Section for Biomedical Physics, Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany.
Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia.
Med Phys. 2017 Jun;44(6):2358-2368. doi: 10.1002/mp.12228. Epub 2017 Apr 20.
Tumor hypoxia is a major cause of radiation resistance, often present in various solid tumors. Dynamic [ F]-fluoromisonidazole (FMISO) PET imaging is able to reliably assess tumor hypoxia. Comprehensive characterization of tumor microenvironment through FMISO-PET and dynamic contrast enhanced (DCE) MR multimodality imaging might be a valuable alternative to the dynamic FMISO-PET acquisition. The aim of this work was to explore the correlation between the FMISO-PET and DCE-MRI kinetic parameters.
This study was done on head and neck cancer patients (N = 6), who were imaged dynamically with FMISO-PET and DCE-MRI on the same day. Images were registered and analyzed for kinetics on a voxel basis. FMISO-PET images were analyzed with the two-tissue compartment three rate-constant model. Additionally, tumor-to-muscle ratio (TMR) maps were evaluated. DCE-MRI was analyzed with the extended Tofts model. Voxel-wise Pearson's coefficients were calculated for each patient to assess pairwise parameter correlations.
Median correlations between FMISO uptake parameters and DCE-MRI kinetic parameters varied across the parameter pairs in the range from -0.05 to 0.71. The highest median correlation of r = 0.71 was observed for the pair V -v , while the K -K median correlation was r = 0.45. Median correlation coefficients for the K -v and the K -K pairs were r = 0.42 and r = 0.32, respectively. Correlations between FMISO uptake rate parameter K and DCE-MRI kinetic parameters varied substantially across the patients, whereas correlations between the FMISO and DCE-MRI vascular parameters were consistently high. Median TMR-K and TMR-K correlations were r = 0.52 and r = 0.46, respectively, but varied substantially across the patients.
Based on this clinical evidence, we can conclude that the vascular fraction parameters obtained through DCE-MRI kinetic analysis or FMISO kinetic analysis measure the same biological property, while other kinetic parameters are unrelated. These results might be useful in the design of future clinical trials involving FMISO-PET/DCE-MR multimodality imaging for the assessment of tumor microenvironment.
肿瘤缺氧是导致放射抵抗的主要原因,常存在于各种实体瘤中。动态 [ F]-氟米索硝唑(FMISO)PET 成像能够可靠地评估肿瘤缺氧。通过 FMISO-PET 和动态对比增强(DCE)MR 多模态成像对肿瘤微环境进行全面特征描述可能是替代动态 FMISO-PET 采集的有价值的方法。本研究旨在探讨 FMISO-PET 和 DCE-MRI 动力学参数之间的相关性。
本研究纳入了 6 例头颈部癌症患者,他们在同一天接受了 FMISO-PET 和 DCE-MRI 动态成像。对图像进行配准,并在体素基础上进行动力学分析。FMISO-PET 图像采用双组织室三速率常数模型进行分析。此外,还评估了肿瘤与肌肉比(TMR)图。DCE-MRI 采用扩展 Tofts 模型进行分析。为每个患者计算了体素间 Pearson 系数,以评估两两参数相关性。
FMISO 摄取参数与 DCE-MRI 动力学参数之间的中位数相关性在参数对之间的范围从 -0.05 到 0.71 不等。V -v 对之间的最高中位数相关性 r = 0.71,而 K -K 的中位数相关性 r = 0.45。K -v 和 K -K 对的中位数相关系数 r 分别为 0.42 和 0.32。FMISO 摄取率参数 K 与 DCE-MRI 动力学参数之间的相关性在患者之间差异很大,而 FMISO 与 DCE-MRI 血管参数之间的相关性则始终较高。TMR-K 和 TMR-K 的中位数相关性 r 分别为 0.52 和 0.46,但在患者之间差异很大。
基于这项临床证据,我们可以得出结论,通过 DCE-MRI 动力学分析或 FMISO 动力学分析获得的血管分数参数测量的是相同的生物学特性,而其他动力学参数则不相关。这些结果可能有助于设计未来涉及 FMISO-PET/DCE-MR 多模态成像评估肿瘤微环境的临床试验。