Search

Background: The first clinical trials to assess the feasibility of FLASH radiotherapy in humans have started (FAST‐01, FAST‐02) and more trials are foreseen. To increase comparability between trials it is important to assure treatment quality and therefore establish a standard for machine quality assurance (QA). Currently, the AAPM TG‐224 report is considered as the standard on machine QA for proton therapy, however, it was not intended to be used for ultra‐high dose rate (UHDR) proton beams, which have gained interest due to the observation of the FLASH effect. Purpose: The aim of this study is to find consensus on practical guidelines on machine QA for UHDR proton beams in transmission mode in terms of which QA is required, how they should be done, which detectors are suitable for UHDR machine QA, and what tolerance limits should be applied. Methods: A risk assessment to determine the gaps in the current standard for machine QA was performed by an international group of medical physicists. Based on that, practical guidelines on how to perform machine QA for UHDR proton beams were proposed. Results: The risk assessment clearly identified the need for additional guidance on temporal dosimetry, addressing dose rate (constancy), dose spillage, and scanning speed. In addition, several minor changes from AAPM TG‐224 were identified; define required dose rate levels, the use of clinically relevant dose levels, and the use of adapted beam settings to minimize activation of detector and phantom materials or to avoid saturation effects of specific detectors. The final report was created based on discussions and consensus. Conclusions: Consensus was reached on what QA is required for UHDR scanning proton beams in transmission mode for isochronous cyclotron‐based systems and how they should be performed. However, the group discussions also showed that there is a lack of high temporal resolution detectors and sufficient QA data to set appropriate limits for some of the proposed QA procedures. [ABSTRACT FROM AUTHOR]

Purpose: In the treatment of cervical cancer, large anatomical deformations, caused by, e.g., tumor shrinkage, bladder and rectum filling changes, organ sliding, and the presence of the brachytherapy (BT) applicator, prohibit the accumulation of external beam radiotherapy (EBRT) and BT dose distributions. This work proposes a structure-wise registration with vector field integration (SW+VF) to map the largely deformed anatomies between EBRT and BT, paving the way for 3D dose accumulation between EBRT and BT. Methods: T2w-MRIs acquired before EBRT and as a part of the MRI-guided BT procedure for 12 cervical cancer patients, along with the manual delineations of the bladder, cervix-uterus, and rectum-sigmoid, were used for this study. A rigid transformation was used to align the bony anatomy in the MRIs. The proposed SW+VF method starts by automatically segmenting features in the area surrounding the delineated organs. Then, each organ and feature pair is registered independently using a feature-based nonrigid registration algorithm developed in-house. Additionally, a background transformation is calculated to account for areas far from all organs and features. In order to obtain one transformation that can be used for dose accumulation, the organ-based, feature-based, and the background transformations are combined into one vector field using a weighted sum, where the contribution of each transformation can be directly controlled by its extent of influence (scope size). The optimal scope sizes for organ-based and feature-based transformations were found by an exhaustive analysis. The anatomical correctness of the mapping was independently validated by measuring the residual distances after transformation for delineated structures inside the cervix-uterus (inner anatomical correctness), and for anatomical landmarks outside the organs in the surrounding region (outer anatomical correctness). The results of the proposed method were compared with the results of the rigid transformation and nonrigid registration of all structures together (AST). Results: The rigid transformation achieved a good global alignment (mean outer anatomical correctness of 4.3 mm) but failed to align the deformed organs (mean inner anatomical correctness of 22.4 mm). Conversely, the AST registration produced a reasonable alignment for the organs (6.3 mm) but not for the surrounding region (16.9 mm). SW+VF registration achieved the best results for both regions (3.5 and 3.4 mm for the inner and outer anatomical correctness, respectively). All differences were significant (p < 0.02, Wilcoxon rank sum test). Additionally, optimization of the scope sizes determined that the method was robust for a large range of scope size values. Conclusions: The novel SW+VF method improved the mapping of large and complex deformations observed between EBRT and BT for cervical cancer patients. Future studies that quantify the mapping error in terms of dose errors are required to test the clinical applicability of dose accumulation by the SW+VF method. [ABSTRACT FROM AUTHOR]

Technical improvements in planning and dose delivery and in verification of patient positioning have substantially widened the therapeutic window for radiation treatment of cancer. However, changes in patient anatomy during the treatment limit the exploitation of these new techniques. To further improve radiation treatments, anatomical changes need to be modeled and accounted for. Nonrigid registration can be used for this purpose. This article describes the design, the implementation, and the validation of a new framework for nonrigid registration for radiotherapy applications. The core of this framework is an improved version of the thin plate spline robust point matching (TPS-RPM) algorithm. The TPS-RPM algorithm estimates a global correspondence and a transformation between the points that represent organs of interest belonging to two image sets. However, the algorithm does not allow for the inclusion of prior knowledge on the correspondence of subset of points, and therefore, it can lead to inconsistent anatomical solutions. In this article TPS-RPM was improved by employing a novel correspondence filter that supports simultaneous registration of multiple structures. The improved method allows for coherent organ registration and for the inclusion of user-defined landmarks, lines, and surfaces inside and outside of structures of interest. A procedure to generate control points from segmented organs is described. The framework parameters r and λ, which control the number of points and the nonrigidness of the transformation, respectively, were optimized for three sites with different degrees of deformation (head and neck, prostate, and cervix) using two cases per site. For the head and neck cases, the salivary glands were manually contoured on CT scans, for the prostate cases the prostate and the vesicles, and for the cervix cases the cervix uterus, the bladder, and the rectum. The transformation error obtained using the best set of parameters was below 1 mm for all the studied cases. The lengths of the deformation vectors were on average (±1 standard deviation) 5.8±2.5 and 2.6±1.1 mm for the head and neck cases, 7.2±4.5 and 8.6±1.9 mm for the prostate cases, and 19.0±11.6 and 14.5±9.3 mm for the cervix cases. Distinguishable anatomical features were identified for each case and were used to validate the registration by calculating residual distances after transformation: 1.5±0.8, 2.3±1.0, and 6.3±2.9 mm for the head and neck, prostate, and cervix sites, respectively. Finally, the authors demonstrated how the inclusion of these anatomical features in the registration process reduced the residual distances to 0.8±0.5, 0.6±0.5, and 1.3±0.7 mm for the head and neck, prostate, and cervix sites, respectively. The inclusion of additional anatomical features produced more anatomically coherent transformations without compromising the transformation error. The authors concluded that the presented nonrigid registration framework is a powerful tool to simultaneously register multiple segmented organs with very different complexities. [ABSTRACT FROM AUTHOR]