BPG is committed to discovery and dissemination of knowledge
Cited by in F6Publishing
For: Li Y, Dai X, Lu Z, Shen C, Zhang J. Diagnostic performance of quantitative, semi-quantitative, and visual analysis of dynamic CT myocardial perfusion imaging: a validation study with invasive fractional flow reserve. Eur Radiol 2021;31:525-34. [PMID: 32794126 DOI: 10.1007/s00330-020-07145-5] [Cited by in Crossref: 9] [Cited by in F6Publishing: 10] [Article Influence: 3.0] [Reference Citation Analysis]
Number Citing Articles
1 Kouchi T, Tanabe Y, Takemoto T, Yoshida K, Yamamoto Y, Miyazaki S, Fukuyama N, Nishiyama H, Inaba S, Kawaguchi N, Kido T, Yamaguchi O, Kido T. A Novel Quantitative Parameter for Static Myocardial Computed Tomography: Myocardial Perfusion Ratio to the Aorta. J Clin Med 2022;11. [PMID: 35407424 DOI: 10.3390/jcm11071816] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
2 Geng W, Gao Y, Zhao N, Yan H, Ma W, An Y, Jia L, Lu B. Dose Reduction of Dynamic Computed Tomography Myocardial Perfusion Imaging by Tube Voltage Change: Investigation in a Swine Model. Front Cardiovasc Med 2022;9:823974. [DOI: 10.3389/fcvm.2022.823974] [Reference Citation Analysis]
3 Dai X, Lu Z, Yu Y, Yu L, Xu H, Zhang J. The use of lesion-specific calcium morphology to guide the appropriate use of dynamic CT myocardial perfusion imaging and CT fractional flow reserve. Quant Imaging Med Surg 2022;12:1257-69. [PMID: 35111621 DOI: 10.21037/qims-21-491] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
4 Lyu L, Pan J, Li D, Li X, Yang W, Dong M, Guo C, Lin P, Han Y, Liang Y, Sun J, Yu D, Zhang P, Zhang M. Knowledge of Hyperemic Myocardial Blood Flow in Healthy Subjects Helps Identify Myocardial Ischemia in Patients With Coronary Artery Disease. Front Cardiovasc Med 2022;9:817911. [DOI: 10.3389/fcvm.2022.817911] [Reference Citation Analysis]
5 Kamphuis ME, de Vries GJ, Kuipers H, Saaltink M, Verschoor J, Greuter MJW, Slart RHJA, Slump CH. Development of a dedicated 3D printed myocardial perfusion phantom: proof-of-concept in dynamic SPECT. Med Biol Eng Comput 2022. [PMID: 35048275 DOI: 10.1007/s11517-021-02490-z] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
6 Yu Y, Yu L, Dai X, Zhang J. CT Fractional Flow Reserve for the Diagnosis of Myocardial Bridging-Related Ischemia: A Study Using Dynamic CT Myocardial Perfusion Imaging as a Reference Standard. Korean J Radiol 2021;22:1964-73. [PMID: 34668350 DOI: 10.3348/kjr.2021.0043] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
7 Ling R, Yu L, Lu Z, Li Y, Zhang J. A Novel Computed Tomography-Based Imaging Approach for Etiology Evaluation in Patients With Acute Coronary Syndrome and Non-obstructive Coronary Angiography. Front Cardiovasc Med 2021;8:735118. [PMID: 34504882 DOI: 10.3389/fcvm.2021.735118] [Reference Citation Analysis]
8 Yun CH, Hung CL, Wen MS, Wan YL, So A. CT Assessment of Myocardial Perfusion and Fractional Flow Reserve in Coronary Artery Disease: A Review of Current Clinical Evidence and Recent Developments. Korean J Radiol 2021;22:1749-63. [PMID: 34431244 DOI: 10.3348/kjr.2020.1277] [Reference Citation Analysis]
9 Vattay B, Boussoussou M, Borzsák S, Vecsey-nagy M, Simon J, Kolossváry M, Merkely B, Szilveszter B. Myocardial perfusion imaging using computed tomography: Current status, clinical value and prognostic implications. Imaging 2021;13:49-60. [DOI: 10.1556/1647.2020.00009] [Reference Citation Analysis]
10 Xu Y, Yu L, Shen C, Lu Z, Zhu X, Zhang J. Prevalence and disease features of myocardial ischemia with non-obstructive coronary arteries: Insights from a dynamic CT myocardial perfusion imaging study. Int J Cardiol 2021;334:142-7. [PMID: 33932431 DOI: 10.1016/j.ijcard.2021.04.055] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]