Influence of the motion correction algorithm on the quality and interpretability of images of single-source 64-detector coronary CT angiography among patients grouped by heart rate

Usefulness of second-generation motion correction algorithm in improving delineation and reducing motion artifact of coronary computed tomography angiography

BACKGROUND

The purpose of this study was to investigate the usefulness of second-generation intra-cycle motion correction algorithm (SnapShot Freeze 2, GE Healthcare, MC2) in improving the delineation and interpretability of coronary arteries in coronary computed tomography angiography (CCTA) compared to first-generation intra-cycle motion correction algorithm (SnapShot Freeze, GE Healthcare, MC1).

METHODS

Fifty consecutive patients with known or suspected coronary artery disease who underwent CCTA on a 256-slice CT scanner were retrospectively studied. CCTA were reconstructed with three different algorithms: no motion correction (NMC), MC1, and MC2. The delineation of coronary arteries on CCTA was qualitatively rated on a 5-point scale from 1 (nondiagnostic) to 5 (excellent) by two radiologists blinded to the reconstruction method and the patient information.

RESULTS

On a per-vessel basis, the delineation scores of coronary arteries were significantly higher on MC2 images compared to MC1 images (median [interquartile range], right coronary artery, 5.0 [4.5-5.0] vs 4.5 [4.0-5.0]; left anterior descending artery, 5.0 [4.5-5.0] vs 4.5 [3.5-5.0]; left circumflex artery, 5.0 [4.5-5.0] vs 4.5 [3.9-5.0]; all p ​< ​0.05). On a per-segment basis, for both 2 observers, the delineation scores on segment 1, 2, 8, 9, 10, 12 and 13 on MC2 images were significantly better than those on MC1 images (p ​< ​0.05). The percentage of interpretable segments (rated score 3 or greater) on NMC, MC1, and MC2 images was 90.5-91.9%, 97.4-97.9%, and 100.0%, respectively.

CONCLUSION

Second-generation intra-cycle motion correction algorithm improves the delineation and interpretability of coronary arteries in CCTA compared to first-generation algorithm.

Optimizing Coronary Computed Tomography Angiography Using a Novel Deep Learning-Based Algorithm

Coronary computed tomography angiography (CCTA) is an essential part of the diagnosis of chronic coronary syndrome (CCS) in patients with low-to-intermediate pre-test probability. The minimum technical requirement is 64-row multidetector CT (64-MDCT), which is still frequently used, although it is prone to motion artifacts because of its limited temporal resolution and z-coverage. In this study, we evaluate the potential of a deep-learning-based motion correction algorithm (MCA) to eliminate these motion artifacts. 124 64-MDCT-acquired CCTA examinations with at least minor motion artifacts were included. Images were reconstructed using a conventional reconstruction algorithm (CA) and a MCA. Image quality (IQ), according to a 5-point Likert score, was evaluated per-segment, per-artery, and per-patient and was correlated with potentially disturbing factors (heart rate (HR), intra-cycle HR changes, BMI, age, and sex). Comparison was done by Wilcoxon-Signed-Rank test, and correlation by Spearman's Rho. Per-patient, insufficient IQ decreased by 5.26%, and sufficient IQ increased by 9.66% with MCA. Per-artery, insufficient IQ of the right coronary artery (RCA) decreased by 18.18%, and sufficient IQ increased by 27.27%. Per-segment, insufficient IQ in segments 1 and 2 decreased by 11.51% and 24.78%, respectively, and sufficient IQ increased by 10.62% and 18.58%, respectively. Total artifacts per-artery decreased in the RCA from 3.11 ± 1.65 to 2.26 ± 1.52. HR dependence of RCA IQ decreased to intermediate correlation in images with MCA reconstruction. The applied MCA improves the IQ of 64-MDCT-acquired images and reduces the influence of HR on IQ, increasing 64-MDCT validity in the diagnosis of CCS.

The influence of motion-compensated reconstruction on coronary artery analysis for a dual-layer detector CT system: a dynamic phantom study

OBJECTIVES

Cardiac motion artifacts hinder the assessment of coronary arteries in coronary computed tomography angiography (CCTA). We investigated the impact of motion compensation reconstruction (MCR) on motion artifacts in CCTA at various heart rates (HR) using a dynamic phantom.

MATERIALS AND METHODS

An artificial hollow coronary artery (5-mm diameter lumen) filled with iodinated contrast agent (400 HU at 120 kVp), positioned centrally in an anthropomorphic chest phantom, was scanned using a dual-layer spectral detector CT. The artery was translated at constant horizontal velocities (0-80 mm/s, increment of 10 mm/s). For each velocity, five CCTA scans were repeated using a clinical protocol. Motion artifacts were quantified using the in-plane motion area. Regression analysis was performed to calculate the reduction in motion artifacts provided by MCR, by division of the slopes of non-MCR and MCR fitted lines.

RESULTS

Reference mean (95% confidence interval) motion artifact area was 24.9 mm2 (23.8, 26.0). Without MCR, motion artifact areas for velocities exceeding 20 mm/s were significantly larger (up to 57.2 mm2 (40.1, 74.2)) than the reference. With MCR, no significant differences compared to the reference were shown for all velocities, except for 70 mm/s (29.0 mm2 (27.0, 31.0)). The slopes of the fitted data were 0.44 and 0.04 for standard and MCR reconstructions, respectively, resulting in an 11-time motion artifact reduction.

CONCLUSION

MCR may improve CCTA assessment in patients by reducing coronary artery motion artifacts, especially in those with elevated HR who cannot receive beta blockers or do not attain the targeted HR.

CLINICAL RELEVANCE STATEMENT

This vendor-specific motion compensation reconstruction may improve coronary computed tomography angiography assessment in patients by reduction of coronary artery motion artifacts, especially in those with elevated various heart rates (HR) who cannot receive beta blockers or do not attain the targeted HR.

KEY POINTS

• Motion artifacts are known to hinder the assessment of coronary arteries on coronary CT angiography (CCTA), leading to more non-diagnostic scans. • This dynamic phantom study shows that motion compensation reconstruction (MCR) reduces motion artifacts at various velocities, which may help to decrease the number of non-diagnostic scans. • MCR in this study showed to reduce motion artifacts 11-fold.

New Whole-Heart motion correction algorithm enables diagnostic CT of aortic valve and coronary arteries in systolic phase for transcatheter aortic valve implantation candidates

OBJECTIVES

To investigate the ability of new generation snapshot freeze (NGSSF) algorithm in improving diagnostic image quality of both aortic valve and coronary arteries for transcatheter aortic valve implantation (TAVI) candidates in TAVI planning CT.

METHODS

Sixty-four TAVI candidates underwent TAVI planning CT were enrolled. Scans from coronary CT angiography were reconstructed at 20%, 30%, 40%, and 75% R-R cardiac phases with NGSSF and standard (STD) algorithm. In each phase, following parameters were compared: aortic valve measurements and their reproducibility; image quality of aortic valve and coronary arteries. The diagnostic accuracies of TAVI planning CT for coronary artery stenosis in 30% R-R phase with NGSSF and STD algorithms were calculated in 47out of 64 patients with invasive coronary angiography as reference standard.

RESULTS

For subjective image quality evaluation, the excellent rate for aortic valve improved from 25.0% to 93.8% and the interpretable rate for coronary arteries increased from 20.3% to 95.3% in the 30% phase images with NGSSF compared with images with STD. For the detection of > 50% coronary artery stenosis, the 30% phase images with NGSSF provided a sensitivity of 90%, specificity of 81.48%, negative predictive value of 91.7%, and positive predictive value of 78.3% on a per-patient basis; While images with STD, had a corresponding results of 95.0%, 33.33%, 90.0%, and 51.4%, respectively.

CONCLUSIONS

NGSSF significantly improves image quality for both aortic valve and coronary arteries compared with STD for TAVI patients of all heart rates. NGSSF enables the accurate measurement for aortic valve and satisfactory diagnostic performance for coronary arteries stenosis in the same systolic phase for TAVI planning.

Recent advances in artificial intelligence for cardiac CT: Enhancing diagnosis and prognosis prediction

Recent advances in artificial intelligence (AI) for cardiac computed tomography (CT) have shown great potential in enhancing diagnosis and prognosis prediction in patients with cardiovascular disease. Deep learning, a type of machine learning, has revolutionized radiology by enabling automatic feature extraction and learning from large datasets, particularly in image-based applications. Thus, AI-driven techniques have enabled a faster analysis of cardiac CT examinations than when they are analyzed by humans, while maintaining reproducibility. However, further research and validation are required to fully assess the diagnostic performance, radiation dose-reduction capabilities, and clinical correctness of these AI-driven techniques in cardiac CT. This review article presents recent advances of AI in the field of cardiac CT, including deep-learning-based image reconstruction, coronary artery motion correction, automatic calcium scoring, automatic epicardial fat measurement, coronary artery stenosis diagnosis, fractional flow reserve prediction, and prognosis prediction, analyzes current limitations of these techniques and discusses future challenges.

Deep Learning-Based Motion Correction in Projection Domain for Coronary Computed Tomography Angiography: A Clinical Evaluation

OBJECTIVE

This study aimed to evaluate the clinical performance of a deep learning-based motion correction algorithm (MCA) in projection domain for coronary computed tomography angiography (CCTA).

METHODS

A total of 192 patients who underwent CCTA examinations were included and divided into 2 groups based on the average heart rate (HR): group 1, 82 patients with HR of <75 beats per minute; group 2, 110 patients with HR of ≥75 beats per minute. The CCTA images were reconstructed with and without MCA. The subjective image quality was graded in terms of vessel visualization, sharpness, diagnostic confidence, and overall image quality using a 5-point scale, where cases with all scores of ≥3 were deemed interpretable. Objective image quality was measured through signal-to-noise ratio and contrast-to-noise ratio in regions relative to the vessels. The image quality scores for 2 reconstructions and effective dose between 2 groups were compared.

RESULTS

The mean effective dose was similar between 2 groups. Neither group showed significant difference on objective image quality for 2 reconstructions. Images reconstructed with and without MCA were both found interpretable for group 1, whereas the subjective image quality was significantly improved by the MCA for all 4 metrics in group 2, with the interpretability increased from 80.91% to 99.09%. Compared with group 1, group 2 showed similar interpretability and diagnostic confidence, despite inferior overall image quality.

CONCLUSIONS

In CCTA examinations, the deep learning-based MCA is capable of improving the image quality and diagnostic confidence for patients with increased HR to a similar level as for those with low HR.

Influence of a new motion correction algorithm (CardioCapture) on the correlation between heart rate and optimal reconstruction phase

Purpose

To investigate the effect of a new motion correction algorithm (CardioCapture) on the correlation between heart rate and optimal reconstruction phase by evaluating the impact of wide detector CT combined with CardioCapture on CCTA image quality.

Materials and methods

All cases were examined from April 2021 to September 2021. Two experienced radiologists scored these images on a four-point Likert scale. First, all images were divided into eight groups according to HR (at an interval of 5 bpm). The subjective score of images, the frequency of used CardioCapture, and the proportion of the diastolic reconstruction phase were compared in each group. Then, all cases were divided into two groups, one group was reconstructed using the automatic temporal reconstruction algorithm (Ephase) only, and the other group was reconstructed using the Ephase with the CardioCapture. The relationship between HR and the diastolic reconstruction phase was analyzed by the receiver operator characteristic curve (ROC).

Result

The data of 515 patients were studied. With the increase in HR, the subjective image score decreased, the frequency of CardioCapture increased, and the phase ratio of diastolic reconstruction decreased. When the HR was less than 70 bpm, the percentage of excellence image in each group surpassed 94.90%. The highest utilization rate of CardioCapture was 65.22%, and the lowest proportion of diastolic reconstruction was 72.46%. When 70 bpm < HR ≤ 75 bpm, the image excellence rate was 90.43%, the CardioCapture utilization rate was 82.05%, and the diastolic reconstruction rate was 56.41%.When 75 bpm < HR ≤ 80 bpm, the image excellence rate was 87.91%, the CardioCapture utilization rate was 80.65%, and the diastolic reconstruction was 6.45%.When the HR > 80 bpm, the image excellence rate was 80.00%, the CardioCapture utilization rate was 75.00%, and the diastolic reconstruction rate was 22.50%. The best cut-off point between HR and the diastolic reconstruction ROC curve in the groups without CardioCapture was 65 bpm, while that in groups with CardioCapture was 68 bpm.

Conclusion

The CardioCapture can effectively improve the image quality of CCTA with high HR. By maintaining the HR below 68 bpm and utilizing the prospective ECG-gated narrow phase axial scan, it is possible to ensure optimal image quality and concurrently reduce radiation dose.

Evaluation of the second-generation whole-heart motion correction algorithm (SSF2) used to demonstrate the aortic annulus on cardiac CT

The main purpose of pre-transcatheter aortic valve implantation (TAVI) cardiac computed tomography (CT) for patients with severe aortic stenosis is aortic annulus measurements. However, motion artifacts present a technical challenge because they can reduce the measurement accuracy of the aortic annulus. Therefore, we applied the recently developed second-generation whole-heart motion correction algorithm (SnapShot Freeze 2.0, SSF2) to pre-TAVI cardiac CT and investigated its clinical utility by stratified analysis of the patient's heart rate during scanning. We found that SSF2 reconstruction significantly reduced aortic annulus motion artifacts and improved the image quality and measurement accuracy compared to standard reconstruction, especially in patients with high heart rate or a 40% R-R interval (systolic phase). SSF2 may contribute to improving the measurement accuracy of the aortic annulus.

Improving the Degree and Uniformity of Enhancement in Coronary CT Angiography with a New Bolus Tracking Method Enabled By Free Breathing

RATIONALE AND OBJECTIVES

To demonstrate the improved enhancement degree and uniformity in coronary CT angiography (CCTA) on a 16 cm wide-coverage CT with a new bolus tracking method enabled by free-breathing, in comparison with the conventional breath-holding method.

MATERIALS AND METHODS

A total of 200 patients with suspected coronary heart disease were randomly divided into two groups for CCTA: Group A (n = 100, free-breathing) started CCTA with 2.2 seconds delay after the attenuation in aorta reached 250 HU; Group B (n = 100, breath-holding), used the standard protocol of 80 HU threshold and 8.4 seconds delay. Both groups used the contrast dose rate of 25 mgI/kg/s. CT value and standard deviation in aortic sinus (AS), right coronary artery, left anterior descending, left circumflex, and pericardial fat were measured. Contrast-to-noise ratio for vessels was calculated. Two experienced Radiologists independently reviewed image quality using a 5-point scale (1: nondiagnostic-5: excellent).

RESULTS

There was no difference in contrast dose, radiation dose, heart rate, and qualitative image quality between the two groups (all p > 0.05). However, Group A had higher mean enhancement in vessels (404 ± 66 HU) than Group B (321 ± 69 HU), and lower coefficients of variation of CT value in aortic sinus, right coronary artery, left anterior descending, and left circumflex (16.3%, 17.7%, 19.2%, and 20.5% vs 21.5%, 22.3%, 23.6%, and 22.9%, respectively), (all p < 0.05).

CONCLUSION

A new bolus tracking method enabled by free-breathing in CCTA on a 16 cm wide-coverage CT system increases the enhancement degree and uniformity in coronary arteries, compared with the conventional breath-holding method.

Influence of virtual monochromatic spectral image at different energy levels on motion artifact correction in dual-energy spectral coronary CT angiography

PURPOSE

To investigate the influence of virtual monochromatic spectral (VMS) CT images at different energy levels on the effectiveness of a motion correction technique (SSF) in dual-energy Spectral coronary CT angiography (CCTA).

MATERIALS AND METHODS

29 cases suspected of or diagnosed with coronary artery disease underwent Spectral CCTA using a prospective ECG triggering with 250 ms padding time. SSF was applied to the determined least-motion phase to generate 6 additional sets of VMS images with energy levels from 40 to 100 keV. CT value and standard deviation (SD) in the aortic root and epicardial adipose tissue were measured. Image quality of the RCA, LAD and LCX was evaluated on a per-vessel basis in each patient. Two reviewers evaluated the artery using the score of the segment.

RESULTS

The low energy VMS images increased CT value and image noise compared with higher-energy VMS images, except 90 keV and 100 keV. The CNR of 40-70 keV were higher than those of 80-100 keV (P < 0.05). The image quality scores for images at 50-80 keV were higher than those of 40, 90, and 100 keV (P < 0.05), and the VMS image quality at 50 keV and 60 keV with SSF was the highest.

CONCLUSION

SSF can effectively reduce the motion artifacts when coronary vessels have suitable contrast enhancement which can be achieved by adjusting energy levels of VMS images.

Second-generation motion correction algorithm improves diagnostic accuracy of single-beat coronary CT angiography in patients with increased heart rate

OBJECTIVE

To assess the effect of a second-generation motion correction algorithm on the diagnostic accuracy of coronary computed tomography angiography (CCTA) using a 256-detector row CT in patients with increased heart rates.

METHODS

Eighty-one consecutive symptomatic cardiac patients with increased heart rates (≥ 75 beats per min) were enrolled. All patients underwent CCTA and invasive coronary angiography (ICA). CCTA was performed with a 256-detector row CT using prospectively ECG-triggered single-beat protocol. Images were reconstructed using standard (STD) algorithm, first-generation intra-cycle motion correction (MC1) algorithm, and second-generation intra-cycle motion correction (MC2) algorithm. The image quality of coronary artery segments was assessed by two experienced radiologists using a 4-point scale (1: non-diagnostic and 4: excellent), according to the 18-segment model. Diagnostic performance for segments with significant lumen stenosis (≥ 50%) was compared between STD, MC1, and MC2 by using ICA as the reference standard.

RESULTS

The mean effective dose of CCTA was 1.0 mSv. On per-segment level, the overall image quality score and interpretability were improved to 3.56 ± 0.63 and 99.2% due to the use of MC2, as compared to 2.81 ± 0.85 and 92.5% with STD and 3.21 ± 0.79 and 97.2% with MC1. On per-segment level, compared to STD and MC1, MC2 improved the sensitivity (92.2% vs. 79.2%, 80.7%), specificity (97.8% vs. 82.1%, 90.8%), positive predictive value (89.9% vs. 48.4%, 65.1%), negative predictive value (98.3% vs. 94.9%, 95.7%), and diagnostic accuracy (96.8% vs. 81.5%, 89.0%).

CONCLUSION

A second-generation intra-cycle motion correction algorithm for single-beat CCTA significantly improves image quality and diagnostic accuracy in patients with increased heart rate.

KEY POINTS

• A second-generation motion correction (MC2) algorithm can further improve the image quality of all coronary arteries than a first-generation motion correction (MC1). • MC2 algorithm can significantly reduce the number of false positive segments compared to standard and MC1 algorithm.

Reduction of Coronary Motion Artifacts in Prospectively Electrocardiography-Gated Coronary Computed Tomography Angiography Using Monochromatic Imaging at Various Energy Levels in Combination With a Motion Correction Algorithm on Single-Source Fast Tube Voltage Switching Dual-Energy Computed Tomography: A Phantom Experiment

OBJECTIVES

The aim of this study was to assess the effect of monochromatic imaging at various energy levels in combination with a motion correction algorithm (MCA) in single-source dual-energy coronary computed tomography angiography (CCTA) with fast switching of tube voltage on the reduction of coronary motion artifacts (CMA) in a phantom setting.

MATERIALS AND METHODS

Using this dual-energy computed tomography technique with a phantom comprising models of coronary vessels filled with contrast medium and pulsating at constant heart rates of 60 to 100 beats per minute, we reconstructed monochromatic images of CCTA obtained at 50 to 90 keV with and without use of MCA. Cardiac motion was modeled by simulating the in vivo time-volume curve of the left ventricle. Two independent readers graded CMA in 9 coronary segments using a 5-point scale (1, poor; 3 to 5, interpretable; 5, excellent). At each heart rate, we compared the average score of CMA between images obtained at 50 to 90 keV with and without use of MCA using Wilcoxon signed rank test, and we compared the score among images obtained at 50 to 90 keV with use of MCA using Kruskal-Wallis and post hoc tests. We also compared the percentages of image interpretability and improvement in image interpretability among images obtained at 50 to 90 keV with use of MCA.

RESULTS

With the use of MCA, the average score of CMA was significantly higher for images obtained at each energy level from 50 to 70 keV (P < 0.05) and was comparable at 80 and 90 keV, and it was comparable among those obtained at 50 to 70 keV. With its use, the percentages of image interpretability were similarly high at 50 to 70 keV at 60 to 80 beats per minute (78%-100%), and they were higher at 50 to 60 keV (72%-83%) than at 70 keV at 90 to 100 beats per minute (50%-56%). The percentages of improved image interpretability with MCA were similarly high at 50 to 70 keV at 60 to 80 beats per minute (56%-100%), and they were higher at 50 to 60 keV (62%-77%) than at 70 keV at 90 to 100 beats per minute (36%-43%). The percentages of image interpretability and improved image interpretability with MCA were insufficient at 80 and 90 keV.

CONCLUSIONS

Coronary motion artifacts were significantly reduced in images of monochromatic CCTA obtained at 50 to 70 keV in combination with MCA compared with those obtained without MCA, and the percentages of image interpretability and improved image interpretability with use of MCA were relatively high at 50 to 70 keV, and particularly at 50 to 60 keV, even at 90 to 100 beats per minute.

A whole-heart motion-correction algorithm: Effects on CT image quality and diagnostic accuracy of mechanical valve prosthesis abnormalities

BACKGROUND

We aimed to determine the effect of a whole-heart motion-correction algorithm (new-generation snapshot freeze, NG SSF) on the image quality of cardiac computed tomography (CT) images in patients with mechanical valve prostheses compared to standard images without motion correction and to compare the diagnostic accuracy of NG SSF and standard CT image sets for the detection of prosthetic valve abnormalities.

METHODS

A total of 20 patients with 32 mechanical valves who underwent wide-coverage detector cardiac CT with single-heartbeat acquisition were included. The CT image quality for subvalvular (below the prosthesis) and valvular regions (valve leaflets) of mechanical valves was assessed by two observers on a four-point scale (1 = poor, 2 = fair, 3 = good, and 4 = excellent). Paired t-tests or Wilcoxon signed rank tests were used to compare image quality scores and the number of diagnostic phases (image quality score≥3) between the standard image sets and NG SSF image sets. Diagnostic performance for detection of prosthetic valve abnormalities was compared between two image sets with the final diagnosis set by re-operation or clinical findings as the standard reference.

RESULTS

NG SSF image sets had better image quality scores than standard image sets for both valvular and subvalvular regions (P < 0.05 for both). The number of phases that were of diagnostic image quality per patient was significantly greater in the NG SSF image set than standard image set for both valvular and subvalvular regions (P < 0.0001). Diagnostic performance of NG SSF image sets for the detection of prosthetic abnormalities (20 pannus and two paravalvular leaks) was greater than that of standard image sets (P < 0.05).

CONCLUSION

Application of NG SSF can improve CT image quality and diagnostic accuracy in patients with mechanical valves compared to standard images.

Improvement of Image Quality and Diagnostic Performance by an Innovative Motion-Correction Algorithm for Prospectively ECG Triggered Coronary CT Angiography

Objective

To investigate the effect of a novel motion-correction algorithm (Snap-short Freeze, SSF) on image quality and diagnostic accuracy in patients undergoing prospectively ECG-triggered CCTA without administering rate-lowering medications.

Materials and Methods

Forty-six consecutive patients suspected of CAD prospectively underwent CCTA using prospective ECG-triggering without rate control and invasive coronary angiography (ICA). Image quality, interpretability, and diagnostic performance of SSF were compared with conventional multisegment reconstruction without SSF, using ICA as the reference standard.

Results

All subjects (35 men, 57.6 ± 8.9 years) successfully underwent ICA and CCTA. Mean heart rate was 68.8±8.4 (range: 50–88 beats/min) beats/min without rate controlling medications during CT scanning. Overall median image quality score (graded 1–4) was significantly increased from 3.0 to 4.0 by the new algorithm in comparison to conventional reconstruction. Overall interpretability was significantly improved, with a significant reduction in the number of non-diagnostic segments (690 of 694, 99.4% vs 659 of 694, 94.9%; P<0.001). However, only the right coronary artery (RCA) showed a statistically significant difference (45 of 46, 97.8% vs 35 of 46, 76.1%; P = 0.004) on a per-vessel basis in this regard. Diagnostic accuracy for detecting ≥50% stenosis was improved using the motion-correction algorithm on per-vessel [96.2% (177/184) vs 87.0% (160/184); P = 0.002] and per-segment [96.1% (667/694) vs 86.6% (601/694); P <0.001] levels, but there was not a statistically significant improvement on a per-patient level [97.8 (45/46) vs 89.1 (41/46); P = 0.203]. By artery analysis, diagnostic accuracy was improved only for the RCA [97.8% (45/46) vs 78.3% (36/46); P = 0.007].

Conclusion

The intracycle motion correction algorithm significantly improved image quality and diagnostic interpretability in patients undergoing CCTA with prospective ECG triggering and no rate control.

Current and Novel Imaging Techniques in Coronary CT

Multidetector coronary computed tomography (CT), which is widely performed to assess coronary artery disease noninvasively and accurately, provides excellent image quality. Use of electrocardiography (ECG)-controlled tube current modulation and low tube voltage can reduce patient exposure to nephrotoxic contrast media and carcinogenic radiation when using standard coronary CT with a retrospective ECG-gated helical scan. Various imaging techniques are expected to overcome the limitations of standard coronary CT, which also include insufficient spatial and temporal resolution, beam-hardening artifacts, limited coronary plaque characterization, and an inability to allow functional assessment of coronary stenosis. Use of a step-and-shoot scan, iterative reconstruction, and a high-pitch dual-source helical scan can further reduce radiation dose. Dual-energy CT can improve contrast medium enhancement and reasonably reduce the contrast dose when combined with noise reduction with the use of iterative reconstruction. High-definition CT can improve spatial resolution and diagnostic evaluation of small or peripheral coronary vessels and coronary stents. Dual-source CT and a motion correction algorithm can improve temporal resolution and reduce coronary motion artifacts. Whole-heart coverage with 320-detector CT and an intelligent boundary registration algorithm can eliminate stair-step artifacts. By decreasing beam hardening and enabling material decomposition, dual-energy CT is expected to remove or reduce the depiction of coronary calcification to improve intraluminal evaluation of calcified vessels and to provide detailed analysis of coronary plaque components and accurate qualitative and quantitative assessment of myocardial perfusion. Fractional flow reserve derived from coronary CT is a state-of-the-art noninvasive technique for accurately identifying myocardial ischemia beyond coronary CT. Understanding these techniques is important to enhance the value of coronary CT for assessment of coronary artery disease.