Coronary Artery Plaque Burden in Smokers and Never-Smokers: Quantification With Cardiac CT

Meinel, Felix G.

doi:10.1016/j.acra.2019.08.017

Cited by 1 publication

(1 citation statement)

References 14 publications

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“…Echocardiography can not only make anatomical diagnosis of cardiovascular diseases but also make functional diagnosis. It can observe the intracardiac movement, ventricular wall thickness, and the connection of cardiac great vessels from any angle, but it is seriously affected by factors such as sound, visual field, resolution, and operator experience [8][9][10]. Although MRI has high temporal resolution and soft tissue resolution, it has poor effect on coronary artery imaging due to the thin diameter of coronary artery, tortuous shape, and more adipose tissue in adjacent parts [11,12].…”

Section: Introductionmentioning

confidence: 99%

Effect of Calcification Based on Computer-Aided System on CT-Fractional Flow Reserve in Diagnosis of Coronary Artery Lesion

Xiao

Gao

et al. 2022

Computational and Mathematical Methods in Medicine

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This study was to analyze the diagnostic value of coronary computed tomography angiography (CCTA) and fractional flow reserve (FFR) based on computer-aided diagnosis (CAD) system for coronary lesions and the possible impact of calcification. 80 patients who underwent CCTA and FFR examination in hospital were selected as the subjects. The FFR value of 0.8 was used as the dividing line and divided into the ischemic group ( FFR ≤ 0.8 ) and nonischemic group ( FFR > 0.8 ). The basic data and imaging characteristics of patients were analyzed. The maximum diameter stenosis rate (MDS %), maximum area stenosis rate (MAS %), and napkin ring sign (NRS) in the ischemic group were significantly lower than those in the nonischemic group ( P < 0.05 ). Remodeling index (RI) and eccentric index (EI) compared with the nonischemic group had no significant difference ( P > 0.05 ). The total plaque volume (TPV), total plaque burden (TPB), calcified plaque volume (CPV), lipid plaque volume (LPV), and lipid plaque burden (LPB) in the ischemic group were significantly different from those in the non-ischemic group ( P < 0.05 ). MAS % had the largest area under curve (AUC) for the diagnosis of coronary myocardial ischemia (0.74), followed by MDS % (0.69) and LPV (0.68). CT-FFR had high diagnostic sensitivity, specificity, accuracy, truncation value, and AUC area data for patients in the ischemic group and nonischemic group. The diagnostic sensitivity, specificity, accuracy, cutoff value, and AUC area data of CT-FFR were higher in the ischemic group (89.93%, 92.07%, 95.84%, 60.51%, 0.932) and nonischemic group (93.75%, 90.88%, 96.24%, 58.22%, 0.944), but there were no significant differences between the two groups ( P > 0.05 ). In summary, CT-FFR based on CAD system has high accuracy in evaluating myocardial ischemia caused by coronary artery stenosis, and within a certain range of calcification scores, calcification does not affect the diagnostic accuracy of CT-FFR.

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