Image quality in coronary computed tomography angiography: influence of adaptive statistical iterative reconstruction at various radiation dose levels

Potential increase in radiation-induced DNA double-strand breaks with higher doses of iodine contrast during coronary CT angiography

Purpose

To investigate the contrast media iodine dose dependency of radiation‐induced DNA double‐strand breaks (DSBs) during a coronary computed tomography angiography (CCTA) scan.

Methods

This prospective patient study was approved by the ethical committee. Between November 2018 and July 2019, 50 patients (31 males and 19 females, mean age 64 years) were included in the study, 45 CCTA and five noncontrast‐enhanced (NCE) cardiac computed tomography (CT) patients. A single‐heartbeat scan protocol with a patient‐tailored contrast media injection protocol was used, administering a patient‐specific iodine dose. DNA double‐strand breaks were quantified using a γH2AX foci assay on peripheral blood lymphocytes. The net amount of γH2AX/cell was normalized to the individual patient CT dose by the size‐specific dose estimate (SSDE). Correlation between the administered and blood‐iodine dose and the SSDE normalized amount of DNA DSBs was investigated using a Pearson correlation test.

Results

CCTA patients were scanned with a mean CTDI_vol of 10.6 ± 5.6 mGy, corresponding to a mean SSDE of 11.3 ± 5.3 mGy while the NCE cardiac CT patients were scanned with a mean CTDI_vol of 6.00 ± 1.8 mGy, corresponding to a mean SSDE of 6.6 ± 2.7 mGy. The administered iodine dose ranged from 16.5 to 34.0 gI in the CCTA patients, resulting in a blood‐iodine dose range from 5.1 to 15.0 gI in the exposed blood volume. A significant linear relationship (r = 0.79, p‐value < 0.001) was observed between the blood iodine dose and SSDE normalized radiation‐induced DNA DSBs. A similar significant linear relationship (r = 0.62, p‐value < 0.001) was observed between the administered iodine dose and SSDE normalized radiation‐induced DNA DSBs.

Conclusions

This study shows that contrast media iodine dose increases the level of radiation‐induced DNA DSBs in peripheral blood lymphocytes in a linear dose‐dependent manner with CCTA. Importantly, the level of DNA DSBs can be reduced by lowering the administered iodine dose.

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.

State of the art of coronary computed tomography angiography

OBJECTIVES

The aim of this paper is to evaluate contrast media (CM) bolus geometry and opacification patterns in the coronary arteries with particular focus on patient, scanner and safety considerations during coronary computed tomography angiography (CCTA).

KEY FINDINGS

The rapid evolution of computed tomography (CT) technology has seen this imaging modality challenge conventional coronary angiography in the evaluation of coronary artery disease. Increases in spatial and temporal resolutions have enabled CCTA to become the modality of choice when evaluating the coronary vascular tree as an alternative in the diagnostic algorithm for acute chest pain. However, these new technologic improvements in scanner technology have imposed new challenges for the optimisation of CM delivery and image acquisition strategies.

CONCLUSION

Understanding basic CM-imaging principles is essential for designing optimal injection protocols according to each specific clinical scenario, independently of scanner technology.

IMPLICATIONS FOR PRACTICE

With rapid advances in CT scanner technology including faster scan acquisitions, the risk of poor opacification of coronary vasculature increases significantly. Therefore, awareness of CM delivery protocols is paramount to consistently provide optimal image quality at a low radiation dose.