Range verification of a clinical proton beam in an abdominal phantom by co-registration of ionoacoustics and ultrasound.

Objective.The range uncertainty in proton radiotherapy is a limiting factor to achieve optimum dose conformity to the tumour volume. Ionoacoustics is a promising approach forin siturange verification, which would allow to reduce the size of the irradiated volume relative to the tumour volume. The energy deposition of a pulsed proton beam leads to an acoustic pressure wave (ionoacoustics), the detection of which allows conclusion about the distance between the Bragg peak and the acoustic detector. This information can be transferred into a co-registered ultrasound image, marking the Bragg peak position relative to the surrounding anatomy.Approach.A CIRS 3D abdominal phantom was irradiated with 126 MeV protons at a clinical proton therapy centre. Acoustic signals were recorded on the beam axis distal to the Bragg peak with a Cetacean C305X hydrophone. The ionoacoustic measurements were processed with a correlation filter using simulated filter templates. The hydrophone was rigidly attached to an ultrasound device (Interson GP-C01) recording ultrasound images of the irradiated region.Main results.The time of flight obtained from ionoacoustic measurements were transferred to an ultrasound image by means of an optoacoustic calibration measurement. The Bragg peak position was marked in the ultrasound image with a statistical uncertainty ofσ= 0.5 mm of 24 individual measurements depositing 1.2 Gy at the Bragg peak. The difference between the evaluated Bragg peak position and the one obtained from irradiation planning (1.0 mm) is smaller than the typical range uncertainty (≈4 mm) at the given penetration depth (10 cm).Significance.The measurements show that it is possible to determine the Bragg peak position of a clinical proton beam with submillimetre precision and transfer the information to an ultrasound image of the irradiated region. The dose required for this is smaller than that used for a typical irradiation fraction.

On the robustness of multilateration of ionoacoustic signals for localization of the Bragg peak at pre-clinical proton beam energies in water.

Objectives.The energy deposited in a medium by a pulsed proton beam results in the emission of thermoacoustic waves, also called ionoacoustics (IA). The proton beam stopping position (Bragg peak) can be retrieved from a time-of-flight analysis (ToF) of IA signals acquired at different sensor locations (multilateration). This work aimed to assess the robustness of multilateration methods in proton beams at pre-clinical energies for the development of a small animal irradiator.Approach.The accuracy of multilateration performed using different algorithms; namely, time of arrival and time difference of arrival, was investigatedin-silicofor ideal point sources in the presence of realistic uncertainties on the ToF estimation and ionoacoustic signals generated by a 20 MeV pulsed proton beam stopped in a homogeneous water phantom. The localisation accuracy was further investigated experimentally based on two different measurements with pulsed monoenergetic proton beams at energies of 20 and 22 MeV.Main results.It was found that the localisation accuracy mainly depends on the position of the acoustic detectors relative to the proton beam due to spatial variation of the error on the ToF estimation. By optimally positioning the sensors to reduce the ToF error, the Bragg peak could be locatedin-silicowith an accuracy better than 90µm (2% error). Localisation errors going up to 1 mm were observed experimentally due to inaccurate knowledge of the sensor positions and noisy ionoacoustic signals.Significance.This study gives a first overview of the implementation of different multilateration methods for ionoacoustics-based Bragg peak localisation in two- and three-dimensions at pre-clinical energies. Different sources of uncertainty were investigated, and their impact on the localisation accuracy was quantifiedin-silicoand experimentally.

Proton beam range verification by means of ionoacoustic measurements at clinically relevant doses using a correlation-based evaluation.

Purpose: The Bragg peak located at the end of the ion beam range is one of the main advantages of ion beam therapy compared to X-Ray radiotherapy. However, verifying the exact position of the Bragg peak within the patient online is a major challenge. The goal of this work was to achieve submillimeter proton beam range verification for pulsed proton beams of an energy of up to 220 MeV using ionoacoustics for a clinically relevant dose deposition of typically 2 Gy per fraction by i) using optimal proton beam characteristics for ionoacoustic signal generation and ii) improved signal detection by correlating the signal with simulated filter templates. Methods: A water tank was irradiated with a preclinical 20 MeV proton beam using different pulse durations ranging from 50 ns up to 1 µs in order to maximise the signal-to-noise ratio (SNR) of ionoacoustic signals. The ionoacoustic signals were measured using a piezo-electric ultrasound transducer in the MHz frequency range. The signals were filtered using a cross correlation-based signal processing algorithm utilizing simulated templates, which enhances the SNR of the recorded signals. The range of the protons is evaluated by extracting the time of flight (ToF) of the ionoacoustic signals and compared to simulations from a Monte Carlo dose engine (FLUKA). Results: Optimised SNR of 28.0 ± 10.6 is obtained at a beam current of 4.5 µA and a pulse duration of 130 ns at a total peak dose deposition of 0.5 Gy. Evaluated ranges coincide with Monte Carlo simulations better than 0.1 mm at an absolute range of 4.21 mm. Higher beam energies require longer proton pulse durations for optimised signal generation. Using the correlation-based post-processing filter a SNR of 17.8 ± 5.5 is obtained for 220 MeV protons at a total peak dose deposition of 1.3 Gy. For this clinically relevant dose deposition and proton beam energy, submillimeter range verification was achieved at an absolute range of 303 mm in water. Conclusion: Optimal proton pulse durations ensure an ideal trade-off between maximising the ionoacoustic amplitude and minimising dose deposition. In combination with a correlation-based post-processing evaluation algorithm, a reasonable SNR can be achieved at low dose levels putting clinical applications for online proton or ion beam range verification into reach.

Investigating the accuracy of co-registered ionoacoustic and ultrasound images in pulsed proton beams.

The sharp spatial and temporal dose gradients of pulsed ion beams result in an acoustic emission (ionoacoustics), which can be used to reconstruct the dose distribution from measurements at different positions. The accuracy of range verification from ionoacoustic images measured with an ultrasound linear array configuration is investigated both theoretically and experimentally for monoenergetic proton beams at energies relevant for pre-clinical studies (20 and 22 MeV). The influence of the linear sensor array arrangement (length up to 4 cm and number of elements from 5 to 200) and medium properties on the range estimation accuracy are assessed using time-reversal reconstruction. We show that for an ideal homogeneous case, the ionoacoustic images enable a range verification with a relative error lower than 0.1%, however, with limited lateral dose accuracy. Similar results were obtained experimentally by irradiating a water phantom and taking into account the spatial impulse response (geometry) of the acoustic detector during the reconstruction of pressures obtained by moving laterally a single-element transducer to mimic a linear array configuration. Finally, co-registered ionoacoustic and ultrasound images were investigated using silicone inserts immersed in the water phantom across the proton beam axis. By accounting for the sensor response and speed of sound variations (deduced from co-registration with ultrasound images) the accuracy is improved to a few tens of micrometers (relative error less than to 0.5%), confirming the promise of ongoing developments for ionoacoustic range verification in pre-clinical and clinical proton therapy applications.

Enhancement of the ionoacoustic effect through ultrasound and photoacoustic contrast agents.

The characteristic depth dose deposition of ion beams, with a maximum at the end of their range (Bragg peak) allows for local treatment delivery, resulting in better sparing of the adjacent healthy tissues compared to other forms of external beam radiotherapy treatments. However, the optimal clinical exploitation of the favorable ion beam ballistic is hampered by uncertainties in the in vivo Bragg peak position. Ionoacoustics is based on the detection of thermoacoustic pressure waves induced by a properly pulsed ion beam (e.g., produced by modern compact accelerators) to image the irradiated volume. Co-registration between ionoacoustics and ultrasound imaging offers a promising opportunity to monitor the ion beam and patient anatomy during the treatment. Nevertheless, the detection of the ionoacoustic waves is challenging due to very low pressure amplitudes and frequencies (mPa/kHz) observed in clinical applications. We investigate contrast agents to enhance the acoustic emission. Ultrasound microbubbles are used to increase the ionoacoustic frequency around the microbubble resonance frequency. Moreover, India ink is investigated as a possible mean to enhance the signal amplitude by taking advantage of additional optical photon absorption along the ion beam and subsequent photoacoustic effect. We report amplitude increase of up to 200% of the ionoacoustic signal emission in the MHz frequency range by combining microbubbles and India ink contrast agents.

Analytical probabilistic modeling of dose-volume histograms.

PURPOSE: Radiotherapy, especially with charged particles, is sensitive to executional and preparational uncertainties that propagate to uncertainty in dose and plan quality indicators, for example, dose-volume histograms (DVHs). Current approaches to quantify and mitigate such uncertainties rely on explicitly computed error scenarios and are thus subject to statistical uncertainty and limitations regarding the underlying uncertainty model. Here we present an alternative, analytical method to approximate moments, in particular expectation value and (co)variance, of the probability distribution of DVH-points, and evaluate its accuracy on patient data. METHODS: We use Analytical Probabilistic Modeling (APM) to derive moments of the probability distribution over individual DVH-points based on the probability distribution over dose. By using the computed moments to parameterize distinct probability distributions over DVH-points (here normal or beta distributions), not only the moments but also percentiles, that is, α - DVHs, are computed. The model is subsequently evaluated on three patient cases (intracranial, paraspinal, prostate) in 30- and single-fraction scenarios by assuming the dose to follow a multivariate normal distribution, whose moments are computed in closed-form with APM. The results are compared to a benchmark based on discrete random sampling. RESULTS: The evaluation of the new probabilistic model on the three patient cases against a sampling benchmark proves its correctness under perfect assumptions as well as good agreement in realistic conditions. More precisely, ca. 90% of all computed expected DVH-points and their standard deviations agree within 1% volume with their empirical counterpart from sampling computations, for both fractionated and single fraction treatments. When computing α - DVH, the assumption of a beta distribution achieved better agreement with empirical percentiles than the assumption of a normal distribution: While in both cases probabilities locally showed large deviations (up to ±0.2), the respective - DVHs for α={0.05,0.5,0.95} only showed small deviations in respective volume (up to ±5% volume for a normal distribution, and up to 2% for a beta distribution). A previously published model from literature, which was included for comparison, exhibited substantially larger deviations. CONCLUSIONS: With APM we could derive a mathematically exact description of moments of probability distributions over DVH-points given a probability distribution over dose. The model generalizes previous attempts and performs well for both choices of probability distributions, that is, normal or beta distributions, over DVH-points.

Towards a novel small animal proton irradiation platform: the SIRMIO project.

Background: Precision small animal radiotherapy research is a young emerging field aiming to provide new experimental insights into tumor and normal tissue models in different microenvironments, to unravel complex mechanisms of radiation damage in target and non-target tissues and assess efficacy of novel therapeutic strategies. For photon therapy, modern small animal radiotherapy research platforms have been developed over the last years and are meanwhile commercially available. Conversely, for proton therapy, which holds potential for an even superior outcome than photon therapy, no commercial system exists yet. Material and methods: The project SIRMIO (Small Animal Proton Irradiator for Research in Molecular Image-guided Radiation-Oncology) aims at realizing and demonstrating an innovative portable prototype system for precision image-guided small animal proton irradiation, suitable for installation at existing clinical treatment facilities. The proposed design combines precise dose application with in situ multi-modal anatomical image guidance and in vivo verification of the actual treatment delivery. Results and conclusions: This manuscript describes the status of the different components under development, featuring a dedicated beamline for degradation and focusing of clinical proton beams, along with novel detector systems for in situimaging and range verification. The foreseen workflow includes pre-treatment proton transmission imaging, complemented by ultrasonic tumor localization, for treatment planning and position verification, followed by image-guided delivery with on site range verification by means of ionoacoustics (for pulsed beams) and positron-emission-tomography (PET, for continuous beams). The proposed compact and cost-effective system promises to open a new era in small animal proton therapy research, contributing to the basic understanding of in vivo radiation action to identify areas of potential breakthroughs for future translation into innovative clinical strategies.

Analytical incorporation of fractionation effects in probabilistic treatment planning for intensity-modulated proton therapy.

PURPOSE: We show that it is possible to explicitly incorporate fractionation effects into closed-form probabilistic treatment plan analysis and optimization for intensity-modulated proton therapy with analytical probabilistic modeling (APM). We study the impact of different fractionation schemes on the dosimetric uncertainty induced by random and systematic sources of range and setup uncertainty for treatment plans that were optimized with and without consideration of the number of treatment fractions. METHODS: The APM framework is capable of handling arbitrarily correlated uncertainty models including systematic and random errors in the context of fractionation. On this basis, we construct an analytical dose variance computation pipeline that explicitly considers the number of treatment fractions for uncertainty quantitation and minimization during treatment planning. We evaluate the variance computation model in comparison to random sampling of 100 treatments for conventional and probabilistic treatment plans under different fractionation schemes (1, 5, 30 fractions) for an intracranial, a paraspinal and a prostate case. The impact of neglecting the fractionation scheme during treatment planning is investigated by applying treatment plans that were generated with probabilistic optimization for 1 fraction in a higher number of fractions and comparing them to the probabilistic plans optimized under explicit consideration of the number of fractions. RESULTS: APM enables the construction of an analytical variance computation model for dose uncertainty considering fractionation at negligible computational overhead. It is computationally feasible (a) to simultaneously perform a robustness analysis for all possible fraction numbers and (b) to perform a probabilistic treatment plan optimization for a specific fraction number. The incorporation of fractionation assumptions for robustness analysis exposes a dose to uncertainty trade-off, i.e., the dose in the organs at risk is increased for a reduced fraction number and/or for more robust treatment plans. By explicit consideration of fractionation effects during planning, we demonstrate that it is possible to exploit this trade-off during optimization. APM optimization considering the fraction number reduced the dose in organs at risk compared to conventional probabilistic optimization neglecting the fraction number. CONCLUSION: APM enables computationally efficient incorporation of fractionation effects in probabilistic uncertainty analysis and probabilistic treatment plan optimization. The consideration of the fractionation scheme in probabilistic treatment planning reveals the trade-off between number of fractions, nominal dose, and treatment plan robustness.

Impact of respiratory motion on variable relative biological effectiveness in 4D-dose distributions of proton therapy.

BACKGROUND: Organ motion during radiation therapy with scanned protons leads to deviations between the planned and the delivered physical dose. Using a constant relative biological effectiveness (RBE) of 1.1 linearly maps these deviations into RBE-weighted dose. However, a constant value cannot account for potential nonlinear variations in RBE suggested by variable RBE models. Here, we study the impact of motion on recalculations of RBE-weighted dose distributions using a phenomenological variable RBE model. MATERIAL AND METHODS: 4D-dose calculation including variable RBE was implemented in the open source treatment planning toolkit matRad. Four scenarios were compared for one field and two field proton treatments for a liver cancer patient assuming (α∕ß)x = 2 Gy and (α∕ß)x = 10 Gy: (A) the optimized static dose distribution with constant RBE, (B) a static recalculation with variable RBE, (C) a 4D-dose recalculation with constant RBE and (D) a 4D-dose recalculation with variable RBE. For (B) and (D), the variable RBE was calculated by the model proposed by McNamara. For (C), the physical dose was accumulated with direct dose mapping; for (D), dose-weighted radio-sensitivity parameters of the linear quadratic model were accumulated to model synergistic irradiation effects on RBE. RESULTS: Dose recalculation with variable RBE led to an elevated biological dose at the end of the proton field, while 4D-dose recalculation exhibited random deviations everywhere in the radiation field depending on the interplay of beam delivery and organ motion. For a single beam treatment assuming (α∕ß)x = 2 Gy, D95% was 1.98 Gy (RBE) (A), 2.15 Gy (RBE) (B), 1.81 Gy (RBE) (C) and 1.98 Gy (RBE) (D). The homogeneity index was 1.04 (A), 1.08 (B), 1.23 (C) and 1.25 (D). CONCLUSION: For the studied liver case, intrafractional motion did not reduce the modulation of the RBE-weighted dose postulated by variable RBE models for proton treatments.

Development of the open-source dose calculation and optimization toolkit matRad.

PURPOSE: We report on the development of the open-source cross-platform radiation treatment planning toolkit matRad and its comparison against validated treatment planning systems. The toolkit enables three-dimensional intensity-modulated radiation therapy treatment planning for photons, scanned protons and scanned carbon ions. METHODS: matRad is entirely written in Matlab and is freely available online. It re-implements well-established algorithms employing a modular and sequential software design to model the entire treatment planning workflow. It comprises core functionalities to import DICOM data, to calculate and optimize dose as well as a graphical user interface for visualization. matRad dose calculation algorithms (for carbon ions this also includes the computation of the relative biological effect) are compared against dose calculation results originating from clinically approved treatment planning systems. RESULTS: We observe three-dimensional γ-analysis pass rates ≥ 99.67% for all three radiation modalities utilizing a distance to agreement of 2 mm and a dose difference criterion of 2%. The computational efficiency of matRad is evaluated in a treatment planning study considering three different treatment scenarios for every radiation modality. For photons, we measure total run times of 145 s-1260 s for dose calculation and fluence optimization combined considering 4-72 beam orientations and 2608-13597 beamlets. For charged particles, we measure total run times of 63 s-993 s for dose calculation and fluence optimization combined considering 9963-45574 pencil beams. Using a CT and dose grid resolution of 0.3 cm3 requires a memory consumption of 1.59 GB-9.07 GB and 0.29 GB-17.94 GB for photons and charged particles, respectively. CONCLUSION: The dosimetric accuracy, computational performance and open-source character of matRad encourages a future application of matRad for both educational and research purposes.