Original contributionAspects on the accuracy of cerebral perfusion parameters obtained by dynamic susceptibility contrast MRI: a simulation study
Introduction
Dynamic susceptibility contrast (DSC) MRI can potentially be used for the determination of cerebral perfusion parameters such as regional cerebral blood volume (rCBV), regional cerebral blood flow (rCBF), and regional mean transit time (rMTT), using the theory of intravascular tracers [1]. High spatial resolution, no patient exposure to ionizing radiation, and the possibility to combine morphological and functional information during one single imaging session make the method an attractive concept in a clinical environment. However, the procedure is not completely straightforward; numerous factors come into play in the calculation of cerebral perfusion. The deconvolution algorithm, the location and registration of the arterial input function (AIF), the temporal resolution, different signal decrease, and signal-to-noise ratio (S/N) all influence the quantification of the cerebral perfusion.
Several authors have discussed the importance of an appropriate deconvolution algorithm to be used in DSC MRI [2], [3], [4], [5], [6], [7], and, currently, the most common technique is based on singular value decomposition (SVD) [3]. The SVD deconvolution algorithm is a nonparametric technique that allows the estimation of perfusion parameters even at low S/Ns. The technique is also fairly independent of underlying vascular structure and volume. By eliminating the singular values in the diagonal matrix (often denoted W) that are smaller than a certain threshold, i.e., by choosing a cut-off value, the influence from noise is reduced [3]. Liu et al. discussed the importance of an appropriate cut-off value [8] and presented functions for choosing the optimal threshold based on the S/N of the concentration time curve. Calamante et al. [9] recently presented simulations of the effects of delay and dispersion in the measured AIF when using SVD deconvolution and found that a significant underestimation of rCBF and overestimation of rMTT were obtained when the two effects were introduced. Furthermore, Sorensen and Reimer stated that the preferred temporal resolution is between 0.8 and 2.2 s and that the optimal temporal resolution is 1 s using an SE EPI sequence [10]. Another important parameter is the echo time (TE) due to its effect on the baseline signal level and the signal decrease. An optimum signal drop is obtained when TE equals T2*, i.e., when the ratio of minimum signal Smin to baseline signal S0 equals 1/e, but a larger decrease leads to a decrease in quality [11].
Experimental optimization investigations have been performed [12] as have theoretical studies of the relationships among different parameters by computer simulations [13], [14], [15]. The results of our simulations constitute a relevant supplement to these, since practical perfusion measurements by use of DSC MRI are carried out with very different pulse sequences and imaging protocols, leading to difficulties in the comparison of results from different studies. Furthermore, quantification of rCBF by DSC MRI is likely to become a powerful tool, for example, in tumor therapy monitoring and for determining tissue at risk in acute ischemic stroke, provided that the technique can yield reproducible absolute values with a well-defined accuracy and precision.
In this study, quantification of cerebral perfusion parameters in GM, WM, and ischemic penumbra under various conditions was simulated using the SVD deconvolution technique. The parameters that were varied in the present simulation study were the temporal resolution, the maximal signal drop, the S/N, the shape of the AIF and the W-matrix cut-off value in the SVD deconvolution.
Section snippets
Subjects and experiments
To obtain reasonable and realistic starting values for the shapes of the concentration curves in artery and tissue, three normal volunteers were examined by DSC MRI at 1.5 T (Magnetom Vision, Siemens Medical Systems, Erlangen, Germany). The contrast agent was injected into a peripheral arm vein, and the bolus passage was monitored using a simultaneous dual fast low angle shot (SD-FLASH) pulse sequence with a temporal resolution of 1.5 s. The imaging parameters were as follows: repetition time
Results
Figure 3 shows rCBF as a function of S/N at different time resolutions using the medium AIF. As seen in the graphs, rCBF appeared to increase systematically when S/N decreased, and WM at large image time intervals showed the highest standard deviations.
The low/broad AIF underestimated the absolute value of rCBF more than the medium and high/narrow AIFs [Figs. 4(a) and 4(b)]. At S/Ns lower than 40, a higher and more narrow AIF led to smaller rCBF standard deviation. Smaller standard deviation
Discussion
The results of this study indicate that a standardized MR perfusion protocol is of value, especially when quantification in absolute terms becomes feasible. Although the rCBF fluctuations we observed were, in general, not extremely large, they may still be of some relevance. For example, it is an attractive idea to try to establish significant tissue viability threshold values [26] to be used for the prediction of final infarct or to objectively discriminate between irreversible infarction and
Conclusion
The following recommendations can be extracted from the present study:
- 1.
Use a narrow or medium AIF, but note that the arterial signal might drop to the noise level. To avoid underestimation of the rCBF, the injection rate should not go below 3 ml/s.
- 2.
To achieve an optimal signal drop, TE should equal T2*, but a long TE also leads to decreased baseline signal and a corresponding decrease in S/N. This indicates that a shorter TE is preferred. According to the simulations in this study, a TE between
Acknowledgements
This study was supported in part by the Swedish Research Council (grant 13514) and the Royal Physiographic Society in Lund. The authors thank Edvin Johansson, Ph.D., for his valuable comments on the study.
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