Med Phys
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Since the publication of the 2004 update to the American Association of Physicists in Medicine (AAPM) Task Group No. 43 Report (TG-43U1) and its 2007 supplement (TG-43U1S1), several new low-energy photon-emitting brachytherapy sources have become available. Many of these sources have satisfied the AAPM prerequisites for routine clinical purposes and are posted on the Brachytherapy Source Registry managed jointly by the AAPM and the Imaging and Radiation Oncology Core Houston Quality Assurance Center (IROC Houston). Given increasingly closer interactions among physicists in North America and Europe, the AAPM and the Groupe Européen de Curiethérapie-European Society for Radiotherapy & Oncology (GEC-ESTRO) have prepared another supplement containing recommended brachytherapy dosimetry parameters for eleven low-energy photon-emitting brachytherapy sources. ⋯ The recent literature is examined on photon energy response corrections for thermoluminescent dosimetry of low-energy photon-emitting brachytherapy sources. Depending upon the dosimetry parameters currently used by individual physicists, use of these recommended consensus datasets may result in changes to patient dose calculations. These changes must be carefully evaluated and reviewed with the radiation oncologist prior to their implementation.
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Performance of the preconditioned alternating projection algorithm (PAPA) using relaxed ordered subsets (ROS) with a non-smooth penalty function was investigated in positron emission tomography (PET). A higher order total variation (HOTV) regularizer was applied and a method for unsupervised selection of penalty weights based on the measured data is introduced. ⋯ Acceleration of HOTV-PAPA was achieved using ROS. This was accompanied by an improved RMSE metric and perceptual image quality that were both superior to that obtained with either clinical or optimized OSEM. This may allow up to a four-fold reduction of the radiation dose to the patients in a PET study, as compared with current clinical practice. The proposed unsupervised parameter selection method provided useful estimates of the penalty weights for the selected phantoms' and patients' PET studies. In sum, the outcomes of this research indicate that ROS-HOTV-PAPA is an appropriate candidate for clinical applications and warrants further research.
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To evaluate a method for measuring breast density using photon-counting spectral mammography. Breast density is an indicator of breast cancer risk and diagnostic accuracy in mammography, and can be used as input to personalized screening, treatment monitoring and dose estimation. ⋯ The spectral method yielded reasonable results in a screening population with a precision approximately two times that of the nonspectral method, which may improve or enable applications of breast-density measurement on an individual basis such as treatment monitoring and personalized screening.
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The growing use of magnetic resonance imaging (MRI) as a substitute for computed tomography-based treatment planning requires the development of effective algorithms to generate electron density maps for treatment planning and patient setup verification. The purpose of this work was to develop a method to synthesize computerized tomography (CT) for MR-only radiotherapy of head and neck cancer patients. ⋯ We developed a novel image analysis technique to synthesize CT for head and neck anatomy. Novel methods were introduced to accurately register atlas CTs and MRIs as well as to weight the final electron density maps using local registration goodness estimates. The resulting accuracy is clinically acceptable, at least for these atlas patients.
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To evaluate and compare the theoretically achievable accuracy of two families of two-parameter photon cross-section models: basis vector model (BVM) and modified parametric fit model (mPFM). ⋯ Compared to modified PFMs, BVM shows superior potential to support dual-energy CT cross-section mapping. In addition, the linear, separable BVM can be more efficiently deployed by iterative model-based DECT image-reconstruction algorithms.