Quantification of effects of mean blood pressure and left ventricular mass on noninvasive fast fractional flow reserve.
Jun-Mei ZhangGaurav ChandolaRu-San TanPing ChaiLynette L S TeoRis LowJohn Carson AllenWeimin HuangJiang Ming FamChee Yang ChinAaron Sung Lung WongAdrian F LowGhassan S KassabTerrance ChuaSwee Yaw TanSoo Teik LimLiang ZhongPublished in: American journal of physiology. Heart and circulatory physiology (2020)
Proper inlet boundary conditions are essential for accurate computational fluid dynamics (CFD) modeling. We developed methodology to derive noninvasive FFRB using CFD and computed tomography coronary angiography (CTCA) images. This study aims to assess the influence of brachial mean blood pressure (MBP) and total coronary inflow on FFRB computation. Twenty-two patients underwent both CTCA and FFR measurements. Total coronary flow was computed from left ventricular mass (LVM) measured from CTCA. A total of 286 CFD simulations were run by varying MBP and LVM at 70, 80, 90, 100, 110, 120, and 130% of the measured values. FFRB increased with incrementally higher input values of MBP: 0.78 ± 0.12, 0.80 ± 0.11, 0.82 ± 0.10, 0.84 ± 0.09, 0.85 ± 0.08, 0.86 ± 0.08, and 0.87 ± 0.07, respectively. Conversely, FFRB decreased with incrementally higher inputs value of LVM: 0.86 ± 0.08, 0.85 ± 0.08, 0.84 ± 0.09, 0.84 ± 0.09, 0.83 ± 0.10, 0.83 ± 0.10, and 0.82 ± 0.10, respectively. Noninvasive FFRB calculated using measured MBP and LVM on a total of 30 vessels was 0.84 ± 0.09 and correlated well with invasive FFR (0.83 ± 0.09) (r = 0.92, P < 0.001). Positive association was observed between FFRB and MBP input values (mmHg) and negative association between FFRB and LVM values (g). Respective slopes were 0.0016 and -0.005, respectively, suggesting potential application of FFRB in a clinical setting. Inaccurate MBP and LVM inputs differing from patient-specific values could result in misclassification of borderline ischemic lesions.NEW & NOTEWORTHY While brachial mean blood pressure (MBP) and left ventricular mass (LVM) measured from CTCA are the two CFD simulation input parameters, their effects on noninvasive fractional flow reserve (FFRB) have not been systematically investigated. We demonstrate that inaccurate MBP and LVM inputs differing from patient-specific values could result in misclassification of borderline ischemic lesions. This is important in the clinical application of noninvasive FFR in coronary artery disease diagnosis.
Keyphrases
- blood pressure
- left ventricular
- coronary artery disease
- computed tomography
- aortic stenosis
- ejection fraction
- heart failure
- coronary artery
- heart rate
- hypertrophic cardiomyopathy
- hypertensive patients
- cardiac resynchronization therapy
- magnetic resonance imaging
- percutaneous coronary intervention
- cardiovascular disease
- type diabetes
- ischemia reperfusion injury
- magnetic resonance
- coronary artery bypass grafting
- adipose tissue
- metabolic syndrome
- machine learning
- positron emission tomography
- atrial fibrillation
- blood glucose
- cerebral ischemia
- weight loss
- blood brain barrier
- patient reported
- pet ct
- diffusion weighted imaging
- peripheral artery disease
- monte carlo