Connection

U. Schoepf to Coronary Stenosis

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This is a "connection" page, showing publications U. Schoepf has written about Coronary Stenosis.
U. Schoepf
Connection Strength
14.418
Coronary Stenosis
  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: 0.611
  2. 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: 0.491
  3. 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: 0.473
  4. 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: 0.468
  5. Coronary Computed Tomography Angiography-Derived Plaque Quantification in Patients With Acute Coronary?Syndrome. Am J Cardiol. 2017 03 01; 119(5):712-718.
    View in: PubMed
    Score: 0.447
  6. Correlation and predictive value of aortic root calcification markers with coronary artery calcification and obstructive coronary artery disease. Radiol Med. 2017 Feb; 122(2):113-120.
    View in: PubMed
    Score: 0.446
  7. 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: 0.440
  8. Prognostic implications of coronary CT angiography-derived quantitative markers for the prediction of major adverse cardiac events. J Cardiovasc Comput Tomogr. 2016 Nov - Dec; 10(6):458-465.
    View in: PubMed
    Score: 0.437
  9. 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: 0.425
  10. Beyond stenosis detection: computed tomography approaches for determining the functional relevance of coronary artery disease. Radiol Clin North Am. 2015 Mar; 53(2):317-34.
    View in: PubMed
    Score: 0.391
  11. Computer-aided stenosis detection at coronary CT angiography: effect on performance of readers with different experience levels. Eur Radiol. 2015 Mar; 25(3):694-702.
    View in: PubMed
    Score: 0.386
  12. Detection of coronary artery stenosis with sub-milliSievert radiation dose by prospectively ECG-triggered high-pitch spiral CT angiography and iterative reconstruction. Eur Radiol. 2013 Nov; 23(11):2927-33.
    View in: PubMed
    Score: 0.352
  13. Influence of observer experience and training on proficiency in coronary CT angiography interpretation. Eur J Radiol. 2013 Aug; 82(8):1240-7.
    View in: PubMed
    Score: 0.348
  14. High-temporal resolution dual-energy computed tomography of the heart using a novel hybrid image reconstruction algorithm: initial experience. J Comput Assist Tomogr. 2011 Jan-Feb; 35(1):119-25.
    View in: PubMed
    Score: 0.297
  15. Evaluation of plaques and stenosis. Radiol Clin North Am. 2010 Jul; 48(4):729-44.
    View in: PubMed
    Score: 0.286
  16. [Coronary CT angiography using prospective ECG triggering: high diagnostic accuracy with low radiation dose]. Radiologe. 2010 Jun; 50(6):500-6.
    View in: PubMed
    Score: 0.285
  17. Adenosine-stress dynamic myocardial CT perfusion imaging: initial clinical experience. Invest Radiol. 2010 Jun; 45(6):306-13.
    View in: PubMed
    Score: 0.285
  18. Correlation of regional distribution and morphological pattern of calcification at CT coronary artery calcium scoring with non-calcified plaque formation and stenosis. Eur Radiol. 2010 Apr; 20(4):855-61.
    View in: PubMed
    Score: 0.273
  19. Noncalcified atherosclerotic plaque burden at coronary CT angiography: a better predictor of ischemia at stress myocardial perfusion imaging than calcium score and stenosis severity. AJR Am J Roentgenol. 2009 Aug; 193(2):410-8.
    View in: PubMed
    Score: 0.269
  20. Dual-energy CT of the heart for diagnosing coronary artery stenosis and myocardial ischemia-initial experience. Eur Radiol. 2008 Nov; 18(11):2414-24.
    View in: PubMed
    Score: 0.248
  21. Significant coronary artery stenosis: comparison on per-patient and per-vessel or per-segment basis at 64-section CT angiography. Radiology. 2007 Jul; 244(1):112-20.
    View in: PubMed
    Score: 0.233
  22. Ultra-high resolution photon-counting coronary CT angiography improves coronary stenosis quantification over a wide range of heart rates - A dynamic phantom study. Eur J Radiol. 2023 Apr; 161:110746.
    View in: PubMed
    Score: 0.172
  23. Diabetes, Atherosclerosis, and Stenosis by AI. Diabetes Care. 2023 02 01; 46(2):416-424.
    View in: PubMed
    Score: 0.171
  24. 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: 0.162
  25. 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: 0.162
  26. 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: 0.161
  27. [Morphological and functional diagnostics of coronary artery disease by computed tomography]. Herz. 2023 Feb; 48(1):39-47.
    View in: PubMed
    Score: 0.161
  28. 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: 0.160
  29. The effect of scan and patient parameters on the diagnostic performance of AI for detecting coronary stenosis on coronary CT angiography. Clin Imaging. 2022 Apr; 84:149-158.
    View in: PubMed
    Score: 0.160
  30. 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: 0.159
  31. 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: 0.159
  32. Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence. Open Heart. 2021 11; 8(2).
    View in: PubMed
    Score: 0.157
  33. 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: 0.150
  34. 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: 0.149
  35. Improved long-term prognostic value of coronary CT angiography-derived plaque measures and clinical parameters on adverse cardiac outcome using machine learning. Eur Radiol. 2021 Jan; 31(1):486-493.
    View in: PubMed
    Score: 0.144
  36. 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: 0.137
  37. 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: 0.137
  38. 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: 0.135
  39. 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: 0.135
  40. 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: 0.135
  41. 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: 0.128
  42. 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: 0.127
  43. 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: 0.127
  44. Diagnostic yield and accuracy of coronary CT angiography after abnormal nuclear myocardial perfusion imaging. Sci Rep. 2018 06 15; 8(1):9228.
    View in: PubMed
    Score: 0.124
  45. 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: 0.124
  46. Predictive value of coronary computed tomography angiography in asymptomatic individuals with diabetes mellitus: Systematic review and meta-analysis. J Cardiovasc Comput Tomogr. 2018 Jul - Aug; 12(4):320-328.
    View in: PubMed
    Score: 0.123
  47. 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: 0.122
  48. Diagnostic accuracy of low and high tube voltage coronary CT angiography using an X-ray tube potential-tailored contrast medium injection protocol. Eur Radiol. 2018 May; 28(5):2134-2142.
    View in: PubMed
    Score: 0.120
  49. Coronary CT Angiography-derived Fractional Flow Reserve. Radiology. 2017 10; 285(1):17-33.
    View in: PubMed
    Score: 0.118
  50. 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: 0.117
  51. FFR-Derived From?Coronary CT?Angiography Using Workstation-Based Approaches. JACC Cardiovasc Imaging. 2017 04; 10(4):497-498.
    View in: PubMed
    Score: 0.114
  52. 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: 0.113
  53. Global quantification of left ventricular myocardial perfusion at dynamic CT imaging: Prognostic value. J Cardiovasc Comput Tomogr. 2017 Jan - Feb; 11(1):16-24.
    View in: PubMed
    Score: 0.112
  54. Dynamic CT myocardial perfusion imaging. Eur J Radiol. 2016 Oct; 85(10):1893-1899.
    View in: PubMed
    Score: 0.109
  55. CAD-RADS(TM) Coronary Artery Disease - Reporting and Data System. An expert consensus document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Radiology (ACR) and the North American Society for Cardiovascular Imaging (NASCI). Endorsed by the American College of Cardiology. J Cardiovasc Comput Tomogr. 2016 Jul-Aug; 10(4):269-81.
    View in: PubMed
    Score: 0.108
  56. 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: 0.104
  57. Image quality, radiation dose, and diagnostic accuracy of prospectively ECG-triggered high-pitch coronary CT angiography at 70?kVp in a clinical setting: comparison with invasive coronary angiography. Eur Radiol. 2016 Mar; 26(3):797-806.
    View in: PubMed
    Score: 0.103
  58. 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: 0.102
  59. 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: 0.100
  60. 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: 0.100
  61. 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: 0.097
  62. Residents' performance in the interpretation of on-call "triple-rule-out" CT studies in patients with acute chest pain. Acad Radiol. 2014 Jul; 21(7):938-44.
    View in: PubMed
    Score: 0.095
  63. Global quantification of left ventricular myocardial perfusion at dynamic CT: feasibility in a multicenter patient population. AJR Am J Roentgenol. 2014 Aug; 203(2):W174-80.
    View in: PubMed
    Score: 0.094
  64. Predictive value of zero calcium score and low-end percentiles for the presence of significant coronary artery stenosis in stable patients with suspected coronary artery disease. Rofo. 2013 Aug; 185(8):726-32.
    View in: PubMed
    Score: 0.089
  65. Atherosclerotic plaque burden in cocaine users with acute chest pain: analysis by coronary computed tomography angiography. Atherosclerosis. 2013 Aug; 229(2):443-8.
    View in: PubMed
    Score: 0.088
  66. Coronary computed tomography and triple rule out CT in patients with acute chest pain and an intermediate cardiac risk for acute coronary syndrome: part 2: economic aspects. Eur J Radiol. 2013 Jan; 82(1):106-11.
    View in: PubMed
    Score: 0.083
  67. Coronary computed tomography and triple rule out CT in patients with acute chest pain and an intermediate cardiac risk profile. Part 1: impact on patient management. Eur J Radiol. 2013 Jan; 82(1):100-5.
    View in: PubMed
    Score: 0.082
  68. Evaluation of heavily calcified vessels with coronary CT angiography: comparison of iterative and filtered back projection image reconstruction. Radiology. 2011 Aug; 260(2):390-9.
    View in: PubMed
    Score: 0.077
  69. Iterative image reconstruction techniques: Applications for cardiac CT. J Cardiovasc Comput Tomogr. 2011 Jul-Aug; 5(4):225-30.
    View in: PubMed
    Score: 0.076
  70. Accuracy of coronary artery stenosis detection with CT versus conventional coronary angiography compared with composite findings from both tests as an enhanced reference standard. Eur Radiol. 2011 Sep; 21(9):1895-903.
    View in: PubMed
    Score: 0.076
  71. A clinical prediction rule for the diagnosis of coronary artery disease: validation, updating, and extension. Eur Heart J. 2011 Jun; 32(11):1316-30.
    View in: PubMed
    Score: 0.075
  72. Automated computer-aided stenosis detection at coronary CT angiography: initial experience. Eur Radiol. 2010 May; 20(5):1160-7.
    View in: PubMed
    Score: 0.068
  73. Comparison of dual-energy computed tomography of the heart with single photon emission computed tomography for assessment of coronary artery stenosis and of the myocardial blood supply. Am J Cardiol. 2009 Aug 01; 104(3):318-26.
    View in: PubMed
    Score: 0.067
  74. Images in cardiology: Dual-energy computed tomography imaging of myocardial infarction. Heart. 2009 Mar; 95(3):180.
    View in: PubMed
    Score: 0.065
  75. 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: 0.040
  76. Prognostic value of coronary atherosclerosis progression evaluated by coronary CT angiography in patients with stable angina. Eur Radiol. 2018 Mar; 28(3):1066-1076.
    View in: PubMed
    Score: 0.030
  77. 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: 0.028
  78. 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: 0.027
  79. Technical prerequisites and imaging protocols for dynamic and dual energy myocardial perfusion imaging. Eur J Radiol. 2015 Dec; 84(12):2401-10.
    View in: PubMed
    Score: 0.025
  80. Aortocoronary saphenous vein graft aneurysm causing high-gradient right ventricular outflow tract obstruction. Eur Heart J Cardiovasc Imaging. 2015 Jan; 16(1):117.
    View in: PubMed
    Score: 0.024
  81. In vitro evaluation of metallic coronary artery stents with 64-MDCT using an ECG-gated cardiac phantom: relationship between in-stent visualization, stent type, and heart rate. AJR Am J Roentgenol. 2010 Mar; 194(3):W256-62.
    View in: PubMed
    Score: 0.017
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Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.