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Bibliography of Published Literature

Compiled PubMed and Web of Science Listing of FFRCT Related Publications

Please note this is a fair and balanced listing as of April 17th, 2018 and is not intended to represent promotional materials. These articles are applicable to FFRCT technology, but not necessarily all non-invasive Fractional Flow Reserve technologies.**
Most of these publications are available through PubMed and/or Web of Science; this list is only intended for reference to a payer audience.

2011

  1. Koo, B.K., et al., Diagnosis of ischemia-causing coronary stenoses by noninvasive fractional flow reserve computed from coronary computed tomographic angiograms. Results from the prospective multicenter DISCOVER-FLOW (Diagnosis of Ischemia-Causing Stenoses Obtained Via Noninvasive Fractional Flow Reserve) study. J Am Coll Cardiol, 2011. 58(19): p. 1989-97.
  2. Min, J.K., et al., Rationale and design of the DeFACTO (Determination of Fractional Flow Reserve by Anatomic Computed Tomographic AngiOgraphy) study. J Cardiovasc Comput Tomogr, 2011. 5(5): p. 301-9.

2012

  1. Arsanjani, R., et al., Integrating Physiologic and Anatomic Assessment of Coronary Artery Disease by Coronary Computed Tomographic Angiography. Current Cardiovascular Imaging Reports, 2012. 5(5): p. 301-309.
  2. Meijs, M.F., et al., CT fractional flow reserve: the next level in non-invasive cardiac imaging. Neth Heart J, 2012. 20(10): p. 410-8.
  3. Min, J.K., et al., Effect of image quality on diagnostic accuracy of noninvasive fractional flow reserve: results from the prospective multicenter international DISCOVER-FLOW study. J Cardiovasc Comput Tomogr, 2012. 6(3): p. 191-9.
  4. Min, J.K., et al., Usefulness of noninvasive fractional flow reserve computed from coronary computed tomographic angiograms for intermediate stenoses confirmed by quantitative coronary angiography. Am J Cardiol, 2012. 110(7): p. 971-6.
  5. Min, J.K., et al., Diagnostic accuracy of fractional flow reserve from anatomic CT angiography. Jama, 2012. 308(12): p. 1237-45.
  6. Serruys, P.W., et al., Non-invasive fractional flow reserve: scientific basis, methods and perspectives. EuroIntervention, 2012. 8(4): p. 511-9.
  7. Yoon, Y.E., et al., Noninvasive diagnosis of ischemia-causing coronary stenosis using CT angiography: diagnostic value of transluminal attenuation gradient and fractional flow reserve computed from coronary CT angiography compared to invasively measured fractional flow reserve. JACC Cardiovasc Imaging, 2012. 5(11): p. 1088-96.
  8. Yoon, Y.E. and B.K. Koo, Non-invasive functional assessment using computed tomography: when will they be ready for clinical use? Cardiovasc Diagn Ther, 2012. 2(2): p. 106-12.

2013

  1. Al-Hassan, D. and J. Leipsic, Noninvasive fractional flow reserve derived from coronary computed tomography angiography: integrated anatomical and functional assessment. Future Cardiol, 2013. 9(2): p. 243-51.
  2. Dai, N., et al., Diagnostic performance of noninvasive cardiac imaging modalities to detect obstructive coronary artery disease. Int J Cardiol, 2013. 168(5): p. 5057-9.
  3. Gaur, S., et al., Rationale and design of the HeartFlowNXT (HeartFlow analysis of coronary blood flow using CT angiography: NeXt sTeps) study. J Cardiovasc Comput Tomogr, 2013. 7(5): p. 279-88.
  4. Grunau, G.L., J.K. Min, and J. Leipsic, Modeling of fractional flow reserve based on coronary CT angiography. Curr Cardiol Rep, 2013. 15(1): p. 336.
  5. Hlatky, M.A., et al., Projected costs and consequences of computed tomography-determined fractional flow reserve. Clin Cardiol, 2013. 36(12): p. 743-8.
  6. Kakouros, N., et al., Coronary pressure-derived fractional flow reserve in the assessment of coronary artery stenoses. Eur Radiol, 2013. 23(4): p. 958-67.
  7. Kochar, M. and J.K. Min, Physiologic assessment of coronary artery disease by cardiac computed tomography. Korean Circ J, 2013. 43(7): p. 435-42.
  8. Lee, A.K., et al., Integrating anatomical and functional imaging for the assessment of coronary artery disease. Expert Rev Cardiovasc Ther, 2013. 11(10): p. 1301-10.
  9. Min, J.K., J. Castellanos, and R. Siegel, New frontiers in CT angiography: physiologic assessment of coronary artery disease by multidetector CT. Heart, 2013. 99(9): p. 661-8.
  10. Nakazato, R., et al., Noninvasive fractional flow reserve derived from computed tomography angiography for coronary lesions of intermediate stenosis severity: results from the DeFACTO study. Circ Cardiovasc Imaging, 2013. 6(6): p. 881-9.
  11. Onuma, Y., et al., Five-year clinical and functional multislice computed tomography angiographic results after coronary implantation of the fully resorbable polymeric everolimus-eluting scaffold in patients with de novo coronary artery disease: the ABSORB cohort A trial. JACC Cardiovasc Interv, 2013. 6(10): p. 999-1009.
  12. Rajani, R., et al., Virtual fractional flow reserve by coronary computed tomography – hope or hype? EuroIntervention, 2013. 9(2): p. 277-84.
  13. Taylor, C.A., T.A. Fonte, and J.K. Min, Computational fluid dynamics applied to cardiac computed tomography for noninvasive quantification of fractional flow reserve: scientific basis. J Am Coll Cardiol, 2013. 61(22): p. 2233-41.
  14. Wasilewski, J., et al., Invasive and non-invasive fractional flow reserve index in validation of hemodynamic severity of intracoronary lesions. Postepy Kardiol Interwencyjnej, 2013. 9(2): p. 160-9.
  15. Zarins, C.K., C.A. Taylor, and J.K. Min, Computed fractional flow reserve (FFTCT) derived from coronary CT angiography. J Cardiovasc Transl Res, 2013. 6(5): p. 708-14.

2014

  1. Alani, A. and M.J. Budoff, Coronary calcium scoring and computed tomography angiography: current indications, future applications. Coron Artery Dis, 2014. 25(6): p. 529-39.
  2. Alani, A., R. Nakanishi, and M.J. Budoff, Recent improvement in coronary computed tomography angiography diagnostic accuracy. Clin Cardiol, 2014. 37(7): p. 428-33.
  3. Choi, A.D., et al.,Physiologic evaluation of ischemia using cardiac CT: current status of CT myocardial perfusion and CT fractional flow reserve. J Cardiovasc Comput Tomogr, 2014. 8(4): p. 272-81.
  4. Elgendy, I.Y., C.R. Conti, and A.A. Bavry, Fractional flow reserve: an updated review. Clin Cardiol, 2014. 37(6): p. 371-80.
  5. Escaned, J., Imaging. Can FFRCT replace old indices of coronary stenosis severity? Nat Rev Cardiol, 2014. 11(5): p. 252-4.
  6. Farooq, V., et al.,Widening clinical applications of the SYNTAX Score. Heart, 2014. 100(4): p. 276-87.
  7. Gaur, S., et al., Fractional flow reserve derived from coronary CT angiography: variation of repeated analyses. J Cardiovasc Comput Tomogr, 2014. 8(4): p. 307-14.
  8. Heo, R., et al., Noninvasive imaging in coronary artery disease. Semin Nucl Med, 2014. 44(5): p. 398-409.
  9. Kim, K.H., et al., A novel noninvasive technology for treatment planning using virtual coronary stenting and computed tomography-derived computed fractional flow reserve. JACC Cardiovasc Interv, 2014. 7(1): p. 72-8.
  10. Koo, B.K., The present and future of fractional flow reserve. Circ J, 2014. 78(5): p. 1048-54.
  11. Leipsic, J., et al.,CT angiography (CTA) and diagnostic performance of noninvasive fractional flow reserve: results from the Determination of Fractional Flow Reserve by Anatomic CTA (DeFACTO) study. AJR Am J Roentgenol, 2014. 202(5): p. 989-94.
  12. Loewe, C. and A. Stadler, Computed tomography assessment of hemodynamic significance of coronary artery disease: CT perfusion, contrast gradients by coronary CTA, and fractional flow reserve review. J Thorac Imaging, 2014. 29(3): p. 163-72.
  13. Maurovich-Horvat, P., et al., Comprehensive plaque assessment by coronary CT angiography. Nat Rev Cardiol, 2014. 11(7): p. 390-402.
  14. Nakazato, R., et al., CFR and FFR assessment with PET and CTA: strengths and limitations. Curr Cardiol Rep, 2014. 16(5): p. 484.
  15. Norgaard, B.L., et al., Diagnostic performance of noninvasive fractional flow reserve derived from coronary computed tomography angiography in suspected coronary artery disease: the NXT trial (Analysis of Coronary Blood Flow Using CT Angiography: Next Steps). J Am Coll Cardiol, 2014. 63(12): p. 1145-55.
  16. Pantos, I. and D. Katritsis, Fractional Flow Reserve Derived from Coronary Imaging and Computational Fluid Dynamics. Interv Cardiol, 2014. 9(3): p. 145-150.
  17. Pattanayak, P. and D.A. Bluemke, Cardiovascular imaging in 2013: New era of evidence-based medicine with noninvasive imaging. Nat Rev Cardiol, 2014. 11(2): p. 74-6.
  18. Rubin, G.D., et al.,CT angiography after 20 years: a transformation in cardiovascular disease characterization continues to advance. Radiology, 2014. 271(3): p. 633-52.
  19. Sun, Z. and L. Xu, Computational fluid dynamics in coronary artery disease. Comput Med Imaging Graph, 2014. 38(8): p. 651-63.
  20. Yoon, Y.E. and T.H. Lim, Current roles and future applications of cardiac CT: risk stratification of coronary artery disease. Korean J Radiol, 2014. 15(1): p. 4-11.
  21. Zhang, J.M., et al.,Perspective on CFD studies of coronary artery disease lesions and hemodynamics: a review. Int J Numer Method Biomed Eng, 2014. 30(6): p. 659-80.

2015

  1. Choi, G., et al., Coronary Artery Axial Plaque Stress and its Relationship With Lesion GeometryApplication of Computational Fluid Dynamics to Coronary CT Angiography. JACC: Cardiovascular Imaging, 2015. 8(10): p. 1156-1166.
  2. Danad, I., L. Baskaran, and J.K. Min, Noninvasive Fractional Flow Reserve Derived from Coronary Computed Tomography Angiography for the Diagnosis of Lesion-specific Ischemia. Interventional Cardiology Clinics. 4(4): p. 481-489.
  3. De Cecco, C.N., et al., Beyond Stenosis Detection: Computed Tomography Approaches for Determining the Functional Relevance of Coronary Artery Disease. Radiologic Clinics. 53(2): p. 317-334.
  4. Deng, S.B., et al., Diagnostic performance of noninvasive fractional flow reserve derived from coronary computed tomography angiography in coronary artery disease: A systematic review and meta-analysis. Int J Cardiol, 2015. 184: p. 703-9.
  5. Douglas, P.S., et al., Clinical outcomes of fractional flow reserve by computed tomographic angiography-guided diagnostic strategies vs. usual care in patients with suspected coronary artery disease: the prospective longitudinal trial of FFR(CT): outcome and resource impacts study. Eur Heart J, 2015. 36(47): p. 3359-67.
  6. Fan, G.X., et al., Noninvasive Measurement of Coronary Fractional Flow Reserve: An Under-exploiting Newland. Chin Med J (Engl), 2015. 128(12): p. 1695-9.
  7. Goncalves Pde, A., et al., Functional Evaluation of Coronary Disease by CT Angiography. JACC Cardiovasc Imaging, 2015. 8(11): p. 1322-35.
  8. Gonzalez, J.A., et al., Meta-Analysis of Diagnostic Performance of Coronary Computed Tomography Angiography, Computed Tomography Perfusion, and Computed Tomography-Fractional Flow Reserve in Functional Myocardial Ischemia Assessment Versus Invasive Fractional Flow Reserve. Am J Cardiol, 2015. 116(9): p. 1469-78.
  9. Hlatky, M.A., et al., Quality-of-Life and Economic Outcomes of Assessing Fractional Flow Reserve With Computed Tomography Angiography: PLATFORM. J Am Coll Cardiol, 2015. 66(21): p. 2315-23.
  10. Jensen, J.M., et al., Noninvasive Fractional Flow Reserve for the Diagnosis of Lesion-specific Ischemia: A Case Example. J Clin Imaging Sci, 2015. 5: p. 3.
  11. Kimura, T., et al., Cost analysis of non-invasive fractional flow reserve derived from coronary computed tomographic angiography in Japan. Cardiovasc Interv Ther, 2015. 30(1): p. 38-44.
  12. Li, S., et al., The diagnostic performance of CT-derived fractional flow reserve for evaluation of myocardial ischaemia confirmed by invasive fractional flow reserve: a meta-analysis. Clin Radiol, 2015. 70(5): p. 476-86.
  13. Machida, H., et al., Current and Novel Imaging Techniques in Coronary CT. Radiographics, 2015. 35(4): p. 991-1010.
  14. Marwick, T.H., et al., Finding the Gatekeeper to the Cardiac Catheterization Laboratory: Coronary CT Angiography or Stress Testing? J Am Coll Cardiol, 2015. 65(25): p. 2747-56.
  15. Min, J.K., et al., Noninvasive Fractional Flow Reserve Derived From Coronary CT AngiographyClinical Data and Scientific Principles. JACC: Cardiovascular Imaging, 2015. 8(10): p. 1209-1222.
  16. Miyoshi, T., et al., Non-invasive computed fractional flow reserve from computed tomography (CT) for diagnosing coronary artery disease – Japanese results from NXT trial (Analysis of Coronary Blood Flow Using CT Angiography: Next Steps). Circ J, 2015. 79(2): p. 406-12.
  17. Morris, P.D., et al., “Virtual” (Computed) Fractional Flow Reserve: Current Challenges and Limitations. JACC Cardiovasc Interv, 2015. 8(8): p. 1009-17.
  18. Motwani, M., et al., Reasons and implications of agreements and disagreements between coronary flow reserve, fractional flow reserve, and myocardial perfusion imaging. J Nucl Cardiol, 2015.
  19. Nakanishi, R., et al., Diagnostic performance of transluminal attenuation gradient and fractional flow reserve by coronary computed tomographic angiography (FFR(CT)) compared to invasive FFR: a sub-group analysis from the DISCOVER-FLOW and DeFACTO studies. Int J Cardiovasc Imaging, 2015. 31(6): p. 1251-9.
  20. Norgaard, B.L., et al., Influence of Coronary Calcification on the Diagnostic Performance of CT Angiography Derived FFR in Coronary Artery Disease: A Substudy of the NXT Trial. JACC Cardiovasc Imaging, 2015.
  21. Norgaard, B.L., et al., A “normal” invasive coronary angiogram may not be normal. J Cardiovasc Comput Tomogr, 2015. 9(4): p. 264-6.
  22. Norgaard, B.L., J.M. Jensen, and J. Leipsic, Fractional flow reserve derived from coronary CT angiography in stable coronary disease: a new standard in non-invasive testing? Eur Radiol, 2015. 25(8): p. 2282-90.
  23. Park, H.B., et al., Atherosclerotic plaque characteristics by CT angiography identify coronary lesions that cause ischemia: a direct comparison to fractional flow reserve. JACC Cardiovasc Imaging, 2015. 8(1): p. 1-10.
  24. Park, J.-B. and B.-K. Koo, Noninvasive hemodynamic assessment using coronary computed tomography angiography: the present and future. Interventional Cardiology, 2015. 7(1): p. 77-88.
  25. Pontone, G., et al., Functional relevance of coronary artery disease by cardiac magnetic resonance and cardiac computed tomography: myocardial perfusion and fractional flow reserve. Biomed Res Int, 2015. 2015: p. 297696.
  26. Pontone, G., et al., Rationale and design of the Prospective LongitudinAl Trial of FFRCT: Outcome and Resource IMpacts study. Am Heart J, 2015. 170(3): p. 438-46.e44.
  27. Precious, B., et al., Fractional flow reserve modeled from resting coronary CT angiography: state of the science. AJR Am J Roentgenol, 2015. 204(3): p. W243-8.
  28. Qi, X., et al., Comprehensive assessment of coronary fractional flow reserve. Arch Med Sci, 2015. 11(3): p. 483-93.
  29. Rajani, R., et al., Comparative efficacy testing – fractional flow reserve by coronary computed tomography for the evaluation of patients with stable chest pain. Int J Cardiol, 2015. 183: p. 173-7.
  30. Sankaran, S., L. Grady, and C.A. Taylor, Impact of geometric uncertainty on hemodynamic simulations using machine learning. Computer Methods in Applied Mechanics and Engineering, 2015. 297: p. 167-190.
  31. Sankaran, S., L. Grady, and C.A. Taylor, Fast Computation of Hemodynamic Sensitivity to Lumen Segmentation Uncertainty. IEEE Trans Med Imaging, 2015. 34(12): p. 2562-71.
  32. Sato, A. and K. Aonuma, Role of cardiac multidetector computed tomography beyond coronary angiography. Circ J, 2015. 79(4): p. 712-20.
  33. Schulman-Marcus, J., I. Danad, and Q.A. Truong, State-of-the-Art Updates on Cardiac Computed Tomographic Angiography for Assessing Coronary Artery Disease. Curr Treat Options Cardiovasc Med, 2015. 17(8): p. 398.
  34. Shantouf, R.S. and A. Mehra, Coronary fractional flow reserve. AJR Am J Roentgenol, 2015. 204(3): p. W261-5.
  35. Sinclair, M.D., et al., Measurement and modeling of coronary blood flow. Wiley Interdiscip Rev Syst Biol Med, 2015. 7(6): p. 335-56.
  36. Taguchi, E., et al., Accuracy and usefulness of noninvasive fractional flow reserve from computed tomographic coronary angiography: comparison with myocardial perfusion imaging, echocardiographic coronary flow reserve, and invasive fractional flow reserve. Cardiovascular Intervention and Therapeutics, 2015: p. 1-6.
  37. Thompson, A.G., et al., Diagnostic accuracy and discrimination of ischemia by fractional flow reserve CT using a clinical use rule: results from the Determination of Fractional Flow Reserve by Anatomic Computed Tomographic Angiography study. J Cardiovasc Comput Tomogr, 2015. 9(2): p. 120-8.
  38. Tu, S., et al., Image-based assessment of fractional flow reserve. EuroIntervention, 2015. 11 Suppl V: p. V50-4.
  39. Xu, L., Z. Sun, and Z. Fan, Noninvasive physiologic assessment of coronary stenoses using cardiac CT. Biomed Res Int, 2015. 2015: p. 435737.
  40. Xu, R., et al., Computed Tomography-Derived Fractional Flow Reserve in the Detection of Lesion-Specific Ischemia: An Integrated Analysis of 3 Pivotal Trials. Medicine, 2015. 94(46): p. e1963.

2016

  1. Adjedj, J., et al.,Coronary artery anomaly and evaluation by FFR computed tomography. Eur Heart J Cardiovasc Imaging, 2016. 17(4): p. 468.
  2. Ahmadi, A., et al.,Association of Coronary Stenosis and Plaque Morphology With Fractional Flow Reserve and Outcomes. JAMA Cardiol, 2016. 1(3): p. 350-7.
  3. Al-Mallah, M.H. and A.M. Ahmed, Controversies in the Use of Fractional Flow Reserve Form Computed Tomography (FFRCT) vs. Coronary Angiography. Current Cardiovascular Imaging Reports, 2016. 9(12): p. 34.
  4. Andreini, D., et al., Severe in-stent restenosis missed by coronary CT angiography and accurately detected with FFRCT. Int J Cardiovasc Imaging, 2016.
  5. Baumann, S., et al., Comparison of Coronary Computed Tomography Angiography-Derived vs Invasive Fractional Flow Reserve Assessment: Meta-Analysis with Subgroup Evaluation of Intermediate Stenosis. Acad Radiol, 2016. 23(11): p. 1402-1411.
  6. Bilbey, N., et al.,Potential impact of clinical use of noninvasive FFRCT on radiation dose exposure and downstream clinical event rate. Clin Imaging, 2016. 40(5): p. 1055-1060.
  7. Budoff, M.J., et al., CT Angiography for the Prediction of Hemodynamic Significance in Intermediate and Severe Lesions: Head-to-Head Comparison With Quantitative Coronary Angiography Using Fractional Flow Reserve as the Reference Standard. JACC Cardiovasc Imaging, 2016. 9(5): p. 559-64.
  8. Cheruvu, C., et al., Beyond Stenosis With Fractional Flow Reserve Via Computed Tomography and Advanced Plaque Analyses for the Diagnosis of Lesion-Specific Ischemia. Can J Cardiol, 2016.
  9. Chinnaiyan, K.M. and G.L. Raff, Coronary CT Angiography in the Emergency Department: Current Status. Curr Treat Options Cardiovasc Med, 2016. 18(10): p. 62.
  10. Curzen, N.P., et al., Does the Routine Availability of CT-Derived FFR Influence Management of Patients With Stable Chest Pain Compared to CT Angiography Alone?: The FFRCT RIPCORD Study. JACC Cardiovasc Imaging, 2016. 9(10): p. 1188-1194.
  11. Dai, N., et al., Enhanced diagnostic utility achieved by myocardial blood analysis: A meta-analysis of noninvasive cardiac imaging in the detection of functional coronary artery disease. Int J Cardiol, 2016. 221: p. 665-73.
  12. Danad, I., et al., Diagnostic performance of cardiac imaging methods to diagnose ischaemia-causing coronary artery disease when directly compared with fractional flow reserve as a reference standard: a meta-analysis. Eur Heart J, 2016.
  13. den Harder, A.M., et al., New horizons in cardiac CT. Clin Radiol, 2016.
  14. Ding, A., et al., Diagnostic performance of noninvasive fractional flow reserve derived from coronary computed tomography angiography in ischemia-causing coronary stenosis: a meta-analysis. Jpn J Radiol, 2016. 34(12): p. 795-808.
  15. Douglas, P.S., et al., 1-Year Outcomes of FFRCT-Guided Care in Patients With Suspected Coronary Disease: The PLATFORM Study. J Am Coll Cardiol, 2016. 68(5): p. 435-45.
  16. Dweck, M.R., et al.,Imaging of coronary atherosclerosis – evolution towards new treatment strategies. Nat Rev Cardiol, 2016. 13(9): p. 533-48.
  17. Eftekhari, A., et al., Fractional flow reserve derived from coronary computed tomography angiography: diagnostic performance in hypertensive and diabetic patients. Eur Heart J Cardiovasc Imaging, 2016.
  18. Ferencik, M., et al.,Highly sensitive troponin and coronary computed tomography angiography in the evaluation of suspected acute coronary syndrome in the emergency department. Eur Heart J, 2016. 37(30): p. 2397-405.
  19. Fordyce, C.B. and P.S. Douglas, Optimal non-invasive imaging test selection for the diagnosis of ischaemic heart disease. Heart, 2016. 102(7): p. 555-64.
  20. Gaemperli, O., et al., The year in cardiology 2015: imaging. Eur Heart J, 2016. 37(8): p. 667-75.
  21. Gaur, S., et al., Coronary plaque quantification and fractional flow reserve by coronary computed tomography angiography identify ischaemia-causing lesions. Eur Heart J, 2016. 37(15): p. 1220-7.
  22. Gaur, S., et al., FFR Derived From Coronary CT Angiography in Nonculprit Lesions of Patients With Recent STEMI. JACC Cardiovasc Imaging, 2016.
  23. Han, D., et al., Relationship Between Endothelial Wall Shear Stress and High-Risk Atherosclerotic Plaque Characteristics for Identification of Coronary Lesions That Cause Ischemia: A Direct Comparison With Fractional Flow Reserve. J Am Heart Assoc, 2016. 5(12).
  24. Hecht, H.S., J. Narula, and W.F. Fearon, Fractional Flow Reserve and Coronary Computed Tomographic Angiography: A Review and Critical Analysis. Circ Res, 2016. 119(2): p. 300-16.
  25. Hulten, E., R. Blankstein, and M.F. Di Carli, The value of noninvasive computed tomography derived fractional flow reserve in our current approach to the evaluation of coronary artery stenosis. Curr Opin Cardiol, 2016. 31(6): p. 970-976.
  26. Hwang, D., J.M. Lee, and B.K. Koo, Physiologic Assessment of Coronary Artery Disease: Focus on Fractional Flow Reserve. Korean J Radiol, 2016. 17(3): p. 307-20.
  27. Kawaji, T., et al., Feasibility and diagnostic performance of fractional flow reserve measurement derived from coronary computed tomography angiography in real clinical practice. Int J Cardiovasc Imaging, 2016.
  28. Kawaji, T., et al., Diagnosis of functional ischemia in a right coronary artery with anomalous aortic origin. J Cardiovasc Comput Tomogr, 2016. 10(2): p. 188-90.
  29. Ko, B.S., et al., Diagnostic Performance of Transluminal Attenuation Gradient and Noninvasive Fractional Flow Reserve Derived from 320-Detector Row CT Angiography to Diagnose Hemodynamically Significant Coronary Stenosis: An NXT Substudy. Radiology, 2016. 279(1): p. 75-83.
  30. Koo, H.J., et al., CT-based myocardial ischemia evaluation: quantitative angiography, transluminal attenuation gradient, myocardial perfusion, and CT-derived fractional flow reserve. Int J Cardiovasc Imaging, 2016. 32 Suppl 1: p. 1-19.
  31. Leber, W.A., Is FFR-CT a “game changer” in the diagnostic management of stable coronary artery disease? Herz, 2016. 41(5): p. 398-404.
  32. Lee, J.H., et al., Multimodality Imaging in Coronary Artery Disease: Focus on Computed Tomography. J Cardiovasc Ultrasound, 2016. 24(1): p. 7-17.
  33. Mester, A., et al., CT Determination of Fractional Flow Reserve in Coronary Lesions. Journal of Interdisciplinary Medicine, 2016. 1(3): p. 237-241.
  34. Nakanishi, R. and M.J. Budoff, Noninvasive FFR derived from coronary CT angiography in the management of coronary artery disease: technology and clinical update. Vasc Health Risk Manag, 2016. 12: p. 269-78.
  35. Nakazato, R., et al., Additive diagnostic value of atherosclerotic plaque characteristics to non-invasive FFR for identification of lesions causing ischaemia: results from a prospective international multicentre trial. EuroIntervention, 2016. 12(4): p. 473-81.
  36. Norgaard, B.L., et al., Clinical Use of Coronary CTA-Derived FFR for Decision-Making in Stable CAD. JACC Cardiovasc Imaging, 2016.
  37. Norgaard, B.L., et al., Coronary Computed Tomography Angiography Derived Fractional Flow Reserve and Plaque Stress. Curr Cardiovasc Imaging Rep, 2016. 9: p. 2.
  38. Nozue, T., et al., Effects of alogliptin on fractional flow reserve evaluated by coronary computed tomography angiography in patients with type 2 diabetes: Rationale and design of the TRACT study. J Cardiol, 2016.
  39. Osawa, K., et al., Coronary lesion characteristics with mismatch between fractional flow reserve derived from CT and invasive catheterization in clinical practice. Heart Vessels, 2016.
  40. Packard, R.R., et al., Fractional flow reserve by computerized tomography and subsequent coronary revascularization. Eur Heart J Cardiovasc Imaging, 2016.
  41. Panchal, H.B., et al., Fractional flow reserve using computed tomography for assessing coronary artery disease: a meta-analysis. J Cardiovasc Med (Hagerstown), 2016. 17(9): p. 694-700.
  42. Pang, C.L., et al., Determining the haemodynamic significance of arterial stenosis: the relationship between CT angiography, computational fluid dynamics, and non-invasive fractional flow reserve. Clin Radiol, 2016.
  43. Pontone, G., et al.,Rationale and design of the PERFECTION (comparison between stress cardiac computed tomography PERfusion versus Fractional flow rEserve measured by Computed Tomography angiography In the evaluation of suspected cOroNary artery disease) prospective study. J Cardiovasc Comput Tomogr, 2016. 10(4): p. 330-4.
  44. Pontone, G., et al.,Fractional flow reserve: lessons from PLATFORM and future perspectives. Minerva Cardioangiol, 2016.
  45. Pontone, G., et al.,The New Frontier of Cardiac Computed Tomography Angiography: Fractional Flow Reserve and Stress Myocardial Perfusion. Curr Treat Options Cardiovasc Med, 2016. 18(12): p. 74.
  46. Rizvi, A., et al., Rationale and Design of the CREDENCE Trial: computed TomogRaphic evaluation of atherosclerotic DEtermiNants of myocardial IsChEmia. BMC Cardiovasc Disord, 2016. 16(1): p. 190.
  47. Rizvi, A., et al., Fractional Flow Reserve Measurement by Coronary Computed Tomography Angiography: A Review with Future Directions. Cardiovascular Innovations and Applications, 2016. 2(1): p. 125-135.
  48. Rodriguez-Granillo, G.A., R. Campisi, and P. Carrascosa, Noninvasive Cardiac Imaging in Patients with Known and Suspected Coronary Artery Disease: What is in it for the Interventional Cardiologist? Curr Cardiol Rep, 2016. 18(1): p. 3.
  49. Sankaran, S., et al., Uncertainty quantification in coronary blood flow simulations: Impact of geometry, boundary conditions and blood viscosity. J Biomech, 2016.
  50. Secchi, F., et al., Fractional flow reserve based on computed tomography: an overview. European Heart Journal, 2016: p. E49-E56.
  51. Tanaka, K., et al., Comparison Between Non-invasive (Coronary Computed Tomography Angiography Derived) and Invasive-Fractional Flow Reserve in Patients with Serial Stenoses Within One Coronary Artery: A NXT Trial substudy. Ann Biomed Eng, 2016. 44(2): p. 580-9.
  52. Wu, W., et al., Noninvasive fractional flow reserve derived from coronary computed tomography angiography for identification of ischemic lesions: a systematic review and meta-analysis. Sci Rep, 2016. 6: p. 29409.
  53. Zimmermann, F.M., et al., Non-invasive FFRCT revealing severe inducible ischaemia in an anomalous right coronary artery. Eur Heart J, 2016.

2017

  1. HeartFlow FFRCT for estimating fractional flow reserve from coronary CT angiography. National Institute for Health and Care Excellence (NICE), 2017.
  2. Coronary Computed Tomography Angiography With Selective Noninvasive Fractional Flow Reserve. BlueCross BlueShield Association, 2017: p. 1-19.
  3. Baskaran, L., et al., Dense calcium and lesion-specific ischemia: A comparison of CCTA with fractional flow reserve. Atherosclerosis, 2017. 260: p. 163-168.
  4. Benton, S.M., Jr., et al., Noninvasive Derivation of Fractional Flow Reserve From Coronary Computed Tomographic Angiography: A Review. J Thorac Imaging, 2017.
  5. Cademartiri, F., et al., Myocardial blood flow quantification for evaluation of coronary artery disease by computed tomography. Cardiovasc Diagn Ther, 2017. 7(2): p. 129-150.
  6. Cavalcante, R., et al., Non-invasive Heart Team assessment of multivessel coronary disease with coronary computed tomography angiography based on SYNTAX score II treatment recommendations: design and rationale of the randomised SYNTAX III Revolution trial. EuroIntervention, 2017. 12(16): p. 2001-2008.
  7. Chinnaiyan, K.M., et al., Rationale, design and goals of the HeartFlow assessing diagnostic value of non-invasive FFRCT in Coronary Care (ADVANCE) registry. J Cardiovasc Comput Tomogr, 2017. 11(1): p. 62-67.
  8. Coenen, A., et al.,Integrating CT Myocardial Perfusion and CT-FFR in the Work-Up of Coronary Artery Disease. JACC Cardiovasc Imaging, 2017. 10(7): p. 760-770.
  9. Colleran, R., et al., An FFRCT diagnostic strategy versus usual care in patients with suspected coronary artery disease planned for invasive coronary angiography at German sites: one-year results of a subgroup analysis of the PLATFORM (Prospective Longitudinal Trial of FFRCT: Outcome and Resource Impacts) study. Open Heart, 2017. 4(1).
  10. Collet, C., et al., Integration of non-invasive functional assessments with anatomical risk stratification in complex coronary artery disease: the non-invasive functional SYNTAX score. Cardiovasc Diagn Ther, 2017. 7(2): p. 151-158.
  11. Cook, C.M., et al., Diagnostic Accuracy of Computed Tomography-Derived Fractional Flow Reserve : A Systematic Review. JAMA Cardiol, 2017. 2(7): p. 803-810.
  12. Fairbairn, T.A., Fractional Flow ReserveCT (FFRCT). European Heart Journal, 2017. 38(24): p. 1867-1869.
  13. Grover, R., et al., Coronary lumen volume to myocardial mass ratio in primary microvascular angina. J Cardiovasc Comput Tomogr, 2017. 11(6): p. 423-428.
  14. Hulten, E.A., Does FFRCT have proven utility as a gatekeeper prior to invasive angiography? J Nucl Cardiol, 2017. 24(5): p. 1619-1625.
  15. Ihdayhid, A.R., A. White, and B. Ko, Assessment of Serial Coronary Stenoses With Noninvasive Computed Tomography-Derived Fractional Flow Reserve and Treatment Planning Using a Novel Virtual Stenting Application. JACC Cardiovasc Interv, 2017. 10(24): p. e223-e225.
  16. Jeremias, A., A.J. Kirtane, and G.W. Stone, A Test in Context: Fractional Flow Reserve: Accuracy, Prognostic Implications, and Limitations. J Am Coll Cardiol, 2017. 69(22): p. 2748-2758.
  17. Jorgensen, M.E., et al., Functional Testing or Coronary Computed Tomography Angiography in Patients With Stable Coronary Artery Disease. J Am Coll Cardiol, 2017. 69(14): p. 1761-1770.
  18. Kueh, S.H., M. Boroditsky, and J. Leipsic, Fractional flow reserve computed tomography in the evaluation of coronary artery disease. Cardiovasc Diagn Ther, 2017.
  19. Kueh, S.H., et al., Fractional flow reserve derived from coronary computed tomography angiography reclassification rate using value distal to lesion compared to lowest value. J Cardiovasc Comput Tomogr, 2017. 11(6): p. 462-467.
  20. Lu, M.T., et al., Noninvasive FFR Derived From Coronary CT Angiography. Management and Outcomes in the PROMISE Trial, 2017.
  21. Mangla, A., et al., Cardiac Imaging in the Diagnosis of Coronary Artery Disease. Curr Probl Cardiol, 2017. 42(10): p. 316-366.
  22. Moller Jensen, J., et al., Computed tomography derived fractional flow reserve testing in stable patients with typical angina pectoris: influence on downstream rate of invasive coronary angiography. Eur Heart J Cardiovasc Imaging, 2017.
  23. Nagaraja, V., et al., Change in angiogram-derived management strategy of patients with chest pain when some FFR data are available: How consistent is the effect? Cardiovasc Revasc Med, 2017.
  24. Nakanishi, R., et al., The diagnostic performance of SPECT-MPI to predict functional significant coronary artery disease by fractional flow reserve derived from CCTA (FFRCT): sub-analysis from ACCURACY and VCT001 studies. Int J Cardiovasc Imaging, 2017. 33(12): p. 2067-2072.
  25. Norgaard, B.L., et al., Myocardial Perfusion Imaging Versus Computed Tomography Angiography-Derived Fractional Flow Reserve Testing in Stable Patients With Intermediate-Range Coronary Lesions: Influence on Downstream Diagnostic Workflows and Invasive Angiography Findings. J Am Heart Assoc, 2017. 6(8).
  26. Norgaard, B.L., et al., Coronary CT Angiography Derived Fractional Flow Reserve: The Game Changer in Noninvasive Testing. Curr Cardiol Rep, 2017. 19(11): p. 112.
  27. Onuma, Y., et al., Long-term serial non-invasive multislice computed tomography angiography with functional evaluation after coronary implantation of a bioresorbable everolimus-eluting scaffold: the ABSORB cohort B MSCT substudy. Eur Heart J Cardiovasc Imaging, 2017. 18(8): p. 870-879.
  28. Otake, H., et al., Noninvasive Fractional Flow Reserve Derived From Coronary Computed Tomography Angiography- Is This Just Another New Diagnostic Test or the Long-Awaited Game Changer? Circ J, 2017. 81(8): p. 1085-1093.
  29. Patel, M.R., et al.,ACC / AATS / AHA / ASE / ASNC / SCAI / SCCT / STS 2017 Appropriate Use Criteria for Coronary Revascularization in Patients With Stable Ischemic Heart Disease: A Report of the American College of Cardiology Appropriate Use Criteria Task Force, American Association for Thoracic Surgery, American Heart Association, American Society of Echocardiography, American Society of Nuclear Cardiology, Society for Cardiovascular Angiography and Interventions, Society of Cardiovascular Computed Tomography, and Society of Thoracic Surgeons. J Am Coll Cardiol, 2017.
  30. Rabbat, M.G., et al., Interpreting results of coronary computed tomography angiography-derived fractional flow reserve in clinical practice. J Cardiovasc Comput Tomogr, 2017. 11(5): p. 383-388.
  31. Raff, G.L., U. Hoffmann, and J.E. Udelson, Trials of Imaging Use in the Emergency Department for Acute Chest Pain. JACC Cardiovasc Imaging, 2017. 10(3): p. 338-349.
  32. Rajani, R., et al., Non-invasive fractional flow reserve using computed tomographic angiography: where are we now and where are we going? Heart, 2017. 103(15): p. 1216-1222.
  33. Rajiah, P. and S. Abbara, CT Coronary Imaging – A Fast evolving World. Qjm, 2017.
  34. Rizvi, A., et al., Diffuse coronary artery disease among other atherosclerotic plaque characteristics by coronary computed tomography angiography for predicting coronary vessel-specific ischemia by fractional flow reserve. Atherosclerosis, 2017.258: p. 145-151.
  35. Shah, T., et al., Practical Considerations of Fractional Flow Reserve Utilization to Guide Revascularization. Curr Treat Options Cardiovasc Med, 2017. 19(2): p. 13.
  36. Sigurdsson, G., Improved Precision of Initial Chest Pain Evaluation With Fractional Flow Reserve Computed Tomography. J Am Heart Assoc, 2017. 6(8).
  37. Sonck, J., et al., Non-invasive planning of complex coronary artery disease using a novel Interactive Planner for PCI. EuroIntervention, 2017.
  38. Tan, X.W., et al., Combined diagnostic performance of coronary computed tomography angiography and computed tomography derived fractional flow reserve for the evaluation of myocardial ischemia: A meta-analysis. Int J Cardiol, 2017. 236: p. 100-106.
  39. Taylor, C.A., et al., Effect of the ratio of coronary arterial lumen volume to left ventricle myocardial mass derived from coronary CT angiography on fractional flow reserve. J Cardiovasc Comput Tomogr, 2017. 11(6): p. 429-436.
  40. Tesche, C., et al., Coronary CT Angiography-derived Fractional Flow Reserve. Radiology, 2017. 285(1): p. 17-33.
  41. Timmis, A. and C.A. Roobottom, National Institute for Health and Care Excellence updates the stable chest pain guideline with radical changes to the diagnostic paradigm. Heart, 2017. 103(13): p. 982-986.
  42. Yoo, S.M., et al., The Expanding Role of Computed Tomography Angiography in the Evaluation of Atherosclerotic Coronary Artery Disease. J Korean Soc Radiol, 2017. 77(6): p. 353-366.

2018

  1. Ahmadi, A., et al., Lesion-Specific and Vessel-Related Determinants of Fractional Flow Reserve Beyond Coronary Artery Stenosis. JACC Cardiovasc Imaging, 2018. 11(4): p. 521-530.
  2. Alfakih, K., J. Byrne, and M. Monaghan, CT coronary angiography: a paradigm shift for functional imaging tests. Open Heart, 2018. 5(1): p. e000754.
  3. Baskaran, L., C.K. Zarins, and J.K. Min, Cardiac CTA Fractional Flow Reserve, in Coronary Artery CTA: A Case-Based Atlas, C. Smuclovisky, Editor. 2018, Springer International Publishing: Cham. p. 203-222.
  4. Beecy, A., et al., Association between epicardial fat volume and fractional flow reserve: An analysis of the determination of fractional flow reserve (DeFACTO) study. Clin Imaging, 2018. 51: p. 30-34.
  5. Benton, S.M., Jr., et al., Noninvasive Derivation of Fractional Flow Reserve From Coronary Computed Tomographic Angiography: A Review. J Thorac Imaging, 2018. 33(2): p. 88-96.
  6. Collet, C., et al., Left main coronary artery disease: pathophysiology, diagnosis, and treatment. Nat Rev Cardiol, 2018.
  7. Collet, C., et al., Impact of Coronary Remodeling on Fractional Flow Reserve. Circulation, 2018. 137(7): p. 747-749.
  8. Dey, D., et al., Integrated prediction of lesion-specific ischaemia from quantitative coronary CT angiography using machine learning: a multicentre study. Eur Radiol, 2018.
  9. Giannopoulos, A.A. and O. Gaemperli, Hybrid Imaging in Ischemic Heart Disease. Rev Esp Cardiol (Engl Ed), 2018.
  10. Kerut, E.K. and M. Turner, Fractional flow reserve-CT assessment of coronary stenosis. Echocardiography, 2018.
  11. Kishi, S., et al., Fractional Flow Reserve Estimated at Coronary CT Angiography in Intermediate Lesions: Comparison of Diagnostic Accuracy of Different Methods to Determine Coronary Flow Distribution. Radiology, 2018. 287(1): p. 76-84.
  12. Kitabata, H., et al., Incidence and predictors of lesion-specific ischemia by FFRCT: Learnings from the international ADVANCE registry. J Cardiovasc Comput Tomogr, 2018. 12(2): p. 95-100.
  13. Lee, J.M., et al., Identification of High-Risk Plaques Destined to Cause Acute Coronary Syndrome Using Coronary Computed Tomographic Angiography and Computational Fluid Dynamics. JACC Cardiovasc Imaging, 2018.
  14. Moller Jensen, J., et al., Computed tomography derived fractional flow reserve testing in stable patients with typical angina pectoris: influence on downstream rate of invasive coronary angiography. Eur Heart J Cardiovasc Imaging, 2018. 19(4): p. 405-414.
  15. Nakanishi, R., et al., Automated estimation of image quality for coronary computed tomographic angiography using machine learning. Eur Radiol, 2018.
  16. Okonogi, T. and T. Kawasaki, Clinical Utility of Fractional Flow Reserve on Computed Tomography in Left Main Trunk Disease. Circ J, 2018. 82(3): p. 930-931.
  17. Rother, J., et al., Comparison of invasively measured FFR with FFR derived from coronary CT angiography for detection of lesion-specific ischemia: Results from a PC-based prototype algorithm. J Cardiovasc Comput Tomogr, 2018. 12(2): p. 101-107.
  18. Schuijf, J.D., et al., Fractional flow reserve and myocardial perfusion by computed tomography: a guide to clinical application. Eur Heart J Cardiovasc Imaging, 2018. 19(2): p. 127-135.
  19. Uzu, K., et al., Lumen Boundaries Extracted from Coronary Computed Tomography Angiography on Computed Fractional Flow Reserve (FFRCT): Validation with Optical Coherence Tomography. EuroIntervention, 2018.
  20. Xia, G., et al., Diagnostic efficacy of fractional flow reserve with coronary angiography in dual-source computed tomography scanner. Acta Cardiol, 2018. 73(1): p. 76-83.
  21. Yang, D.H., et al., Incremental Value of Subtended Myocardial Mass for Identifying FFR-Verified Ischemia Using Quantitative CT Angiography: Comparison With Quantitative Coronary Angiography and CT-FFR. JACC Cardiovasc Imaging, 2018.
  22. Zreik, M., et al., Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis. Med Image Anal, 2018. 44: p. 72-85.
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The information provided by the HeartFlow Analysis is intended to be used in conjunction with the patient’s clinical history, symptoms, and other diagnostic tests, as well as the clinician’s professional judgement. The HeartFlow Analysis may not be appropriate for all patients. See indications for use for more information. The HeartFlow Analysis, featuring the FFRCT Analysis, RoadMapTM Analysis, Plaque Analysis, and HeartFlow Planner, has received FDA Clearance in the United States of America. The FFRCT Analysis and HeartFlow Planner are CE Marked in Europe and the United Kingdom and approved in Japan and Canada. The HeartFlow Analysis, featuring FFRCT Analysis, RoadMapTM Analysis, Plaque Analysis, and HeartFlow Planner, is commercially available in the United States. The FFRCT Analysis and HeartFlow Planner are commercially available in the United Kingdom. The FFRCT Analysis is also commercially available in Europe, Japan, and Canada.

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HeartFlow FFRCT 分析は、有資格の臨床医による臨床的に安定した症状のある冠状動脈疾患患者への使用を目的とした個別化された心臓検査です。 HeartFlow Analysis によって提供される情報は、資格のある臨床医が患者の病歴、症状、その他の診断検査、および臨床医の専門的判断と組み合わせて使用​​することを目的としています。

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The HeartFlow FFRCT Analysis is a personalized cardiac test indicated for use in clinically stable symptomatic patients with coronary artery disease by qualified clinicians. The information provided by the HeartFlow Analysis is intended to be used by qualified clinicians in conjunction with the patient’s history, symptoms, and other diagnostic tests, as well as the clinician’s professional judgement.

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Campbell Rogers, M.D., F.A.C.C.

Executive Vice President and Chief Medical Officer

Campbell brings a wealth of experience to HeartFlow, where he serves as the Chief Medical Officer. Prior to joining HeartFlow, he was the Chief Scientific Officer and Global Head of Research and Development at Cordis Corporation, Johnson & Johnson, where he was responsible for leading investments and research in cardiovascular devices. Prior to Cordis, he was Associate Professor of Medicine at Harvard Medical School and the Harvard-M.I.T. Division of Health Sciences and Technology, and Director of the Cardiac Catheterization and Experimental Cardiovascular Interventional Laboratories at Brigham and Women’s Hospital. He served as Principal Investigator for numerous interventional cardiology device, diagnostic, and pharmacology trials, is the author of numerous journal articles, chapters, and books in the area of coronary artery and other cardiovascular diseases, and was the recipient of research grant awards from the NIH and AHA.

He received his A.B. from Harvard College and his M.D. from Harvard Medical School.

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