linear regression analysis and the area under the receiver operating characteristic curve were used to evaluate the effect of vessel wall calcifications on the clinical utility of CT angiography and the use of patient characteristics to predict the number of calcified segments at CT angiography.

Results: A total of 145 patients were included (mean age, 64 years; 70% men). The authors found that the number of calcified segments was a significant predictor of the need for additional imaging (P = .001) and of the confidence scores (P < .001). The number of calcified segments discriminated between patients who required additional imaging after CT angiography and those who did not (area under the receiver operating characteristic curve, 0.66; 95% confidence interval: 0.54, 0.77). Age, diabetes mellitus, and cardiac disease were significant predictors of the number of calcified segments in both the univariable and multivariable analyses (P < .05).

Conclusion: Vessel wall calcifications decrease the clinical utility of CT angiography in patients with peripheral arterial disease. Diabetes mellitus, cardiac disease, and elderly age (older than 84 years) are independently predictive for the presence of vessel wall calcifications.

© RSNA, 2006


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ADVANCES IN KNOWLEDGE
 References
 
Computed tomographic (CT) angiography is increasingly used for diagnostic imaging in patients with peripheral arterial disease. The use of multi–detector row technology has resulted in shorter acquisition time, increased volume coverage, lower dose of contrast medium, and improved spatial resolution for assessing small arterial branches (1,2). The number of studies showing that multi–detector row CT angiography is accurate for imaging peripheral arteries is still increasing (310). Furthermore, in our institution we showed (11,12) that patient outcomes and the clinical utility for CT angiography were comparable with those for both digital subtraction angiography (DSA) and magnetic resonance (MR) angiography, but CT angiography incurred lower diagnostic costs than both DSA and MR angiography in patients with peripheral arterial disease. These results suggest that CT angiography is the optimal strategy for the initial diagnostic work-up for peripheral arterial disease.

A major drawback of CT angiography is the difficulty in assessing arterial luminal stenosis in extensively calcified vessels. Several groups of investigators (3,5,10) reported that calcified plaques were the main reason for misinterpretations of CT angiograms. In the presence of extensive vessel wall calcifications, especially in small arteries, it is difficult to produce interpretable maximum intensity projection images. Continuous calcification of the vessel wall may lead to false-negative findings of patency, whereas high-attenuation artifacts, or "blooming," caused by calcification on transverse images may result in a false-positive diagnosis of a substantial stenosis or occlusion. Researchers in two studies (6,13) found significantly lower diagnostic accuracy and interobserver agreement in arterial segments with calcifications than in segments without calcifications. Furthermore, some authors (5,6) stated that when extensive calcifications are present, the end product of CT angiography is of questionable diagnostic value at best and that, in these cases, patients could not be treated without undergoing DSA for accurate evaluation.

The effect of vessel wall calcifications on the clinical utility of CT angiography, defined in terms of therapeutic confidence and the number of additional imaging tests performed, remains to be clarified. Furthermore, it would be useful to identify clinical predictors of vessel wall calcifications that would help select patients for whom CT angiography is less clinically useful. The purpose of our study, therefore, was to evaluate retrospectively the effect of vessel wall calcifications on the clinical utility of CT angiography performed in patients with peripheral arterial disease and to identify clinical predictors for the presence of vessel wall calcifications.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ADVANCES IN KNOWLEDGE
 References
 
Study Design
The patient population recruited for this study comprises patients included in two randomized controlled trials in which the costs and effects of initial imaging tests in the diagnostic work-up of peripheral arterial disease were measured. Both studies were performed in the same university hospital. In the first study (12) performed between April 2000 and August 2001, patients with peripheral arterial disease were randomly assigned to undergo CT angiography or DSA as the initial imaging test. In a second study (11) performed between December 2001 and September 2003, patients with peripheral arterial disease were randomized between CT angiography and MR angiography.

Inclusion criteria for participation in both studies were age older than 18 years, symptomatic peripheral arterial disease, an ankle-brachial index of less than 0.90, and referral for diagnostic imaging work-up to evaluate the feasibility of a revascularization procedure. Exclusion criteria included contraindications to MR angiography (eg, pacemaker or claustrophobia) or CT angiography and DSA (eg, severe renal insufficiency or adverse reactions to iodinated contrast agents), and the necessity for an immediate intervention. Both trials were approved by the institutional review board, and informed consent was obtained for both studies. The approval and informed consent also applied to all retrospective studies deriving from these trials.

Imaging Technique and Evaluation
Multi–detector row CT angiography was performed with a scanner (Somatom Plus 4 Volume Zoom or Sensation 16; Siemens Medical Systems, Forchheim, Germany). After an initial scout image (120 kV, 100 mAs) was obtained, the scanning range was planned to encompass the entire vascular system, from the diaphragm to the level of the ankles. For optimal intraluminal contrast material enhancement, the delay time between the start of contrast material administration and the start of scanning was obtained for each patient individually by using a bolus-tracking technique (CARE-Bolus, Siemens Medical Systems). Each patient received 120 mL of iodixanol (Visipaque; Amersham Health, Buckinghamshire, England), 320 mg of iodine per milliliter, intravenously at a flow rate of 3 mL/sec.

Data were acquired craniocaudally with the following parameters for the 16- and four-section CT scanners, respectively: collimation, 0.75 and 2.50 mm; number of detector rows, 16 and four; pitch, 1.5 and 1.6; x-ray tube voltage setting, 120 kV for both; and current, 140 and 110 mAs. Transverse sections were reconstructed with a 2–3-mm section thickness at an interval of 1–1.5 mm. Postprocessing resulted in orthogonal curved planar reformations through the aortoiliac artery and rotating volume maximum intensity projections for aortoiliac, femoropopliteal, and crural arteries.

Two readers with experience in interpreting CT angiograms, a vascular radiologist (M.G.M.H.) with 13 years of postresidency experience and a dedicated researcher (R.O.) with 2.5 years of general radiology training and 1 year of experience in vascular radiology, independently evaluated all images for arterial stenosis or other abnormalities. For image interpretation, the readers used the curved planar reformations, the rotating-volume maximum intensity projections, and the source data on a workstation (EasyVision; Philips Medical Systems, Best, the Netherlands). For analytic purposes, the arterial vascular system was divided into 31 segments, namely, the distal aorta, the paired common iliac arteries, the external iliac arteries, the common femoral arteries, the deep femoral arteries, the superficial femoral arteries (proximal and distal parts), the popliteal arteries (above and below the knee), the anterior tibial arteries (proximal and distal parts), the tibial peroneal trunk, the posterior tibial arteries (proximal and distal parts), and the peroneal arteries (proximal and distal parts).

The following five-point scale was used to assign a grade to stenotic or occlusive disease: grade 0, stenosis of 0%–19%; grade 1, stenosis of 20%–49%; grade 2, stenosis of 50%–74%; grade 3, stenosis of 75%–99%; and grade 4, occlusion. When two or more stenotic luminal lesions were detected in the same vessel segment, the most severe lesion was used for assignment of a grade. Furthermore, the readers recorded the presence of vessel wall calcifications. The presence of calcifications (ranging from a single spot to extensive calcifications) in a segment was counted as 1, and the absence of calcifications was counted as 0. The final calcification score for each patient was the sum of the individual scores from all the segments, ranging from 0 to 31. After the first independent evaluation, the readers evaluated the images in a consensus reading. These consensus readings were used for the data analysis. All images were evaluated without knowledge of further work-up findings.

Measurement of Clinical Utility
In both studies, we assessed the therapeutic confidence of vascular radiologists and surgeons during the weekly vascular conference (11,12,14). In addition to patient history and physical examination findings, the findings of the initial imaging test were discussed and each clinician was asked to rate his or her individual confidence in making a well-founded therapeutic choice on a 10-point rating scale (score 1, absolutely uncertain, and score 10, absolutely certain). Furthermore, we measured the recommendations for additional imaging (duplex ultrasonography, DSA, MR angiography, or CT angiography) during the vascular conference. Any additional vascular imaging test performed within 6 months after the initial test was noted.

Measurement of Clinical Predictors
In both studies, we collected information concerning patient characteristics. Baseline data included information on history of cardiovascular disease and cardiovascular risk factors. The stage of peripheral arterial disease (intermittent claudication or critical ischemia) was assessed by the vascular surgeon. In regard to smoking history, patients were classified in two groups: patients who had ever smoked (current and former smokers) and patients who had never smoked. Hypertension was defined as a systolic blood pressure of 160 mm Hg or higher, a diastolic blood pressure of 100 mm Hg or higher, or current use of antihypertensive drugs for the indication of hypertension. Diabetes mellitus was defined as the current use of antidiabetic drugs. Hyperlipidemia was defined as the current use of lipid-lowering drugs. History of cardiac disease (including chest pain, percutaneous transluminal coronary angioplasty, coronary artery bypass graft, and myocardial infarction), cerebrovascular disease (including transient ischemic attack and stroke), renal disease (including renal insufficiency, hemodialysis, and renal transplantation), and previous vascular interventions (including percutaneous transluminal angioplasty and vascular surgery) were determined by means of direct questioning and medical records.

Statistical Analysis
The predictive ability of the number of calcified segments for prediction of the need for additional imaging and the confidence scores were assessed with univariable and multivariable logistic and linear regression analysis, respectively. The area under the receiver operating characteristic curve was calculated to assess the discriminatory power of the number of calcified segments in distinguishing patients who required additional imaging from those who did not. To evaluate which variables were predictive for the number of calcified segments, we first assessed each variable separately with univariable linear regression analysis and calculated the regression coefficient and the 95% confidence interval (CI). Subsequently, we performed multivariable linear regression analysis and included all variables that had a P value less than .1 in from the univariable analysis. The final multivariable model was obtained by using a stepwise backward selection with a significance level of .05.

To determine whether the effect of predictor variables on the number of calcified segments differed between three regions (aortoiliac, femoropopliteal, and crural), we calculated the percentage of calcified segments per region. Subsequently, we performed a multivariable linear regression analysis following the generalized estimating equations (GEE) approach, and we used the regional scores as the dependent variable and the same predictor variables as in the final model, with addition of the interaction terms with the regions. All calculations except those for the GEE analysis were performed with software (SPSS 11.0 for Windows; SPSS, Chicago, Ill). GEE analysis was performed with different software (Proc Genmod, SAS version 8.2; SAS Institute, Cary, NC).


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ADVANCES IN KNOWLEDGE
 References
 
In both studies a total of 152 patients were randomized to CT angiography (Fig 1). The final analysis included 145 patients, because seven patients participated in both studies (at different times; ie, they returned with recurrent symptoms) and were excluded from analysis. The baseline characteristics of the study population are shown in Table 1.


Figure 1
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Figure 1: Flow diagram of patients passing through both randomized controlled trials (RCTs) and those included in the current study. CTA = CT angiography, MRA = MR angiography. Numbers in square brackets are references.

 

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Table 1. Baseline Characteristics in 145 Patients

 
The distribution of the number of calcified segments was slightly skewed, with a median of 10 and a range of zero to 28. During the follow-up period, 40 patients underwent additional vascular imaging.

With univariable logistic and linear regression analysis, the number of calcified segments was a significant predictor of the need for additional imaging (odds ratio = 1.09; 95% CI: 1.03, 1.14; P = .001) and of the confidence scores (regression coefficient = –0.08; 95% CI: –0.10, –0.05; P < .001; R2 = 0.21). When all baseline characteristics were controlled in a multivariable model, the number of calcified segments was still a significant predictor of both the need for additional imaging and the confidence scores. Furthermore, the number of calcified segments discriminated well between patients who required additional imaging after CT angiography and those who did not (area under the receiver operating characteristic curve, 0.66; 95% CI: 0.54, 0.77) (Fig 2).


Figure 2
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Figure 2: Receiver operating characteristic curve for the number of calcified segments as a predictor of the need for additional vascular imaging.

 
Table 2 presents the regression coefficients and 95% CIs of all clinical variables that were assessed in the univariable linear regression analysis. Age, diabetes mellitus, cardiac disease, renal disease, and critical ischemia had P values of less than .1 and were subsequently used in the multivariable linear regression analysis (Table 3). We found that diabetes mellitus, cardiac disease, and age were independently predictive for the presence of vessel wall calcifications (all P < .05). The GEE analysis of the regional calcification scores showed that only the effect of age was significantly (P = .02) different for the three regions, the effect on the femoropopliteal region being about twice as strong as for the crural region, with the effect on the aortoiliac region between those for the other two regions.


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Table 2. Performance of Clinical Variables in Prediction of Number of Calcified Segments: Univariable Linear Regression Analysis

 

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Table 3. Performance of Clinical Variables in Prediction of Number of Calcified Segments: Multivariable Linear Regression Analysis

 

    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ADVANCES IN KNOWLEDGE
 References
 
Multi–detector row CT angiography is increasingly used to aid clinical decision making in patients who are suspected of having arterial occlusive disease. Because CT angiograms of extensively calcified vessels are difficult to interpret, it is important to evaluate the effect of vessel wall calcifications on the clinical utility of CT angiography. Subsequently, if vessel wall calcifications decrease the clinical utility of CT angiography, it would be useful to identify clinical predictors of calcifications in peripheral arteries to select patients for whom CT angiography is less clinically useful. With use of the data from two randomized controlled trials, we found that the number of calcified segments was a significant predictor of both the need for additional imaging and lower confidence scores. Furthermore, we showed that diabetes mellitus, cardiac disease, and elderly age were independently predictive for the presence of vessel wall calcifications.

Our results imply that CT angiography has decreased clinical utility for elderly patients (older than 84 years), patients with diabetes mellitus, and those with cardiac disease. In these patients, MR angiography should be considered as the initial imaging test. Although renal disease was only a significant predictor for calcified segments in the univariable analysis and not an independent predictor in the multivariable analysis, patients with renal disease will generally undergo MR angiography instead of CT angiography because of the nephrotoxicity of iodinated contrast agents. Furthermore, in patients with critical ischemia, the choice of test depends largely on the availability of imaging equipment and the urgency of the need for revascularization. If percutaneous intervention is deemed urgently necessary and possible, one should consider proceeding directly to the angiography suite, where DSA can be performed as the initial test, followed by an intervention.

Unlike the literature about prediction of coronary calcification, articles about prediction of calcifications in the arteries to the lower extremities are scarce. Researchers in one study (15) evaluated calcifications in plain radiographs of the pelvis and hands of patients undergoing hemodialysis. The authors reported that diabetes mellitus, male sex, age, duration of hemodialysis, and mean arterial pressure were independently associated with vessel wall calcifications in the arteries of the pelvis and hands, but they did not evaluate the history of cardiac disease as a predictor.

We acknowledge several limitations of our study. We used a limited sample size of 145 patients. A larger sample size would be better for identifying predictors of vessel wall calcifications. In particular, the number of patients with renal disease was limited, implying that our study probably could not have demonstrated renal disease as an independent predictor for calcified segments in the multivariable analysis even if it is predictive, which is likely. Another limitation is that we used data from two different studies. Although the studies were performed almost consecutively in the same center with the same inclusion and exclusion criteria, combining the data from two studies may have led to misclassification of baseline characteristics. The two studies involved different researchers, who may have applied the definitions for the baseline characteristics differently. Furthermore, diabetes mellitus was defined as the current use of antidiabetic drugs, and hyperlipidemia was defined as the current use of lipid-lowering drugs. These definitions could have led to misclassification because patients may have had undiagnosed diabetes or hyperlipidemia at the time of inclusion. Finally, vessel wall calcifications were not assigned scores quantitatively, as with calcium volume or Agatston scores (16). Quantitative measurement is a more accurate measure of the amount of calcification than the method we used and could lead to more precise prediction of vessel wall calcifications.

To the best of our knowledge, ours is the first study to evaluate the effect of vessel wall calcifications on the clinical usefulness of CT angiography in patients with peripheral arterial disease. We showed that vessel wall calcifications at CT angiography are associated with the need for additional vascular imaging and lower confidence in the imaging findings. This result implies that it would be useful to identify in advance patients for whom the initial CT angiographic findings would not be conclusive because of vessel wall calcifications and to refer these patients for another imaging modality. Although our study had several limitations, we performed an initial evaluation of clinical predictors of vessel wall calcifications at CT angiography. A future study is needed to develop and validate a clinical prediction rule for this problem. The results from the current study can be used to help design such a future study and restrict the data collection to the most relevant variables. In conclusion, the results of our study demonstrated that vessel wall calcifications decrease the clinical utility of CT angiography in patients with peripheral arterial disease and that diabetes mellitus, cardiac disease, and elderly age (older than 84 years) are independently predictive for the presence of vessel wall calcifications.


    ADVANCES IN KNOWLEDGE
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ADVANCES IN KNOWLEDGE
 References
 


    FOOTNOTES
 

Abbreviations: CI = confidence interval • DSA = digital subtraction angiography • GEE = generalized estimating equations

Authors stated no financial relationship to disclose.

Author contributions: Guarantor of integrity of entire study, M.G.M.H.; study concepts/study design or data acquisition or data analysis/interpretation, all authors; manuscript drafting or manuscript revision for important intellectual content, all authors; manuscript final version approval, all authors; literature research, R.O.; clinical studies, R.O., M.C.J.M.K., L.C.v.D., M.R.H.M.v.S.; statistical analysis, R.O., T.S., M.G.M.H.; and manuscript editing, R.O., M.G.M.H.


    References
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ADVANCES IN KNOWLEDGE
 References
 

  1. Rubin GD, Dake MD, Napel S, et al. Spiral CT of renal artery stenosis: comparison of three-dimensional rendering techniques. Radiology 1994;190(1):181–189.
  2. Rubin GD, Shiau MC, Leung AN, Kee ST, Logan LJ, Sofilos MC. Aorta and iliac arteries: single versus multiple detector-row helical CT angiography. Radiology 2000;215(3):670–676.[Abstract/Free Full Text]
  3. Catalano C, Fraioli F, Laghi A, et al. Infrarenal aortic and lower-extremity arterial disease: diagnostic performance of multi–detector row CT angiography. Radiology 2004;231(2):555–563.[Abstract/Free Full Text]
  4. Martin ML, Tay KH, Flak B, et al. Multidetector CT angiography of the aortoiliac system and lower extremities: a prospective comparison with digital subtraction angiography. AJR Am J Roentgenol 2003;180(4):1085–1091.[Abstract/Free Full Text]
  5. Ofer A, Nitecki SS, Linn S, et al. Multidetector CT angiography of peripheral vascular disease: a prospective comparison with intraarterial digital subtraction angiography. AJR Am J Roentgenol 2003;180(3):719–724.[Abstract/Free Full Text]
  6. Ota H, Takase K, Igarashi K, et al. MDCT compared with digital subtraction angiography for assessment of lower extremity arterial occlusive disease: importance of reviewing cross-sectional images. AJR Am J Roentgenol 2004;182(1):201–209.[Abstract/Free Full Text]
  7. Portugaller HR, Schoellnast H, Hausegger KA, Tiesenhausen K, Amann W, Berghold A. Multislice spiral CT angiography in peripheral arterial occlusive disease: a valuable tool in detecting significant arterial lumen narrowing? Eur Radiol 2004;14(9):1681–1687.[Medline]
  8. Romano M, Mainenti PP, Imbriaco M, et al. Multidetector row CT angiography of the abdominal aorta and lower extremities in patients with peripheral arterial occlusive disease: diagnostic accuracy and interobserver agreement. Eur J Radiol 2004;50(3):303–308.[CrossRef][Medline]
  9. Tins B, Oxtoby J, Patel S. Comparison of CT angiography with conventional arterial angiography in aortoiliac occlusive disease. Br J Radiol 2001;74(879):219–225.[Abstract/Free Full Text]
  10. Willmann JK, Wildermuth S, Pfammatter T, et al. Aortoiliac and renal arteries: prospective intraindividual comparison of contrast-enhanced three-dimensional MR angiography and multi–detector row CT angiography. Radiology 2003;226(3):798–811.[Abstract/Free Full Text]
  11. Ouwendijk R, de Vries M, Pattynama P, et al. Imaging peripheral arterial disease: a randomized controlled trial comparing contrast-enhanced MR angiography and multi–detector row CT angiography. Radiology 2005;236(3):1094–1103.[Abstract/Free Full Text]
  12. Kock MC, Adriaensen ME, Pattynama PM, et al. DSA versus multi–detector row CT angiography in peripheral arterial disease: randomized controlled trial. Radiology 2005;237(2):727–737.[Abstract/Free Full Text]
  13. Ouwendijk R, Kock MC, Visser K, Pattynama PM, de Haan MW, Hunink MG. Interobserver agreement for the interpretation of contrast-enhanced 3D MR angiography and MDCT angiography in peripheral arterial disease. AJR Am J Roentgenol 2005;185(5):1261–1267.[Abstract/Free Full Text]
  14. Adriaensen M, Kock M, Stijnen T, et al. Peripheral arterial disease: therapeutic confidence of CT versus digital subtraction angiography and effects on additional imaging recommendations. Radiology 2004;233(2):385–391.[Abstract/Free Full Text]
  15. Adragao T, Pires A, Lucas C, et al. A simple vascular calcification score predicts cardiovascular risk in haemodialysis patients. Nephrol Dial Transplant 2004;19(6):1480–1488.[Abstract/Free Full Text]
  16. Yamamoto H, Budoff MJ, Lu B, Takasu J, Oudiz RJ, Mao S. Reproducibility of three different scoring systems for measurement of coronary calcium. Int J Cardiovasc Imaging 2002;18(5):391–397.[CrossRef][Medline]



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