Non-invasive diagnostic tests for Helicobacter pylori infection

BACKGROUND: Helicobacter pylori (H pylori) infection has been implicated in a number of malignancies and non-malignant conditions including peptic ulcers, non-ulcer dyspepsia, recurrent peptic ulcer bleeding, unexplained iron deficiency anaemia, idiopathic thrombocytopaenia purpura, and colorectal adenomas. The confirmatory diagnosis of H pylori is by endoscopic biopsy, followed by histopathological examination using haemotoxylin and eosin (H & E) stain or special stains such as Giemsa stain and Warthin-Starry stain. Special stains are more accurate than H & E stain. There is significant uncertainty about the diagnostic accuracy of non-invasive tests for diagnosis of H pylori. OBJECTIVES: To compare the diagnostic accuracy of urea breath test, serology, and stool antigen test, used alone or in combination, for diagnosis of H pylori infection in symptomatic and asymptomatic people, so that eradication therapy for H pylori can be started. SEARCH METHODS: We searched MEDLINE, Embase, the Science Citation Index and the National Institute for Health Research Health Technology Assessment Database on 4 March 2016. We screened references in the included studies to identify additional studies. We also conducted citation searches of relevant studies, most recently on 4 December 2016. We did not restrict studies by language or publication status, or whether data were collected prospectively or retrospectively. SELECTION CRITERIA: We included diagnostic accuracy studies that evaluated at least one of the index tests (urea breath test using isotopes such as13C or14C, serology and stool antigen test) against the reference standard (histopathological examination using H & E stain, special stains or immunohistochemical stain) in people suspected of having H pylori infection. DATA COLLECTION AND ANALYSIS: Two review authors independently screened the references to identify relevant studies and independently extracted data. We assessed the methodological quality of studies using the QUADAS-2 tool. We performed meta-analysis by using the hierarchical summary receiver operating characteristic (HSROC) model to estimate and compare SROC curves. Where appropriate, we used bivariate or univariate logistic regression models to estimate summary sensitivities and specificities. MAIN RESULTS: We included 101 studies involving 11,003 participants, of which 5839 participants (53.1%) had H pylori infection. The prevalence of H pylori infection in the studies ranged from 15.2% to 94.7%, with a median prevalence of 53.7% (interquartile range 42.0% to 66.5%). Most of the studies (57%) included participants with dyspepsia and 53 studies excluded participants who recently had proton pump inhibitors or antibiotics.There was at least an unclear risk of bias or unclear applicability concern for each study.Of the 101 studies, 15 compared the accuracy of two index tests and two studies compared the accuracy of three index tests. Thirty-four studies (4242 participants) evaluated serology; 29 studies (2988 participants) evaluated stool antigen test; 34 studies (3139 participants) evaluated urea breath test-13C; 21 studies (1810 participants) evaluated urea breath test-14C; and two studies (127 participants) evaluated urea breath test but did not report the isotope used. The thresholds used to define test positivity and the staining techniques used for histopathological examination (reference standard) varied between studies. Due to sparse data for each threshold reported, it was not possible to identify the best threshold for each test.Using data from 99 studies in an indirect test comparison, there was statistical evidence of a difference in diagnostic accuracy between urea breath test-13C, urea breath test-14C, serology and stool antigen test (P = 0.024). The diagnostic odds ratios for urea breath test-13C, urea breath test-14C, serology, and stool antigen test were 153 (95% confidence interval (CI) 73.7 to 316), 105 (95% CI 74.0 to 150), 47.4 (95% CI 25.5 to 88.1) and 45.1 (95% CI 24.2 to 84.1). The sensitivity (95% CI) estimated at a fixed specificity of 0.90 (median from studies across the four tests), was 0.94 (95% CI 0.89 to 0.97) for urea breath test-13C, 0.92 (95% CI 0.89 to 0.94) for urea breath test-14C, 0.84 (95% CI 0.74 to 0.91) for serology, and 0.83 (95% CI 0.73 to 0.90) for stool antigen test. This implies that on average, given a specificity of 0.90 and prevalence of 53.7% (median specificity and prevalence in the studies), out of 1000 people tested for H pylori infection, there will be 46 false positives (people without H pylori infection who will be diagnosed as having H pylori infection). In this hypothetical cohort, urea breath test-13C, urea breath test-14C, serology, and stool antigen test will give 30 (95% CI 15 to 58), 42 (95% CI 30 to 58), 86 (95% CI 50 to 140), and 89 (95% CI 52 to 146) false negatives respectively (people with H pylori infection for whom the diagnosis of H pylori will be missed).Direct comparisons were based on few head-to-head studies. The ratios of diagnostic odds ratios (DORs) were 0.68 (95% CI 0.12 to 3.70; P = 0.56) for urea breath test-13C versus serology (seven studies), and 0.88 (95% CI 0.14 to 5.56; P = 0.84) for urea breath test-13C versus stool antigen test (seven studies). The 95% CIs of these estimates overlap with those of the ratios of DORs from the indirect comparison. Data were limited or unavailable for meta-analysis of other direct comparisons. AUTHORS' CONCLUSIONS: In people without a history of gastrectomy and those who have not recently had antibiotics or proton ,pump inhibitors, urea breath tests had high diagnostic accuracy while serology and stool antigen tests were less accurate for diagnosis of Helicobacter pylori infection.This is based on an indirect test comparison (with potential for bias due to confounding), as evidence from direct comparisons was limited or unavailable. The thresholds used for these tests were highly variable and we were unable to identify specific thresholds that might be useful in clinical practice.We need further comparative studies of high methodological quality to obtain more reliable evidence of relative accuracy between the tests. Such studies should be conducted prospectively in a representative spectrum of participants and clearly reported to ensure low risk of bias. Most importantly, studies should prespecify and clearly report thresholds used, and should avoid inappropriate exclusions

Feature extraction in palmprint recognition using spiral of moment skewness and kurtosis algorithm

International audienceBecause of their high recognition rates, coding-based approaches that use multispectral palmprint images have become one of the most popular palmprint recognition methods. This paper describes a new multispectral palmprint recognition method that aims to further improve the performance of coding-based approaches by focusing on the local binary pattern (LBP) filters and spiral moments features. The final feature map is derived through a staged process of creating a composite of spiral and LBP features by fusing them together and passing the features through the minimum redundancy maximum relevance transformers. Using Hamming distances, the inter- and intra-similarities of the palmprint feature maps are determined. The experimental technique was evaluated using the available data on the IITD, MSPolyU and PolyU PPDB databases. The results indicate that the method achieved high levels of accuracy in the identification and verification modes. Furthermore, this method outperforms the existing advanced techniques

Efficient heart disease diagnosis based on twin support vector machine

Heart disease is the leading cause of death in the world according to the World Health Organization (WHO). Researchers are more interested in using machine learning techniques to help medical staff diagnose or detect heart disease early. In this paper, we propose an efficient medical decision support system based on twin support vector machines (Twin-SVM) for heart disease diagnosing with binary target (i.e. presence or absence of disease). Unlike conventional support vector machines (SVM) that finds only one optimal hyperplane for separating the data points of first class from those of second class, which causes inaccurate decision, Twin-SVM finds two non-parallel hyper-planes so that each one is closer to the first class and is as far from the second class as possible. Our experiments are conducted on real heart disease dataset and many evaluation metrics have been considered to evaluate the performance of the proposed method. Furthermore, a comparison between the proposed method and several well-known classifiers as well as the state-of-the-art methods has been performed. The obtained results proved that our proposed method based on Twin-SVM technique gives promising performances better than the state-of-the-art. This improvement can seriously reduce time, materials, and labor in healthcare services while increasing the final decision accuracy

Histogram of gradient and binarized statistical image features of wavelet subband-based palmprint features extraction

International audiencePalmprint recognition systems are dependent on feature extraction. A method of feature extraction using higher discrimination information was developed to characterize palmprint images. In this method, two individual feature extraction techniques are applied to a discrete wavelet transform of a palmprint image, and their outputs are fused. The two techniques used in the fusion are the histogram of gradient and the binarized statistical image features. They are then evaluated using an extreme learning machine classifier before selecting a feature based on principal component analysis. Three palmprint databases, the Hong Kong Polytechnic University (PolyU) Multispectral Palmprint Database, Hong Kong PolyU Palmprint Database II, and the Delhi Touchless (IIDT) Palmprint Database, are used in this study. The study shows that our method effectively identifies and verifies palmprints and outperforms other methods based on feature extraction. © 2017 SPIE and IS&T

Improved Simultaneous Algebraic Reconstruction Technique Algorithm for Positron-Emission Tomography Image Reconstruction via Minimizing the Fast Total Variation

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Superpixel-based Zernike Moments for Palm-print Recognition

International audienceIn the contemporary period, significant attention has been focused on the prospects of innovative personal recognition methods based on palm print biometrics. However, diminished local consistency and interference from noise are only some of the obstacles that hinder the most common methods of palm-print imaging such as the grey texture and other low-level of the palm. Nevertheless, the development of the process and tackling of the obstacles faced have a potential solution in the form of high-level characteristic imaging for palm-print identification. In this study, Zernike Moments are used for acquiring superpixel features that are spiral scanned images, which is an innovative recognition method. By using the extreme learning machine, the inter- and intra-similarities of the palm-print feature maps are determined. Our experiments yield good results with an accuracy rate of 97.52 and an equal error rate of 1.47 % on the palm-print PolyU database

Application of BSIF, Log-Gabor and mRMR Transforms for Iris and Palmprint based Bi-modal Identification System

International audienceVerification of individual identity through the process of biometric identification involves comparison between an encoded value and a stored value of the biometric feature in question. The effectiveness of a multimodal user authentication system is greater, but so is its complexity. The system error rate is reduced by the fact that multiple biometric features are combined, thus solving the weakness of the single biometric. Performance of individual authentication through palm-print-and iris-based bi-modal biometric system is proposed in the present study. To this end, Log-Gabor filter and BSIF (Binarised Statistical Image Feature) coefficients are employed to obtain the iris and palm-print traits, and subsequently selection of the features vector is conducted with mRMR (Minimum Redundancy Maximum Relevance) transforms in higher coefficients. To match the iris or palm-print feature vector, the Hamming Distance is applied. According to the experiment outcomes, the proposed system not only has a significantly high recognition rate but it also affords greater security compared to the single biometric system

Heart disease prediction using neighborhood component analysis and support vector machines

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Science and mission status of EUSO-SPB2

The Extreme Universe Space Observatory on a Super Pressure Balloon II (EUSO-SPB2) is a second generation stratospheric balloon instrument for the detection of Ultra High Energy Cosmic Rays (UHECRs, E > 1 EeV) via the fluorescence technique and of Very High Energy (VHE, E > 10 PeV) neutrinos via Cherenkov emission. EUSO-SPB2 is a pathfinder mission for instruments like the proposed Probe Of Extreme Multi-Messenger Astrophysics (POEMMA). The purpose of such a space-based observatory is to measure UHECRs and UHE neutrinos with high statistics and uniform exposure. EUSO-SPB2 is designed with two Schmidt telescopes, each optimized for their respective observational goals. The Fluorescence Telescope looks at the nadir to measure the fluorescence emission from UHECR-induced extensive air shower (EAS), while the Cherenkov Telescope is optimized for fast signals (∼10 ns) and points near the Earth's limb. This allows for the measurement of Cherenkov light from EAS caused by Earth skimming VHE neutrinos if pointed slightly below the limb or from UHECRs if observing slightly above. The expected launch date of EUSO-SPB2 is Spring 2023 from Wanaka, NZ with target duration of up to 100 days. Such a flight would provide thousands of VHECR Cherenkov signals in addition to tens of UHECR fluorescence tracks. Neither of these kinds of events have been observed from either orbital or suborbital altitudes before, making EUSO-SPB2 crucial to move forward towards a space-based instrument. It will also enhance the understanding of potential background signals for both detection techniques. This contribution will provide a short overview of the detector and the current status of the mission as well as its scientific goals.ISSN:1824-803

An overview of the JEM-EUSO program and results

The field of UHECRs (Ultra-High energy cosmic Rays) and the understanding of particle acceleration in the cosmos, as a key ingredient to the behaviour of the most powerful sources in the universe, is of outmost importance for astroparticle physics as well as for fundamental physics and will improve our general understanding of the universe. The current main goals are to identify sources of UHECRs and their composition. For this, increased statistics is required. A space-based detector for UHECR research has the advantage of a very large exposure and a uniform coverage of the celestial sphere. The aim of the JEM-EUSO program [1] is to bring the study of UHECRs to space. The principle of observation is based on the detection of UV light emitted by isotropic fluorescence of atmospheric nitrogen excited by the Extensive Air Showers (EAS) in the Earth's atmosphere and forward-beamed Cherenkov radiation reflected from the Earth's surface or dense cloud tops. In addition to the prime objective of UHECR studies, JEM-EUSO will do several secondary studies due to the instruments' unique capacity of detecting very weak UV-signals with extreme time-resolution around 1 μs: meteors, Transient Luminous Events (TLE), bioluminescence, maps of human generated UV-light, searches for Strange Quark Matter (SQM) and high-energy neutrinos, and more. The JEM-EUSO program includes several missions from ground (EUSO-TA [2]), from stratospheric balloons (EUSO-Balloon [3], EUSO-SPB1 [4], EUSO-SPB2 [5]), and from space (TUS [6], Mini-EUSO [7]) employing fluorescence detectors to demonstrate the UHECR observation from space and prepare the large size missions K-EUSO [8] and POEMMA [9]. A review of the current status of the program, the key results obtained so far by the different projects, and the perspectives for the near future are presented.ISSN:1824-803