Computing intracoronary blood flow rate under incomplete boundary conditions: Combing coronary anatomy and fractional flow reserve

Li, Weihao; Lian, Kun; Chen, Yan; Zhao, Shuai; Guo, Xiaoqiong; Tao, Qian; Gao, Haokao; Xie, Songyun; Li, Chengxiang; Wang, Qiong; Xie, Xinzhou

doi:10.1016/j.medengphy.2022.103942

Cited by 5 publications

(4 citation statements)

References 36 publications

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“…QFR and OFR are both techniques based on blood flow simulation, which require assumptions such as vessel wall thickness, blood viscosity, vessel elasticity and other parameters, which may vary greatly in different patients and different vessels, thus affecting the calculated results of FFR. On the contrary, some studies have also shown that the model assumptions of QFR and OFR do not affect their adaptability, as long as the corresponding blood flow parameters and boundary conditions are adjusted according to different blood flow conditions and vessel characteristics, accurate results can be obtained [ 43 ]. Finally, in terms of consistency, all four techniques are good, with a high degree of automation, stable and repeatable results [ 44 , 45 , 46 ].…”

Section: Discussion: Comprehensive Evaluation Of Computational Hemody...mentioning

confidence: 99%

An Overview of Computational Coronary Physiology Technologies Based on Medical Imaging and Artificial Intelligence

Li,

Chen,

Wang

et al. 2024

Rev. Cardiovasc. Med.

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This article reviews four new technologies for assessment of coronary hemodynamics based on medical imaging and artificial intelligence, including quantitative flow ratio (QFR), optical flow ratio (OFR), computational fractional flow reserve (CT-FFR) and artificial intelligence (AI)-based instantaneous wave-free ratio (iFR). These technologies use medical imaging such as coronary angiography, computed tomography angiography (CTA), and optical coherence tomography (OCT), to reconstruct three-dimensional vascular models through artificial intelligence algorithms, simulate and calculate hemodynamic parameters in the coronary arteries, and achieve non-invasive and rapid assessment of the functional significance of coronary stenosis. This article details the working principles, advantages such as non-invasiveness, efficiency, accuracy, limitations such as image dependency, and assumption restrictions, of each technology. It also compares and analyzes the image dependency, calculation accuracy, calculation speed, and operation simplicity, of the four technologies. The results show that these technologies are highly consistent with the traditional invasive wire method, and shows distinct advantages in terms of accuracy, reliability, convenience and cost-effectiveness, but there are also factors that affect accuracy. The results of this review demonstrates that AI-based iFR technology is currently one of the most promising technologies. The main challenges and directions for future development are also discussed. These technologies bring new ideas for the non-invasive assessment of coronary artery disease, and are expected to promote the technological progress in this field.

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Section: Discussion: Comprehensive Evaluation Of Computational Hemody...mentioning

confidence: 99%

An Overview of Computational Coronary Physiology Technologies Based on Medical Imaging and Artificial Intelligence

Li,

Chen,

Wang

et al. 2024

Rev. Cardiovasc. Med.

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“…1 where P a is the mean proximal pressure, P d is the mean distal pressure, Q is the absolute mean ow rate, VF and EL are ow resistance parameters of epicardial coronary artery, namely viscous friction (VF) and expansion loss (EL). These two ow resistance parameters (VF and EL) are mainly determined by the anatomy of epicardial coronary artery, and can be obtained by a CFD-based pressure-ow curve method from the reconstructed 3D anatomy model, which was proposed by our group previously [15,18]. Then, with the measured P a and P d during routine FFR measurement, the corresponding Q can be calculated through Eq.…”

Section: Cfd Computational Modelmentioning

confidence: 99%

“…However, routine FFR measurement only records the distal pressure at target vessel, resulting that the side branches are ignored in the CFD model (lacking of boundary conditions to include side branches). This simpli cation has great impact on the computed ow rate [15]. To overcome this limitation, our group proposed a novel CFD method which implicitly specifying constraints for splitting ow between branches within a pressure-ow curve based ow resistance model [15].…”

Section: Introductionmentioning

confidence: 99%

“…This simpli cation has great impact on the computed ow rate [15]. To overcome this limitation, our group proposed a novel CFD method which implicitly specifying constraints for splitting ow between branches within a pressure-ow curve based ow resistance model [15]. With this approach, the mean intracoronary blood ow rate can be calculated in two or more branches by only recording the distal pressure at target vessel.…”

Section: Introductionmentioning

confidence: 99%

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A novel CFD based method for assessing the coronary microvascular dysfunction: combining coronary angiography and routine fractional flow reserve Running Title: CFD based method for assessing the CMD

Xie,

Zhao,

Chen

et al. 2024

Preprint

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Background A novel computational fluid dynamics (CFD) based method was proposed for the measurement of intracoronary mean flow rate (Q) and absolute microvascular resistance (AMR) by combining coronary angiography and routine fractional flow reserve (FFR) measurement. The aim of this study is to explore the potential of the proposed method to assess the presence of coronary microvascular dysfunction (CMD). Methods Patients without hemodynamically significant coronary artery stenosis or those after a successful PCI were enrolled. Rest SPECT myocardial perfusion imaging (MPI) was employed as evidence for assessing the presence of CMD. Based on the sum rest score of target vessel (SRSTV), patients were divided into normal MPI group (SRSTV ≤ 1) and abnormal MPI group (SRSTV > 1). Q and AMR were obtained with a CFD based method during rest and hyperemia condition, and receiver operating characteristic (ROC) curve analyses were performed for discriminating patients with normal MPI and with abnormal MPI. Results A total of 57 patients with 61 target vessels were investigated. Based on SRSTV, 22 patients (38.6%) with 23 target vessels (37.7%) were associated with abnormal MPI. Compared with abnormal MPI group, the AMR was significantly lower in normal MPI group (1.97 ± 1.50 mmHg·s/ml vs 3.41 ± 2.30 mmHg·s/ml, p = 0.011), and the Q was significant higher in normal MPI group (0.94 ± 70 mmHg·s/ml vs 0.56 ± 0.50 mmHg·s/ml, p = 0.025). According to ROC curve analysis, the ROC-AUC of Q and AMR for discriminating normal MPI and abnormal MPI was 0.720(95% CI: 0.591–0.828, p = 0.001) and 0.731(95% CI: 0.602–0.836, p = 0.001). Conclusions The new CFD based method provides an easy and accurate way to measure the intracoronary flow rate and absolute microvascular resistance, and constitutes a new opportunity for assessing the presence of CMD.

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Evaluation of models of sequestration flow in coronary arteries—Physiology versus anatomy?

Taylor,

Saxton,

Halliday

et al. 2024

Computers in Biology and Medicine

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Computing intracoronary blood flow rate under incomplete boundary conditions: Combing coronary anatomy and fractional flow reserve

Cited by 5 publications

References 36 publications

An Overview of Computational Coronary Physiology Technologies Based on Medical Imaging and Artificial Intelligence

An Overview of Computational Coronary Physiology Technologies Based on Medical Imaging and Artificial Intelligence

A novel CFD based method for assessing the coronary microvascular dysfunction: combining coronary angiography and routine fractional flow reserve Running Title: CFD based method for assessing the CMD

Evaluation of models of sequestration flow in coronary arteries—Physiology versus anatomy?

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