Connection

U. Schoepf to Fractional Flow Reserve, Myocardial

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This is a "connection" page, showing publications U. Schoepf has written about Fractional Flow Reserve, Myocardial.
U. Schoepf
Connection Strength
11.801
Fractional Flow Reserve, Myocardial
  1. Influence of coronary stenosis location on diagnostic performance of machine learning-based fractional flow reserve from CT angiography. J Cardiovasc Comput Tomogr. 2021 Nov-Dec; 15(6):492-498.
    View in: PubMed
    Score: 0.651
  2. Influence of Coronary Calcium on Diagnostic Performance of Machine Learning CT-FFR: Results From MACHINE Registry. JACC Cardiovasc Imaging. 2020 03; 13(3):760-770.
    View in: PubMed
    Score: 0.575
  3. FFR-CT and CT Myocardial?Perfusion?Imaging: Friends or Foes? JACC Cardiovasc Imaging. 2019 12; 12(12):2472-2474.
    View in: PubMed
    Score: 0.562
  4. Prognostic value of CT myocardial perfusion imaging and CT-derived fractional flow reserve for major adverse cardiac events in patients with coronary artery disease. J Cardiovasc Comput Tomogr. 2019 May - Jun; 13(3):26-33.
    View in: PubMed
    Score: 0.555
  5. Coronary CT Angiography-derived Fractional Flow Reserve: Machine Learning Algorithm versus Computational Fluid Dynamics Modeling. Radiology. 2018 Jul; 288(1):64-72.
    View in: PubMed
    Score: 0.523
  6. Coronary Computed Tomography-Based Fractional Flow Reserve: A Rapidly Developing Field. JAMA Cardiol. 2018 01 01; 3(1):87.
    View in: PubMed
    Score: 0.514
  7. Coronary CT Angiography-derived Fractional Flow Reserve. Radiology. 2017 10; 285(1):17-33.
    View in: PubMed
    Score: 0.505
  8. Coronary Computed Tomographic Angiography-Derived Fractional Flow Reserve for Therapeutic Decision Making. Am J Cardiol. 2017 Dec 15; 120(12):2121-2127.
    View in: PubMed
    Score: 0.504
  9. Coronary Computed Tomographic Angiography-Derived Fractional Flow Reserve Based on Machine Learning for Risk Stratification of Non-Culprit Coronary Narrowings in Patients with Acute Coronary Syndrome. Am J Cardiol. 2017 Oct 15; 120(8):1260-1266.
    View in: PubMed
    Score: 0.498
  10. Comparison of Coronary Computed Tomography Angiography-Derived vs Invasive Fractional Flow Reserve Assessment: Meta-Analysis with Subgroup Evaluation of Intermediate Stenosis. Acad Radiol. 2016 11; 23(11):1402-1411.
    View in: PubMed
    Score: 0.470
  11. Coronary CT angiography derived morphological and functional quantitative plaque markers correlated with invasive fractional flow reserve for detecting hemodynamically significant stenosis. J Cardiovasc Comput Tomogr. 2016 May-Jun; 10(3):199-206.
    View in: PubMed
    Score: 0.453
  12. Coronary CTA With AI-QCT Interpretation: Comparison With Myocardial Perfusion Imaging for Detection of Obstructive Stenosis Using Invasive Angiography as Reference Standard. AJR Am J Roentgenol. 2022 09; 219(3):407-419.
    View in: PubMed
    Score: 0.173
  13. Impact of machine-learning-based coronary computed tomography angiography-derived fractional flow reserve on decision-making in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement. Eur Radiol. 2022 Sep; 32(9):6008-6016.
    View in: PubMed
    Score: 0.172
  14. Functional CAD-RADS using FFRCT on therapeutic management and prognosis in patients with coronary artery disease. Eur Radiol. 2022 Aug; 32(8):5210-5221.
    View in: PubMed
    Score: 0.172
  15. [Morphological and functional diagnostics of coronary artery disease by computed tomography]. Herz. 2023 Feb; 48(1):39-47.
    View in: PubMed
    Score: 0.171
  16. One-year outcomes of CCTA alone versus machine learning-based FFRCT for coronary artery disease: a single-center, prospective study. Eur Radiol. 2022 Aug; 32(8):5179-5188.
    View in: PubMed
    Score: 0.171
  17. AI Evaluation of Stenosis on Coronary CTA, Comparison With Quantitative Coronary Angiography and Fractional Flow Reserve: A CREDENCE Trial Substudy. JACC Cardiovasc Imaging. 2023 02; 16(2):193-205.
    View in: PubMed
    Score: 0.171
  18. Stable patients with suspected myocardial ischemia: comparison of machine-learning computed tomography-based fractional flow reserve and stress perfusion cardiovascular magnetic resonance imaging to detect myocardial ischemia. BMC Cardiovasc Disord. 2022 02 05; 22(1):34.
    View in: PubMed
    Score: 0.171
  19. Additive value of epicardial adipose tissue quantification to coronary CT angiography-derived plaque characterization and CT fractional flow reserve for the prediction of lesion-specific ischemia. Eur Radiol. 2022 Jun; 32(6):4243-4252.
    View in: PubMed
    Score: 0.170
  20. Prognostic value of epicardial adipose tissue volume in combination with coronary plaque and flow assessment for the prediction of major adverse cardiac events. Eur J Radiol. 2022 Mar; 148:110157.
    View in: PubMed
    Score: 0.170
  21. Coronary CT Fractional Flow Reserve before Transcatheter Aortic Valve Replacement: Clinical Outcomes. Radiology. 2022 01; 302(1):50-58.
    View in: PubMed
    Score: 0.167
  22. Non-invasive fractional flow reserve (FFRCT) in the evaluation of acute chest pain - Concepts and first experiences. Eur J Radiol. 2021 May; 138:109633.
    View in: PubMed
    Score: 0.160
  23. Serial coronary CT angiography-derived fractional flow reserve and plaque progression can predict long-term outcomes of coronary artery disease. Eur Radiol. 2021 Sep; 31(9):7110-7120.
    View in: PubMed
    Score: 0.160
  24. Coronary plaque assessment of Vasodilative capacity by CT angiography effectively estimates fractional flow reserve. Int J Cardiol. 2021 05 15; 331:307-315.
    View in: PubMed
    Score: 0.159
  25. Stress Myocardial Perfusion Imaging vs Coronary Computed Tomographic Angiography for Diagnosis of Invasive Vessel-Specific Coronary Physiology: Predictive Modeling Results From the Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia (CREDENCE) Trial. JAMA Cardiol. 2020 12 01; 5(12):1338-1348.
    View in: PubMed
    Score: 0.157
  26. Impact of machine learning-based coronary computed tomography angiography fractional flow reserve on treatment decisions and clinical outcomes in patients with suspected coronary artery disease. Eur Radiol. 2020 Nov; 30(11):5841-5851.
    View in: PubMed
    Score: 0.152
  27. Correlation of machine learning computed tomography-based fractional flow reserve with instantaneous wave free ratio to detect hemodynamically significant coronary stenosis. Clin Res Cardiol. 2020 Jun; 109(6):735-745.
    View in: PubMed
    Score: 0.146
  28. Diagnostic Performance of Machine Learning Based CT-FFR in Detecting Ischemia in Myocardial Bridging and Concomitant Proximal Atherosclerotic Disease. Can J Cardiol. 2019 11; 35(11):1523-1533.
    View in: PubMed
    Score: 0.144
  29. CT FFR for Ischemia-Specific CAD With?a?New Computational Fluid Dynamics Algorithm: A Chinese Multicenter Study. JACC Cardiovasc Imaging. 2020 04; 13(4):980-990.
    View in: PubMed
    Score: 0.144
  30. Impact of Coronary Computerized Tomography Angiography-Derived Plaque Quantification and Machine-Learning Computerized Tomography Fractional Flow Reserve on Adverse Cardiac Outcome. Am J Cardiol. 2019 11 01; 124(9):1340-1348.
    View in: PubMed
    Score: 0.143
  31. Effect of Tube Voltage on Diagnostic Performance of Fractional Flow Reserve Derived From Coronary CT Angiography With Machine Learning: Results From the MACHINE Registry. AJR Am J Roentgenol. 2019 08; 213(2):325-331.
    View in: PubMed
    Score: 0.141
  32. Diagnostic performance of fractional flow reserve derived from coronary CT angiography for detection of lesion-specific ischemia: A multi-center study and meta-analysis. Eur J Radiol. 2019 Jul; 116:90-97.
    View in: PubMed
    Score: 0.141
  33. Machine Learning Using CT-FFR Predicts Proximal Atherosclerotic Plaque Formation Associated With LAD Myocardial Bridging. JACC Cardiovasc Imaging. 2019 08; 12(8 Pt 1):1591-1593.
    View in: PubMed
    Score: 0.140
  34. Coronary CT angiography-derived plaque quantification with artificial intelligence CT fractional flow reserve for the identification of lesion-specific ischemia. Eur Radiol. 2019 May; 29(5):2378-2387.
    View in: PubMed
    Score: 0.137
  35. Comparison of the Diagnostic Performance of Coronary Computed Tomography Angiography-Derived Fractional Flow Reserve in Patients With Versus Without Diabetes Mellitus (from the MACHINE Consortium). Am J Cardiol. 2019 02 15; 123(4):537-543.
    View in: PubMed
    Score: 0.137
  36. Fractional flow reserve derived from CCTA may have a prognostic role in myocardial bridging. Eur Radiol. 2019 Jun; 29(6):3017-3026.
    View in: PubMed
    Score: 0.136
  37. Artificial intelligence machine learning-based coronary CT fractional flow reserve (CT-FFRML): Impact of iterative and filtered back projection reconstruction techniques. J Cardiovasc Comput Tomogr. 2019 Nov - Dec; 13(6):331-335.
    View in: PubMed
    Score: 0.136
  38. Low CT temporal sampling rates result in a substantial underestimation of myocardial blood flow measurements. Int J Cardiovasc Imaging. 2019 Mar; 35(3):539-547.
    View in: PubMed
    Score: 0.135
  39. Diagnostic Accuracy of a Machine-Learning Approach to Coronary Computed Tomographic Angiography-Based Fractional Flow Reserve: Result From the MACHINE Consortium. Circ Cardiovasc Imaging. 2018 06; 11(6):e007217.
    View in: PubMed
    Score: 0.132
  40. Noninvasive Derivation of Fractional Flow Reserve From Coronary Computed Tomographic Angiography: A Review. J Thorac Imaging. 2018 Mar; 33(2):88-96.
    View in: PubMed
    Score: 0.130
  41. What is the optimal anatomic location for coronary artery pressure measurement at CT-derived FFR? J Cardiovasc Comput Tomogr. 2017 Sep - Oct; 11(5):397-403.
    View in: PubMed
    Score: 0.125
  42. FFR-Derived From?Coronary CT?Angiography Using Workstation-Based Approaches. JACC Cardiovasc Imaging. 2017 04; 10(4):497-498.
    View in: PubMed
    Score: 0.122
  43. 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 Jun 01; 236:100-106.
    View in: PubMed
    Score: 0.121
  44. Analysis of myocardial perfusion parameters in an ex-vivo porcine heart model using third generation dual-source CT. J Cardiovasc Comput Tomogr. 2017 Mar - Apr; 11(2):141-147.
    View in: PubMed
    Score: 0.121
  45. Letter by Baumann et al Regarding Article, "Fractional Flow Reserve and Coronary Computed Tomographic Angiography: A Review and Critical Analysis". Circ Res. 2016 09 02; 119(6):e106-7.
    View in: PubMed
    Score: 0.117
  46. [Computed tomography in patients with chronic stable angina : Fractional flow reserve measurement]. Herz. 2017 Feb; 42(1):51-57.
    View in: PubMed
    Score: 0.115
  47. Different Approaches for Coronary Computed Tomography Angiography-Derived Versus Invasive Fractional Flow Reserve Assessment. Am J Cardiol. 2016 Feb 01; 117(3):486.
    View in: PubMed
    Score: 0.111
  48. Comparison of quantitative stenosis characteristics at routine coronary computed tomography angiography with invasive fractional flow reserve for assessing lesion-specific ischemia. J Cardiovasc Comput Tomogr. 2015 Nov-Dec; 9(6):546-52.
    View in: PubMed
    Score: 0.109
  49. Diagnostic value of quantitative stenosis predictors with coronary CT angiography compared to invasive fractional flow reserve. Eur J Radiol. 2015 Aug; 84(8):1509-1515.
    View in: PubMed
    Score: 0.107
  50. A novel approach for fractional flow reserve derivation from coronary computed tomographic angiography. Coron Artery Dis. 2015 May; 26(3):279-80.
    View in: PubMed
    Score: 0.107
  51. Coronary CT angiography-derived fractional flow reserve correlated with invasive fractional flow reserve measurements--initial experience with a novel physician-driven algorithm. Eur Radiol. 2015 Apr; 25(4):1201-7.
    View in: PubMed
    Score: 0.103
  52. Comparison of diagnostic value of a novel noninvasive coronary computed tomography angiography method versus standard coronary angiography for assessing fractional flow reserve. Am J Cardiol. 2014 Nov 01; 114(9):1303-8.
    View in: PubMed
    Score: 0.102
  53. Magnetic resonance myocardial perfusion imaging at 3.0 Tesla for the identification of myocardial ischaemia: comparison with coronary catheter angiography and fractional flow reserve measurements. Eur Heart J Cardiovasc Imaging. 2013 Dec; 14(12):1174-80.
    View in: PubMed
    Score: 0.095
  54. Coronary CT angiography derived plaque markers correlated with invasive instantaneous flow reserve for detecting hemodynamically significant coronary stenoses. Eur J Radiol. 2020 Jan; 122:108744.
    View in: PubMed
    Score: 0.037
  55. Gender differences in the diagnostic performance of machine learning coronary CT angiography-derived fractional flow reserve -results from the MACHINE registry. Eur J Radiol. 2019 Oct; 119:108657.
    View in: PubMed
    Score: 0.036
  56. Fractional flow reserve derived by coronary computed tomography angiography : A?sophisticated analysis method for detecting hemodynamically significant coronary stenosis. Herz. 2017 Sep; 42(6):604-606.
    View in: PubMed
    Score: 0.030
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