Physics in medicine and biology
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Diffusion-weighted magnetic resonance imaging is a key investigation technique in modern neuroscience. In clinical settings, diffusion-weighted imaging and its extension to diffusion tensor imaging (DTI) are usually performed applying the technique of echo-planar imaging (EPI). EPI is the commonly available ultrafast acquisition technique for single-shot acquisition with spatial encoding in a Cartesian system. ⋯ We show that, after correction, fusion with T1- or T2-weighted images can be obtained by a simple rigid registration. Furthermore, we demonstrate the improvement due to the novel regularization scheme. Most importantly, we show that it provides meaningful, i.e. diffeomorphic, geometric transformations, independent of the actual choice of the regularization parameters.
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Surgical targeting of the incorrect vertebral level (wrong-level surgery) is among the more common wrong-site surgical errors, attributed primarily to the lack of uniquely identifiable radiographic landmarks in the mid-thoracic spine. The conventional localization method involves manual counting of vertebral bodies under fluoroscopy, is prone to human error and carries additional time and dose. We propose an image registration and visualization system (referred to as LevelCheck), for decision support in spine surgery by automatically labeling vertebral levels in fluoroscopy using a GPU-accelerated, intensity-based 3D-2D (namely CT-to-fluoroscopy) registration. ⋯ Physical experiments demonstrated the robustness of the algorithm against quantum noise and x-ray scatter. The ability to automatically localize target anatomy in fluoroscopy in near-real-time could be valuable in reducing the occurrence of wrong-site surgery while helping to reduce radiation exposure. The method is applicable beyond the specific case of vertebral labeling, since any structure defined in pre-operative (or intra-operative) CT or cone-beam CT can be automatically registered to the fluoroscopic scene.
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In a recent paper, we have published a new algorithm, designated 'iCycle', for fully automated multi-criterial optimization of beam angles and intensity profiles. In this study, we have used this algorithm to investigate the relationship between plan quality and the extent of the beam direction search space, i.e. the set of candidate beam directions that may be selected for generating an optimal plan. For a group of ten prostate cancer patients, optimal IMRT plans were made for stereotactic body radiation therapy (SBRT), mimicking high dose rate brachytherapy dosimetry. ⋯ Addition of posterior beams (CK(++) → F-NCP) did not lead to further improvements in OAR sparing. Plans with 25 beams clearly performed better than 11-beam plans. For CP plans, an increase from 11 to 25 involved beams resulted in reductions in rectum D(Mean), V(40Gy), V(60Gy) and D(2%) of 39%, 57%, 64% and 13%, respectively.