Abstract
Glioblastoma progression involves multifaceted changes in vascularity, cellularity, and metabolism. Capturing such complexities of the tumor niche, from the tumor core to the periphery, by magnetic resonance imaging (MRI) and spectroscopic imaging (MRSI) methods has translational impact. In human-derived glioblastoma models (U87, U251) we made simultaneous and longitudinal measurements of tumor perfusion (Fp), permeability (Ktrans), and volume fractions of extracellular (ve) and blood (vp) spaces from dynamic contrast enhanced (DCE) MRI, cellularity from apparent diffusion coefficient (ADC) MRI, and extracellular pH (pHe) from an MRSI method called Biosensor Imaging of Redundant Deviation in Shifts (BIRDS). Spatiotemporal patterns of these parameters during tumorigenesis were unique for each tumor. While U87 tumors grew faster, Fp, Ktrans, and vp increased with tumor growth in both tumors but these trends were more pronounced for U251 tumors. Perfused regions between tumor periphery and core with U87 tumors exhibited higher Fp, but Ktrans of U251 tumors remained lowest at the tumor margin, suggesting primitive vascularization. Tumor growth was uncorrelated with ve, ADC, and pHe. U87 tumors showed correlated regions of reduced ve and lower ADC (higher cellularity), suggesting ongoing proliferation. U251 tumors revealed that the tumor core had higher ve and elevated ADC (lower cellularity), suggesting necrosis development. The entire tumor was uniformly acidic (pHe 6.1-6.8) early and throughout progression, but U251 tumors were more acidic, suggesting lower aerobic glycolysis in U87 tumors. Characterizing these cancer hallmarks with DCE-MRI, ADC-MRI, and BIRDS-MRSI will be useful for exploring tumorigenesis as well as timely therapies targeted to specific vascular and metabolic aspects of the tumor microenvironment.
Highlights
Glioblastomas (GBM) are the most frequently occurring and aggressive primary brain tumors in adults [1]
We aim to demonstrate multi-modal longitudinal characterization of the GBM microenvironment in preclinical GBM models to highlight the spatial heterogeneity that exists in tumor cellularity, vascularity, and metabolism and how it changes throughout tumor progression
A total of 29 time points were acquired across 15 rats with U87 tumors and 23 time points acquired across 13 rats with U251 tumors (Supplementary Table 1)
Summary
Glioblastomas (GBM) are the most frequently occurring and aggressive primary brain tumors in adults [1]. Contrast-enhanced T1-weighted and T2 fluid-attenuated recovery (FLAIR) images are used for clinical detection and size monitoring after treatment [3]; there remain numerous unmet imaging needs as many findings are nonspecific and do not allow for direct mapping of the tumor microenvironment that may be reflective of treatment response [4] These imaging contrasts largely ignore spatial heterogeneity as tumors are extremely diverse in their anatomic features, do not highlight variation in tumor metabolism and vasculature which are reflective of different genetic mutations in GBM, and are confounded in the setting of different therapies, especially anti-angiogenic therapies, that results in drastic changes in the imaging findings despite little change in the structural tumor architecture [5]. We aim to demonstrate multi-modal longitudinal characterization of the GBM microenvironment in preclinical GBM models to highlight the spatial heterogeneity that exists in tumor cellularity, vascularity, and metabolism and how it changes throughout tumor progression
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