Image quality and sharpness improvement in coronary CT angiography using a deep-learning super-resolution reconstruction algorithm: a phantom study
Author Block: T. W. Holmes1, S. Sharma2, S. Ross2, K. Schultz2, P. Gleason1, J. Schuzer2, Z. Yu2, R. Thompson2, A. Pourmorteza1; 1Atlanta, GA/US, 2Vernon Hills, IL/US
Purpose: The purpose of this study was to investigate the performance of a super-resolution deep-learning-based reconstruction (DLR) algorithm named precision image quality engine (PIQE) developed for cardiac CT against two clinical reconstruction algorithms: adaptive iterative dose reduction (AIDR) and high-resolution DLR (AiCE).
Methods or Background: We 3D-printed inserts with microfluidic channels (d= 0.25 - 3.5 mm) with stents and calcified plaques embedded and filled with dilutions of iodinated contrast agent. The inserts were placed inside a 12-cm diameter water tank and scanned on a clinical CT scanner with prospective ECG-gating: 120 kVp, exposure: 25, 50, 250, and 400 mAs. Images were reconstructed with matched parameters using AIDR, AiCE, and PIQE: 512 x 512 matrix, 0.312 x 0.312 x 0.5 mm3 voxel size. PIQE images were also reconstructed with a 1024 x 1024 matrix and 0.156 x 0.156 x 0.5 mm3. We evaluated CT number stability, contrast-to-noise ratio (CNR), and image sharpness as a function of radiation dose.
Results or Findings: CT number deviations from the 400 mAs baseline were measured in iodine, water, and fat inserts and were in the [-1.1 3.1], [-1.1, 3.4], and [-2.2 0.26] for AIDR, AiCE, and PIQE, respectively. CNRs between iodine, water, fat (soft plaque), and calcium (hard plaque), were between 36% to 97% higher for PIQE compared to AIDR, with maximum CNR improvement observed in the lowest dose (25 mAs) scans. AiCE images showed a 0% - 37% increase in CNR in low-dose scans (25,50 mAs), however, their CNR was between 11% to 27% lower for the higher-dose scans (400,250 mAs), compared to AIDR. MTF cutoff at 10% was 8.98, 10.68, 10.44, and 13.61 lp/cm for AIDR, AiCE, PIQE, and PIQE1024 respectively.
Conclusion: Overall, DLR algorithms improved CNR and image sharpness between 16%-18% at normal resolution voxel size. Furthermore, PIQE improved image sharpness by 51% when reconstructed at high-resolution voxel size.
Limitations: More experiments mimicking different patient sizes are warranted.
Funding for this study: This study was sponsored research agreement with Canon Medical Research USA.
Has your study been approved by an ethics committee? Not applicable
Ethics committee - additional information: No information provided by the submitter.