Objective evaluation of improved image quality with application of novel noise reduction filter in dynamic myocardial CT perfusion

Funding Acknowledgements Type of funding sources: None. Background Dynamic myocardial CT perfusion (CTP) is a non-invasive imaging technique able to depict cardiac ischemia. It is expected that the application of a new dynamic perfusion image noise reducing filter, the similarity filter (4DSF) would improve the image quality of CTP, resulting in clear visualization of perfusion deficits and hypo-perfused tissue and allowing for a substantial reduction in the radiation dose in dynamic myocardial CTP. Purpose To evaluate image quality before and after the application of a novel noise reducing filter on dynamic myocardial CT perfusion images reconstructed with deep learning-based algorithm. Methods The image datasets of patients with stable chest pain at intermediate risk of cardiovascular disease, who underwent stress dynamic CTP scanning as clinically indicated were retrospectively collected. The images were acquired with a 320-slice CT system, reconstructed using a deep learning-based algorithm (8 mm slice thickness) and filtered with the 4DSF. For each case, the signal-to-noise ratio (SNR) and the contrast-to-noise ratio (CNR) in six regions-of-interest (ROIs, 33-38 mm2) were computed, before and after filtering. The signal ROIs were located midventricular, in both four-chamber and short-axis views in the left ventricle blood pool, and the background ROIs in the cardiac septum and lateral wall. Differences in the SNR and CNR values were compared using paired t-tests. Results As a part of an ongoing study, twenty five cases were analysed to date. The following results (means for AiCE and AiCE + 4DSF, and corresponding p-values) were obtained in short axis view: septum SNR: 3.46 vs 6.25 (p = 0.007), lateral wall SNR: 3.66 vs 6.52 (p = 0.000), septum CNR: 13.35 vs 23.85 (p = 0.005), lateral wall CNR: 13.16 vs 23.57 (p = 0.010); and in four-chamber view: septum SNR: 3.67 vs 7.44 (p = 0.003), lateral wall SNR: 3.97 vs 7.65 (p = 0.001) and septum CNR: 13.92 vs 29.97 (p = 0.016), lateral wall CNR: 13.63 vs 29.75 (p = 0.018). All results are statistically significant. Conclusions We confirmed that the similarity filter decreases noise and therefore improves the objective image quality in both short axis and four chamber views. Therefore, the improved tissue texture depiction and improved visualization of perfusion defects may facilitate detection of ischemia and lead to reduction in radiation dose necessary for dynamic CTP, maintaining image quality. Abstract Figure. Region-of-interests (ROIs) location