Search

FLASH radiation therapy (FLASH-RT), delivered with ultrahigh dose rate (UHDR), may allow patients to be treated with less normal tissue toxicity for a given tumor dose compared with currently used conventional dose rate. Clinical trials are being carried out and are needed to test whether this improved therapeutic ratio can be achieved clinically. During the clinical trials, quality assurance and credentialing of equipment and participating sites, particularly pertaining to UHDR-specific aspects, will be crucial for the validity of the outcomes of such trials. This report represents an initial framework proposed by the NRG Oncology Center for Innovation in Radiation Oncology FLASH working group on quality assurance of potential UHDR clinical trials and reviews current technology gaps to overcome. An important but separate consideration is the appropriate design of trials to most effectively answer clinical and scientific questions about FLASH. This paper begins with an overview of UHDR RT delivery methods. UHDR beam delivery parameters are then covered, with a focus on electron and proton modalities. The definition and control of safe UHDR beam delivery and current and needed dosimetry technologies are reviewed and discussed. System and site credentialing for large, multi-institution trials are reviewed. Quality assurance is then discussed, and new requirements are presented for treatment system standard analysis, patient positioning, and treatment planning. The tables and figures in this paper are meant to serve as reference points as we move toward FLASH-RT clinical trial performance. Some major questions regarding FLASH-RT are discussed, and next steps in this field are proposed. FLASH-RT has potential but is associated with significant risks and complexities. We need to redefine optimization to focus not only on the dose but also on the dose rate in a manner that is robust and understandable and that can be prescribed, validated, and confirmed in real time. Robust patient safety systems and access to treatment data will be critical as FLASH-RT moves into the clinical trials.

This study aimed to determine the relationship between geometric and dosimetric agreement metrics in head and neck (H&N) cancer radiotherapy plans. A total 287 plans were retrospectively analyzed, comparing auto-contoured and clinically used contours using a Dice similarity coefficient (DSC), surface DSC (sDSC), and Hausdorff distance (HD). Organs-at-risk (OARs) with ≥200 cGy dose differences from the clinical contour in terms of Dmax (D0.01cc) and Dmean were further examined against proximity to the planning target volume (PTV). A secondary set of 91 plans from multiple institutions validated these findings. For 4995 contour pairs across 19 OARs, 90% had a DSC, sDSC, and HD of at least 0.75, 0.86, and less than 7.65 mm, respectively. Dosimetrically, the absolute difference between the two contour sets was <200 cGy for 95% of OARs in terms of Dmax and 96% in terms of Dmean. In total, 97% of OARs exhibiting significant dose differences between the clinically edited contour and auto-contour were within 2.5 cm PTV regardless of geometric agreement. There was an approximately linear trend between geometric agreement and identifying at least 200 cGy dose differences, with higher geometric agreement corresponding to a lower fraction of cases being identified. Analysis of the secondary dataset validated these findings. Geometric indices are approximate indicators of contour quality and identify contours exhibiting significant dosimetric discordance. For a small subset of OARs within 2.5 cm of the PTV, geometric agreement metrics can be misleading in terms of contour quality. [ABSTRACT FROM AUTHOR]

Background: Successful generation of biomechanical‐model‐based deformable image registration (BM‐DIR) relies on user‐defined parameters that dictate surface mesh quality. The trial‐and‐error process to determine the optimal parameters can be labor‐intensive and hinder DIR efficiency and clinical workflow. Purpose: To identify optimal parameters in surface mesh generation as boundary conditions for a BM‐DIR in longitudinal liver and lung CT images to facilitate streamlined image registration processes. Methods: Contrast‐enhanced CT images of 29 colorectal liver cancer patients and end‐exhale four‐dimensional CT images of 26 locally advanced non‐small cell lung cancer patients were collected. Different combinations of parameters that determine the triangle mesh quality (voxel side length and triangle edge length) were investigated. The quality of DIRs generated using these parameters was evaluated with metrics for geometric accuracy, robustness, and efficiency. Metrics for geometric accuracy included target registration error (TRE) of internal vessel bifurcations, dice similar coefficient (DSC), mean distance to agreement (MDA), Hausdorff distance (HD) for organ contours, and number of vertices in the triangle mesh. American Association of Physicists in Medicine Task Group 132 was used to ensure parameters met TRE, DSC, MDA recommendations before the comparison among the parameters. Robustness was evaluated as the success rate of DIR generation, and efficiency was evaluated as the total time to generate boundary conditions and compute finite element analysis. Results: Voxel side length of 0.2 cm and triangle edge length of 3 were found to be the optimal parameters for both liver and lung, with success rate of 1.00 and 0.98 and average DIR computation time of 100 and 143 s, respectively. For this combination, the average TRE, DSC, MDA, and HD were 0.38–0.40, 0.96–0.97, 0.09–0.12, and 0.87–1.17 mm, respectively. Conclusion: The optimal parameters were found for the analyzed patients. The decision‐making process described in this study serves as a recommendation for BM‐DIR algorithms to be used for liver and lung. These parameters can facilitate consistence in the evaluation of published studies and more widespread utilization of BM‐DIR in clinical practice. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this work was to provide a novel description of how the radiotherapy community configures treatment planning system (TPS) radiation beam models for clinically used treatment machines. Here we describe the results of a survey of self‐reported TPS beam modeling parameter values across different C‐arm linear accelerators, beam energies, and multileaf collimator (MLC) configurations. Acquisition and validation methods: Beam modeling data were acquired via electronic survey implemented through the Imaging and Radiation Oncology Core (IROC) Houston Quality Assurance Center's online facility questionnaire. The survey was open to participation from January 2018 through January 2019 for all institutions monitored by IROC. After quality control, 2818 beam models were collected from 642 institutions. This survey, designed for Eclipse, Pinnacle, and RayStation, instructed physicists to report parameter values used to model the radiation source and MLC for each treatment machine and beam energy used clinically for intensity‐modulated radiation therapy. Parameters collected included the effective source/spot size, MLC transmission, dosimetric leaf gap, tongue and groove effect, and other nondosimetric parameters specific to each TPS. To facilitate survey participation, instructions were provided on how to identify requested beam modeling parameters within each TPS environment. Data format and usage notes: Numeric values of the beam modeling parameters are compiled and tabulated according to TPS and calculation algorithm, linear accelerator model class, beam energy, and MLC configuration. Values are also presented as distributions, ranging from the 2.5th to the 97.5th percentile. Potential applications: These data provide an independent guide describing how the radiotherapy community mathematically represents its clinical radiation beams. These distributions may be used by the community for comparison during the commissioning or verification of their TPS beam models. Ultimately, we hope that the current work will allow institutions to spot potentially suspicious parameter values and help ensure more accurate radiotherapy delivery. [ABSTRACT FROM AUTHOR]

Purpose: While disparities in the inclusion and advancement of women and minorities in science, technology, engineering, mathematics, and medical fields have been well documented, less work has focused on medical physics specifically. In this study, we evaluate historical and current diversity within the medical physics workforce, in cohorts representative of professional advancement (PA) in the field, and within National Institutes of Health (NIH)-funded medical physics research activities., Methods and Materials: The 2020 American Association of Physicists in Medicine (AAPM) membership was queried as surrogate for the medical physics workforce. Select subsets of the AAPM membership were queried as surrogate for PA and early career professional advancement (ECPA) in medical physics. Self-reported AAPM-member demographics data representative of study analysis groups were identified and analyzed. Demographic characteristics of the 2020 AAPM membership were compared with those of the PA and ECPA cohorts and United States (US) population. The AAPM-NIH Research Database was appended with principal investigator (PI) demographics data and analyzed to evaluate trends in grant allocation by PI demographic characteristics., Results: Women, Hispanic/Latinx/Spanish individuals, and individuals reporting a race other than White or Asian alone comprised 50.8%, 18.7%, and 32.4% of the US population, respectively, but only 23.9%, 9.1%, and 7.9% of the 2020 AAPM membership, respectively. In general, representation of women and minorities was further decreased in the PA cohort; however, significantly higher proportions of women ( P < .001) and Hispanic/Latinx/Spanish members ( P < .05) were observed in the ECPA cohort than the 2020 AAPM membership. Analysis of historical data revealed modest increases in diversity within the AAPM membership since 2002. Across NIH grants awarded to AAPM members between 1985 and 2020, only 9.4%, 5.3%, and 1.7% were awarded to women, Hispanic/Latinx/Spanish, and non-White, non-Asian PIs, respectively., Conclusions: Diversity within medical physics is limited. Proactive policy should be implemented to ensure diverse, equitable, and inclusive representation within research activities, roles representative of PA, and the profession at large., (© 2022 The Author(s).)