El Fakhri Georges, Sitek Arkadiusz, Zimmerman Robert E, Ouyang Jinsong
Department of Radiology, Harvard Medical School and Brigham and Women's Hospital, Boston, Massachusetts 02115, USA.
Med Phys. 2006 Apr;33(4):1016-24. doi: 10.1118/1.2179168.
We have generalized the spectral factor analysis and the factor analysis of dynamic sequences (FADS) in SPECT imaging to a five-dimensional general factor analysis model (5D-GFA), where the five dimensions are the three spatial dimensions, photon energy, and time. The generalized model yields a significant advantage in terms of the ratio of the number of equations to that of unknowns in the factor analysis problem in dynamic SPECT studies. We solved the 5D model using a least-squares approach. In addition to the traditional non-negativity constraints, we constrained the solution using a priori knowledge of both time and energy, assuming that primary factors (spectra) are Gaussian-shaped with full-width at half-maximum equal to gamma camera energy resolution. 5D-GFA was validated in a simultaneous pre-/post-synaptic dual isotope dynamic phantom study where 99mTc and 123I activities were used to model early Parkinson disease studies. 5D-GFA was also applied to simultaneous perfusion/dopamine transporter (DAT) dynamic SPECT in rhesus monkeys. In the striatal phantom, 5D-GFA yielded significantly more accurate and precise estimates of both primary 99mTc (bias=6.4 % +/- 4.3 %) and 1231 (-1.7% +/- 6.9%) time activity curves (TAC) compared to conventional FADS (biases = 15.5% +/- 10.6% in 99mTc and 8.3% +/- 12.7% in 123I, p < 0.05). Our technique was also validated in two primate dynamic dual isotope perfusion/DAT transporter studies. Biases of 99mTc-HMPAO and 123I-DAT activity estimates with respect to estimates obtained in the presence of only one radionuclide (sequential imaging) were significantly lower with 5D-GFA (9.4% +/- 4.3% for 99mTc-HMPAO and 8.7% +/-4.1% for 123I-DAT) compared to biases greater than 15% for volumes of interest (VOI) over the reconstructed volumes (p < 0.05). 5D-GFA is a novel and promising approach in dynamic SPECT imaging that can also be used in other modalities. It allows accurate and precise dynamic analysis while compensating for Compton scatter and cross-talk.
我们已将单光子发射计算机断层扫描(SPECT)成像中的谱因子分析和动态序列因子分析(FADS)推广为一种五维通用因子分析模型(5D - GFA),其中五个维度分别是三个空间维度、光子能量和时间。在动态SPECT研究的因子分析问题中,该广义模型在方程数量与未知数数量之比方面具有显著优势。我们使用最小二乘法求解5D模型。除了传统的非负性约束外,我们还利用时间和能量的先验知识对解进行约束,假设主要因子(谱)呈高斯形状,半高宽等于伽马相机能量分辨率。5D - GFA在一项突触前/后双同位素动态体模研究中得到验证,该研究使用99mTc和123I的活度来模拟早期帕金森病研究。5D - GFA还应用于恒河猴的同步灌注/多巴胺转运体(DAT)动态SPECT。在纹状体体模中,与传统的FADS相比,5D - GFA对主要的99mTc(偏差 = 6.4% ± 4.3%)和123I( - 1.7% ± 6.9%)时间 - 活度曲线(TAC)产生了显著更准确和精确的估计(99mTc的偏差为15.5% ± 10.6%,123I的偏差为8.3% ± 12.7%,p < 0.05)。我们的技术还在两项灵长类动物动态双同位素灌注/DAT转运体研究中得到验证。与在仅存在一种放射性核素(序贯成像)的情况下获得的估计值相比,5D - GFA对99mTc - HMPAO和123I - DAT活度估计的偏差显著更低(99mTc - HMPAO为9.4% ± 4.3%,123I - DAT为8.7% ± 4.1%),而重建体积上感兴趣区域(VOI)的偏差大于15%(p < 0.05)。5D - GFA是动态SPECT成像中一种新颖且有前景的方法,也可用于其他模态。它能够在补偿康普顿散射和串扰的同时进行准确而精确的动态分析。