Connection

Rozemarijn Vliegenthart to Myocardial Perfusion Imaging

This is a "connection" page, showing publications Rozemarijn Vliegenthart has written about Myocardial Perfusion Imaging.
  1. Validation of myocardial perfusion quantification by dynamic CT in an ex-vivo porcine heart model. Int J Cardiovasc Imaging. 2017 Nov; 33(11):1821-1830.
    View in: PubMed
    Score: 0.518
  2. 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: 0.507
  3. 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: 0.483
  4. Development of an Ex Vivo, Beating Heart Model for CT Myocardial Perfusion. Biomed Res Int. 2015; 2015:412716.
    View in: PubMed
    Score: 0.453
  5. Expert opinion: How and when to perform CT myocardial perfusion imaging. J Thorac Imaging. 2015 May; 30(3):167-8.
    View in: PubMed
    Score: 0.449
  6. Early detection of obstructive coronary artery disease in the asymptomatic high-risk population: objectives and study design of the EARLY-SYNERGY trial. Am Heart J. 2022 04; 246:166-177.
    View in: PubMed
    Score: 0.179
  7. Dynamic Myocardial Perfusion CT for the Detection of Hemodynamically Significant Coronary Artery Disease. JACC Cardiovasc Imaging. 2022 01; 15(1):75-87.
    View in: PubMed
    Score: 0.175
  8. Machine Learning and Deep Neural Networks Applications in Computed Tomography for Coronary Artery Disease and Myocardial Perfusion. J Thorac Imaging. 2020 May; 35 Suppl 1:S58-S65.
    View in: PubMed
    Score: 0.159
  9. T1 reactivity as an imaging biomarker in myocardial tissue characterization discriminating normal, ischemic and infarcted myocardium. Int J Cardiovasc Imaging. 2019 Jul; 35(7):1319-1325.
    View in: PubMed
    Score: 0.148
  10. Intermodel disagreement of myocardial blood flow estimation from dynamic CT perfusion imaging. Eur J Radiol. 2019 Jan; 110:175-180.
    View in: PubMed
    Score: 0.144
  11. 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: 0.142
  12. Quantitative myocardial perfusion evaluation with positron emission tomography and the risk of cardiovascular events in patients with coronary artery disease: a systematic review of prognostic studies. Eur Heart J Cardiovasc Imaging. 2018 10 01; 19(10):1179-1187.
    View in: PubMed
    Score: 0.142
  13. Disagreement between splenic switch-off and myocardial T1-mapping after caffeine intake. Int J Cardiovasc Imaging. 2018 Apr; 34(4):625-632.
    View in: PubMed
    Score: 0.134
  14. Accuracy of iodine quantification using dual energy CT in latest generation dual source and dual layer CT. Eur Radiol. 2017 Sep; 27(9):3904-3912.
    View in: PubMed
    Score: 0.127
  15. Caffeine intake inverts the effect of adenosine on myocardial perfusion during stress as measured by T1 mapping. Int J Cardiovasc Imaging. 2016 Oct; 32(10):1545-53.
    View in: PubMed
    Score: 0.122
  16. 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: 0.114
  17. Iodine quantification based on rest / stress perfusion dual energy CT to differentiate ischemic, infarcted and normal myocardium. Eur J Radiol. 2019 Mar; 112:136-143.
    View in: PubMed
    Score: 0.036
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.