Coronary artery plaques: cardiac CT with model-based and adaptive-statistical iterative reconstruction technique

Area of Science:

• Cardiovascular Imaging
• Radiology
• Medical Physics

Background:

• Coronary artery plaque visualization is crucial for diagnosing cardiovascular disease.
• Current CT angiography reconstruction techniques like filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASIR) have limitations in image quality.
• Model based iterative reconstruction (MBIR) offers potential for enhanced image reconstruction.

Purpose of the Study:

• To compare the image quality of coronary artery plaque visualization using CT angiography reconstructed with FBP, ASIR, and MBIR.
• To evaluate qualitative and quantitative image quality parameters, including image noise and contrast-to-noise ratio (CNR).

Main Methods:

• Three ex vivo human hearts were imaged using CT.
• Coronary artery images were reconstructed using FBP, ASIR, and MBIR techniques.
• Co-registered cross-sectional images were assessed for image quality by blinded readers.

Main Results:

• MBIR reconstruction resulted in excellent overall image quality in 26% of cases, significantly outperforming ASIR (4%) and FBP (13%).
• MBIR demonstrated significant noise reduction compared to ASIR and FBP.
• MBIR achieved a higher contrast-to-noise ratio (CNR) (44±19) compared to ASIR (29±15) and FBP (26±9).

Conclusions:

• MBIR significantly enhances coronary artery plaque visualization in CT angiography.
• MBIR improves image quality by reducing noise and increasing CNR.
• These advancements may enable improved plaque detection and potential radiation dose reduction.