Proton FLASH Radiotherapy Ameliorates Radiation-induced Salivary Gland Dysfunction and Oral Mucositis and Increases Survival in a Mouse Model of Head and Neck Cancer.

Head and neck cancer radiotherapy often damages salivary glands and oral mucosa, severely negatively impacting patients' quality of life. The ability of FLASH proton radiotherapy (F-PRT) to decrease normal tissue toxicity while maintaining tumor control compared with standard proton radiotherapy (S-PRT) has been previously demonstrated for several tissues. However, its potential in ameliorating radiation-induced salivary gland dysfunction and oral mucositis and controlling orthotopic head and neck tumor growth has not been reported. The head and neck area of C57BL/6 mice was irradiated with a single dose of radiotherapy (ranging from 14-18 Gy) or a fractionated dose of 8 Gy × 3 of F-PRT (128 Gy/second) or S-PRT (0.95 Gy/second). Following irradiation, the mice were studied for radiation-induced xerostomia by measuring their salivary flow. Oral mucositis was analyzed by histopathologic examination. To determine the ability of F-PRT to control orthotopic head and neck tumors, tongue tumors were generated in the mice and then irradiated with either F-PRT or S-PRT. Mice treated with either a single dose or fractionated dose of F-PRT showed significantly improved survival than those irradiated with S-PRT. F-PRT-treated mice showed improvement in their salivary flow. S-PRT-irradiated mice demonstrated increased fibrosis in their tongue epithelium. F-PRT significantly increased the overall survival of the mice with orthotopic tumors compared with the S-PRT-treated mice. The demonstration that F-PRT decreases radiation-induced normal tissue toxicity without compromising tumor control, suggests that this modality could be useful for the clinical management of patients with head and neck cancer.

Reassessment of stopping power ratio uncertainties caused by mean excitation energies using a water-based formalism.

PURPOSE: In proton therapy planning, the accuracy of the Stopping Power Ratios (SPR) calculated in the stoichiometric CT calibration is affected by, among others, uncertainties on the mean excitation energies (I-values) of human tissues and water. Traditionally, the contribution of these uncertainties on the SPR has been conservatively estimated of the order of 1% or more for a reference tissue of known composition. This study provides a methodology that enables a finer estimation of this uncertainty, eventually showing that the traditional estimates of the uncertainty are too conservative. METHODS: Since human tissues contain water, a correlation exists between the I-values of tissues and water. As the SPR is the ratio of the tissue stopping power to that of water, this correlation decreases the uncertainty of the SPR. Our formalism considers this by expressing the I-value of the tissue as a function of the water weight fraction and the I-value of water, while applying Bragg's additivity rule only to the nonaqueous mixture of the tissue. For 22 reference tissue compositions, the SPR uncertainty was estimated by randomly sampling Gaussian distributions, based on ICRU data, for the I-values of water and the nonaqueous mixture, as well as for the water weight fraction. RESULTS: The relative standard deviation of the SPR, estimated at 150 MeV, is in the range of 0.1%-0.3% for soft tissues with an average water weight percentage of at least 60%. For tissues with a low water content (e.g., adipose and bones), this uncertainty is in the range of 0.5%-0.7%. CONCLUSION: Uncertainties on the I-values of human tissues and water appear to have a significantly lower impact on the SPR uncertainty than traditionally expected. In the future, this may provide a rationale for using smaller distal and proximal margins on the target volume, provided that all other range uncertainty components are correctly estimated too.

Registration of pencil beam proton radiography data with X-ray CT.

PURPOSE: Proton radiography seems to be a promising tool for assessing the quality of the stopping power computation in proton therapy. However, range error maps obtained on the basis of proton radiographs are very sensitive to small misalignment between the planning CT and the proton radiography acquisitions. In order to be able to mitigate misalignment in postprocessing, the authors implemented a fast method for registration between pencil proton radiography data obtained with a multilayer ionization chamber (MLIC) and an X-ray CT acquired on a head phantom. METHODS: The registration was performed by optimizing a cost function which performs a comparison between the acquired data and simulated integral depth-dose curves. Two methodologies were considered, one based on dual orthogonal projections and the other one on a single projection. For each methodology, the robustness of the registration algorithm with respect to three confounding factors (measurement noise, CT calibration errors, and spot spacing) was investigated by testing the accuracy of the method through simulations based on a CT scan of a head phantom. RESULTS: The present registration method showed robust convergence towards the optimal solution. For the level of measurement noise and the uncertainty in the stopping power computation expected in proton radiography using a MLIC, the accuracy appeared to be better than 0.3° for angles and 0.3 mm for translations by use of the appropriate cost function. The spot spacing analysis showed that a spacing larger than the 5 mm used by other authors for the investigation of a MLIC for proton radiography led to results with absolute accuracy better than 0.3° for angles and 1 mm for translations when orthogonal proton radiographs were fed into the algorithm. In the case of a single projection, 6 mm was the largest spot spacing presenting an acceptable registration accuracy. CONCLUSIONS: For registration of proton radiography data with X-ray CT, the use of a direct ray-tracing algorithm to compute sums of squared differences and corrections of range errors showed very good accuracy and robustness with respect to three confounding factors: measurement noise, calibration error, and spot spacing. It is therefore a suitable algorithm to use in the in vivo range verification framework, allowing to separate in postprocessing the proton range uncertainty due to setup errors from the other sources of uncertainty.

Prompt Gamma Imaging for In Vivo Range Verification of Pencil Beam Scanning Proton Therapy.

PURPOSE: To report the first clinical results and value assessment of prompt gamma imaging for in vivo proton range verification in pencil beam scanning mode. METHODS AND MATERIALS: A stand-alone, trolley-mounted, prototype prompt gamma camera utilizing a knife-edge slit collimator design was used to record the prompt gamma signal emitted along the proton tracks during delivery of proton therapy for a brain cancer patient. The recorded prompt gamma depth detection profiles of individual pencil beam spots were compared with the expected profiles simulated from the treatment plan. RESULTS: In 6 treatment fractions recorded over 3 weeks, the mean (± standard deviation) range shifts aggregated over all spots in 9 energy layers were -0.8 ± 1.3 mm for the lateral field, 1.7 ± 0.7 mm for the right-superior-oblique field, and -0.4 ± 0.9 mm for the vertex field. CONCLUSIONS: This study demonstrates the feasibility and illustrates the distinctive benefits of prompt gamma imaging in pencil beam scanning treatment mode. Accuracy in range verification was found in this first clinical case to be better than the range uncertainty margin applied in the treatment plan. These first results lay the foundation for additional work toward tighter integration of the system for in vivo proton range verification and quantification of range uncertainties.

Technical Note: A direct ray-tracing method to compute integral depth dose in pencil beam proton radiography with a multilayer ionization chamber.

PURPOSE: To introduce a fast ray-tracing algorithm in pencil proton radiography (PR) with a multilayer ionization chamber (MLIC) for in vivo range error mapping. METHODS: Pencil beam PR was obtained by delivering spots uniformly positioned in a square (45 × 45 mm2 field-of-view) of 9 × 9 spots capable of crossing the phantoms (210 MeV). The exit beam was collected by a MLIC to sample the integral depth dose (IDDMLIC). PRs of an electron-density and of a head phantom were acquired by moving the couch to obtain multiple 45 × 45 mm2 frames. To map the corresponding range errors, the two-dimensional set of IDDMLIC was compared with (i) the integral depth dose computed by the treatment planning system (TPS) by both analytic (IDDTPS) and Monte Carlo (IDDMC) algorithms in a volume of water simulating the MLIC at the CT, and (ii) the integral depth dose directly computed by a simple ray-tracing algorithm (IDDdirect) through the same CT data. The exact spatial position of the spot pattern was numerically adjusted testing different in-plane positions and selecting the one that minimized the range differences between IDDdirect and IDDMLIC. RESULTS: Range error mapping was feasible by both the TPS and the ray-tracing methods, but very sensitive to even small misalignments. In homogeneous regions, the range errors computed by the direct ray-tracing algorithm matched the results obtained by both the analytic and the Monte Carlo algorithms. In both phantoms, lateral heterogeneities were better modeled by the ray-tracing and the Monte Carlo algorithms than by the analytic TPS computation. Accordingly, when the pencil beam crossed lateral heterogeneities, the range errors mapped by the direct algorithm matched better the Monte Carlo maps than those obtained by the analytic algorithm. Finally, the simplicity of the ray-tracing algorithm allowed to implement a prototype procedure for automated spatial alignment. CONCLUSIONS: The ray-tracing algorithm can reliably replace the TPS method in MLIC PR for in vivo range verification and it can be a key component to develop software tools for spatial alignment and correction of CT calibration.

Acoustic time-of-flight for proton range verification in water.

PURPOSE: Measurement of the arrival times of thermoacoustic waves induced by pulsed proton dose depositions (protoacoustics) may provide a proton range verification method. The goal of this study is to characterize the required dose and protoacoustic proton range (distance) verification accuracy in a homogeneous water medium at a hospital-based clinical cyclotron. METHODS: Gaussian-like proton pulses with 17 µs widths and instantaneous currents of 480 nA (5.6 × 10(7) protons/pulse, 3.4 cGy/pulse at the Bragg peak) were generated by modulating the cyclotron proton source with a function generator. After energy degradation, the 190 MeV proton pulses irradiated a water phantom, and the generated protoacoustic emissions were measured by a hydrophone. The detector position and proton pulse characteristics were varied. The experimental results were compared to simulations. Different arrival time metrics derived from acoustic waveforms were compared, and the accuracy of protoacoustic time-of-flight distance calculations was assessed. RESULTS: A 27 mPa noise level was observed in the treatment room during irradiation. At 5 cm from the proton beam, an average maximum pressure of 5.2 mPa/1 × 10(7) protons (6.1 mGy at the Bragg peak) was measured after irradiation with a proton pulse with 10%-90% rise time of 11 µs. Simulation and experiment arrival times agreed well, and the observed 2.4 µs delay between simulation and experiment is attributed to the difference between the hydrophone's acoustic and geometric centers. Based on protoacoustic arrival times, the beam axis position was measured to within (x, y) = (-2.0, 0.5) ± 1 mm. After deconvolution of the exciting proton pulse, the protoacoustic compression peak provided the most consistent measure of the distance to the Bragg peak, with an error distribution with mean = - 4.5 mm and standard deviation = 2.0 mm. CONCLUSIONS: Based on water tank measurements at a clinical hospital-based cyclotron, protoacoustics is a potential method for measuring the beam's position (x and y within 2.0 mm) and Bragg peak range (2.0 mm standard deviation), although range verification will require simulation or experimental calibration to remove systematic error. Based on extrapolation, a protoacoustic arrival time reproducibility of 1.5 µs (2.2 mm) is achievable with 2 Gy of total deposited dose. Of the compared methods, deconvolution of the excitation proton pulse is the best technique for extracting protoacoustic arrival times, particularly if there is variation in the proton pulse shape.

Sensitivity study of prompt gamma imaging of scanned beam proton therapy in heterogeneous anatomies.

BACKGROUND AND PURPOSE: To investigate the use of a fast analytical prediction algorithm in the evaluation of the accuracy in Bragg peak position estimation using prompt gamma imaging in realistic anatomies. MATERIAL AND METHODS: Brain, nasal cavity and lung spot scanning treatments were planned on an anthropomorphic phantom. Plan delivery in a clinical proton therapy facility was monitored using a prompt gamma camera. A pencil-beam algorithm was developed to simulate prompt gamma acquisition. For each spot, the sensitivity to setup and CT conversion errors was evaluated based on error scenarios. RESULTS: Good agreement was found between simulations and measurements (average shift of 0.4mm on whole-layer profiles). The spots with greatest sensitivity to setup or CT conversion errors could be identified. The comparison between expected and estimated shifts showed that the errors in shift estimation due to heterogeneities were in average lower than 1mm in all cases except the lung. In the lung case, only 40% of the spots showed accuracy better than 2mm. CONCLUSIONS: The analytical prediction algorithm was successfully used to simulate prompt gamma acquisitions of scanned treatment plans. The accuracy in Bragg peak position estimation was generally sub-millimeter in heterogeneous anatomies, except in lung tissues.

Experimental observation of acoustic emissions generated by a pulsed proton beam from a hospital-based clinical cyclotron.

PURPOSE: To measure the acoustic signal generated by a pulsed proton spill from a hospital-based clinical cyclotron. METHODS: An electronic function generator modulated the IBA C230 isochronous cyclotron to create a pulsed proton beam. The acoustic emissions generated by the proton beam were measured in water using a hydrophone. The acoustic measurements were repeated with increasing proton current and increasing distance between detector and beam. RESULTS: The cyclotron generated proton spills with rise times of 18 µs and a maximum measured instantaneous proton current of 790 nA. Acoustic emissions generated by the proton energy deposition were measured to be on the order of mPa. The origin of the acoustic wave was identified as the proton beam based on the correlation between acoustic emission arrival time and distance between the hydrophone and proton beam. The acoustic frequency spectrum peaked at 10 kHz, and the acoustic pressure amplitude increased monotonically with increasing proton current. CONCLUSIONS: The authors report the first observation of acoustic emissions generated by a proton beam from a hospital-based clinical cyclotron. When modulated by an electronic function generator, the cyclotron is capable of creating proton spills with fast rise times (18 µs) and high instantaneous currents (790 nA). Measurements of the proton-generated acoustic emissions in a clinical setting may provide a method for in vivo proton range verification and patient monitoring.

First test of the prompt gamma ray timing method with heterogeneous targets at a clinical proton therapy facility.

Ion beam therapy promises enhanced tumour coverage compared to conventional radiotherapy, but particle range uncertainties significantly blunt the achievable precision. Experimental tools for range verification in real-time are not yet available in clinical routine. The prompt gamma ray timing method has been recently proposed as an alternative to collimated imaging systems. The detection times of prompt gamma rays encode essential information about the depth-dose profile thanks to the measurable transit time of ions through matter. In a collaboration between OncoRay, Helmholtz-Zentrum Dresden-Rossendorf and IBA, the first test at a clinical proton accelerator (Westdeutsches Protonentherapiezentrum Essen, Germany) with several detectors and phantoms is performed. The robustness of the method against background and stability of the beam bunch time profile is explored, and the bunch time spread is characterized for different proton energies. For a beam spot with a hundred million protons and a single detector, range differences of 5 mm in defined heterogeneous targets are identified by numerical comparison of the spectrum shape. For higher statistics, range shifts down to 2 mm are detectable. A proton bunch monitor, higher detector throughput and quantitative range retrieval are the upcoming steps towards a clinically applicable prototype. In conclusion, the experimental results highlight the prospects of this straightforward verification method at a clinical pencil beam and settle this novel approach as a promising alternative in the field of in vivo dosimetry.

Analytical computation of prompt gamma ray emission and detection for proton range verification.

A prompt gamma (PG) slit camera prototype recently demonstrated that Bragg Peak position in a clinical proton scanned beam could be measured with 1-2 mm accuracy by comparing an expected PG detection profile to a measured one. The computation of the expected PG detection profile in the context of a clinical framework is challenging but must be solved before clinical implementation. Obviously, Monte Carlo methods (MC) can simulate the expected PG profile but at prohibitively long calculation times. We implemented a much faster method that is based on analytical processing of precomputed MC data that would allow practical evaluation of this range monitoring approach in clinical conditions. Reference PG emission profiles were generated with MC simulations (PENH) in targets consisting of either (12)C, (14)N, (16)O, (31)P or (40)Ca, with 10% of (1)H. In a given geometry, the local PG emission can then be derived by adding the contribution of each element, according to the local energy of the proton obtained by continuous slowing down approximation and the local composition. The actual incident spot size is taken into account using an optical model fitted to measurements and by super sampling the spot with several rays (up to 113). PG transport in the patient/camera geometries and the detector response are modelled by convolving the PG production profile with a transfer function. The latter is interpolated from a database of transfer functions fitted to MC data (PENELOPE) generated for a photon source in a cylindrical phantom with various radiuses and a camera placed at various positions. As a benchmark, the analytical model was compared to MC and experiments in homogeneous and heterogeneous phantoms. Comparisons with MC were also performed in a thoracic CT. For all cases, the analytical model reproduced the prediction of the position of the Bragg peak computed with MC within 1 mm for the camera in nominal configuration. When compared to measurements, the shape of the profiles was well reproduced and agreement for the estimation of the position of the Bragg peak was within 2.7 mm on average (1.4 mm standard deviation). On a non-optimized MATLAB code, computation time with the analytical model is between 0.3 to 10 s depending on the number of rays simulated per spot. The analytical model can be further used to determine which spots are the best candidates to evaluate the range in clinical conditions and eventually correct for over- and under-shoots depending on the acquired PG profiles.