Parallelized Monte-Carlo dosimetry using graphics processing units to model cylindrical diffusers used in photodynamic therapy: From implementation to validation

Simple Characterization of Cylindrical Diffuser Fibers With a Fluorescent Layer

OBJECTIVES

A fast, simple, versatile, and reliable method to record light emission intensity profiles of cylindrical light diffusers (CDFs) in air and transparent liquids has been developed.

METHODS

A fluorescent color glass filter (RG695) converts red light emitted by a cylindrical diffuser fiber into near-infrared light in an emission angle-independent manner. The red light was provided from a diode laser system at 635 nm. Near-infrared fluorescence from the RG695 was imaged with a camera. Images from this camera were processed to obtain emission intensity profiles. Cylindrical diffuser fiber profiles of four different manufacturers were compared.

RESULTS

The proposed method provides angle-independent intensity profiles of cylindrical diffuser fibers with a single camera shot. It could be demonstrated that dependent on the underlying principle of how the diffuser fiber tips emit light, the emission profile can change significantly in media with different refractive indices.

CONCLUSIONS

By converting the light emitted by a diffuser fiber tip into fluorescence light one can eliminate the dependence of the recorded profile on the emission angle from the diffusor. This approach allows for easily taking into account refraction-index (mis)matching by placing the equipment into a suitable liquid. The proposed measurement principle bears potential for quality assurance measurements of CDFs used for interstitial laser thermotherapy or photodynamic therapy.

Devices and Methods for Dosimetry of Personalized Photodynamic Therapy of Tumors: A Review on Recent Trends

Significance: Despite the widespread use of photodynamic therapy in clinical practice, there is a lack of personalized methods for assessing the sufficiency of photodynamic exposure on tumors, depending on tissue parameters that change during light irradiation. This can lead to different treatment results. Aim: The objective of this article was to conduct a comprehensive review of devices and methods employed for the implicit dosimetric monitoring of personalized photodynamic therapy for tumors. Methods: The review included 88 peer-reviewed research articles published between January 2010 and April 2024 that employed implicit monitoring methods, such as fluorescence imaging and diffuse reflectance spectroscopy. Additionally, it encompassed computer modeling methods that are most often and successfully used in preclinical and clinical practice to predict treatment outcomes. The Internet search engine Google Scholar and the Scopus database were used to search the literature for relevant articles. Results: The review analyzed and compared the results of 88 peer-reviewed research articles presenting various methods of implicit dosimetry during photodynamic therapy. The most prominent wavelengths for PDT are in the visible and near-infrared spectral range such as 405, 630, 660, and 690 nm. Conclusions: The problem of developing an accurate, reliable, and easily implemented dosimetry method for photodynamic therapy remains a current problem, since determining the effective light dose for a specific tumor is a decisive factor in achieving a positive treatment outcome.

Simulating photodynamic therapy for the treatment of glioblastoma using Monte Carlo radiative transport

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 = 200    J / cm 2 at balloon wall) and assuming an initial photosensitizer concentration of 5    μ M . Increases in treatment time and light power (light fluence = 400    J / cm 2 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 10    μ M 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.

Integrating clinical access limitations into iPDT treatment planning with PDT-SPACE

PDT-SPACE is an open-source software tool that automates interstitial photodynamic therapy treatment planning by providing patient-specific placement of light sources to destroy a tumor while minimizing healthy tissue damage. This work extends PDT-SPACE in two ways. The first enhancement allows specification of clinical access constraints on light source insertion to avoid penetrating critical structures and to minimize surgical complexity. Constraining fiber access to a single burr hole of adequate size increases healthy tissue damage by 10%. The second enhancement generates an initial placement of light sources as a starting point for refinement, rather than requiring entry of a starting solution by the clinician. This feature improves productivity and also leads to solutions with 4.5% less healthy tissue damage. The two features are used in concert to perform simulations of various surgery options of virtual glioblastoma multiforme brain tumors.

Moving Forward in the Next Decade: Radiation Oncology Sciences for Patient-Centered Cancer Care

In a time of rapid advances in science and technology, the opportunities for radiation oncology are undergoing transformational change. The linkage between and understanding of the physical dose and induced biological perturbations are opening entirely new areas of application. The ability to define anatomic extent of disease and the elucidation of the biology of metastases has brought a key role for radiation oncology for treating metastatic disease. That radiation can stimulate and suppress subpopulations of the immune response makes radiation a key participant in cancer immunotherapy. Targeted radiopharmaceutical therapy delivers radiation systemically with radionuclides and carrier molecules selected for their physical, chemical, and biochemical properties. Radiation oncology usage of “big data” and machine learning and artificial intelligence adds the opportunity to markedly change the workflow for clinical practice while physically targeting and adapting radiation fields in real time. Future precision targeting requires multidimensional understanding of the imaging, underlying biology, and anatomical relationship among tissues for radiation as spatial and temporal “focused biology.” Other means of energy delivery are available as are agents that can be activated by radiation with increasing ability to target treatments. With broad applicability of radiation in cancer treatment, radiation therapy is a necessity for effective cancer care, opening a career path for global health serving the medically underserved in geographically isolated populations as a substantial societal contribution addressing health disparities. Understanding risk and mitigation of radiation injury make it an important discipline for and beyond cancer care including energy policy, space exploration, national security, and global partnerships.

Receptor-Targeted Photodynamic Therapy of Glucagon-Like Peptide 1 Receptor-Positive Lesions

Treatment of hyperinsulinemic hypoglycemia is challenging. Surgical treatment of insulinomas and focal lesions in congenital hyperinsulinism is invasive and carries major risks of morbidity. Medication to treat nesidioblastosis and diffuse congenital hyperinsulinism has varying efficacy and causes significant side effects. Here, we describe a novel method for therapy of hyperinsulinemic hyperglycemia, highly selectively killing β-cells by receptor-targeted photodynamic therapy (rtPDT) with exendin-4-IRDye700DX, targeting the glucagon-like peptide 1 receptor (GLP-1R). Methods: A competitive binding assay was performed using Chinese hamster lung (CHL) cells transfected with the GLP-1R. The efficacy and specificity of rtPDT with exendin-4-IRDye700DX were examined in vitro in cells with different levels of GLP-1R expression. Tracer biodistribution was determined in BALB/c nude mice bearing subcutaneous CHL-GLP-1R xenografts. Induction of cellular damage and the effect on tumor growth were analyzed to determine treatment efficacy. Results: Exendin-4-IRDye700DX has a high affinity for the GLP-1R, with a half-maximal inhibitory concentration of 6.3 nM. rtPDT caused significant specific phototoxicity in GLP-1R–positive cells (2.3% ± 0.8% and 2.7% ± 0.3% remaining cell viability in CHL-GLP-1R and INS-1 cells, respectively). The tracer accumulates dose-dependently in GLP-1R–positive tumors. In vivo, rtPDT induces cellular damage in tumors, shown by strong expression of cleaved caspase-3, and leads to a prolonged median survival of the mice (36.5 vs. 22.5 d, respectively; P < 0.05). Conclusion: These data show in vitro as well as in vivo evidence of the potency of rtPDT using exendin-4-IRDye700DX. This approach might in the future provide a new, minimally invasive, highly specific treatment method for hyperinsulinemic hypoglycemia.

FullMonteCUDA: a fast, flexible, and accurate GPU-accelerated Monte Carlo simulator for light propagation in turbid media

Optimizing light delivery for photodynamic therapy, quantifying tissue optical properties or reconstructing 3D distributions of sources in bioluminescence imaging and absorbers in diffuse optical imaging all involve solving an inverse problem. This can require thousands of forward light propagation simulations to determine the parameters to optimize treatment, image tissue or quantify tissue optical properties, which is time-consuming and computationally expensive. Addressing this problem requires a light propagation simulator that produces results quickly given modelling parameters. In previous work, we developed FullMonteSW: currently the fastest, tetrahedral-mesh, Monte Carlo light propagation simulator written in software. Additional software optimizations showed diminishing performance improvements, so we investigated hardware acceleration methods. This work focuses on FullMonteCUDA: a GPU-accelerated version of FullMonteSW which targets NVIDIA GPUs. FullMonteCUDA has been validated across several benchmark models and, through various GPU-specific optimizations, achieves a 288-936x speedup over the single-threaded, non-vectorized version of FullMonteSW and a 4-13x speedup over the highly optimized, hand-vectorized and multi-threaded version. The increase in performance allows inverse problems to be solved more efficiently and effectively.