Ion computed tomography (iCT) represents a potential replacement for x-ray CT (xCT) in ion therapy treatment planning to reduce range uncertainties, inherent in the semi-empirical conversion of xCT information into relative stopping power (RSP). In this work, we aim to quantify the increase in dosimetric accuracy associated with using proton-, helium- and carbon-CT compared to conventional xCT for clinical scenarios in proton therapy. Three cases imaged with active beam-delivery using an ideal single-particle-tracking detector were investigated using FLUKA Monte-Carlo (MC) simulations. The RSP accuracy of the iCTs was evaluated against the ground truth at similar physical dose. Next, the resulting dosimetric accuracy was investigated by using the RSP images as a patient model in proton therapy treatment planning, in comparison to common uncertainties associated with xCT. Finally, changes in relative biological effectiveness (RBE) with iCT particle type/spectrum were investigated by incorporating the repair-misrepair-fixation (RMF) model into FLUKA, to enable first insights on the associated biological imaging dose. Helium-CT provided the lowest overall RSP error, whereas carbon-CT offered the highest accuracy for bone and proton-CT for soft tissue. For a single field, the average relative proton beam-range variation was −1.00%, +0.09%, −0.08% and −0.35% for xCT, proton-, helium- and carbon-CT, respectively. Using a 0.5%/0.5mm gamma-evaluation, all iCTs offered comparable accuracy with a better than 99% passing rate, compared to 83% for xCT. The RMF model predictions for RBE for cell death relative to a diagnostic xCT spectrum were 0.82–0.85, 0.85–0.89 and 0.97–1.03 for proton-, helium-, and carbon-CT, respectively. The corresponding RBE for DNA double-strand break induction was generally below one. iCT offers great clinical potential for proton therapy treatment planning by providing superior dose calculation accuracy as well as lower physical and potentially biological dose exposure compared to xCT. For the investigated dose level and ideal detector, proton-CT and helium-CT yielded the best performance.
Ion beam therapy offers the possibility of a highly conformal tumor-dose distribution; however, this technique is extremely sensitive to inaccuracies in the treatment procedures. Ambiguities in the conversion of Hounsfield units of the treatment planning x-ray CT to relative stopping power (RSP) can cause uncertainties in the estimated ion range of up to several millimeters. Ion CT (iCT) represents a favorable solution allowing to directly assess the RSP. In this simulation study we investigate the performance of the integration-mode configuration for carbon iCT, in comparison with a single-particle approach under the same set-up. The experimental detector consists of a stack of 61 air-filled parallel-plate ionization chambers, interleaved with 3 mm thick PMMA absorbers. By means of Monte Carlo simulations, this design was applied to acquire iCTs of phantoms of tissue-equivalent materials. An optimization of the acquisition parameters was performed to reduce the dose exposure, and the implications of a reduced absorber thickness were assessed. In order to overcome limitations of integration-mode detection in the presence of lateral tissue heterogeneities a dedicated post-processing method using a linear decomposition of the detector signal was developed and its performance was compared to the list-mode acquisition. For the current set-up, the phantom dose could be reduced to below 30 mGy with only minor image quality degradation. By using the decomposition method a correct identification of the components and a RSP accuracy improvement of around 2.0% was obtained. The comparison of integration- and list-mode indicated a slightly better image quality of the latter, with an average median RSP error below 1.8% and 1.0%, respectively. With a decreased absorber thickness a reduced RSP error was observed. Overall, these findings support the potential of iCT for low dose RSP estimation, showing that integration-mode detectors with dedicated post-processing strategies can provide a RSP accuracy comparable to list-mode configurations.
Towards a novel small animal proton irradiation platformthe SIRMIO project Background: Precision small animal radiotherapy research is a young emerging field aiming to provide new experimental insights into tumour and tissue models in different microenvironments, to unravel the complex mechanisms of radiation damage in target and non-target tissues and assess the efficacy of novel therapeutic strategies. To this end, for photon therapy, modern small animal radiotherapy research platforms have been developed over the last years and are meanwhile commercially available. Conversely, for proton therapy, which holds a great potential for an even superior outcome than photon therapy, no commercial system exists yet. Material and methods: The project SIRMIO (Small Animal Proton Irradiator for Research in Molecular Image-guided Radiation-Oncology) aims at realizing and demonstrating an innovative portable prototype system for precision small animal proton irradiation, suitable for integration at existing clinical treatment facilities. The proposed design combines precise dose application with novel insitu multi-modal anatomical image guidance and in-vivo verification of the actual treatment delivery for precision small animal irradiation. Results and conclusions: This manuscript describes the status of the different components under development, featuring a dedicated beamline for degradation and focusing of clinical proton beams, along with novel detector systems for insitu imaging. The foreseen workflow includes pre-treatment proton transmission imaging for treatment planning and position verification, complemented by ultrasonic tumour localization, followed by image-guided delivery with on-site range verification by means of ionoacoustics (for pulsed beams) and positronemission-tomography (PET, for continuous beams). The proposed compact and cost-effective system promises to open a new era in small animal proton therapy research, contributing to the basic understanding of in-vivo radiation action to identify areas of potential breakthroughs in radiotherapy for future translation into innovative clinical strategies.
The purpose of this work is to investigate the potentiality of using a limited number of in-room proton radiographies to compensate anatomical changes in adaptive proton therapy. The treatment planning CT is adapted to the treatment delivery scenario relying on 2D-3D deformable image registration (DIR). The proton radiographies, expressed in water equivalent thickness (WET) are simulated for both list-mode and integration-mode detector configurations in pencil beam scanning. Geometrical and analytical simulations of an anthropomorphic phantom in the presence of anatomical changes due to breathing are adopted. A Monte Carlo simulation of proton radiographies based on a clinical CT image in the presence of artificial anatomical changes is also considered. The accuracy of the 2D-3D DIR, calculated as root mean square error, strongly depends on the considered anatomical changes and is considered adequate for promising adaptive proton therapy when comparable to the accuracy of conventional 3D-3D DIR. In geometrical simulation, this is achieved with a minimum of eight/nine radiographies (more than 90% accuracy). Negligible improvement (sim1%) is obtained with the use of 180 radiographies. Comparing different detector configurations, superior accuracy is obtained with list-mode than integration-mode max (WET with maximum occurrence) and mean (average WET weighted by occurrences). Moreover, integration-mode max performs better than integration-mode mean. Results are minimally affected by proton statistics. In analytical simulation, the anatomical changes are approximately compensated (about 60%–70% accuracy) with two proton radiographies and minor improvement is observed with nine proton radiographies. In clinical data, two proton radiographies from list-mode have demonstrated better performance than nine from integration-mode (more than 100% and about 50%–70% accuracy, respectively), even avoiding the finer grid spacing of the last numerical optimization stage. In conclusion, the choice of detector configuration as well as the amount and complexity of the considered anatomical changes determine the minimum number of radiographies to be used.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.