Connection

U. Schoepf to Coronary Artery Disease

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This is a "connection" page, showing publications U. Schoepf has written about Coronary Artery Disease.
U. Schoepf
Connection Strength
26.086
Coronary Artery Disease
  1. The Feasibility, Tolerability, Safety, and Accuracy of Low-radiation Dynamic Computed Tomography Myocardial Perfusion Imaging With Regadenoson Compared With Single-photon Emission Computed Tomography. J Thorac Imaging. 2021 Nov 01; 36(6):345-352.
    View in: PubMed
    Score: 0.494
  2. 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: 0.480
  3. A Brave New World: Toward Precision Phenotyping and Understanding of Coronary Artery Disease Using Radiomics Plaque Analysis. Radiology. 2021 04; 299(1):107-108.
    View in: PubMed
    Score: 0.470
  4. Evaluating a New Contrast Media Injection System in Coronary CT Angiography. Radiol Technol. 2021 Jan; 92(3):232-239.
    View in: PubMed
    Score: 0.466
  5. Automatic coronary calcium scoring in chest CT using a deep neural network in direct comparison with non-contrast cardiac CT: A validation study. Eur J Radiol. 2021 Jan; 134:109428.
    View in: PubMed
    Score: 0.463
  6. Machine Learning and Coronary Artery Calcium Scoring. Curr Cardiol Rep. 2020 07 09; 22(9):90.
    View in: PubMed
    Score: 0.451
  7. In-Hospital Cost Comparison of Triple-Rule-Out Computed Tomography Angiography Versus Standard of Care in Patients With Acute Chest Pain. J Thorac Imaging. 2020 May; 35(3):198-203.
    View in: PubMed
    Score: 0.445
  8. Accuracy of an Artificial Intelligence Deep Learning Algorithm Implementing a Recurrent Neural Network With Long Short-term Memory for the Automated Detection of Calcified Plaques From Coronary Computed Tomography Angiography. J Thorac Imaging. 2020 May; 35 Suppl 1:S49-S57.
    View in: PubMed
    Score: 0.445
  9. Evaluation of a Deep Learning-Based Automated CT Coronary Artery Calcium Scoring Algorithm. JACC Cardiovasc Imaging. 2020 02; 13(2 Pt 1):524-526.
    View in: PubMed
    Score: 0.431
  10. 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: 0.424
  11. Relationship Between Pregnancy Complications and Subsequent Coronary Artery Disease Assessed by Coronary Computed Tomographic Angiography in Black Women. Circ Cardiovasc Imaging. 2019 07; 12(7):e008754.
    View in: PubMed
    Score: 0.421
  12. Oracle of Our Time: Machine Learning for Predicting Cardiovascular Events. Radiology. 2019 Aug; 292(2):363-364.
    View in: PubMed
    Score: 0.420
  13. Design of CTP-PRO study (impact of stress Cardiac computed Tomography myocardial Perfusion on downstream resources and PROgnosis in patients with suspected or known coronary artery disease: A multicenter international study). Int J Cardiol. 2019 10 01; 292:253-257.
    View in: PubMed
    Score: 0.419
  14. 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: 0.409
  15. Intermodel disagreement of myocardial blood flow estimation from dynamic CT perfusion imaging. Eur J Radiol. 2019 Jan; 110:175-180.
    View in: PubMed
    Score: 0.403
  16. 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: 0.352
  17. Accuracy and Radiation Dose Reduction Using Low-Voltage Computed Tomography Coronary Artery Calcium Scoring With Tin Filtration. Am J Cardiol. 2017 02 15; 119(4):675-680.
    View in: PubMed
    Score: 0.350
  18. 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: 0.350
  19. 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: 0.344
  20. Coronary CT angiography-derived quantitative markers for predicting in-stent restenosis. J Cardiovasc Comput Tomogr. 2016 Sep-Oct; 10(5):377-83.
    View in: PubMed
    Score: 0.342
  21. Myocardial perfusion imaging with dual energy CT. Eur J Radiol. 2016 Oct; 85(10):1914-1921.
    View in: PubMed
    Score: 0.341
  22. Dynamic CT myocardial perfusion imaging identifies early perfusion abnormalities in diabetes and hypertension: Insights from a multicenter registry. J Cardiovasc Comput Tomogr. 2016 Jul-Aug; 10(4):301-8.
    View in: PubMed
    Score: 0.339
  23. 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: 0.334
  24. Response. Radiology. 2015 Nov; 277(2):616.
    View in: PubMed
    Score: 0.326
  25. CT myocardial perfusion imaging. AJR Am J Roentgenol. 2015 Mar; 204(3):487-97.
    View in: PubMed
    Score: 0.311
  26. Coronary artery disease and the myocardial ischemic cascade: state-of-the-art computed tomography and MR imaging. Radiol Clin North Am. 2015 Mar; 53(2):xv-xvi.
    View in: PubMed
    Score: 0.311
  27. Effect of reduced x-ray tube voltage, low iodine concentration contrast medium, and sinogram-affirmed iterative reconstruction on image quality and radiation dose at coronary CT angiography: results of the prospective multicenter REALISE trial. J Cardiovasc Comput Tomogr. 2015 May-Jun; 9(3):215-24.
    View in: PubMed
    Score: 0.309
  28. Reply: the ethics of publishing dual exposure scans involving ionizing radiation when validated alternatives exist. JACC Cardiovasc Imaging. 2014 Sep; 7(9):964-5.
    View in: PubMed
    Score: 0.301
  29. Coronary artery computed tomography scanning. Circulation. 2014 Mar 25; 129(12):1341-5.
    View in: PubMed
    Score: 0.292
  30. Monoenergetic extrapolation of cardiac dual energy CT for artifact reduction. Acta Radiol. 2015 Apr; 56(4):413-8.
    View in: PubMed
    Score: 0.291
  31. Iterative reconstruction to preserve image quality and diagnostic accuracy at reduced radiation dose in coronary CT angiography: an intraindividual comparison. JACC Cardiovasc Imaging. 2013 Dec; 6(12):1239-49.
    View in: PubMed
    Score: 0.283
  32. Expert opinion: should coronary CT angiography be used as a screening test? J Thorac Imaging. 2012 Nov; 27(6):339.
    View in: PubMed
    Score: 0.265
  33. Dual-energy CT of the heart. AJR Am J Roentgenol. 2012 Nov; 199(5 Suppl):S54-63.
    View in: PubMed
    Score: 0.265
  34. Fully automated derivation of coronary artery calcium scores and cardiovascular risk assessment from contrast medium-enhanced coronary CT angiography studies. Eur Radiol. 2013 Mar; 23(3):650-7.
    View in: PubMed
    Score: 0.262
  35. Independent association between obstructive sleep apnea and noncalcified coronary plaque demonstrated by noninvasive coronary computed tomography angiography. Clin Cardiol. 2012 Oct; 35(10):641-5.
    View in: PubMed
    Score: 0.262
  36. Coronary computed tomography angiography in patients with chronic chest pain: systematic review of evidence base and cost-effectiveness. J Thorac Imaging. 2012 Sep; 27(5):277-88.
    View in: PubMed
    Score: 0.262
  37. CT detection of myocardial blood volume deficits: dual-energy CT compared with single-energy CT spectra. J Cardiovasc Comput Tomogr. 2011 Nov-Dec; 5(6):421-9.
    View in: PubMed
    Score: 0.247
  38. Can non-calcified coronary artery plaques be detected on non-contrast CT calcium scoring studies? Acad Radiol. 2011 Jul; 18(7):858-65.
    View in: PubMed
    Score: 0.241
  39. Integrative computed tomographic imaging of coronary artery disease. Expert Rev Cardiovasc Ther. 2011 Jan; 9(1):27-43.
    View in: PubMed
    Score: 0.233
  40. Integrative computed tomographic imaging of cardiac structure, function, perfusion, and viability. Cardiol Rev. 2010 Sep-Oct; 18(5):219-29.
    View in: PubMed
    Score: 0.228
  41. Coming of age: coronary computed tomography angiography. J Thorac Imaging. 2010 Aug; 25(3):221-30.
    View in: PubMed
    Score: 0.227
  42. Evaluation of plaques and stenosis. Radiol Clin North Am. 2010 Jul; 48(4):729-44.
    View in: PubMed
    Score: 0.225
  43. [Comprehensive assessment of coronary disease using perfusion CT with pharmacologically induced stress]. Radiologia. 2010 Sep-Oct; 52(5):469-72.
    View in: PubMed
    Score: 0.223
  44. CT of coronary artery disease. Radiology. 2009 Nov; 253(2):317-38.
    View in: PubMed
    Score: 0.215
  45. Reproducibility of automated noncalcified coronary artery plaque burden assessment at coronary CT angiography. J Thorac Imaging. 2009 May; 24(2):96-102.
    View in: PubMed
    Score: 0.208
  46. CT of the heart--quo vadis? J Thorac Imaging. 2007 Feb; 22(1):2-3.
    View in: PubMed
    Score: 0.178
  47. Coronary CTA: image acquisition and interpretation. J Thorac Imaging. 2007 Feb; 22(1):22-34.
    View in: PubMed
    Score: 0.178
  48. Coronary CTA: indications, patient selection, and clinical implications. J Thorac Imaging. 2007 Feb; 22(1):35-9.
    View in: PubMed
    Score: 0.178
  49. CT of coronary artery disease. J Thorac Imaging. 2007 Feb; 22(1):40-8.
    View in: PubMed
    Score: 0.178
  50. Novel developments in cardiac computed tomography. Am Heart Hosp J. 2005; 3(3):167-74.
    View in: PubMed
    Score: 0.154
  51. Multidetector-row CT of the heart. Radiol Clin North Am. 2003 May; 41(3):491-505, v.
    View in: PubMed
    Score: 0.137
  52. Diabetes, Atherosclerosis, and Stenosis by AI. Diabetes Care. 2023 02 01; 46(2):416-424.
    View in: PubMed
    Score: 0.135
  53. Serial Changes in Coronary Plaque Formation Using CT Angiography in Patients Undergoing PCSK9-Inhibitor Therapy With 1-year Follow-up. J Thorac Imaging. 2022 Sep 01; 37(5):285-291.
    View in: PubMed
    Score: 0.130
  54. Deep learning for vessel-specific coronary artery calcium scoring: validation on a multi-centre dataset. Eur Heart J Cardiovasc Imaging. 2022 06 01; 23(6):846-854.
    View in: PubMed
    Score: 0.129
  55. Machine Learning for the Prevalence and Severity of Coronary Artery Calcification in Nondialysis Chronic Kidney Disease Patients: A Chinese Large Cohort Study. J Thorac Imaging. 2022 Nov 01; 37(6):401-408.
    View in: PubMed
    Score: 0.128
  56. 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: 0.128
  57. 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: 0.127
  58. Coronary Computed Tomography Angiography-Based Calcium Scoring: In Vitro and In Vivo Validation of a Novel Virtual Noniodine Reconstruction Algorithm on a Clinical, First-Generation Dual-Source Photon Counting-Detector System. Invest Radiol. 2022 08 01; 57(8):536-543.
    View in: PubMed
    Score: 0.127
  59. 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: 0.127
  60. [Morphological and functional diagnostics of coronary artery disease by computed tomography]. Herz. 2023 Feb; 48(1):39-47.
    View in: PubMed
    Score: 0.126
  61. 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: 0.126
  62. 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: 0.126
  63. 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: 0.126
  64. Visualization of Concurrent Epicardial and Microvascular Coronary Artery Disease in a Patient with Systemic Lupus Erythematosus by Magnetic Resonance Imaging. Top Magn Reson Imaging. 2022 Feb 01; 31(1):3-8.
    View in: PubMed
    Score: 0.126
  65. 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: 0.125
  66. 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: 0.125
  67. Calcium Scoring at Coronary CT Angiography Using Deep Learning. Radiology. 2022 02; 302(2):309-316.
    View in: PubMed
    Score: 0.124
  68. Radiomics: The Next Frontier of Cardiac Computed Tomography. Circ Cardiovasc Imaging. 2021 03; 14(3):e011747.
    View in: PubMed
    Score: 0.118
  69. 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: 0.118
  70. Prognostic Value of Coronary Computed Tomography Angiography-derived Morphologic and Quantitative Plaque Markers Using Semiautomated Plaque Software. J Thorac Imaging. 2021 Mar 01; 36(2):108-115.
    View in: PubMed
    Score: 0.118
  71. 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: 0.118
  72. 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: 0.117
  73. Gadobutrol-Enhanced Cardiac Magnetic Resonance Imaging for Detection of Coronary Artery Disease. J Am Coll Cardiol. 2020 09 29; 76(13):1536-1547.
    View in: PubMed
    Score: 0.115
  74. 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: 0.113
  75. Ischemia and outcome prediction by cardiac CT based machine learning. Int J Cardiovasc Imaging. 2020 Dec; 36(12):2429-2439.
    View in: PubMed
    Score: 0.113
  76. 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: 0.112
  77. Individualized coronary calcium scoring at any tube voltage using a kV-independent reconstruction algorithm. Eur Radiol. 2020 Nov; 30(11):5834-5840.
    View in: PubMed
    Score: 0.112
  78. Low-kV coronary artery calcium scoring with tin filtration using a kV-independent reconstruction algorithm. J Cardiovasc Comput Tomogr. 2020 May - Jun; 14(3):246-250.
    View in: PubMed
    Score: 0.108
  79. 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: 0.106
  80. Assessing the value of coronary artery computed tomography as the first-line anatomical test for stable patients with indications for invasive angiography due to suspected coronary artery disease. Initial cost analysis in the CAT-CAD randomized trial. J Cardiovasc Comput Tomogr. 2020 Jan - Feb; 14(1):75-79.
    View in: PubMed
    Score: 0.106
  81. Diagnosis of obstructive coronary artery disease using computed tomography angiography in patients with stable chest pain depending on clinical probability and in clinically important subgroups: meta-analysis of individual patient data. BMJ. 2019 06 12; 365:l1945.
    View in: PubMed
    Score: 0.105
  82. Automated plaque analysis for the prognostication of major adverse cardiac events. Eur J Radiol. 2019 Jul; 116:76-83.
    View in: PubMed
    Score: 0.104
  83. 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: 0.103
  84. Progression of coronary atherosclerotic plaque burden and relationship with adverse cardiovascular event in asymptomatic diabetic patients. BMC Cardiovasc Disord. 2019 02 11; 19(1):39.
    View in: PubMed
    Score: 0.102
  85. Association of Serum Lipid Profile With Coronary Computed Tomographic Angiography-derived Morphologic and Functional Quantitative Plaque Markers. J Thorac Imaging. 2019 Jan; 34(1):26-32.
    View in: PubMed
    Score: 0.101
  86. 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: 0.101
  87. 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: 0.100
  88. The value of Coronary Artery computed Tomography as the first-line anatomical test for stable patients with indications for invasive angiography due to suspected Coronary Artery Disease: CAT-CAD randomized trial. J Cardiovasc Comput Tomogr. 2018 Nov - Dec; 12(6):472-479.
    View in: PubMed
    Score: 0.099
  89. 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: 0.098
  90. 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: 0.097
  91. Current and future applications of CT coronary calcium assessment. Expert Rev Cardiovasc Ther. 2018 Jun; 16(6):441-453.
    View in: PubMed
    Score: 0.097
  92. 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: 0.097
  93. High-pitch low-voltage CT coronary artery calcium scoring with tin filtration: accuracy and radiation dose reduction. Eur Radiol. 2018 Jul; 28(7):3097-3104.
    View in: PubMed
    Score: 0.095
  94. Heavily Calcified Coronary Arteries: Advanced Calcium Subtraction Improves Luminal Visualization and Diagnostic Confidence in Dual-Energy Coronary Computed Tomography Angiography. Invest Radiol. 2018 02; 53(2):103-109.
    View in: PubMed
    Score: 0.095
  95. 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: 0.093
  96. 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: 0.092
  97. Iterative beam-hardening correction with advanced modeled iterative reconstruction in low voltage CT coronary calcium scoring with tin filtration: Impact on coronary artery calcium quantification and image quality. J Cardiovasc Comput Tomogr. 2017 Sep - Oct; 11(5):354-359.
    View in: PubMed
    Score: 0.092
  98. CT angiography to evaluate coronary artery disease and revascularization requirement before trans-catheter aortic valve replacement. J Cardiovasc Comput Tomogr. 2017 Sep - Oct; 11(5):338-346.
    View in: PubMed
    Score: 0.091
  99. FFR-Derived From?Coronary CT?Angiography Using Workstation-Based Approaches. JACC Cardiovasc Imaging. 2017 04; 10(4):497-498.
    View in: PubMed
    Score: 0.090
  100. Coronary artery calcium in breast cancer survivors after radiation therapy. Int J Cardiovasc Imaging. 2017 Sep; 33(9):1425-1431.
    View in: PubMed
    Score: 0.090
  101. CT coronary calcium scoring with tin filtration using iterative beam-hardening calcium correction reconstruction. Eur J Radiol. 2017 Jun; 91:29-34.
    View in: PubMed
    Score: 0.090
  102. Prognostic Value of Stress Dynamic Myocardial Perfusion CT in a Multicenter Population With Known or Suspected Coronary Artery Disease. AJR Am J Roentgenol. 2017 Apr; 208(4):761-769.
    View in: PubMed
    Score: 0.089
  103. 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: 0.088
  104. CT myocardial perfusion: state of the science. Minerva Cardioangiol. 2017 Jun; 65(3):252-264.
    View in: PubMed
    Score: 0.088
  105. Correction Factors for CT Coronary Artery Calcium Scoring Using Advanced Modeled Iterative Reconstruction Instead of Filtered Back Projection. Acad Radiol. 2016 12; 23(12):1480-1489.
    View in: PubMed
    Score: 0.086
  106. Coronary Artery Disease - Reporting and?Data?System (CAD-RADS): An Expert Consensus Document of SCCT, ACR and NASCI: Endorsed by the ACC. JACC Cardiovasc Imaging. 2016 09; 9(9):1099-1113.
    View in: PubMed
    Score: 0.086
  107. CAD-RADS?: 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 Am Coll Radiol. 2016 Dec; 13(12 Pt A):1458-1466.e9.
    View in: PubMed
    Score: 0.085
  108. 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: 0.085
  109. Approaches to ultra-low radiation dose coronary artery calcium scoring based on 3rd generation dual-source CT: A phantom study. Eur J Radiol. 2016 Jan; 85(1):39-47.
    View in: PubMed
    Score: 0.082
  110. Impact of an advanced image-based monoenergetic reconstruction algorithm on coronary stent visualization using third generation dual-source dual-energy CT: a phantom study. Eur Radiol. 2016 Jun; 26(6):1871-8.
    View in: PubMed
    Score: 0.081
  111. Mammographic detection of breast arterial calcification as an independent predictor of coronary atherosclerotic disease in a single ethnic cohort of African American women. Atherosclerosis. 2015 Sep; 242(1):218-21.
    View in: PubMed
    Score: 0.080
  112. Absolute Versus Relative Myocardial Blood Flow by Dynamic CT Myocardial Perfusion Imaging in Patients With Anatomic Coronary Artery Disease. AJR Am J Roentgenol. 2015 Jul; 205(1):W67-72.
    View in: PubMed
    Score: 0.080
  113. Prospectively ECG-triggered high-pitch 80?kVp coronary computed tomography angiography with 30?mL of 270?mg I/mL contrast material and iterative reconstruction. Acta Radiol. 2016 Mar; 57(3):287-94.
    View in: PubMed
    Score: 0.079
  114. Expert opinion: How and when to perform CT myocardial perfusion imaging. J Thorac Imaging. 2015 May; 30(3):167-8.
    View in: PubMed
    Score: 0.079
  115. Prognostic value of epicardial fat volume measurements by computed tomography: a systematic review of the literature. Eur Radiol. 2015 Nov; 25(11):3372-81.
    View in: PubMed
    Score: 0.079
  116. Intermodel agreement of myocardial blood flow estimation from stress-rest myocardial perfusion magnetic resonance imaging in patients with coronary artery disease. Invest Radiol. 2015 Apr; 50(4):275-82.
    View in: PubMed
    Score: 0.078
  117. Imaging coronary artery disease and the myocardial ischemic cascade: clinical principles and scope. Radiol Clin North Am. 2015 Mar; 53(2):261-9.
    View in: PubMed
    Score: 0.078
  118. Computed tomographic assessment of coronary artery disease: state-of-the-art imaging techniques. Radiol Clin North Am. 2015 Mar; 53(2):271-85.
    View in: PubMed
    Score: 0.078
  119. Computed tomography imaging of coronary artery plaque: characterization and prognosis. Radiol Clin North Am. 2015 Mar; 53(2):307-15.
    View in: PubMed
    Score: 0.078
  120. 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: 0.078
  121. The dream of a one-stop-shop: Meta-analysis on myocardial perfusion CT. Eur J Radiol. 2015 Dec; 84(12):2411-20.
    View in: PubMed
    Score: 0.077
  122. Dual-source CT imaging to plan transcatheter aortic valve replacement: accuracy for diagnosis of obstructive coronary artery disease. Radiology. 2015 Apr; 275(1):80-8.
    View in: PubMed
    Score: 0.076
  123. 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: 0.075
  124. Incremental value of pharmacological stress cardiac dual-energy CT over coronary CT angiography alone for the assessment of coronary artery disease in a high-risk population. AJR Am J Roentgenol. 2014 Jul; 203(1):W70-7.
    View in: PubMed
    Score: 0.074
  125. Image quality and radiation dose of low tube voltage 3rd generation dual-source coronary CT angiography in obese patients: a phantom study. Eur Radiol. 2014 Jul; 24(7):1643-50.
    View in: PubMed
    Score: 0.074
  126. Differences in coronary artery disease by CT angiography between patients developing unstable angina pectoris vs. major adverse cardiac events. Eur J Radiol. 2014 07; 83(7):1113-1119.
    View in: PubMed
    Score: 0.073
  127. Feasibility of prospectively ECG-triggered high-pitch coronary CT angiography with 30 mL iodinated contrast agent at 70 kVp: initial experience. Eur Radiol. 2014 Jul; 24(7):1537-46.
    View in: PubMed
    Score: 0.073
  128. Comparison of the effect of iterative reconstruction versus filtered back projection on cardiac CT postprocessing. Acad Radiol. 2014 Mar; 21(3):318-24.
    View in: PubMed
    Score: 0.072
  129. First-arterial-pass dual-energy CT for assessment of myocardial blood supply: do we need rest, stress, and delayed acquisition? Comparison with SPECT. Radiology. 2014 Mar; 270(3):708-16.
    View in: PubMed
    Score: 0.071
  130. Automated quantification of epicardial adipose tissue using CT angiography: evaluation of a prototype software. Eur Radiol. 2014 Feb; 24(2):519-26.
    View in: PubMed
    Score: 0.071
  131. Dynamic CT myocardial perfusion imaging: performance of 3D semi-automated evaluation software. Eur Radiol. 2014 Jan; 24(1):191-9.
    View in: PubMed
    Score: 0.070
  132. 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: 0.070
  133. 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: 0.070
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Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.