Twelve high schools in Japan (of which six are in Fukushima Prefecture), four in France, eight in Poland and two in Belarus cooperated in the measurement and comparison of individual external doses in 2014. In total 216 high-school students and teachers participated in the study. Each participant wore an electronic personal dosimeter D-shuttle for two weeks, and kept a journal of his/her whereabouts and activities. The distributions of annual external doses estimated for each region overlap with each other, demonstrating that the personal external individual doses in locations where residence is currently allowed in Fukushima Prefecture and in Belarus are well within the range of estimated annual doses due to the background radiation level of other regions/countries.
There is a growing need for biolabels that can be used in both optical and electron microscopies, are non-cytotoxic, and do not photobleach. Such biolabels could enable targeted nanoscale imaging of sub-cellular structures, and help to establish correlations between conjugation-delivered biomolecules and function. Here we demonstrate a subcellular multi-modal imaging methodology that enables localization of inert particulate probes, consisting of nanodiamonds having fluorescent nitrogen-vacancy centers. These are functionalized to target specific structures, and are observable by both optical and electron microscopies. Nanodiamonds targeted to the nuclear pore complex are rapidly localized in electron-microscopy diffraction mode to enable zooming-in to regions of interest for detailed structural investigations. Optical microscopies reveal nanodiamonds for in-vitro tracking or uptake-confirmation. The approach is general, works down to the single nanodiamond level, and can leverage the unique capabilities of nanodiamonds, such as biocompatibility, sensitive magnetometry, and gene and drug delivery.
Despite the spectacular achievements of molecular biology in the second half of the twentieth century and the crucial advances it permitted in cancer research, the fight against cancer has brought some disillusions. It is nowadays more and more apparent that getting a global picture of the very diverse and interlinked aspects of cancer development necessitates, in synergy with these achievements, other perspectives and investigating tools. In this undertaking, multidisciplinary approaches that include quantitative sciences in general and physics in particular play a crucial role. This `focus on collection contains 19 articles representative of the diversity and state-of-the-art of the contributions that physics can bring to the field of cancer research.
Source localization in EEG represents a high dimensional inverse problem, which is severely ill-posed by nature. Fortunately, sparsity constraints have come into rescue as it helps solving the ill-posed problems when the signal is sparse. When the signal has a structure such as block structure, consideration of block sparsity produces better results. Knowing sparse Bayesian learning is an important member in the family of sparse recovery, and a superior choice when the projection matrix is highly coherent (which is typical the case for EEG), in this work we evaluate the performance of block sparse Bayesian learning (BSBL) method for EEG source localization. It is already accepted by the EEG community that a group of dipoles rather than a single dipole are activated during brain activities; thus, block structure is a reasonable choice for EEG. In this work we use two definitions of blocks: Brodmann areas and automated anatomical labelling (AAL), and analyze the reconstruction performance of BSBL methodology for them. A realistic head model is used for the experiment, which was obtained from segmentation of MRI images. When the number of simultaneously active blocks is 2, the BSBL produces overall localization accuracy of less than 5 mm without the presence of noise. The presence of more than 3 simultaneously active blocks and noise significantly affect the localization performance. Consideration of AAL based blocks results more accurate source localization in comparison to Brodmann area based blocks.
To compare the dosimetrical differences between plans generated by helical tomotherapy using 2D or 3D margining technique in in prostate cancer. Ten prostate cancer patients were included in this study. For 2D plans, planning target volume (PTV) was created by adding 5 mm (lateral/anterior-posterior) to clinical target volume (CTV). For 3D plans, 5 mm margin was added not only in lateral/anterior-posterior, but also in superior-inferior to CTV. Various dosimetrical indices, including the prescription isodose to target volume (PITV) ratio, conformity index (CI), homogeneity index (HI), target coverage index (TCI), modified dose homogeneity index (MHI), conformation number (CN), critical organ scoring index (COSI), and quality factor (QF) were determined to compare the different treatment plans. Differences between 2D and 3D PTV indices were not significant except for CI (p = 0.023). 3D margin plans (11195 MUs) resulted in higher (13.0%) monitor units than 2D margin plans (9728 MUs). There were no significant differences in any OARs between the 2D and 3D plans. Overall, the average 2D plan dose was slightly lower than the 3D plan dose. Compared to the 2D plan, the 3D plan increased average treatment time by 1.5 minutes; however, this difference was not statistically significant (p = 0.082). We confirmed that 2D and 3D margin plans are not significantly different with regard to various dosimetric indices such as PITV, CI, and HI for PTV, and OARs with tomotherapy.
A three-dimensional unilateral contact problem for articular cartilage layers attached to subchondral bones shaped as elliptic paraboloids is considered in the framework of the biphasic cartilage model. The main novelty of the study is in accounting not only for the normal (vertical), but also for tangential vertical (horisontal) displacements of the contacting surfaces. Exact general relationships have been established between the contact approach and some integral characteristics of the contact pressure, including the contact force. Asymptotic representations for the contact pressure integral characteristics are obtained in terms of the contact approach and some integral characteristics of the contact zone. The main result is represented by the first-order approximation problem.
We recently built an analytical source model for GPU-based MC dose engine. In this paper, we present a sampling strategy to efficiently utilize this source model in GPU-based dose calculation. Our source model was based on a concept of phase-space-ring (PSR). This ring structure makes it effective to account for beam rotational symmetry, but not suitable for dose calculations due to rectangular jaw settings. Hence, we first convert PSR source model to its phase-space let (PSL) representation. Then in dose calculation, different types of sub-sources were separately sampled. Source sampling and particle transport were iterated. So that the particles being sampled and transported simultaneously are of same type and close in energy to alleviate GPU thread divergence. We also present an automatic commissioning approach to adjust the model for a good representation of a clinical linear accelerator . Weighting factors were introduced to adjust relative weights of PSRs, determined by solving a quadratic minimization problem with a non-negativity constraint. We tested the efficiency gain of our model over a previous source model using PSL files. The efficiency was improved by 1.70 ~ 4.41, due to the avoidance of long data reading and transferring. The commissioning problem can be solved in ~20 sec. Its efficacy was tested by comparing the doses computed using the commissioned model and the uncommissioned one, with measurements in different open fields in a water phantom under a clinical Varian Truebeam 6MV beam. For the depth dose curves, the average distance-to-agreement was improved from 0.04~0.28 cm to 0.04~0.12 cm for build-up region and the root-mean-square (RMS) dose difference after build-up region was reduced from 0.32%~0.67% to 0.21%~0.48%. For lateral dose profiles, RMS difference was reduced from 0.31%~2.0% to 0.06%~0.78% at inner beam and from 0.20%~1.25% to 0.10%~0.51% at outer beam.
Monte Carlo (MC) simulation is considered as the most accurate method for radiation dose calculations. Accuracy of a source model for a linear accelerator is critical for the overall dose calculation accuracy. In this paper, we presented an analytical source model that we recently developed for GPU-based MC dose calculations. A key concept called phase-space-ring (PSR) was proposed. It contained a group of particles that are of the same type and close in energy and radial distance to the center of the phase-space plane. The model parameterized probability densities of particle location, direction and energy for each primary photon PSR, scattered photon PSR and electron PSR. For a primary photon PSRs, the particle direction is assumed to be from the beam spot. A finite spot size is modeled with a 2D Gaussian distribution. For a scattered photon PSR, multiple Gaussian components were used to model the particle direction. The direction distribution of an electron PSRs was also modeled as a 2D Gaussian distribution with a large standard deviation. We also developed a method to analyze a phase-space file and derive corresponding model parameters. To test the accuracy of our linac source model, dose distributions of different open fields in a water phantom were calculated using our source model and compared to those directly calculated using the reference phase-space file. The average distance-to-agreement (DTA) was within 1 mm for the depth dose in the build-up region and beam penumbra regions. The root-mean-square (RMS) dose difference was within 1.1% for dose profiles at inner and outer beam regions. The maximal relative difference of output factors was within 0.5%. Good agreements were also found in an IMRT prostate patient case and an IMRT head-and-neck case. These results demonstrated the efficacy of our source model in terms of accurately representing a reference phase-space file.
Monte Carlo (MC) method has been recognized the most accurate dose calculation method for radiotherapy. However, its extremely long computation time impedes clinical applications. Recently, a lot of efforts have been made to realize fast MC dose calculation on GPUs. Nonetheless, most of the GPU-based MC dose engines were developed in NVidia CUDA environment. This limits the code portability to other platforms, hindering the introduction of GPU-based MC simulations to clinical practice. The objective of this paper is to develop a fast cross-platform MC dose engine oclMC using OpenCL environment for external beam photon and electron radiotherapy in MeV energy range. Coupled photon-electron MC simulation was implemented with analogue simulations for photon transports and a Class II condensed history scheme for electron transports. To test the accuracy and efficiency of our dose engine oclMC, we compared dose calculation results of oclMC and gDPM, our previously developed GPU-based MC code, for a 15 MeV electron beam and a 6 MV photon beam on a homogenous water phantom, one slab phantom and one half-slab phantom. Satisfactory agreement was observed in all the cases. The average dose differences within 10% isodose line of the maximum dose were 0.48-0.53% for the electron beam cases and 0.15-0.17% for the photon beam cases. In terms of efficiency, our dose engine oclMC was 6-17% slower than gDPM when running both codes on the same NVidia TITAN card due to both different physics particle transport models and different computational environments between CUDA and OpenCL. The cross-platform portability was also validated by successfully running our new dose engine on a set of different compute devices including an Nvidia GPU card, two AMD GPU cards and an Intel CPU card using one or four cores. Computational efficiency among these platforms was compared.
Radiotherapy is often the most straightforward first line cancer treatment for solid tumors. While it is highly effective against tumors, there is also collateral damage to healthy proximal tissues especially with high doses. The use of radiosensitizers is an effective way to boost the killing efficacy of radiotherapy against the tumor while drastically limiting the received dose and reducing the possible damage to normal tissues. Here, we report the design and application of a good radiosensitizer by using ultrasmall gold nanoclusters with a naturally occurring peptide (e.g., glutathione or GSH) as the protecting shell. The GSH coated gold nanoclusters can escape the RES absorption, leading to a good tumor uptake (8.1% ID/g at 24 h post injection). As a result, the as-designed Au nanoclusters led to a strong enhancement for radiotherapy, as well as a negligible damage to normal tissues. After the treatment, the ultrasmall gold nanoclusters can be efficiently cleared by the kidney, thereby avoiding potential long term side effects caused by the accumulation of gold atoms in the body. Our data suggest that the ultrasmall peptide protected Au nanoclusters are a promising radiosensitizer for cancer radiotherapy.
