Fralin Biomedical Research Institute at Virginia Tech Carilion, Virginia Tech, Roanoke, VA, United States; Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA, United States.
Department of Biomedical Engineering, University of Virginia, United States.
Methods. 2024 Nov;231:78-93. doi: 10.1016/j.ymeth.2024.09.008. Epub 2024 Sep 14.
We present a comprehensive methodology for measuring heterogeneous interstitial fluid flow in murine brain tumors using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) coupled with the computational tool, Lymph4D. This four-part protocol encompasses glioma cell preparation, tumor inoculation, MRI imaging protocol, and histological verification using Evans Blue. While conventional DCE-MRI analysis primarily focuses on vascular perfusion, our methods reveal untapped potential to extract crucial information about interstitial fluid dynamics, including directions, velocities, and diffusion coefficients. This methodology extends beyond glioma research, with applicability to conditions routinely imaged with DCE-MRI, thereby offering a versatile tool for investigating interstitial fluid dynamics across a wide range of diseases and conditions. Our methodology holds promise for accelerating discoveries and advancements in biomedical research, ultimately enhancing diagnostic and therapeutic strategies for a wide range of diseases and conditions.
我们提出了一种使用动态对比增强磁共振成像(DCE-MRI)结合计算工具 Lymph4D 来测量小鼠脑肿瘤中不均匀间质液流动的综合方法。该四部分方案包括神经胶质瘤细胞制备、肿瘤接种、MRI 成像方案以及使用 Evans Blue 的组织学验证。虽然传统的 DCE-MRI 分析主要集中在血管灌注上,但我们的方法揭示了提取间质液动力学关键信息的潜力,包括方向、速度和扩散系数。这种方法不仅限于神经胶质瘤研究,还适用于常规 DCE-MRI 成像的情况,因此为研究广泛的疾病和病症中的间质液动力学提供了一种通用工具。我们的方法有望加速生物医学研究的发现和进展,最终为广泛的疾病和病症的诊断和治疗策略提供帮助。