Javascript must be enabled to continue!
Diagnostic efficacy of CCTA and CT-FFR based on risk factors for myocardial ischemia
View through CrossRef
Abstract
Background
Coronary artery coronary computed tomography angiography (CCTA) can observe the degree of coronary artery stenosis and fractional flow reserve (FFR) can diagnose hemodynamic abnormalities caused by coronary artery stenosis. However, noninvasive imaging examination that can both observe the above two methods at the same time has not yet been elucidated.
Objective
To investigate the diagnostic efficacy of CCTA and computed tomography-derived fractional flow reserve (CT-FFR) based on different risk factors for myocardial ischemia.
Methods
Patients undergoing CCTA in our hospital from August 18, 2020 to April 28, 2021 were randomly selected, and the data were subjected to CT-FFR analysis. Vascular characteristics were measured, including total plaque volume, calcified plaque volume, non-calcified plaque volume, plaque length, and lumen stenosis, and the patients were categorized into a non-ischemia group (FFR > 0.8) and an ischemia group (FFR ≤ 0.8). Plaque characteristics were compared between the two groups, and logistic regression analysis was employed to explore the correlations between plaque characteristics and ischemic lesions.
Results
From a total of 122 patients enrolled in the study, there were 218 vascular branches with FFR > 0.8 and 174 vascular branches with FFR ≤ 0.8. There were significant group differences in total plaque volume, calcified plaque volume, plaque length, and lumen stenosis > 50% (n). The obtained data were as follows: non-ischemic group 10.57 (4.80, 259.65), ischemic group 14.87 (3.39, 424.45), Z = 9.772, p = 0.002, non-ischemic group 10.57 (0, 168.77), ischemic group 14.87 (0, 191.00), Z = 2.503, p ≤ 0.001), non-ischemic group 8.17 (37.05, 40.53), ischemic group 8.38 (56.66, 86.47), Z = 5.923, p = 0.016, and lumen stenosis > 50%, non-ischemic group 46, ischemic group 90, x2 = 14.77, p ≤ 0.001. The regression analysis results indicated that total plaque volume, calcified plaque volume, plaque length and lumen stenosis > 50% were risk factors for myocardial ischemia, with ORs and p values of (2.311, p = 0.002), (1.021, p = 0.004), (2.159, p < 0.001), and (0.181, p < 0.001), respectively.
Conclusion
Total plaque volume, calcified plaque volume, plaque length and lumen stenosis > 50% are predictors for myocardial ischemia. Coronary artery CCTA combined with CT-FFR could simultaneously observe the anatomical stenosis and evaluate myocardial blood supply at the functional level. Thus, myocardial ischemia could be better diagnosed.
Springer Science and Business Media LLC
Title: Diagnostic efficacy of CCTA and CT-FFR based on risk factors for myocardial ischemia
Description:
Abstract
Background
Coronary artery coronary computed tomography angiography (CCTA) can observe the degree of coronary artery stenosis and fractional flow reserve (FFR) can diagnose hemodynamic abnormalities caused by coronary artery stenosis.
However, noninvasive imaging examination that can both observe the above two methods at the same time has not yet been elucidated.
Objective
To investigate the diagnostic efficacy of CCTA and computed tomography-derived fractional flow reserve (CT-FFR) based on different risk factors for myocardial ischemia.
Methods
Patients undergoing CCTA in our hospital from August 18, 2020 to April 28, 2021 were randomly selected, and the data were subjected to CT-FFR analysis.
Vascular characteristics were measured, including total plaque volume, calcified plaque volume, non-calcified plaque volume, plaque length, and lumen stenosis, and the patients were categorized into a non-ischemia group (FFR > 0.
8) and an ischemia group (FFR ≤ 0.
8).
Plaque characteristics were compared between the two groups, and logistic regression analysis was employed to explore the correlations between plaque characteristics and ischemic lesions.
Results
From a total of 122 patients enrolled in the study, there were 218 vascular branches with FFR > 0.
8 and 174 vascular branches with FFR ≤ 0.
8.
There were significant group differences in total plaque volume, calcified plaque volume, plaque length, and lumen stenosis > 50% (n).
The obtained data were as follows: non-ischemic group 10.
57 (4.
80, 259.
65), ischemic group 14.
87 (3.
39, 424.
45), Z = 9.
772, p = 0.
002, non-ischemic group 10.
57 (0, 168.
77), ischemic group 14.
87 (0, 191.
00), Z = 2.
503, p ≤ 0.
001), non-ischemic group 8.
17 (37.
05, 40.
53), ischemic group 8.
38 (56.
66, 86.
47), Z = 5.
923, p = 0.
016, and lumen stenosis > 50%, non-ischemic group 46, ischemic group 90, x2 = 14.
77, p ≤ 0.
001.
The regression analysis results indicated that total plaque volume, calcified plaque volume, plaque length and lumen stenosis > 50% were risk factors for myocardial ischemia, with ORs and p values of (2.
311, p = 0.
002), (1.
021, p = 0.
004), (2.
159, p < 0.
001), and (0.
181, p < 0.
001), respectively.
Conclusion
Total plaque volume, calcified plaque volume, plaque length and lumen stenosis > 50% are predictors for myocardial ischemia.
Coronary artery CCTA combined with CT-FFR could simultaneously observe the anatomical stenosis and evaluate myocardial blood supply at the functional level.
Thus, myocardial ischemia could be better diagnosed.
Related Results
Diagnostic performance of IVUS-FFR analysis based on generative adversarial network and bifurcation fractal law for assessing myocardial ischemia
Diagnostic performance of IVUS-FFR analysis based on generative adversarial network and bifurcation fractal law for assessing myocardial ischemia
BackgroundIVUS-based virtual FFR (IVUS-FFR) can provide additional functional assessment information to IVUS imaging for the diagnosis of coronary stenosis. IVUS image segmentation...
Physiological disease pattern as assessed by PPGI in vessels with FFR and iFR discordance
Physiological disease pattern as assessed by PPGI in vessels with FFR and iFR discordance
Abstract
Background
Fractional flow reserve (FFR) and instantaneous wave-free ratio (iFR) disagree on the hemodynamic significan...
CORRELATION BETWEEN FRACTIONAL FLOW RESERVE AND QUANTITATIVE CORONARY ANGIOGRAPHY PARAMETERS IN INTERMEDIATE CORONARY ARTERY STENOSIS
CORRELATION BETWEEN FRACTIONAL FLOW RESERVE AND QUANTITATIVE CORONARY ANGIOGRAPHY PARAMETERS IN INTERMEDIATE CORONARY ARTERY STENOSIS
Objectives
To clarify the relationship between quantitative coronary angiography (QCA) parameters and fractional flow reserve (FFR) for screening out ideal angiog...
Audit committee and financial reporting fraud: the moderating role of firm size
Audit committee and financial reporting fraud: the moderating role of firm size
Purpose
The purpose of this study was to examine whether firm size moderates the relationship between audit committee (AC) characteristics and financial statements fraud (FFR) amon...
FFR-gesteuerte Revaskularisation – wann indiziert, wann überflüssig?
FFR-gesteuerte Revaskularisation – wann indiziert, wann überflüssig?
AbstractAn invasive measurement of the fractional flow reserve (FFR) allows the valuation of the individual risk for ischemic events in patients with coronary artery disease. There...
A Comparative Study of 64-Slice Coronary CT Angiography (CCTA) and Myocardial Perfusion Imaging (MPI) in the Identification of Coronary Artery Stenosis
A Comparative Study of 64-Slice Coronary CT Angiography (CCTA) and Myocardial Perfusion Imaging (MPI) in the Identification of Coronary Artery Stenosis
Objective: The aim of this study was to compare the diagnostic accuracy of 64-Slice Coronary Computer Tomography Angiography (CCTA) and Myocardial Perfusion Imaging (MPI) in the id...
ADENOSINE AND ATP STRESS OF FRACTIONAL FLOW RESERVE EVALUATION OF CORONARY ARTERY DISEASE
ADENOSINE AND ATP STRESS OF FRACTIONAL FLOW RESERVE EVALUATION OF CORONARY ARTERY DISEASE
Objectives
To compare fractional flow reserve (FFR) obtained during maximal hyperaemia by Intravenous (IV) ATP and adenosine.
...
Improving Image Quality and Diagnostic Performance of CCTA in Patients with Challenging Heart Rate Conditions using a Deep Learning-based Motion Correction Algorithm
Improving Image Quality and Diagnostic Performance of CCTA in Patients with Challenging Heart Rate Conditions using a Deep Learning-based Motion Correction Algorithm
Objective:
Challenging HR conditions, such as elevated Heart Rate (HR) and Heart Rate Variability (HRV), are major contributors to motion artifacts in
Coronary Computed Tomography ...


