An alternative approach to estimation of the brain perfusion index for measurement of cerebral blood flow using technetium-99m compounds

Abstract

Cerebral blood flow (CBF) has been quantified non-invasively using the brain perfusion index (BPI) determined from radionuclide angiographic data generated by technetium-99m hexamethylpropylene amine oxime( )((99m)Tc-HMPAO) or technetium-99m ethyl cysteinate dimer( )((99m)Tc-ECD). The BPI is generally calculated using graphical analysis (GA). In the present study, BPI was measured using spectral analysis (SA), and its usefulness evaluated in comparison with GA. The BPI was calculated from the sum of spectral data obtained by SA. We applied this method to radionuclide angiographic data collected from the bilateral brain hemispheres of 20 patients with various brain diseases using (99m)Tc-HMPAO and from those of 20 patients using (99m)Tc-ECD. We also measured BPI using GA. The BPI values obtained by SA (BPI(S)) (x) and by GA (BPI(G)) (y) correlated closely (y=0.708x+0.038, r=0.945 for (99m)Tc-HMPAO and y=0.559x+0.093, r=0.931 for (99m)Tc-ECD). However, the BPI(G) values were underestimated by 22.9%+/-6.6% (mean+/-SD) for (99m)Tc-HMPAO and by 27.9%+/-7.5% for (99m)Tc-ECD as compared with the BPI(S) values. The extent of underestimation tended to increase with increasing BPI(S) values. These findings were considered to be a result of the BPI(G) values being affected by the first-pass extraction fraction of the tracer. We also compared the BPI(S) and BPI(G) values with those of CBF measured using N-isopropyl-p-[(123)I]iodoamphetamine (CBF(IMP)) in 16 patients (six for (99m)Tc-HMPAO and ten for (99m)Tc-ECD). Although both BPI(S) and BPI(G) values correlated significantly with the CBF(IMP) values, the correlation coefficient in BPI(S) was always better than that in BPI(G) (r=0.869 for (99m)Tc-HMPAO and r=0.929 for (99m)Tc-ECD in BPI(S), r=0.629 for (99m)Tc-HMPAO and r=0.856 for (99m)Tc-ECD in BPI(G)). These results suggest that SA can provide a more reliable BPI for quantifying CBF using (99m)Tc-HMPAO or (99m)Tc-ECD than the conventional method using GA. Our method will be useful especially when using a tracer with a low first-pass extraction fraction and/or when performing activation studies using pharmacological intervention.

Alzheimer ́s Disease – The New Actors of an Old Drama

“…We explored also a possible association between gCBF and cognitive function, after controlling for age, gender, level of education and global brain atrophy (quantified on 3D T1-weighted MRI images). gCBF was measured by spectral analysis of radionuclide angiography, which is a simple and non-invasive method for the quantification of gCBF (Murase et al, 1999;Van et al, 2001) and linearly correlated with gCBF measured by using PET (Takasawa et al, 2004). Our results show a significant decrease of gCBF in the MCI group as compared with controls (p < 0.05, Mann-Whitney U Test, figure 5).…”

Automatic determination of brain perfusion index for measurement of cerebral blood flow using spectral analysis and 99m Tc-HMPAO

“…Murase et al was the first to apply the SA method to SPET data [2]. They demonstrated two crucial advantages to estimating the BPI using SA.…”

“…SA was used to calculate the 99m Tc-HMPAO level [2], and the level of 99m Tc-HMPAO radioactivity in the brain at a given time t[C s (t)] was modelled as a convolution of the blood input function [C a (t)] with a sum of k exponential terms, as shown by the following equation: (1) where α i and β i were assumed to be positive or zero. The upper limit, k, represents the maximum number of terms to be included in the model and was set at 1,000.…”

“…Regions of interest (ROIs) were hand-drawn over the left and right cerebral hemispheres and the aortic arch using the workstation and a software package (Dr. View; Asahi Kasei Joho System Co., Ltd., Tokyo, Japan), as described by Matsuda et al [3]. The BPI calculations for the ROIs were performed using the workstation and a software package for BPI analysis developed by Murase et al [2].…”

“…The method provides a spectrum of kinetic components involved in the regional uptake and partitioning of a tracer from the blood to tissues and allows tissue impulse response functions to be derived with minimal modelling assumptions. Murase et al were the first to apply SA to dynamic single-photon emission tomography (SPET) data acquired with technetium-99m labelled compounds [2]. They obtained the brain perfusion index (BPI) from the time-activity curves in the brain and aortic arch, and demonstrated a good correlation between the BPI estimated using SA and the absolute CBF, as measured using iodine-123 iodoamphetamine.…”