Original Research
Cardiac Imaging
June 2008

Effect of Decrease in Heart Rate Variability on the Diagnostic Accuracy of 64-MDCT Coronary Angiography

Abstract

OBJECTIVE. The purpose of this study was to evaluate the effect of average heart rate and heart rate variability on the diagnostic accuracy of 64-MDCT in the assessment of coronary artery stenosis.
SUBJECTS AND METHODS. CT and invasive coronary angiography were performed on 114 patients (mean age, 62 years) referred for known coronary artery disease (n = 26), atypical chest pain (n = 58), and presurgical exclusion of coronary artery disease before abdominal aortic (n = 14) or cardiac valve (n = 16) surgery. The population was divided into two groups depending on median average heart rate (60.0 beats/min) and median heart rate variability (2.7 beats/min) during scanning. Heart rate variability was calculated as SD from the mean heart rate. Two blinded observers using a 4-point scale independently assessed the quality of images of each coronary artery segment and classified each segment as being stenosed (luminal diameter narrowing > 50%) or not. Invasive coronary angiography was used as the reference standard.
RESULTS. In 71 (62.3%) of the patients, 241 significant coronary artery stenoses were identified with invasive coronary angiography. In 11 (9.7%) of the patients, 1.6% (26/1,672) of the segments were not evaluable with CT. Overall sensitivity, specificity, and positive and negative predictive values in a patient-based analysis were 97%, 81%, 90%, and 95%, respectively. Image quality was better (p < 0.05) in the low average heart rate group than in the high average heart rate group, but diagnostic accuracy was comparable for the two groups. In contrast, image quality and diagnostic accuracy were significantly better (p < 0.01) among patients in the low heart rate variability group than in the high heart rate variability group.
CONCLUSION. Lower heart rate variability is associated with higher diagnostic accuracy of 64-MDCT coronary angiography.

Introduction

Hemodynamically significant coronary artery stenosis can be reliably detected or excluded with MDCT [1-7]. The advent of 64-MDCT scanners with their high temporal and spatial resolution has brought noninvasive technique into clinical practice [8, 9]. In addition to obesity [7], breathing artifacts [10], calcified plaques [7], and coronary artery stents [11], the patient's average heart rate during scanning affects the image quality of CT coronary angiography [12]. Heart rate control by administration of oral or IV β-receptor antagonists [13] is recommended for 64-MDCT [1, 3, 6, 7]. A study [14] has shown that an irregular heart rate deteriorates the image quality of 64-MDCT coronary angiography more so than does an average heart rate during scanning. Although the general dependence of image quality on heart rate during CT coronary angiography is well agreed on in the literature [14-16], to the best of our knowledge, the influence of average heart rate and heart rate variability on diagnostic accuracy has not been systematically investigated. The aim of this study was to prospectively evaluate, with invasive coronary angiography as the reference standard, the dependence of the diagnostic accuracy of 64-MDCT coronary angiography on average heart rate and variability of heart rate during scanning in the assessment of coronary artery stenosis.

Subjects and Methods

Study Population

Between May 2005 and October 2005, we prospectively enrolled 120 consecutively register ed patients (42 women, 78 men; mean age, 64.1 ± 11.2 [SD] years; range, 30-83 years) for coronary CT angiography. Six patients were excluded because of previous allergic reactions to iodinated contrast media in two cases, renal insufficiency (creatinine level > 120 μmol/L in one case, and nonsinus rhythm in two cases. One patient denied written informed consent. Thus the final study population comprised 114 patients (41 women, 73 men; mean age 62.2 ± 11.1 years; range, 30-83 years). Indications for coronary CT angiography were known coronary artery disease (CAD) (n = 26), atypical chest pain suggestive of CAD (n = 58), and presurgical exclusion of CAD before abdominal aortic surgery (n = 14) or cardiac valve surgery (n = 16). The mean body mass index (BMI) (weight in kilograms divided by height squared in meters) was 26.3 ± 4.2 kg/m2 (range, 17.2-35.8 kg/m2). At the time of CT, 63 (55.3%) of the patients were taking the following oral negative chronotropic drugs as part of their baseline medication: the β-receptor antagonists atenolol (mean daily dose, 72 ± 22 mg; range, 50-100 mg) in 29 cases and metoprolol (mean daily dose, 199 ± 74 mg; range, 100-300 mg) in 34 cases and the calcium channel blocker amlodipine (mean daily dose, 7 ± 3 mg; range, 5-10 mg) in 12 cases. Reasons for medication were management of arterial hypertension in 56 cases and long-term management of angina pectoris in 22 cases. No additional β-blockers were administered before CT. The study protocol was approved by the local ethics committee, and written informed consent was obtained from all patients.

CT Protocol

All examinations were performed with a 64-MDCT scanner (Somatom Sensation 64, Siemens Medical Solutions). The scanning range covered the heart from the level of tracheal bifurcation to the diaphragm. A bolus of 80 mL of iodixanol (Visipaque 320, 320 mg/mL, GE Healthcare) followed by 30 mL of saline solution was injected at a rate of 5 mL/s. Contrast administration was controlled with bolus tracking. One radiologist placed a region of interest into the aortic root, and image acquisition was started 5 seconds after attenuation reached the predefined threshold of 140 H. Data acquisition was performed in a craniocaudal direction at detector collimation, 32 × 0.6 mm; slice collimation, 64 × 0.6 mm with a z-flying focal spot; gantry rotation time, 330 milliseconds; pitch, 0.2; tube potential, 120 kV; effective tube current-time product, 650 mAs. ECG pulsing for radiation dose reduction [17] was used in all patients.

CT Image Reconstruction

The adaptive cardiac volume approach was used for image reconstruction [18]. Data sets were retrospectively reconstructed in synchronization with ECG data during the mid- to end-diastolic phase with reconstruction windows set at 60-70% of the R-R interval. In the case of insufficient image quality, additional reconstructions were performed in 5% steps of the R-R interval within the full tube current window. Images were reconstructed from the CT data sets at slice thickness, 0.75 mm; reconstruction increment, 0.5 mm; medium soft-tissue convolution kernel (B30f). The reconstructed field of view was adjusted to exactly encompass the heart (mean field of view, 149 ± 34 mm; range, 129-182 mm; matrix size, 512 × 512). All images were transferred to a separate workstation (Wizard, Siemens Medical Solutions) equipped with cardiac postprocessing software (Syngo Circulation, Siemens Medical Solutions).

CT Data Analysis

Coronary arteries were subdivided according to a 15-segment model proposed by the American Heart Association [19], and all segments with a diameter of at least 1.5 mm at the origin were included. Diameter measurements were performed with an electronic caliper tool. Axial source images, multiplanar reformations, and thin-slab maximum intensity projections were evaluated by two independent blinded readers. First, the two readers semiquantitatively rated the image quality of each coronary segment on a 4-point scale as follows: 1, excellent (no artifacts, unrestricted evaluation); 2, good (minor artifacts, good diagnostic quality); 3, adequate (moderate artifacts but still acceptable and diagnostic); and 4, not evaluative (severe artifacts impairing accurate evaluation). For each coronary artery segment, both observers selected the individual optimal reconstruction interval with the least motion artifacts. Second, both observers visually estimated all coronary artery segments for the presence of significant stenoses, defined as more than 50% narrowing of the luminal diameter. In the event of disagreement at data analysis, consensus was achieved.
A third observer, who was not involved in image quality reading or stenosis assessment, used the recorded ECG information to document the heart rate of each cardiac cycle. For calculation of heart rate variability, the length of each heartbeat during CT acquisition was measured for each patient. The variability of heart rate during scanning was calculated as the SD from the average heart rate from this set of measurements, as previously described [14].

Invasive Coronary Angiography

All patients underwent invasive coronary angiography within 4 weeks after CT (mean, 10.1 ± 8.9 days; range, 0-26 days). Invasive coronary angiography was performed according to standard techniques, and multiple views were stored on a CD-ROM. The angiograms were evaluated by one experienced observer, who was blinded to the results of CT coronary angiography. Coronary arteries were subdivided according to the model described for CT data analysis [19]. With visual estimation, each vessel segment was scored as being significantly stenosed (diameter reduction > 50%) or not stenosed.

Statistical Analysis

Quantitative variables were expressed as mean ± SD, and categoric variables as frequencies or percentages. The median of the average heart rate and the median of the variability of the heart rate during scanning (i.e., the SD of the mean heart rate) were used as cutoff points to subdivide the patients into two average heart rate groups and two heart rate variability groups. The Fisher's exact test was used to evaluate categoric data (prevalence of coronary stenosis, sex distribution, and β-blocker use among heart rate groups and variability groups). Wilcoxon's signed rank test for paired samples was used to evaluate quantitative parameters stratified across the heart rate groups (age, BMI, variability of heart rate) and variability groups (age, BMI, average heart rate) and for comparison of image quality between the heart rate groups and the heart rate variability groups. Interobserver agreement for image quality readout and assessment of significant coronary artery stenosis was calculated with kappa statistics. A kappa value of 0.80 or higher was considered excellent agreement; between 0.40 and 0.80, moderate to substantial agreement; between 0.20 and 0.40, fair agreement; and 0.20 or less, slight or poor agreement. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated from results of chi-square tests of contingency, and 95% CI was calculated from binomial expression. Invasive coronary angiography was considered the standard of reference.
Nonevaluable segments were censored as positive findings in the vessel-based and patient-based analyses, reflecting the intention-to-diagnose nature of the study [20]. The statistics were calculated in segment-based and patient-based analyses (presence of at least one significant coronary artery stenosis or absence of any significant stenosis in each patient). Overall diagnostic accuracy for assessment of coronary artery stenosis was individually calculated for each patient as the sum of true-positive and true-negative findings divided with the individual number of segments per patient. Pearson correlation analysis was performed to compare the overall diagnostic accuracy for each patient with the average heart rate and the SD of the mean heart rate during CT. A value of p < 0.05 indicated a statistically significant difference. All statistical analysis was performed with SPSS statistical software (version 12.0, SPSS).
Fig. 1A 60-year-old man with atypical chest pain. Average heart rate was 75.6 beats/min, and heart rate variability was 1.6 beats/min. Image quality of 64-MDCT coronary angiography was rated good to excellent in all segments. Curved planar CT image along centerline of left anterior descending artery shows coronary artery stenosis in proximal segment. Reconstructions perpendicular to proximal left anterior descending artery (magnified views 1-3) show noncalcified plaque causing approximately 70% luminal diameter stenosis. Maximum intensity projection (inset 4) shows plaque composed of calcified and noncalcified portions.
Fig. 1B 60-year-old man with atypical chest pain. Average heart rate was 75.6 beats/min, and heart rate variability was 1.6 beats/min. Image quality of 64-MDCT coronary angiography was rated good to excellent in all segments. Invasive coronary angiogram corresponding to (A) confirms CT diagnosis of high-grade stenosis in proximal left anterior descending artery (arrow).

Results

Image Quality of Coronary Artery Segments

A total of 1,672 coronary artery segments were evaluated in 114 patients. Interobserver agreement for image quality rating was good (κ = 0.75). With use of the individual reconstruction interval with the best image quality for each segment, image quality was graded excellent (score 1) for 45.9% (768/1,672) of the coronary artery segments, good (score 2) for 37.8% (633/1,672), and adequate (score 3) for 14.7% (245/1,672). Image quality was graded not evaluative (score 4) for 1.6% (26/1,672) of the segments (six right coronary artery segments, six left anterior descending coronary artery segments, 14 left circumflex artery segments) even when the best individual reconstruction interval was used. As many as five nonevaluable coronary artery segments (mean, 2.4 ± 1.3 segments; range, 1-5 segments) were present in 9.7% (11/114) of the patients. In patients who had nonevaluable segments, mean image quality score was 2.6 ± 0.5 (range, 1.93-3.21), average heart rate was 63.9 ± 12.5 beats/min (range, 50-82 beats/min), and variability of heart rate was 8.1 ± 4.2 beats/min (range, 2.7-15.5 beats/min).

Overall Diagnostic Accuracy in Assessment of Coronary Artery Stenosis

A total of 241 coronary artery stenoses with luminal diameter narrowing greater than 50% were identified with invasive coronary angiography in 71 (62.3%) of the patients. Single-vessel disease was present in 14.0% (16/114), two-vessel disease in 14.0% (16/114), and three-vessel disease in 34.3% (39/114) of the patients. Significant coronary artery stenosis was absent in 37.7% (43/114) of the patients. The kappa value for detection of coronary artery stenosis with CT was 0.86, indicating excellent interobserver agreement. CT coronary angiography correctly depicted 218 of 241 significant stenoses detected with invasive coronary angiography (Figs. 1A and 1B). Among the 23 lesions missed by both readers, image quality was rated other than excellent for 20 (87.0%) of the segments because of motion artifacts. In 48 segments, lesions were incorrectly graded as stenotic on CT. If all 26 nonevaluable segments are considered false-positive findings, a total of 74 false-positive ratings were made. Thus the overall sensitivity of CT coronary angiography in segment-based analysis was 90.5% (218/241; 95% CI, 86.0-93.9), the specificity was 94.8% (1,357/1,431; 95% CI, 93.6-95.9), the positive predictive value was 74.7% (218/292; 95% CI, 69.3-79.5), and the negative predictive value was 98.3% (1,357/1,380; 95% CI, 97.5-98.9).
CT correctly depicted at least one significant coronary artery stenosis in 97.2% (69/71) of patients with significant CAD on invasive coronary angiography; the diagnosis was missed in two patients (2.8%). In six (5.3%) of the 114 patients, CAD was not found at invasive coronary angiography, but CT evidence suggested the presence of significant stenosis. False ratings with CT led to the diagnosis of multivessel disease instead of one-vessel disease in 10 patients. The misdiagnosis of one-vessel disease was made with CT in the cases of two patients in whom multivessel disease was found on invasive coronary angiography. In two of the 11 patients with not completely evaluative CT angiograms, coronary stenosis was absent on invasive coronary angiography, and therefore the findings had to be considered false-positive (Figs. 2A and 2B). In the other nine patients with nonevaluable segments, coronary artery stenosis was identified in at least one evaluable segment, correctly indicating the need for invasive coronary angiography. In patient-based analysis, the overall sensitivity of CT coronary angiography was 97.2% (69/71; 95% CI, 90.2-99.7), the specificity was 81.4% (35/43; 95% CI, 66.6-91.6), the positive predictive value was 89.6% (69/77; 95% CI, 80.6-95.4), and the negative predictive value was 94.6% (35/37; 95% CI, 81.8-99.3).
Fig. 2A 56-year-old man with known coronary artery disease. Average heart rate was 66.1 beats/min and heart rate variability was 5.9 beats/min. Image quality of 64-MDCT coronary angiography was rated good in proximal and distal segments of right coronary artery (RCA). Curved planar CT image along centerline of RCA suggests presence of coronary stenosis in proximal RCA (arrowhead); severe blurring in middle segment (arrow) results in nonevaluable image quality (score 4).
Fig. 2B 56-year-old man with known coronary artery disease. Average heart rate was 66.1 beats/min and heart rate variability was 5.9 beats/min. Image quality of 64-MDCT coronary angiography was rated good in proximal and distal segments of right coronary artery (RCA). Invasive coronary angiogram corresponding to A confirms presence of stenosis in proximal RCA and proves absence of significant coronary artery stenosis in mid RCA.

Diagnostic Accuracy in Relation to Average Heart Rate

The median of the average heart rate among all 114 patients was 60.0 beats/min; thus 57 (50.0%) of the patients had a heart rate of 60.0 beats/min or less (mean, 52.4 ± 4.7 beats/min), and 57 (50.0%) a heart rate greater than 60.0 beats/min (mean, 71.8 ± 9.8 beats/min). There were no statistically significant differences in patient age (p = 0.92), BMI (p = 0.66), or heart rate variability (p = 0.77), but there were significantly (p < 0.05) fewer women in the low average heart rate group than in the high average heart rate group. There was no significant difference in use of β-blocker medication for the two heart rate subgroups (p = 0.24). Tables 1 and 2 summarize the demographic data, image quality scoring results, and diagnostic accuracy in the two heart rate subgroups.
TABLE 1: Demographic Data and Image Quality Scoring Results for Heart Rate Subgroups
Heart Rate Group
Characteristic≤ 60 Beats/Min> 60 Beats/Minp
No. of patients57 (50.0)57 (50.0) 
No. of segments with >50% stenosisa172/844 (20.4)69/828 (8.3)< 0.05 b
Age (y)62.9 ± 10.361.6 ± 12.00.92c
Male/female ratio43/1430/27< 0.05 b
Body mass index (kg/m2)26.3 ± 4.026.3 ± 4.40.66c
No. of patients using β-receptor antagonist33 (57.9)30 (52.6)0.24b
Average heart rate (beats/min)52.4 ± 4.771.8 ± 9.8< 0.01 c
Heart rate variability (beats/min)d3.4 ± 2.73.5 ± 2.50.77c
Image quality score   
Average motion-related artifacts score at consensus reading1.62 ± 0.601.82 ± 0.55< 0.05 c
No. of arterial segments with score   
1447 (53.0)321 (38.8) 
2282 (33.4)351 (42.4) 
3103 (12.2)142 (17.1) 
4
12 (1.4)
14 (1.7)

Note—Values are number with percentage in parentheses or mean ± SD. Statistically significant differences are displayed bold.
a
More than 50% narrowing of luminal diameter as identified on invasive coronary angiography.
b
Fisher's exact test.
c
Wilcoxon's signed rank test.
d
Heart rate variability calculated as SD of heart rate during scanning.
TABLE 2: Diagnostic Accuracy in Heart Rate Subgroups
≤60 Beats/Min Group>60 Beats/Min Group
 Segment-BasedPatient-BasedSegment-BasedPatient-Based
Valuen%95% CIn%95% CIn%95% CIn%95% CI
Sensitivity157/17291.386.0-95.045/4697.888.5-99.961/6988.478.4-94.924/2596.079.7-99.9
Specificity633/67493.991.8-95.68/1172.739.0-94.0732/76595.794.0-97.027/3284.467.2-94.7
Positive predictive value157/19879.373.0-84.745/4893.882.8-98.761/9464.954.4-74.524/2982.864.2-94.2
Negative predictive value
633/648
97.7
96.2-98.7
8/9
88.9
51.8-99.7
732/740
98.9
97.9-99.5
27/28
96.4
81.7-99.9
With use of the individual reconstruction interval with best image quality for each coronary artery segment, mean image quality was significantly better in the cases of patients with heart rates of 60.0 beats/min or less (score, 1.62 ± 0.60) than in those of patients with a heart rate greater than 60.0 beats/min (score, 1.82 ± 0.55) (p < 0.05). In contrast, the percentages of nonevaluable segments were comparable for the two heart rate subgroups at 1.4% (12/844) and 1.7% (14/828).
Significant coronary artery stenosis was present in 20.4% (172/844) of segments in patients with a heart rate of 60.0 beats/min or less and in 8.3% (69/828) of segments in patients with a heart rate greater than 60.0 beats/min (p < 0.05). At a heart rate of 60.0 beats/min or less, 15 false-negative and 41 false-positive ratings (29 because of misclassification, 12 because of inclusion of nonevaluable segments) were made with CT. At a heart rate greater than 60.0 beats/min, eight false-negative and 33 false-positive ratings (19 because of misclassification, 14 because of inclusion of nonevaluable segments) were made with CT. There was no tendency toward decreased diagnostic accuracy in association with elevated heart rate in per-segment or per-patient analysis (Tables 1 and 2). Pearson correlation analysis revealed no significant correlation between average heart rate and overall diagnostic accuracy per patient (r = -0.05, p = 0.79) (Fig. 3).

Diagnostic Accuracy in Relation to Variability of Heart Rate

The median of heart rate variability for all 114 patients was 2.7 beats/min; thus 57 (50.0%) patients had a heart rate variability of 2.7 beats/min or less (mean, 1.8 ± 0.7 beats/min) and 57 (50.0%) had a variability greater than 2.7 beats/min (mean, 5.2 ± 2.7 beats/min). There were no statistically significant differences in patient age (p = 0.12), BMI (p = 0.42), average heart rate (p = 0.47), or sex (p = 0.57) for the two heart rate variability groups. There was a significantly lower rate of β-blocker use by patients with a heart rate variability greater than 2.7 beats/min than by patients with a variability of 2.7 beats/min or less (p < 0.05). Tables 3 and 4 summarize the demographic data, image quality scoring results, and diagnostic accuracy for the subgroups of heart rate variability.
TABLE 3: Demographic Data and Image Quality Scoring Results for Heart Rate Variability Subgroups
Heart Rate Variability Group
Characteristic≤2.7 Beats/Min>2.7 Beats/Minp
No. of patients57 (50.0)57 (50.0) 
No. of segments with > 50% stenosisa138/841 (16.4)103/831 (12.4)0.09b
Age (y)65.2 ± 8.459.3 ± 12.80.12c
Male/female ratio37/2036/210.57b
Body mass index (kg/m2)26.0 ± 4.126.6 ± 4.30.42c
No. of patients using β-receptor antagonist40 (70.2)23 (40.4)< 0.05 b
Average heart rate (beats/min)61.4 ± 13.362.9 ± 11.50.47c
Heart rate variability (beats/min)d1.8 ± 0.75.2 ± 2.7< 0.01 c
Image quality score   
Average motion-related artifacts score at consensus reading1.38 ± 0.352.05 ± 0.57< 0.01 c
No. of arterial segments with score   
1553 (65.8)215 (25.9) 
2253 (30.1)380 (45.7) 
334 (4.0)211 (25.4) 
4
1 (0.1)
25 (3.0)

Note—Values are number with percentage in parentheses or mean ± SD. Statistically significant differences are displayed bold.
a
More than 50% narrowing of luminal diameter as identified on invasive coronary angiography.
b
Fisher's exact test.
c
Wilcoxon's signed rank test.
d
Heart rate variability calculated as SD of heart rate during scanning.
TABLE 4: Diagnostic Accuracy in Heart Rate Variability Subgroups
≤ 2.7 Beats/Min Group> 2.7 Beats/Min Group
 Segment-BasedPatient-BasedSegment-BasedPatient-Based
Valuen%95% CIn%95% CIn%95% CIn%95% CI
Sensitivity131/13894.989.8-97.937/37100.090.5-10087/10384.576.0-90.932/3494.180.3-99.3
Specificity689/70497.996.5-98.817/2085.062.1-96.8676/73592.089.8-93.818/2378.356.3-92.5
Positive predictive value131/14689.783.6-94.137/4092.579.6-98.487/14659.651.2-67.632/3786.571.2-95.5
Negative predictive value
689/696
99.0
97.9-99.6
17/17
100.0
80.5-100
676/692
97.7
96.3-98.7
18/20
90.0
68.3-98.8
Fig. 3 Diagnostic accuracy in relation to average heart rate during CT. Linear regression plot shows overall diagnostic accuracy for assessment of coronary artery stenosis calculated for each patient as sum of true-positive and true-negative ratings divided by number of segments per patient. Dotted lines represent 95% confidence limits. Linear correlation indicates no significant dependence of diagnostic accuracy on average heart rate (Pearson r = -0.05, p = 0.79). Circles indicate individual patients represented by overall diagnostic accuracy (y-axis) plotted against average heart rate during scan acquisition (x-axis).
Fig. 4 Diagnostic accuracy in relation to variability of heart rate during CT. Linear regression plot shows overall diagnostic accuracy for assessment of coronary artery stenosis calculated for each patient as sum of true-positive and true-negative ratings divided by number of segments per patient. Dotted lines represent 95% confidence limits. Linear correlation indicates significant decrease in diagnostic accuracy with increasing heart rate variability (Pearson r = -0.61, p < 0.01). Circles indicate individual patients represented by overall diagnostic accuracy (y-axis) plotted against SD of heart rate during data acquisition (x-axis).
Mean image quality was significantly better in the cases of patients with minor variability (score, 1.38 ± 0.35) than in the cases of patients with higher heart rate variability (score, 2.05 ± 0.57) (p < 0.01). Among patients with more regular heart rhythm (i.e., variability ≤ 2.7 beats/min), only one (0.1%) of 841 segments was considered nonevaluable. Greater heart rate variability (> 2.7 beats/min) was associated with a higher rate (3.0% [25/831]) of nonevaluable coronary segments.
As identified with invasive coronary angiography, significant coronary artery stenosis was present in 16.4% (138/841) of the segments in patients with a heart rate variability of 2.7 beats/min or less, whereas 12.4% (103/831) of the segments were stenosed in patients with a heart rate variability greater than 2.7 beats/min (p = 0.09). In the lower variability group, seven false-negative and 15 false-positive ratings (14 because of misclassification, one because of inclusion of nonevaluable segments) were made with CT. At a heart rate variability greater than 2.7 beats/min, 16 false-negative and 59 false-positive ratings (34 because of misclassification, 25 because of inclusion of nonevaluable segments) were made with CT. The highest diagnostic accuracy was observed in the group with less-variable heart rhythm (≤ 2.7 beats/min) at a sensitivity of 94.9%, specificity of 97.9%, positive predictive value of 89.7%, and negative predictive value of 99.0% in per-segment analysis. With heart rate variability greater than 2.7 beats/min, there was substantial deterioration in accuracy, sensitivity declining to 84.5%, specificity to 92.0%, and positive predictive value to 59.6%; negative predictive value remained high at 97.7%. Similar results were obtained in a patient-based analysis. Sensitivity decreased from 100% to 94.1%, specificity from 85.0% to 78.3%, positive predictive value from 92.5% to 86.5%, and negative predictive value from 100% to 90.0% among patients with heart rate variability greater than 2.7 beats/min compared with the lower heart rate variability group. Pearson correlation analysis revealed a significant correlation between heart rate variability during scanning and diagnostic accuracy per patient (r = -0.61, p < 0.01) (Fig. 4).

Discussion

Because of its yet unmatched spatial and temporal resolution, invasive coronary angiography is considered the reference standard for evaluation of CAD. Nevertheless, the invasive nature, risk of serious complications, and high cost of the procedure have led to a search for noninvasive alternatives. Rapid advances in CT technology have generated immense interest in the use of CT to image coronary arteries. Studies [1-7] comparing 64-MDCT coronary angiography with invasive coronary angiography have proved the high diagnostic accuracy of CT in the detection of significant coronary stenosis, the sensitivity ranging from 73% to 99% [1, 3] and the specificity from 93% to 98% [4, 5]. Artifact-free visualization of coronary arteries, however, continues to be limited by coronary artery motion, which often impairs image quality at higher heart rates. Therefore, many authors [1, 3, 6, 7] have proposed using oral or IV β-blockers to decrease the heart rate to less than 65-70 beats/min before scanning. The benefit of β-receptor antagonists relies on decreasing the heart rate and thus pro-longing diastole, the phase of minimal coronary motion. With 64-MDCT, the number of nonevaluable segments has been substantially lower than with 4-MDCT [21] and 16-MDCT [22]. Nevertheless, even with 64-MDCT, as many as 12% of coronary segments have to be excluded from analysis [7].
In our study, the overall sensitivity of 97% was comparable with that in previous 64-MDCT studies [1-7]; the specificity of 81% was lower than in other studies. This finding can be explained by our approach of including nonevaluable coronary segments as false-positive ratings on an intent-to-diagnose basis [20]. In contrast, in the group of patients with a regular heart rate, the sensitivity of 91% and specificity of 94% were within the range of those in previous 64-MDCT studies [1-7].
The most important finding in our study is that regularity of heart rate during scanning significantly correlates with diagnostic accuracy per patient. An investigation of the influence of average heart rate and heart rate variability on image quality [14] showed that an average heart rate had no significant effect on image quality whereas a variable heart rate during scanning significantly degraded visualization of coronary arteries. In addition, there was only a minor difference in the number of nonevaluable segments between the groups with low and high heart rates. This finding was most probably due to the fact that heart rate variability was not increased in patients with high heart rates.
With intercycle variability of heart rate, the commonly used relative ECG-gated image reconstruction technique (reconstructions at a certain percentage of the R-R interval) does not generate images in exactly corresponding cardiac phases. The functionally different parts within one cardiac cycle are shortened or prolonged with different degrees of lack of proportion of the heart rate [23]. We used an optional two-segment reconstruction algorithm. This algorithm was initially designated to compensate with increased temporal resolution for coronary motion at a higher heart rate. However, in two- or multiple-segment reconstruction algorithms, periodic motion over n consecutive cardiac cycles is assumed.
Inconsistencies between heart cycles due to arrhythmia result in merging of slightly different cardiac phases despite acquisition of data from consecutive cardiac cycles at the same percentage in relation to the R wave. This merging of data introduces blurring of the reconstructed image. For images reconstructed with monosegment techniques, acquisition of data from slightly different cardiac phases results in a timing shift from image to image, giving 2D or 3D reformats a stair-step appearance. However, for images reconstructed with multisegment techniques, the timing shift is incorporated into individual images, reducing the stair-step appearance of reformats at the expense of increased blurring within individual images [24]. Thus irregular heart rate has resulted in impairment of image quality in an increasing number of nonevaluable segments. It also has resulted in a decline of diagnostic accuracy for stenosis detection.
Besides the heart rate decreasing effect of β-blockers, the major mechanism of β-blockers in improving the image quality of CT coronary angiography is considered its ability to reduce heart rate variability [14]. Consequently, administration of β-blockers can be recommended for imaging of patients with only slightly increased but highly irregular heart rates. In our study, low heart rate variability, best image quality, lowest rate of nonevaluable segments, and highest diagnostic accuracy were found in the group of patients taking β-receptor antagonists.
There were several limitations to this study. First, the patient cohort was heterogeneous, including patients with suspected and known CAD and who had undergone coronary surgery or intracoronary stenting. Second, the degree of variability in heart rate was higher among patients with a heart rate less than 60 beats/min than in the high heart rate group. This effect was most probably due to the indications for β-blocker treatment or to the individual response to β-blocker medication in our population [25]. In addition, the prevalence of coronary stenosis differed in the two mean heart rate subgroups, which might have affected the sensitivity and negative predictive value. Third, stenosis assessment with CT coronary angiography was restricted to visual estimation; the degree of stenosis was not quantified. Fourth, factors such as the influence of intracoronary attenuation of contrast agent on the diagnostic accuracy of CT coronary angiography [26] were not studied. Fifth, we did not use the most recent CT scanner technology to assess the effect of heart rate variables on diagnostic accuracy [27]. Sixth, because of the lack of a reference standard, we did not assess the effect of heart rate variability on identifying and characterizing coronary plaques. Finally, we did not use the absolute ECG gating technique to investigate the effect of heart rate parameters on the image quality of CT coronary angiography. It has been suggested [28] that this technique is advantageous in imaging of patients with variable heart rates.
The diagnostic accuracy of 64-MDCT coronary angiography in the detection of significant coronary artery stenosis is high but decreases in imaging of patients with an irregular heart rate. Regularity of heart rate appears to be more important than average heart rate for optimal image quality and high diagnostic accuracy. The results of this study support the administration of β-receptor antagonists to imaging patients with irregular heart rates, even when the average heart rate is relatively low. In contrast, patients with high but regular heart rates can undergo CT coronary angiography without premedication, and the image quality will be diagnostic for identification of coronary artery stenosis.

Footnotes

Supported by the National Center of Competence in Research, Computer Aided and Image Guided Medical Interventions of the Swiss National Science Foundation, Switzerland.
Address correspondence to H. Alkadhi ([email protected]).

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Information & Authors

Information

Published In

American Journal of Roentgenology
Pages: 1583 - 1590
PubMed: 18492910

History

Submitted: February 1, 2007
Accepted: May 18, 2007

Keywords

  1. 64-MDCT
  2. coronary angiography
  3. coronary artery disease
  4. heart rate

Authors

Affiliations

Sebastian Leschka
Institute of Diagnostic Radiology, Department of Medical Radiology, University Hospital Zurich, Raemistrasse 100, 8091 Zurich, Switzerland.
Hans Scheffel
Institute of Diagnostic Radiology, Department of Medical Radiology, University Hospital Zurich, Raemistrasse 100, 8091 Zurich, Switzerland.
Lars Husmann
Cardiovascular Center, University Hospital Zurich, Zurich, Switzerland.
Oliver Gämperli
Cardiovascular Center, University Hospital Zurich, Zurich, Switzerland.
Borut Marincek
Institute of Diagnostic Radiology, Department of Medical Radiology, University Hospital Zurich, Raemistrasse 100, 8091 Zurich, Switzerland.
Philipp A. Kaufmann
Cardiovascular Center, University Hospital Zurich, Zurich, Switzerland.
Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland.
Hatem Alkadhi
Institute of Diagnostic Radiology, Department of Medical Radiology, University Hospital Zurich, Raemistrasse 100, 8091 Zurich, Switzerland.

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