Relative Stopping Power Research Articles

Dual-energy CT based mass density and relative stopping power estimation for proton therapy using physics-informed deep learning

Proton therapy requires accurate dose calculation for treatment planning to ensure the conformal doses are precisely delivered to the targets. The conversion of CT numbers to material properties is a significant source of uncertainty for dose calculation. The aim of this study is to develop a physics-informed deep learning (PIDL) framework to derive accurate mass density and relative stopping power maps from dual-energy computed tomography (DECT) images. The PIDL framework allows deep learning (DL) models to be trained with a physics loss function, which includes a physics model to constrain DL models. Five DL models were implemented including a fully connected neural network (FCNN), dual-FCNN (DFCNN), and three variants of residual networks (ResNet): ResNet-v1 (RN-v1), ResNet-v2 (RN-v2), and dual-ResNet-v2 (DRN-v2). An artificial neural network (ANN) and the five DL models trained with and without physics loss were explored to evaluate the PIDL framework. Two empirical DECT models were implemented to compare with the PIDL method. DL training data were from CIRS electron density phantom 062M (Computerized Imaging Reference Systems, Inc., Norfolk, VA). The performance of DL models was tested by CIRS adult male, adult female, and 5-year-old child anthropomorphic phantoms. For density map inference, the physics-informed RN-v2 was 3.3%, 2.9% and 1.9% more accurate than ANN for the adult male, adult female, and child phantoms. The physics-informed DRN-v2 was 0.7%, 0.6%, and 0.8% more accurate than DRN-v2 without physics training for the three phantoms, respectfully. The results indicated that physics-informed training could reduce uncertainty when ANN/DL models without physics training were insufficient to capture data structures or derived significant errors. DL models could also achieve better image noise control compared to the empirical DECT parametric mapping methods. The proposed PIDL framework can potentially improve proton range uncertainty by offering accurate material properties conversion from DECT.

Comparative accuracy and resolution assessment of two prototype proton computed tomography scanners.

Improving the accuracy of relative stopping power (RSP) in proton therapy may allow reducing range margins. Proton computed tomography (pCT) has been shown to provide state-of-the-art RSP accuracy estimation, and various scanner prototypes have recently been built. The different approaches used in scanner design are expected to impact spatial resolution and RSPaccuracy. The goal of this study was to perform the first direct comparison, in terms of spatial resolution and RSP accuracy, of two pCT prototype scanners installed at the same facility and by using the same image reconstructionalgorithm. A phantom containing cylindrical inserts of known RSP was scanned at the phase-II pCT prototype of the U.S. pCT collaboration and at the commercially oriented ProtonVDA scanner. Following distance-driven binning filtered backprojection reconstruction, the radial edge spread function of high-density inserts was used to estimate the spatial resolution. RSP accuracy was evaluated by the mean absolute percent error (MAPE) over the inserts. No direct imaging dose estimation was possible, which prevented a comparison of the two scanners in terms of RSPnoise. In terms of RSP accuracy, both scanners achieved the same MAPE of 0.72% when excluding the porous sinus insert from the evaluation. The ProtonVDA scanner reached a better overall MAPE when all inserts and the body of the phantom were accounted for (0.81%), compared to the phase-II scanner (1.14%). The spatial resolution with the phase-II scanner was found to be 0.61lp/mm, while for the ProtonVDA scanner somewhat lower at 0.46lp/mm. The comparison between two prototype pCT scanners operated in the same clinical facility showed that they both fulfill the requirement of an RSP accuracy of about 1%. Their spatial resolution performance reflects the different design choices of either a scanner with full tracking capabilities (phase-II) or of a more compact tracker system, which only provides the positions of protons but not their directions (ProtonVDA).

Improved accuracy of relative electron density and proton stopping power ratio through CycleGAN machine learning

Objective. Kilovoltage computed tomography (kVCT) is the cornerstone of radiotherapy treatment planning for delineating tissues and towards dose calculation. For the former, kVCT provides excellent contrast and signal-to-noise ratio. For the latter, kVCT may have greater uncertainty in determining relative electron density () and proton stopping power ratio (SPR). Conversely, megavoltage CT (MVCT) may result in superior dose calculation accuracy. The purpose of this work was to convert kVCT HU to MVCT HU using deep learning to obtain higher accuracy and SPR. Approach. Tissue-mimicking phantoms were created to compare kVCT- and MVCT-determined and SPR to physical measurements. Using 100 head-and-neck datasets, an unpaired deep learning model was trained to learn the relationship between kVCTs and MVCTs, creating synthetic MVCTs (sMVCTs). Similarity metrics were calculated between kVCTs, sMVCTs, and MVCTs in 20 test datasets. An anthropomorphic head phantom containing bone-mimicking material with known composition was scanned to provide an independent determination of and SPR accuracy by sMVCT. Main results. In tissue-mimicking bone, errors were 2.20% versus 0.19% and SPR errors were 4.38% versus 0.22%, for kVCT versus MVCT, respectively. Compared to MVCT, in vivo mean difference (MD) values were 11 and 327 HU for kVCT and 2 and 3 HU for sMVCT in soft tissue and bone, respectively. MD decreased from 1.3% to 0.35% in soft tissue and 2.9% to 0.13% in bone, for kVCT and sMVCT, respectively. SPR MD decreased from 1.8% to 0.24% in soft tissue and 6.8% to 0.16% in bone, for kVCT and sMVCT, respectively. Relative to physical measurements, and SPR error in anthropomorphic bone decreased from 7.50% and 7.48% for kVCT to <1% for both MVCT and sMVCT. Significance. Deep learning can be used to map kVCT to sMVCT, suggesting higher accuracy and SPR is achievable with sMVCT versus kVCT.

Feasibility study of a proton CT system based on 4D-tracking and residual energy determination via time-of-flight

Objective. For dose calculations in ion beam therapy, it is vital to accurately determine the relative stopping power (RSP) distribution within the treatment volume. A suitable imaging modality to achieve the required RSP accuracy is proton computed tomography (pCT), which usually uses a tracking system and a separate residual energy (or range) detector to directly measure the RSP distribution. This work investigates the potential of a novel pCT system based on a single detector technology, namely low gain avalanche detectors (LGADs). LGADs are fast 4D-tracking detectors, which can be used to simultaneously measure the particle position and time with precise timing and spatial resolution. In contrast to standard pCT systems, the residual energy is determined via a time-of-flight (TOF) measurement between different 4D-tracking stations. Approach. To show the potential of using 4D-tracking for proton imaging, we studied and optimized the design parameters for a realistic TOF-pCT system using Monte Carlo simulations. We calculated the RSP accuracy and RSP resolution inside the inserts of the CTP404 phantom and compared the results to a simulation of an ideal pCT system. Main results. After introducing a dedicated calibration procedure for the TOF calorimeter, RSP accuracies less than 0.6% could be achieved. We also identified the design parameters with the strongest impact on the RSP resolution and proposed a strategy to further improve the image quality. Significance. This comprehensive study of the most important design aspects for a novel TOF-pCT system could help guide future hardware developments and, once implemented, improve the quality of treatment planning in ion beam therapy.

Dosimetric considerations for moldable silicone composites used in radiotherapy applications.

Due to their many favorable characteristics, moldable silicone (MS) composites have gained popularity in medicine and recently, in radiotherapy applications. We investigate the dosimetric properties of silicones in radiotherapy beams and determine their suitability as water substitutes for constructing boluses and phantoms. Two types of silicones were assessed (ρ= 1.04 g/cm3 and ρ= 1.07 g/cm3). Various dosimetric properties were characterized, including the relative electron density, the relative mean mass energy‐absorption coefficient, and the relative mean mass restricted stopping power. Silicone slabs with thickness of 1.5 cm and 5.0 cm were molded to mimic a bolus setup and a phantom setup, respectively. Measurements were conducted for Co‐60 and 6 MV photon beams, and 6 MeV electron beams. The doses at 1.5 cm and 5.0 cm depths in MS were measured with solid water (SW) backscatter material (D MS–SW), and with a full MS setup (D MS–MS), then compared with doses at the same depths in a full SW setup (D SW–SW). Relative doses were reported as D MS–SW/D MS–SW and D MS–MS/D SW–SW. Experimental results were verified using Monaco treatment planning system dose calculations and Monte Carlo EGSnrc simulations. Film measurements showed varying dose ratios according to MS and beam types. For photon beams, the bolus setup D MS–SW/D SW–SW exhibited a 5% relative dose reduction. The dose for 6 MV beams was reduced by nearly 2% in a full MS setup. Up to 2% dose increase in both scenarios was observed for electron beams. Compared with dose in SW, an interface of MS–SW can cause relatively high differences. We conclude that it is important to characterize a particular silicone's properties in a given beam quality prior to clinical use. Because silicone compositions vary between manufacturers and differ from water/SW, accurate dosimetry using these materials requires consideration of the reported differences.

Physical characterization of therapeutic proton delivery through common dental materials.

Dental fixtures are commonplace in an aging, radiation treatment population. The current, local standard of practice in particle therapy is to employ treatment geometries to avoid delivery through implanted dental fixtures. The present study aims to observe the physical effect of delivering therapeutic proton beams through common dental fixture materials as prelude to an eventual goal of assessing the feasibility of using treatment geometries not specified for avoidance of oral implants. A sampling of common dental materials was selected based on prosthodontic consult and was evaluated in terms of relative stopping power and three-dimensional (3D) dose perturbation. Amalgams, porcelain-fused-to-metal (PFM) crowns consisting of zirconia and non-noble base metals, and lithium disilicate implants were chosen for analysis. Theoretical stopping power (S) and mass stopping power (S/ρ) were calculated using the Stopping and Range of Ions in Matter (SRIM) application, basing stoichiometric compositions of each fixture on published materials data. S and S/ρ were calculated for a range of historically available compositions of amalgams from 1900 until the current era. The perturbance of S and S/ρ as a function of clinically relevant ranges of amalgam compositions for the modern era was analyzed. Water equivalent thickness (WET) and relative stopping power (Srel ) of each material was measured for a clinical spot-scanning proton beam with monoenergies of 159.9 and 228.8MeV with a multi-layer ionization chamber (MLIC). Subsequently, 3D dose perturbation was assessed by delivering proton beams through a custom phantom designed to simulate both en-face and on-edge treatment geometries through the selected materials. A treatment plan mimicking the experimental delivery was constructed in the institutional treatment planning system and calculated using TOPAS-based Monte Carlo simulation (MCS). Experimental results were used to validate the MCS. Finally, treatment planning system (TPS) outputs were compared to MCS to determine the accuracy of the dose calculation model. Historical compositions of amalgams ranged in S from 44.8 to 42.9MeV/cm, with the greatest deviation being observed for the 1900-1959 era. Deviation as a function of amalgam composition from the modern era was most sensitive to proportion of Hg, accounting for deviations up to -4.2% at the greatest clinically relevant concentration. S/ρ was not found to vary greatly between each porcelain and metal alloy material for PFM type crowns. Relative stopping powers ranged between 1.3 and 5.4 for all studied materials, suggesting substantial changes in proton range with respect to water. Film measurements of pristine spots confirm dose perturbance and shortening of proton range, with an upstream shift of each Bragg peak being observed directly behind the installed fixture. At high energies, cold spots were found in all cases directly behind each material feature with a medial fill-in of dose occurring distally. Qualitative agreement of spot perturbance was confirmed between film measurements and MCS. Finally, when comparing integrated depth doses (IDD) by summing over all axial directions, good agreement is observed between TPS and MCS. All dental materials studied substantially perturbed the dosimetry of pristine proton spots both in terms of WET/Srel as well as the spatial distribution of dose. Proton range was quantifiably shortened, and each dental material affected a cold spot directly behind the object with medial dose back-filling was observed distally. MCS and Eclipse dose calculations exhibited good agreement with measurements, suggesting that treatment planning without employing avoidance strategies may be possible with further investigation.

Developments in Mathematical Algorithms and Computational Tools for Proton CT and Particle Therapy Treatment Planning

We summarize recent results and ongoing activities in mathematical algorithms and computer science methods related to proton computed tomography (pCT) and intensity-modulated particle therapy (IMPT) treatment planning. Proton therapy necessitates a high level of delivery accuracy to exploit the selective targeting imparted by the Bragg peak. For this purpose, pCT utilizes the proton beam itself to create images. The technique works by sending a low-intensity beam of protons through the patient and measuring the position, direction, and energy loss of each exiting proton. The pCT technique allows reconstruction of the volumetric distribution of the relative stopping power (RSP) of the patient tissues for use in treatment planning and pretreatment range verification. We have investigated new ways to make the reconstruction both efficient and accurate. Better accuracy of RSP also enables more robust inverse approaches to IMPT. For IMPT, we developed a framework for performing intensity modulation of the proton pencil beams. We expect that these developments will lead to additional project work in the years to come, which requires a regular exchange between experts in the fields of mathematics, computer science, and medical physics. We have initiated such an exchange by organizing annual workshops on the pCT and IMPT algorithm and technology developments. This report is, admittedly, tilted toward our interdisciplinary work and methods. We offer a comprehensive overview of results, problems, and challenges in pCT and IMPT with the aim of making other scientists wanting to tackle such issues and to strengthen their interdisciplinary collaboration by bringing together cutting-edge know-how from medicine, computer science, physics, and mathematics to bear on medical physics problems at hand.

Evaluation of the impact of a scanner prototype on proton CT and helium CT image quality and dose efficiency with Monte Carlo simulation

Objective. The use of ion computed tomography (CT) promises to yield improved relative stopping power (RSP) estimation as input to particle therapy treatment planning. Recently, proton CT (pCT) has been shown to yield RSP accuracy on par with state-of-the-art x-ray dual energy CT. There are however concerns that the lower spatial resolution of pCT compared to x-ray CT may limit its potential, which has spurred interest in the use of helium ion CT (HeCT). The goal of this study was to investigate image quality of pCT and HeCT in terms of noise, spatial resolution, RSP accuracy and imaging dose using a detailed Monte Carlo (MC) model of an existing ion CT prototype. Approach. Three phantoms were used in simulated pCT and HeCT scans allowing estimation of noise, spatial resolution and the scoring of dose. An additional phantom was used to evaluate RSP accuracy. The imaging dose required to achieve the same image noise in a water and a head phantom was estimated at both native spatial resolution, and in a scenario where the HeCT spatial resolution was reduced and matched to that of pCT using Hann windowing of the reconstruction filter. A variance reconstruction formalism was adapted to account for Hann windowing. Main results. We confirmed that the scanner prototype would produce higher spatial resolution for HeCT than pCT by a factor 1.8 (0.86 lp mm−1 versus 0.48 lp mm−1 at the center of a 20 cm water phantom). At native resolution, HeCT required a factor 2.9 more dose than pCT to achieve the same noise, while at matched resolution, HeCT required only 38% of the pCT dose. Finally, RSP mean absolute percent error (MAPE) was found to be 0.59% for pCT and 0.67% for HeCT. Significance. This work compared the imaging performance of pCT and HeCT when using an existing scanner prototype, with the spatial resolution advantage of HeCT coming at the cost of increased dose. When matching spatial resolution via Hann windowing, HeCT had a substantial dose advantage. Both modalities provided state-of-the-art RSP MAPE. HeCT might therefore help reduce the dose exposure of patients with comparable image noise to pCT, enhanced spatial resolution and acceptable RSP accuracy at the same time.

Toward MR-only proton therapy planning for pediatric brain tumors: Synthesis of relative proton stopping power images with multiple sequence MRI and development of an online quality assurance tool.

To generate synthetic relative proton stopping power (sRPSP) images from magnetic resonance imaging (MRI) sequence(s) and develop an online quality assurance (QA) tool for sRPSP to facilitate safe integration of magnetic resonance (MR)-only proton planning into clinical practice. Planning computed tomography (CT) and MR images of 195 pediatric brain tumor patients were utilized (training: 150, testing: 45). Seventeen consistent-cycle generative adversarial network (ccGAN) models were trained separately using paired CT-converted RPSP and MRI datasets to transform a subject's MRI into sRPSP. T1-weighted (T1W), T2-weighted (T2W), and FLAIR MRI were permutated to form 17 combinations, with or without preprocessing, for determining the optimal training sequence(s). For evaluation, sRPSP images were converted to synthetic CT (sCT) and compared to the real CT in terms of mean absolute error (MAE) in Hounsfield units (HU). For QA, sCT was deformed and compared to a reference template built from training dataset to produce a flag map, highlighting pixels that deviate by >100HU and fall outside the mean±standard deviation reference intensity. The gamma intensity analysis (10%/3mm) of the deformed sCT against the QA template on the intensity difference was investigated as a surrogate of sCT accuracy. The sRPSP images generated from a single T1W or T2W sequence outperformed that generated from multi-MRI sequences in terms of MAE (all p<0.05). Preprocessing with N4 bias and histogram matching reduced MAE of T2W MRI-based sCT (54±21HU vs. 42±13HU, p=0.002). The gamma intensity analysis of sCT against the QA template was highly correlated with the MAE of sCT against the real CT in the testing cohort (r=-0.89 for T1W sCT; r=-0.93 for T2W sCT). Accurate sRPSP images can be generated from T1W/T2W MRI for proton planning. A QA tool highlights regions of inaccuracy, flagging problematic cases unsuitable for clinical use.

A novel range telescope concept for proton CT

Proton beam therapy can potentially offer improved treatment for cancers of the head and neck and in paediatric patients. There has been a sharp uptake of proton beam therapy in recent years as improved delivery techniques and patient benefits are observed. However, treatments are currently planned using conventional x-ray CT images due to the absence of devices able to perform high quality proton computed tomography (pCT) under realistic clinical conditions. A new plastic-scintillator-based range telescope concept, named ASTRA, is proposed here to measure the proton’s energy loss in a pCT system. Simulations conducted using GEANT4 yield an expected energy resolution of 0.7%. If calorimetric information is used the energy resolution could be further improved to about 0.5%. In addition, the ability of ASTRA to track multiple protons simultaneously is presented. Due to its fast components, ASTRA is expected to reach unprecedented data collection rates, similar to 108 protons/s. The performance of ASTRA has also been tested by simulating the imaging of phantoms. The results show excellent image contrast and relative stopping power reconstruction.

Stopping power measurement for proton therapy by combining proton radiography and X-ray CT

Exact information on the relative stopping power (RSP) of the high-energy proton in the human body is necessary to precisely control radiation dose and position in proton beam therapy. RSP has been estimated by converting the X-ray computed tomography (CT) information. However, it causes up to 5% uncertainty in the RSP measurements because of the fundamental difference between the X-ray and proton interaction. Therefore, this study investigates a scheme of the RSP distribution measurement in the human body with a combination of X-ray CT and proton radiography with beam injection to a single direction. We studied the accuracy of the RSP measurement using GEANT4 simulation with silicon trackers, crystal calorimeter, and proton beam. The RSP accuracy has been generally measured below 1% from the reference values for simple objects with multi cylindrical shapes. The simulation results present the requirements of a proton tracking system on the spatial resolution and the acquisition rate. We developed a tracking detector prototype consisting of double-sided silicon strip detectors and amplifier–shaper–discriminator LSI chips. We evaluated the performance with an 80 MeV proton beam in Cyclotron and Radioisotope Center, Tohoku University. It succeeded in reconstructing a proton trajectory with 160 kHz and fulfilled the requirements to realize the proposed scheme. Furthermore, this study describes the detailed study of the scheme of the RSP measurement and the beam test of the tracking system prototype.

Empirical method for modeling the percent depth dose curves of electron beam in radiation therapy

Abstract Introduction: This study presents an empirical method to model the electron beam percent depth dose curve (PDD) using the primary and tail functions in radiation therapy. The modeling parameters N and n can be used to derive the depth relative stopping power of the electron energy in radiation therapy. Methods and Materials: The electrons PDD curves were modeled with the primary-tail function in this study. The primary function included exponential function and main parameters of N, µ while the tail function was composed by a sigmoid function with the main parameter of n. The PDD for five electron energies were modeled by the primary and tail function by adjusting the parameters of N, µ and n. The R50 and Rp can be derived from the modeled straight line of 80% to 20% region of PDD. The same electron energy with different cone sizes was also modeled with the primary-tail function. The stopping power for different electron energies at different depths can also be derived from the parameters of N, µ and n. Percent ionization depth curve can then be derived from the percent depth dose by dividing its depth relevant stopping power for comparing with the original water phantom measurement. Results: The main parameters N, n increase, but µ decreases in primary-tail function when electron energy increased. The relationship of parameters n, N and LN(-µ) with electron energy are n = 31.667 E0 - 88, N = 0.9975 E0 - 2.8535, LN(-µ) = -0.1355 E0 - 6.0986, respectively. Stopping power of different electron energy can be derived from n and N with the equation: stopping power = (−0.042 ln N E 0 + 1.072)e(−n−E0·5·10−5+0.0381·d), where d is the depth in water. Percent depth dose was derived from the percent reading curve by multiplying the stopping power relevant to the depth in water at certain electron energy. Conclusion: The PDD of electrons at different energies and field sizes can be modeled with an empirical model to deal with the stopping power calculation. The primary-tail equation provides a uncomplicated solution than a pencil beam or other numerical algorism for investigators to research the behavior of electron beam in radiation therapy.

A comparison of proton stopping power measured with proton CT and x-ray CT in fresh postmortem porcine structures.

Currently, calculations of proton range in proton therapy patients are based on a conversion of CT Hounsfield units of patient tissues into proton relative stopping power. Uncertainties in this conversion necessitate larger proximal and distal planned target volume margins. Proton CT can potentially reduce these uncertainties by directly measuring proton stopping power. We aim to demonstrate proton CT imaging with complex porcine samples, to analyze in detail three-dimensional regions of interest, and to compare proton stopping powers directly measured by proton CT to those determined from x-ray CT scans. We have used a prototype proton imaging system with single proton tracking to acquire proton radiography and proton CT images of a sample of porcine pectoral girdle and ribs, and a pig's head. We also acquired close in time x-ray CT scans of the same samples and compared proton stopping power measurements from the two modalities. In the case of the pig's head, we obtained x-ray CT scans from two different scanners and compared results from high-dose and low-dose settings. Comparing our reconstructed proton CT images with images derived from x-ray CT scans, we find agreement within 1% to 2% for soft tissues and discrepancies of up to 6% for compact bone. We also observed large discrepancies, up to 40%, for cavitated regions with mixed content of air, soft tissue, and bone, such as sinus cavities or tympanic bullae. Our images and findings from a clinically realistic proton CT scanner demonstrate the potential for proton CT to be used for low-dose treatment planning with reduced margins.

Experimental comparison of photon versus particle computed tomography to predict tissue relative stopping powers.

Measurements comparing relative stopping power (RSP) accuracy of state-of-the-art systems representing single-energy and dual-energy computed tomography (SECT/DECT) with proton CT (pCT) and helium CT (HeCT) in biological tissuesamples. We used 16 porcine and bovine samples of various tissue types and water, covering an RSP range from 0.90 0.06 to 1.78 0.05. Samples were packed and sealed into 3D-printed cylinders ( cm, cm) and inserted into an in-house designed cylindrical polymethyl methacrylate (PMMA) phantom ( cm, cm). We scanned the phantom in a commercial SECT and DECT (120kV; 100 and 140kV/Sn (tin-filtered)); and acquired pCT and HeCT ( MeV/u, 2 steps, (p)/ (He) particles/projection) with a particle imaging prototype. RSP maps were calculated from SECT/DECT using stoichiometric methods and from pCT/HeCT using the DROP-TVS algorithm. We estimated the average RSP of each tissue per modality in cylindrical volumes of interest and compared it to ground truth RSP taken from peak-detectionmeasurements. Throughout all samples, we observe the following root-mean-squared RSP prediction errors combined uncertainty from reference measurement and imaging: SECT 3.10 2.88%, DECT 0.75 2.80%, pCT 1.19 2.81%, and HeCT 0.78 2.81%. The largest mean errors combined uncertainty per modality are SECT 8.22 2.79% in cortical bone, DECT 1.74 2.00% in back fat, pCT 1.80 4.27% in bone marrow, and HeCT 1.37 4.25% in bone marrow. Ring artifacts were observed in both pCT and HeCT reconstructions, imposing a systematic shift to predicted RSPs. Comparing state-of-the-art SECT/DECT technology and a pCT/HeCT prototype, DECT provided the most accurate RSP prediction, closely followed by particle imaging. The novel modalities pCT and HeCT have the potential to further improve on RSP accuracies with work focusing on the origin and correction of ring artifacts. Future work will study accuracy of proton treatment plans using RSP maps from investigated imagingmodalities.

The Value of On-Site Proton Audits

This study aimed to highlight the value and key findings of on-site proton audits. The authors performed 38 on-site measurement-based peer reviews of proton centers participating in National Cancer Institute-funded clinical trials. The reviews covered beam calibration, lateral and depth measurements, mechanical checks, treatment planning and clinical practice, and quality assurance (QA) practices. Program deficiencies were noted, and recommendations were made about ways institutions could improve their practices. Institutions received an average of 3 (range, 1-8) recommendations for practice improvements. The number of deficiencies did not decrease over time, highlighting the continued need for this type of peer review. The most common deficiencies were for Task Group-recommended QA compliance (97% of centers), computed tomography number (CTN) to relative linear stopping power conversion (59%), and QA procedures (53%). In addition, 32% of institutions assessed failed at least 1 lateral beam profile measurement (<90% of pixels passing 3% [global]/3 mm; 10% threshold), despite passing internal QA measurements. These failures occurred for several different plan configurations (large, small, shallow, and deep targets) and at different depths in the beam path (proximal to target, central, and distal). CTN to relative linear stopping power conversion curves showed deviations at low, mid, and high CTNs and highlighted areas of inconsistency between proton centers, with many centers falling outside of 2 sigma of the mean curve of their peers. All deficiencies from the peer review were discussed with the institutions, and many implemented dosimetric treatment planning and practice changes to improve the accuracy of their system and consistency with other institutions. This peer review program has been integral in confirming and promoting consistency and best practice across proton centers for clinical trials, minimizing deviations for outcomes data.

Application of Silicone-Filled Vaginal Spacers for Pediatric Proton Therapy

Tissue spacers, including vaginal wall spacers, are used in a number of cancer diagnoses including soft tissue sarcomas, prostate cancer, cervical and uterine cancers. In proton therapy, the benefit of tissue spacers can be even greater as the device can serve as a beam stopper where protons reach their end of range in the material of the spacer instead of adjacent tissues.Commercially available hollow vaginal spacers which come in sizes ranging from 1.46 cm to 3.65 cm in diameter were filled with air-free silicone in a custom-made vacuum chamber. Two adolescent patients with pelvic soft tissue sarcomas receiving proton therapy were CT-simulated with and without a vaginal spacer. The relative stopping power of silicone was measured in a water tank to estimate the water equivalent thickness from 1.56 cm to 3.91 cm used in the treatment planning system for dosimetric comparisons. The dosimetric advantages of the silicone-filled vaginal spacer were investigated in three different dosimetric scenarios: (1) no vaginal spacer, (2) hollow vaginal spacer, (3) silicone-filled vaginal spacer in terms of plan quality and sparing of contralateral vaginal wall during primary and boost phases for two patients.While the target coverages remained comparable for the phase I (CTV, Rx = 36 Gy) and the phase II (GTV, Rx = 59.4 Gy), the dose distributions of ipsilateral and contralateral vaginal walls varied across these scenarios. After the phase II, the dosimetric sparing of contralateral vaginal wall was chiefly achieved in the patient A as the mean dose was 8.4 Gy with the silicone-filled spacer, and 17.1 Gy with hollow spacer, and 30.8 Gy with no spacer. However, due to the size and location of the tumor relative to the vagina, the sparing of contralateral vaginal was not observed in the patient B. While the patient A had a unilateral tumor with smaller GTV volume (23.3 cc) irradiated by straight lateral and posterior beams, the patient B had bilaterally located larger GTV volume (342.2 cc) covered by two posterior oblique beams.The study suggested that when the vagina is adjacent but located distal to the tumor, a significant dose reduction can be achieved with the insertion of a silicon-filled vaginal spacer.

Characterization of an Iodinated Rectal Spacer for Prostate Photon and Proton Radiation Therapy

PurposeConventional rectal spacers (nonI-SPs) are low-contrast on computed tomography (CT), often necessitating magnetic resonance imaging for accurate delineation. A new formulation of spacers (I-SPs) incorporates iodine to improve radiopacity and CT visualization. We characterized placement, stability, and plan quality of I-SPs compared to nonI-SPs. Methods and MaterialsPatients with intact prostate cancer (n = 50) treated with I-SPs and photons were compared to randomly selected patients (n = 50) with nonI-SPs (photon or proton therapy). The I-SP was contoured on the planning CT and cone beam CTs at 3 timepoints: first, middle, and final treatment (n = 200 scans). I-SPs Hounsfield units (HU), volume, surface area (SA), centroid position relative to prostate centroid, and distance between prostate/rectum centroids were compared on the planning CTs between each cohort. I-SP changes were evaluated on cone beam CTs over courses of treatment. Dosimetric evaluations of plan quality and robustness were performed. I-SP was tested in a phantom to characterize its relative linear stopping power for protons. ResultsI-SPs yielded a distinct visible contrast on planning CTs compared to nonI-SPs (HU 138 vs 12, P < .001), allowing delineation on CT alone. The delineated volume and SA of I-SPs were smaller than nonI-SPs (volume 8.9 vs 10.6 mL, P < .001; SA 28 vs 35 cm2, P < .001), yet relative spacer position and prostate-rectal separation were similar (P = .79). No significant change in HU, volume, SA, or relative position of the I-SPs hydrogel occurred over courses of treatment (all P > .1). Dosimetric analysis concluded there were no significant changes in plan quality or robustness for I-SPs compared to nonI-SPs. The I-SP relative linear stopping power was 1.018, necessitating HU override for proton planning. ConclusionsI-SPs provide a manifest CT contrast, allowing for delineation on planning CT alone with no magnetic resonance imaging necessary. I-SPs radiopacity, size, and relative position remained stable over courses of treatment from 28 to 44 fractions. No changes in plan quality or robustness were seen comparing I-SPs and nonI-SPs.

Low Intensity Beam Extraction Mode on the Protom Synchrotron for Proton Radiography Implementation

Proton radiography is one of the most important and actual areas of research that can significantly improve the quality and accuracy of proton therapy. Currently, the calculation of the proton range in patients receiving proton therapy is based on the conversion of Hounsfield CT units of the patient's tissues into the relative stopping power of protons. Proton radiography is able to reduce these uncertainties by directly measuring proton stopping power. The study demonstrates the possibility of Protom synchrotron-based proton therapy facilities to operate in a special mode which makes it possible to implement proton radiography. This work presents the status of the new low beam intensity extraction mode. The paper describes algorithms of low flux beam control, calibration procedures and experimental measurements. Measurements and calibration procedures were performed with certified Protom Faraday Cup, PTW Bragg Peak Chamber and specially designed experimental external.

Investigating beam range uncertainty in proton prostate treatment using pelvic-like biological phantoms

This study aims to develop a method for verifying site-specific and/or beam path specific proton beam range, which could reduce range uncertainty margins and the associated treatment complications. It investigates the range uncertainties from both CT HU to relative stopping power conversion and patient positioning errors for prostate treatment using pelvic-like biological phantoms. Three 25 × 14 × 12 cm3 phantoms, made of fresh animal tissues mimicking the pelvic anatomies of prostate patients, were scanned with a general electric CT simulator. A 22 cm circular passive scattering beam with 29 cm range and 8 cm modulation width was used to measure the water equivalent path lengths (WEPL) through the phantoms at multiple points using the dose extinction method with a MatriXXPT detector. The measured WEPLs were compared to those predicted by TOPAS simulations and ray-tracing WEPL calculations. For the three phantoms, the WEPL differences between measured and theoretical prediction (WDMT) are below 1.8% for TOPAS, and 2.5% for ray-tracing. WDMT varies with phantom anatomies by about 0.5% for both TOPAS and ray-tracing. WDMT also correlates with the tissue types of a specific treated region. For the regions where the proton beam path is parallel to sharp bone edges, the WDMTs of TOPAS and ray-tracing respectively reach up to 1.8% and 2.5%. For the region where proton beams pass through just soft tissues, the WDMT is mostly less than 1% for both TOPAS and ray-tracing. For prostate treatments, range uncertainty depends on the tissue types within a specific treated region, patient anatomies and the range calculation methods in the planning algorithms. Our study indicates range uncertainty is less than 2.5% for the whole treated region with both ray-tracing and TOPAS, which suggests the potential to reduce the current 3.5% range uncertainty margin used in the clinics by at least 1% even for single-energy CT data.

Implementation and experimental evaluation of Mega-voltage fan-beam CT using a linear accelerator

BackgroundMega-voltage fan-beam Computed Tomography (MV-FBCT) holds potential in accurate determination of relative electron density (RED) and proton stopping power ratio (SPR) but is not widely available.ObjectiveTo demonstrate the feasibility of MV-FBCT using a medical linear accelerator (LINAC) with a 2.5 MV imaging beam, an electronic portal imaging device (EPID) and multileaf collimators (MLCs).MethodsMLCs were used to collimate MV beam along z direction to enable a 1 cm width fan-beam. Projection data were acquired within one gantry rotation and preprocessed with in-house developed artifact correction algorithms before the reconstruction. MV-FBCT data were acquired at two dose levels: 30 and 60 monitor units (MUs). A Catphan 604 phantom was used to evaluate basic image quality. A head-sized CIRS phantom with three configurations of tissue-mimicking inserts was scanned and MV-FBCT Hounsfield unit (HU) to RED calibration was established for each insert configuration using linear regression. The determination coefficient ({R}^{2}) was used to gauge the accuracy of HU-RED calibration. Results were compared with baseline single-energy kilo-voltage treatment planning CT (TP-CT) HU-RED calibration which represented the current standard clinical practice.ResultsThe in-house artifact correction algorithms effectively suppressed ring artifact, cupping artifact, and CT number bias in MV-FBCT. Compared to TP-CT, MV-FBCT was able to improve the prediction accuracy of the HU-RED calibration curve for all three configurations of insert materials, with {R}^{2} > 0.9994 and {R}^{2} < 0.9990 for MV-FBCT and TP-CT HU-RED calibration curves of soft-tissue inserts, respectively. The measured mean CT numbers of blood-iodine mixture inserts in TP-CT drastically deviated from the fitted values but not in MV-FBCT. Reducing the radiation level from 60 to 30 MU did not decrease the prediction accuracy of the MV-FBCT HU-RED calibration curve.ConclusionWe demonstrated the feasibility of MV-FBCT and its potential in providing more accurate RED estimation.