Biomechanical Role of Bone Anisotropy Estimated on Clinical CT Scans by Image Registration

Image-based modeling is a popular approach to perform patient-specific biomechanical simulations. Accurate modeling is critical for orthopedic application to evaluate implant design and surgical planning. It has been shown that bone strength can be estimated from the bone mineral density (BMD) and trabecular bone architecture. However, these findings cannot be directly and fully transferred to patient-specific modeling since only BMD can be derived from clinical CT. Therefore, the objective of this study was to propose a method to predict the trabecular bone structure using a µCT atlas and an image registration technique. The approach has been evaluated on femurs and patellae under physiological loading. The displacement and ultimate force for femurs loaded in stance position were predicted with an error of 2.5% and 3.7%, respectively, while predictions obtained with an isotropic material resulted in errors of 7.3% and 6.9%. Similar results were obtained for the patella, where the strain predicted using the registration approach resulted in an improved mean squared error compared to the isotropic model. We conclude that the registration of anisotropic information from of a single template bone enables more accurate patient-specific simulations from clinical image datasets than isotropic model.

Diffusion tensor imaging of the human kidney: Does image registration permit scanning without respiratory triggering?

PURPOSE To investigate if image registration of diffusion tensor imaging (DTI) allows omitting respiratory triggering for both transplanted and native kidneys MATERIALS AND METHODS: Nine kidney transplant recipients and eight healthy volunteers underwent renal DTI on a 3T scanner with and without respiratory triggering. DTI images were registered using a multimodal nonrigid registration algorithm. Apparent diffusion coefficient (ADC), the contribution of perfusion (FP ), and the fractional anisotropy (FA) were determined. Relative root mean square errors (RMSE) of the fitting and the standard deviations of the derived parameters within the regions of interest (SDROI ) were evaluated as quality criteria. RESULTS Registration significantly reduced RMSE in all DTI-derived parameters of triggered and nontriggered measurements in cortex and medulla of both transplanted and native kidneys (P < 0.05 for all). In addition, SDROI values were lower with registration for all 16 parameters in transplanted kidneys (14 of 16 SDROI values were significantly reduced, P < 0.04) and for 15 of 16 parameters in native kidneys (9 of 16 SDROI values were significantly reduced, P < 0.05). Comparing triggered versus nontriggered DTI in transplanted kidneys revealed no significant difference for RMSE (P > 0.14) and for SDROI (P > 0.13) of all parameters. In contrast, in native kidneys relative RMSE from triggered scans were significantly lower than those from nontriggered scans (P < 0.02), while SDROI was slightly higher in triggered compared to nontriggered measurements in 15 out of 16 comparisons (significantly for two, P < 0.05). CONCLUSION Registration improves the quality of DTI in native and transplanted kidneys. Diffusion parameters in renal allografts can be measured without respiratory triggering. In native kidneys, respiratory triggering appears advantageous. J. Magn. Reson. Imaging 2016.

Natural History of Geographic Atrophy Progression Secondary to Age-Related Macular Degeneration (Geographic Atrophy Progression Study).

PURPOSE The Geographic Atrophy Progression (GAP) study was designed to assess the rate of geographic atrophy (GA) progression and to identify prognostic factors by measuring the enlargement of the atrophic lesions using fundus autofluorescence (FAF) and color fundus photography (CFP). DESIGN Prospective, multicenter, noninterventional natural history study. PARTICIPANTS A total of 603 participants were enrolled in the study; 413 of those had gradable lesion data from FAF or CFP, and 321 had gradable lesion data from both FAF and CFP. METHODS Atrophic lesion areas were measured by FAF and CFP to assess lesion progression over time. Lesion size assessments and best-corrected visual acuity (BCVA) were conducted at screening/baseline (day 0) and at 3 follow-up visits: month 6, month 12, and month 18 (or early exit). MAIN OUTCOME MEASURES The GA lesion progression rate in disease subgroups and mean change from baseline visual acuity. RESULTS Mean (standard error) lesion size changes from baseline, determined by FAF and CFP, respectively, were 0.88 (0.1) and 0.78 (0.1) mm(2) at 6 months, 1.85 (0.1) and 1.57 (0.1) mm(2) at 12 months, and 3.14 (0.4) and 3.17 (0.5) mm(2) at 18 months. The mean change in lesion size from baseline to month 12 was significantly greater in participants who had eyes with multifocal atrophic spots compared with those with unifocal spots (P < 0.001) and those with extrafoveal lesions compared with those with foveal lesions (P = 0.001). The mean (standard deviation) decrease in visual acuity was 6.2 ± 15.6 letters for patients with image data available. Atrophic lesions with a diffuse (mean 0.95 mm(2)) or banded (mean 1.01 mm(2)) FAF pattern grew more rapidly by month 6 compared with those with the "none" (mean, 0.13 mm(2)) and focal (mean, 0.36 mm(2)) FAF patterns. CONCLUSIONS Although differences were observed in mean lesion size measurements using FAF imaging compared with CFP, the measurements were highly correlated with one another. Significant differences were found in lesion progression rates in participants stratified by hyperfluorescence pattern subtype. This large GA natural history study provides a strong foundation for future clinical trials.

Bufferless Compression of Asynchronously Sampled ECG Signals in Cubic Hermitian Vector Space.

Asynchronous level crossing sampling analog-to-digital converters (ADCs) are known to be more energy efficient and produce fewer samples than their equidistantly sampling counterparts. However, as the required threshold voltage is lowered, the number of samples and, in turn, the data rate and the energy consumed by the overall system increases. In this paper, we present a cubic Hermitian vector-based technique for online compression of asynchronously sampled electrocardiogram signals. The proposed method is computationally efficient data compression. The algorithm has complexity O(n), thus well suited for asynchronous ADCs. Our algorithm requires no data buffering, maintaining the energy advantage of asynchronous ADCs. The proposed method of compression has a compression ratio of up to 90% with achievable percentage root-mean-square difference ratios as a low as 0.97. The algorithm preserves the superior feature-to-feature timing accuracy of asynchronously sampled signals. These advantages are achieved in a computationally efficient manner since algorithm boundary parameters for the signals are extracted a priori.

Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study

Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.

Modern diatom, cladocera, chironomid, and chrysophyte cyst assemblages as quantitative indicators for the reconstruction of past environmental conditions in the Alps. II. Nutrients

Surface sediments from 68 small lakes in the Alps and 9 well-dated sediment core samples that cover a gradient of total phosphorus (TP) concentrations of 6 to 520 μg TP l-1 were studied for diatom, chrysophyte cyst, cladocera, and chironomid assemblages. Inference models for mean circulation log10 TP were developed for diatoms, chironomids, and benthic cladocera using weighted-averaging partial least squares. After screening for outliers, the final transfer functions have coefficients of determination (r2, as assessed by cross-validation, of 0.79 (diatoms), 0.68 (chironomids), and 0.49 (benthic cladocera). Planktonic cladocera and chrysophytes show very weak relationships to TP and no TP inference models were developed for these biota. Diatoms showed the best relationship with TP, whereas the other biota all have large secondary gradients, suggesting that variables other than TP have a strong influence on their composition and abundance. Comparison with other diatom – TP inference models shows that our model has high predictive power and a low root mean squared error of prediction, as assessed by cross-validation.

Selection bias and the cross-validation of regression models for prediction

Strategies are compared for the development of a linear regression model with stochastic (multivariate normal) regressor variables and the subsequent assessment of its predictive ability. Bias and mean squared error of four estimators of predictive performance are evaluated in simulated samples of 32 population correlation matrices. Models including all of the available predictors are compared with those obtained using selected subsets. The subset selection procedures investigated include two stopping rules, C$\sb{\rm p}$ and S$\sb{\rm p}$, each combined with an 'all possible subsets' or 'forward selection' of variables. The estimators of performance utilized include parametric (MSEP$\sb{\rm m}$) and non-parametric (PRESS) assessments in the entire sample, and two data splitting estimates restricted to a random or balanced (Snee's DUPLEX) 'validation' half sample. The simulations were performed as a designed experiment, with population correlation matrices representing a broad range of data structures.^ The techniques examined for subset selection do not generally result in improved predictions relative to the full model. Approaches using 'forward selection' result in slightly smaller prediction errors and less biased estimators of predictive accuracy than 'all possible subsets' approaches but no differences are detected between the performances of C$\sb{\rm p}$ and S$\sb{\rm p}$. In every case, prediction errors of models obtained by subset selection in either of the half splits exceed those obtained using all predictors and the entire sample.^ Only the random split estimator is conditionally (on $\\beta$) unbiased, however MSEP$\sb{\rm m}$ is unbiased on average and PRESS is nearly so in unselected (fixed form) models. When subset selection techniques are used, MSEP$\sb{\rm m}$ and PRESS always underestimate prediction errors, by as much as 27 percent (on average) in small samples. Despite their bias, the mean squared errors (MSE) of these estimators are at least 30 percent less than that of the unbiased random split estimator. The DUPLEX split estimator suffers from large MSE as well as bias, and seems of little value within the context of stochastic regressor variables.^ To maximize predictive accuracy while retaining a reliable estimate of that accuracy, it is recommended that the entire sample be used for model development, and a leave-one-out statistic (e.g. PRESS) be used for assessment. ^

THE IMPROVEMENT REGION IN RIDGE REGRESSION

One of the difficulties in the practical application of ridge regression is that, for a given data set, it is unknown whether a selected ridge estimator has smaller squared error than the least squares estimator. The concept of the improvement region is defined, and a technique is developed which obtains approximate confidence intervals for the value of ridge k which produces the maximum reduction in mean squared error. Two simulation experiments were conducted to investigate how accurate these approximate confidence intervals might be. ^

Geochemical and physical sediment properties of sediment cores from the Portuguese shelf

Marine sediments from the Portuguese shelf are influenced by environmental changes in the surrounding continental and marine environment. These are largely controlled by the North Atlantic Oscillation, but additional impacts may arise from episodic tsunamis. In order to investigate these influences, a high resolution multi-proxy study has been carried out on a 5.4 m long gravity core and five box cores from the Tagus prodelta on the western Portuguese margin, incorporating geochemical (Corg/Ntotal ratios, d13Corg, d15N, d18O, Corg and CaCO3 content) and physical sediment properties (magnetic susceptibility, grain-size). Subsurface data of the five box cores indicate no major effect of early postdepositional alteration. Surface data show a higher fraction of terrigenous organic material close to the river mouth and in the southern prodelta. Gravity core GeoB 8903 covers the last 3.2 kyrs with a temporal resolution of at least 0.1 cm/yr. Very high sedimentation rates between 69 and 140 cm core depth indicate a possible disturbance of the record by the AD1755 tsunami, although no evidence for a disturbance is observed in the data. Sea surface temperature and salinity on the prodelta, the local budget of marine NO3- as well as the provenance of organic matter remained virtually constant during the past 3.2 kyrs. A positive correlation between magnetic susceptibility (MS) and North Atlantic Oscillation (NAO) is evident for the past 250 years, coinciding with a negative correlation between mean grain-size and NAO. This is assigned to a constant riverine supply of fine material with high MS, which is diluted by the riverine input of a coarser, low-MS component during NAO negative, high-precipitation phases. End-member modelling of the lithic grain-size spectrum supports this, revealing a third, coarse lithic component. The high abundance of this coarse end-member prior to 2 kyr BP is interpreted as the result of stronger bottom currents, concentrating the coarse sediment fraction by winnowing. As continental climate was more arid prior to 2 kyr BP (Subboreal), the coarse end-member may also consist of dust from local sources. A decrease in grain-size and CaCO3 content after 2 kyr BP is interpreted as a result of decreasing wind strength. The onset of a fining trend and a further decrease in CaCO3 around AD900 occurs simultaneous to climatic variations, reconstructed from eastern North Atlantic records. A strong increase in MS between AD1400 and AD1500 indicates higher lithic terrigenous input, caused by deforestation in the hinterland.

Particulate and phytoplankton absorption during POLARSTERN cruises ANT-XXVI/3 and ANT-XXVIII/3

The euphotic depth (Zeu) is a key parameter in modelling primary production (PP) using satellite ocean colour. However, evaluations of satellite Zeu products are scarce. The objective of this paper is to investigate existing approaches and sensors to estimate Zeu from satellite and to evaluate how different Zeu products might affect the estimation of PP in the Southern Ocean (SO). Euphotic depth was derived from MODIS and SeaWiFS products of (i) surface chlorophyll-a (Zeu-Chla) and (ii) inherent optical properties (Zeu-IOP). They were compared with in situ measurements of Zeu from different regions of the SO. Both approaches and sensors are robust to retrieve Zeu, although the best results were obtained using the IOP approach and SeaWiFS data, with an average percentage of error (E) of 25.43% and mean absolute error (MAE) of 0.10 m (log scale). Nevertheless, differences in the spatial distribution of Zeu-Chla and Zeu-IOP for both sensors were found as large as 30% over specific regions. These differences were also observed in PP. On average, PP based on Zeu-Chla was 8% higher than PP based on Zeu-IOP, but it was up to 30% higher south of 60°S. Satellite phytoplankton absorption coefficients (aph) derived by the Quasi-Analytical Algorithm at different wavelengths were also validated and the results showed that MODIS aph are generally more robust than SeaWiFS. Thus, MODIS aph should be preferred in PP models based on aph in the SO. Further, we reinforce the importance of investigating the spatial differences between satellite products, which might not be detected by the validation with in situ measurements due to the insufficient amount and uneven distribution of the data.

Sistematización de suelos : eficiencia en la ejecución del proyecto en suelos complejos

El manejo sustentable de los recursos naturales relacionados con proyectos de utilización de los recursos hídricos (entre otros), requiere en muchos casos de la modificación del relieve existente. Esto conlleva la necesidad de adecuación de la capa homogénea superior del suelo, operación que suele denominarse "sistematización", la cual facilita una distribución más uniforme de las lluvias y del agua de riego. Esta modificación de la capa superior del suelo es realizada en base a un proyecto, cuya inclinación responda a las pendientes naturales o a las establecidas por el diseñador. En la ejecución del diseño proyectado, en superficies superiores a una hectárea, el movimiento de tierra se realiza con equipos pesados, que no aseguran un alto porcentaje de eficiencia en lo que al movimiento de tierra se refiere, ya que parte del material se pierde en el acarreo, pero muy especialmente, por la compactación desuniforme del mismo, asociada con las texturas complejas del suelo a trabajar. El presente trabajo determinó el índice de precisión en la ejecución del proyecto de sistematización a partir de un índice estadístico internacionalmente aceptado, el "Root Mean Squared Error (RMSE)", comparando los valores altimétricos proyectados y los realmente obtenidos luego de la ejecución del proyecto, en tres parcelas con distinta secuencia de labores y maquinaria utilizadas, pero con el mismo tipo de suelo en el área del eje Pilar - La Plata (Argentina). Los resultados obtenidos, que varían de un RMSE de 4 a 6 cm, permiten concluir, para los sitios y las condiciones estudiadas, que no pueden asegurarse en la sistematización índices de precisión en la ejecución de la obra, inferiores a los 4 cm.

Modelos digitales de elevación generados por captura directa e indirecta de datos fuente : evaluación de su calidad

La información básica sobre el relieve de una cuenca hidrográfica, mediante metodologías analítico-descriptivas, permite a quienes evalúan proyectos relacionados con el uso de los recursos naturales, tales como el manejo integrado de cuencas, estudios sobre impacto ambiental, degradación de suelos, deforestación, conservación de los recursos hídricos, entre otros, contar para su análisis con los parámetros físicos necesarios. Estos procesos mencionados tienen un fuerte componente espacial y el empleo de Sistemas de Información Geográfica (SIG) son de suma utilidad, siendo los Modelos Digitales de Elevación (DEM) y sus derivados un componente relevante de esta base de datos. Los productos derivados de estos modelos, como pendiente, orientación o curvatura, resultarán tan precisos como el DEM usado para derivarlos. Por otra parte, es fundamental maximizar la habilidad del modelo para representar las variaciones del terreno; para ello se debe seleccionar una adecuada resolución (grilla) de acuerdo con los datos disponibles para su generación. En este trabajo se evalúa la calidad altimétrica de seis DEMs generados a partir de dos sistemas diferentes de captura de datos fuente y de distintas resoluciones de grilla. Para determinar la exactitud de los DEMs habitualmente se utiliza un grupo de puntos de control considerados como "verdad de campo" que se comparan con los generados por el modelo en la misma posición geográfica. El área seleccionada para realizar el estudio está ubicada en la localidad de Arrecifes, provincia de Buenos Aires (Argentina) y tiene una superficie de aproximadamente 120 ha. Los resultados obtenidos para los dos algoritmos y para los tres tamaños de grilla analizados presentaron los siguientes resultados: el algoritmo DEM from contourn, un RMSE (Root Mean Squared Error) de ± 0,11 m (para grilla de 1 m), ± 0,11 m (para grilla de 5 m) y de ± 0,15 m (para grilla de 10 m). Para el algoritmo DEM from vector/points, un RMSE de ± 0,09 m (para grilla de 1 m), ± 0,11 m (para grilla de 5 m) y de ± 0,11 m (para grilla de 10 m). Los resultados permiten concluir que el DEM generado a partir de puntos acotados del terreno como datos fuente y con el menor tamaño de grilla es el único que satisface los valores enumerados en la bibliografía, tanto nacional como internacional, lo que lo hace apto para proyectos relacionados con recursos naturales a nivel de ecotopo (predial). El resto de los DEMs generados presentan un RMSE que permite asegurar su aptitud para la evaluación de proyectos relacionados con el uso de los recursos naturales a nivel de unidad de paisaje (conjunto de ecotopos).

Isotopic composition of water in fog, rain, throughfall and stemflow in the Monte Verde, Costa Rica

Fog deposition, precipitation, throughfall and stemflow were measured in a windward tropical montane cloud forest near Monteverde, Costa Rica, for a 65-day period during the dry season of 2003. Net fog deposition was measured directly using the eddy covariance (EC) method and it amounted to 1.2 ± 0.1 mm/day (mean ± standard error). Fog water deposition was 5-9% of incident rainfall for the entire period, which is at the low end of previously reported values. Stable isotope concentrations (d18O and d2H) were determined in a large number of samples of each water component. Mass balance-based estimates of fog deposition were 1.0 ± 0.3 and 5.0 ± 2.7 mm/day (mean ± SE) when d18O and d2H were used as tracer, respectively. Comparisons between direct fog deposition measurements and the results of the mass balance model using d18O as a tracer indicated that the latter might be a good tool to estimate fog deposition in the absence of direct measurement under many (but not all) conditions. At 506 mm, measured water inputs over the 65 days (fog plus rain) fell short by 46 mm compared to the canopy output of 552 mm (throughfall, stemflow and interception evaporation). This discrepancy is attributed to the underestimation of rainfall during conditions of high wind.