Workshop Report for Cancer Research: Defining the Shades of Gy: Utilizing the Biological Consequences of Radiotherapy in the Development of New Treatment Approaches—Meeting Viewpoint

The ability to physically target radiotherapy using image-guidance is continually improving with photons and particle therapy that include protons and heavier ions such as carbon. The unit of dose deposited is the gray (Gy); however, particle therapies produce different patterns of ionizations, and there is evidence that the biological effects of radiation depend on dose size, schedule, and type of radiation. This National Cancer Institute (NCI)–sponsored workshop addressed the potential of using radiation-induced biological perturbations in addition to physical dose, Gy, as a transformational approach to quantifying radiation

Monte Carlo Processing on a Chip (MCoaC)-preliminary experiments toward the realization of optimal-hardware for TOPAS/Geant4 to drive discovery

Amongst the scientific frameworks powered by the Monte Carlo (MC) toolkit Geant4 (Agostinelli et al., 2003), the TOPAS (Tool for Particle Simulation) (Perl et al., 2012) is one. TOPAS focuses on providing ease of use, and has significant implementation in the radiation oncology space at present. TOPAS functionality extends across the full capacity of Geant4, is freely available to non-profit users, and is being extended into radiobiology via TOPAS-nBIO (Ramos-Mendez et al., 2018). A current "grand problem" in cancer therapy is to convert the dose of treatment from physical dose to biological dose, optimized ultimately to the individual context of administration of treatment. Biology MC calculations are some of the most complex and require significant computational resources. In order to enhance TOPAS's ability to become a critical tool to explore the definition and application of biological dose in radiation therapy, we chose to explore the use of Field Programmable Gate Array (FPGA) chips to speedup the Geant4 calculations at the heart of TOPAS, because this approach called "Reconfigurable Computing" (RC), has proven able to produce significant (around 90x) (Sajish et al., 2012) speed increases in scientific computing. Here, we describe initial steps to port Geant4 and TOPAS to be used on FPGA. We provide performance analysis of the current TOPAS/Geant4 code from an RC implementation perspective. Baseline benchmarks are presented. Achievable performance figures of the subsections of the code on optimal hardware are presented; Aspects of practical implementation of "Monte Carlo on a chip" are also discussed

Understanding High-Dose, Ultra-High Dose Rate, and Spatially Fractionated Radiation Therapy.

The National Cancer Institute's Radiation Research Program, in collaboration with the Radiosurgery Society, hosted a workshop called Understanding High-Dose, Ultra-High Dose Rate and Spatially Fractionated Radiotherapy on August 20 and 21, 2018 to bring together experts in experimental and clinical experience in these and related fields. Critically, the overall aims were to understand the biological underpinning of these emerging techniques and the technical/physical parameters that must be further defined to drive clinical practice through innovative biologically based clinical trials