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.


  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.


  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.


  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.


  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.


  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.


  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.
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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.