- Meeting abstract
- Open Access
2133 Effect of the bolus size on the quantification of myocardial perfusion using MRI
© Ivancevic et al; licensee BioMed Central Ltd. 2008
- Published: 22 October 2008
- Compartment Model
- Arterial Input Function
- Intensity Time Curve
- Bode Diagram
- Signal Intensity Time Curve
A limitation of MRI for cardiac perfusion on routine clinical MR scanners is the trade-off between the temporal resolution and spatial coverage. Assuming that a higher contrast media dose and a slower injection rate allow lower sampling rate without a significant loss of precision in an one compartmental model, we performed a simulation study to compare two contrast injection strategies (wide and narrow bolus). The validity of the protocol was then demonstrated in patients with a history of myocardial infarction, using 201-Tl SPECT imaging as reference.
The myocardial perfusion is quantified using the one compartment model described by: dCmyo(t)/dt = K1Cart(t) – K2Cmyo(t) where Cart(t) and Cmyo(t) are the arterial and myocardial signal intensity time curves respectively, K1 the perfusion index related to the first order transfer constant from the LV blood to the myocardium and the ratio K1/K2 the fractional distribution volume of the contrast media.
The validity of the protocol was then demonstrated in 12 patients with a history of myocardial infarction, using 201-Tl SPECT imaging as reference. The MR perfusion sequence was a T1 weighted FGRE sequence with eight slices (4 short-axis, and 4 long-axis) acquired during three to six cardiac cycles, depending on patient's heart rate. the average inter-image delay was 4 seconds (± 0.5). A bolus of 0.08 mmol/kg Gd-DTPA was injected in a brachial vein at 0.5 ml/s injection rate. Standard one compartment model analysis was then applied.
the Bode diagram showed a similar behaviour of the narrow and wide AIF around the cut-off frequency and indicating that both bolus shapes are adapted to this one compartment model. No significant difference in bias and standard deviation were observed with the identification process between the two shapes. Under-sampled curves introduce an increase of standard deviation of K1 and K2 but with a lower bias for the broad AIF. For typical noise encountered in patient data (around 1%), the standard deviation and biais remain within acceptable limits (< 5%). In the clinical study, the wide AIF protocol was able to differentiate between normal and abnormal thallium sectors. A decrease in the perfusion values measured by MRI in the infarcted regions was observed (k1 = 0.27 ± 0.21 ml/min/g compared to 0.4 ± 0.21 ml/min/g in normal, p 0.8).
The technique presented here overcomes the spatial limitation of cardiac MR perfusion assessment by allowing for reduced temporal acquisition rate without significant loss in accuracy for the perfusion quantification.
This article is published under license to BioMed Central Ltd.