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Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions
Mar 26, 2025;

Validation of a Novel Computational Fluid Dynamics Based Method for Assessing Intracoronary Flow: Combining Coronary Angiography and Fractional Flow Reserve.

Xinzhou Xie, Na Li, Tiantong Yu, Wenjun Pu, Heqiang Lin, Xiang Li, Guoquan Li, Chengxiang Li, Yan Chen, Kun Lian
Author Information
  1. Xinzhou Xie: Department of Information Engineering, School of Electronics and Information, Northwestern Polytechnical University, Xi'an, Shaanxi, P.R. China.
  2. Na Li: Department of Cardiology, Xi'an International Medical Center Hospital, Northwest University, Xi'an, Shaanxi, China.
  3. Tiantong Yu: Department of Cardiology, The First Affiliated Hospital of the Fourth Military Medical University, Xi'an, Shaanxi, P.R. China.
  4. Wenjun Pu: Department of Information Engineering, School of Electronics and Information, Northwestern Polytechnical University, Xi'an, Shaanxi, P.R. China.
  5. Heqiang Lin: Department of Information Engineering, School of Electronics and Information, Northwestern Polytechnical University, Xi'an, Shaanxi, P.R. China.
  6. Xiang Li: Department of Nuclear Medicine, The First Affiliated Hospital of the Fourth Military Medical University, Xi'an, Shaanxi, P.R. China.
  7. Guoquan Li: Department of Nuclear Medicine, The First Affiliated Hospital of the Fourth Military Medical University, Xi'an, Shaanxi, P.R. China.
  8. Chengxiang Li: Department of Cardiology, The First Affiliated Hospital of the Fourth Military Medical University, Xi'an, Shaanxi, P.R. China.
  9. Yan Chen: Department of Cardiology, No.971 Hospital of the PLA Navy, Qingdao, Shandong, P.R. China.
  10. Kun Lian: Department of Cardiology, The First Affiliated Hospital of the Fourth Military Medical University, Xi'an, Shaanxi, P.R. China. ORCID
PMID: 40136007 DOI: 10.1002/ccd.31498

Abstract

BACKGROUND: With a 3D model reconstructed from coronary angiography, intracoronary blood flow can be calculated using a computational fluid dynamics (CFD) model with fractional flow reserve (FFR) measured pressure as boundary conditions.
AIMS: The aim of this study is to investigate the clinical feasibility of this method by evaluating its ability to identify myocardial ischemia diagnosed by SPECT myocardial perfusion imaging (MPI).
METHODS: Patients who underwent both SPECT-MPI and coronary angiography with FFR within 1 week were enrolled. Based on the summed stress score (SSS) and summed difference score (SDS) of SPECT MPI, myocardial ischemia in individual coronary territories was identified. Mean flow rate (Q), total flow resistance (TFR), absolute microvascular resistance (AMR) and their corresponding resting state indices were computed using the novel CFD model.
RESULTS: A total of 52 patients with 53 vessels were investigated. Based on SPECT MPI, 23 patients (43.4%) were associated with abnormal MPI. Q was significant higher in normal MPI group compared with abnormal MPI group (59.68��������40.33���mL/min vs. 25.67��������21.55���mL/min, p���<���0.001). The TFR were significantly lower in normal MPI group (TFR: 1898.25��������951.55���mmHg���min/L vs. 4786.31��������3056.18���mmHg���min/L, p���<���0.001). The ROC-AUC of Q and TFR for discriminating normal and abnormal MPI were 0.876 (95% CI: 0.783-0.970, p���<���0.001) and 0.854 (95% CI: 0.745-0.963, p���<���0.001).
CONCLUSIONS: Intracoronary flow assessed by the novel CFD based method has shown promise in accurately identifying patients with abnormal SPECT MPI, offering a convenient and quantitative approach for assessing coronary physiology.

Keywords

CFD fractional flow reserve intracoronary flow myocardial ischemia

References

  1. T. Vos, S. S. Lim, C. Abbafati, et al., ���Global Burden of 369 Diseases and Injuries in 204 Countries and Territories, 1990���2019: A Systematic Analysis for the Global Burden of Disease Study 2019,��� Lancet 396 (2020): 1204���1222, https://doi.org/10.1016/S0140-6736(20)30925-9.
  2. G. A. Roth, G. A. Mensah, C. O. Johnson, et al., ���Global Burden of Cardiovascular Diseases and Risk Factors, 1990���2019,��� Journal of the American College of Cardiology 76 (2020): 2982���3021, https://doi.org/10.1016/j.jacc.2020.11.010.
  3. K. L. Gould and K. Lipscomb, ���Effects of Coronary Stenoses on Coronary Flow Reserve and Resistance,��� American Journal of Cardiology 34 (1974): 48���55, https://doi.org/10.1016/0002-9149(74)90092-7.
  4. W. Aarnoudse, P. van den Berg, F. van de Vosse, et al., ���Myocardial Resistance Assessed by Guidewire���Based Pressure���Temperature Measurement: In Vitro Validation,��� Catheterization and Cardiovascular Interventions 62 (2004): 56���63, https://doi.org/10.1002/ccd.10793.
  5. P. D. Morris, R. K. Al���Lamee, and C. Berry, ���Coronary Physiological Assessment in the Catheter Laboratory: Haemodynamics, Clinical Assessment and Future Perspectives,��� Heart 108 (2022): 1737���1746, https://doi.org/10.1136/heartjnl-2020-318743.
  6. V. E. Stegehuis, G. W. Wijntjens, T. Murai, J. J. Piek, and T. P. Hoef, ���Assessing the Haemodynamic Impact of Coronary Artery Stenoses: Intracoronary Flow Versus Pressure Measurements,��� European Cardiology Review 13 (2018): 46���53, https://doi.org/10.15420/ecr.2018:7:2.
  7. C. Vrints, F. Andreotti, K. C. Koskinas, et al., ���2024 ESC Guidelines for the Management of Chronic Coronary Syndromes,��� European Heart Journal 45 (2024): 3415���3537, https://doi.org/10.1093/eurheartj/ehae177.
  8. P. Ong, B. Safdar, A. Seitz, A. Hubert, J. F. Beltrame, and E. Prescott, ���Diagnosis of Coronary Microvascular Dysfunction in the Clinic,��� Cardiovascular Research 116 (2020): 841���855, https://doi.org/10.1093/cvr/cvz339.
  9. R. Eerdekens, M. El Farissi, G. L. De Maria, et al., ���Prognostic Value of Microvascular Resistance Reserve After Percutaneous Coronary Intervention in Patients With Myocardial Infarction,��� Journal of the American College of Cardiology 83 (2024): 2066���2076, https://doi.org/10.1016/j.jacc.2024.02.052.
  10. J. W. Doucette, P. D. Corl, H. M. Payne, et al., ���Validation of a Doppler Guide Wire for Intravascular Measurement of Coronary Artery Flow Velocity,��� Circulation 85 (1992): 1899���1911, https://doi.org/10.1161/01.CIR.85.5.1899.
  11. M. J. Kern and A. H. Seto, ���The Challenges of Measuring Coronary Flow Reserve,��� JACC: Cardiovascular Interventions 11 (2018): 2055���2057, https://doi.org/10.1016/j.jcin.2018.08.004.
  12. R. P. Williams, G. A. de Waard, K. De Silva, et al., ���Doppler Versus Thermodilution���Derived Coronary Microvascular Resistance to Predict Coronary Microvascular Dysfunction in Patients With Acute Myocardial Infarction or Stable Angina Pectoris,��� American Journal of Cardiology 121 (2018): 1���8, https://doi.org/10.1016/j.amjcard.2017.09.012.
  13. E. Gallinoro, D. T. Bertolone, E. Fernandez���Peregrina, et al., ���Reproducibility of Bolus Versus Continuous Thermodilution for Assessment of Coronary Microvascular Function in Patients With ANOCA,��� EuroIntervention 19 (2023): e155���e166, https://doi.org/10.4244/EIJ-D-22-00772.
  14. E. Gallinoro, A. Candreva, I. Colaiori, et al., ���Thermodilution���Derived Volumetric Resting Coronary Blood Flow Measurement in Humans,��� EuroIntervention 17 (2021): e672���e679, https://doi.org/10.4244/EIJ-D-20-01092.
  15. A. Candreva, E. Gallinoro, M. van 't Veer, et al., ���Basics of Coronary Thermodilution,��� JACC: Cardiovascular Interventions 14 (2021): 595���605, https://doi.org/10.1016/j.jcin.2020.12.037.
  16. T. P. J. Jansen, A. de Vos, V. Paradies, et al., ���Continuous Versus Bolus Thermodilution���Derived Coronary Flow Reserve and Microvascular Resistance Reserve and Their Association With Angina and Quality of Life in Patients With Angina and Nonobstructive Coronaries: A Head���to���Head Comparison,��� Journal of the American Heart Association 12 (2023): e030480, https://doi.org/10.1161/JAHA.123.030480.
  17. P. D. Morris, R. Gosling, I. Zwierzak, et al., ���A Novel Method for Measuring Absolute Coronary Blood Flow and Microvascular Resistance in Patients With Ischaemic Heart Disease,��� Cardiovascular Research 117 (2021): 1567���1577, https://doi.org/10.1093/cvr/cvaa220.
  18. W. Li, K. Lian, Y. Chen, et al., ���Computing Intracoronary Blood Flow Rate Under Incomplete Boundary Conditions: Combing Coronary Anatomy and Fractional Flow Reserve,��� Medical Engineering & Physics 111 (2023): 103942, https://doi.org/10.1016/j.medengphy.2022.103942.
  19. D. F. Young and F. Y. Tsai, ���Flow Characteristics in Models of Arterial Stenoses���I. Steady Flow,��� Journal of Biomechanics 6 (1973): 395���410, https://doi.org/10.1016/0021-9290(73)90099-7.
  20. X. Xie, D. Wen, R. Zhang, et al., ���Pressure���Flow Curve Derived From Coronary CT Angiography for Detection of Significant Hemodynamic Stenosis,��� European Radiology 30 (2020): 4347���4355.
  21. A. Banerjee, F. Galassi, E. Zacur, G. L. De Maria, R. P. Choudhury, and V. Grau, ���Point���Cloud Method for Automated 3D Coronary Tree Reconstruction From Multiple Non���Simultaneous Angiographic Projections,��� IEEE Transactions on Medical Imaging 39 (2020): 1278���1290, https://doi.org/10.1109/TMI.2019.2944092.
  22. X. Kang, D. S. Berman, H. C. Lewin, et al., ���Incremental Prognostic Value of Myocardial Perfusion Single Photon Emission Computed Tomography in Patients With Diabetes Mellitus,��� American Heart Journal 138 (1999): 1025���1032, https://doi.org/10.1016/s0002-8703(99)70066-9.
  23. M. Czaja, Z. Wygoda, A. Dusza��ska, et al., ���Interpreting Myocardial Perfusion Scintigraphy Using Single���Photon Emission Computed Tomography. Part 1,��� Polish Journal of Cardio���Thoracic Surgery 3 (2017): 192���199, https://doi.org/10.5114/kitp.2017.70534.
  24. B. De Bruyne, N. H. J. Pijls, E. Gallinoro, et al., ���Microvascular Resistance Reserve for Assessment of Coronary Microvascular Function,��� Journal of the American College of Cardiology 78 (2021): 1541���1549, https://doi.org/10.1016/j.jacc.2021.08.017.
  25. A. de Vos, S. Troost, A. Waterschoot, N. Pijls, and M. van ���t Veer, ���Mixing Properties of Coronary Infusion Catheters Assessed by In Vitro Experiments and Computational Fluid Dynamics,��� European Heart Journal ��� Digital Health 5 (2024): 491���501, https://doi.org/10.1093/ehjdh/ztae033.
  26. S. Fournier, D. C. J. Keulards, M. van 't Veer, et al., ���Normal Values of Thermodilution���Derived Absolute Coronary Blood Flow and Microvascular Resistance in Humans,��� EuroIntervention 17 (2021): e309���e316, https://doi.org/10.4244/EIJ-D-20-00684.
  27. D. J. Taylor, H. Saxton, I. Halliday, et al., ���Evaluation of Models of Sequestration Flow in Coronary Arteries���Physiology Versus Anatomy?,��� Computers in Biology and Medicine 173 (2024): 108299, https://doi.org/10.1016/j.compbiomed.2024.108299.
  28. N. H. Pijls, J. A. van Son, R. L. Kirkeeide, B. De Bruyne, and K. L. Gould, ���Experimental Basis of Determining Maximum Coronary, Myocardial, and Collateral Blood Flow by Pressure Measurements for Assessing Functional Stenosis Severity Before and After Percutaneous Transluminal Coronary Angioplasty,��� Circulation 87 (1993): 1354���1367, https://doi.org/10.1161/01.CIR.87.4.1354.
  29. L. Aubiniere���Robb, R. Gosling, D. J. Taylor, et al., ���The Complementary Value of Absolute Coronary Flow in the Assessment of Patients With Ischaemic Heart Disease,��� Nature Cardiovascular Research 1 (2022): 611���616, https://doi.org/10.1038/s44161-022-00091-z.
  30. W. Pu, Y. Chen, S. Zhao, et al., ���Computing Pulsatile Blood Flow of Coronary Artery Under Incomplete Boundary Conditions,��� Medical Engineering & Physics 130 (2024): 104193, https://doi.org/10.1016/j.medengphy.2024.104193.

Grants

  1. /This work was supported by the General Project of Shaanxi Province Key Research and Development Plan (2024GX-YBXM-136), the Clinical Research Project of Air Force Medical University (2022LC2208), New Clinical Technology and New Business of Xijing Hospital (XJGX15Y39), Medical and health scientific research guidance project of Qingdao (2023-WJZD244), and the Program for the National Natural Science Foundation of China (62171371).
Journal Article

Word Cloud

Created with Highcharts 10.0.0MPIflowcoronaryCFDmyocardialSPECTabnormalp���<���00010modelischemiaBasedQTFRpatientsnormalgroupangiographyintracoronaryusingfractionalreserveFFRmethodsummedscoretotalresistancenovelvs95%CI:IntracoronaryBACKGROUND:3Dreconstructedbloodcancalculatedcomputationalfluiddynamicsmeasured pressureboundaryconditionsAIMS:aimstudyinvestigateclinicalfeasibilityevaluatingabilityidentifydiagnosedperfusionimagingMETHODS:PatientsunderwentSPECT-MPIwithin1weekenrolledstressSSSdifferenceSDSindividualterritoriesidentifiedMeanrateabsolutemicrovascularAMRcorrespondingrestingstateindicescomputedRESULTS:5253vesselsinvestigated23434%associatedsignificanthighercompared5968��������4033���mL/min2567��������2155���mL/minsignificantlylowerTFR:189825��������95155���mmHg���min/L478631��������305618���mmHg���min/LROC-AUCdiscriminating876783-0970854745-0963CONCLUSIONS:assessedbasedshownpromiseaccuratelyidentifyingofferingconvenientquantitativeapproachassessingphysiologyValidationNovelComputationalFluidDynamicsMethodAssessingFlow:CombiningCoronaryAngiographyFractionalFlowReserve

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