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For: Tomiyama T, Ishihara K, Suda M, Kanaya K, Sakurai M, Takahashi N, Takano H, Nitta K, Hakozaki K, Kumita S. Impact of time-of-flight on qualitative and quantitative analyses of myocardial perfusion PET studies using (13)N-ammonia. J Nucl Cardiol 2015;22:998-1007. [PMID: 25467250 DOI: 10.1007/s12350-014-0037-8] [Cited by in Crossref: 12] [Cited by in F6Publishing: 8] [Article Influence: 1.5] [Reference Citation Analysis]
Number Citing Articles
1 Case JA. The Importance of Time-of-Flight Reconstruction and Point Spread Modeling in the Measurement of Myocardial Blood Flow Parameters. Curr Cardiol Rep 2021;23:77. [PMID: 34081208 DOI: 10.1007/s11886-021-01507-1] [Reference Citation Analysis]
2 Julien HM, Bravo PE. Thick and thin: Bridging the gap to a better understanding of apical thinning. J Nucl Cardiol 2020;27:461-464. [DOI: 10.1007/s12350-018-1451-0] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
3 Steffen DA, Giannopoulos AA, Grossmann M, Messerli M, Schwyzer M, Gräni C, Gebhard C, Pazhenkottil AP, Kaufmann PA, Buechel RR. “Apical thinning”: Relations between myocardial wall thickness and apical left ventricular tracer uptake as assessed with positron emission tomography myocardial perfusion imaging. J Nucl Cardiol 2020;27:452-60. [DOI: 10.1007/s12350-018-1397-2] [Cited by in Crossref: 8] [Cited by in F6Publishing: 8] [Article Influence: 2.0] [Reference Citation Analysis]
4 Hashimoto H, Fukushima Y, Kumita S, Tomiyama T, Kiriyama T. Feasibility of myocardial flow reserve prediction without the use of dynamic data from myocardial perfusion positron emission tomography. Int J Cardiovasc Imaging 2018;34:1323-1329. [DOI: 10.1007/s10554-018-1335-z] [Reference Citation Analysis]
5 Kero T, Nordström J, Harms HJ, Sörensen J, Ahlström H, Lubberink M. Quantitative myocardial blood flow imaging with integrated time-of-flight PET-MR. EJNMMI Phys 2017;4:1. [PMID: 28058674 DOI: 10.1186/s40658-016-0171-2] [Cited by in Crossref: 11] [Cited by in F6Publishing: 13] [Article Influence: 2.2] [Reference Citation Analysis]
6 Armstrong IS, Memmott MJ, Tonge CM, Arumugam P. The impact of prompt gamma compensation on myocardial blood flow measurements with rubidium-82 dynamic PET. J Nucl Cardiol 2018;25:596-605. [PMID: 27624818 DOI: 10.1007/s12350-016-0583-3] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 1.0] [Reference Citation Analysis]
7 Wang L, Wu D, Yang Y, Chen IJ, Lin CY, Hsu B, Fang W, Tang YD. Avoiding full corrections in dynamic SPECT images impacts the performance of SPECT myocardial blood flow quantitation. J Nucl Cardiol 2017;24:1332-46. [PMID: 27338944 DOI: 10.1007/s12350-016-0513-4] [Cited by in Crossref: 11] [Cited by in F6Publishing: 11] [Article Influence: 1.8] [Reference Citation Analysis]
8 Sciagrà R, Passeri A, Bucerius J, Verberne HJ, Slart RH, Lindner O, Gimelli A, Hyafil F, Agostini D, Übleis C, Hacker M; Cardiovascular Committee of the European Association of Nuclear Medicine (EANM). Clinical use of quantitative cardiac perfusion PET: rationale, modalities and possible indications. Position paper of the Cardiovascular Committee of the European Association of Nuclear Medicine (EANM). Eur J Nucl Med Mol Imaging 2016;43:1530-45. [PMID: 26846913 DOI: 10.1007/s00259-016-3317-5] [Cited by in Crossref: 40] [Cited by in F6Publishing: 30] [Article Influence: 6.7] [Reference Citation Analysis]
9 Slomka PJ, Pan T, Germano G. Recent Advances and Future Progress in PET Instrumentation. Seminars in Nuclear Medicine 2016;46:5-19. [DOI: 10.1053/j.semnuclmed.2015.09.006] [Cited by in Crossref: 126] [Cited by in F6Publishing: 128] [Article Influence: 21.0] [Reference Citation Analysis]
10 Nesterov SV, Lee BC, Moody JB, Slomka P, Han C, Knuuti JM. The Status and Future of PET Myocardial Blood Flow Quantification Software. Annals of Nuclear Cardiology 2016;2:106-110. [DOI: 10.17996/anc.02.01.106] [Cited by in Crossref: 9] [Cited by in F6Publishing: 9] [Article Influence: 1.5] [Reference Citation Analysis]
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