Low-dose dynamic myocardial perfusion CT image reconstruction using pre-contrast normal-dose CT scan induced...

Area of Science:

• Medical Imaging
• Radiology
• Cardiovascular Imaging

Background:

• Dynamic myocardial perfusion CT (DMP-CT) offers quantitative functional data for coronary artery disease (CAD) diagnosis and risk stratification.
• Current DMP-CT protocols may involve high radiation doses, posing a clinical challenge.
• Accurate calculation of myocardial perfusion hemodynamic parameter (MPHP) maps is crucial for effective CAD assessment.

Purpose of the Study:

• To develop a novel low-dose CT acquisition and image reconstruction method for DMP-CT.
• To improve image quality and reduce radiation exposure in DMP-CT while maintaining diagnostic accuracy.
• To enhance the calculation of MPHP maps for better CAD diagnosis.

Main Methods:

• Development of a penalized weighted least-squares (PWLS) criterion with pre-contrast normal-dose scan induced structure tensor total variation (ndiSTV) regularization.
• Exploitation of spatial-temporal structure information and higher-order derivatives for enhanced denoising.
• Application of an optimization algorithm based on the split-Bregman approach for objective function minimization.
• Validation using modified dynamic XCAT phantom and preclinical porcine datasets.

Main Results:

• The proposed PWLS-ndiSTV approach demonstrated significant noise-induced artifact mitigation.
• Improved preservation of edge details in low-mAs DMP-CT images was observed.
• Accurate calculation of MPHP maps was achieved, outperforming existing methods.
• The method enables high-quality DMP-CT with reduced radiation dose.

Conclusions:

• The PWLS-ndiSTV method offers a promising solution for low-dose DMP-CT imaging.
• This technique enhances image quality and accuracy for CAD diagnosis and risk stratification.
• The approach effectively reduces radiation exposure while preserving essential diagnostic information.