MRI analysis to map interstitial flow in the brain tumor microenvironment
| dc.contributor.author | Kingsmore, Kathryn M. | en |
| dc.contributor.author | Vaccari, Andrea | en |
| dc.contributor.author | Abler, Daniel | en |
| dc.contributor.author | Cui, Sophia X. | en |
| dc.contributor.author | Epstein, Frederick H. | en |
| dc.contributor.author | Rockne, Russell C. | en |
| dc.contributor.author | Acton, Scott T. | en |
| dc.contributor.author | Munson, Jennifer M. | en |
| dc.date.accessioned | 2021-01-04T17:26:40Z | en |
| dc.date.available | 2021-01-04T17:26:40Z | en |
| dc.date.issued | 2018-06-26 | en |
| dc.description.abstract | Glioblastoma (GBM), a highly aggressive form of brain tumor, is a disease marked by extensive invasion into the surrounding brain. Interstitial fluid flow (IFF), or the movement of fluid within the spaces between cells, has been linked to increased invasion of GBM cells. Better characterization of IFF could elucidate underlying mechanisms driving this invasion in vivo. Here, we develop a technique to noninvasively measure interstitial flow velocities in the glioma microenvironment of mice using dynamic contrast-enhanced magnetic resonance imaging (MRI), a common clinical technique. Using our in vitro model as a phantom “tumor” system and in silico models of velocity vector fields, we show we can measure average velocities and accurately reconstruct velocity directions. With our combined MR and analysis method, we show that velocity magnitudes are similar across four human GBM cell line xenograft models and the direction of fluid flow is heterogeneous within and around the tumors, and not always in the outward direction. These values were not linked to the tumor size. Finally, we compare our flow velocity magnitudes and the direction of flow to a classical marker of vessel leakage and bulk fluid drainage, Evans blue. With these data, we validate its use as a marker of high and low IFF rates and IFF in the outward direction from the tumor border in implanted glioma models. These methods show, for the first time, the nature of interstitial fluid flow in models of glioma using a technique that is translatable to clinical and preclinical models currently using contrast-enhanced MRI. | en |
| dc.description.sponsorship | This work was supported in part by ACS-IRG-81-001-29, NIH 1R01CA222563-01 to J. M. Munson and funding to K. M. Kingsmore by the NSF-GFRP. Additionally, research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under award number P30CA033572 to City of Hope and funding to D. Abler from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 753878. | en |
| dc.identifier.doi | https://doi.org/10.1063/1.5023503 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/101732 | en |
| dc.identifier.volume | 2 | en |
| dc.language.iso | en_US | en |
| dc.publisher | AIP Publishing | en |
| dc.rights | Attribution 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en |
| dc.title | MRI analysis to map interstitial flow in the brain tumor microenvironment | en |
| dc.title.serial | APL Bioengineering | en |
| dc.type | Article - Refereed | en |