Physics in medicine and biology
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3D segmentation of annulus fibrosus and nucleus pulposus from T2-weighted magnetic resonance images.
Computational medicine aims at employing personalised computational models in diagnosis and treatment planning. The use of such models to help physicians in finding the best treatment for low back pain (LBP) is becoming popular. One of the challenges of creating such models is to derive patient-specific anatomical and tissue models of the lumbar intervertebral discs (IVDs), as a prior step. ⋯ The images follow a standard T2-weighted protocol in coronal and sagittal acquisitions. These two image volumes were fused in order to overcome large inter-slice spacing. The agreement between expert-delineated structures, used here as gold-standard, and our automatic segmentation was evaluated using Dice Similarity Index and surface-to-surface distances, obtaining a mean error of 0.68 mm in the annulus segmentation and 1.88 mm in the nucleus, which are the best results with respect to the image resolution in the current literature.
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Proton therapy treatments are based on a proton RBE (relative biological effectiveness) relative to high-energy photons of 1.1. The use of this generic, spatially invariant RBE within tumors and normal tissues disregards the evidence that proton RBE varies with linear energy transfer (LET), physiological and biological factors, and clinical endpoint. Based on the available experimental data from published literature, this review analyzes relationships of RBE with dose, biological endpoint and physical properties of proton beams. ⋯ In most cases the RBE also increases with decreasing dose, specifically for systems with low (α/β)x. Data on RBE for endpoints other than clonogenic cell survival are too diverse to allow general statements other than that the RBE is, on average, in line with a value of ~1.1. This review can serve as a source for defining input parameters for applying or refining biophysical models and to identify endpoints where additional radiobiological data are needed in order to reduce the uncertainties to clinically acceptable levels.
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An algorithm for intensity-based 3D-2D registration of CT and C-arm fluoroscopy is evaluated for use in surgical guidance, specifically considering the low-dose limits of the fluoroscopic x-ray projections. The registration method is based on a framework using the covariance matrix adaptation evolution strategy (CMA-ES) to identify the 3D patient pose that maximizes the gradient information similarity metric. ⋯ In each case, registration accuracy was evaluated as a function of the entrance surface dose associated with the projection view(s). Results indicate that images acquired at a dose as low as 4 μGy (approximately one-tenth the dose of a typical fluoroscopic frame) were sufficient to provide TRE comparable or superior to that of conventional surgical tracking, allowing 3D-2D guidance at a level of dose that is at most 10% greater than conventional fluoroscopy (scenario #2) and potentially reducing the dose to approximately 20% of the level in a conventional fluoroscopically guided procedure (scenario #3).
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Advanced tumors are often inoperable due to their size and proximity to critical vascular structures. High intensity focused ultrasound (HIFU) has been developed to non-invasively thermally ablate inoperable solid tumors. However, the clinical feasibility of HIFU ablation therapy has been limited by the long treatment times (on the order of hours) and high acoustic intensities required. ⋯ For example, the mean per cent change in temperature achieved at 5.2 W of acoustic power was 46 ± 22% with PSNE injection. The results indicate that PSNE nucleates cavitation which correlates with enhanced HIFU-mediated heating in tumors. This suggests that PSNE could potentially be used to reduce the time and/or acoustic intensity required for HIFU-mediated heating, thereby increasing the feasibility and clinical efficacy of HIFU thermal ablation therapy.
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The aim of this paper is to describe a new automatic method for compensation of metal-implant-induced segmentation errors in MR-based attenuation maps (MRMaps) and to evaluate the quantitative influence of those artifacts on the reconstructed PET activity concentration. The developed method uses a PET-based delineation of the patient contour to compensate metal-implant-caused signal voids in the MR scan that is segmented for PET attenuation correction. PET emission data of 13 patients with metal implants examined in a Philips Ingenuity PET/MR were reconstructed with the vendor-provided method for attenuation correction (MRMap(orig), PET(orig)) and additionally with a method for attenuation correction (MRMap(cor), PET(cor)) developed by our group. ⋯ MRMap(cor) only showed small residual segmentation errors in eight patients. ε(rel)(av) (mean ± standard deviation) were: (-56 ± 3)% for B1, (-43 ± 4)% for B2, (21 ± 18)% for L1, (120 ± 47)% for L2 regions. ε(rel) (mean ± standard deviation) of hot focal structures were: (-52 ± 12)% in B1, (-45 ± 13)% in B2, (19 ± 19)% in L1, (51 ± 31)% in L2 regions. Consequently, metal-implant-induced artifacts severely disturb MR-based attenuation correction and SUV quantification in PET/MR. The developed algorithm is able to compensate for these artifacts and improves SUV quantification accuracy distinctly.