RESUMO
Objective. Single-isocenter-multiple-target technique for stereotactic radiosurgery (SRS) can reduce treatment duration but risks compromised dose coverage due to potential rotational errors. Clustering targets into two groups can reduce isocenter-target distances, mitigating the impact of rotational uncertainty. However, a comprehensive evaluation of clustering algorithms for SRS is absent. This study addresses this gap by introducing the SRS Target Clustering Framework (Framework), a comprehensive tool that utilizes commonly used clustering algorithms to generate efficient cluster configurations.Approach. The Framework incorporates four distinct optimization objectives based on two key metrics: the isocenter-target distance and the ratio of this distance to the target radius. Agglomerative and weighted agglomerative clustering are employed for minimax and weighted minimax objectives, respectively. K-means and weighted k-means are utilized for sum-of-squares and weighted sum-of-squares objectives. We applied the Framework to 126 SRS plans, comparing results to ground truth solutions obtained through a brute force algorithm.Main results. For the minimax objective, the average maximum isocenter-target distance from agglomerative clustering (4.8 cm) was slightly higher than the ground truth (4.6 cm). Similarly, the weighted agglomerative clustering achieved an average maximum ratio of 15.1 compared to the ground truth of 14.6. Notably, both k-means and weighted k-means clustering showed close agreement (within a precision of 0.1) with the ground truth for average root-mean-square target-isocenter distance and ratio (3.6 cm and 11.1, respectively).Significance. These results demonstrate the Framework's effectiveness in generating clusters for SRS targets. The proposed approach has the potential to become a valuable tool in SRS treatment planning. Furthermore, this study is the first to investigate clustering algorithms for both minimizing maximum and sum-of-squares uncertainty in SRS.
Assuntos
Algoritmos , Radiocirurgia , Planejamento da Radioterapia Assistida por Computador , Radiocirurgia/métodos , Humanos , Análise por Conglomerados , Planejamento da Radioterapia Assistida por Computador/métodos , Dosagem RadioterapêuticaRESUMO
PURPOSE: The purpose of this study was to investigate the impact of using flattening filter-free (FFF) beams and the aperture shape controller (ASC) on the complexity of conventional large-field treatment plans. METHODS AND MATERIALS: A total of 24 head and neck (H&N) and 24 prostate with pelvic nodes treatment plans were used in this study. Each plan was reoptimized using the original clinical objectives with both flattened and FFF beams, as well as six different ASC settings. The dosimetric qualities of each plan cohort were evaluated using commonly used dose-volume histogram values, and plan complexities were assessed through metrics including monitor unit (MU)/Dose, change in gantry speed, multileaf collimator (MLC) speed, the edge area ratio metric (EM), and the equivalent square length. RESULTS: No significant differences in dosimetric qualities were found between plans with flattened and FFF beams. The ASC settings did not have significant effects on dosimetric qualities in the H&N plan cohort, but the "very high" ASC setting resulted in poorer dosimetric results for the prostate plans. Plans with FFF beams had significantly higher MU/Dose compared to plans with flattened beams. The use of flattening filter (FF) had significant effects on the change in gantry speed, with flattened beams producing plans that required higher change in gantry speed. However, the FF did not have significant effects on MLC speed, EM, or equivalent square length. In contrast, ASC settings had significant effects on these three metrics; increasing the ASC level resulted in plans with decreasing MLC speed, lower edge area ratio, and higher equivalent square length. CONCLUSION: This study demonstrated that using FFF beams with various ASC settings, except for the "very high" level, can produce plans with reduced complexities without compromising dosimetric qualities in conventional large-field treatment plans.
Assuntos
Radiocirurgia , Radioterapia de Intensidade Modulada , Masculino , Humanos , Radioterapia de Intensidade Modulada/métodos , Planejamento da Radioterapia Assistida por Computador/métodos , Radiometria/métodos , Dosagem Radioterapêutica , Radiocirurgia/métodosRESUMO
BACKGROUND: There is currently a need for a clinically relevant small-animal model for irradiated, implant-based breast reconstruction. Present models are inadequate in terms of suboptimal location of expander placement and mode of radiation delivery, correlating poorly with the human clinical scenario. The authors hypothesized that by delivering fractionated radiation and placing an expander under the scalp of the animal, they would achieve soft-tissue changes histologically analogous to those seen in human irradiated, implant-based breast reconstruction. METHODS: This study consisted of 11 immunocompetent, hairless rats divided into three groups as follows: untreated control (n = 3), tissue-expanded scalps (n = 4), and fractionated irradiation plus tissue expansion of the scalp (n = 4). At the completion of the experiment for each group, skin tissue samples were analyzed histologically for vascularity, epidermal and dermal thickness, and collagen fiber alignment or scar formation. RESULTS: Expanded rat epidermis was significantly thicker and dermis was more vascular than nonexpanded skin. The authors observed a greater degree of collagen fiber alignment in the expanded group compared with nonexpanded skin. The combination of irradiation and expansion resulted in significant dermal thinning, vascular depletion, and increased scar formation compared with expanded skin alone. CONCLUSIONS: The authors describe a novel small-animal model for irradiated, implant-based breast reconstruction where histologic analysis shows structural changes in the skin consistent with known effects of radiation therapy and expansion in human skin. This model represents a significant improvement from previous ones and, as such, holds the potential to be used to test new therapeutic agents to improve clinical outcomes.
Assuntos
Mamoplastia , Couro Cabeludo/efeitos da radiação , Animais , Implante Mamário , Angiografia por Tomografia Computadorizada , Modelos Animais de Doenças , Fracionamento da Dose de Radiação , Epiderme/anatomia & histologia , Epiderme/efeitos da radiação , Masculino , Radiação Ionizante , Ratos Pelados , Couro Cabeludo/irrigação sanguínea , Expansão de Tecido/métodosRESUMO
PURPOSE: To develop a quality assurance (QA) tool that identifies inaccurate organ at risk (OAR) delineations. METHODS: The QA tool computed volumetric features from prior OAR delineation data from 73 thoracic patients to construct a reference database. All volumetric features of the OAR delineation are computed in three-dimensional space. Volumetric features of a new OAR are compared with respect to those in the reference database to discern delineation outliers. A multicriteria outlier detection system warns users of specific delineation outliers based on combinations of deviant features. Fifteen independent experimental sets including automatic, propagated, and clinically approved manual delineation sets were used for verification. The verification OARs included manipulations to mimic common errors. Three experts reviewed the experimental sets to identify and classify errors, first without; and then 1 week after with the QA tool. RESULTS: In the cohort of manual delineations with manual manipulations, the QA tool detected 94% of the mimicked errors. Overall, it detected 37% of the minor and 85% of the major errors. The QA tool improved reviewer error detection sensitivity from 61% to 68% for minor errors (P = 0.17), and from 78% to 87% for major errors (P = 0.02). CONCLUSIONS: The QA tool assists users to detect potential delineation errors. QA tool integration into clinical procedures may reduce the frequency of inaccurate OAR delineation, and potentially improve safety and quality of radiation treatment planning.