Treatment planning of scanned proton beams in RayStation
Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
Cited by 10 publications
References 73 publications
Beyond a constant proton relative biological effectiveness: A survey of clinical and research perspectives among proton institutions in Europe and the United States
PurposeAlthough proton relative biological effectiveness (RBE) depends on factors like linear energy transfer (LET), tissue properties, dose, and biological endpoint, a constant RBE of 1.1 is recommended in clinical practice. This study surveys proton institutions to explore activities using functionalities beyond a constant proton RBE.MethodsResearch versions of RayStation integrate functionalities considering variable proton RBE, LET, proton track‐ends, and dirty dose. A survey of 19 institutions in Europe and the United States, with these functionalities available, investigated clinical adoption and research prospects using a 25‐question online questionnaire.ResultsOf the 16 institutions that responded (84% response rate), 13 were clinically active. These clinical institutions prescribe RBE = 1.1 but also employ planning strategies centered around special beam arrangements to address potentially enhanced RBE effects in serially structured organs at risk (OARs). Clinical plan evaluation encompassed beam angles/spot position (69%), dose‐averaged LET (LETd) (46%), and variable RBE distributions (38%). High ratings (discrete scale: 1–5) were reported for the research functionalities using linear LETd‐RBE models, LETd, track‐end frequency and dirty dose (averages: 4.0–4.8), while LQ‐based phenomenological RBE models dependent on LETd scored lower for optimization (average: 2.2) but congruent for evaluation (average: 4.1). The institutions preferred LET reported as LETd (94%), computed in unit‐density water (56%), for all protons (63%), and lean toward LETd‐based phenomenological RBE models for clinical use (> 50%).ConclusionsProton institutions recognize RBE variability but adhere to a constant RBE while actively mitigating potential enhancements, particularly in serially structured OARs. Research efforts focus on planning techniques that utilize functionalities beyond a constant RBE, emphasizing standardized LET and RBE calculations to facilitate their adoption in clinical practice and improve clinical data collection. LETd calculated in unit‐density water for all protons as input to adaptable phenomenological RBE models was the most suggested approach, aligning with predominant clinical LET and variable RBE reporting.
Beyond a constant proton relative biological effectiveness: A survey of clinical and research perspectives among proton institutions in Europe and the United States
PurposeAlthough proton relative biological effectiveness (RBE) depends on factors like linear energy transfer (LET), tissue properties, dose, and biological endpoint, a constant RBE of 1.1 is recommended in clinical practice. This study surveys proton institutions to explore activities using functionalities beyond a constant proton RBE.MethodsResearch versions of RayStation integrate functionalities considering variable proton RBE, LET, proton track‐ends, and dirty dose. A survey of 19 institutions in Europe and the United States, with these functionalities available, investigated clinical adoption and research prospects using a 25‐question online questionnaire.ResultsOf the 16 institutions that responded (84% response rate), 13 were clinically active. These clinical institutions prescribe RBE = 1.1 but also employ planning strategies centered around special beam arrangements to address potentially enhanced RBE effects in serially structured organs at risk (OARs). Clinical plan evaluation encompassed beam angles/spot position (69%), dose‐averaged LET (LETd) (46%), and variable RBE distributions (38%). High ratings (discrete scale: 1–5) were reported for the research functionalities using linear LETd‐RBE models, LETd, track‐end frequency and dirty dose (averages: 4.0–4.8), while LQ‐based phenomenological RBE models dependent on LETd scored lower for optimization (average: 2.2) but congruent for evaluation (average: 4.1). The institutions preferred LET reported as LETd (94%), computed in unit‐density water (56%), for all protons (63%), and lean toward LETd‐based phenomenological RBE models for clinical use (> 50%).ConclusionsProton institutions recognize RBE variability but adhere to a constant RBE while actively mitigating potential enhancements, particularly in serially structured OARs. Research efforts focus on planning techniques that utilize functionalities beyond a constant RBE, emphasizing standardized LET and RBE calculations to facilitate their adoption in clinical practice and improve clinical data collection. LETd calculated in unit‐density water for all protons as input to adaptable phenomenological RBE models was the most suggested approach, aligning with predominant clinical LET and variable RBE reporting.
Comparison of translation algorithms in determining maximum allowable CTV shifts for Real‐Time Gated Proton Therapy (RGPT) robustness evaluation in prostate cancers
IntroductionReal‐Time Gated Proton Therapy (RGPT) is an active motion management technique that utilizes treatment gating and tumor tracking via fiducial markers. When performing RGPT treatment for prostate cancer, it is essential to account for the CTV displacement relative to the body in the clinical workflow. The workflow at the National Cancer Centre Singapore (NCCS) includes bone matching via CT‐CBCT images, followed by fiducial matching via pulsed fluoroscopy (soft tissue matching), and finally, a robustness evaluation procedure to determine if the difference is within an allowable tolerance. In this study, we compare two CTV translation methods for robustness evaluation: (1) an in‐house translation algorithm and (2) the RayStation “simulate organ motion” Deformable image registration (DIR) algorithm.MethodsNine RGPT prostate patient plans with CTV volumes ranging from 17.1 to 96.72 cm2 were included in this study. An in‐house translation algorithm and “simulate organ motion” DIR RayStation algorithm were used to generate CTV shifts along R‐L, I‐S, and P‐A axes between 10 mm at 2 mm steps. At each step, dose metrics, which include CTV Dmax, CTV D95%, and CTV D98%, were extracted and used as comparative metrics for CTV target coverage and hot spot evaluation.ResultsAcross all axes, there were no statistically significant differences between the two algorithms for all three dose metrics: CTV Dmax (P = 0.92, P = 0.91, and P = 0.47), CTV D95% (P = 0.97, P = 0.22, and P = 0.33), and CTV D98% (P = 0.85, P = 0.33, and P = 0.36). Further, the in‐house translation algorithm evaluation time was less than 10 s, two orders of magnitude faster than the DIR algorithm.ConclusionOur results demonstrate that the simpler in‐house algorithm performs equivalently to the realistic DIR algorithm when simulating CTV motion in prostate cancers. Furthermore, the in‐house algorithm completes the robustness evaluation two orders of magnitude faster than the DIR algorithm. This significant reduction in evaluation time is crucial especially when preparatory time efficiency is of paramount importance in a busy clinic.
TEAM: Triangular‐mEsh Adaptive and Multiscale proton spot generation method
BackgroundProton therapy is preferred for its dose conformality to spare normal tissues and organs‐at‐risk (OAR) via Bragg peaks with negligible exit dose. However, proton dose conformality can be further optimized: (1) the spot placement is based on the structured (e.g., Cartesian) grid, which may not offer conformal shaping to complex tumor targets; (2) the spot sampling pattern is uniform, which may be insufficient at the tumor boundary to provide the sharp dose falloff, and at the same time may be redundant at the tumor interior to provide the uniform dose coverage, for example, due to multiple Coulomb scattering (MCS); and (3) the lateral spot penumbra increases with respect to the depth due to MCS, which blurs the lateral dose falloff. On the other hand, while (1) the deliverable spots are subject to the minimum‐monitor‐unit (MMU) constraint, and (2) the dose rate is proportional to the MMU threshold, the current spot sampling method is sensitive to the MMU threshold and can fail to provide satisfactory plan quality for a large MMU threshold (i.e., high‐dose‐rate delivery).PurposeThis work will develop a novel Triangular‐mEsh‐based Adaptive and Multiscale (TEAM) proton spot generation method to address these issues for optimizing proton dose conformality and plan delivery efficiency.MethodsCompared to the standard clinically‐used spot placement method, three key elements of TEAM are as follows: (1) a triangular mesh instead of a structured grid: the triangular mesh is geometrically more conformal to complex target shapes and therefore more efficient and accurate for dose shaping inside and around the target; (2) adaptive sampling instead of uniform sampling: the adaptive sampling consists of relatively dense sampling at the tumor boundary to create the sharp dose falloff, which is more accurate, and coarse sampling at the tumor interior to uniformly cover the target, which is more efficient; and (3) depth‐dependent sampling instead of depth‐independent sampling: the depth‐dependent sampling is used to compensate for MCS, that is, with increasingly dense sampling at the tumor boundary to improve dose shaping accuracy, and increasingly coarse sampling at the tumor interior to improve dose shaping efficiency, as the depth increases. In the TEAM method the spot locations are generated for each energy layer and layer‐by‐layer in the multiscale fashion; and then the spot weights are derived by solving the IMPT problem of dose‐volume planning objectives, MMU constraints, and robustness optimization with respect to range and setup uncertainties.ResultsCompared to the standard clinically‐used spot placement method UNIFORM, TEAM achieved (1) better plan quality using <60% number of spots of UNIFORM; (2) better robustness to the number of spots; (3) better robustness to a large MMU threshold. Furthermore, TEAM provided better plan quality with fewer spots than other adaptive methods (Cartesian‐grid or triangular‐mesh).ConclusionsA novel triangular‐mesh‐based proton spot placement method called TEAM is proposed, and it is demonstrated to improve plan quality, robustness to the number of spots, and robustness to the MMU threshold, compared to the clinically‐used spot placement method and other adaptive methods.
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.
Contact Info
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Product
Resources
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.
