Abstract 2581: Measuring interstitial fluid flow to predict and optimize spatial CAR-T dynamics in the clinic

Abstract Interstitial fluid flow dynamics in brain tumors are known to be an important indicator for tumor invasion into healthy tissue, as cancerous cells follow the interstitial flow towards tumor-stimulating chemokines. These flow gradients not only carry tumor-stimulating chemokines, but also carry cytokines secreted by immune response. CAR-T cells are known to also depend highly on the cytokines present in the CSF and serum. For these reasons, we have developed a novel method, Localized Convolutional Function Regression (LCFR) for measuring interstitial fluid flow, perfusion, and diffusion using dynamic contrast-enhanced MRI. LCFR works by applying the known physics of contrast agent transport, and fitting the observed contrast agent dynamics to the known physics. From LCFR, we can recover standard Tofts-Kety perfusion dynamics, including Ktrans and Vp, and also recover the underlying flow field and diffusivity. These new measurements allow for the prediction of where tumors invade, and allow for us to model how CAR-T cells move within a tumor. In a case study, we model the spatial distribution of CAR-T cells and glioblastoma cells over time, assuming that the fluid velocity field drives CAR-T spread throughout the tumor. Using multiple delivery locations, we identify the optimal catheter placement to optimally distribute CAR-T cells through the tumor, improving the 50% kill rate of simulated tumor cells by over 25% from a naive delivery strategy. Further, we collect longitudinal cytokine levels from patients undergoing CAR-T therapy, allowing us to understand how interstitial flow, CAR-T dynamics, and tumor dynamics interact with each other. We report a case study wherein a patient is longitudinally followed through their treatment with CAR-Ts. Perfusion imaging reveals that the patient experienced a steady increase in perfusion and decrease in fluid leakage into surrounding tissue. VEGF and IL12 levels are observed to increase as tumor volume increases. To better understand this patient's dynamics, we use the fluid velocity field measured by LCFR to simulate the development of CAR-T cells within the tumor, using the cytokine profile as a surrogate measurement of CAR-T population. These results demonstrate the importance of fluid flow and cytokines in understanding how brain tumors develop and respond to treatment. Citation Format: Ryan T. Woodall, Cora Esparza, Christine C. Brown, Jennifer M. Munson, Russell C. Rockne. Measuring interstitial fluid flow to predict and optimize spatial CAR-T dynamics in the clinic abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 2581.