Department of Bioengineering, University of Washington, Seattle, Washington 98195-5601, USA.
Ann N Y Acad Sci. 2010 Feb;1188:111-20. doi: 10.1111/j.1749-6632.2009.05090.x.
Large-scale models accounting for the processes supporting metabolism and function in an organ or tissue with a marked heterogeneity of flows and metabolic rates are computationally complex and tedious to compute. Their use in the analysis of data from positron emission tomography (PET) and magnetic resonance imaging (MRI) requires model reduction since the data are composed of concentration-time curves from hundreds of regions of interest (ROI) within the organ. Within each ROI, one must account for blood flow, intracapillary gradients in concentrations, transmembrane transport, and intracellular reactions. Using modular design, we configured a whole organ model, GENTEX, to allow adaptive usage for multiple reacting molecular species while omitting computation of unused components. The temporal and spatial resolution and the number of species are adaptable and the numerical accuracy and computational speed is adjustable during optimization runs, which increases accuracy and spatial resolution as convergence approaches. An application to the interpretation of PET image sequences after intravenous injection of 13NH3 provides functional image maps of regional myocardial blood flows.
大规模模型考虑到支持器官或组织中代谢和功能的过程,其具有明显的流动和代谢率异质性,计算起来非常复杂且繁琐。由于数据由器官内数百个感兴趣区域(ROI)的浓度-时间曲线组成,因此在分析正电子发射断层扫描(PET)和磁共振成像(MRI)的数据时需要进行模型简化。在每个 ROI 中,必须考虑到血流、毛细血管内浓度梯度、跨膜转运和细胞内反应。我们使用模块化设计,配置了一个完整的器官模型 GENTEX,允许对多种反应分子物种进行自适应使用,同时省略未使用组件的计算。时间和空间分辨率以及物种数量是可适应的,并且在优化运行期间可以调整数值精度和计算速度,这会随着收敛的接近而提高精度和空间分辨率。将其应用于静脉注射 13NH3 后的 PET 图像序列的解释,提供了局部心肌血流的功能图像地图。