Stopping power and range estimations in proton therapy based on prompt gamma timing: motion models and automated parameter optimization.

OBJECTIVE: Particle therapy treatments are currently limited by uncertainties of the delivered dose. Verification techniques like Prompt-Gamma-Timing-based Stopping Power Estimation (PGT-SPE) may allow for reduction of safety margins in treatment planning. Approach: From Prompt-Gamma-Timing measurements, we reconstruct the spatiotemporal distribution of prompt gamma emissions, which is linked to the average motion of the primary particles. The stopping power is determined by fitting a model of the average particle motion. Here, we compare a previously published implementation of the particle motion model with an alternative formulation and present two formulations to automatically select the hyperparameters of our procedure. The performance was assessed using Monte-Carlo simulations of proton beams (60 MeV to 219 MeV) impinging on a homogeneous PMMA phantom. Main results: The range was successfully determined within a standard deviation of 3 mm for proton beam energies from 70 MeV to 219 MeV. Stopping power estimates showed errors below 5 % for beam energies above 160 MeV. At lower energies, the estimation performance degraded to unsatisfactory levels due to the short range of the protons. The new motion model improved the estimation performance by up to 5 % for beam energies from 100 MeV to 150 MeV with mean errors ranging from 6 % to 18 %. The automated hyperparameter optimization matched the average error of previously reported manual selections, while significantly reducing the outliers. Significance: The data-driven hyperparameter optimization allowed for a reproducible and fast evaluation of our method. The updated motion model and evaluation at new beam energies bring us closer to applying PGT-SPE in more complex scenarios. Direct comparison of stopping power estimates between treatment planning and measurements during irradiation would offer a more direct verification than other secondary-particle-based techniques.

Using the gamma-index analysis for inter-fractional comparison of in-beam PET images for head-and-neck treatment monitoring in proton therapy: A Monte Carlo simulation study.

GOAL: In-beam Positron Emission Tomography (PET) is a technique for in-vivo non-invasive treatment monitoring for proton therapy. To detect anatomical changes in patients with PET, various analysis methods exist, but their clinical interpretation is problematic. The goal of this work is to investigate whether the gamma-index analysis, widely used for dose comparisons, is an appropriate tool for comparing in-beam PET distributions. Focusing on a head-and-neck patient, we investigate whether the gamma-index map and the passing rate are sensitive to progressive anatomical changes. METHODS/MATERIALS: We simulated a treatment course of a proton therapy patient using FLUKA Monte Carlo simulations. Gradual emptying of the sinonasal cavity was modeled through a series of artificially modified CT scans. The in-beam PET activity distributions from three fields were evaluated, simulating a planar dual head geometry. We applied the 3D-gamma evaluation method to compare the PET images with a reference image without changes. Various tolerance criteria and parameters were tested, and results were compared to the CT-scans. RESULTS: Based on 210 MC simulations we identified appropriate parameters for the gamma-index analysis. Tolerance values of 3 mm/3% and 2 mm/2% were suited for comparison of simulated in-beam PET distributions. The gamma passing rate decreased with increasing volume change for all fields. CONCLUSION: The gamma-index analysis was found to be a useful tool for comparing simulated in-beam PET images, sensitive to sinonasal cavity emptying. Monitoring the gamma passing rate behavior over the treatment course is useful to detect anatomical changes occurring during the treatment course.

Synthetic CT imaging for PET monitoring in proton therapy: a simulation study.

Objective.This study addresses a fundamental limitation of in-beam positron emission tomography (IB-PET) in proton therapy: the lack of direct anatomical representation in the images it produces. We aim to overcome this shortcoming by pioneering the application of deep learning techniques to create synthetic control CT images (sCT) from combining IB-PET and planning CT scan data.Approach.We conducted simulations involving six patients who underwent irradiation with proton beams. Leveraging the architecture of a visual transformer (ViT) neural network, we developed a model to generate sCT images of these patients using the planning CT scans and the inter-fractional simulated PET activity maps during irradiation. To evaluate the model's performance, a comparison was conducted between the sCT images produced by the ViT model and the authentic control CT images-serving as the benchmark.Main results.The structural similarity index was computed at a mean value across all patients of 0.91, while the mean absolute error measured 22 Hounsfield Units (HU). Root mean squared error and peak signal-to-noise ratio values were 56 HU and 30 dB, respectively. The Dice similarity coefficient exhibited a value of 0.98. These values are comparable to or exceed those found in the literature. More than 70% of the synthetic morphological changes were found to be geometrically compatible with the ones reported in the real control CT scan.Significance.Our study presents an innovative approach to surface the hidden anatomical information of IB-PET in proton therapy. Our ViT-based model successfully generates sCT images from inter-fractional PET data and planning CT scans. Our model's performance stands on par with existing models relying on input from cone beam CT or magnetic resonance imaging, which contain more anatomical information than activity maps.

Performance of LGAD strip detectors for particle counting of therapeutic proton beams.

Objective. The performance of silicon detectors with moderate internal gain, named low-gain avalanche diodes (LGADs), was studied to investigate their capability to discriminate and count single beam particles at high fluxes, in view of future applications for beam characterization and on-line beam monitoring in proton therapy.Approach. Dedicated LGAD detectors with an active thickness of 55µm and segmented in 2 mm2strips were characterized at two Italian proton-therapy facilities, CNAO in Pavia and the Proton Therapy Center of Trento, with proton beams provided by a synchrotron and a cyclotron, respectively. Signals from single beam particles were discriminated against a threshold and counted. The number of proton pulses for fixed energies and different particle fluxes was compared with the charge collected by a compact ionization chamber, to infer the input particle rates.Main results. The counting inefficiency due to the overlap of nearby signals was less than 1% up to particle rates in one strip of 1 MHz, corresponding to a mean fluence rate on the strip of about 5 × 107p/(cm2·s). Count-loss correction algorithms based on the logic combination of signals from two neighboring strips allow to extend the maximum counting rate by one order of magnitude. The same algorithms give additional information on the fine time structure of the beam.Significance. The direct counting of the number of beam protons with segmented silicon detectors allows to overcome some limitations of gas detectors typically employed for beam characterization and beam monitoring in particle therapy, providing faster response times, higher sensitivity, and independence of the counts from the particle energy.

Calibration method and performance of a time-of-flight detector to measure absolute beam energy in proton therapy.

BACKGROUND: The beam energy is one of the most significant parameters in particle therapy since it is directly correlated to the particles' penetration depth inside the patient. Nowadays, the range accuracy is guaranteed by offline routine quality control checks mainly performed with water phantoms, 2D detectors with PMMA wedges, or multi-layer ionization chambers. The latter feature low sensitivity, slow collection time, and response dependent on external parameters, which represent limiting factors for the quality controls of beams delivered with fast energy switching modalities, as foreseen in future treatments. In this context, a device based on solid-state detectors technology, able to perform a direct and absolute beam energy measurement, is proposed as a viable alternative for quality assurance measurements and beam commissioning, paving the way for online range monitoring and treatment verification. PURPOSE: This work follows the proof of concept of an energy monitoring system for clinical proton beams, based on Ultra Fast Silicon Detectors (featuring tenths of ps time resolution in 50 µm active thickness, and single particle detection capability) and time-of-flight techniques. An upgrade of such a system is presented here, together with the description of a dedicated self-calibration method, proving that this second prototype is able to assess the mean particles energy of a monoenergetic beam without any constraint on the beam temporal structure, neither any a priori knowledge of the beam energy for the calibration of the system. METHODS: A new detector geometry, consisting of sensors segmented in strips, has been designed and implemented in order to enhance the statistics of coincident protons, thus improving the accuracy of the measured time differences. The prototype was tested on the cyclotron proton beam of the Trento Protontherapy Center (TPC). In addition, a dedicated self-calibration method, exploiting the measurement of monoenergetic beams crossing the two telescope sensors for different flight distances, was introduced to remove the systematic uncertainties independently from any external reference. RESULTS: The novel calibration strategy was applied to the experimental data collected at TPC (Trento) and CNAO (Pavia). Deviations between measured and reference beam energies in the order of a few hundreds of keV with a maximum uncertainty of 0.5 MeV were found, in compliance with the clinically required water range accuracy of 1 mm. CONCLUSIONS: The presented version of the telescope system, minimally perturbative of the beam, relies on a few seconds of acquisition time to achieve the required clinical accuracy and therefore represents a feasible solution for beam commission, quality assurance checks, and online beam energy monitoring.