Med Phys
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We propose a robust treatment planning model that simultaneously considers proton range and patient setup uncertainties and reduces high linear energy transfer (LET) exposure in organs at risk (OARs) to minimize the relative biological effectiveness (RBE) dose in OARs for intensity-modulated proton therapy (IMPT). Our method could potentially reduce the unwanted damage to OARs. ⋯ Explicitly considering LET in IMPT robust treatment planning can reduce the high LET to OARs and minimize the possible toxicity of high RBE dose to OARs without sacrificing plan quality. We believe this will allow one to design and deliver safer proton therapy.
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The implementation of motion management techniques in radiation therapy can aid in mitigating uncertainties and reducing margins. For motion management to be effective, it is necessary to track key structures both accurately and at a real-time speed. Therefore, the focus of this work was to develop a 2D algorithm for the real-time tracking of ultrasound features to aid in radiation therapy motion management. ⋯ Initial implementations indicated an accuracy that was comparable to or exceeding those achieved by alternative 2D tracking methods, with a computational speed that is more than sufficient for real-time applications in a radiation therapy environment. While the overall performance reached levels suitable for implementation in radiation therapy, the observed increase in failures for smaller features, as well as the algorithm's inability to be applied to nonconvex features warrants additional investigation to address the shortcomings observed.
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As part of a program to implement automatic lesion detection methods for whole body magnetic resonance imaging (MRI) in oncology, we have developed, evaluated, and compared three algorithms for fully automatic, multiorgan segmentation in healthy volunteers. ⋯ Three state-of-the-art algorithms were developed and used to automatically segment major organs and bones in whole body MRI; good agreement to manual segmentations performed by clinical MRI experts was observed. CNNs perform favorably, when using T2w volumes as input. Using multimodal MRI data as input to CNNs did not improve the segmentation performance.
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Radiosurgery is an established technique to treat cerebral arteriovenous malformations (AVMs). Obliteration of larger AVMs (> 10-15 cm3 or diameter > 3 cm) in a single session is challenging with current radiosurgery platforms due to toxicity. We present a novel technique of multistage stereotactic radiosurgery (SRS) for large intracranial arteriovenous malformations (AVM) using the Gamma Knife system. ⋯ The Gamma Knife system can deliver a multistaged conformal dose to treat large AVMs when correcting for translational setup errors of each shot at each staged treatment.
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The objective of this study was to introduce and evaluate a method for MR-based attenuation and truncation correction in phantom and patient measurements to improve PET quantification in PET/MR hybrid imaging. ⋯ The HUGE method for truncation correction combined with continuous table movement extends the lateral MR field-of-view and effectively reduces truncations along the outer contours of the patient's arms in whole-body PET/MR imaging. HUGE as a fully MR-based approach is independent of the choice of radiotracer, thus also offering robust truncation correction in patients that are not injected with Fluordesoxyglucose (FDG) as radiotracer. Therefore, this method improves the standard Dixon MR-based attenuation correction and PET image quantification in whole-body PET/MR imaging applications.