New transluminal attenuation gradient derived from dynamic coronary CT angiography: diagnostic ability of ischemia detected by 13N-ammonia PET

Dynamic coronary CT Angiography-Estimated coronary flow in Non-Obstructive, Plaque-free coronary Arteries: Association with dyslipidemia and diabetes

Rationale and Objectives

In this study, we implemented dynamic coronary CT angiography (CCTA) in order to estimate the coronary flow rate in morphologically normal coronary arteries as well as to identify factors affecting the coronary flow rate.

Materials and Methods

We retrospectively enrolled 95 consecutively presenting patients without stenosis or plaque in their major coronary arteries on CCTA conducted with a 320-detector scanner (mean age, 57 years; 43 % men). Time-attenuation curves of the distal sites of the major coronary arteries and the aortic root were extracted from dynamic CCTA data. Coronary flow rate, an indicator of coronary blood flow, was calculated via a convolution-integration method integrating the two curves. Patients with dyslipidemia were divided according to the presence or absence of familial hypercholesterolemia (FH) as well as according to the receipt of statin therapy.

Results

We found that the coronary flow rate was statistically significantly lower in statin-naïve patients with dyslipidemia (n = 27, 0.56 ± 0.10) than in patients without dyslipidemia (n = 32, 0.64 ± 0.10, p = 0.0013). In FH (n = 26), the coronary flow rate was statistically significantly lower in statin-naïve patients (n = 7, 0.65 ± 0.08) than in those taking statins (n = 19, 0.72 ± 0.10, p = 0.0221). Coronary flow rate likewise exhibited a statistically significant negative correlation with hemoglobin A1c (Pearson r, −0.437; p = 0.0003), but no correlation with other coronary risk factors. The coronary flow rate was statistically significantly lower in patients with diabetes (n = 14, 0.55 ± 0.10) than in those without diabetes (n = 81, 0.61 ± 0.11, p = 0.0461).

Conclusion

We found a reduction in coronary flow rate in patients with statin-naive dyslipidemia and diabetes, even within morphologically normal coronary arteries.

Research Progress of Imaging Methods for Detection of Microvascular Angina Pectoris in Diabetic Patients

Diabetes is a complex metabolic disease characterized by hyperglycemia. Its complications are various, often involving the heart, brain, kidney, and other essential organs. At present, the number of diabetic patients in the world is growing day by day. The cardiovascular disease caused by diabetes has dramatically affected the quality of life of diabetic patients. It is the leading cause of death of diabetic patients. Diabetic patients often suffer from microvascular angina pectoris without obstructive coronary artery disease. Still, there are typical ECG ischemia and angina pectoris, that is, chest pain and dyspnea under exercise. Unlike obstructive coronary diseases, nitrate does not affect chest pain caused by coronary microvascular angina in most cases. With the increasing emphasis on diabetic microvascular angina, the need for accurate diagnosis of the disease is also increasing. We can use SPECT, PET, CMR, MCE, and other methods to evaluate coronary microvascular function. SPECT is commonly used in clinical practice, and PET is considered the gold standard for non-invasive detection of myocardial blood flow. This article mainly introduces the research progress of these imaging methods in detecting microvascular angina in diabetic patients.

Radiation dose for 320-row dose-modulated dynamic coronary CT angiography

OBJECTIVES

The area detector 320-row CT scanner, which can cover the whole heart in one rotation, can aid in reducing radiation exposure during electrocardiography (ECG)-gated coronary CT angiography (CCTA). Recently, researchers have proposed dose-modulated dynamic CCTA with a 320-row scanner for the detection of functional myocardial ischemia. In the present study, we compared and validated the radiation dose of this method with that of the standard CCTA method and the latest diagnostic reference levels (DRLs).

MATERIALS AND METHODS

The study included a total of 164 consecutive patients with suspected or known coronary artery disease (CAD) who underwent CCTA with a 320-row scanner. The patients were randomly divided into dynamic and standard CCTA groups, and the CT dose index (CTDIvol) and dose length product (DLP) calculated by the CT system were compared between the two protocols and with the latest DRL.

RESULTS

Standard and dynamic CCTA scans were performed in 77 and 87 patients, respectively. CTDIvol was significantly higher for standard CCTA than for dynamic CCTA (41 ± 35 mGy vs. 22 ± 7 mGy, p = 0.0014). DLP was also significantly higher for standard CCTA than for dynamic CCTA (864 ± 702 mGy × cm vs. 434 ± 106 mGy × cm, p < .0001). For standard scans, CTDIvol and DLP exceeded the 2020 DRL in Japan in 16% (12/77) and 17% (13/77) of cases, respectively. In contrast, rates for the dynamic scan were only 1% (1/87) for CTDIvol and 0% (0/87) for DLP.

CONCLUSION

The dose of radiation exposure during dynamic CCTA with a 320-row scanner does not exceed that of standard CCTA and is sufficient to meet the latest DRL. Thus, our results suggest that the method is safe from the perspective of radiation exposure.

Detection of 3D Arterial Centerline Extraction in Spiral CT Coronary Angiography

This paper presents an in-depth study and analysis of the 3D arterial centerline in spiral CT coronary angiography, and constructs its detection and extraction technique. The first time, the distance transform is used to complete the boundary search of the original figure; the second time, the distance transform is used to calculate the value of the distance transform of all voxels, and according to the value of the distance transform, unnecessary voxels are deleted, to complete the initial contraction of the vascular region and reduce the computational consumption in the next process; then, the nonwitnessed voxels are used to construct the maximum inner joint sphere model and find the skeletal voxels that can reflect the shape of the original figure. Finally, the skeletal lines were optimized on these initially extracted skeletal voxels using a dichotomous-like principle to obtain the final coronary artery centerline. Through the evaluation of the experimental results, the algorithm can extract the coronary centerline more accurately. In this paper, the segmentation method is evaluated on the test set data by two kinds of indexes: one is the index of segmentation result evaluation, including dice coefficient, accuracy, specificity, and sensitivity; the other is the index of clinical diagnosis result evaluation, which is to refine the segmentation result for vessel diameter detection. The results obtained in this paper were compared with the physicians' labeling results. In terms of network performance, the Dice coefficient obtained in this paper was 0.89, the accuracy was 98.36%, the sensitivity was 93.36%, and the specificity was 98.76%, which reflected certain advantages in comparison with the advanced methods proposed by previous authors. In terms of clinical evaluation indexes, by performing skeleton line extraction and diameter calculation on the results obtained by the segmentation method proposed in this paper, the absolute error obtained after comparing with the diameter of the labeled image was 0.382 and the relative error was 0.112, which indicates that the segmentation method in this paper can recover the vessel contour more accurately. Then, the results of coronary artery centerline extraction with and without fine branch elimination were evaluated, which proved that the coronary artery centerline has higher accuracy after fine branch elimination. The algorithm is also used to extract the centerline of the complete coronary artery tree, and the results prove that the algorithm has better results for the centerline extraction of the complete coronary vascular tree.