Linninger Andreas A, Somayaji Mahadevabharath R, Erickson Terrianne, Guo Xiaodong, Penn Richard D
Laboratory for Product and Process Design, Department of Chemical Engineering and Bioengineering, University of Illinois at Chicago, 851 S. Morgan Street-218, Chicago, IL 60607, USA.
J Biomech. 2008 Jul 19;41(10):2176-87. doi: 10.1016/j.jbiomech.2008.04.025. Epub 2008 Jun 11.
Effective drug delivery for many neurodegenerative diseases or tumors of the central nervous system is challenging. Targeted invasive delivery of large macromolecules such as trophic factors to desired locations inside the brain is difficult due to anisotropy and heterogeneity of the brain tissue. Despite much experimental research, prediction of bio-transport phenomena inside the brain remains unreliable. This article proposes a rigorous computational approach for accurately predicting the fate of infused therapeutic agents inside the brain. Geometric and physiological properties of anisotropic and heterogeneous brain tissue affecting drug transport are accounted for by in-vivo diffusion tensor magnetic resonance imaging data. The three-dimensional brain anatomy is reconstructed accurately from subject-specific medical images. Tissue anisotropy and heterogeneity are quantified with the help of diffusion tensor imaging (DTI). Rigorous first principles physical transport phenomena are applied to predict the fate of a high molecular weight trophic factor infused into the midbrain. Computer prediction of drug distribution in humans accounting for heterogeneous and anisotropic brain tissue properties have not been adequately researched in open literature before.
对许多神经退行性疾病或中枢神经系统肿瘤进行有效的药物递送具有挑战性。由于脑组织的各向异性和异质性,将诸如营养因子等大型大分子靶向侵入性递送至脑内的期望位置十分困难。尽管进行了大量实验研究,但对脑内生物传输现象的预测仍然不可靠。本文提出了一种严格的计算方法,用于准确预测注入脑内的治疗药物的命运。影响药物传输的各向异性和异质性脑组织的几何和生理特性通过体内扩散张量磁共振成像数据来考虑。从特定个体的医学图像精确重建三维脑解剖结构。借助扩散张量成像(DTI)对组织各向异性和异质性进行量化。应用严格的第一原理物理传输现象来预测注入中脑的高分子量营养因子的命运。在公开文献中,此前尚未对考虑异质性和各向异性脑组织特性的人体药物分布计算机预测进行充分研究。