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The present study verified and evaluated the dosimetric effects of protons scattered from a snout and an aperture in clinical practice, when a range compensator was included. The dose distribution calculated by a treatment planning system (TPS) was compared with the measured dose distribution and the dose distribution calculated by Monte Carlo simulation at several depths. The difference between the measured and calculated results was analyzed using Monte Carlo simulation with filtration of scattering in the snout and aperture. The dependence of the effects of scattered protons on snout size, beam range, and minimum thickness of the range compensator was also investigated using the Monte Carlo simulation. The simulated and measured results showed that the additional dose compared with the results calculated by the TPS at shallow depths was mainly due to protons scattered by the snout and aperture. This additional dose was filtered by the structure of the range compensator so that it was observed under the thin region of the range compensator. The maximum difference was measured at a depth of 16 mm (8.25%), with the difference decreasing with depth. Analysis of protons contributing to the additional dose showed that the contribution of protons scattered from the snout was greater than that of protons scattered from the aperture when a narrow snout was used. In the Monte Carlo simulation, this effect of scattered protons was reduced when wider snouts and longer‐range proton beams were used. This effect was also reduced when thicker range compensator bases were used, even with a narrow snout. This study verified the effect of scattered protons even when a range compensator was included and emphasized the importance of snout‐scattered protons when a narrow snout is used for small fields. It indicated that this additional dose can be reduced by wider snouts, longer range proton beams, and thicker range compensator bases. These results provide a better understanding of the additional dose from scattered protons in clinical practice.

International audience; An accurate knowledge of in vivo proton dose distribution is key to fully utilizing the potential advantages of proton therapy. Two representative indirect methods for in vivo range verification, namely, prompt gamma (PG) imaging and positron emission tomography (PET), are available. This study proposes a PG-PET system that combines the advantages of these two methods and presents detector geometry and background reduction techniques optimized for the PG-PET system. The characteristics of the secondary radiations emitted by a water phantom by interaction with a 150 MeV proton beam were analysed using Geant4.10.00, and the 2-D PG distributions were obtained and assessed for different detector geometries. In addition, the energy window (EW), depth-of-interaction (DOI), and time-of-flight (TOF) techniques are proposed as the background reduction techniques. To evaluate the performance of the PG-PET system, the 3-D dose distribution in the water phantom caused by two proton beams of energies 80 MeV and 100 MeV was verified using 16 optimal detectors. The thickness of the parallel-hole tungsten collimator of pitch 8 mm and width 7 mm was determined as 200 mm, and that of the GAGG scintillator was determined as 30 mm, by an optimization study. Further, 3–7 MeV and 2–7 MeV were obtained as the optimal EWs when the DOI and both the DOI and TOF techniques were applied for data processing, respectively; the detector performances were improved by about 38% and 167%, respectively, compared with that when applying only the 3–5 MeV EW. In this study, we confirmed that the PG distribution can be obtained by simply combining the 2-D parallel hole collimator and the PET detector module. In the future, we will develop an accurate 3-D dose evaluation technique using deep learning algorithms based on the image sets of dose, PG, and PET distributions for various proton energies.

For in-vivo range verification in proton therapy, attempts have been made to measure the spatial distribution of the prompt gammas generated by the proton-induced interactions and to determine the proton dose distribution. However, the high energies of prompt gammas and background gammas are still problematic in measuring the distribution. In this study, we suggested a new method for determining the in-vivo range by utilizing the time structure of the prompt gammas formed during the rotation of a range modulation wheel (RMW) in passive scattering proton therapy. To validate the Monte Carlo code simulating the proton beam nozzle, we compared the axial percent depth doses (PDDs) with the measured PDDs for varying beam range from 4.73 to 24.01 cm. Also, we assessed the relationship between the proton dose rate and the time structure of the prompt gammas in a water phantom. The results of the PDD showed agreement within relative errors of 1.1% in the distal range and 2.9% in the modulation width. The average dose difference in the modulation was assessed as less than 1.3% by comparison with the measurements. The time structure of prompt gammas was well-matched, within 0.39 ms, with the proton dose rate, and this enabled an accurate prediction of the in-vivo range.

International audience; For the independent validation of treatment plans, we developed a fully automated Monte Carlo (MC)-based patient dose calculation system with the tool for particle simulation (TOPAS) and proton therapy machine installed at the National Cancer Center in Korea to enable routine and automatic dose recalculation for each patient. The proton beam nozzle was modeled with TOPAS to simulate the therapeutic beam, and MC commissioning was performed by comparing percent depth dose with the measurement. The beam set-up based on the prescribed beam range and modulation width was automated by modifying the vendor-specific method. The CT phantom was modeled based on the DICOM CT files with TOPAS-built-in function, and an in-house-developed C++ code directly imports the CT files for positioning the CT phantom, RT-plan file for simulating the treatment plan, and RT-structure file for applying the Hounsfield unit (HU) assignment, respectively. The developed system was validated by comparing the dose distributions with those calculated by the treatment planning system (TPS) for a lung phantom and two patient cases of abdomen and internal mammary node. The results of the beam commissioning were in good agreement of up to 0.8 mm2 ${\rm g}^{-1}$ for B8 option in both of the beam range and the modulation width of the spread-out Bragg peaks. The beam set-up technique can predict the range and modulation width with an accuracy of 0.06% and 0.51%, respectively, with respect to the prescribed range and modulation in arbitrary points of B5 option (128.3, 132.0, and 141.2 mm2 ${\rm g}^{-1}$ of range). The dose distributions showed higher than 99% passing rate for the 3D gamma index (3 mm distance to agreement and 3% dose difference) between the MC simulations and the clinical TPS in the target volume. However, in the normal tissues, less favorable agreements were obtained for the radiation treatment planning with the lung phantom and internal mammary node cases. The discrepancies might come from the limitations of the clinical TPS, which is the inaccurate dose calculation algorithm for the scattering effect, in the range compensator and inhomogeneous material. Moreover, the steep slope of the compensator, conversion of the HU values to the human phantom, and the dose calculation algorithm for the HU assignment also could be reasons of the discrepancies. The current study could be used for the independent dose validation of treatment plans including high inhomogeneities, the steep compensator, and riskiness such as lung, head & neck cases. According to the treatment policy, the dose discrepancies predicted with MC could be used for the acceptance decision of the original treatment plan.

We introduce the automation of the range difference calculation deduced from particle-irradiation induced β(+)-activity distributions with the so-called most-likely-shift approach, and evaluate its reliability via the monitoring of algorithm- and patient-specific uncertainty factors. The calculation of the range deviation is based on the minimization of the absolute profile differences in the distal part of two activity depth profiles shifted against each other. Depending on the workflow of PET (positron emission tomography)-based range verification, the two profiles under evaluation can correspond to measured and simulated distributions, or only measured data from different treatment sessions. In comparison to previous work, the proposed approach includes an automated identification of the distal region of interest for each pair of PET depth profiles and under consideration of the planned dose distribution, resulting in the optimal shift distance. Moreover, it introduces an estimate of uncertainty associated to the identified shift, which is then used as weighting factor to “red flag” problematic large range differences. Furthermore, additional patient-specific uncertainty factors are calculated using available CT (computed tomography) data to support the range analysis. The performance of the new method for in-vivo treatment verification in the clinical routine is investigated with in-room PET images for proton therapy as well as with offline PET images for proton and carbon ion therapy. The comparison between measured PET activity distributions and predictions obtained by Monte Carlo simulations or measurements from previous treatment fractions is performed. For this purpose, a total of 15 patient datasets were analyzed, which were acquired at Massachusetts General Hospital and Heidelberg Ion-Beam Therapy Center with in-room PET and offline PET/CT scanners, respectively. Calculated range differences between the compared activity distributions are reported in a two-dimensional map in beam-eye-view. In comparison to previously proposed approaches, the new most-likely-shift method shows more robust results for assessing in-vivo the range from strongly varying PET distributions caused by differing patient geometry, ion beam species, beam delivery techniques, PET imaging concepts and counting statistics. The additional visualization of the uncertainties and the dedicated weighting strategy contribute to the understanding of the reliability of observed range differences and the complexity in the prediction of activity distributions. The proposed method promises to offer a feasible technique for clinical routine of PET-based range verification.

We present a proof of principle study of proton radiography and proton computed tomography (pCT) based on time-resolved dose measurements. We used a prototype, two-dimensional, diode-array detector capable of fast dose rate measurements, to acquire proton radiographic images expressed directly in water equivalent path length (WEPL). The technique is based on the time dependence of the dose distribution delivered by a proton beam traversing a range modulator wheel in passive scattering proton therapy systems. The dose rate produced in the medium by such a system is periodic and has a unique pattern in time at each point along the beam path and thus encodes the WEPL. By measuring the time dose pattern at the point of interest, the WEPL to this point can be decoded. If one measures the time–dose patterns at points on a plane behind the patient for a beam with sufficient energy to penetrate the patient, the obtained 2D distribution of the WEPL forms an image. The technique requires only a 2D dosimeter array and it uses only the clinical beam for a fraction of second with negligible dose to patient. We first evaluated the accuracy of the technique in determining the WEPL for static phantoms aiming at beam range verification of the brain fields of medulloblastoma patients. Accurate beam ranges for these fields can significantly reduce the dose to the cranial skin of the patient and thus the risk of permanent alopecia. Second, we investigated the potential features of the technique for real-time imaging of a moving phantom. Real-time tumor tracking by proton radiography could provide more accurate validations of tumor motion models due to the more sensitive dependence of proton beam on tissue density compared to x-rays. Our radiographic technique is rapid (∼100 ms) and simultaneous over the whole field, it can image mobile tumors without the problem of interplay effect inherently challenging for methods based on pencil beams. Third, we present the reconstructed pCT images of a cylindrical phantom containing inserts of different materials. As for all conventional pCT systems, the method illustrated in this work produces tomographic images that are potentially more accurate than x-ray CT in providing maps of proton relative stopping power (RSP) in the patient without the need for converting x-ray Hounsfield units to proton RSP. All phantom tests produced reasonable results, given the currently limited spatial and time resolution of the prototype detector. The dose required to produce one radiographic image, with the current settings, is ∼0.7 cGy. Finally, we discuss a series of techniques to improve the resolution and accuracy of radiographic and tomographic images for the future development of a full-scale detector.

Positron emission tomography (PET) has been suggested as an imaging technique for in vivo proton dose and range verification after proton induced-tissue activation. During proton treatment, irradiated tissue is activated and decays while emitting positrons. In this paper, we assessed the feasibility of using PET imaging after proton treatment to determine tissue elemental composition by evaluating the resultant composite decay curve of activated tissue. A phantom consisting of sections composed of different combinations of (1)H, (12)C, (14)N, and (16)O was irradiated using a pristine Bragg peak and a 6 cm spread-out Bragg-peak (SOBP) proton beam. The beam ranges defined at 90% distal dose were 10 cm; the delivered dose was 1.6 Gy for the near monoenergetic beam and 2 Gy for the SOBP beam. After irradiation, activated phantom decay was measured using an in-room PET scanner for 30 min in list mode. Decay curves from the activated (12)C and (16)O sections were first decomposed into multiple simple exponential decay curves, each curve corresponding to a constituent radioisotope, using a least-squares method. The relative radioisotope fractions from each section were determined. These fractions were used to guide the decay curve decomposition from the section consisting mainly of (12)C + (16)O and calculate the relative elemental composition of (12)C and (16)O. A Monte Carlo simulation was also used to determine the elemental composition of the (12)C + (16)O section. The calculated compositions of the (12)C + (16)O section using both approaches (PET and Monte Carlo) were compared with the true known phantom composition. Finally, two patients were imaged using an in-room PET scanner after proton therapy of the head. Their PET data and the technique described above were used to construct elemental composition ((12)C and (16)O) maps that corresponded to the proton-activated regions. We compared the (12)C and (16)O compositions of seven ROIs that corresponded to the vitreous humor, adipose/face mask, adipose tissue, and brain tissue with ICRU 46 elemental composition data. The (12)C and (16)O compositions of the (12)C + (16)O phantom section were estimated to within a maximum difference of 3.6% for the near monoenergetic and SOBP beams over an 8 cm depth range. On the other hand, the Monte Carlo simulation estimated the corresponding (12)C and (16)O compositions in the (12)C + (16)O section to within a maximum difference of 3.4%. For the patients, the (12)C and (16)O compositions in the seven ROIs agreed with the ICRU elemental composition data, with a mean (maximum) difference of 9.4% (15.2%). The (12)C and (16)O compositions of the phantom and patients were estimated with relatively small differences. PET imaging may be useful for determining the tissue elemental composition and thereby improving proton treatment planning and verification.

Purpose The purpose of this study is to evaluate the potential of using in-room positron emission tomography (PET) for treatment verification in proton therapy and for deriving suitable PET scan times. Methods and Materials Nine patients undergoing passive scattering proton therapy underwent scanning immediately after treatment with an in-room PET scanner. The scanner was positioned next to the treatment head after treatment. The Monte Carlo (MC) method was used to reproduce PET activities for each patient. To assess the proton beam range uncertainty, we designed a novel concept in which the measured PET activity surface distal to the target at the end of range was compared with MC predictions. The repositioning of patients for the PET scan took, on average, approximately 2 minutes. The PET images were reconstructed considering varying scan times to test the scan time dependency of the method. Results The measured PET images show overall good spatial correlations with MC predictions. Some discrepancies could be attributed to uncertainties in the local elemental composition and biological washout. For 8 patients treated with a single field, the average range differences between PET measurements and computed tomography (CT) image-based MC results were Conclusions Our first clinical trials in 9 patients using an in-room PET system demonstrated its potential for in vivo treatment monitoring in proton therapy. For a quantitative range prediction with arbitrary shape of target volume, we suggest using the distal PET activity surface.

Purpose While positron emission tomography (PET) allows for the imaging of tissues activated by proton beams in terms of monitoring the therapy administered, most endogenous tissue elements are activated by relatively high-energy protons. Therefore, a relatively large distance off-set exists between the dose fall-off and activity fall-off. However, 16O(p,2p,2n)13N has a relatively low energy threshold which peaks around 12 MeV and also a residual proton range that is approximately 1 to 2 mm. In this phantom study, we tested the feasibility of utilizing the 13N production peak as well as the differences in activity fall-off between early and late PET scans for proton range verification. One of the main purposes for this research was developing a proton range verification methodology that would not require Monte Carlo simulations. Methods and materials Both monoenergetic and spread-out Bragg peak beams were delivered to two phantoms — a water-like gel and a tissue-like gel where the proton ranges came to be approximately 9.9 and 9.1 cm, respectively. After 1 min of postirradiation delay, the phantoms were scanned for a period of 30 min using an in-room PET. Two separate (Early and Late) PET images were reconstructed using two different postirradiation delays and acquisition times; Early PET: 1 min delay and 3 min acquisition, Late PET: 21 min delay and 10 min acquisition. The depth gradients of the PET signals were then normalized and plotted as functions of depth. The normalized gradient of the early PET images was subtracted from that of the late PET images, to observe the 13N activity distribution in relation to depth. Monte Carlo simulations were also conducted with the same set-up as the measurements stated previously. Results The subtracted gradients show peaks at 9.4 and 8.6 cm in water-gel and tissue-gel respectively for both pristine and SOBP beams. These peaks are created in connection with the sudden change of 13N signals with depth and consistently occur 2 mm upstream to where 13N signals were most abundantly created (9.6 and 8.8 cm in water-gel and tissue-gel, respectively). Monte Carlo simulations provided similar results as the measurements. Conclusions The subtracted PET signal gradient peaks and the proton ranges for water-gel and tissue-gel show distance off-sets of 4 to 5 mm. This off-set may potentially be used for proton range verification using only the PET measured data without Monte Carlo simulations. More studies are necessary to overcome various limitations, such as perfusion-driven washout, for the feasibility of this technique in living patients.

To verify in-vivo proton dose distribution, a 2-dimensional (2D) prompt-gamma measurement system, comprised of a multi-hole collimation system, a 2D array of CsI(Tl) scintillators, and a position-sensitive photomultiplier tube (PS-PMT), is under development. In the present study, to determine the optimal dimension of the measurement system, we employed a series of Monte Carlo simulations with the MCNPX code. To effectively measure the high-energy prompt gammas while minimizing background gammas, we determined the collimator hole size, collimator thickness, and scintillator length to be 0.4 × 0.4 cm2, 15 cm, and 5 cm, respectively. Thereafter, the performance of the optimized measurement system was estimated for monoenergetic proton pencil beams. The peak locations of the prompt-gamma distributions for 80- and 150-MeV proton beams were clearly distinguished, and the correlation between the beam range and the peak location was confirmed by using the measurement system. For a 200-MeV proton beam, however, the peak location could not be determined due to the dominance of background gammas and the lateral dispersion of the proton beam at the end of the beam range. Based on these simulation results, a prototype 2D prompt-gamma measurement system currently is under construction and, upon completion, will be tested with therapeutic proton beams.

Purpose: In vivo range verification is one of the most important parts of proton therapy to fully utilize its benefits delivering high radiationdose to tumor, while sparing the normal tissue with the so-called Bragg peak. Currently, however, range verification method is not used in clinics. The purpose of the present study is to optimize and evaluate the configuration of an array-type prompt gamma measurement system on determining distal dose edge for in vivo range verification of proton therapy. Methods: To effectively measure the prompt gammas against the background gammas, the Monte Carlo simulations with the MCNPX code were employed in optimizing the configuration of the measurement system, and the Monte Carlo method was also used to understand the effect of the background gammas, mainly neutron capture gammas, in the measured gamma distribution. To reduce the effect of the background gammas, the optimized energy window of 4–10 MeV in measuring the prompt gammas was employed. A parameterized source was used to maximize computation speed in the optimization study. A simplified test measurement system, using only one detector moving from one measurement location to the next, was constructed and applied to therapeuticproton beams of 80–220 MeV. For accurate determination of the distal dose edge, the sigmoidal curve-fitting method was applied to the measured distributions of the prompt gammas, and then, the location of the half-value between the maximum and minimum value in the curve-fitting was determined as the distal dose edge and compared with the beam range assessed by the protondose distribution. Results: The parameterized source term employed in optimization process improved the calculation speed by up to ∼300 times. The optimization study indicates that an array-type measurement system with 3, 2, 2, and 150 mm for scintillator thickness, slit width, septal thickness, and slit length, respectively, can effectively measure the prompt gamma distributions minimizing the contribution of background gammas. The present results show that a few hundred counts of prompt gammas can be easily obtained by measuring 10 s at each measurement location for proton beams of ∼4 nA. The distal dose edges determined by the prompt gamma distribution are 5.45, 14.73, and 27.74 cm for proton beams of 5.17 (80 MeV), 14.99 (150 MeV), and 27.38 (220 MeV) cm, respectively. Conclusions: The results show that the array-type measurement system can measure prompt gamma distributions from a therapeuticproton beam within a short measurement time, and that the distal dose edge can be determined within a few millimeters of error without using any sophisticated analysis.

In proton therapy, accurate verification of in vivo dose distribution is necessary to ensure not only the safety of the patient but also the success of the treatment itself. It has been shown, both...

The close relationship between the proton dose distribution and the distribution of prompt gammas generated by proton-induced nuclear interactions along the path of protons in a water phantom was demonstrated by means of both Monte Carlo simulations and limited experiments. In order to test the clinical applicability of the method for determining the distal dose edge in a human body, a human voxel model, constructed based on a body-composition-approximated physical phantom, was used, after which the MCNPX code was used to analyze the energy spectra and the prompt gamma yields from the major elements composing the human voxel model; finally, the prompt gamma distribution, generated from the voxel model and measured by using an array-type prompt gamma detection system, was calculated and compared with the proton dose distribution. According to the results, eective prompt gammas were produced mainly by oxygen, and the specific energy of the prompt gammas, allowing for selective measurement, was found to be 4.44 MeV. The results also show that the distal dose edge in the human phantom, despite the heterogeneous composition and the complicated shape, can be determined by measuring the prompt gamma distribution with an array-type detection system.

A scanning-type prompt gamma measurement system, called prompt gamma scanner (PGS), was constructed and used to determine the relationship between the proton dose distribution and the longitudinal profile of the prompt gammas generated by the nuclear interaction from the proton beam passage in a medium. However, the PGS system entails insuperable difficulties when used in clinical proton therapy owing to its scanning process. In order to measure the prompt gamma distribution without the scanning process, it was proposed to develop an array-type prompt gamma measurement system that can measure the prompt gammas with a linear array of radiation detectors through multiple collimation slits. Prior to constructing afull-scale measurement system with many detectors and multiple data acquisition channels, a simplified prototype measurement system, using only one detector moving from one measurement location to the next, was constructed in the present study and applied to a 39-MeV proton beam. The results are very encouraging, as the prototype measurement system predicted the distal dose edge very accurately within a few millimeters of error despite the fact that the level of background gammas increased as a result of reduced collimator shielding.

The range of a proton beam in a patient can be determined by scanning the distribution of the prompt gammas emitted from the beam passage. However, this method suffers from a high level of background gammas, especially in the case of high energy proton beams. The present study determined the optimal energy window for selective measurement of the prompt gammas, effectively discriminating background gammas, for a prompt gamma scanning system. To that end, the energy spectra of the prompt and background gammas were calculated by transporting the protons and other secondary particles with MCNPX. A detailed analysis of these spectra revealed that the optimal energy window is 4–10 MeV. The application of the energy window to simulated and measured data confirmed that the range of a proton beam in a patient can be determined much more accurately by employing the optimal energy window.

Recently a prototype prompt gamma scanner system, named the PGS (prompt gamma scanner), was constructed and used to demonstrate that there is a clear correlation between prompt gamma distribution and the range of the proton beam in a patient. However, the PGS system requires a scanning process to obtain the prompt gamma distribution; consequently, it cannot be used in \spot scanning", in which the proton beam is continuously moving during treatment. The present Monte Carlo study explored the feasibility of a new detection system that does not require a scanning process, that is, that uses a linear array of scintillation detectors and photodiodes for online measurement of the proton beam range. The simulation results are very encouraging, showing that an array-type prompt gamma detection system can measure the proton beam range despite the fact that, with this system, the level of background gammas somewhat increases as a result of reduced collimator shielding. This paper discusses those simulation results, as well as some important design considerations based on them.

Purpose To assess the impact of approximations in current analytical dose calculation methods (ADCs) on tumor control probability (TCP) in proton therapy. Methods Dose distributions planned with ADC were compared with delivered dose distributions as determined by Monte Carlo simulations. A total of 50 patients were investigated in this analysis with 10 patients per site for 5 treatment sites (head and neck, lung, breast, prostate, liver). Differences were evaluated using dosimetric indices based on a dose-volume histogram analysis, a γ-index analysis, and estimations of TCP. Results We found that ADC overestimated the target doses on average by 1% to 2% for all patients considered. The mean dose, D95, D50, and D02 (the dose value covering 95%, 50% and 2% of the target volume, respectively) were predicted within 5% of the delivered dose. The γ-index passing rate for target volumes was above 96% for a 3%/3 mm criterion. Differences in TCP were up to 2%, 2.5%, 6%, 6.5%, and 11% for liver and breast, prostate, head and neck, and lung patients, respectively. Differences in normal tissue complication probabilities for bladder and anterior rectum of prostate patients were less than 3%. Conclusion Our results indicate that current dose calculation algorithms lead to underdosage of the target by as much as 5%, resulting in differences in TCP of up to 11%. To ensure full target coverage, advanced dose calculation methods like Monte Carlo simulations may be necessary in proton therapy. Monte Carlo simulations may also be required to avoid biases resulting from systematic discrepancies in calculated dose distributions for clinical trials comparing proton therapy with conventional radiation therapy.

Purpose This work was a proof-of-principle study for the evaluation of oxygen-15 ( 15 O) production as an imaging target through the use of positron emission tomography (PET), to improve verification of proton treatment plans and to study the effects of perfusion. Methods and Materials Dynamic PET measurements of irradiation-produced isotopes were made for a phantom and rabbit thigh muscles. The rabbit muscle was irradiated and imaged under both live and dead conditions. A differential equation was fitted to phantom and in vivo data, yielding estimates of 15 O production and clearance rates, which were compared to live versus dead rates for the rabbit and to Monte Carlo predictions. Results PET clearance rates agreed with decay constants of the dominant radionuclide species in 3 different phantom materials. In 2 oxygen-rich materials, the ratio of 15 O production rates agreed with the expected ratio. In the dead rabbit thighs, the dynamic PET concentration histories were accurately described using 15 O decay constant, whereas the live thigh activity decayed faster. Most importantly, the 15 O production rates agreed within 2% ( P >.5) between conditions. Conclusions We developed a new method for quantitative measurement of 15 O production and clearance rates in the period immediately following proton therapy. Measurements in the phantom and rabbits were well described in terms of 15 O production and clearance rates, plus a correction for other isotopes. These proof-of-principle results support the feasibility of detailed verification of proton therapy treatment delivery. In addition, 15 O clearance rates may be useful in monitoring permeability changes due to therapy.

We propose a proton range verification technique for passive scattering proton therapy systems where spread out Bragg peak (SOBP) fields are produced with rotating range modulator wheels. The technique is based on the correlation of time patterns of the prompt gamma ray emission with the range of protons delivering the SOBP. The main feature of the technique is the ability to verify the proton range with a single point of measurement and a simple detector configuration. We performed four-dimensional (time-dependent) Monte Carlo simulations using TOPAS to show the validity and accuracy of the technique. First, we validated the hadronic models used in TOPAS by comparing simulations and prompt gamma spectrometry measurements published in the literature. Second, prompt gamma simulations for proton range verification were performed for the case of a water phantom and a prostate cancer patient. In the water phantom, the proton range was determined with 2 mm accuracy with a full ring detector configuration for a dose of ~2.5 cGy. For the prostate cancer patient, 4 mm accuracy on range determination was achieved for a dose of ~15 cGy. The results presented in this paper are encouraging in view of a potential clinical application of the technique.

The purpose of this study was to assess the possibility of introducing site-specific range margins to replace current generic margins in proton therapy. Further, the goal was to study the potential of reducing margins with current analytical dose calculations methods. For this purpose we investigate the impact of complex patient geometries on the capability of analytical dose calculation algorithms to accurately predict the range of proton fields. Dose distributions predicted by an analytical pencil-beam algorithm were compared with those obtained using Monte Carlo (MC) simulations (TOPAS). A total of 508 passively scattered treatment fields were analyzed for seven disease sites (liver, prostate, breast, medulloblastoma?spine, medulloblastoma?whole brain, lung and head and neck). Voxel-by-voxel comparisons were performed on two-dimensional distal dose surfaces calculated by pencil-beam and MC algorithms to obtain the average range differences and root mean square deviation for each field for the?distal position of the 90% dose level (R90) and the 50% dose level (R50). The average dose degradation of the distal falloff region, defined as the distance between the distal position of the 80% and 20% dose levels (R80?R20), was also analyzed. All ranges were calculated in water-equivalent distances. Considering total range uncertainties and uncertainties from dose calculation alone, we were able to deduce site-specific estimations. For liver, prostate and whole brain fields our results demonstrate that a reduction of currently used uncertainty margins is feasible even without introducing MC dose calculations. We recommend range margins of 2.8%?+?1.2?mm for liver and prostate treatments and 3.1%?+?1.2?mm for whole brain treatments, respectively. On the other hand, current margins seem to be insufficient for some breast, lung and head and neck patients, at least if used generically. If no case specific adjustments are applied, a generic margin of 6.3%?+?1.2?mm would be needed for breast, lung and head and neck treatments. We conclude that the currently used generic range uncertainty margins in proton therapy should be redefined site specific and that complex geometries may require a field specific adjustment. Routine verifications of treatment plans using MC simulations are recommended for patients with heterogeneous geometries.

We describe the rationale and implementation of a method for analyzing in-room positron emission tomography (PET) data to verify the proton beam range. The method is based on analyzing distal PET surfaces after passive scattering proton beam delivery. Typically in vivo range verification is done by comparing measured and predicted PET distribution for a single activity level at a selected activity line along the beam passage. In the method presented here, we suggest using a middle point method based on dual PET activity levels to minimize the uncertainty due to local variations in the PET activity. Furthermore, we introduce 2-dimensional (2D) PET activity level surfaces based on 3-dimensional maps of the PET activities along the beam passage. This allows determining not only average range differences but also range difference distributions as well as root mean square deviations (RMSDs) for a more comprehensive range analysis. The method is demonstrated using data from 8 patients who were scanned with an in-room PET scanner. For each of the 8 patients, the average range difference was less than 5 mm and the RMSD was 4 to 11 mm between the measured and simulated PET activity level surfaces for single-field treatments. An ongoing protocol at our institution allows the use of a single field for patients being imaged for the PET range verification study at 1 fraction during their treatment course. Visualizing the range difference distributions using the PET surfaces offers a convenient visual verification of range uncertainties in 2D. Using the distal activity level surfaces of simulated and measured PET distributions at the middle of 25% and 50% activity level is a robust method for in vivo range verification.

In an effort to verify the dose delivery in proton therapy, Positron Emission Tomography (PET) scans have been employed to measure the distribution of β+ radioactivity produced from nuclear reactions of the protons with native nuclei. Because the dose and PET distributions are difficult to compare directly, the range verification is currently carried out by comparing measured and Monte Carlo (MC) simulation predicted PET distributions. In order to reduce the reliance on MC, simulated PET (simPET) and dose distal endpoints were compared to explore the feasibility of using distal endpoints for in-room PET range verification. MC simulations were generated for six head and neck patients with corrections for radiological decay, biological washout, and PET resolution. One-dimensional profiles of the dose and simPET were examined along the direction of the beam and covering the cross section of the beam. The chosen endpoints of the simPET (x-intercept of the linear fit to the distal falloff) and planned dose (20–50% of maximum dose) correspond to where most of the protons are below the threshold energy for the nuclear reactions. The difference in endpoint range between the distal surfaces of the dose and MC-PET were compared and the spread of range differences were assessed. Among the six patients, the mean difference between MC-PET and dose depth was found to be −1.6 mm to +0.5 mm between patients, with a standard deviation of 1.1 to 4.0 mm across the individual beams. In clinical practice, regions with deviations beyond the safety margin need to be examined more closely and can potentially lead to adjustments to the treatment plan.

Purpose: To assess the clinical impact of Monte Carlo (MC) dose calculations in proton therapy by analyzing uncertainties of analytical algorithms when predicting dose to target and critical structures and beam ranges in patient geometries. Methods: We used TOPAS to simulate double scattering proton treatments, which were compared to analytical treatment planning dose calculations (TPC). We investigated: 1)beam ranges, dose distributions, does‐rate profiles and output factors using various dedicated experiments.range differences caused by the patient heterogeneity considering 48 fields and 4 treatment sites. We calculated distal 2)dose surfaces composed of beam ranges and assessed average range difference (dR) and root‐mean‐square deviation (RMSD).3)dose delivery accuracy using a DVH based analysis considering patient treatment plans from 3 sites. 4)the accuracy of dose delivery for small fields (diameter below 7cm) based on patient heterogeneity for 38 head fields. We assess differences in D50. Results: 1)MC and measurements agree within statistical uncertainties.2)For 3 of 4 patient sites the RMSD between TPC and TOPAS was

Purpose: We propose a novel technique for in‐vivo and real‐time range verification based on the unique temporal dependence of prompt‐gamma produced by passively modulated proton beams Methods: For passively modulated proton beams, the dose delivered to a medium is periodic with the period of the Range Modulator Wheel (RMW) rotation. It has been confirmed experimentally that such periodic dose‐rate functions, measured inside a medium, have a unique correlation with their point of measurement along a Spread‐Out Bragg Peak (SOBP). Therefore, also the time‐structure of prompt‐gammas, generated by proton induced nuclear interactions in the target and detected outside the medium, is expected to be periodic and correlated with their source‐location along the SOBP. To verify such correlation, we employed the Monte Carlo method using TOol for PArticle Simulation (TOPAS). The simulated detection system is constituted by a single‐slit collimated detector placed at 90° from the beam direction. Discrimination of prompt‐γ from background radiation is done trough energy and time‐of‐flight (TOF) selectionResults: We verified that the time‐pattern of prompt‐gamma rate functions (i.e. gamma‐counts vs. RMW rotation‐time) is periodic and correlated with the detection depth along the SOBP. Utilizing this feature it is feasible to predict the range of a SOBP within few millimeters with a single point of prompt‐gamma measurement. The influence of the prescribed dose and collimation setup over the detection statistics is discussed in order to assess the potential clinical application of the technique. TOF selection and background subtraction can significantly increase the signal to noise ratio Conclusion: Our results show that the range of a SOBP can be determined, with a single point of measurement, by analyzing the time‐pattern of prompt‐gamma detected with a single‐slit detection system. This novel technique potentially represents a powerful tool for real‐time range verification for passively modulated proton therapy systems

Purpose: The objective of this study is to evaluate the feasibility of proton beam treatment verification using in‐room PET. As of February 2012, four patients have been studied in a clinical trial. In addition, we suggest a new method comparing the distal surface of the measured and simulated PET activities to verify the location of the distal dose surface.Methods: Patients were scanned for 20 minutes with an in‐room PET positioned next to the proton treatment head in a gantry room for beam delivery using passive scattering. The time between end of treatment and the start of the scan was within about 2 minutes. The predicted distribution of the PET activities and the proton dose distributions in the patients were also calculated using Monte Carlo (MC). Along the beam direction, the 50% fall‐off positions of the maximum PET activity at each line profile were compared with the MC simulated and the measuredPETimages, and then the differences were assessed with root‐mean‐square deviation (RMSD) and mapped in the beam's eye view. Results: The measuredPETimages showed a good spatial correlation with the simulated PETimages and the proton dose distributions even though the treated volumes and locations varied between patients. The RMSD values, representing the surface differences between the measured and simulated PET, were assessed to be 4.3–5.1 mm for four patients. Some region including the penumbra showed larger differences but was excluded. Conclusions: We have explored the potential of the in‐room PET for proton therapy monitoring through a clinical trial. The PETimage analysis method based on MC simulations showed that the distal dose surface could be determined within a few millimeters but not within the aimed accuracy of 2–3 mm. Improvements in PET‐CT image registration and biological washout modeling will most likely increase the accuracy further. NIH/NCI P01 CA021239

While a proton beam has an advantage over conventional electron and photon radiation therapy by sparing healthy tissues and organs surrounding the tumor volume, it is important to know the proton dose distribution, especially the location of distal dose falloff, to ensure the patient’s safety and the effectiveness of the treatments. This study is aimed at developing a prompt gamma scanning system by using a Monte Carlo technique for a 70-MeV proton beam, which is a usual low-energy bound of the therapy beam and at designing a system as compact as possible for actual construction. The system is set to measure the distribution of prompt gammas emitted at 90 ± 1◦ relative to the incident proton beam. The simulation showed that the distal falloff position of the proton beam could be determined from the prompt gamma distribution to an accuracy of 1 – 2 mm.

The location of the distal falloff in the proton therapy is an important but often uncertain parameter as different tissue elements are traversed by the beam. A multilayered collimator system has been constructed as a practical means to locate the dose ends by measuring prompt gammas. The collimator is designed to moderate and capture fast neutrons and to prevent unwanted gammas from reaching the scintillation detector. The system has been studied using Monte Carlo technique and has been tested in the beam energy range of 100–200MeV. Measurements clearly indicated correlations between the gamma distributions and the distal falloff regions.

Background: To precisely calculate skin dose and thus to evaluate the relationship between the skin dose and permanent alopecia for pediatric medulloblastoma patients treated with proton beams. Methods: The dosimetry and alopecia outcomes of 12 children with medulloblastoma (ages 4-15 years) comprise the study cohort. Permanent alopecia was assessed and graded after completion of the entire therapy. Skin threshold doses of permanent alopecia were calculated based on the skin dose from the craniospinal irradiation (CSI) plan using the concept of generalized equivalent uniform dose (gEUD) and accounting for chemotherapy intensity. Monte Carlo simulations were employed to accurately assess uncertainties due to beam range prediction and secondary particles. Results: Increasing the dose of the CSI field or the dose given by the boost field to the posterior fossa increased total skin dose delivered in that region. It was found that permanent alopecia could be correlated with CSI dose with a threshold of about 21 Gy (relative biological effectiveness, RBE) with high dose chemotherapy and 30 Gy (RBE) with conventional chemotherapy. Conclusions: Our results based on 12 patients provide a relationship between the skin dose and permanent alopecia for pediatric medulloblastoma patients treated with protons. The alopecia risk as assessed with gEUD could be predicted based on the treatment plan information.