Evaluation of an integrated 3D-printed phantom for coronary CT angiography using iterative reconstruction algorithm.

Area of Science:

• Medical Imaging Physics
• Radiological Sciences
• Biomedical Engineering

Background:

• 3D-printed imaging phantoms are increasingly utilized for computed tomography (CT) dose optimization and image quality analysis.
• Evaluating novel reconstruction algorithms with advanced phantoms is crucial for advancing diagnostic imaging protocols.

Purpose of the Study:

• To assess the efficacy of an integrated 3D-printed cardiac phantom for evaluating iterative reconstruction (IR) algorithms.
• To analyze image quality metrics in coronary CT angiography (CCTA) protocols using varying IR strengths and radiation doses.

Main Methods:

• A 3D-printed cardiac insert phantom was incorporated into a chest phantom and scanned using a 16-slice CT scanner.
• Coronary CT angiography (CCTA) protocols were performed at 120 kVp with tube currents of 300, 200, 100, and 50 mA.
• Image datasets were reconstructed using filtered back projection (FBP) and three strengths of an iterative reconstruction (IR) algorithm.

Main Results:

• Reduced radiation dose significantly increased image noise and decreased signal-to-noise ratio (SNR) and contrast-noise ratio (CNR) for FBP.
• Filtered back projection (FBP) at the lowest dose (50 mA) exhibited the highest noise and poorest SNR/CNR.
• The strongest iterative reconstruction (IR) algorithm (AIDR3D_strong) demonstrated the lowest image noise, with excellent SNR and CNR across dose levels.

Conclusions:

• Iterative reconstruction (IR) algorithms, particularly at higher strengths, significantly reduce image noise, thereby enhancing SNR and CNR compared to FBP.
• The integrated 3D-printed phantom is a valuable tool for CT dose optimization and image quality assessment in CCTA.
• This phantom-based approach supports the development and validation of advanced reconstruction techniques for improved CCTA protocols.