Computational fluid dynamics with imaging of cleared tissue and of in vivo perfusion predicts drug uptake and treatment responses in tumours

• Published in: Nature biomedical engineering Vol. 2; no. 10; pp. 773 - 787
• Main Authors: d’Esposito, Angela, Sweeney, Paul W., Ali, Morium, Saleh, Magdy, Ramasawmy, Rajiv, Roberts, Thomas A., Agliardi, Giulia, Desjardins, Adrien, Lythgoe, Mark F., Pedley, R. Barbara, Shipley, Rebecca, Walker-Samuel, Simon
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.10.2018; Nature Publishing Group
• Subjects: 13/106; 14/34; 14/63; 59/57; 631/57/2266; 631/67; 631/67/2329; 692/700/1421/1628; 692/700/1421/2025; Animal models; Animals; Antineoplastic Agents - metabolism; Antineoplastic Agents - pharmacology; Antineoplastic Agents - therapeutic use; Biomedical and Life Sciences; Biomedical Engineering/Biotechnology; Biomedicine; Blood flow; Blood Vessels - drug effects; Blood Vessels - physiology; Cell Line, Tumor; Chemical compounds; Colorectal carcinoma; Colorectal Neoplasms - diagnostic imaging; Colorectal Neoplasms - drug therapy; Computational fluid dynamics; Computer applications; Contrast Media - chemistry; Contrast Media - metabolism; Diphosphates - metabolism; Diphosphates - therapeutic use; Disease Models, Animal; Equilibrium flow; Female; Fluid pressure; Gadolinium; Gadolinium - chemistry; Gadolinium - metabolism; Glioma; Glioma - diagnostic imaging; Glioma - drug therapy; Humans; Hydrodynamics; Image Processing, Computer-Assisted; Image resolution; Mathematical analysis; Mathematical models; Mice; Mice, Inbred C57BL; Mice, Nude; Models, Theoretical; Pathophysiology; Perfusion; Pharmacology; Regional Blood Flow; Spatial distribution; Stilbenes - metabolism; Stilbenes - therapeutic use; Temporal distribution; Transplantation, Heterologous; Tumors
• ISSN: 2157-846X; 2157-846X
• DOI: 10.1038/s41551-018-0306-y

Understanding the uptake of a drug by diseased tissue, and the drug’s subsequent spatiotemporal distribution, are central factors in the development of effective targeted therapies. However, the interaction between the pathophysiology of diseased tissue and individual therapeutic agents can be complex, and can vary across tissue types and across subjects. Here, we show that the combination of mathematical modelling, high-resolution optical imaging of intact and optically cleared tumour tissue from animal models, and in vivo imaging of vascular perfusion predicts the heterogeneous uptake, by large tissue samples, of specific therapeutic agents, as well as their spatiotemporal distribution. In particular, by using murine models of colorectal cancer and glioma, we report and validate predictions of steady-state blood flow and intravascular and interstitial fluid pressure in tumours, of the spatially heterogeneous uptake of chelated gadolinium by tumours, and of the effect of a vascular disrupting agent on tumour vasculature. The combination of mathematical modelling of tumour tissue, optical imaging of cleared tumours from animal models, and in vivo imaging of vascular perfusion in tumours predicts the tumour uptake and distribution of specific therapeutic agents.