Susceptibility of Tmax to tracer delay on perfusion analysis: quantitative evaluation of various deconvolution algorithms using digital phantoms - PubMed (original) (raw)

Comparative Study

Susceptibility of Tmax to tracer delay on perfusion analysis: quantitative evaluation of various deconvolution algorithms using digital phantoms

Kohsuke Kudo et al. J Cereb Blood Flow Metab. 2011 Mar.

Abstract

The time-to-maximum of the tissue residue function (T(max)) perfusion index has proven very predictive of infarct growth in large clinical trials, yet its dependency on simple tracer delays remains unknown. Here, we determine the dependency of computed tomography (CT) perfusion (CTP) T(max) estimates on tracer delay using a range of deconvolution techniques and digital phantoms. Digital phantom data sets simulating the tracer delay were created from CTP data of six healthy individuals, in which time frames of the left cerebral hemisphere were shifted forward and backward by up to ±5 seconds. These phantoms were postprocessed with three common singular value decomposition (SVD) deconvolution algorithms-standard SVD (sSVD), block-circulant SVD (bSVD), and delay-corrected SVD (dSVD)-with an arterial input function (AIF) obtained from the right middle cerebral artery (MCA). The T(max) values of the left hemisphere were compared among different tracer delays and algorithms by a region of interest-based analysis. The T(max) values by sSVD were positively correlated with 'positive shifts' but unchanged with 'negative shifts,' those by bSVD had an excellent positive linear correlation with both positive and negative shifts, and those by dSVD were relatively constant, although slightly increased with the positive shifts. The T(max) is a parameter highly dependent on tracer delays and deconvolution algorithm.

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Figures

Figure 1

Figure 1

Color maps of time-to-maximum of the tissue residue function (_T_max). The _T_max color maps of digital computed tomography (CT) perfusion (CTP) phantoms, obtained by different deconvolution algorithms, are shown. Time frames of the left hemisphere were shifted from −5 to +5 seconds compared with the original data. Arterial input function (AIF) was obtained from the identical location at the insular segment of the right middle cerebral artery (MCA). Three kinds of the singular value decomposition (SVD) algorithm, standard SVD (sSVD), block-circulant SVD (bSVD), and delay-corrected SVD (dSVD), were used to obtain the _T_max color maps. In sSVD, the _T_max is apparently increased with the positive delays (+3 and +5 seconds) but is nearly constant with the negative delays (−3 and −5 seconds) compared with the original image (A). In bSVD, the _T_max is increased and decreased with the positive and negative delays, respectively (B). The _T_max is almost stable in dSVD, regardless of the positive or negative delays (C).

Figure 2

Figure 2

Relationship between time-to-maximum of the tissue residue function (_T_max) and time shifts. Relationship between the _T_max and positive and negative shifts of the time frame in the left hemisphere is shown. In standard singular value decomposition (sSVD), the _T_max is increased in a sigmoidal manner with the positive delays but is constant with the negative delays. In block-circulant SVD (bSVD), the _T_max is perfectly linear with the positive and negative delays. In delay-corrected SVD (dSVD), the _T_max is mostly constant with both the delays, but is slightly increased with the positive delays. Plots and error bars represent the average and s.d. of the _T_max values in the six subjects.

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