Relationship between pericoronary adipose tissue attenuation value and image reconstruction parameters

Area of Science:

• Cardiovascular Imaging
• Radiology
• Medical Physics

Background:

• Pericoronary adipose tissue (PCAT) characterization is crucial for cardiovascular risk assessment.
• Accurate measurement of PCAT mean attenuation (PCAT_MA) is essential for reliable risk stratification.
• Image reconstruction parameters can influence quantitative CT measurements.

Purpose of the Study:

• To investigate the relationship between PCAT_MA and image reconstruction parameters in CT coronary angiography.
• To determine the impact of adaptive statistical iterative reconstruction-veo (ASIR-V) percentage, kernel type, and slice thickness on PCAT_MA.

Main Methods:

• 198 patients undergoing CT coronary angiography at 100 kVp or 120 kVp were analyzed.
• Scans were reconstructed using varying ASIR-V percentages, kernels (soft, standard, detail, bone), and slice thicknesses (0.625 mm, 1.25 mm).
• PCAT_MA was calculated for the three main coronary arteries using dedicated software, with statistical analysis including linear regression and ANOVA.

Main Results:

• PCAT_MA showed a strong positive linear correlation with ASIR-V percentage (R squared >0.99).
• Different reconstruction kernels significantly affected PCAT_MA (P < 0.001), with notable differences between standard and bone kernels.
• Slice thickness variations (0.625 mm vs. 1.25 mm) also resulted in statistically significant differences in PCAT_MA for major coronary arteries (P < 0.001).

Conclusions:

• PCAT_MA measurements are linearly dependent on the ASIR-V percentage used during image reconstruction.
• Reconstruction kernel and slice thickness are significant factors influencing PCAT_MA values, particularly with sharper kernels.
• Optimizing these parameters is critical for accurate and reproducible PCAT_MA assessment in clinical practice.