Magnetic resonance imaging-guided radiation therapy using animal models of glioblastoma

Glioblastoma multiforme: Diagnosis, treatment, and invasion

Glioblastoma multiforme (GBM) is an essentially incurable brain tumor, which has been explored for approximately a century. Nowadays, surgical resection, chemotherapy, and radiation therapy are still the standardized therapeutic options. However, due to the intrinsic invasion and metastasis features and the resistance to chemotherapy, the survival rate of glioblastoma patients remains unsatisfactory. To improve the current situation, much more research is needed to provide comprehensive knowledge of GBM. In this review, we summarize the latest updates on GBM treatment and invasion. Firstly, we review the traditional and emerging therapies that have been used for GBM treatment. Given the limited efficiency of these therapies, we further discuss the role of invasion in GBM recurrence and progression, and present current research progress on the mode and mechanisms of GBM invasion.

Mobile bioluminescence tomography-guided system for pre-clinical radiotherapy research

Due to low imaging contrast, a widely-used cone-beam computed tomography-guided small animal irradiator is less adept at localizing in vivo soft tissue targets. Bioluminescence tomography (BLT), which combines a model of light propagation through tissue with an optimization algorithm, can recover a spatially resolved tomographic volume for an internal bioluminescent source. We built a novel mobile BLT system for a small animal irradiator to localize soft tissue targets for radiation guidance. In this study, we elaborate its configuration and features that are indispensable for accurate image guidance. Phantom and in vivo validations show the BLT system can localize targets with accuracy within 1 mm. With the optimal choice of threshold and margin for target volume, BLT can provide a distinctive opportunity for investigators to perform conformal biology-guided irradiation to malignancy.

A deep learning and Monte Carlo based framework for bioluminescence imaging center of mass-guided glioblastoma targeting

Objective. Bioluminescence imaging (BLI) is a valuable tool for non-invasive monitoring of glioblastoma multiforme (GBM) tumor-bearing small animals without incurring x-ray radiation burden. However, the use of this imaging modality is limited due to photon scattering and lack of spatial information. Attempts at reconstructing bioluminescence tomography (BLT) using mathematical models of light propagation show limited progress. Approach. This paper employed a different approach by using a deep convolutional neural network (CNN) to predict the tumor’s center of mass (CoM). Transfer-learning with a sizeable artificial database is employed to facilitate the training process for, the much smaller, target database including Monte Carlo (MC) simulations of real orthotopic glioblastoma models. Predicted CoM was then used to estimate a BLI-based planning target volume (bPTV), by using the CoM as the center of a sphere, encompassing the tumor. The volume of the encompassing target sphere was estimated based on the total number of photons reaching the skin surface. Main results. Results show sub-millimeter accuracy for CoM prediction with a median error of 0.59 mm. The proposed method also provides promising performance for BLI-based tumor targeting with on average 94% of the tumor inside the bPTV while keeping the average healthy tissue coverage below 10%. Significance. This work introduced a framework for developing and using a CNN for targeted radiation studies for GBM based on BLI. The framework will enable biologists to use BLI as their main image-guidance tool to target GBM tumors in rat models, avoiding delivery of high x-ray imaging dose to the animals.

Evolution of the Supermodel: Progress in Modelling Radiotherapy Response in Mice

Mouse models are essential tools in cancer research that have been used to understand the genetic basis of tumorigenesis, cancer progression and to test the efficacies of anticancer treatments including radiotherapy. They have played a critical role in our understanding of radiotherapy response in tumours and normal tissues and continue to evolve to better recapitulate the underlying biology of humans. In addition, recent developments in small animal irradiators have significantly improved in vivo irradiation techniques, allowing previously unimaginable experimental approaches to be explored in the laboratory. The combination of contemporary mouse models with small animal irradiators represents a major step forward for the radiobiology field in being able to much more accurately replicate clinical exposure scenarios. As radiobiology studies become ever more sophisticated in reflecting developments in the clinic, it is increasingly important to understand the basis and potential limitations of extrapolating data from mice to humans. This review provides an overview of mouse models and small animal radiotherapy platforms currently being used as advanced radiobiological research tools towards improving the translational power of preclinical studies.