Journal of Diabetes and Its Complications 21 (2007) 69 – 74
Diagnostic accuracy of multislice computed tomography for the detection of coronary artery disease in diabetic patients Christof Burgstahler a,1, Torsten Beck a,1, Anja Reimannb, Axel Kuettnerb, Andreas F. Koppb, Martin Heuschmidb, Claus D. Claussenb, Stephen Schroeder a,4 a
Division of Cardiology, Department of Internal Medicine, Eberhard-Karls-University Tuebingen, 72076 Tuebingen, Germany b Department of Diagnostic Radiology, Eberhard-Karls-University Tuebingen, 72076 Tuebingen, Germany Received 15 August 2005; received in revised form 29 November 2005; accepted 29 December 2005
Abstract Background: Diabetes mellitus is an important risk factor for coronary artery disease. Cardiac multislice computed tomography (MSCT) permits visualization of the coronary arteries with good sensitivity and specificity. However, at present, there are no data whether MSCT allows an accurate assessment of coronary arteries of diabetic patients, in comparison to nondiabetic patients. Thus, we compared the catheter-controlled MSCT results from diabetic and nondiabetic patients in a cohort of 116 patients with regard to sensitivity, specificity, positive predictive value, and negative predictive value, as well as image quality. Methods and Materials: Twenty-two diabetic patients (age, 64.6F8.5 years; number of risk factors, 3.4F1.1) and 94 nondiabetic patients (age, 64.2F9.2 years; number of risk factors, 2.4F1.0) were examined by MSCT (Sensation 16 Speed 4 D, Siemens, Forchheim, Germany; gantry rotation time, 375 ms) and invasive coronary angiography. MSCT results were compared, blinded to the results of the coronary angiography with regard to the presence or absence of a significant stenosis (N50%) in a modified American Heart Association 13-segment model. Image quality was assessed on a qualitative scale between 1 (very good) and 5 (invisible) for each segment. Results: Sensitivity, specificity, positive predictive value, and negative predictive value were statistically not different in diabetic and nondiabetic patients (0.85/0.98/0.92/0.96 vs. 0.84/0.97/0.91/0.95). One diabetic and three nondiabetic patients had to be excluded from analysis. Diabetic patients had relevantly more risk factors ( P b .05), but calcium scoring was not different in both groups (Agatston score 1090F1278 vs. 798F1033). The image quality in both cohorts was comparable. Conclusions: MSCT allows the assessment of the coronary arteries noninvasively in diabetic patients with a good sensitivity and specificity, and diabetes does not have an impact on the number of evaluable segments. Thus, MSCT is a noninvasive tool in the care of these patients. D 2007 Elsevier Inc. All rights reserved. Keywords: Multislice computed tomography; Diabetes; 16 row; Coronary artery disease; Image quality
1. Introduction Coronary arteriosclerosis is known to be the major cause for morbidity and mortality in the industrial world. Worldwide, almost 17 million persons are dying annually as
4 Corresponding author. Tel.: +49 7071 2982711; fax: +49 7071 293169. E-mail address:
[email protected] (S. Schroeder). 1 Both authors contributed equally. 1056-8727/07/$ – see front matter D 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.jdiacomp.2005.12.002
a result of coronary artery disease (CAD) (Smith et al., 2004). Diabetes mellitus is one of several known risk factor to develop CAD (Sundell, 2005). Within the last years, spiral multislice computed tomography (MSCT) has shown to be a tool for noninvasive visualization of the coronary arteries. Modern MSCT scanners permit the detection of coronary lesions with good sensitivity and specificity (Kopp et al., 2000; Kuettner et al., 2005; Kuettner, Kopp, et al. 2004; Kuettner, Trabold, et al., 2004; Ropers et al., 2003; Schroeder et al., 2001). Published data concerning the diagnostic accuracy of MSCT in diabetic patients is available
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advanced heart failure (New York Heart Association III and IV). To reduce motion artefacts caused by elevated heart rate (Giesler et al., 2002; Schroeder et al., 2002) additional h-blockade with 50 to 100 mg metoprolol po was performed at least 30 min prior to the computed tomographic (CT) scan in patients with heart rates N65/min in 109 of 116 patients. 2.2. Multislice computed tomography
Fig. 1. (1) Volume rendering image showing a calcified left anterior descending artery (arrow). (2) Maximum intensity projection of the proximal part of the left anterior descending artery (arrow). The vessel is calcified, but image quality is still diagnostic. Ao: aorta, LA: left atrium. (3) Curved multiplanar reformation of a right coronary artery being free of stenosis. Image quality was judged as very good.
(Schuijf et al., 2004). However, at present, there is no data whether MSCT allows an accurate assessment of the coronary arteries of diabetic patients in a head-to-head comparison to nondiabetic patients. Thus, we compared the catheter-controlled MSCT results from diabetic and nondiabetic patients in a cohort of 116 patients with regard to sensitivity, specificity, positive predictive value, and negative predictive value and image quality. 2. Methods 2.1. Patients and study protocol The data of 116 consecutive patients scheduled for invasive coronary angiography because of suspicion of CAD or progression of previously diagnosed CAD were retrospectively enrolled in this study. The cohort consisted of 22 diabetic patients (age, 64.6F8.5 years; number of risk factors, 3.4F1.1) and 94 nondiabetic patients (age, 64.2F9.2 years; number of risk factors, 2.4F1.0). All patients were examined by MSCT and invasive coronary angiography. The study protocol had been approved by the local ethics committee, and all participants had given informed consent. Clinical exclusion criteria were renal failure (creatinine N1.5 mg/dl), unstable angina pectoris, acute myocardial infarction, known allergic reaction to contrast media, increased exposure to radiation in the last 12 months (N15 mSv), hyperthyroidism (basal thyroid stimulation hormone b0.03 mU/l in combination with elevated thyroid hormone levels in the peripheral blood, testing was done in all patients), known epilepsy, liver dysfunction (glutamic oxaloacetic and glutamic pyruvic transaminase values N3 reference value due to the possible potential for liver toxicity of iomeprol), and
MSCT was performed by using a Sensation 16 Speed 4 D (Siemens, Forchheim, Germany) scanner. This technique allows the application of dedicated spiral algorithms that provide up to 188 ms of temporal resolution. Electrocardiogram (ECG)-gated heart phase selective imaging reconstruction was used in all patients. After a low-dose precontrast spiral scan (collimation 16 1.5 mm, 3.8 mm table feed/rotation, 120 kV, 133 mAs, rotation time 375 ms) with simultaneously recorded ECG signal, a test bolus of 20 ml of contrast medium and a chaser bolus of 20 ml of physiological saline solution were injected through an 18-gauge catheter into an antecubital vein to determine the circulation time. The following scan protocol was used: 160.75-mm collimation, caudocranial scan direction, 80-cc contrast media (400 mg iodine/cc) with a biphasic injection protocol (50 ml at 4 ml/s and 30 ml at 2.5 ml/s), gantry rotation time 375 ms, temporal resolution 188 ms, effective slice thickness 1.0 mm, 120 kV, maximal 650 mAs. To reduce radiation exposure, ECG-triggered tube current modulation was used in all patients. All scans could be performed within one single breath-hold (15–20 s). Algorithms optimized for retrospective ECG-gated MSCT were used for reconstructing the raw data. According to prior studies, image reconstruction was performed in the diastolic phase with a relative retrospective gating of 60% for all coronary arteries in a first step. In case of impaired image quality, additional image reconstruction was performed at different RR intervals after a test series. The reconstructed data of the MSCT angiography (MSCTA) were transferred to a computer workstation for further processing (Leonardo [Siemens] or Vitrea 2, Vital Images, Minnetonka, MN, USA). The analyses were performed on conventional contrast-enhanced axial slices, as well as on 3D volume-rendering images (Fig. 1). 2.3. Image analysis The coronary tree was divided into 13 segments according to a modified American Heart Association scheme (Kuettner, Kopp, et al., 2004; Kuettner, Trabold, et al., 2004). The image quality of each segment was determined as: (1) excellent—free of motion artifacts, (2) good—mild motion artifacts, (3) relevant artifacts—but still diagnostic value, (4) severe calcification, and (5) insufficient image quality—missing or invisible segment. Segments with minor
C. Burgstahler et al. / Journal of Diabetes and Its Complications 21 (2007) 69 – 74 Table 1 Patient characteristics Number of patients Male Female Age (years) Number of risk factors Body mass index [range] Patients without stenotic CAD (according to invasive angiography) Stented segments Additional beta-blockade prior to CT scan Mean heart rate prior to CT scan (beats per minute) Agatston score Patients with Agatston score of zero Agatston score of patients with Agatston score N 0
Diabetic
Nondiabetic
22
94
17 (77%) 5 (23%) 64.6F8.5 3.4F1.1 29.4F4.1 [22.3-38.1] 7/22 (32%)
60 (64%) 34 (36%) 64.2F9.2 2.4F1.0 28.0F3.7 [20.2-36.6] 27/94 (29%)
N.S.
3/286 (1%) 12/22 (55%)
11/1222 (1%) 49/94 (55%)
N.S. N.S.
63F10
64F10
P value N.S. N.S. N.S. b.05 N.S.
N.S.
1090F1278 1/22 (5%)
798F1033 13/94 (14%)
N.S. N.S.
1199F1291
926F1063
N.S.
N.S.: not significant.
calcifications with or without additional motion artifacts were classified as segments with relevant artifacts in case of a still diagnostic image quality. Otherwise they were classified as segments with insufficient image quality. As previously reported, each narrowing of more than 50% of the vessel diameter was considered to be a significant stenosis (Nieman et al., 2002). The degree of stenosis severity was classified by visual judgement blinded to the results from invasive angiography. Vessel occlusion was defined as a total interruption of the contrast-enhanced lumen, whereas a missing segment showed no contrast enhancement at all. There was no exclusion of coronary segments in our analysis. The MSCT analysis was done in a consensus reading by two experienced radiologists blinded to the results from invasive coronary angiography, which was performed by a cardiologist. The results were compared by another independent physician. 2.4. Coronary angiography X-ray coronary angiography was performed by an experienced cardiologist according to standard procedures using the transfemoral Judkins technique in all cases. To visualize the right coronary artery at least two projections, for the left coronary artery, at least six different projections were performed. Stenosis severity was evaluated by quantitative coronary analysis (QCA V3.3, Philips, Eindhoven, Netherlands). 2.5. Statistics Continuous variables are described as means and standard deviations. Categorical data are presented with absolute frequencies and percentages. Chi-square tests were used to
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compare categorical data. Unpaired t tests were performed to evaluate differences between patient groups. Values of P b .05 were considered to reveal statistically relevant differences. All statistic analyses were done using Prism 3.0 (GraphPad Software, San Diego, CA, USA).
3. Results 3.1. Study population The study group consisted of 116 consecutive patients scheduled for conventional coronary angiography. Within the study group, there were 22 diabetic patients (age, 64.6F8.5 years, 21/22 type 2, HbA1c 7.3F0.7%, 9/22 insulin-dependent) and 94 nondiabetic patients (age, 64.2F9.2 years). One diabetic patient had to be excluded from the analysis because of extravasation of the contrast medium. From the nondiabetic group, three patients had to be excluded (one patient because of technical problems with the ECG; two patients did not receive invasive angiography). The number of risk factors was relevantly higher in the diabetic group (3.4F1.1 vs. 2.4F1.0, P b .05). The mean calcium burden expressed as Agatston score was not relevantly different between diabetic and nondiabetic patients (1090F1278 vs. 798F1033). However, from 14 patients without coronary calcifications, there was only one diabetic person, and we found significant CAD in 9 (64%) of 14 patients (8 nondiabetic), with an Agatston score of zero. Mean heart beat prior to the scan was not relevantly different. The number of patients without stenotic CAD was comparable in both groups (7/22 [32%] vs. 27/94 [29%]). The patient characteristics are summarized in Table 1. 3.2. Image quality 3.2.1. Diabetic patients Of 273 scanned segments, 86 (31.5%) showed excellent image quality. Ninety-six (35.1%) could be visualized with good image quality. Relevant artifacts that allowed only to distinguish between the presence or absence of vessel occlusion were seen in 32 (17.6%). Fifteen (5.5%) presented severe calcifications or stented lesions that did not allow to assess vessel narrowing accurately. Twenty-eight (10.6%) could not be visualized by MSCT. 3.2.2. Nondiabetic patients Of 1183 scanned segments, 305 (25.8%) showed excellent and 398 (33.6%), good image quality. Relevant artifacts were seen in 209 (17.7%), 186 (15.7%) presented severe calcifications or stented lesions, and 85 (7.2%) could not be visualized. The percentage of segments with diagnostic image quality (very good, good, and still diagnostic) was not relevantly different in diabetic and nondiabetic patients.
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Table 2 Diagnostic accuracy of MDCT in detecting/excluding significant lesions Sensitivity (%) Specificity (%) PPV (%) NPV (%) TP FP TN FN
Diabetic
Nondiabetic
Total
85 98 92 96 46 4 215 8
84 97 91 95 244 25 868 46
84 97 91 95 290 29 1083 54
PPV: positive predictive value, NPV: negative predictive value, TP: true positive, FP: false positive, TN: true negative, FN: false negative.
Severe calcified lesions that did not allow to assess the vessel lumen was relevantly higher in the nondiabetic group ( P b .0001), but the number of invisible segments was not relevantly different between the groups. 3.3. Lesion detection 3.3.1. Diabetic patients Forty-six (85%) of 54 significant stenosis (N50%) of the coronary vessels were correctly detected by MSCT. Two hundred fifteen (98%) of 219 segments without significant stenosis were correctly classified by MSCT. Sensitivity, specificity, positive predictive value, and negative predictive value were 0.85, 0.98, 0.92, and 0.96, respectively. 3.3.2. Nondiabetic patients Two hundred forty-four (84%) of 290 significant stenosis were correctly detected by MSCT. Of 893 segments without significant stenosis, 868 (97%) were correctly classified by MSCT. Sensitivity, specificity, positive predictive value, and negative predictive value were 0.84, 0.97, 0.91, and 0.95, respectively. Sensitivity, specificity and positive and negative predictive values were statistically not different between diabetic and nondiabetic patients (chi-square test). The data for sensitivity, specificity, positive predictive value, and negative predictive value for each group and the total cohort are given in Table 2.
4. Discussion As at the beginning of the MSCT era, coronary imaging was limited to the proximal vessel segments (Achenbach et al., 2001); continuous modifications of hardware and scan protocol, e.g., lowering of the heart rate by application of beta-blockers (Giesler et al., 2002; Schroeder et al., 2002), has led to a significant stabilization and improvement of image quality (Achenbach, 2004). Important determinants are temporal and spatial resolution. Another improvement could be achieved by the 16-row MSCT scanner generation with a temporal resolution of 188 ms and an effective slice thickness of 1.0 mm. The total scan time could be reduced to 15 to 20 s
and a complete heart scan could, thus, be performed within one single breath-hold, reducing breathing artifacts. The most important finding of the present study is that diabetic patients who are at an elevated risk to develop symptomatic and asymptomatic CAD can be reliably diagnosed noninvasively by the use of MSCT. In our study, we could show that the diagnostic accuracy of MSCT in the detection of severe coronary artery stenosis in diabetic patients is comparable to nondiabetic patients. Sensitivity and specificity for the detection or exclusion of severe lesions were not relevantly different in both groups. This might be caused by the fact that the number of analyzable segments was equal in diabetic and nondiabetic patients. Moreover, our results confirm data published before (Nieman et al., 2002; Ropers et al., 2003). Just recently, data from 64-slice scanners were published (Leber et al., 2005; Leschka et al., 2005; Raff, Gallagher, O’Neill, & Goldstein, 2005), showing an even more accurate assessment of the coronary arteries and plaque area. However, in contrast to some 64-slice data, patients with known CAD or elevated calcium scores were not excluded in our cohort. The percentage of diagnostic segments did not differ relevantly between diabetic and nondiabetic patients. However, we found a statistically relevant difference in the segments judged as being severely calcified with more severely calcified lesions in the nondiabetic group. As neither the percentage of stented lesions nor the degree of calcification expressed in Agatston score were different between the two groups, it might be possible that diabetic patients have a more diffuse pattern of coronary calcifications. Probably, diabetic patients receive more aggressive lipid-lowering therapy—even if they are asymptomatic— than nondiabetic patients. In that case, the progression of coronary calcification—that might be present in more segments than in asymptomatic nondiabetic patients—might be slowed down, leading to a more diffuse pattern of calcification. However, in our retrospective study, we did not focus on this interesting topic, which should be evaluated in prospective trials. Comparable to previous data from our group (Schroeder et al., 2003), it could be demonstrated, again, that the absence of coronary calcifications (especially in nondiabetic patients) does not rule out significant CAD. Whether these data are transferable to diabetic patients remains unclear, as only one patient from the diabetic group showed no coronary calcification but significant disease. In contrast to the study published by Schuijf et al. (2004), the number of evaluable segments was higher in our cohort, and the overall sensitivity and specificity was higher. This might be explained by the fact that a newer scanner generation with an improved gantry rotation time was used in our study. Moreover, the data assessed by Schuijf et al. were based on two different scanner types, and lowering the heart rate by beta-blockers was not performed. Our results therefore underline the need of lowering the heart rate to achieve optimal image quality and accuracy in MSCTA.
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Diabetic patients are at elevated risk to develop CAD but may not have typical symptoms due to diabetic neuropathy. Besides the detection of CAD in symptomatic individuals, MSCT can help to detect asymptomatic patients with subclinical CAD or pathological stress testing without clinical symptoms. In this setting, MSCT might be understood as tool for further risk assessment or as another pretest before invasive angiography. Thus, MSCT might become a very important noninvasive diagnostic modality in the care of these patients. However, if MSCT is performed in patients for risk assessment, contrast-enhanced scans should be performed. Only in that case can persons without coronary calcifications but with evidence of coronary atherosclerosis be also detected noninvasively. One limitation of CT remains the radiation exposure. Although ECG-pulsed tube current modulation was used in all patients, a radiation exposure of at least 6 mSv (Gerber, Stratmann, Kuzo, Kantor, & Morin, 2005; Trabold et al., 2003) has to be calculated for calcium scoring and MSCTA. This remains one main limitation of noninvasive MSCT coronary angiography. Another important issue is the need of iodinated contrast medium with a potential risk of nephrotoxicity. Thus, especially in patients with severely impaired renal function, alternative noninvasive modalities like stress magnetic resonance imaging should be considered. 4.1. Study limitations The data of this study are based on retrospective findings, and the number of diabetic patients is limited. Prospective studies with larger patient number are required to reevaluate our results. In addition, only one patient of the cohort had diabetes mellitus type 1. Thus, it remains unclear whether these results are transferable to those patients. 4.2. Conclusions The 16-slice MSCT technology with a fast gantry rotation time does allow for the detection of significant coronary lesions with high sensitivity and specificity in diabetic and nondiabetic patients. In our study, diabetes mellitus did not have an impact on the diagnostic accuracy of MSCT and did not influence the number segments with diagnostic image quality. Thus, MSCT is a noninvasive method to detect or rule out CAD also in patients with diabetes mellitus. These retrospective data have to be confirmed in larger prospective trials. References Achenbach, S. (2004). Detection of coronary stenoses by multidetector computed tomography: It’s all about resolution. Journal of the American College of Cardiology, 43, 840 – 841. Achenbach, S., Giesler, T., Ropers, D., Ulzheimer, S., Derlien, H., Schulte, C., et al. (2001). Detection of coronary artery stenoses by contrastenhanced, retrospectively electrocardiographically-gated, multislice spiral computed tomography. Circulation, 103, 2535 – 2538.
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