Multiple Coulomb scattering (MCS) is the largest contributor to blurring in proton imaging. In this work, we developed a maximum likelihood least squares estimator that improves proton radiography's spatial resolution. The water equivalent thickness (WET) through projections defined from the source to the detector pixels were estimated such that they maximizes the likelihood of the energy loss of every proton crossing the volume. The length spent in each projection was calculated through the optimized cubic spline path estimate. The proton radiographies were produced using Geant4 simulations. Three phantoms were studied here: a slanted cube in a tank of water to measure 2D spatial resolution, a voxelized head phantom for clinical performance evaluation as well as a parametric Catphan phantom (CTP528) for 3D spatial resolution. Two proton beam configurations were used: a parallel and a conical beam. Proton beams of 200 and 330 MeV were simulated to acquire the radiography. Spatial resolution is increased from 2.44 lp cm to 4.53 lp cm in the 200 MeV beam and from 3.49 lp cm to 5.76 lp cm in the 330 MeV beam. Beam configurations do not affect the reconstructed spatial resolution as investigated between a radiography acquired with the parallel (3.49 lp cm to 5.76 lp cm) or conical beam (from 3.49 lp cm to 5.56 lp cm). The improved images were then used as input in a photon tomography algorithm. The proton CT reconstruction of the Catphan phantom shows high spatial resolution (from 2.79 to 5.55 lp cm for the parallel beam and from 3.03 to 5.15 lp cm for the conical beam) and the reconstruction of the head phantom, although qualitative, shows high contrast in the gradient region. The proposed formulation of the optimization demonstrates serious potential to increase the spatial resolution (up by 65[Formula: see text]) in proton radiography and greatly accelerate proton computed tomography reconstruction.
A comprehensive evaluation of the accuracy of CBCT and deformable registration based dose calculation 4 in lung proton therapy 5 The uncertainties in water equivalent thickness (WET) and accuracy of dose estimation using a virtual CT 30 (vCT), generated from deforming the planning CT (pCT) onto the daily cone-beam CT (CBCT), were 31 comprehensively evaluated in the context of lung malignancies and passive scattering proton therapy. The 32 validation methodology utilized multiple CBCT datasets to generate the vCTs of twenty lung cancer 33 patients. A correction step was applied to the vCTs to account for anatomical modifications that could not 34 be modeled by deformation alone. The CBCT datasets included a regular CBCT (rCBCT) and synthetic 35CBCTs created from the rCBCT and rescan CT (rCT), which minimized the variation in setup between the 36 vCT and the gold-standard image (i.e., rCT). The uncertainty in WET was defined as the voxelwise 37 2 difference in WET between vCT and rCT, and calculated in 3D (planning target volume, PTV) and 2D 1 (distal and proximal surfaces). The uncertainty in WET based dose warping was defined as the difference 2 between the warped dose and a forward dose recalculation on the rCT. The overall root mean square (RMS) 3 uncertainty in WET was 3.6±1.8, 2.2±1.4 and 3.3±1.8 mm for the distal surface, proximal surface and PTV, 4 respectively. For the warped dose, the RMS uncertainty of the voxelwise dose difference was 6±2% of the 5 maximum dose (%mD), using a 20% cut-off. The rCBCT resulted in higher uncertainties due to setup 6 variability with the rCT; the uncertainties reported with the two synthetic CBCTs were similar. The vCT 7 followed by a correction step was found to be an accurate alternative to rCT.
The relative stopping power (RSP) uncertainty is the largest contributor to the range uncertainty in proton therapy. The purpose of this work was to develop a systematic method that yields accurate and patient-specific RSPs by combining (1) pre-treatment x-ray CT and (2) daily proton radiography of the patient. The method was formulated as a penalized least squares optimization problem (argmin([Formula: see text])). The parameter A represents the cumulative path-length crossed by the proton in each material, separated by thresholding on the HU. The material RSPs (water equivalent thickness/physical thickness) are denoted by x. The parameter b is the list-mode proton radiography produced using Geant4 simulations. The problem was solved using a non-negative linear-solver with [Formula: see text]. A was computed by superposing proton trajectories calculated with a cubic or linear spline approach to the CT. The material's RSP assigned in Geant4 were used for reference while the clinical HU-RSP calibration curve was used for comparison. The Gammex RMI-467 phantom was first investigated. The standard deviation between the estimated material RSP and the calculated RSP is 0.45%. The robustness of the techniques was then assessed as a function of the number of projections and initial proton energy. Optimization with two initial projections yields precise RSP (⩽1.0%) for 330 MeV protons. 250 MeV protons have shown higher uncertainty (⩽2.0%) due to the loss of precision in the path estimate. Anthropomorphic phantoms of the head, pelvis, and lung were subsequently evaluated. Accurate RSP has been obtained for the head ([Formula: see text]), the lung ([Formula: see text]) and the pelvis ([Formula: see text]). The range precision has been optimized using the calibration curves obtained with the algorithm, yielding a mean [Formula: see text] difference to the reference of 0.11 ±0.09%, 0.28 ± 0.34% and [Formula: see text] in the same order. The solution's accuracy is limited by the assumed HU/RSP bijection, neglecting inherent degeneracy. The proposed formulation of the problem with prior knowledge x-ray CT demonstrates potential to increase the accuracy of present RSP estimates.
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