Simulating photodynamic therapy for the treatment of glioblastoma using Monte Carlo radiative transport
Louise Finlayson1, Lewis McMillan1, Szabolcs Suveges2
1SUPA, University of St Andrews, School of Physics and Astronomy, St Andrews, United Kingdom.
Significance:
Glioblastoma (GBM) is a rare but deadly form of brain tumor with a low median survival rate of 14.6 months, due to its resistance to treatment. An independent simulation of the INtraoperative photoDYnamic therapy for GliOblastoma (INDYGO) trial, a clinical trial aiming to treat the GBM resection cavity with photodynamic therapy (PDT) via a laser coupled balloon device, is demonstrated.
Aim:
To develop a framework providing increased understanding for the PDT treatment, its parameters, and their impact on the clinical outcome.
Approach:
We use Monte Carlo radiative transport techniques within a computational brain model containing a GBM to simulate light path and PDT effects. Treatment parameters (laser power, photosensitizer concentration, and irradiation time) are considered, as well as PDT's impact on brain tissue temperature.
Results:
The simulation suggests that 39% of post-resection GBM cells are killed at the end of treatment when using the standard INDYGO trial protocol (light fluence = at balloon wall) and assuming an initial photosensitizer concentration of . Increases in treatment time and light power (light fluence = at balloon wall) result in further cell kill but increase brain cell temperature, which potentially affects treatment safety. Increasing the p hotosensitizer concentration produces the most significant increase in cell kill, with 61% of GBM cells killed when doubling concentration to and keeping the treatment time and power the same. According to these simulations, the standard trial protocol is reasonably well optimized with improvements in cell kill difficult to achieve without potentially dangerous increases in temperature. To improve treatment outcome, focus should be placed on improving the photosensitizer.
Conclusions:
With further development and optimization, the simulation could have potential clinical benefit and be used to help plan and optimize intraoperative PDT treatment for GBM.
Insights
Photodynamic therapy (PDT) simulations show that increasing photosensitizer concentration significantly improves glioblastoma (GBM) cell kill. Optimizing PDT requires focusing on photosensitizer development for better glioblastoma treatment outcomes.
Area of Science:
- Computational modeling
- Biomedical engineering
- Oncology
Background:
- Glioblastoma (GBM) presents a significant therapeutic challenge due to its resistance to conventional treatments, leading to poor patient prognoses.
- Photodynamic therapy (PDT) offers a promising approach for treating residual GBM cells in the resection cavity.
- The INtraoperative photoDYnamic therapy for GliOblastoma (INDYGO) trial investigates PDT for GBM treatment.
Purpose of the Study:
- To develop a computational framework for simulating PDT in GBM.
- To analyze the impact of key PDT parameters on treatment efficacy and safety.
- To provide insights for optimizing intraoperative PDT protocols.
Main Methods:
- Utilized Monte Carlo radiative transport simulations within a computational brain model.
- Modeled glioblastoma (GBM) tumor environment and light propagation.
- Investigated effects of laser power, photosensitizer concentration, and irradiation time on cell kill and tissue temperature.
Main Results:
- Standard INDYGO protocol achieved 39% GBM cell kill.
- Increasing photosensitizer concentration to resulted in 61% cell kill.
- Higher laser power or longer irradiation increased cell kill but also elevated brain tissue temperature, raising safety concerns.
Conclusions:
- The standard INDYGO PDT protocol is relatively optimized, with significant improvements in cell kill challenging without increasing temperature risks.
- Enhancing photosensitizer efficacy is crucial for improving GBM treatment outcomes.
- The developed simulation framework holds potential for clinical application in planning and optimizing intraoperative PDT for GBM.
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