Prediction of residential radon exposure of the whole Swiss population: comparison of model-based predictions with measurement-based predictions

Radon plays an important role for human exposure to natural sources of ionizing radiation. The aim of this article is to compare two approaches to estimate mean radon exposure in the Swiss population: model-based predictions at individual level and measurement-based predictions based on measurements aggregated at municipality level. A nationwide model was used to predict radon levels in each household and for each individual based on the corresponding tectonic unit, building age, building type, soil texture, degree of urbanization, and floor. Measurement-based predictions were carried out within a health impact assessment on residential radon and lung cancer. Mean measured radon levels were corrected for the average floor distribution and weighted with population size of each municipality. Model-based predictions yielded a mean radon exposure of the Swiss population of 84.1 Bq/m(3) . Measurement-based predictions yielded an average exposure of 78 Bq/m(3) . This study demonstrates that the model- and the measurement-based predictions provided similar results. The advantage of the measurement-based approach is its simplicity, which is sufficient for assessing exposure distribution in a population. The model-based approach allows predicting radon levels at specific sites, which is needed in an epidemiological study, and the results do not depend on how the measurement sites have been selected.

ANOVA kernels and RKHS of zero mean functions for model-based sensitivity analysis

Given a reproducing kernel Hilbert space (H,〈.,.〉)(H,〈.,.〉) of real-valued functions and a suitable measure μμ over the source space D⊂RD⊂R, we decompose HH as the sum of a subspace of centered functions for μμ and its orthogonal in HH. This decomposition leads to a special case of ANOVA kernels, for which the functional ANOVA representation of the best predictor can be elegantly derived, either in an interpolation or regularization framework. The proposed kernels appear to be particularly convenient for analyzing the effect of each (group of) variable(s) and computing sensitivity indices without recursivity.

Statistical model-based segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs.

PURPOSE    Segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs is required to create a three-dimensional model of the hip joint for use in planning and treatment. However, manually extracting the femoral contour is tedious and prone to subjective bias, while automatic segmentation must accommodate poor image quality, anatomical structure overlap, and femur deformity. A new method was developed for femur segmentation in AP pelvic radiographs. METHODS    Using manual annotations on 100 AP pelvic radiographs, a statistical shape model (SSM) and a statistical appearance model (SAM) of the femur contour were constructed. The SSM and SAM were used to segment new AP pelvic radiographs with a three-stage approach. At initialization, the mean SSM model is coarsely registered to the femur in the AP radiograph through a scaled rigid registration. Mahalanobis distance defined on the SAM is employed as the search criteria for each annotated suggested landmark location. Dynamic programming was used to eliminate ambiguities. After all landmarks are assigned, a regularized non-rigid registration method deforms the current mean shape of SSM to produce a new segmentation of proximal femur. The second and third stages are iteratively executed to convergence. RESULTS    A set of 100 clinical AP pelvic radiographs (not used for training) were evaluated. The mean segmentation error was [Formula: see text], requiring [Formula: see text] s per case when implemented with Matlab. The influence of the initialization on segmentation results was tested by six clinicians, demonstrating no significance difference. CONCLUSIONS    A fast, robust and accurate method for femur segmentation in digital AP pelvic radiographs was developed by combining SSM and SAM with dynamic programming. This method can be extended to segmentation of other bony structures such as the pelvis.

True four-dimensional analysis of thoracic aortic displacement and distension using model-based segmentation of computed tomography angiography.

Previous analyses of aortic displacement and distension using computed tomography angiography (CTA) were performed on double-oblique multi-planar reformations and did not consider through-plane motion. The aim of this study was to overcome this limitation by using a novel computational approach for the assessment of thoracic aortic displacement and distension in their true four-dimensional extent. Vessel segmentation with landmark tracking was executed on CTA of 24 patients without evidence of aortic disease. Distension magnitudes and maximum displacement vectors (MDV) including their direction were analyzed at 5 aortic locations: left coronary artery (COR), mid-ascending aorta (ASC), brachiocephalic trunk (BCT), left subclavian artery (LSA), descending aorta (DES). Distension was highest for COR (2.3 ± 1.2 mm) and BCT (1.7 ± 1.1 mm) compared with ASC, LSA, and DES (p < 0.005). MDV decreased from COR to LSA (p < 0.005) and was highest for COR (6.2 ± 2.0 mm) and ASC (3.8 ± 1.9 mm). Displacement was directed towards left and anterior at COR and ASC. Craniocaudal displacement at COR and ASC was 1.3 ± 0.8 and 0.3 ± 0.3 mm. At BCT, LSA, and DES no predominant displacement direction was observable. Vessel displacement and wall distension are highest in the ascending aorta, and ascending aortic displacement is primarily directed towards left and anterior. Craniocaudal displacement remains low even close to the left cardiac ventricle.

Model-Based Estimates of Calanus Finmarchicus Abundance in the Gulf of Maine

Ocean observing systems and satellites routinely collect a wealth of information on physical conditions in the ocean. With few exceptions, such as chlorophyll concentrations, information on biological properties is harder to measure autonomously. Here, we present a system to produce estimates of the distribution and abundance of the copepod Calanus finmarchicus in the Gulf of Maine. Our system uses satellite-based measurements of sea surface temperature and chlorophyll concentration to determine the developmental and reproductive rates of C. finmarchicus. The rate information then drives a population dynamics model of C. finmarchicus that is embedded in a 2-dimensional circulation field. The first generation of this system produces realistic information on interannual variability in C. finmarchicus distribution and abundance during the winter and spring. The model can also be used to identify key drivers of interannual variability in C. finmarchicus. Experiments with the model suggest that changes in initial conditions are overwhelmed by variability in growth rates after approximately 50 d. Temperature has the largest effect on growth rate. Elevated chlorophyll during the late winter can lead to increased C. finmarchicus abundance during the spring, but the effect of variations in chlorophyll concentrations is secondary to the other inputs. Our system could be used to provide real-time estimates or even forecasts of C. finmarchicus distribution. These estimates could then be used to support management of copepod predators such as herring and right whales.

Model-Based Estimates of Right Whale Habitat Use in the Gulf of Maine

Balancing human uses of the marine environment with the recovery of protected species requires accurate information on when and where species of interest are likely to be present. Here, we describe a system that can produce useful estimates of right whale Eubalaena glacialis presence and abundance on their feeding grounds in the Gulf of Maine. The foundation of our system is a coupled physical-biological model of the copepod Calan us finmarchicus, the preferred prey of right whales. From the modeled prey densities, we can estimate when whales will appear in the Great South Channel feeding ground. Based on our experience with the system, we consider how the relationship between right whales and copepods changes across spatial scales. The scale-dependent relationship between whales and copepods provides insight into how to improve future estimates of the distribution of right whales and other pelagic predators.

Graphical Model-Based Vertebra Identification from X-Ray Image(s)

Automated identification of vertebrae from X-ray image(s) is an important step for various medical image computing tasks such as 2D/3D rigid and non-rigid registration. In this chapter we present a graphical model-based solution for automated vertebra identification from X-ray image(s). Our solution does not ask for a training process using training data and has the capability to automatically determine the number of vertebrae visible in the image(s). This is achieved by combining a graphical model-based maximum a posterior probability (MAP) estimate with a mean-shift based clustering. Experiments conducted on simulated X-ray images as well as on a low-dose low quality X-ray spinal image of a scoliotic patient verified its performance.

Articulated Statistical Shape Model-Based 2D-3D Reconstruction of a Hip Joint

In this paper, reconstruction of three-dimensional (3D) patient-specific models of a hip joint from two-dimensional (2D) calibrated X-ray images is addressed. Existing 2D-3D reconstruction techniques usually reconstruct a patient-specific model of a single anatomical structure without considering the relationship to its neighboring structures. Thus, when those techniques would be applied to reconstruction of patient-specific models of a hip joint, the reconstructed models may penetrate each other due to narrowness of the hip joint space and hence do not represent a true hip joint of the patient. To address this problem we propose a novel 2D-3D reconstruction framework using an articulated statistical shape model (aSSM). Different from previous work on constructing an aSSM, where the joint posture is modeled as articulation in a training set via statistical analysis, here it is modeled as a parametrized rotation of the femur around the joint center. The exact rotation of the hip joint as well as the patient-specific models of the joint structures, i.e., the proximal femur and the pelvis, are then estimated by optimally fitting the aSSM to a limited number of calibrated X-ray images. Taking models segmented from CT data as the ground truth, we conducted validation experiments on both plastic and cadaveric bones. Qualitatively, the experimental results demonstrated that the proposed 2D-3D reconstruction framework preserved the hip joint structure and no model penetration was found. Quantitatively, average reconstruction errors of 1.9 mm and 1.1 mm were found for the pelvis and the proximal femur, respectively.

Experimental validation of a nonlinear μ FE model based on cohesive-frictional plasticity for trabecular bone

Trabecular bone is a porous mineralized tissue playing a major load bearing role in the human body. Prediction of age-related and disease-related fractures and the behavior of bone implant systems needs a thorough understanding of its structure-mechanical property relationships, which can be obtained using microcomputed tomography-based finite element modeling. In this study, a nonlinear model for trabecular bone as a cohesive-frictional material was implemented in a large-scale computational framework and validated by comparison of μFE simulations with experimental tests in uniaxial tension and compression. A good correspondence of stiffness and yield points between simulations and experiments was found for a wide range of bone volume fraction and degree of anisotropy in both tension and compression using a non-calibrated, average set of material parameters. These results demonstrate the ability of the model to capture the effects leading to failure of bone for three anatomical sites and several donors, which may be used to determine the apparent behavior of trabecular bone and its evolution with age, disease, and treatment in the future.

Model-based changes in global annual mean surface temperature change (Delta T_g) and radiative forcing due to land ice albedo changes (Delta R_[LI]) over the last 5 Myr, supplementary material

It is still an open question how equilibrium warming in response to increasing radiative forcing - the specific equilibrium climate sensitivity S - depends on background climate. We here present palaeodata-based evidence on the state dependency of S, by using CO2 proxy data together with a 3-D ice-sheet-model-based reconstruction of land ice albedo over the last 5 million years (Myr). We find that the land ice albedo forcing depends non-linearly on the background climate, while any non-linearity of CO2 radiative forcing depends on the CO2 data set used. This non-linearity has not, so far, been accounted for in similar approaches due to previously more simplistic approximations, in which land ice albedo radiative forcing was a linear function of sea level change. The latitudinal dependency of ice-sheet area changes is important for the non-linearity between land ice albedo and sea level. In our set-up, in which the radiative forcing of CO2 and of the land ice albedo (LI) is combined, we find a state dependence in the calculated specific equilibrium climate sensitivity, S[CO2,LI], for most of the Pleistocene (last 2.1 Myr). During Pleistocene intermediate glaciated climates and interglacial periods, S[CO2,LI] is on average ~ 45 % larger than during Pleistocene full glacial conditions. In the Pliocene part of our analysis (2.6-5 Myr BP) the CO2 data uncertainties prevent a well-supported calculation for S[CO2,LI], but our analysis suggests that during times without a large land ice area in the Northern Hemisphere (e.g. before 2.82 Myr BP), the specific equilibrium climate sensitivity, S[CO2,LI], was smaller than during interglacials of the Pleistocene. We thus find support for a previously proposed state change in the climate system with the widespread appearance of northern hemispheric ice sheets. This study points for the first time to a so far overlooked non-linearity in the land ice albedo radiative forcing, which is important for similar palaeodata-based approaches to calculate climate sensitivity. However, the implications of this study for a suggested warming under CO2 doubling are not yet entirely clear since the details of necessary corrections for other slow feedbacks are not fully known and the uncertainties that exist in the ice-sheet simulations and global temperature reconstructions are large.

Gotland Deep (Baltic Sea) independent age model based on Palaeomagnetic Secular Variation (PSV) and lead (Pb) deposition profiles

Dating of sediment cores from the Baltic Sea has proven to be difficult due to uncertainties surrounding the 14C reservoir age and a scarcity of macrofossils suitable for dating. Here we present the results of multiple dating methods carried out on cores in the Gotland Deep area of the Baltic Sea. Particular emphasis is placed on the Littorina stage (8 ka ago to the present) of the Baltic Sea and possible changes in the 14C reservoir age of our dated samples. Three geochronological methods are used. Firstly, palaeomagnetic secular variations (PSV) are reconstructed, whereby ages are transferred to PSV features through comparison with varved lake sediment based PSV records. Secondly, lead (Pb) content and stable isotope analysis are used to identify past peaks in anthropogenic atmospheric Pb pollution. Lastly, 14C determinations were carried out on benthic foraminifera (Elphidium spec.) samples from the brackish Littorina stage of the Baltic Sea. Determinations carried out on smaller samples (as low as 4 µg C) employed an experimental, state-of-the-art method involving the direct measurement of CO2 from samples by a gas ion source without the need for a graphitisation step - the first time this method has been performed on foraminifera in an applied study. The PSV chronology, based on the uppermost Littorina stage sediments, produced ten age constraints between 6.29 and 1.29 cal ka BP, and the Pb depositional analysis produced two age constraints associated with the Medieval pollution peak. Analysis of PSV data shows that adequate directional data can be derived from both the present Littorina saline phase muds and Baltic Ice Lake stage varved glacial sediments. Ferrimagnetic iron sulphides, most likely authigenic greigite (Fe3S4), present in the intermediate Ancylus Lake freshwater stage sediments acquire a gyroremanent magnetisation during static alternating field (AF) demagnetisation, preventing the identification of a primary natural remanent magnetisation for these sediments. An inferred marine reservoir age offset (deltaR) is calculated by comparing the foraminifera 14C determinations to a PSV & Pb age model. This deltaR is found to trend towards younger values upwards in the core, possibly due to a gradual change in hydrographic conditions brought about by a reduction in marine water exchange from the open sea due to continued isostatic rebound.