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

Novel motion correction algorithm improves diagnostic performance of CT fractional flow reserve

OBJECTIVES

This study aimed to investigate the diagnostic performance of computed tomography (CT) fractional flow reserve (CT-FFR) derived from standard images (STD) and images processed via first-generation (SnapShot Freeze, SSF1) and second-generation (SnapShot Freeze 2, SSF2) motion correction algorithms.

METHODS

151 patients who underwent coronary CT angiography (CCTA) and invasive coronary angiography (ICA)/FFR within 3 months were retrospectively included. CCTA images were reconstructed using an iterative reconstruction technique and then further processed through SSF1 and SSF2 algorithms. All images were divided into three groups: STD, SSF1, and SSF2. Obstructive stenosis was defined as a diameter stenosis of ≥ 50 % in the left main artery or ≥ 70 % in other epicardial vessels. Stenosis with an FFR of ≤ 0.8 or a diameter stenosis of ≥ 90 % (as revealed via ICA) was considered ischemic. In patients with multiple lesions, the lesion with lowest CT-FFR was used for patient-level analysis.

RESULTS

The overall quality score in SSF2 group (median = 3.67) was markedly higher than that in STD (median = 3) and SSF1 (median = 3) groups (P < 0.001). The best correlation (r = 0.652, P < 0.001) and consistency (mean difference = 0.04) between the CT-FFR and FFR values were observed in the SSF2 group. At the per-lesion level, CT-FFRSSF2 outperformed CT-FFRSSF1 in diagnosing ischemic lesions (area under the curve = 0.887 vs. 0.795, P < 0.001). At the per-patient level, the SSF2 group also demonstrated the highest diagnostic performance.

CONCLUSION

The SSF2 algorithm significantly improved CCTA image quality and enhanced its diagnostic performance for evaluating stenosis severity and CT-FFR calculations.

Motion artifact correction in cardiac CT using cross-phase temporospatial information and synergistic attention gate and spatial transformer sub-networks

Objectives.To improve quality of coronary CT angiography (CCTA) images using a generalizable motion-correction algorithm.Approach. A neural network with attention gate and spatial transformer (ATOM) was developed to correct coronary motion. Phantom and patient CCTA images (39 males, 32 females, age range 19-92, scan date 02/2020 to 10/2021) retrospectively collected from dual-source CT were used to create training, development, and testing sets corresponding to 140- and 75 ms temporal resolution, with 75 ms images as labels. To test generalizability, ATOM was deployed for locally adaptive motion-correction in both 140- and 75 ms patient images. Objective metrics were used to assess motion-corrupted and corrected phantom and patient images, including structural-similarity-index (SSIM), dice-similarity-coefficient (DSC), peak-signal-noise-ratio (PSNR), and normalized root-mean-square-error (NRMSE). In objective quality assessment, ATOM was compared with several baseline networks, including U-net, U-net plus attention gate, U-net plus spatial transformer, VDSR, and ResNet. Two cardiac radiologists independently interpreted motion-corrupted and -corrected images at 75 and 140 ms in a blinded fashion and ranked diagnostic image quality (worst to best: 1-4, no ties).Main results. ATOM improved quality metrics (p< 0.05) before/after correction: in phantom, SSIM 0.87/0.95, DSC 0.85/0.93, PSNR 19.4/22.5, NRMSE 0.38/0.27; in patient images, SSIM 0.82/0.88, DSC 0.88/0.90, PSNR 30.0/32.0, NRMSE 0.16/0.12. ATOM provided more consistent improvement of objective image quality, compared to the presented baseline networks. The motion-corrected images received better ranks than un-corrected at the same temporal resolution (p< 0.05): 140 ms images 1.65/2.25, and 75 ms images 3.1/3.2. The motion-corrected 75 ms images received the best rank in 65% of testing cases. A fair-to-good inter-reader agreement was observed (Kappa score 0.58).Significance. ATOM reduces motion artifacts, improving visualization of coronary arteries. This algorithm can be used to virtually improve temporal resolution in both single- and dual-source CT.

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.

Improved visualization of the coronary arteries using motion correction during vasodilator stress CT myocardial perfusion imaging

BACKGROUND

Vasodilator stress computed tomography perfusion (sCTP) imaging is complementary to coronary CT angiography (CCTA), used to determine the hemodynamic significance of coronary artery disease. However, it requires a separate image acquisition due to motion artifacts caused by higher heart rates during stress, resulting in increased iodine contrast dose and radiation. We sought to determine whether a novel motion correction algorithm applied to stress images would improve the visualization of the coronary arteries to potentially allow CCTA + sCTP evaluation in a single scan.

METHODS

28 patients referred for clinically indicated CCTA (iCT, Philips) underwent sCTP imaging (retrospective-gating with dose modulation; 100 kVp and 250 mA; 5.2 ± 4.3 mSv) after regadenoson (0.4 mg, Astellas). Stress images were reconstructed using standard filtered back-projection (FBP) and also processed to generate interaction-free coronary motion-compensated back-projection reconstructions (MCR). Each coronary artery from standard FBP and MCR images was viewed side-by-side by a reader blinded to the reconstruction technique, who graded severity of motion artifact by segment (scale 0-5, with 3 as the threshold for diagnostic quality) and to measure signal-to-noise and contrast-to-noise ratios (SNR, CNR).

RESULTS

Visualization scores were higher with MCR for all coronary segments, including 14/86 (16%) segments deemed as non-diagnostic on FBP images. SNR (7 ± 2) and CNR (15 ± 8) were unchanged by motion-correction (7 ± 3, p = 0.88 and 15 ± 5, p = 0.94, respectively).

CONCLUSIONS

MCR improves the visualization of coronary anatomy on sCTP images without degrading image characteristics. This algorithm is an important step towards the combined assessment of coronary anatomy and myocardial perfusion in a single scan, which will reduce study time, radiation exposure and contrast dose.

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.