Med Phys
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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.
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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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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 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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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.