2026 Tradeoffs between spatial coverage and dynamic temporal resolution in quantitative first-pass perfusion imaging
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BioMed Central
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Meeting abstract
2026 Tradeoffs between spatial coverage and dynamic temporal resolution in quantitative first-pass perfusion imaging Li-Yueh Hsu*1, Peter Kellman1, Sven Zuehlsdorff2, Patricia W Bandettini1, Christine Mancini1, Marsha Block1, Tracy Lowrey1, Anthony H Aletras1 and Andrew E Arai1 Address: 1National Institutes of Health, Bethesda, MD, USA and 2Siemens Medical Solutions, Chicago, IL, USA * Corresponding author
from 11th Annual SCMR Scientific Sessions Los Angeles, CA, USA. 1–3 February 2008 Published: 22 October 2008 Journal of Cardiovascular Magnetic Resonance 2008, 10(Suppl 1):A295
doi:10.1186/1532-429X-10-S1-A295
Abstracts of the 11th Annual SCMR Scientific Sessions - 2008
Meeting abstracts – A single PDF containing all abstracts in this Supplement is available here. http://www.biomedcentral.com/content/pdf/1532-429X-10-S1-info.pdfThis abstract is available from: http://jcmr-online.com/content/10/S1/A295 © 2008 Hsu et al; licensee BioMed Central Ltd.
Introduction First-pass contrast-enhanced perfusion MRI is a useful tool for the diagnosis of ischemic cardiac disease. Quantitative analysis of myocardial perfusion depends on measuring dynamic signal intensity changes of the LV blood and myocardium as a function of time. There is an inverse relationship between the number of slices imaged per unit time and the repetition time for those spatial locations. For example, a perfusion sequence that can image 3 slices per heartbeat could image 6 locations every other heartbeat.
Purpose The purpose of this study was to show that high temporal sampling of the input function is important for perfusion quantification, but the myocardial sampling rate may be reduced and still achieve highly accurate measures of perfusion.
Methods Dual-bolus (Gd-DTPA 0.005 and 0.1 mmol/kg) rest and dipyridamole stress myocardial perfusion MR imaging was performed on 10 normal volunteers on a 1.5 T Siemens scanner. Each perfusion study was acquired in a breath-hold and with single RR imaging interval. A segmented GRE-EPI sequence was used by the following parameters: 90° prep, 25° readout, TR 7.5 ms, TE 1.48 ms, 8 mm slice thickness, echo train length 4, acquisition matrix 128 × 80–96, FOV 360 × 270 mm. Time-signal
intensity curves of the perfusion images were analyzed by dividing the myocardium into 6 sectors. Myocardial blood flow (MBF) was estimated from LV input and myocardial output time-signal intensity curves by a Fermi model constrained deconvolution. Using MBF quantified from LV and myocardial curves at 1RR temporal resolution as a reference standard, we compared MBF estimated from 2RR and 3RR under-sampled time-signal intensity curves.
Results Figure 1 shows an example of the LV input curve at 1RR that was under-sampled to 2RR and 3RR temporal resolutions. The shape of the curve was distorted noticeably at contrast arrival and peak contrast enhancement time points. At 3RR under-sampling, the LV curve only has 2 points above half height and clearly underestimates the peak. F
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