| dc.contributor |
Biomedical Engineering and Mechanics |
|
| dc.contributor |
Fralin Biomedical Research Institute |
|
| dc.creator |
Chatterjee, Krishnashis |
|
| dc.creator |
Atay, Naciye |
|
| dc.creator |
Abler, Daniel |
|
| dc.creator |
Bhargava, Saloni |
|
| dc.creator |
Sahoo, Prativa |
|
| dc.creator |
Rockne, Russell C. |
|
| dc.creator |
Munson, Jennifer M. |
|
| dc.date |
2021-02-05T17:10:47Z |
|
| dc.date |
2021-02-05T17:10:47Z |
|
| dc.date |
2021-02-04 |
|
| dc.date |
2021-02-05T14:10:17Z |
|
| dc.date.accessioned |
2023-03-01T18:52:11Z |
|
| dc.date.available |
2023-03-01T18:52:11Z |
|
| dc.identifier |
Chatterjee, K.; Atay, N.; Abler, D.; Bhargava, S.; Sahoo, P.; Rockne, R.C.; Munson, J.M. Utilizing Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to Analyze Interstitial Fluid Flow and Transport in Glioblastoma and the Surrounding Parenchyma in Human Patients. Pharmaceutics 2021, 13, 212. |
|
| dc.identifier |
http://hdl.handle.net/10919/102276 |
|
| dc.identifier |
https://doi.org/10.3390/pharmaceutics13020212 |
|
| dc.identifier.uri |
http://localhost:8080/xmlui/handle/CUHPOERS/281594 |
|
| dc.description |
Background: 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. Methods: 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. Results: 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. Conclusions: 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. |
|
| dc.description |
Published version |
|
| dc.format |
application/pdf |
|
| dc.format |
application/pdf |
|
| dc.language |
en |
|
| dc.publisher |
MDPI |
|
| dc.rights |
Creative Commons Attribution 4.0 International |
|
| dc.rights |
http://creativecommons.org/licenses/by/4.0/ |
|
| dc.subject |
glioblastoma (GBM) |
|
| dc.subject |
DCE-MRI |
|
| dc.subject |
interstitial flow |
|
| dc.subject |
convection |
|
| dc.subject |
diffusion |
|
| dc.subject |
Cancer Imaging Archive |
|
| dc.title |
Utilizing Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to Analyze Interstitial Fluid Flow and Transport in Glioblastoma and the Surrounding Parenchyma in Human Patients |
|
| dc.title |
Pharmaceutics |
|
| dc.type |
Article - Refereed |
|
| dc.type |
Text |
|