S Pioli

Bio: S Pioli is an academic researcher from Sapienza University of Rome. The author has contributed to research in topics: CPU time & Monte Carlo method. The author has an hindex of 2, co-authored 2 publications receiving 40 citations.

Fred: a GPU-accelerated fast-Monte Carlo code for rapid treatment plan recalculation in ion beam therapy.

Abstract: Ion beam therapy is a rapidly growing technique for tumor radiation therapy. Ions allow for a high dose deposition in the tumor region, while sparing the surrounding healthy tissue. For this reason, the highest possible accuracy in the calculation of dose and its spatial distribution is required in treatment planning. On one hand, commonly used treatment planning software solutions adopt a simplified beam-body interaction model by remapping pre-calculated dose distributions into a 3D water-equivalent representation of the patient morphology. On the other hand, Monte Carlo (MC) simulations, which explicitly take into account all the details in the interaction of particles with human tissues, are considered to be the most reliable tool to address the complexity of mixed field irradiation in a heterogeneous environment. However, full MC calculations are not routinely used in clinical practice because they typically demand substantial computational resources. Therefore MC simulations are usually only used to check treatment plans for a restricted number of difficult cases. The advent of general-purpose programming GPU cards prompted the development of trimmed-down MC-based dose engines which can significantly reduce the time needed to recalculate a treatment plan with respect to standard MC codes in CPU hardware. In this work, we report on the development of fred, a new MC simulation platform for treatment planning in ion beam therapy. The code can transport particles through a 3D voxel grid using a class II MC algorithm. Both primary and secondary particles are tracked and their energy deposition is scored along the trajectory. Effective models for particle-medium interaction have been implemented, balancing accuracy in dose deposition with computational cost. Currently, the most refined module is the transport of proton beams in water: single pencil beam dose-depth distributions obtained with fred agree with those produced by standard MC codes within 1-2% of the Bragg peak in the therapeutic energy range. A comparison with measurements taken at the CNAO treatment center shows that the lateral dose tails are reproduced within 2% in the field size factor test up to 20 cm. The tracing kernel can run on GPU hardware, achieving 10 million primary [Formula: see text] on a single card. This performance allows one to recalculate a proton treatment plan at 1% of the total particles in just a few minutes.

A fast - Monte Carlo toolkit on GPU for treatment plan dose recalculation in proton therapy

Abstract: In the context of the particle therapy a crucial role is played by Treatment Planning Systems (TPSs), tools aimed to compute and optimize the tratment plan. Nowadays one of the major issues related to the TPS in particle therapy is the large CPU time needed. We developed a software toolkit (FRED) for reducing dose recalculation time by exploiting Graphics Processing Units (GPU) hardware. Thanks to their high parallelization capability, GPUs significantly reduce the computation time, up to factor 100 respect to a standard CPU running software. The transport of proton beams in the patient is accurately described through Monte Carlo methods. Physical processes reproduced are: Multiple Coulomb Scattering, energy straggling and nuclear interactions of protons with the main nuclei composing the biological tissues. FRED toolkit does not rely on the water equivalent translation of tissues, but exploits the Computed Tomography anatomical information by reconstructing and simulating the atomic composition of each crossed tissue. FRED can be used as an efficient tool for dose recalculation, on the day of the treatment. In fact it can provide in about one minute on standard hardware the dose map obtained combining the treatment plan, earlier computed by the TPS, and the current patient anatomic arrangement.

Roadmap: proton therapy physics and biology

Abstract: The treatment of cancer with proton radiation therapy was first suggested in 1946 followed by the first treatments in the 1950s. As of 2020, almost 200,000 patients have been treated with proton beams worldwide and the number of operating proton therapy facilities will soon reach one hundred. Proton therapy has long moved from research institutions into hospital-based facilities that are increasingly being utilized with workflows similar to conventional radiation therapy. While proton therapy has become mainstream and has established itself as a treatment option for many cancers, it is still an area of active research for various reasons: the advanced dose shaping capabilities of proton therapy cause susceptibility to uncertainties, the high degrees of freedom in dose delivery offer room for further improvements, the limited experience and understanding of optimizing pencil beam scanning, and the biological effects differ from photon radiation. In addition to these challenges and opportunities currently being investigated, there is an economic aspect because proton therapy treatments are, on average, still more expensive compared to conventional photon based treatment options. This roadmap highlights the current state and future direction in proton therapy categorized into four different themes, "improving efficiency", "improving planning and delivery", "improving imaging", and "improving patient selection".

Fast robust dose calculation on GPU for high-precision 1 H, 4 He, 12 C and 16 O ion therapy: the FRoG platform

Abstract: Radiotherapy with protons and heavier ions landmarks a novel era in the field of high-precision cancer therapy. To identify patients most benefiting from this technologically demanding therapy, fast assessment of comparative treatment plans utilizing different ion species is urgently needed. Moreover, to overcome uncertainties of actual in-vivo physical dose distribution and biological effects elicited by different radiation qualities, development of a reliable high-throughput algorithm is required. To this end, we engineered a unique graphics processing unit (GPU) based software architecture allowing rapid and robust dose calculation. FRoG, Fast Recalculation on GPU, currently operates with four particle beams available at Heidelberg Ion Beam Therapy center, i.e., raster-scanning proton (1H), helium (4He), carbon (12C) and oxygen ions (16O). FRoG enables comparative analysis of different models for estimation of physical and biological effective dose in 3D within minutes and in excellent agreement with the gold standard Monte Carlo (MC) simulation. This is a crucial step towards development of next-generation patient specific radiotherapy.

Technical Note: Integrating an open source Monte Carlo code “MCsquare” for clinical use in intensity-modulated proton therapy

Abstract: PURPOSE To commission an open source Monte Carlo (MC) dose engine, "MCsquare" for a synchrotron-based proton machine, integrate it into our in-house C++-based I/O user interface and our web-based software platform, expand its functionalities, and improve calculation efficiency for intensity-modulated proton therapy (IMPT). METHODS We commissioned MCsquare using a double Gaussian beam model based on in-air lateral profiles, integrated depth dose of 97 beam energies, and measurements of various spread-out Bragg peaks (SOBPs). Then we integrated MCsquare into our C++-based dose calculation code and web-based second check platform "DOSeCHECK." We validated the commissioned MCsquare based on 12 different patient geometries and compared the dose calculation with a well-benchmarked GPU-accelerated MC (gMC) dose engine. We further improved the MCsquare efficiency by employing the computed tomography (CT) resampling approach. We also expanded its functionality by adding a linear energy transfer (LET)-related model-dependent biological dose calculation. RESULTS Differences between MCsquare calculations and SOBP measurements were <2.5% (<1.5% for ~85% of measurements) in water. The dose distributions calculated using MCsquare agreed well with the results calculated using gMC in patient geometries. The average 3D gamma analysis (2%/2 mm) passing rates comparing MCsquare and gMC calculations in the 12 patient geometries were 98.0 ± 1.0%. The computation time to calculate one IMPT plan in patients' geometries using an inexpensive CPU workstation (Intel Xeon E5-2680 2.50 GHz) was 2.3 ± 1.8 min after the variable resolution technique was adopted. All calculations except for one craniospinal patient were finished within 3.5 min. CONCLUSIONS MCsquare was successfully commissioned for a synchrotron-based proton beam therapy delivery system and integrated into our web-based second check platform. After adopting CT resampling and implementing LET model-dependent biological dose calculation capabilities, MCsquare will be sufficiently efficient and powerful to achieve Monte Carlo-based and LET-guided robust optimization in IMPT, which will be done in the future studies.

Evaluation of electromagnetic and nuclear scattering models in GATE/Geant4 for proton therapy.

Abstract: Purpose The dose core of a proton pencil beam (PB) is enveloped by a low dose area reaching several centimeters off the central axis and containing a considerable amount of the dose. Adequate modeling of the different components of the PB profile is, therefore, required for accurate dose calculation. In this study, we experimentally validated one electromagnetic and two nuclear scattering models in GATE/Geant4 for dose calculation of proton beams in the therapeutic energy window (62-252 MeV) with and without range shifter (RaShi). Methods The multiple Coulomb scattering (MCS) model was validated by lateral dose core profiles measured for five energies at up to four depths from beam plateau to Bragg peak region. Nuclear halo profiles of single PBs were evaluated for three (62.4, 148.2, and 252.7 MeV) and two (97.4 and 124.7 MeV) energies, without and with RaShi, respectively. The influence of the dose core and nuclear halo on field sizes varying from 2-20 cm was evaluated by means of output factors (OFs), namely frame factors (FFs) and field size factors (FSFs), to quantify the relative increase of dose when increasing the field size. Results The relative increase in the dose core width in the simulations deviated negligibly from measurements for depths until 80% of the beam range, but was overestimated by up to 0.2 mm in σ toward the end of range for all energies. The dose halo region of the lateral dose profile agreed well with measurements in the open beam configuration, but was notably overestimated in the deepest measurement plane of the highest energy or when the beam passed through the RaShi. The root-mean-square deviations (RMSDs) between the simulated and the measured FSFs were less than 1% at all depths, but were higher in the second half of the beam range as compared to the first half or when traversing the RaShi. The deviations in one of the two tested hadron physics lists originated mostly in elastic scattering. The RMSDs could be reduced by approximately a factor of two by exchanging the default elastic scattering cross sections for protons. Conclusions GATE/Geant4 agreed satisfyingly with most measured quantities. MCS was systematically overestimated toward the end of the beam range. Contributions from nuclear scattering were overestimated when the beam traversed the RaShi or at the depths close to the end of the beam range without RaShi. Both, field size effects and calculation uncertainties, increased when the beam traversed the RaShi. Measured field size effects were almost negligible for beams up to medium energy and were highest for the highest energy beam without RaShi, but vice versa when traversing the RaShi.