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The Influence of Iterative Reconstruction Technique on the Diagnosis of Coronary Artery Calcification

Objectives: This study aimed to assess the impact of iterative reconstruction (IR) algorithms for the evaluation of coronary artery calcification (CAC) in terms of image quality and subjective diagnostic performance. Methods: This study was performed in a single center and written informed consent was obtained from all patients. Thirty-one consecutive patients (26 men/5 women) underwent CT calcium score to rule out CAC. Image data were reconstructed with both; filtered back projection (FBP) and different levels of IR algorithms. Both the qualitative and quantitative image quality and subjective diagnostic performance were compared; Agatston scores and calcium density were measured for a total of 100 coronary arteries. Results: Quantitatively; image noise was substantially reduced with high levels of IR reflecting high significances of noise level (p < 0.001). In terms of subjective diagnostic performance, it was observed with increased IR levels; 49% of coronary arteries showed decrease, 14% showed increase, 32% were constant and 5% of coronary arteries showed fluctuation in total Agatston scores. Certain Agatston scores were not detected in coronary arteries in some levels of IR algorithms. Conclusions: IR resulted in substantial noise reduction and improved in both signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Higher levels of IR might lead to disappearance or underestimation of detectable calcium in coronary arteries with low calcium burden. Iterative reconstruction technique should be used with caution for better calcium quantification.