A multifactorial analysis of obesity as CVD risk factor: use of neural network based methods in a nutrigenetics context

Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex etiology beneath obesity and identify genetic variations and/or factors related to nutrition that contribute to its variability. To this end, a set of more than 2300 white subjects who participated in a nutrigenetics study was used. For each subject a total of 63 factors describing genetic variants related to CVD (24 in total), gender, and nutrition (38 in total), e.g. average daily intake in calories and cholesterol, were measured. Each subject was categorized according to body mass index (BMI) as normal (BMI ≤ 25) or overweight (BMI > 25). Two artificial neural network (ANN) based methods were designed and used towards the analysis of the available data. These corresponded to i) a multi-layer feed-forward ANN combined with a parameter decreasing method (PDM-ANN), and ii) a multi-layer feed-forward ANN trained by a hybrid method (GA-ANN) which combines genetic algorithms and the popular back-propagation training algorithm.

The performance of conventional and fluorescence-based methods for occlusal caries detection: an in vivo study with histologic validation

The authors conducted an in vivo study to determine clinical cutoffs for a laser fluorescence (LF) device, an LF pen and a fluorescence camera (FC), as well as to evaluate the clinical performance of these methods and conventional methods in detecting occlusal caries in permanent teeth by using the histologic gold standard for total validation of the sample.

Effectiveness of fluorescence-based methods to detect in situ demineralization and remineralization on smooth surfaces.

This study aimed to evaluate the effectiveness of fluorescence-based methods (DIAGNOdent, LF; DIAGNOdent pen, LFpen, and VistaProof fluorescence camera, FC) in detecting demineralization and remineralization on smooth surfaces in situ. Ten volunteers wore acrylic palatal appliances, each containing 6 enamel blocks that were demineralized for 14 days by exposure to a 20% sucrose solution and 3 of them were remineralized for 7 days with fluoride dentifrice. Sixty enamel blocks were evaluated at baseline, after demineralization and 30 blocks after remineralization by two examiners using LF, LFpen and FC. They were submitted to surface microhardness (SMH) and cross-sectional microhardness analysis. The integrated loss of surface hardness (ΔKHN) was calculated. The intraclass correlation coefficient for interexaminer reproducibility ranged from 0.21 (FC) to 0.86 (LFpen). SMH, LF and LFpen values presented significant differences among the three phases. However, FC fluorescence values showed no significant differences between the demineralization and remineralization phases. Fluorescence values for baseline, demineralized and remineralized enamel were, respectively, 5.4 ± 1.0, 9.2 ± 2.2 and 7.0 ± 1.5 for LF; 10.5 ± 2.0, 15.0 ± 3.2 and 12.5 ± 2.9 for LFpen, and 1.0 ± 0.0, 1.0 ± 0.1 and 1.0 ± 0.1 for FC. SMH and ΔKHN showed significant differences between demineralization and remineralization phases. There was a negative and significant correlation between SMH and LF and LFpen in the remineralization phase. In conclusion, LF and LFpen devices were effective in detecting demineralization and remineralization on smooth surfaces provoked in situ.

Effectiveness of Fluorescence-based Methods in Monitoring Progression of Noncavitated Caries-like Lesions on Smooth Surfaces

Although there has been a significant decrease in caries prevalence in developed countries, the slower progression of dental caries requires methods capable of detecting and quantifying lesions at an early stage. The aim of this study was to evaluate the effectiveness of fluorescence-based methods (DIAGNOdent 2095 laser fluorescence device [LF], DIAGNOdent 2190 pen [LFpen], and VistaProof fluorescence camera [FC]) in monitoring the progression of noncavitated caries-like lesions on smooth surfaces. Caries-like lesions were developed in 60 blocks of bovine enamel using a bacterial model of Streptococcus mutans and Lactobacillus acidophilus . Enamel blocks were evaluated by two independent examiners at baseline (phase I), after the first cariogenic challenge (eight days) (phase II), and after the second cariogenic challenge (a further eight days) (phase III) by two independent examiners using the LF, LFpen, and FC. Blocks were submitted to surface microhardness (SMH) and cross-sectional microhardness analyses. The intraclass correlation coefficient for intra- and interexaminer reproducibility ranged from 0.49 (FC) to 0.94 (LF/LFpen). SMH values decreased and fluorescence values increased significantly among the three phases. Higher values for sensitivity, specificity, and area under the receiver operating characteristic curve were observed for FC (phase II) and LFpen (phase III). A significant correlation was found between fluorescence values and SMH in all phases and integrated loss of surface hardness (ΔKHN) in phase III. In conclusion, fluorescence-based methods were effective in monitoring noncavitated caries-like lesions on smooth surfaces, with moderate correlation with SMH, allowing differentiation between sound and demineralized enamel.

A Hybrid Multimodal Non-Rigid Registration of MR Images Based on Diffeomorphic Demons

n this paper we present a novel hybrid approach for multimodal medical image registration based on diffeomorphic demons. Diffeomorphic demons have proven to be a robust and efficient way for intensity-based image registration. A very recent extension even allows to use mutual information (MI) as a similarity measure to registration multimodal images. However, due to the intensity correspondence uncertainty existing in some anatomical parts, it is difficult for a purely intensity-based algorithm to solve the registration problem. Therefore, we propose to combine the resulting transformations from both intensity-based and landmark-based methods for multimodal non-rigid registration based on diffeomorphic demons. Several experiments on different types of MR images were conducted, for which we show that a better anatomical correspondence between the images can be obtained using the hybrid approach than using either intensity information or landmarks alone.

Influence of different professional prophylactic methods on fluorescence measurements for detection of occlusal caries

This study aimed to evaluate the influence of professional prophylactic methods on the DIAGNOdent 2095, DIAGNOdent 2190 and VistaProof performance in detecting occlusal caries. Assessments were performed in 110 permanent teeth at baseline and after bicarbonate jet or prophylactic paste and rinsing. Performance in terms of sensitivity improved after rinsing of the occlusal surfaces when the prophylactic paste was used. However, the sodium bicarbonate jet did not significantly influence the performance of the fluorescence-based methods. It can be concluded that different professional prophylactic methods can significantly influence the performance of fluorescence-based methods for occlusal caries detection.

Applied Graph Theory in Computer Vision and Pattern Recognition

This book will serve as a foundation for a variety of useful applications of graph theory to computer vision, pattern recognition, and related areas. It covers a representative set of novel graph-theoretic methods for complex computer vision and pattern recognition tasks. The first part of the book presents the application of graph theory to low-level processing of digital images such as a new method for partitioning a given image into a hierarchy of homogeneous areas using graph pyramids, or a study of the relationship between graph theory and digital topology. Part II presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, including a survey of graph based methodologies for pattern recognition and computer vision, a presentation of a series of computationally efficient algorithms for testing graph isomorphism and related graph matching tasks in pattern recognition and a new graph distance measure to be used for solving graph matching problems. Finally, Part III provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks. It includes a critical review of the main graph-based and structural methods for fingerprint classification, a new method to visualize time series of graphs, and potential applications in computer network monitoring and abnormal event detection.

Performance of fluorescence methods, radiographic examination and ICDAS II on occlusal surfaces in vitro

This study compared the performance of fluorescence-based methods, radiographic examination, and International Caries Detection and Assessment System (ICDAS) II on occlusal surfaces. One hundred and nineteen permanent human molars were assessed twice by 2 experienced dentists using the laser fluorescence (LF and LFpen) and fluorescence camera (FC) devices, ICDAS II and bitewing radiographs (BW). After measuring, the teeth were histologically prepared and assessed for caries extension. The sensitivities for dentine caries detection were 0.86 (FC), 0.78 (LFpen), 0.73 (ICDAS II), 0.51 (LF) and 0.34 (BW). The specificities were 0.97 (BW), 0.89 (LF), 0.65 (ICDAS II), 0.63 (FC) and 0.56 (LFpen). BW presented the highest values of likelihood ratio (LR)+ (12.47) and LR- (0.68). Rank correlations with histology were 0.53 (LF), 0.52 (LFpen), 0.41 (FC), 0.59 (ICDAS II) and 0.57 (BW). The area under the ROC curve varied from 0.72 to 0.83. Inter- and intraexaminer intraclass correlation values were respectively 0.90 and 0.85 (LF), 0.93 and 0.87 (LFpen) and 0.85 and 0.76 (FC). The ICDAS II kappa values were 0.51 (interexaminer) and 0.61 (intraexaminer). The BW kappa values were 0.50 (interexaminer) and 0.62 (intraexaminer). The Bland and Altman limits of agreement were 46.0 and 38.2 (LF), 55.6 and 40.0 (LFpen) and 1.12 and 0.80 (FC), for intra- and interexaminer reproducibilities. The posttest probability for dentine caries detection was high for BW and LF. In conclusion, LFpen, FC and ICDAS II presented better sensitivity and LF and BW better specificity. ICDAS II combined with BW showed the best performance and is the best combination for detecting caries on occlusal surfaces.

Non-ignorable loss to follow-up: correcting mortality estimates based on additional outcome ascertainment

Loss to follow-up (LTFU) is a common problem in many epidemiological studies. In antiretroviral treatment (ART) programs for patients with human immunodeficiency virus (HIV), mortality estimates can be biased if the LTFU mechanism is non-ignorable, that is, mortality differs between lost and retained patients. In this setting, routine procedures for handling missing data may lead to biased estimates. To appropriately deal with non-ignorable LTFU, explicit modeling of the missing data mechanism is needed. This can be based on additional outcome ascertainment for a sample of patients LTFU, for example, through linkage to national registries or through survey-based methods. In this paper, we demonstrate how this additional information can be used to construct estimators based on inverse probability weights (IPW) or multiple imputation. We use simulations to contrast the performance of the proposed estimators with methods widely used in HIV cohort research for dealing with missing data. The practical implications of our approach are illustrated using South African ART data, which are partially linkable to South African national vital registration data. Our results demonstrate that while IPWs and proper imputation procedures can be easily constructed from additional outcome ascertainment to obtain valid overall estimates, neglecting non-ignorable LTFU can result in substantial bias. We believe the proposed estimators are readily applicable to a growing number of studies where LTFU is appreciable, but additional outcome data are available through linkage or surveys of patients LTFU. Copyright © 2013 John Wiley & Sons, Ltd.

Traditional and novel methods for occlusal caries detection: performance on primary teeth

This study aimed to assess the performance of International Caries Detection and Assessment System (ICDAS), radiographic examination, and fluorescence-based methods for detecting occlusal caries in primary teeth. One occlusal site on each of 79 primary molars was assessed twice by two examiners using ICDAS, bitewing radiography (BW), DIAGNOdent 2095 (LF), DIAGNOdent 2190 (LFpen), and VistaProof fluorescence camera (FC). The teeth were histologically prepared and assessed for caries extent. Optimal cutoff limits were calculated for LF, LFpen, and FC. At the D (1) threshold (enamel and dentin lesions), ICDAS and FC presented higher sensitivity values (0.75 and 0.73, respectively), while BW showed higher specificity (1.00). At the D (2) threshold (inner enamel and dentin lesions), ICDAS presented higher sensitivity (0.83) and statistically significantly lower specificity (0.70). At the D(3) threshold (dentin lesions), LFpen and FC showed higher sensitivity (1.00 and 0.91, respectively), while higher specificity was presented by FC (0.95), ICDAS (0.94), BW (0.94), and LF (0.92). The area under the receiver operating characteristic (ROC) curve (Az) varied from 0.780 (BW) to 0.941 (LF). Spearman correlation coefficients with histology were 0.72 (ICDAS), 0.64 (BW), 0.71 (LF), 0.65 (LFpen), and 0.74 (FC). Inter- and intraexaminer intraclass correlation values varied from 0.772 to 0.963 and unweighted kappa values ranged from 0.462 to 0.750. In conclusion, ICDAS and FC exhibited better accuracy in detecting enamel and dentin caries lesions, whereas ICDAS, LF, LFpen, and FC were more appropriate for detecting dentin lesions on occlusal surfaces in primary teeth, with no statistically significant difference among them. All methods presented good to excellent reproducibility.

A benchmark of kriging-based infill criteria for noisy optimization

Responses of many real-world problems can only be evaluated perturbed by noise. In order to make an efficient optimization of these problems possible, intelligent optimization strategies successfully coping with noisy evaluations are required. In this article, a comprehensive review of existing kriging-based methods for the optimization of noisy functions is provided. In summary, ten methods for choosing the sequential samples are described using a unified formalism. They are compared on analytical benchmark problems, whereby the usual assumption of homoscedastic Gaussian noise made in the underlying models is meet. Different problem configurations (noise level, maximum number of observations, initial number of observations) and setups (covariance functions, budget, initial sample size) are considered. It is found that the choices of the initial sample size and the covariance function are not critical. The choice of the method, however, can result in significant differences in the performance. In particular, the three most intuitive criteria are found as poor alternatives. Although no criterion is found consistently more efficient than the others, two specialized methods appear more robust on average.

A g-factor metric for k-t-GRAPPA- and PEAK-GRAPPA-based parallel imaging.

PURPOSE The aim of this work is to derive a theoretical framework for quantitative noise and temporal fidelity analysis of time-resolved k-space-based parallel imaging methods. THEORY An analytical formalism of noise distribution is derived extending the existing g-factor formulation for nontime-resolved generalized autocalibrating partially parallel acquisition (GRAPPA) to time-resolved k-space-based methods. The noise analysis considers temporal noise correlations and is further accompanied by a temporal filtering analysis. METHODS All methods are derived and presented for k-t-GRAPPA and PEAK-GRAPPA. A sliding window reconstruction and nontime-resolved GRAPPA are taken as a reference. Statistical validation is based on series of pseudoreplica images. The analysis is demonstrated on a short-axis cardiac CINE dataset. RESULTS The superior signal-to-noise performance of time-resolved over nontime-resolved parallel imaging methods at the expense of temporal frequency filtering is analytically confirmed. Further, different temporal frequency filter characteristics of k-t-GRAPPA, PEAK-GRAPPA, and sliding window are revealed. CONCLUSION The proposed analysis of noise behavior and temporal fidelity establishes a theoretical basis for a quantitative evaluation of time-resolved reconstruction methods. Therefore, the presented theory allows for comparison between time-resolved parallel imaging methods and also nontime-resolved methods. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.

Decreasing Proportion of Recent Infections among Newly Diagnosed HIV-1 Cases in Switzerland, 2008 to 2013 Based on Line-Immunoassay-Based Algorithms.

BACKGROUND: HIV surveillance requires monitoring of new HIV diagnoses and differentiation of incident and older infections. In 2008, Switzerland implemented a system for monitoring incident HIV infections based on the results of a line immunoassay (Inno-Lia) mandatorily conducted for HIV confirmation and type differentiation (HIV-1, HIV-2) of all newly diagnosed patients. Based on this system, we assessed the proportion of incident HIV infection among newly diagnosed cases in Switzerland during 2008-2013. METHODS AND RESULTS: Inno-Lia antibody reaction patterns recorded in anonymous HIV notifications to the federal health authority were classified by 10 published algorithms into incident (up to 12 months) or older infections. Utilizing these data, annual incident infection estimates were obtained in two ways, (i) based on the diagnostic performance of the algorithms and utilizing the relationship 'incident = true incident + false incident', (ii) based on the window-periods of the algorithms and utilizing the relationship 'Prevalence = Incidence x Duration'. From 2008-2013, 3'851 HIV notifications were received. Adult HIV-1 infections amounted to 3'809 cases, and 3'636 of them (95.5%) contained Inno-Lia data. Incident infection totals calculated were similar for the performance- and window-based methods, amounting on average to 1'755 (95% confidence interval, 1588-1923) and 1'790 cases (95% CI, 1679-1900), respectively. More than half of these were among men who had sex with men. Both methods showed a continuous decline of annual incident infections 2008-2013, totaling -59.5% and -50.2%, respectively. The decline of incident infections continued even in 2012, when a 15% increase in HIV notifications had been observed. This increase was entirely due to older infections. Overall declines 2008-2013 were of similar extent among the major transmission groups. CONCLUSIONS: Inno-Lia based incident HIV-1 infection surveillance proved useful and reliable. It represents a free, additional public health benefit of the use of this relatively costly test for HIV confirmation and type differentiation.

Automated Intervertebral Disc Detection from Low Resolution, Sparse MRI Images for the Planning of Scan Geometries

Robust and accurate identification of intervertebral discs from low resolution, sparse MRI scans is essential for the automated scan planning of the MRI spine scan. This paper presents a graphical model based solution for the detection of both the positions and orientations of intervertebral discs from low resolution, sparse MRI scans. Compared with the existing graphical model based methods, the proposed method does not need a training process using training data and it also has the capability to automatically determine the number of vertebrae visible in the image. Experiments on 25 low resolution, sparse spine MRI data sets verified its performance.