Feasibility of Four-Dimensional Similarity Filter For Radiation Dose Reduction in Dynamic Myocardial Computed Tomography Perfusion Imaging

Purpose: We aimed to evaluate the impact of four-dimensional noise reduction filtering using a similarity algorithm (4D-SF) on image noise during dynamic myocardial computed tomography perfusion (CTP) to simulate the reduction of radiation dose.Methods: A total of 43 patients who underwent dynamic myocardial CTP using 320-row CT were included in the study. The original images were reconstructed using iterative reconstruction (IR); three different CTP datasets with simulated noise, which corresponded to 25%, 50%, and 75% reduction of the original dose (= 300mA), were reconstructed using a combination of IR and 4D-SF. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed, and CT-derived myocardial blood flow (CT-MBF) was quantified. The results were compared between the original and simulated images with radiation dose reduction.Results: The original, 25%-, 50%-, and 75%-dose reduced images with 4D-SF showed an SNR of 8.3 (6.5–10.2), 16.5 (11.9–21.7), 15.6 (11.0–20.1), and 12.8 (8.8–18.1) and a CNR of 4.4 (3.2–5.8), 6.7 (4.6–10.3), 6.6 (4.3–10.1), and 5.5 (3.5–9.1), respectively. Compared to the original images, the 25%-, 50%-, and 75%-dose reduced-simulated images showed significant improvement in both SNR and CNR with 4D-SF. There was no significant difference in CT-MBF between the original and 25%- or 50%-dose reduced-simulated images with 4D-SF, however, there was a significant difference in CT-MBF between the original and 75%-dose reduced-simulated images.Conclusion: 4D-SF has the potential to reduce the radiation dose associated with dynamic myocardial CTP imaging by half, without impairing the robustness of MBF quantification.