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Visualizing vasculature and its response to therapy in the tumor microenvironment.

ABSTRACT: Tumor vasculature plays a critical role in the progression and metastasis of tumors, antitumor immunity, drug delivery, and resistance to therapies. The morphological and functional changes of tumor vasculature in response to therapy take place in a spatiotemporal-dependent manner, which can be predictive of treatment outcomes. Dynamic monitoring of intratumor vasculature contributes to an improved understanding of the mechanisms of action of specific therapies or reasons for treatment failure, leading to therapy optimization. There is a rich history of methods used to image the vasculature. This review describes recent advances in imaging technologies to visualize the tumor vasculature, with a focus on enhanced intravital imaging techniques and tumor window models. We summarize new insights on spatial-temporal vascular responses to various therapies, including changes in vascular perfusion and permeability and immune-vascular crosstalk, obtained from intravital imaging. Finally, we briefly discuss the clinical applications of intravital imaging techniques.

SUBMITTER: Lin Q

PROVIDER: S-EPMC10614675 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Visualizing vasculature and its response to therapy in the tumor microenvironment.

Lin Qiaoya Q Choyke Peter L PL Sato Noriko N

Theranostics 20230925 15

Tumor vasculature plays a critical role in the progression and metastasis of tumors, antitumor immunity, drug delivery, and resistance to therapies. The morphological and functional changes of tumor vasculature in response to therapy take place in a spatiotemporal-dependent manner, which can be predictive of treatment outcomes. Dynamic monitoring of intratumor vasculature contributes to an improved understanding of the mechanisms of action of specific therapies or reasons for treatment failure, ...[more]

PMID: 37908739

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Project description:BACKGROUND:Intra-and inter-tumoral heterogeneity in growth dynamics and vascularity influence tumor response to radiation therapy. Quantitative imaging techniques capture these dynamics non-invasively, and these data can initialize and constrain predictive models of response on an individual basis. METHODS:We have developed a family of 10 biologically-based mathematical models describing the spatiotemporal dynamics of tumor volume fraction, blood volume fraction, and response to radiation therapy. To evaluate this family of models, rats (n?=?13) with C6 gliomas were imaged with magnetic resonance imaging (MRI) three times before, and four times following a single fraction of 20?Gy or 40?Gy whole brain irradiation. The first five 3D time series data of tumor volume fraction, estimated from diffusion-weighted (DW-) MRI, and blood volume fraction, estimated from dynamic contrast-enhanced (DCE-) MRI, were used to calibrate tumor-specific model parameters. The most parsimonious and well calibrated of the 10 models, selected using the Akaike information criterion, was then utilized to predict future growth and response at the final two imaging time points. Model predictions were compared at the global level (percent error in tumor volume, and Dice coefficient) as well as at the local or voxel level (concordance correlation coefficient). RESULT:The selected model resulted in <?12% error in tumor volume predictions, strong spatial agreement between predicted and observed tumor volumes (Dice coefficient?>?0.74), and high level of agreement at the voxel level between the predicted and observed tumor volume fraction and blood volume fraction (concordance correlation coefficient?>?0.77 and?>?0.65, respectively). CONCLUSIONS:This study demonstrates that serial quantitative MRI data collected before and following radiation therapy can be used to accurately predict tumor and vasculature response with a biologically-based mathematical model that is calibrated on an individual basis. To the best of our knowledge, this is the first effort to characterize the tumor and vasculature response to radiation therapy temporally and spatially using imaging-driven mathematical models.

Dataset Information

Visualizing vasculature and its response to therapy in the tumor microenvironment.

Publications

Visualizing vasculature and its response to therapy in the tumor microenvironment.

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