Cancer Research UK/MRC Oxford Institute for Radiation Oncology, Gray Laboratories, Department of Oncology, University of Oxford, Oxford, UK.
Radiation Physics and Protection, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Med Phys. 2017 Sep;44(9):4665-4676. doi: 10.1002/mp.12416. Epub 2017 Jul 21.
The aim of this study was to determine the relative abilities of compartment models to describe time-courses of F-fluoromisonidazole (FMISO) uptake in tumor voxels of patients with non-small cell lung cancer (NSCLC) imaged using dynamic positron emission tomography. Also to use fits of the best-performing model to investigate changes in fitted rate-constants with distance from the tumor edge.
Reversible and irreversible two- and three-tissue compartment models were fitted to 24 662 individual voxel time activity curves (TACs) obtained from tumors in nine patients, each imaged twice. Descriptions of the TACs provided by the models were compared using the Akaike and Bayesian information criteria (AIC and BIC). Two different models (two- and three-tissue) were fitted to 30 measured voxel TACs to provide ground-truth TACs for a statistical simulation study. Appropriately scaled noise was added to each of the resulting ground-truth TACs, generating 1000 simulated noisy TACs for each ground-truth TAC. The simulation study was carried out to provide estimates of the accuracy and precision with which parameter values are determined, the estimates being obtained for both assumptions about the ground-truth kinetics. A BIC clustering technique was used to group the fitted rate-constants, taking into consideration the underlying uncertainties on the fitted rate-constants. Voxels were also categorized according to their distance from the tumor edge.
For uptake time-courses of individual voxels an irreversible two-tissue compartment model was found to be most precise. The simulation study indicated that this model had a one standard deviation precision of 39% for tumor fractional blood volumes and 37% for the FMISO binding rate-constant. Weighted means of fitted FMISO binding rate-constants of voxels in all tumors rose significantly with increasing distance from the tumor edge, whereas fitted fractional blood volumes fell significantly. When grouped using the BIC clustering, many centrally located voxels had high-fitted FMISO binding rate-constants and low rate-constants for tracer flow between the vasculature and tumor, both indicative of hypoxia. Nevertheless, many of these voxels had tumor-to-blood (TBR) values lower than the 1.4 level commonly expected for hypoxic tissues, possibly due to the low rate-constants for tracer flow between the vasculature and tumor cells in these voxels.
Time-courses of FMISO uptake in NSCLC tumor voxels are best analyzed using an irreversible two-tissue compartment model, fits of which provide more precise parameter values than those of a three-tissue model. Changes in fitted model parameter values indicate that levels of hypoxia rise with increasing distance from tumor edges. The average FMISO binding rate-constant is higher for voxels in tumor centers than in the next tumor layer out, but the average value of the more simplistic TBR metric is lower in tumor centers. For both metrics, higher values might be considered indicative of hypoxia, and the mismatch in this case is likely to be due to poor perfusion at the tumor center. Kinetics analysis of dynamic PET images may therefore provide more accurate measures of the hypoxic status of such regions than the simpler TBR metric, a hypothesis we are presently exploring in a study of tumor imaging versus histopathology.
本研究旨在确定房室模型相对能力，以描述使用动态正电子发射断层扫描对非小细胞肺癌（NSCLC）患者肿瘤体素进行氟代米索硝唑（FMISO）摄取的时间过程。还利用表现最佳模型的拟合来研究肿瘤边缘距离与拟合率常数的变化。
将可逆和不可逆的两室和三室房室模型拟合到 9 名患者的 24662 个肿瘤体素时间活动曲线（TAC），每个患者都进行了两次成像。使用 Akaike 和贝叶斯信息准则（AIC 和 BIC）比较模型对 TAC 的描述。将两种不同的模型（两室和三室）拟合到 30 个测量的体素 TAC，为统计模拟研究提供地面真实 TAC。为每个地面真实 TAC 适当缩放噪声，为每个地面真实 TAC 生成 1000 个模拟噪声 TAC。进行了模拟研究，以提供参数值确定的准确性和精密度的估计值，这两个估计值都是基于对地面真实动力学的假设。使用 BIC 聚类技术根据拟合率常数的潜在不确定性对其进行分组。还根据与肿瘤边缘的距离对体素进行分类。
对于个体体素的摄取时间过程，发现不可逆的两室房室模型最为精确。模拟研究表明，对于肿瘤的部分血容量，该模型的标准差精度为 39%，对于 FMISO 结合率常数的标准差精度为 37%。所有肿瘤中体素拟合的 FMISO 结合率常数的加权平均值随着与肿瘤边缘距离的增加而显著升高，而拟合的部分血容量则显著降低。使用 BIC 聚类进行分组时，许多中央体素具有高拟合的 FMISO 结合率常数和示踪剂在脉管系统和肿瘤之间流动的低率常数，这两者都表明存在缺氧。尽管如此，许多这些体素的肿瘤与血液（TBR）值低于 1.4，这是缺氧组织通常预期的水平，这可能是由于这些体素中示踪剂在脉管系统和肿瘤细胞之间的流动率常数较低。
使用不可逆的两室房室模型对 NSCLC 肿瘤体素的 FMISO 摄取时间过程进行分析最佳，其拟合提供了比三室模型更精确的参数值。拟合模型参数值的变化表明，缺氧水平随肿瘤边缘距离的增加而升高。位于肿瘤中心的体素的平均 FMISO 结合率常数高于下一肿瘤层的体素，但肿瘤中心的更简单 TBR 指标的平均值较低。对于这两个指标，较高的值可能被认为是缺氧的指标，而在这种情况下的不匹配很可能是由于肿瘤中心的灌注不良。因此，与简单的 TBR 指标相比，动态 PET 图像的动力学分析可能为这些区域的缺氧状态提供更准确的测量，我们目前正在一项肿瘤成像与组织病理学的研究中探索这一假设。
