Improving image quality and resolution of coronary arteries in coronary computed tomography angiography by using high-definition scans and deep learning image reconstruction

Abstract

Background Coronary computed tomography angiography (CTA) has been increasingly used to identify the degree of coronary artery stenosis and plaque lesions in vessels. This study evaluated the feasibility of using high-definition (HD) scanning with high-level deep learning image reconstruction (DLIR-H) to improve the image quality and spatial resolution when imaging calcified plaques and stents in coronary CTA as compared to the standard definition (SD) reconstruction mode with adaptive statistical iterative reconstruction-V (ASIR-V). Methods A total of 34 patients (age 63.3±10.9 years; 55.88% female) with calcified plaques and/or stents who underwent coronary CTA in HD-mode were included in this study. Images were reconstructed with SD-ASIR-V, HD-ASIR-V, and HD-DLIR-H. Subjective image quality with image noise and clarity of vessels, calcifications, and stented lumens was evaluated by 2 radiologists using a 5-point scale. The kappa (κ) test was used to analyze the interobserver agreement. Objective image quality with image noise, signal-to-noise-ratio (SNR), and contrast-to-noise-ratio (CNR) was measured and compared. Image spatial resolution and beam-hardening artifacts (BHAs) were also evaluated using the calcification diameter and CT numbers in 3 points along the stented lumen (inside, at the proximal and distal ends just outside stent). Results There were 45 calcified plaques and 4 coronary stents. HD-DLIR-H images had the highest overall image quality score (4.50±0.63) with the lowest image noise (22.59±3.59 HU) and the highest SNR (18.30±4.88) and CNR (26.56±6.33), followed by SD-ASIR-V50% image quality score (4.06±2.49), image noise (35.02±8.09 HU), SNR (12.77±1.59), CNR(15.67±1.92) and HD-ASIR-V50% image quality score (3.90±0.64), image noise (57.7±12.03 HU), SNR (8.16±1.86), CNR (10.01±2.39). HD-DLIR-H images also had the smallest calcification diameter measurement (2.36±1.58 mm), followed by HD-ASIR-V50% (3.46±2.07 mm) and SD-ASIR-V50% (4.06±2.49 mm). HD-DLIR-H images had the closest CT value measurements for the 3 points along the stented lumen, indicating much less BHA. Interobserver agreement on the image quality assessment was good to excellent (HD-DLIR-H: κ value =0.783; HD-ASIR-V50%: κ value =0.789; SD-ASIR-V50%: κ value =0.671). Conclusions Coronary CTA with HD scan mode and DLIR-H significantly improves the spatial resolution for displaying calcifications and in-stent lumens while simultaneously reducing image noise.

Improved image quality in CT pulmonary angiography using deep learning-based image reconstruction

“…We applied DLIR to CTPA studies in suspected PE. Our results are in line with those that have been described for various cardiovascular CT applications including coronary CTA 19 – 23 , CT for planning of transcatheter aortic valve repair 24 , 25 , CT of the aorta 26 , head and neck CT angiography 27 and triple-rule-out CT 28 . In the field of thoracic imaging, several previous studies have investigated the value of DLIR with regards to pulmonary imaging and lung nodule detection.…”

“…Previously, DLIR has been shown to improve image denoising and increase image quality beyond the levels of achieved with iterative reconstruction techniques in various cardiovascular CT applications including coronary CTA 18 – 23 , CT for planning of transcatheter aortic valve repair 24 , 25 , CT of the aorta 26 , head and neck CT angiography 27 and triple-rule-out CT 28 . There are very limited data about DLIR in CTPA despite this being one of the most commonly performed cardiovascular CT examinations.…”

Effect of deep learning image reconstruction with high-definition standard scan mode on image quality of coronary stents and arteries

“…It has been demonstrated that CCTA reconstructed by different vendor techniques based on deep learning can achieve higher image quality than can traditional image reconstruction (FBP and IR) ( 23 - 25 ), but no previous studies have evaluated the effect of using specific DLIR algorithms on HD-standard scanned CCTA images. One recent study evaluated coronary artery images acquired with the HD-standard mode and the DLIR algorithm ( 26 ), but the sample size of the study was insufficiently large (only four stents were evaluated), and STND scan mode was not used for comparison. In contrast, our study evaluated 76 stents with a greater array of evaluation parameters and used the STND scan mode of comparison; in other words, our study further complemented and confirmed these findings.…”