CT coronary angiography: impact of adapted statistical iterative reconstruction (ASIR) on coronary stenosis and plaque composition analysis. Int J Cardiovasc Imaging. 2013;29:719-724. [PMID: 23053859 DOI: 10.1007/s10554-012-0134-1]

Coronary CT angiography for the assessment of atherosclerotic plaque inflammation: postmortem proof of concept with histological validation

OBJECTIVES

To evaluate the diagnostic utility of multiphase postmortem CT angiography (PMCTA) to detect plaque enhancement as a surrogate marker of inflammation, using fatal coronary plaques obtained from autopsies following sudden cardiac death.

METHODS

In this retrospective study, we included 35 cases (12 women, 34%; median [IQR] age, 52 [11] years), with autopsy-proven coronary thrombosis, histological examination, and multiphase PMCTA. Two radiologists blinded towards histological findings assessed PMCTA for plaque enhancement of the culprit lesion in consensus. Two forensic pathologists determined the culprit lesion and assessed histological samples in consensus. Cases with concomitant vasa vasorum density increase and intraplaque and periadventital inflammation were considered positive for plaque inflammation. Finally, we correlated radiology and pathology findings.

RESULTS

All 35 cases had histological evidence of atherosclerotic plaque disruption and thrombosis; 30 (85.7%) had plaque inflammation. Plaque enhancement at multiphase PMCTA was reported in 21 (60%) and resulted in a PPV of 95.2% (77.3-99.2%) and an NPV of 28.6% (17-43.9%). Median histological ratings indicated higher intraplaque inflammation (p = .024) and vasa vasorum density (p = .032) in plaques with enhancement. We found no evidence of a difference in adventitial inflammation between CT-negative and CT-positive plaques (p = .211).

CONCLUSIONS

Plaque enhancement was found in 2/3 of fatal atherothrombotic occlusions at coronary postmortem CT angiography. Furthermore, plaque enhancement correlated with histopathological plaque inflammation and increased vasa vasorum density. Plaque enhancement on multiphase CT angiography could potentially serve as a noninvasive marker of inflammation in high-risk populations.

CLINICAL RELEVANCE STATEMENT

Phenotyping coronary plaque more comprehensively is one of the principal challenges cardiac imaging is facing. Translating our ex vivo findings of CT-based plaque inflammation assessment into clinical studies might help pave the way in defining high-risk plaque better.

KEY POINTS

• Most thrombosed coronary plaques leading to fatality in our series had histological signs of inflammation. • Multiphase postmortem CT angiography can provide a noninvasive interrogation of plaque inflammation through contrast enhancement. • Atherosclerotic plaque enhancement at multiphase postmortem CT angiography correlated with histopathological signs of plaque inflammation and could potentially serve as an imaging biological marker of plaque vulnerability.

Radiation dose reduction with deep-learning image reconstruction for coronary computed tomography angiography

OBJECTIVES

Deep-learning image reconstruction (DLIR) offers unique opportunities for reducing image noise without degrading image quality or diagnostic accuracy in coronary CT angiography (CCTA). The present study aimed at exploiting the capabilities of DLIR to reduce radiation dose and assess its impact on stenosis severity, plaque composition analysis, and plaque volume quantification.

METHODS

This prospective study includes 50 patients who underwent two sequential CCTA scans at normal-dose (ND) and lower-dose (LD). ND scans were reconstructed with Adaptive Statistical Iterative Reconstruction-Veo (ASiR-V) 100%, and LD scans with DLIR. Image noise (in Hounsfield units, HU) and quantitative plaque volumes (in mm3) were assessed quantitatively. Stenosis severity was visually categorized into no stenosis (0%), stenosis (< 20%, 20-50%, 51-70%, 71-90%, 91-99%), and occlusion (100%). Plaque composition was classified as calcified, non-calcified, or mixed.

RESULTS

Reduction of radiation dose from ND scans with ASiR-V 100% to LD scans with DLIR at the highest level (DLIR-H; 1.4 mSv vs. 0.8 mSv, p < 0.001) had no impact on image noise (28 vs. 27 HU, p = 0.598). Reliability of stenosis severity and plaque composition was excellent between ND scans with ASiR-V 100% and LD scans with DLIR-H (intraclass correlation coefficients of 0.995 and 0.974, respectively). Comparison of plaque volumes using Bland-Altman analysis revealed a mean difference of - 0.8 mm3 (± 2.5 mm3) and limits of agreement between - 5.8 and + 4.1 mm3.

CONCLUSION

DLIR enables a reduction in radiation dose from CCTA by 43% without significant impact on image noise, stenosis severity, plaque composition, and quantitative plaque volume.

KEY POINTS

•Deep-learning image reconstruction (DLIR) enables radiation dose reduction by over 40% for coronary computed tomography angiography (CCTA). •Image noise remains unchanged between a normal-dose CCTA reconstructed by ASiR-V and a lower-dose CCTA reconstructed by DLIR. •There is no impact on the assessment of stenosis severity, plaque composition, and quantitative plaque volume between the two scans.

Coronary artery lumen volume index as a marker of flow-limiting atherosclerosis-validation against 13N-ammonia positron emission tomography

OBJECTIVES

Coronary artery volume indexed to left myocardial mass (CAVi), derived from coronary computed tomography angiography (CCTA), has been proposed as an indicator of diffuse atherosclerosis. We investigated the association of CAVi with quantitative flow parameters and its ability to predict ischemia as derived from ¹³N-ammonia positron emission tomography myocardial perfusion imaging (PET-MPI).

METHODS

Sixty patients who underwent hybrid CCTA/PET-MPI due to suspected CAD were retrospectively included. CAVi was defined as total coronary artery lumen volume over myocardial mass, both derived from CCTA. From PET-MPI, quantitative stress and rest myocardial blood flow (MBF) and myocardial flow reserve (MFR) were obtained and correlated with CAVi, and semi-quantitative perfusion images were analyzed for the presence of ischemia. Harrell's c-statistic and net reclassification improvement (NRI) analysis were performed to evaluate the incremental value of CAVi over the CCTA model (i.e., stenosis > 50% and > 70%).

RESULTS

CAVi correlated moderately with stress MBF and MFR (R = 0.50, p < 0.001, and R = 0.39, p = 0.002). Mean stress MBF and MFR were lower in patients with low (i.e., ≤ 20.2 mm³/g, n = 24) versus high (i.e., > 20.2 mm³/g, n = 36) CAVi (p < 0.001 for both comparisons). CAVi was independently associated with abnormal stress MBF (OR 0.90, 95% CI 0.82-0.998, p = 0.045). CAVi increased the predictive ability of the CCTA model for abnormal stress MBF and ischemia (c-statistic 0.763 versus 0.596, p_diff < 0.05 and 0.770 versus 0.645, p_diff < 0.05, NRI 0.84, p = 0.001 and 0.96, p < 0.001, respectively).

CONCLUSIONS

CAVi exhibits incremental value to predict both abnormal stress MBF and ischemia over CCTA alone.

KEY POINTS

• Coronary artery volume indexed to left myocardial mass (CAVi), derived from coronary computed tomography angiography (CCTA), is correlated with myocardial blood flow indices derived from ¹³N-ammonia positron emission tomography myocardial perfusion imaging. • CAVi is independently associated with abnormal stress myocardial blood flow. • CAVi provides incremental diagnostic value over CCTA for both abnormal stress MBF and ischemia.

Incremental Image Noise Reduction in Coronary CT Angiography Using a Deep Learning-Based Technique with Iterative Reconstruction

Objective

To assess the feasibility of applying a deep learning-based denoising technique to coronary CT angiography (CCTA) along with iterative reconstruction for additional noise reduction.

Materials and Methods

We retrospectively enrolled 82 consecutive patients (male:female = 60:22; mean age, 67.0 ± 10.8 years) who had undergone both CCTA and invasive coronary artery angiography from March 2017 to June 2018. All included patients underwent CCTA with iterative reconstruction (ADMIRE level 3, Siemens Healthineers). We developed a deep learning based denoising technique (ClariCT.AI, ClariPI), which was based on a modified U-net type convolutional neural net model designed to predict the possible occurrence of low-dose noise in the originals. Denoised images were obtained by subtracting the predicted noise from the originals. Image noise, CT attenuation, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were objectively calculated. The edge rise distance (ERD) was measured as an indicator of image sharpness. Two blinded readers subjectively graded the image quality using a 5-point scale. Diagnostic performance of the CCTA was evaluated based on the presence or absence of significant stenosis (≥ 50% lumen reduction).

Results

Objective image qualities (original vs. denoised: image noise, 67.22 ± 25.74 vs. 52.64 ± 27.40; SNR [left main], 21.91 ± 6.38 vs. 30.35 ± 10.46; CNR [left main], 23.24 ± 6.52 vs. 31.93 ± 10.72; all p < 0.001) and subjective image quality (2.45 ± 0.62 vs. 3.65 ± 0.60, p < 0.001) improved significantly in the denoised images. The average ERDs of the denoised images were significantly smaller than those of originals (0.98 ± 0.08 vs. 0.09 ± 0.08, p < 0.001). With regard to diagnostic accuracy, no significant differences were observed among paired comparisons.

Conclusion

Application of the deep learning technique along with iterative reconstruction can enhance the noise reduction performance with a significant improvement in objective and subjective image qualities of CCTA images.

Machine learning for diagnosis of coronary artery disease in computed tomography angiography: A survey

Coronary artery disease (CAD) has become a major illness endangering human health. It mainly manifests as atherosclerotic plaques, especially vulnerable plaques without obvious symptoms in the early stage. Once a rupture occurs, it will lead to severe coronary stenosis, which in turn may trigger a major adverse cardiovascular event. Computed tomography angiography (CTA) has become a standard diagnostic tool for early screening of coronary plaque and stenosis due to its advantages in high resolution, noninvasiveness, and three-dimensional imaging. However, manual examination of CTA images by radiologists has been proven to be tedious and time-consuming, which might also lead to intra- and interobserver errors. Nowadays, many machine learning algorithms have enabled the (semi-)automatic diagnosis of CAD by extracting quantitative features from CTA images. This paper provides a survey of these machine learning algorithms for the diagnosis of CAD in CTA images, including coronary artery extraction, coronary plaque detection, vulnerable plaque identification, and coronary stenosis assessment. Most included articles were published within this decade and are found in the Web of Science. We wish to give readers a glimpse of the current status, challenges, and perspectives of these machine learning-based analysis methods for automatic CAD diagnosis.

Reducing both radiation and contrast doses in coronary CT angiography in lean patients on a 16-cm wide-detector CT using 70 kVp and ASiR-V algorithm, in comparison with the conventional 100-kVp protocol

OBJECTIVE

To investigate the value of prospectively ECG-triggered coronary CT angiography (CCTA) for lean patients with body mass index (BMI) ≤ 23 kg/m² using 70 kVp and high-level volume-based adaptive statistical iterative reconstruction (ASiR-V) algorithm on a 16-cm wide-detector CT system for reducing both radiation and contrast doses in comparison with the conventional 100-kVp protocol.

MATERIALS AND METHODS

Thirty patients (group A) were prospectively enrolled to undergo 70-kVp CCTA on a 16-cm wide-detector CT scanner with noise index (NI) of 36 HU and at weight-dependent contrast dose rate of 16 mg I/kg/s for 9-s injection. Images were reconstructed with 80% ASiR-V. Radiation dose, contrast dose, and image quality were statistically compared with 30 patients (group B) in database with matching BMI who underwent conventional 100-kVp CCTA with NI of 25 HU, and at 25 mg I/kg/s rate for 10-s injection and reconstructed with 60% ASiR-V.

RESULTS

There was no significant difference in patient demographics between the two groups (all p > 0.05). The two groups also had similar mean CT values and contrast-noise ratio (CNR) and subjective image quality (all p > 0.05). However, group A with 70 kVp reduced the effective dose by 75.3% compared with group B (0.43 ± 0.20 mSv vs. 1.74 ± 1.01 mSv, p < 0.001), and required 42.4% less contrast dose than group B (22.46 ± 2.94 ml vs. 38.99 ± 5.10 ml, p < 0.001).

CONCLUSIONS

Prospectively ECG-triggered CCTA using 70 kVp and high-level ASiR-V on a 16-cm wide-detector CT system provides diagnostic images with substantial reduction in both radiation and contrast doses for patients with BMI ≤ 23 kg/m² compared to the conventional 100-kVp protocol.

KEY POINTS

• 70-kVp CCTA produces excellent images at sub-millisievert radiation. • 70-kVp CCTA reduces both radiation and contrast doses over conventional protocol. • Achieving low-dose CCTA with combined low kVp and high-level ASIR-V.

Impact of a New Adaptive Statistical Iterative Reconstruction (ASIR)-V Algorithm on Image Quality in Coronary Computed Tomography Angiography

RATIONALE AND OBJECTIVES

A new postprocessing algorithm named adaptive statistical iterative reconstruction (ASIR)-V has been recently introduced. The aim of this article was to analyze the impact of ASIR-V algorithm on signal, noise, and image quality of coronary computed tomography angiography.

MATERIALS AND METHODS

Fifty consecutive patients underwent clinically indicated coronary computed tomography angiography (Revolution CT; GE Healthcare, Milwaukee, WI). Images were reconstructed using filtered back projection and ASIR-V 0%, and a combination of filtered back projection and ASIR-V 20%-80% and ASIR-V 100%. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were calculated for left main coronary artery (LM), left anterior descending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA) and were compared between the different postprocessing algorithms used. Similarly a four-point Likert image quality score of coronary segments was graded for each dataset and compared. A cutoff value of P < .05 was considered statistically significant.

RESULTS

Compared to ASIR-V 0%, ASIR-V 100% demonstrated a significant reduction of image noise in all coronaries (P < .01). Compared to ASIR-V 0%, SNR was significantly higher with ASIR-V 60% in LM (P < .01), LAD (P < .05), LCX (P < .05), and RCA (P < .01). Compared to ASIR-V 0%, CNR for ASIR-V ≥60% was significantly improved in LM (P < .01), LAD (P < .05), and RCA (P < .01), whereas LCX demonstrated a significant improvement with ASIR-V ≥80%. ASIR-V 60% had significantly better Likert image quality scores compared to ASIR-V 0% in segment-, vessel-, and patient-based analyses (P < .01).

CONCLUSIONS

Reconstruction with ASIR-V 60% provides the optimal balance between image noise, SNR, CNR, and image quality.

Diagnostic accuracy of coronary CT angiography performed in 100 consecutive patients with coronary stents using a whole-organ high-definition CT scanner

AIMS

To evaluate image quality, interpretability, diagnostic accuracy and radiation exposure of coronary CT angiography (CCTA) performed with a new scanner equipped with 0.23-mm spatial resolution, new generation iterative reconstruction, 0.28-second gantry rotation time and intra-cycle motion-correction algorithm in consecutive patients with coronary stents, including those with high heart rate (HR) and atrial fibrillation (AF).

MATERIALS AND METHODS

We enrolled 100 consecutive patients (85 males, mean age 65 ± 10 years) with previous coronary stent implantation scheduled for clinically indicated non-emergent invasive coronary angiography (ICA). Image quality, coronary interpretability and diagnostic accuracy vs. ICA were evaluated and the effective dose (ED) was recorded.

RESULTS

Mean HR during the scan was 67 ± 13 bpm. Twenty-six patients had >65 bpm HR during scanning and 13 patients had AF. Overall, image quality was high (Likert = 3.2 ± 0.9). Stent interpretability was 95.8% (184/192 stents). Among 192 stented segments, CCTA correctly identified 22 out of 24 with >50% in-stent restenosis (ISR) (sensitivity 92%). In a stent-based analysis, specificity, positive and negative predictive values and diagnostic accuracy for ISR detection were 91%, 99%, 60% and 91%, respectively. In a patient-based analysis, CCTA diagnostic accuracy was 85%. Overall, mean ED of CCTA was 2.4 ± 1.2 mSv.

CONCLUSIONS

A whole-organ CT scanner was able to evaluate coronary stents with good diagnostic performance and low radiation exposure, also in presence of unfavorable HR and heart rhythm.

TRANSLATIONAL ASPECT

The present study is the first to evaluate the CCTA capability of detecting in-stent restenosis in consecutive patients, including those with high HR and AF, using a recent scanner generation that combines improved spatial and temporal resolution with wide coverage. Using the whole-organ high-definition CT scanner we obtained high quality images of coronary stents with good interpretability and diagnostic accuracy combined with low radiation exposure, even in patients with unfavorable HR or heart rhythm for CCTA evaluation.

An automatic multi-class coronary atherosclerosis plaque detection and classification framework

Detection of different classes of atherosclerotic plaques is important for early intervention of coronary artery diseases. However, previous methods focused either on the detection of a specific class of coronary plaques or on the distinction between plaques and normal arteries, neglecting the classification of different classes of plaques. Therefore, we proposed an automatic multi-class coronary atherosclerosis plaque detection and classification framework. Firstly, we retrieved the transverse cross sections along centerlines from the computed tomography angiography. Secondly, we extracted the region of interests based on coarse segmentation. Thirdly, we extracted a random radius symmetry (RRS) feature vector, which incorporates multiple descriptions into a random strategy and greatly augments the training data. Finally, we fed the RRS feature vector into the multi-class coronary plaque classifier. In experiments, we compared our proposed framework with other methods on the cross sections of Rotterdam Coronary Datasets, including 729 non-calcified plaques, 511 calcified plaques, and 546 mixed plaques. Our RRS with support vector machine outperforms the intensity feature vector and the random forest classifier, with the average precision of 92.6 ± 1.9% and average recall of 94.3 ± 2.1%. The proposed framework provides a computer-aided diagnostic method for multi-class plaque detection and classification. Graphical abstract Diagram of the proposed automatic multi-class coronary atherosclerosis plaque detection and classification framework. ᅟ.

The role of advanced reconstruction algorithms in cardiac CT

Non-linear iterative reconstruction (IR) algorithms have been increasingly incorporated into clinical cardiac CT protocols at institutions around the world. Multiple IR algorithms are available commercially from various vendors. IR algorithms decrease image noise and are primarily used to enable lower radiation dose protocols. IR can also be used to improve image quality for imaging of obese patients, coronary atherosclerotic plaques, coronary stents, and myocardial perfusion. In this article, we will review the various applications of IR algorithms in cardiac imaging and evaluate how they have changed practice.

Improved Estimation of Coronary Plaque and Luminal Attenuation Using a Vendor-specific Model-based Iterative Reconstruction Algorithm in Contrast-enhanced CT Coronary Angiography

RATIONALE AND OBJECTIVES

To investigate the stabilities of plaque attenuation and coronary lumen for different plaque types, stenotic degrees, lumen densities, and reconstruction methods using coronary vessel phantoms and the visualization of coronary plaques in clinical patients through coronary computed tomography (CT) angiography.

MATERIALS AND METHODS

We performed 320-detector volume scanning of vessel tubes with stenosis and a tube without stenosis using three types of plaque CT numbers. The stenotic degrees were 50% and 75%. Images were reconstructed with filtered back projection (FBP) and two types of iterative reconstructions (AIDR3D and FIRST [forward-projected model-based iterative reconstruction solution]), with stenotic CT number of approximately 40, 80, and 150 HU (Hounsfield unit), respectively. In each case, the tubing of the coronary vessel was filled with diluted contrast material and distilled water to reach the target lumen CT numbers of approximately 350 HU and 450 HU, and 0 HU, respectively. Peak lumen and plaque CT numbers were measured to calculate the lumen-plaque contrast. In addition, we retrospectively evaluated the image quality with regard to coronary arterial lumen and the plaque in 10 clinical patients on a 4-point scale.

RESULTS

At 50% stenosis, the plaque CT number with contrast enhancement increased for FBP and AIDR3D, and the difference in the plaque CT number with and without contrast enhancement was 15-44 HU for FBP and 10-31 HU for AIDR3D. However, the plaque CT number for FIRST had a smaller variation and the difference with and without contrast enhancement was -12 to 8 HU. The visual evaluation score for the vessel lumen was 2.8 ± 0.6, 3.5 ± 0.5, and 3.7 ± 0.5 for FBP, AIDR3D, and FIRST, respectively.

CONCLUSIONS

The FIRST method controls the increase in plaque density and the lumen-plaque contrast. Consequently, it improves the visualization of coronary plaques in coronary CT angiography.

Coronary Artery Stent Evaluation with Model-based Iterative Reconstruction at Coronary CT Angiography

RATIONALE AND OBJECTIVES

This study aims to compare the image quality of coronary artery stent scans on computed tomography images reconstructed with forward projected model-based iterative reconstruction solution (FIRST) and adaptive iterative dose reduction 3D (AIDR 3D).

MATERIALS AND METHODS

Coronary computed tomography angiography scans of 23 patients with 32 coronary stents were used. The images were reconstructed with AIDR 3D and FIRST. We generated computed tomography attenuation profiles across the stents and measured the width of the edge rise distance and the edge rise slope (ERS). We also calculated the stent lumen attenuation increase ratio (SAIR) and measured visible stent lumen diameters. Two radiologists visually evaluated the image quality of the stents using a 4-point scale (1 = poor, 4 = excellent).

RESULTS

There was no significant difference in the edge rise distance between the two reconstruction methods (P = 0.36). The ERS on FIRST images was greater than the ERS on AIDR 3D images (325.2 HU/mm vs 224.4 HU/mm; P <0.01). The rate of the visible stent lumen diameter compared to the true diameter on FIRST images was higher than that on AIDR 3D images (51.4% vs 47.3%, P <0.01). The SAIR on FIRST images was lower than the SAIR on AIDR 3D images (0.19 vs 0.30, P <0.01). The mean image quality scores for AIDR 3D and FIRST images were 3.18 and 3.63, respectively; the difference was also significant (P <0.01).

CONCLUSION

The image quality of coronary artery stent scans is better on FIRST than on AIDR 3D images.

Iterative Image Reconstruction Improves the Accuracy of Automated Plaque Burden Assessment in Coronary CT Angiography: A Comparison With Intravascular Ultrasound

OBJECTIVE

The purpose of this study was to determine whether use of iterative image reconstruction algorithms improves the accuracy of coronary CT angiography (CCTA) compared with intravascular ultrasound (IVUS) in semiautomated plaque burden assessment.

MATERIALS AND METHODS

CCTA and IVUS images of seven coronary arteries were acquired ex vivo. CT images were reconstructed with filtered back projection (FBP) and adaptive statistical (ASIR) and model-based (MBIR) iterative reconstruction algorithms. Cross-sectional images of the arteries were coregistered between CCTA and IVUS in 1-mm increments. In CCTA, fully automated (without manual corrections) and semiautomated (allowing manual corrections of vessel wall boundaries) plaque burden assessments were performed for each of the reconstruction algorithms with commercially available software. In IVUS, plaque burden was measured manually. Agreement between CCTA and IVUS was determined with Pearson correlation.

RESULTS

A total of 173 corresponding cross sections were included. The mean plaque burden measured with IVUS was 63.39% ± 10.63%. With CCTA and the fully automated technique, it was 54.90% ± 11.70% with FBP, 53.34% ± 13.11% with ASIR, and 55.35% ± 12.22% with MBIR. With CCTA and the semiautomated technique mean plaque burden was 54.90% ± 11.76%, 53.40% ± 12.85%, 57.09% ± 11.05%. Manual correction of the semiautomated assessments was performed in 39% of all cross sections and improved plaque burden correlation with the IVUS assessment independently of reconstruction algorithm (p < 0.0001). Furthermore, MBIR was superior to FBP and ASIR independently of assessment method (semiautomated, r = 0.59 for FBP, r = 0.52 for ASIR, r = 0.78 for MBIR, all p < 0.001; fully automated, r = 0.40 for FBP, r = 0.37 for ASIR, r = 0.53 for MBIR, all p < 0.001).

CONCLUSION

For the quantification of plaque burden with CCTA, MBIR led to better correlation with IVUS than did traditional reconstruction algorithms such as FBP, independently of the use of a fully automated or semiautomated assessment approach. The highest accuracy for quantifying plaque burden with CCTA can be achieved by using MBIR data with semiautomated assessment.

Iterative model reconstruction reduces calcified plaque volume in coronary CT angiography

OBJECTIVE

To assess the impact of iterative model reconstruction (IMR) on calcified plaque quantification as compared to filtered back projection reconstruction (FBP) and hybrid iterative reconstruction (HIR) in coronary computed tomography angiography (CTA).

METHODS

Raw image data of 52 patients who underwent 256-slice CTA were reconstructed with IMR, HIR and FBP. We evaluated qualitative, quantitative image quality parameters and quantified calcified and partially calcified plaque volumes using automated software.

RESULTS

Overall qualitative image quality significantly improved with HIR as compared to FBP, and further improved with IMR (p<0.01 all). Contrast-to-noise ratios were improved with IMR, compared to HIR and FBP (51.0 [43.5-59.9], 20.3 [16.2-25.9] and 14.0 [11.2-17.7], respectively, all p<0.01) Overall plaque volumes were lowest with IMR and highest with FBP (121.7 [79.3-168.4], 138.7 [90.6-191.7], 147.0 [100.7-183.6]). Similarly, calcified volumes (>130 HU) were decreased with IMR as compared to HIR and FBP (105.9 [62.1-144.6], 110.2 [63.8-166.6], 115.9 [81.7-164.2], respectively, p<0.05 all). High-attenuation non-calcified volumes (90-129 HU) yielded similar values with FBP and HIR (p=0.81), however it was lower with IMR (p < 0.05 both). Intermediate- (30-89 HU) and low-attenuation (<30 HU) non-calcified volumes showed no significant difference (p=0.22 and p=0.67, respectively).

CONCLUSIONS

IMR improves image quality of coronary CTA and decreases calcified plaque volumes.

Assessment of Coronary Artery Calcium on Low-Dose Coronary Computed Tomography Angiography With Iterative Reconstruction

OBJECTIVE

This study aims to evaluate whether coronary calcium scoring (CCS) is also feasible using low-radiation-dose coronary computed tomography angiography (CCTA) in combination with iterative reconstruction.

METHODS

Forty-three individuals without known coronary artery disease underwent both noncontrast CCS (±1 mSv) for reference Agatston scores and low-dose CCTA (±3 mSv). Raw CCTA data were reconstructed with filtered back projection (FBP), hybrid iterative reconstruction (HIR), and model-based iterative reconstruction (MIR). Calcification volumes were derived with thresholds of >351 and >600 Hounsfield units (HU) and converted to proxy Agatston scores with linear regression analysis.

RESULTS

Intraclass correlation coefficients for Agatston scores versus CCTA volumes with FBP and iterative reconstruction were excellent (ranges 0.94-0.99 and 0.96-0.99 for >351 HU and >600 HU thresholds, respectively). The >351 HU threshold resulted in higher CCTA volume scores ranging from 65.9 (15.1-347.0) for HIR to 94.8 (42.0-423.0) for MIR (P = 0.001 and <0.001, respectively). The >600 HU threshold scores ranged from 14.1 (0.0-159.3) for HIR to 28.6 (0.0-215.6) for MIR (P = 0.003 and 0.027, respectively). At >351 HU, reclassification occurred in 21 individuals (49%) for FBP and HIR and 25 individuals (58%) for MIR. Reclassifications decreased with >600 HU to 10 (HIR, 23%), 8 (FBP, 19%), and 4 (MIR, 9%).

CONCLUSIONS

The CCS is feasible using iteratively reconstructed low-dose CCTA with a calcium threshold of >600 HU. Using MIR, only 9% of individuals were reclassified.

Coronary CT Angiography in Heavily Calcified Coronary Arteries: Improvement of Coronary Lumen Visualization and Coronary Stenosis Assessment With Image Postprocessing Methods

To compare the diagnostic value of coronary CT angiography (CCTA) with use of 2 image postprocessing methods (CCTA_S) and (CCTA_OS) and original data (CCTA_O) for the assessment of heavily calcified plaques. Fifty patients (41 men, 9 women; mean age 61.9 years ± 9.1) with suspected coronary artery disease who underwent CCTA and invasive coronary angiography (ICA) examinations were included in the study. Image data were postprocessed with "sharpen" and smooth reconstruction algorithms in comparison with the original data without undergoing any image postprocessing to determine the effects on suppressing blooming artifacts due to heavy calcification in the coronary arteries. Minimal lumen diameter and degree of stenosis were measured and compared between CCTA_S, CCTA_OS, and CCTA_O with ICA as the reference method. The area under the curve (AUC) by receiver-operating characteristic curve analysis (ROC) was also compared among these 3 CCTA techniques. On a per-vessel assessment, the sensitivity, specificity, positive predictive value and negative predictive value, and 95% confidence interval (CI) were 100% (95% CI: 89%, 100%), 33% (95% CI: 22%, 45%), 41% (95% CI: 30%, 53%), 100% (95% CI: 85%, 100%) for CCTA_O, 94% (95% CI: 79%, 99%), 66% (95% CI: 54%, 77%), 57% (95% CI: 43%, 70%), and 95% (95% CI: 85%, 99%) for CCTA_S, 94% (95% CI: 79%, 99%), 44% (95% CI: 32%, 57%), 44% (95% CI: 32%, 57%), and 97% (95% CI: 79%, 99%) for CCTA_OS, respectively. The AUC by ROC curve analysis for CCTA_S showed significant improvement for detection of >50% coronary stenosis in left anterior descending coronary artery compared to that of CCTA_OS and CCTA_O methods (P < 0.05), with no significance differences for detection of coronary stenosis in the left circumflex and right coronary arteries (P > 0.05).CCTA with "sharpen" reconstruction reduces blooming artifacts from heavy calcification, thus, leading to significant improvement of specificity and positive predictive value of CCTA in patients with heavily calcified plaques. However, specificity is still moderate and additional functional imaging may be needed.

Association of left bundle branch block with obstructive coronary artery disease on coronary CT angiography: a case-control study

AIMS

Left bundle branch block (LBBB) is considered an unfavourable prognostic marker in patients with underlying heart disease. Testing for coronary artery disease (CAD) is often prompted by incidental LBBB finding, but published studies disagree about a significant association between LBBB and CAD. We therefore assessed the association of LBBB with previously unknown CAD in patients undergoing coronary computed tomography angiography (CCTA).

METHODS AND RESULTS

We enrolled 818 patients (mean age 57.2 ± 11.1 years, 106 patients with presumably new LBBB and 712 controls) without known CAD who underwent 64-slice CCTA. Image quality was assessed for each coronary segment. Comparison of obstructive CAD prevalence (defined as ≥50% stenosis) was performed using triple case-matching for pre-test probability (based on age, gender, and symptom typicality) in 101 LBBB patients and 303 matched controls with diagnostic quality in all segments. We found no difference in obstructive CAD prevalence between LBBB patients and matched controls (15 vs. 16%, P = 0.88). Similarly, there were no significant differences in cardiovascular risk factors (CVRF), stenosis severity, CAD extent, non-obstructive CAD, and vessel-based analysis between patient groups. Image quality was very high in LBBB patients and comparable to controls. On multivariate analysis, age, gender, typical angina, and CVRF, but not LBBB (P = 0.94), emerged as significant and independent predictors of obstructive CAD.

CONCLUSION

CAD prevalence is similar in LBBB patients at low-to-moderate pre-test probability compared with controls with similar CVRF matched for age, gender, and symptom typicality. CCTA is a useful imaging modality in LBBB patients, providing comparable image quality to non-LBBB controls.

Plaque assessment by coronary CT

Coronary CT angiography (CTA) has emerged as a highly reliable and non-invasive modality for the exclusion of coronary artery disease. Recent technological advancements in coronary CTA imaging allow for robust qualitative and quantitative assessment of atherosclerotic plaques. Furthermore, CTA is a promising modality for functional evaluation of coronary lesions. Individual plaque features, the extent and severity of atherosclerotic plaque burden were proposed to improve cardiovascular risk stratification. It has been suggested that total atherosclerotic plaque burden is a stronger predictor of coronary events than total ischemia burden. The quest to noninvasively detect individual vulnerable plaques still remains. In the current review we sought to summarize state-of-the-art coronary artery plaque assessment by CTA.

Dose reduction in cardiothoracic CT: review of currently available methods

Radiation exposure from computed tomography (CT) has received much attention lately in the medical literature and the media, given the relatively high radiation dose that characterizes a CT examination. Although there are a variety of possible strategies for reducing radiation exposure from CT in an individual patient, optimal CT image acquisition requires that the radiologist understand new scanner technology and how to implement the most effective means of dose reduction while maintaining image quality. The authors describe a practical approach to dose reduction in cardiothoracic radiology, discussing CT radiation dose metrics (eg, CT dose index, dose-length product, effective diameter, and size-specific dose estimate) as well as CT scanner parameters that directly or indirectly influence radiation dose (eg, scan length, x-ray tube output, tube current modulation, pitch, image reconstruction techniques [including iterative reconstruction], and noise reduction). These variables are discussed in terms of their relative importance to image quality and the implications of parametric changes for image quality and diagnostic content, and practical recommendations are made for their immediate implementation in the clinical setting. Taken together, the principles of physics and key parameters involved in reducing radiation dose while maintaining image quality can serve as a "survival guide" for a diagnostic radiology practice.

Coronary plaque characterization using CT

OBJECTIVE. In this article, we review the histopathologic classification of coronary atherosclerotic plaques and describe the possibilities and limitations of CT regarding the evaluation of coronary artery plaques. CONCLUSION. The composition of atherosclerotic plaques in the coronary arteries displays substantial variability and is associated with the likelihood for rupture and downstream ischemic events. Accurate identification and quantification of coronary plaque components on CT is challenging because of the limited temporal, spatial, and contrast resolutions of current scanners. Nonetheless, CT may provide valuable information that has potential for characterization of coronary plaques. For example, the extent of calcification can be determined, lipid-rich lesions can be separated from more fibrous ones, and positive remodeling can be identified.

Iterative reconstruction in cardiac CT

Iterative reconstruction (IR) has the ability to reduce image noise in CT without compromising diagnostic quality, which permits a significant reduction in effective radiation dose. This been increasingly integrated into clinical CT practice over the past 7 years and has been particularly important in the field of cardiac CT with multiple vendors introducing cardiac CT-compatible IR algorithms. The following review will summarize the principles of IR algorithms, studies validating their noise- and dose-reducing abilities, and the specific applications of IR in cardiac CT.

Accuracy of coronary CT angiography using a submillisievert fraction of radiation exposure: comparison with invasive coronary angiography

BACKGROUND

Coronary computed tomography angiography (CTA) is increasingly being used for evaluation of coronary artery disease (CAD). As a result of the widely reported potential of carcinogenic risk from x-ray based examinations, many strategies have been developed for dose reduction with CTA.

OBJECTIVES

The purpose of this study was to assess the diagnostic accuracy of CTA acquired with a submillisievert fraction of effective radiation dose reconstructed with a model-based iterative reconstruction (MBIR) using invasive coronary angiography (ICA) as a standard of reference.

METHODS

In 36 patients (body mass index range 17 to 39 kg/m(2)) undergoing ICA for CAD evaluation, a CTA was acquired using very low tube voltage (80 to 100 kV) and current (150 to 210 mA) and was reconstructed with MBIR. CAD (defined as ≥50% luminal narrowing) was assessed on CTA and on ICA.

RESULTS

CTA resulted in an estimated radiation dose exposure of 0.29 ± 0.12 mSv (range 0.16 to 0.53 mSv), yielding 96.9% (436 of 450) interpretable segments. On an intention-to-diagnose basis, no segment was excluded, and vessels with at least 1 nonevaluable segment and no further finding were classified as false positive. This resulted in a sensitivity, specificity, positive, and negative predictive value and accuracy of 100%, 74%, 77%, 100%, and 86% per patient and 85%, 86%, 56%, 96%, and 85% per vessel, respectively.

CONCLUSIONS

The use of MBIR reconstruction allows accurate noninvasive diagnosis of CAD with CTA at a submillisievert fraction of effective radiation dose comparable with a chest x-ray in 2 views.

Effect of iDose4 iterative reconstruction algorithm on image quality and radiation exposure in prospective and retrospective electrocardiographically gated coronary computed tomographic angiography

OBJECTIVES

The aims of this study were to compare a commercially available reconstruction algorithm (iDose4) with filtered back projection (FBP) in terms of image quality (IQ) for both retrospective electrocardiographically gated and prospective electrocardiographically triggered cardiac computed tomographic angiography (CCTA) protocols and to evaluate the achievable radiation dose reduction.

METHODS

A total cohort of 58 patients underwent either prospective CTCA or retrospective CTCA with full or reduced tube current-time product (in milliampere-second) protocol on a 64-slice multidetector computed tomographic scanner. All images were reconstructed with FBP, whereas the reduced milliampere-second images were also reconstructed using 2 levels (levels 4 and 6) of iDose4. Subjective and objective IQ was evaluated.

RESULTS

Dose reductions of 43% in the retrospective CCTA protocol and 27% in the prospective CCTA protocol were achieved without compromising IQ. In the prospective CCTA protocol, the reduced-dose images were highly scored; thus, additional reduction of exposure settings is feasible. In the retrospective acquisition, dose reduction has led to similar IQ scores between the reduced-dose iDose4 images and the full-dose FBP images. Considering different reconstructions (FBP, iDose-L4 and -L6) of the same acquisition data, increase in iDose4 level resulted in less noisy images. A slight improvement was also noticed in all IQ indices; however, this improvement was not statistically significant for both acquisition protocols.

CONCLUSIONS

This study demonstrated that the application of iDose at CCTA facilitates significant radiation dose reduction by maintaining diagnostic quality. The combination of iDose4 with prospective acquisition is able to significantly reduce effective dose associated with CTCA at values of approximately 2 mSv and even lower.

Effect of iterative reconstruction algorithms on peripheral MDCT angiography virtual histology plaque volumes: have we been overestimating disease burden?

Our objective was to compare plaque volumes of multidetector computed tomographic images reconstructed using adaptive statistical iterative reconstruction (ASIR), model-based iterative reconstruction (MBIR), and filtered back projection (FBP). We reviewed 25 patients for a total of 50 extremities imaged on the same scanner. Calcified plaque FBP volume (3468.2 ± 2634.8 mm(3)) was higher than ASIR (2548.1 ± 2166.5 mm(3)). Calcified plaque FBP volume was higher than MBIR (mean=2345.7 ± 1935.4 mm(3)). Our findings suggest that traditional FBP methods overestimate disease compared to newer reconstruction methods.

Computed tomography depiction of small pediatric vessels with model-based iterative reconstruction

BACKGROUND

Computed tomography (CT) is extremely important in characterizing blood vessel anatomy and vascular lesions in children. Recent advances in CT reconstruction technology hold promise for improved image quality and also reductions in radiation dose. This report evaluates potential improvements in image quality for the depiction of small pediatric vessels with model-based iterative reconstruction (Veo™), a technique developed to improve image quality and reduce noise.

OBJECTIVE

To evaluate Veo™ as an improved method when compared to adaptive statistical iterative reconstruction (ASIR™) for the depiction of small vessels on pediatric CT.

MATERIALS AND METHODS

Seventeen patients (mean age: 3.4 years, range: 2 days to 10.0 years; 6 girls, 11 boys) underwent contrast-enhanced CT examinations of the chest and abdomen in this HIPAA compliant and institutional review board approved study. Raw data were reconstructed into separate image datasets using Veo™ and ASIR™ algorithms (GE Medical Systems, Milwaukee, WI). Four blinded radiologists subjectively evaluated image quality. The pulmonary, hepatic, splenic and renal arteries were evaluated for the length and number of branches depicted. Datasets were compared with parametric and non-parametric statistical tests.

RESULTS

Readers stated a preference for Veo™ over ASIR™ images when subjectively evaluating image quality criteria for vessel definition, image noise and resolution of small anatomical structures. The mean image noise in the aorta and fat was significantly less for Veo™ vs. ASIR™ reconstructed images. Quantitative measurements of mean vessel lengths and number of branches vessels delineated were significantly different for Veo™ and ASIR™ images. Veo™ consistently showed more of the vessel anatomy: longer vessel length and more branching vessels.

CONCLUSION

When compared to the more established adaptive statistical iterative reconstruction algorithm, model-based iterative reconstruction appears to produce superior images for depiction of small pediatric vessels on computed tomography.

256-MDCT for evaluation of urolithiasis: iterative reconstruction allows for a significant reduction of the applied radiation dose while maintaining high subjective and objective image quality

PURPOSE

Multidetector CT (MDCT) is the established imaging modality in diagnostics of urolithiasis. The aim of iterative reconstruction (IR) is to allow for a radiation dose reduction while maintaining high image quality. This study evaluates its performance in MDCT for assessment of urolithiasis.

MATERIALS AND METHODS

Fifty-two patients underwent non-contrast abdominal MDCT. Twenty-six patients were referred to MDCT under suspicion of urolithiasis, and examined using a dose-reduced scan protocol (RDCT). Twenty-six patients, who had undergone standard-dose MDCT, served as reference for radiation dose comparison. RDCT images were reconstructed using an IR system (iDose4™, Philips Healthcare, Cleveland, OH, USA). Objective image noise (OIN) was recorded and five radiologists rated the subjective image quality independently. Radiation parameters were derived from the scan protocols.

RESULTS

The CTDIvol could be reduced by 50% to 5.8 mGy (P < 0.0001). The same reduction was achieved for DLP and effective dose to 253 ± 27 mGy*cm (P < 0.0001) and 3.9 ± 0.4 mSv (P < 0.0001). IR led to a reduction of the OIN of up to 61% compared with classic filtered back projection (FBP) (P < 0.0001). The OIN declined with increasing IR levels. RDCT with FBP showed the lowest scores of subjective image quality (2.32 ± 0.04). Mean scores improved with increasing IR levels. iDose6 was rated with the best mean score (3.66 ± 0.04).

CONCLUSION

The evaluated IR-tool and protocol may be applied to achieve a considerable radiation dose reduction in MDCT for diagnostics of urolithiasis while maintaining a confident image quality. Best image quality, suitable for evaluation of the entire abdomen concerning differential diagnoses, was achieved with iDose6.

Impact of a new motion-correction algorithm on image quality of low-dose coronary CT angiography in patients with insufficient heart rate control

RATIONALE AND OBJECTIVES

Prospective electrocardiogram (ECG) triggering allows coronary computed tomography angiography (CCTA) scanning with low radiation dose but requires heart rates below 63 beats/min. We assessed the impact of a novel vendor-specific motion-correction algorithm on image quality and interpretability of low-dose CCTA acquired despite insufficient heart rate control.

MATERIALS AND METHODS

In 40 patients undergoing CCTA for the assessment of known or suspected coronary artery disease who did not reach the target heart rate below 63 beats/min despite β-blockade before prospective low-dose scanning, the temporal acquisition window was increased (80 ms additional padding). The new algorithm detects and integrates vessel path and velocity from adjacent cardiac phases for motion correction. Two blinded observers assessed image quality on a 4-point Likert scale (1, nonevaluative; 2, reduced but evaluative; 3, good; and 4, excellent) and the fraction of interpretable segments (score 2 or more) using motion correction versus standard reconstruction.

RESULTS

Image reconstruction with motion correction resulted in an increased median coronary artery image quality score (excellent interobserver agreement, κ = 0.85) compared to standard reconstruction (3.4 vs. 3.0, P < .001). Consequently, motion-corrected reconstruction significantly improved the overall interpretability of coronary arteries (from 78% to 88%, P < .001). Estimated mean effective radiation dose was 2.3 ± 0.8 mSv.

CONCLUSIONS

A novel, vendor-specific, motion-corrected, reconstruction algorithm improves image quality and interpretability of prospectively ECG-triggered low-dose CCTA despite insufficient heart rate control.

Coronary computed tomography angiography with model-based iterative reconstruction using a radiation exposure similar to chest X-ray examination

Aims

To evaluate the feasibility and image quality of coronary computed tomography angiography (CCTA) acquisition with a submillisievert fraction of effective radiation dose using model-based iterative reconstruction (MBIR) for noise reduction.

Methods and results

In 42 patients undergoing standard low-dose (100–120 kV; 450–700 mA) and additional ultra-low-dose CCTA (80–100 kV; 150–210 mA) reconstructed with MBIR, segmental image quality was graded on a four-point scale [(i): non-evaluative, (ii): good, (iii): adequate, and (iv): excellent]. Signal-to-noise ratio (SNR) was calculated dividing left main artery (LMA) and right coronary artery (RCA) attenuation by the aortic root noise. Over a wide range of body mass index (18–40 kg/m²), the estimated median radiation dose exposure was 1.19 mSv [interquartile range (IQR): 1.07–1.30 mSv] for standard and 0.21 mSv (IQR: 0.18–0.23 mSv) for ultra-low-dose CCTA (P < 0.001). The median image quality score per segment was 3.5 (IQR: 3.0–4.0) in standard CCTA vs. 3.5 (IQR: 2.5–4.0) in ultra-low dose with MBIR (P = 0.29). Diagnostic image quality (scores 2–4) was found in 98.7 vs. 97.8% coronary segments (P = 0.36). Introduction of MBIR for ultra-low-dose CCTA resulted in a significant increase in SNR (P < 0.001) for LMA (from 15 ± 5 to 29 ± 7) and RCA (from 14 ± 4 to 27 ± 6) despite 82% dose reduction.

Conclusion

Coronary computed tomography angiography acquisition with diagnostic image quality is feasible at an ultra-low radiation dose of 0.21 mSv, e.g. in the range reported for a postero-anterior and lateral chest X-ray.

The effect of iterative reconstruction on quantitative computed tomography assessment of coronary plaque composition

To compare coronary plaque size and composition as well as degree of coronary artery stenosis on coronary Computed Tomography angiography (CCTA) using three levels of iterative reconstruction (IR) with standard filtered back projection (FBP). In 63 consecutive patients with a clinical indication for CCTA 55 coronary plaques were analysed. Raw data were reconstructed using standard FBP and levels 2, 4 and 6 of a commercially available IR algorithm (iDose(4)). CT attenuation and noise were measured in the aorta and two coronary arteries. Both signal-to-noise-ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. The amount of lipid, fibrous and calcified plaque components and mean cross-sectional luminal area were analysed using dedicated software. Image noise was reduced by 41.6% (p < 0.0001) and SNR and CNR in the aorta were improved by 73.4% (p < 0.0001) and 72.9% (p < 0.0001) at IR level 6, respectively. IR improved objective image quality measures more in the aorta than in the coronary arteries. Furthermore, IR had no significant effect on measurements of plaque volume and cross-sectional luminal area. The application of IR significantly improves objective image quality, and does not alter quantitative analysis of coronary plaque volume, composition and luminal area.