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Updated: Jul 5, 2025
A Novel High-resolution In vivo Imaging Technique to Study the Dynamic Response of Intracranial Structures to Tumor Growth and Therapeutics
Published on: June 16, 2013
Therapy-induced modulation of tumor vasculature and oxygenation in a murine glioblastoma model quantified by deep
Nadine Bauer1,2, Daniel Beckmann3,4, Dirk Reinhardt1
1European Institute for Molecular Imaging (EIMI), Multiscale Imaging Centre (MIC), University of Münster, Röntgenstr. 16, 48149, Münster, Germany.
Abstract:
Glioblastoma presents characteristically with an exuberant, poorly functional vasculature that causes malperfusion, hypoxia and necrosis. Despite limited clinical efficacy, anti-angiogenesis resulting in vascular normalization remains a promising therapeutic approach. Yet, fundamental questions concerning anti-angiogenic therapy remain unanswered, partly due to the scale and resolution gap between microscopy and clinical imaging and a lack of quantitative data readouts. To what extend does treatment lead to vessel regression or vessel normalization and does it ameliorate or aggravate hypoxia? Clearly, a better understanding of the underlying mechanisms would greatly benefit the development of desperately needed improved treatment regimens. Here, using orthotopic transplantation of Gli36 cells, a widely used murine glioma model, we present a mesoscopic approach based on light sheet fluorescence microscopic imaging of wholemount stained tumors. Deep learning-based segmentation followed by automated feature extraction allowed quantitative analyses of the entire tumor vasculature and oxygenation statuses. Unexpectedly in this model, the response to both cytotoxic and anti-angiogenic therapy was dominated by vessel normalization with little evidence for vessel regression. Equally surprising, only cytotoxic therapy resulted in a significant alleviation of hypoxia. Taken together, we provide and evaluate a quantitative workflow that addresses some of the most urgent mechanistic questions in anti-angiogenic therapy.
Insights
Anti-angiogenic therapy for glioblastoma surprisingly promoted vessel normalization, not regression. Cytotoxic therapy, however, was the only effective treatment for reducing tumor hypoxia, highlighting the need for better therapeutic strategies.
Area of Science:
- Oncology
- Vascular Biology
- Medical Imaging
Background:
- Glioblastoma exhibits abnormal vasculature, leading to poor blood flow, oxygen deprivation (hypoxia), and tissue death (necrosis).
- Anti-angiogenic therapies aim to normalize tumor vasculature but their precise effects on vessel structure and hypoxia remain unclear.
- Current research faces limitations due to the gap between microscopic and clinical imaging scales and a lack of quantitative data.
Purpose of the Study:
- To investigate the impact of anti-angiogenic and cytotoxic therapies on glioblastoma vasculature and oxygenation.
- To evaluate a mesoscopic imaging approach for quantitative analysis of tumor microenvironment.
- To address fundamental questions regarding vessel normalization versus regression and hypoxia alleviation in response to therapy.
Main Methods:
- Utilized an orthotopic murine glioma model (Gli36 cells).
- Employed light-sheet fluorescence microscopy for wholemount tumor imaging.
- Applied deep learning for automated segmentation and feature extraction to analyze vasculature and oxygenation.
Main Results:
- Both cytotoxic and anti-angiogenic therapies predominantly induced vessel normalization, with minimal evidence of vessel regression.
- Only cytotoxic therapy significantly alleviated tumor hypoxia.
- The developed quantitative workflow enabled detailed analysis of treatment effects.
Conclusions:
- The study reveals unexpected responses to glioblastoma therapies, emphasizing vessel normalization over regression.
- Cytotoxic therapy demonstrates superior efficacy in mitigating tumor hypoxia compared to anti-angiogenic approaches.
- The quantitative mesoscopic imaging workflow provides a valuable tool for mechanistic studies in anti-angiogenic therapy research.
