The impact of motion artifacts on the reproducibility of repeated coronary artery calcium measurements

The Role of Artificial Intelligence in Coronary Calcium Scoring in Standard Cardiac Computed Tomography and Chest Computed Tomography With Different Reconstruction Kernels

PURPOSE

To assess the correlation of coronary calcium score (CS) obtained by artificial intelligence (AI) with those obtained by electrocardiography gated standard cardiac computed tomography (CCT) and nongated chest computed tomography (ChCT) with different reconstruction kernels.

PATIENTS AND METHODS

Seventy-six patients received standard CCT and ChCT simultaneously. We compared CS obtained in 4 groups: CS CCT , by the traditional method from standard CCT, 25 cm field of view, 3 mm slice thickness, and kernel filter convolution 12 (FC12); CS AICCT , by AI from the standard CCT; CS ChCTsoft , by AI from the non-gated CCT, 40 cm field of view, 3 mm slice thickness, and a soft kernel FC02; and CS ChCTsharp , by AI from CCT image with same parameters for CS ChCTsoft except for using a sharp kernel FC56. Statistical analyses included Spearman rank correlation coefficient (ρ), intraclass correlation (ICC), Bland-Altman plots, and weighted kappa analysis (κ).

RESULTS

The CS AICCT was consistent with CS CCT (ρ = 0.994 and ICC of 1.00, P < 0.001) with excellent agreement with respect to cardiovascular (CV) risk categories of the Agatston score (κ = 1.000). The correlation between CS ChCTsoft and CS ChCTsharp was good (ρ = 0.912, 0.963 and ICC = 0.929, 0.948, respectively, P < 0.001) with a tendency of underestimation (Bland-Altman mean difference and 95% upper and lower limits of agreements were 329.1 [-798.9 to 1457] and 335.3 [-651.9 to 1322], respectively). The CV risk category agreement between CS ChCTsoft and CS ChCTsharp was moderate (κ = 0.556 and 0.537, respectively).

CONCLUSIONS

There was an excellent correlation between CS CCT and CS AICCT , with excellent agreement between CV risk categories. There was also a good correlation between CS CCT and CS obtained by ChCT albeit with a tendency for underestimation and moderate accuracy in terms of CV risk assessment.

Performance of 1-mm non-gated low-dose chest computed tomography using deep learning-based noise reduction for coronary artery calcium scoring

OBJECTIVE

To investigate performance of 1-mm, sharp kernel, low-dose chest computed tomography (LDCT) for coronary artery calcium scoring (CACS) using deep learning (DL)-based denoising technique.

METHODS

This retrospective, intra-individual comparative study consisted of four image datasets of 131 participants who underwent LDCT and calcium CT on the same day between January and February 2020; 1-mm LDCT with DL, 1-mm LDCT with iterative reconstruction (IR), 3-mm LDCT, and calcium CT. CACS from calcium CT were considered as reference and CACS were categorized as 0, 1-10, 11-100, 101-400, and > 400. We compared CACS from LDCTs with that from calcium CT.

RESULTS

Mean CACS was 104.8 ± 249.1 and proportion of positive CACS was 45% (59/131). CACS from LDCT images tended to be underestimated than those from calcium CT: 1-mm LDCT with DL (93.5 ± 249.6, p = 0.002), 1-mm LDCT with IR (94.7 ± 249.9, p < 0.001), and 3-mm LDCT (90.3 ± 245.3, p = 0.004). All LDCT datasets showed excellent agreement with calcium CT: intraclass correlation coefficient (ICC) = 0.961 (95% confidence interval (CI), 0.945-0.972) for DL, 0.969 (95% CI, 0.956-0.978) for IR, and 0.952 (95% CI, 0.932-0.966) for 3-mm LDCT; weighted kappa for CACS classification, 0.930 (95% CI, 0.893-0.966) for 1-mm LDCT with DL, 0.908 (95% CI, 0.866-0.950) for 1-mm LDCT with IR, and 0.846 (95% CI, 0.780-0.912) for 3-mm LDCT. The accuracy of CACS classification of 1-mm LDCT with DL (90%) tended to be better than 1-mm LDCT with IR (87%) and 3-mm LDCT (84.7%) (p = 0.10).

CONCLUSION

DL-based noise reduction algorithm can offer reliable calcium scores in 1-mm LDCT reconstructed with sharp kernel.

KEY POINTS

• Deep learning (DL)-based noise reduction enables calcium scoring at 1-mm, sharp kernel reconstructed low-dose chest CT (LDCT). • Both iterative reconstruction and DL-based noise reduction underestimated calcium score, but agreement were excellent with those from calcium CT. • Accuracy of categorical classification of calcium scoring tended to be highest in 1-mm LDCT with DL compared to 1-mm LDCT with IR and 3-mm LDCT (90%, 87%, and 84.7%, p = 0.10).

Reproducibility of quantitative coronary calcium scoring from PET/CT attenuation maps: comparison to ECG-gated CT scans

PURPOSE

We sought to evaluate inter-scan and inter-reader agreement of coronary calcium (CAC) scores obtained from dedicated, ECG-gated CAC scans (standard CAC scan) and ultra-low-dose, ungated computed tomography attenuation correction (CTAC) scans obtained routinely during cardiac PET/CT imaging.

METHODS

From 2928 consecutive patients who underwent same-day ⁸²Rb cardiac PET/CT and gated CAC scan in the same hybrid PET/CT scanning session, we have randomly selected 200 cases with no history of revascularization. Standard CAC scans and ungated CTAC scans were scored by two readers using quantitative clinical software. We assessed the agreement between readers and between two scan protocols in 5 CAC categories (0, 1-10, 11-100, 101-400, and > 400) using Cohen's Kappa and concordance.

RESULTS

Median age of patients was 70 (inter-quartile range: 63-77), and 46% were male. The inter-scan concordance index and Cohen's Kappa for readers 1 and 2 were 0.69; 0.75 (0.69, 0.81) and 0.72; 0.8 (0.75, 0.85) respectively. The inter-reader concordance index and Cohen's Kappa (95% confidence interval [CI]) was higher for standard CAC scans: 0.9 and 0.92 (0.89, 0.96), respectively, vs. for CTAC scans: 0.83 and 0.85 (0.79, 0.9) for CTAC scans (p = 0.02 for difference in Kappa). Most discordant readings between two protocols occurred for scans with low extent of calcification (CAC score < 100).

CONCLUSION

CAC can be quantitatively assessed on PET CTAC maps with good agreement with standard scans, however with limited sensitivity for small lesions. CAC scoring of CTAC can be performed routinely without modification of PET protocol and added radiation dose.

Radiomics of Coronary Artery Calcium in the Framingham Heart Study

PURPOSE

To extract radiomic features from coronary artery calcium (CAC) on CT images and to determine whether this approach could improve the ability to identify individuals at risk for a composite endpoint of clinical events.

MATERIALS AND METHODS

Participants from the Offspring and Third Generation cohorts of the community-based Framingham Heart Study underwent noncontrast cardiac CT (2002-2005) and were followed for more than a median of 9.1 years for composite major events. A total of 624 participants with CAC Agatston score (AS) of greater than 0 and good or excellent CT image quality were included for manual CAC segmentation and extraction of a predefined set of radiomic features reflecting intensity, shape, and texture. In a discovery cohort (n = 318), machine learning was used to select the 20 most informative and nonredundant CAC radiomic features, classify features predicting events, and define a radiomic-based score (RS). Performance of the RS was tested independently for the prediction of events in a validation cohort (n = 306).

RESULTS

The RS had a median value of 0.08 (interquartile range, 0.007-0.71) and a weak and modest correlation with Framingham risk score (FRS) (r = 0.2) and AS (r = 0.39), respectively. The continuous RS unadjusted, adjusted for age and sex, FRS, AS, and FRS plus AS were significantly associated with events (hazard ratio [HR] = 2.2, P < .001; HR = 1.8, P = .002; HR = 2.0, P < .001; HR = 1.7, P = .02; and HR = 1.8, P = .01, respectively). In participants with AS of less than 300, RS association with events remained significant when unadjusted and adjusted for age and sex, FRS, AS, and FRS plus AS (HR = 2.4, 2.8, 2.8, 2.3, and 2.6; P < .001, respectively). In the same subgroup of participants, adding the RS to AS resulted in a significant improvement in the discriminatory ability for events as compared with the AS (area under the receiver operating curve: 0.80 vs 0.68, respectively; P = .03).

CONCLUSION

A radiomic-based score, including the complex properties of CAC, may constitute an imaging biomarker to be further developed to identify individuals at risk for major adverse cardiovascular events in a community-based cohort. Supplemental material is available for this article. © RSNA, 2020.

Impact of automatically detected motion artifacts on coronary calcium scoring in chest computed tomography

The amount of coronary artery calcification (CAC) quantified in computed tomography (CT) scans enables prediction of cardiovascular disease (CVD) risk. However, interscan variability of CAC quantification is high, especially in scans made without ECG synchronization. We propose a method for automatic detection of CACs that are severely affected by cardiac motion. Subsequently, we evaluate the impact of such CACs on CAC quantification and CVD risk determination. This study includes 1000 baseline and 585 one-year follow-up low-dose chest CTs from the National Lung Screening Trial. About 415 baseline scans are used to train and evaluate a convolutional neural network that identifies observer determined CACs affected by severe motion artifacts. Therefore, 585 paired scans acquired at baseline and follow-up were used to evaluate the impact of severe motion artifacts on CAC quantification and risk categorization. Based on the CAC amount, the scans were categorized into four standard CVD risk categories. The method identified CACs affected by severe motion artifacts with 85.2% accuracy. Moreover, reproducibility of CAC scores in scan pairs is higher in scans containing mostly CACs not affected by severe cardiac motion. Hence, the proposed method enables identification of scans affected by severe cardiac motion, where CAC quantification may not be reproducible.

Coronary vessel wall 3-T MR imaging with time-resolved acquisition of phase-sensitive dual inversion-recovery (TRAPD) technique: initial results in patients with risk factors for coronary artery disease

PURPOSE

To develop a technique for time-resolved acquisition of phase-sensitive dual-inversion recovery (TRAPD) coronary vessel wall magnetic resonance (MR) images, to investigate the success rate in coronary wall imaging compared with that of single-frame imaging, and to assess vessel wall thickness in healthy subjects and subjects with risk factors for coronary artery disease (CAD).

MATERIALS AND METHODS

Thirty-eight subjects (12 healthy subjects, 26 subjects with at least one CAD risk factor) provided informed consent for participation in this institutional review board-approved and HIPAA-compliant study. The TRAPD coronary vessel wall imaging sequence was developed and validated with a flow phantom. Time-resolved coronary artery wall images at three to five cine phases were obtained in all subjects. Qualitative and quantitative comparisons were made between TRAPD and conventional single-image wall measurements. Measurement reproducibility also was assessed. Statistical analysis was performed for all comparisons.

RESULTS

The TRAPD sequence successfully restored the negative polarity of lumen signal and enhanced lumen wall contrast on the cine images of the flow phantom and in all subjects. Use of three to five frames increased the success rate of acquiring at least one image of good to excellent quality from 76% in single-image acquisitions to 95% with the TRAPD sequence. The difference in vessel wall thickness between healthy subjects and subjects with CAD risk factors was significant (P < .05) with the TRAPD sequence (1.07 vs 1.46 mm, respectively; 36% increase) compared with single-frame dual inversion-recovery imaging (1.24 vs 1.55 mm, respectively; 25% increase). Intraobserver, interobserver, and interexamination agreement for wall thickness measurement were 0.98, 0.97, and 0.92, respectively.

CONCLUSION

TRAPD imaging of coronary arteries improved arterial wall visualization and quantitative assessment by increasing the success rate of obtaining good- to excellent-quality images and sections orthogonal to the longitudinal axis of the vessel. This also resulted in vessel wall thickness measurements that show a more distinct difference between healthy subjects and those with CAD risk factors.

SUPPLEMENTAL MATERIAL

http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12120068/-/DC1.

Agreement of visual estimation of coronary artery calcium from low-dose CT attenuation correction scans in hybrid PET/CT and SPECT/CT with standard Agatston score

OBJECTIVES

We sought to evaluate the accuracy and reproducibility of visual estimation of coronary artery calcium (CAC) from computed tomography attenuation correction (CTAC) scans performed for hybrid positron emission tomography (PET)/computed tomography (CT) and single-photon emission computed tomography (SPECT)/CT myocardial perfusion imaging (MPI).

BACKGROUND

At the time of MPI, hybrid systems obtain a low-dose, non-electrocardiogram (ECG)-gated CT scan that is used to perform attenuation correction. Utility of this CTAC scan in estimating actual CAC as measured by Agatston score (AS) on standard ECG-gated scans has not been previously studied.

METHODS

A total of 492 patients, from 3 centers, receiving both MPI with CTAC and a standard CAC scan were studied. At each site, experienced readers blinded to AS reviewed CTAC images, visually estimating CAC on a 6-level scale: classifying patients as estimated AS of 0, 1 to 9, 10 to 99, 100 to 300, 400 to 999, or ≥1,000. Agreement between visually estimated coronary artery calcium (VECAC) on CTAC and AS, measured standardly and converted to the same scale, was evaluated, as was inter-reader agreement.

RESULTS

Although CTAC images are low dose and nongated, a high degree of association was observed between VECAC and AS, with 63% of VECACs in the same category as the AS category and 93% within 1 category. Weighted kappa was 0.89 (95% confidence interval: 0.88 to 0.91, p < 0.0001). High weighted kappa statistics were observed for each site, scanner type, and sex. Readers reported identical scores in 65% of cases and scores within 1 category in 93%.

CONCLUSIONS

CAC can be visually assessed from low-dose CTAC scans with high agreement with AS. CTAC scans should be routinely assessed for VECAC.

Computerized method for evaluating diagnostic image quality of calcified plaque images in cardiac CT: validation on a physical dynamic cardiac phantom

PURPOSE

In cardiac computed tomography (CT), important clinical indices, such as the coronary calcium score and the percentage of coronary artery stenosis, are often adversely affected by motion artifacts. As a result, the expert observer must decide whether or not to use these indices during image interpretation. Computerized methods potentially can be used to assist in these decisions. In a previous study, an artificial neural network (ANN) regression model provided assessability (image quality) indices of calcified plaque images from the software NCAT phantom that were highly agreeable with those provided by expert observers. The method predicted assessability indices based on computer-extracted features of the plaque. In the current study, the ANN-predicted assessability indices were used to identify calcified plaque images with diagnostic calcium scores (based on mass) from a physical dynamic cardiac phantom. The basic assumption was that better quality images were associated with more accurate calcium scores.

METHODS

A 64-channel CT scanner was used to obtain 500 calcified plaque images from a physical dynamic cardiac phantom at different heart rates, cardiac phases, and plaque locations. Two expert observers independently provided separate sets of assessability indices for each of these images. Separate sets of ANN-predicted assessability indices tailored to each observer were then generated within the framework of a bootstrap resampling scheme. For each resampling iteration, the absolute calcium score error between the calcium scores of the motion-contaminated plaque image and its corresponding stationary image served as the ground truth in terms of indicating images with diagnostic calcium scores. The performances of the ANN-predicted and observer-assigned indices in identifying images with diagnostic calcium scores were then evaluated using ROC analysis.

RESULTS

Assessability indices provided by the first observer and the corresponding ANN performed similarly (AUC(OBS1) = 0.80 [0.73, 0.86] vs AUC(ANN1) = 0.88 [0.82, 0.92]) as that of the second observer and the corresponding ANN (AUC(OBS2) = 0.87 [0.83,0.91] vs. AUC(ANN2) = 0.90 [0.85, 0.94]). Moreover, the ANN-predicted indices were generated in a fraction of the time required to obtain the observer-assigned indices.

CONCLUSIONS

ANN-predicted assessability indices performed similar to observer-assigned assessability indices in identifying images with diagnostic calcium scores from the physical dynamic cardiac phantom. The results of this study demonstrate the potential of using computerized methods for identifying images with diagnostic clinical indices in cardiac CT images.

Coronary artery calcification scoring in low-dose ungated CT screening for lung cancer: interscan agreement

OBJECTIVE

In previous studies detection of coronary artery calcification (CAC) with low-dose ungated MDCT performed for lung cancer screening has been compared with detection with cardiac CT. We evaluated the interscan agreement of CAC scores from two consecutive low-dose ungated MDCT examinations.

SUBJECTS AND METHODS

The subjects were 584 participants in the screening segment of a lung cancer screening trial who underwent two low-dose ungated MDCT examinations within 4 months (mean, 3.1 +/- 0.6 months) of a baseline CT examination. Agatston score, volume score, and calcium mass score were measured by two observers. Interscan agreement of stratification of participants into four Agatston score risk categories (0, 1-100, 101-400, > 400) was assessed with kappa values. Interscan variability and 95% repeatability limits were calculated for all three calcium measures and compared by repeated measures analysis of variance.

RESULTS

An Agatston score > 0 was detected in 443 baseline CT examinations (75.8%). Interscan agreement of the four risk categories was good (kappa = 0.67). The Agatston scores were in the same risk category in both examinations in 440 cases (75.3%); 578 participants (99.0%) had scores differing a maximum of one category. Furthermore, mean interscan variability ranged from 61% for calcium volume score to 71% for Agatston score (p < 0.01). A limitation of this study was that no comparison of CAC scores between low-dose ungated CT and the reference standard ECG-gated CT was performed.

CONCLUSION

Cardiovascular disease risk stratification with low-dose ungated MDCT is feasible and has good interscan agreement of stratification of participants into Agatston score risk categories. High mean interscan variability precludes the use of this technique for monitoring CAC scores for individual patients.

A model for quantitative correction of coronary calcium scores on multidetector, dual source, and electron beam computed tomography for influences of linear motion, calcification density, and temporal resolution: a cardiac phantom study

PURPOSE

The objective of this study is to quantify the influence of linear motion, calcification density, and temporal resolution on coronary calcium determination using multidetector computed tomography (MDCT), dual source CT (DSCT), and electron beam tomography (EBT) and to find a quantitative method which corrects for the influences of these parameters using a linear moving cardiac phantom.

METHODS

On a robotic arm with artificial arteries with four calcifications of increasing density, a linear movement was applied between 0 and 120 mm/s (step of 10 mm/s). The phantom was scanned five times on 64-slice MDCT, DSCT, and EBT using a standard acquisition protocol. The average Agatston, volume, and mass scores were determined for each velocity, calcification, and scanner. Susceptibility to motion was quantified using a cardiac motion susceptibility (CMS) index. Resemblance to EBT and physical volume and mass was quantified using a Delta index.

RESULTS

Increasing motion artifacts were observed at increasing velocities on all scanners, with increasing severity from EBT to DSCT to 64-slice MDCT. The calcium score showed a linear dependency on motion from which a correction factor could be derived. This correction factor showed a linear dependency on the mean calcification density with a good fit for all three scoring methods and all three scanners (0.73 < or = R2 < or = 0.95). The slope and offset of this correction factor showed a linear dependency on temporal resolution with a good fit for all three scoring methods and all three scanners (0.83 < or = R2 < or = 0.98). CMS was minimal for EBT and increasing values were observed for DSCT and highest values for 64-slice MDCT. CMS was minimal for mass score and increasing values were observed for volume score and highest values for Agatston score. For all densities and scoring methods DSCT showed on average the closest resemblance to EBT calcium scores. When using the correction factor, CMS index decreased on average by 15% and Delta index decreased by 35%.

CONCLUSIONS

Calcium scores determined on DSCT and 64-slice MDCT are highly susceptible to motion as compared to EBT. The mass score is less susceptible to motion compared to volume and Agatston score. Calcium scores determined on DSCT bear a closer resemblance to EBT obtained calcium scores than 64-slice MDCT. In addition, the calcium score is highly dependent on the average density of individual calcifications and the dependency of the calcium score on motion showed a linear behavior on calcification density. From these relations, a quantitative method could be derived which corrects the measured calcium score for the influence of linear motion, mean calcification density, and temporal resolution.

Carotid MR angiography with traditional bolus timing: clinical observations and Fourier-based modelling of contrast kinetics

This study analyses the relation between image quality and contrast kinetics in bolus-timed carotid magnetic resonance angiography (MRA) and interprets the findings by Fourier-based numerical modelling. One hundred patients prone to carotid stenosis were studied using contrast-enhanced carotid MRA with bolus timing. The carotid MRAs were timed to start relatively early without accounting for the injection time of the contrast medium. For interpretation different starting times were modelled, utilising the spectral information of the test bolus series. In the test bolus series the arterial time-to-peak showed a large 95% confidence interval of 12-27 s, indicating the need for individual MRA timing. All bolus-timed MRAs were of good diagnostic quality. The mean (+/-SD) arterial contrast-to-noise ratio was 53.0 (+/-12.8) and thus high, and 95% of the MRAs showed a slight venous contamination of 11.8% or less (median 5.6%). According to the Fourier-based modelling the central k-space may be acquired about 2 s before the arterial contrast peak. This results in carotid MRAs with sufficiently high arterial enhancement and little venous contamination. In conclusion, in bolus-timed carotid MRA a relatively short timing provides good arterial contrast with little venous contamination, which can be explained by Fourier-based numerical modelling of the contrast kinetics.

Feature-based characterization of motion-contaminated calcified plaques in cardiac multidetector CT

In coronary calcium scoring, motion artifacts affecting calcified plaques are commonly characterized using descriptive terms, which incorporate an element of subjectivity in their interpretations. Quantitative indices may improve the objective characterization of these motion artifacts. In this paper, an automated method for generating 12 quantitative indices, i.e., features that characterize the motion artifacts affecting calcified plaques, is presented. This method consists of using the rapid phase-correlated region-of-interest (ROI) tracking algorithm for reconstructing ROI images of calcified plaques automatically from the projection data obtained during a cardiac scan, and applying methods for extracting features from these images. The 12 features include two dynamic, six morphological, and four intensity-based features. The two dynamic features are three-dimensional (3D) velocity and 3D acceleration. The six morphological features include edge-based volume, threshold-based volume, sphericity, irregularity, average margin gradient, and variance of margin gradient. The four intensity-based features are maximum intensity, mean intensity, minimum intensity, and standard deviation of intensity. The 12 features were extracted from 54 reconstructed sets of simulated four-dimensional images from the dynamic NCAT phantom involving six calcified plaques under nine heart rate/multi-sector gating combinations. In order to determine how well the 12 features correlated with a plaque motion index, which was derived from the trajectory of the plaque, partial correlation coefficients adjusted for heart rate, number of gated sectors, and mean feature values of the six plaques were calculated for all 12 features. Features exhibiting stronger correlations ([r] epsilon [0.60,1.00]) with the motion index were 3D velocity, maximum intensity, and standard deviation of intensity. Features demonstrating stronger correlations ([r] epsilon [0.60, 1.00]) with other features mostly involved intensity-based features. Edge-based volume/irregularity and average margin gradient/variance of margin gradient were the only two feature pairs out of 12 with stronger correlations that did not involve intensity-based features. Automatically extracted features of the motion artifacts affecting calcified plaques in cardiac computed tomography images potentially can be used to develop models for predicting image assessability with respect to motion artifacts.

Computerized assessment of motion-contaminated calcified plaques in cardiac multidetector CT

An automated method for evaluating the image quality of calcified plaques with respect to motion artifacts in noncontrast-enhanced cardiac computed tomography (CT) images is introduced. This method involves using linear regression (LR) and artificial neural network (ANN) regression models for predicting two patient-specific, region-of-interest-specific, reconstruction-specific and temporal phase-specific image quality indices. The first is a plaque motion index, which is derived from the actual trajectory of the calcified plaque and is represented on a continuous scale. The second is an assessability index, which reflects the degree to which a calcified plaque is affected by motion artifacts, and is represented on an ordinal five-point scale. Two sets of assessability indices were provided independently by two radiologists experienced in evaluating cardiac CT images. Inputs for the regression models were selected from 12 features characterizing the dynamic, morphological, and intensity-based properties of the calcified plaques. Whereas LR-velocity (LR-V) used only a single feature (three-dimensional velocity), the LR-multiple (LR-M) and ANN regression models used the same subset of these 12 features selected through stepwise regression. The regression models were parameterized and evaluated using a database of simulated calcified plaque images from the dynamic NCAT phantom involving nine heart rate/multi-sector gating combinations and 40 cardiac phases covering two cardiac cycles. Six calcified plaques were used for the plaque motion indices and three calcified plaques were used for both sets of assessability indices. In one configuration, images from the second cardiac cycle were used for feature selection and regression model parameterization, whereas images from the first cardiac cycle were used for testing. With this configuration, repeated measures concordance correlation coefficients (CCCs) and associated 95% confidence intervals for the LR-V, LR-M, and ANN were 0.817 [0.785, 0.848], 0.894 [0.869, 0.916], and 0.917 [0.892, 0.936] for the plaque motion indices. For the two sets of assess-ability indices, CCC values for the ANN model were 0.843 [0.791, 0.877] and 0.793 [0.747, 0.828]. These two CCC values were statistically greater than the CCC value of 0.689 [0.648, 0.727], which was obtained by comparing the two sets of assessability indices with each other. These preliminary results suggest that the variabilities of assessability indices provided by regression models can lie within the variabilities of the indices assigned by independent observers. Thus, the potential exists for using regression models and assessability indices for determining optimal phases for cardiac CT image interpretation.

Variability of coronary calcium scores throughout the cardiac cycle: implications for the appropriate use of electrocardiogram-dose modulation with retrospectively gated computed tomography

OBJECTIVE

To study how much the calcium scores at various phases throughout the cardiac cycle deviate from the score in the most motionless phase during retrospectively electrocardiogram (ECG)-gated multidetector row computed tomography (MDCT) of the heart and to evaluate how to optimize ECG-based tube current modulation so that errors in calcium scoring can be minimized while dose savings can be maximized.

MATERIALS AND METHODS

In 73 subjects with known or suspected coronary artery disease we performed retrospectively ECG-gated 64-detector row computed tomography for calcium scoring. Four subjects were excluded after scanning because of breathing artifacts or lack of coronary calcification. The scans of 69 subjects (46 men, mean age 62 +/- 6 years) were used for further analysis. Heart rate during the scan was recorded. In each patient, calcium scoring [Agatston score (AS), mass score (MS), and volume score, (VS)] was performed on 10 data sets reconstructed at 10%-intervals throughout the cardiac cycle. The most motionless phase was subjectively determined and used as the reference phase. For the score in each phase, deviation from the score in the reference phase was determined. An ECG-simulator was used to determine the amount of dose saving while scanning with dose modulation and applying diagnostic dose during 1 or several phases.

RESULTS

Mean heart rate was 63 (+/-13) beats per minute (bpm). In 51% of patients the reference phase was the 70% phase. Using the calcium score in the 70% phase (mid-diastole) instead of the reference at heart rates below 70 bpm would have induced a median score deviation of 0% [interquartile range: 0%-6% (AS, MS, and VS)] and using the calcium score in the 40% phase (end-systole) at heart rates > or =70 bpm would also have induced a median score deviation of 0% [interquartile range: 0%-7% (AS), 0%-5% (MS), and 0%-3% (VS)]. Errors in calcium scores of more than 10% occur in around 10% of subjects for all 3 scoring algorithms. Dose savings increased with lower heart rates and shorter application of diagnostic dose.

CONCLUSIONS

The optimum phases for dose modulation are 70% (mid-diastole) at heart rates below 70 bpm and 40% (end-systole) at heart rates above 70 bpm. Under these conditions dose saving is maximum and a median error of 0% is found for the various calcium scoring techniques with score errors of more than 10% in around 10% of subjects.

Measurement of coronary calcium scores by electron beam computed tomography or exercise testing as initial diagnostic tool in low-risk patients with suspected coronary artery disease

We determined the efficiency of a screening protocol based on coronary calcium scores (CCS) compared with exercise testing in patients with suspected coronary artery disease (CAD), a normal ECG and troponin levels. Three-hundred-and-four patients were enrolled in a screening protocol including CCS by electron beam computed tomography (Agatston score), and exercise testing. Decision-making was based on CCS. When CCS>or=400, coronary angiography (CAG) was recommended. When CCS<10, patients were discharged. Exercise tests were graded as positive, negative or nondiagnostic. The combined endpoint was defined as coronary event or obstructive CAD at CAG. During 12+/-4 months, CCS>or=400, 10-399 and <10 were found in 42, 103 and 159 patients and the combined endpoint occurred in 24 (57%), 14 (14%) and 0 patients (0%), respectively. In 22 patients (7%), myocardial perfusion scintigraphy was performed instead of exercise testing due to the inability to perform an exercise test. A positive, nondiagnostic and negative exercise test result was found in 37, 76 and 191 patients, and the combined endpoint occurred in 11 (30%), 15 (20%) and 12 patients (6%), respectively. Receiver-operator characteristics analysis showed that the area under the curve of 0.89 (95% CI: 0.85-0.93) for CCS was superior to 0.69 (95% CI: 0.61-0.78) for exercise testing (P<0.0001). In conclusion, measurement of CCS is an appropriate initial screening test in a well-defined low-risk population with suspected CAD.

Variability of repeated coronary artery calcium measurements by 1.25-mm- and 2.5-mm-thickness images on prospective electrocardiograph-triggered 64-slice CT

High reproducibility on coronary artery calcium scoring is a key requirement in monitoring the progression of coronary atherosclerosis. The purpose of this prospective study is to assess the reproducibility of 1.25-mm- and 2.5-mm-thickness images on prospective electrocardiograph-triggered 64-slice CT with respect to 2.5-mm-thickness images on spiral overlapping reconstruction. One hundred patients suspected of coronary artery disease were scanned twice repeatedly, both on prospective electrocardiograph-triggered step-and-shoot and retrospective electrocardiograph-gated spiral scans. Using 1.25-mm-thickness collimation, 1.25-mm- and 2.5-mm-thickness image sets on prospective scans and 2.5-mm-thickness image sets with 1.25-mm increment (overlapping) on retrospective scans were obtained. Coronary artery calcium scores, interscan variability and interobserver variability were evaluated. The mean interscan variability in coronary artery calcium measurement on 1.25-mm prospective/2.5-mm prospective/2.5-mm overlapping retrospective scans were Agatston: 10%/18%/12%, volume: 10%/12%/10% and mass: 8%/13%/11% for observer 1 and Agatston: 8%/14%/10%, volume: 7%/9%/10% and mass: 7%/10%/9% for observer 2, respectively. The mean interobserver variability was 5% to 14%. In conclusion, prospective electrocardiograph-triggered 64-slice CT using the 1.25-mm prospective scan shows the lowest variability. The 2.5-mm prospective scan on volume or mass scoring shows variability of around 10%, comparable to 2.5-mm-thickness spiral overlapping reconstruction images.

Visual and automatic grading of coronary artery stenoses with 64-slice CT angiography in reference to invasive angiography

The aim of this study was to assess the performance of a software tool for quantitative coronary artery analysis of computed tomography coronary angiography (CT-QCA) in comparison with invasive coronary angiography with quantitative analysis (CAG-QCA) as standard of reference. Two radiologists reviewed the CT angiography data sets (Siemens Sensation 64) of 25 patients, grading coronary artery stenoses visually and with a software tool (Circulation, Siemens). Twenty-three data sets with sufficient image quality were included in the final analysis. CAG revealed a total of 30 wall irregularities and 28 stenoses, of which 17 were graded as moderate and nine as hemodynamically significant. CT-QCA showed a better agreement to CAG-QCA, with a systematic overestimation of the degree of stenosis of 6.1% and limits of agreement of +36.1% and -23.9; the correlation coefficient was 0.82 (p < 0.0001). Using CT-QCA, sensitivity, specificity, and positive and negative predictive value were 89%, 100%, 89%, and 100%, respectively, for significant area stenoses greater than 75%. The positive predictive value for the visual assessment amounted to 53%. Interobserver variability between CT-QCA and visual assessment showed a kappa value of 0.72. In conclusion, software-supported CT-QCA makes it possible to quantify significant coronary artery stenoses automatically, with good agreement to CAG-QCA.

Cost effectiveness of coronary angiography and calcium scoring using CT and stress MRI for diagnosis of coronary artery disease

We compared the cost effectiveness of recent approaches [coronary angiography and calcium scoring using computed tomography (CT) and stress magnetic resonance imaging (MRI)] to the diagnosis of coronary artery disease (CAD) with those of the traditional diagnostic modalities [conventional angiography (CATH), exercise ECG, and stress echocardiography] using a decision tree model. For patients with a 10% to 50% pretest likelihood of coronary artery disease, non-invasive coronary angiography using CT was the most cost effective approach, with costs per correctly identified CAD patient of euro4,435 (10% likelihood) to euro1,469 (50% likelihood). Only for a pretest likelihood of 30% to 40% was calcium scoring using CT more cost effective than any of the traditional diagnostic modalities, while MRI was not cost effective for any pretest likelihood. At a pretest likelihood of 60%, CT coronary angiography and CATH were equally effective, while CATH was most cost effective for a pretest likelihood of at least 70%. In conclusion, up to a pretest likelihood for coronary artery disease of 50%, CT coronary angiography is the most cost-effective procedure, being superior to the other new modalities and the most commonly used traditional diagnostic modalities. With a very high likelihood for disease (above 60%), CATH is the most effective procedure from the perspective of society.