Purpose To demonstrate a proton‐imaging system based on well‐established fast scintillator technology to achieve high performance with low cost and complexity, with the potential of a straightforward translation into clinical use. Methods The system tracks individual protons through one (X, Y) scintillating fiber tracker plane upstream and downstream of the object and into a 13‐cm ‐thick scintillating block residual energy detector. The fibers in the tracker planes are multiplexed into silicon photomultipliers (SiPMs) to reduce the number of electronics channels. The light signal from the residual energy detector is collected by 16 photomultiplier tubes (PMTs). Only four signals from the PMTs are output from each event, which allows for fast signal readout. A robust calibration method of the PMT signal to residual energy has been developed to obtain accurate proton images. The development of patient‐specific scan patterns using multiple input energies allows for an image to be produced with minimal excess dose delivered to the patient. Results The calibration of signals in the energy detector produces accurate residual range measurements limited by intrinsic range straggling. We measured the water‐equivalent thickness (WET) of a block of solid water (physical thickness of 6.10 mm) with a proton radiograph. The mean WET from all pixels in the block was 6.13 cm (SD 0.02 cm). The use of patient‐specific scan patterns using multiple input energies enables imaging with a compact range detector. Conclusions We have developed a prototype clinical proton radiography system for pretreatment imaging in proton radiation therapy. We have optimized the system for use with pencil beam scanning systems and have achieved a reduction of size and complexity compared to previous designs.

Verification of patient-specific proton stopping powers obtained in the patient's treatment position can be used to reduce the distal and proximal margins needed in particle beam planning. Proton radiography can be used as a pretreatment instrument to verify integrated stopping power consistency with the treatment planning CT. Although a proton radiograph is a pixel by pixel representation of integrated stopping powers, the image may also be of high enough quality and contrast to be used for patient alignment. This investigation quantifies the accuracy and image quality of a prototype proton radiography system on a clinical proton delivery system. Methods: We have developed a clinical prototype proton radiography system designed for integration into efficient clinical workflows. We tested the images obtained by this system for water-equivalent thickness (WET) accuracy, image noise, and spatial resolution. We evaluated the WET accuracy by comparing the average WET and rms error in several regions of interest (ROI) on a proton radiograph of a custom peg phantom. We measured the spatial resolution on a CATPHAN Line Pair phantom and a custom edge phantom by measuring the 10% value of the modulation transfer function (MTF). In addition, we tested the ability to detect proton range errors due to anatomical changes in a patient with a customized CIRS pediatric head phantom and inserts of varying WET placed in the posterior fossae of the brain. We took proton radiographs of the phantom with each insert in place and created difference maps between the resulting images. Integrated proton range was measured from an ROI in the difference maps. Results: We measured the WET accuracy of the proton radiographic images to be AE0.2 mm (0.33%) from known values. The spatial resolution of the images was 0.6 lp/mm on the line pair phantom and 1.13 lp/mm on the edge phantom. We were able to detect anatomical changes producing changes in WET as low as 0.6 mm.

Objective Proton beam therapy is an emerging modality for cancer treatment that, compared to X-ray radiation therapy, promises to provide better dose delivery to clinical targets with lower doses to normal tissues. Crucial to accurate treatment planning and dose delivery is knowledge of the water equivalent path length (WEPL) of each ray, or pencil beam, from the skin to every point in the target. For protons, this length is estimated from relative stopping power based on X-ray Hounsfield units. Unfortunately, such estimates lead to 3 to 4% uncertainties in the proton range prediction. Therefore, protons in the Bragg peak may overshoot (or undershoot) the desired stopping depth in the target causing tissue damage beyond the target volume. Recent studies indicate that tomographic imaging using protons has the potential to provide directly more accurate measurement of RSPs with significantly lower radiation dose than X-rays. We are currently working on a proton radiography system that promises to provide accurate two-dimensional (2D) images of WEPL values for protons that pass through the body. These will be suitable for positioning and range verification in daily treatments. In this study, we demonstrate that this system is capable of rapidly achieving such accurate images in clinically meaningful times. Methods We have developed a software platform to characterize the potential performance of the prototype proton radiography system. We use Geant4 to simulate raw data detected by the device. An especially written software -pRadwas written to process these data as they are received and uses iterative methods to generate radiographs. The software has been designed to generate a radiograph from a few million protons in under a minute after receiving the first proton from the device. We used a head phantom with known chemical compositions that could be modeled quite accurately in Geant4 simulations of proton radiographs. The radiographs are displayed as pixelated WEPL values displayed on a 2D gray scale image of WEPL values. Results Rapid radiograph reconstruction of 3D phantoms using simulated proton pencil beams have been achieved with our software platform. On a modest desktop computer with a single central processing unit (CPU) and a single graphics processing unit (GPU), it takes about 11 s to reconstruct images using iterative linear algorithms to reconstruct a radiograph from 7.6 million protons. For the radiographic reconstructions of the head phantom described here, the mean WEPL errors, in the proton radiograph using a large majority of the pixels in the complete image were less than 1 mm when compared to images obtained without proton scattering and without detector resolution included.

Purpose: 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. Methods: 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. Results: 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. Conclusions: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. K E Y W O R D Sdigitally reconstructed radiograph, iterative algorithm, proton computed tomography, proton imaging, proton radiography, relative stopping power 7998

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BackgroundImproving 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 RSP accuracy. PurposeThe 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 reconstruction algorithm. MethodsA 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 RSP noise. ResultsIn 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 0.61 lp/mm, while for the ProtonVDA scanner somewhat lower at 0.46 lp/mm. ConclusionsThe 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).

Purpose/Objective(s): Margin reduction and hypo-fractionated treatment of pancreatic cancer is increasing in interest and practice in radiation oncology, but pancreatic motion has the potential to limit clinical efficacy. This study details the magnitude of observed positional variations of pancreatic tumors treated with radiation therapy utilizing the results of daily image guided radiation therapy (IGRT). Materials/Methods: Daily IGRT shifts based on cone-beam CT (CBCT) and mega-voltage CT (MVCT) were recorded and evaluated in order to estimate positioning variations of pancreatic target volumes. A total of 72 patients and 1159 3D-images captured immediately prior to daily conventionally fractionated RT were considered. Overall positioning variations, inter-patient variations, and correlations between position variations and patient-specific factors including PTV volume, tumor location (head/body/tail of pancreas), and central or lateral positioning of the PTV were estimated. Statistical analysis of the positioning variations included Kolmogorov-Smirnov (KS) testing for normality of distributions. Estimation of appropriate margins was carried out based on MZ2.5S+0.7s assuming the measured inter-fraction shifts are representative of intrafraction motion, and present a conservative estimate of spatial expansions to ensure coverage of the CTV. Results: Mean and standard deviation of IGRT shifts for all patients was 0.2AE5.2 mm in lateral directions,-0.3AE4.3 mm in vertical directions, and-0.7AE5.5 mm in longitudinal directions. The systematic variation (the standard deviation of inter-patient average shifts) was 2.6 mm, 2.6 mm, and 3.0 mm in lateral, vertical, and longitudinal directions. The random variation (the average of inter-patient standard deviations) was 3.9 mm, 3.0 mm, and 4.1 mm lateral, vertical, and longitudinal directions. Combined, these results suggest uniform margins about the CTV up to 10.4 mm are sufficient to account for observed positioning variations during IGRT. For each patient, KS testing implies the patient-specific shifts were representative of Gaussian distributions for 70/72 patients and 2/216 patient-specific directional distributions. The patient-specific distributions were not correlated with PTV volume, central or lateral location of the PTV, or whether the tumor was in the pancreatic head, tail, or body. Conclusion: Pancreas is a mobile organ with potential for large motion; our results suggest this motion is normally distributed and well-represented by Gaussian distributions. If intra-and inter-fraction motion are similar, which is plausible if pancreas motion is due to breathing and gastrointestinal motion, our data suggest margins of 10.4 mm will account for these spatial variations. These margins will surely overlap with surrounding bowel, duodenum, and/or stomach and imply dose escalation of margin-based PTVs may not be feasible.

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