Impact of Knowledge-Based Iterative Model Reconstruction on Image Quality and Hemodynamic Parameters in Dynamic Myocardial Computed Tomography Perfusion Using Low-Tube-Voltage Scan: A Feasibility Study.

OBJECTIVE: Knowledge-based iterative model reconstruction (IMR) yields diagnostically acceptable image quality in low-dose static computed tomography (CT). We aimed to evaluate the feasibility of IMR in dynamic myocardial computed tomography perfusion (CTP). METHODS: We enrolled 24 patients who underwent stress dynamic CTP using a 256-slice CT. Images were reconstructed using filtered back projection (FBP), hybrid IR, and IMR. Image quality and hemodynamic parameters were compared among three algorithms. RESULTS: Qualitative image quality and contrast-to-noise ratio were significantly higher by IMR than by FBP or hybrid IR (visual score: 4.1 vs. 3.0 and 3.5; contrast-to-noise ratio: 12.4 vs. 6.6 and 8.4; P < 0.05). No significant difference was observed among algorithms in CTP-derived myocardial blood flow (1.68 vs. 1.73 and 1.70 mL/g/min). CONCLUSIONS: The use of knowledge-based iterative model reconstruction improves image quality without altering hemodynamic parameters in low-dose dynamic CTP, compared with FBP or hybrid IR.

Late iodine enhancement computed tomography with image subtraction for assessment of myocardial infarction.

OBJECTIVE: To evaluate the feasibility of image subtraction in late iodine enhancement CT (LIE-CT) for assessment of myocardial infarction (MI). METHODS: A comprehensive cardiac CT protocol and late gadolinium enhancement MRI (LGE-MRI) was used to assess coronary artery disease in 27 patients. LIE-CT was performed after stress CT perfusion (CTP) and CT angiography. Subtraction LIE-CT was created by subtracting the mask volume of the left ventricle (LV) cavity from the original LIE-CT using CTP dataset. The %MI volume was quantified as the ratio of LIE to entire LV volume, and transmural extent (TME) of LIE was classified as 0%, 1-24%, 25-49%, 50-74% or 75-100%. These results were compared with LGE-MRI using the Spearman rank test, Bland-Altman method and chi-square test. RESULTS: One hundred twenty-five (29%) of 432 segments were positive on LGE-MRI. Correlation coefficients for original and subtraction LIE-CT to LGE-MRI were 0.79 and 0.85 for %MI volume. Concordances of the 5-point grading scale between original and subtraction LIE-CT with LGE-MRI were 75% and 84% for TME; concordance was significantly improved using the subtraction technique (p <0.05). CONCLUSION: Subtraction LIE-CT allowed more accurate assessment of MI extent than the original LIE-CT. KEY POINTS: • Subtraction LIE-CT allows for accurate assessment of the extent of myocardial infarction. • Subtraction LIE-CT shows a close correlation with LGE-MRI in %MI volume. • Subtraction LIE-CT has significantly higher concordance with TME assessment than original LIE-CT.

Coronary computed tomography angiography for clinical practice.

Coronary artery disease (CAD) is a common condition caused by the accumulation of atherosclerotic plaques. It can be classified into stable CAD or acute coronary syndrome. Coronary computed tomography angiography (CCTA) has a high negative predictive value and is used as the first examination for diagnosing stable CAD, particularly in patients at intermediate-to-high risk. CCTA is also adopted for diagnosing acute coronary syndrome, particularly in patients at low-to-intermediate risk. Myocardial ischemia does not always co-exist with coronary artery stenosis, and the positive predictive value of CCTA for myocardial ischemia is limited. However, CCTA has overcome this limitation with recent technological advancements such as CT perfusion and CT-fractional flow reserve. In addition, CCTA can be used to assess coronary artery plaques. Thus, the indications for CCTA have expanded, leading to an increased demand for radiologists. The CAD reporting and data system (CAD-RADS) 2.0 was recently proposed for standardizing CCTA reporting. This RADS evaluates and categorizes patients based on coronary artery stenosis and the overall amount of coronary artery plaque and links this to patient management. In this review, we aimed to review the major trials and guidelines for CCTA to understand its clinical role. Furthermore, we aimed to introduce the CAD-RADS 2.0 including the assessment of coronary artery stenosis, plaque, and other key findings, and highlight the steps for CCTA reporting. Finally, we aimed to present recent research trends including the perivascular fat attenuation index, artificial intelligence, and the advancements in CT technology.

A Novel Quantitative Parameter for Static Myocardial Computed Tomography: Myocardial Perfusion Ratio to the Aorta.

We evaluated the feasibility of myocardial perfusion ratio to the aorta (MPR) in static computed tomography perfusion (CTP) for detecting myocardial perfusion abnormalities assessed by single-photon emission computed tomography (SPECT). Twenty-five patients with suspected coronary artery disease who underwent dynamic CTP and SPECT were retrospectively evaluated. CTP images scanned at a sub-optimal phase for detecting myocardial perfusion abnormalities were selected from dynamic CTP images and used as static CTP images in the present study. The diagnostic accuracy of MPR derived from static CTP was compared to those of visual assessment and conventional quantitative parameters such as myocardial CT attenuation (HU) and transmural perfusion ratio (TPR). The area under the curve of MPR (0.84; 95% confidence interval [CI], 0.76−0.90) was significantly higher than those of myocardial CT attenuation (0.73; 95% CI, 0.65−0.79) and TPR (0.76; 95% CI, 0.67−0.83) (p < 0.05). Sensitivity and specificity were 67% (95% CI, 54−77%) and 90% (95% CI, 86−92%) for visual assessment, 51% (95% CI, 39−63%) and 86% (95% CI, 82−89%) for myocardial CT attenuation, 63% (95% CI, 51−74%) and 84% (95% CI, 80−88%) for TPR, and 78% (95% CI, 66−86%) and 84% (95% CI, 80−88%) for MPR, respectively. MPR showed higher diagnostic accuracy for detecting myocardial perfusion abnormality compared with myocardial CT attenuation and TPR.

Clinical application of four-dimensional noise reduction filtering with a similarity algorithm in dynamic myocardial computed tomography perfusion imaging.

We aimed to evaluate the effects of four-dimensional noise reduction filtering using a similarity algorithm (4D-SF) on the image quality and hemodynamic parameter of dynamic myocardial computed tomography perfusion (CTP). Sixty-eight patients who underwent dynamic myocardial CTP for the assessment of coronary artery disease were enrolled. Dynamic CTP was performed using a 320-row CT with low tube voltage scan (80 kVp). Two different datasets of dynamic CTP were reconstructed using iterative reconstruction (IR) alone and a combination of IR and 4D-SF. Qualitative (5-grade scale) and quantitative image quality scores were assessed, and the CT-derived myocardial blood flow (CT-MBF) was quantified. These results were compared between the two different CTP images. The qualitative image quality in CTP images reconstructed with IR and 4D-SF was significantly higher than that with IR alone (noise score: 4.7 vs. 3.4, p < 0.05). The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in CTP images reconstructed with IR and 4D-SF were significantly higher than those with IR alone (SNR: 20.6 vs. 9.7; CNR: 7.9 vs. 3.9, respectively; p < 0.05). There was no significant difference in mean CT-MBF between the two sets of CTP images (3.01 vs. 3.03 mL/g/min, p = 0.1081). 4D-SF showed incremental value in improving image quality in combination with IR without altering CT-MBF quantification in dynamic myocardial CTP imaging with a low tube potential.