Chatterjee Krishnashis, Atay Naciye, Abler Daniel, Bhargava Saloni, Sahoo Prativa, Rockne Russell C, Munson Jennifer M
Department of Biomedical Engineering & Mechanics, Fralin Biomedical Research Institute, Virginia Tech, Roanoke, VA 24016, USA.
Department of Computational and Quantitative Medicine, Division of Mathematical Oncology, Beckman Research Institute, City of Hope, Duarte, CA 91010, USA.
Pharmaceutics. 2021 Feb 4;13(2):212. doi: 10.3390/pharmaceutics13020212.
Glioblastoma (GBM) is the deadliest and most common brain tumor in adults, with poor survival and response to aggressive therapy. Limited access of drugs to tumor cells is one reason for such grim clinical outcomes. A driving force for therapeutic delivery is interstitial fluid flow (IFF), both within the tumor and in the surrounding brain parenchyma. However, convective and diffusive transport mechanisms are understudied. In this study, we examined the application of a novel image analysis method to measure fluid flow and diffusion in GBM patients.
Here, we applied an imaging methodology that had been previously tested and validated in vitro, in silico, and in preclinical models of disease to archival patient data from the Ivy Glioblastoma Atlas Project (GAP) dataset. The analysis required the use of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which is readily available in the database. The analysis results, which consisted of IFF flow velocity and diffusion coefficients, were then compared to patient outcomes such as survival.
We characterized IFF and diffusion patterns in patients. We found strong correlations between flow rates measured within tumors and in the surrounding parenchymal space, where we hypothesized that velocities would be higher. Analyzing overall magnitudes indicated a significant correlation with both age and survival in this patient cohort. Additionally, we found that neither tumor size nor resection significantly altered the velocity magnitude. Lastly, we mapped the flow pathways in patient tumors and found a variability in the degree of directionality that we hypothesize may lead to information concerning treatment, invasive spread, and progression in future studies.
An analysis of standard DCE-MRI in patients with GBM offers more information regarding IFF and transport within and around the tumor, shows that IFF is still detected post-resection, and indicates that velocity magnitudes correlate with patient prognosis.
胶质母细胞瘤(GBM)是成人中最致命且最常见的脑肿瘤,生存率低且对积极治疗反应不佳。药物难以进入肿瘤细胞是导致如此严峻临床结果的原因之一。治疗递送的一个驱动力是肿瘤内部和周围脑实质中的组织液流动(IFF)。然而,对流和扩散传输机制的研究较少。在本研究中,我们检验了一种新型图像分析方法在测量GBM患者液体流动和扩散方面的应用。
在此,我们将一种先前已在体外、计算机模拟和疾病临床前模型中进行过测试和验证的成像方法应用于来自常春藤胶质母细胞瘤图谱项目(GAP)数据集的存档患者数据。该分析需要使用动态对比增强磁共振成像(DCE-MRI),而数据库中很容易获取这种成像数据。然后将由IFF流速和扩散系数组成的分析结果与患者生存等结局进行比较。
我们对患者的IFF和扩散模式进行了特征描述。我们发现在肿瘤内部和周围实质空间测量的流速之间存在强相关性,我们原本假设后者的流速会更高。对总体大小的分析表明,在该患者队列中与年龄和生存均存在显著相关性。此外,我们发现肿瘤大小和切除均未显著改变流速大小。最后,我们绘制了患者肿瘤中的流动路径,发现方向性程度存在差异,我们推测这可能会在未来研究中为治疗、侵袭性扩散和进展提供相关信息。
对GBM患者的标准DCE-MRI进行分析可提供更多关于肿瘤内部和周围的IFF及传输的信息,表明切除后仍可检测到IFF,并表明流速大小与患者预后相关。