Monte-Carlo model development for evaluation of current clinical target volume definition for heterogeneous and hypoxic glioblastoma

An Integrated Monte Carlo Model for Heterogeneous Glioblastoma Treated with Boron Neutron Capture Therapy

BACKGROUND

Glioblastomas (GBMs) are notorious for their aggressive features, e.g., intrinsic radioresistance, extensive heterogeneity, hypoxia, and highly infiltrative behaviours. The prognosis has remained poor despite recent advances in systemic and modern X-ray radiotherapy. Boron neutron capture therapy (BNCT) represents an alternative radiotherapy technique for GBM. Previously, a Geant4 BNCT modelling framework was developed for a simplified model of GBM.

PURPOSE

The current work expands on the previous model by applying a more realistic in silico GBM model with heterogeneous radiosensitivity and anisotropic microscopic extensions (ME).

METHODS

Each cell within the GBM model was assigned an α/β value associated with different GBM cell lines and a 10B concentration. Dosimetry matrices corresponding to various MEs were calculated and combined to evaluate cell survival fractions (SF) using clinical target volume (CTV) margins of 2.0 & 2.5 cm. SFs for the BNCT simulation were compared with external X-ray radiotherapy (EBRT) SFs.

RESULTS

The SFs within the beam region decreased by more than two times compared to EBRT. It was demonstrated that BNCT results in markedly reduced SFs for both CTV margins compared to EBRT. However, the SF reduction as a result of the CTV margin extension using BNCT was significantly lower than using X-ray EBRT for one MEP distribution, while it remained similar for the other two MEP models.

CONCLUSIONS

Although the efficiency of BNCT in terms of cell kill is superior to EBRT, the extension of the CTV margin by 0.5 cm may not increase the BNCT treatment outcome significantly.

Geant4 beam model for boron neutron capture therapy: investigation of neutron dose components

Boron neutron capture therapy (BNCT) is a biochemically-targeted type of radiotherapy, selectively delivering localized dose to tumour cells diffused in normal tissue, while minimizing normal tissue toxicity. BNCT is based on thermal neutron capture by stable [Formula: see text]B nuclei resulting in emission of short-ranged alpha particles and recoil [Formula: see text]Li nuclei. The purpose of the current work was to develop and validate a Monte Carlo BNCT beam model and to investigate contribution of individual dose components resulting of neutron interactions. A neutron beam model was developed in Geant4 and validated against published data. The neutron beam spectrum, obtained from literature for a cyclotron-produced beam, was irradiated to a water phantom with boron concentrations of 100 μg/g. The calculated percentage depth dose curves (PDDs) in the phantom were compared with published data to validate the beam model in terms of total and boron depth dose deposition. Subsequently, two sensitivity studies were conducted to quantify the impact of: (1) neutron beam spectrum, and (2) various boron concentrations on the boron dose component. Good agreement was achieved between the calculated and measured neutron beam PDDs (within 1%). The resulting boron depth dose deposition was also in agreement with measured data. The sensitivity study of several boron concentrations showed that the calculated boron dose gradually converged beyond 100 μg/g boron concentration. This results suggest that 100μg/g tumour boron concentration may be optimal and above this value limited increase in boron dose is expected for a given neutron flux.

Computational modeling in glioblastoma: from the prediction of blood-brain barrier permeability to the simulation of tumor behavior

The integrated in silico-in vitro-in vivo approaches have fostered the development of new treatment strategies for glioblastoma patients and improved diagnosis, establishing the bridge between biochemical research and clinical practice. These approaches have provided new insights on the identification of bioactive compounds and on the complex mechanisms underlying the interactions among glioblastoma cells, and the tumor microenvironment. This review focuses on the key advances pertaining to computational modeling in glioblastoma, including predictive data on drug permeability across the blood-brain barrier, tumor growth and treatment responses. Structure- and ligand-based methods have been widely adopted, enabling the study of dynamic and evolutionary aspects of glioblastoma. Their potential applications as predictive tools and the advantages over other well-known methodologies are outlined. Challenges regarding in silico approaches for predicting tumor properties are also discussed.

Development of an integrated Monte Carlo model for glioblastoma multiforme treated with boron neutron capture therapy

Glioblastomas (GBM) are notorious for their high fatality rate. Boron Neutron Capture Therapy (BNCT) being a biochemically targeted type of radiotherapy is a potent modality for GBM. In the current work, a BNCT treatment modelling framework for GBM was developed. Optimal Clinical Target Volume (CTV) margins for GBM-BNCT and the BNCT efficacy have been investigated. The model integrated a cell-based dosimetry model, an in-house-developed epithermal neutron beam model and previously-developed Microscopic Extension Probability (MEP) model. The system was defined as a cubic ICRP-brain phantom divided into 20 μm side voxels. The corresponding ¹⁰B concentrations in GBM and normal brain cells were applied. The in-silico model was irradiated with the epithermal neutron beam using 2 and 2.5 cm CTV margins. Results from the cell-based dosimetry and the MEP models were combined to calculate GBM cell survival fractions (SF) post BNCT and compared to x-ray radiotherapy (XRT) SFs. Compared to XRT, the SF within the beam decreased by five orders of magnitudes and the total SF was reduced three times following BNCT. CTV extension by 0.5 cm reduced the SF by additional (53.8 ± 0.3)%. In conclusion, BNCT results in a more efficient cell kill. The extension of the CTV margin, however, may not increase the treatment outcome significantly.