Center for Advanced Medical Imaging Sciences NMMI, Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA,
Mol Imaging Biol. 2013 Dec;15(6):666-74. doi: 10.1007/s11307-013-0631-1.
With single-photon emission computed tomography, simultaneous imaging of two physiological processes relies on discrimination of the energy of the emitted gamma rays, whereas the application of dual-tracer imaging to positron emission tomography (PET) imaging has been limited by the characteristic 511-keV emissions.
To address this limitation, we developed a novel approach based on generalized factor analysis of dynamic sequences (GFADS) that exploits spatio-temporal differences between radiotracers and applied it to near-simultaneous imaging of 2-deoxy-2-[(18)F]fluoro-D-glucose (FDG) (brain metabolism) and (11)C-raclopride (D2) with simulated human data and experimental rhesus monkey data. We show theoretically and verify by simulation and measurement that GFADS can separate FDG and raclopride measurements that are made nearly simultaneously.
The theoretical development shows that GFADS can decompose the studies at several levels: (1) It decomposes the FDG and raclopride study so that they can be analyzed as though they were obtained separately. (2) If additional physiologic/anatomic constraints can be imposed, further decomposition is possible. (3) For the example of raclopride, specific and nonspecific binding can be determined on a pixel-by-pixel basis. We found good agreement between the estimated GFADS factors and the simulated ground truth time activity curves (TACs), and between the GFADS factor images and the corresponding ground truth activity distributions with errors less than 7.3 ± 1.3 %. Biases in estimation of specific D2 binding and relative metabolism activity were within 5.9 ± 3.6 % compared to the ground truth values. We also evaluated our approach in simultaneous dual-isotope brain PET studies in a rhesus monkey and obtained accuracy of better than 6 % in a mid-striatal volume, for striatal activity estimation.
Dynamic image sequences acquired following near-simultaneous injection of two PET radiopharmaceuticals can be separated into components based on the differences in the kinetics, provided their kinetic behaviors are distinct.
利用单光子发射计算机断层扫描，两种生理过程的同时成像依赖于发射伽马射线能量的区分，而双示踪剂成像在正电子发射断层扫描（PET）成像中的应用受到特征性 511keV 发射的限制。
为了解决这一限制，我们开发了一种基于动态序列广义因子分析（GFADS）的新方法，该方法利用示踪剂之间的时空差异，并将其应用于 2-脱氧-2-[(18)F]氟-D-葡萄糖（FDG）（脑代谢）和（11)C-氯普噻吨（D2）的近同时成像，具有模拟人体数据和实验恒河猴数据。我们从理论上进行了证明，并通过模拟和测量验证了 GFADS 可以分离几乎同时进行的 FDG 和氯普噻吨测量。
理论发展表明，GFADS 可以在多个层面上分解研究：（1）它分解 FDG 和氯普噻吨研究，以便可以将它们作为单独获得的进行分析。（2）如果可以施加额外的生理/解剖约束，则可以进一步分解。（3）对于氯普噻吨的示例，可以逐像素确定特异性和非特异性结合。我们发现，估计的 GFADS 因子与模拟的地面真实时间活动曲线（TAC）之间以及 GFADS 因子图像与相应的地面真实活动分布之间的吻合度较好，误差小于 7.3±1.3%。与地面真实值相比，特异性 D2 结合和相对代谢活性的估计偏差小于 5.9±3.6%。我们还在恒河猴的同时双同位素脑 PET 研究中评估了我们的方法，并在中纹状体体积中获得了准确性优于 6%的纹状体活动估计。
在近同时注射两种 PET 放射性药物后获得的动态图像序列可以根据动力学差异分离成成分，只要它们的动力学行为不同。
