A proton therapy workflow based on CBCT provided clinical indicators similar to those using rCT for patients with lung cancer with considerable anatomic changes.

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In electron and proton radiotherapy, applications of patient‐specific electron bolus or proton compensators during radiation treatments are often necessary to accommodate patient body surface irregularities, tissue inhomogeneity, and variations in PTV depths to achieve desired dose distributions. Emerging 3D printing technologies provide alternative fabrication methods for these bolus and compensators. This study investigated the potential of utilizing 3D printing technologies for the fabrication of the electron bolus and proton compensators. Two printing technologies, fused deposition modeling (FDM) and selective laser sintering (SLS), and two printing materials, PLA and polyamide, were investigated. Samples were printed and characterized with CT scan and under electron and proton beams. In addition, a software package was developed to convert electron bolus and proton compensator designs to printable Standard Tessellation Language file format. A phantom scalp electron bolus was printed with FDM technology with PLA material. The HU of the printed electron bolus was 106.5±15.2. A prostate patient proton compensator was printed with SLS technology and polyamide material with −70.1±8.1 HU. The profiles of the electron bolus and proton compensator were compared with the original designs. The average over all the CT slices of the largest Euclidean distance between the design and the fabricated bolus on each CT slice was found to be 0.84±0.45 mm and for the compensator to be 0.40±0.42 mm. It is recommended that the properties of specific 3D printed objects are understood before being applied to radiotherapy treatments.PACS number: 81.40

A major source of uncertainty in proton therapy is the conversion of Hounsfield unit (HU) to proton stopping power ratio relative to water (SPR). In this study, we measured and quantified the accuracy of a stoichiometric dual energy CT (DECT) SPR calibration. We applied a stoichiometric DECT calibration method to derive the SPR using CT images acquired sequentially at [Formula: see text] and [Formula: see text]. The dual energy index was derived based on the HUs of the paired spectral images and used to calculate the effective atomic number (Z ), relative electron density ([Formula: see text]), and SPRs of phantom and biological materials. Two methods were used to verify the derived SPRs. The first method measured the sample's water equivalent thicknesses to deduce the SPRs using a multi-layer ion chamber (MLIC) device. The second method utilized Gafchromic EBT3 film to directly compare relative ranges between sample and water after proton pencil beam irradiation. Ex vivo validation was performed using five different types of frozen animal tissues with the MLIC and three types of fresh animal tissues using film. In addition, the residual ranges recorded on the film were used to compare with those from the treatment planning system using both DECT and SECT derived SPRs. Bland-Altman analysis indicates that the differences between DECT and SPR measurement of tissue surrogates, frozen and fresh animal tissues has a mean of 0.07% and standard deviation of 0.58% compared to 0.55% and 1.94% respectively for single energy CT (SECT) and SPR measurement. Our ex vivo study indicates that the stoichiometric DECT SPR calibration method has the potential to be more accurate than SECT calibration under ideal conditions although beam hardening effects and other image artifacts may increase this uncertainty.

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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.

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Background: Radiotherapy treatment planning is increasingly automated and knowledge-based planning has been shown to match and sometimes improve upon manual clinical plans, with increased consistency and efficiency. In this study, we benchmarked a novel prototype knowledge-based intensity-modulated proton therapy (IMPT) planning solution, against three international proton centers. Methods: A model library was constructed, comprising 50 head and neck cancer (HNC) manual IMPT plans from a single center. Three external-centers each provided seven manual benchmark IMPT plans. A knowledge-based plan (KBP) using a standard beam arrangement for each patient was compared with the benchmark plan on the basis of planning target volume (PTV) coverage and homogeneity and mean organ-at-risk (OAR) dose. Results: PTV coverage and homogeneity of KBPs and benchmark plans were comparable. KBP mean OAR dose was lower in 32/54, 45/48 and 38/53 OARs from center-A, -B and -C, with 23/32, 38/45 and 23/38 being >2 Gy improvements, respectively. In isolated cases the standard beam arrangement or an OAR not being included in the model or being contoured differently, led to higher individual KBP OAR doses. Generating a KBP typically required <10 min. Conclusions: A knowledge-based IMPT planning solution using a single-center model could efficiently generate plans of comparable quality to manual HNC IMPT plans from centers with differing planning aims. Occasional higher KBP OAR doses highlight the need for beam angle optimization and manual review of KBPs. The solution furthermore demonstrated the potential for robust optimization.