Wide Variation in Adenoma Detection Rates at Screening Flexible Sigmoidoscopy

Background & Aims: Wide between-center variation in adenoma detection rates (ADRs) was observed in the U.K. Flexible Sigmoidoscopy Screening Trial (overall, 12.1%; range, 8.6%-15.9%; P <0.0001). The aim of this study was to determine whether the observed differences could be attributed to varying performance by endoscopists, to examine the effect of experience on performance, and to identify an attainable, standard ADR to which endoscopists could aspire. 

Methods: Thirteen medical endoscopists, one per trial center, each performed about 3000 examinations (200 per month) using the same equipment and protocol. Overall and monthly ADRs were compared using multivariable logistic regression. 

Results: Differences in ADRs were not explained by patient characteristics, incidence of colorectal cancer in the local population, or the endoscopists' medical specialty or previous experience. Average ADRs increased significantly with screening experience (up to 400 examinations). Endoscopists were classified as higher, intermediate, or lower adenoma detectors, and performance levels were maintained over time. Higher detectors had ADRs of 15% overall (men, 20%; women, 10%) and also detected more adenomas per case (higher/lower detectors, 21.7/10.4 adenomas per :100 examinations). 

Conclusions: The differences in ADRs were due to variation in performance of the endoscopists. Long-term follow-up will determine whether this variation is clinically important. We suggest that the standards in higher detecting centers should be achievable by all endoscopists screening unscreened populations aged older than 55 years. Endoscopists should aim to stay above the lower 95% confidence interval band for 200 examinations (10% overall; 5% in women, 15% in men).

Increased diagnosis and detection rates of carcinoma in situ of the breast

The purpose of this study was to identify trends in the diagnosis of carcinoma in situ (CIS) of the breast in the United Kingdom (UK) and the Republic of Ireland (ROI) and to examine the impact of mammography. Data on cases of newly diagnosed CIS of the breast and mode of detection (screen detected or not) were obtained, where available, from regional cancer registries between 1990 and 2007. Age-standardised diagnosis rates for the UK and the ROI, and regional screen detected diagnosis rates were compared by calculating the annual percentage change (APC) over time. The APC of the diagnosis rate amongst women aged 50-64 years (original screening age group) showed a significant 5.9% increase in the UK (1990-2007) and 11.5% increase in the ROI (1994-2007). The rate of diagnosis (50-64 years) stabilized in the UK between 2005 and 2007 and was substantially higher than in other western populations with national screening programmes. The APC of the diagnosis rate amongst those aged 65-69 years showed a significant 12.4% increase in the UK (1990-2007) and 10.3% increase in the ROI (1994-2007). amongst women aged 50-74 years in the UK, approximately 4,300 cases of CIS (˜90% ductal carcinoma in situ) were diagnosed in 2007. Our analyses have shown that screen detected CIS contributed primarily to the increase in diagnosis of CIS of the breast. The high diagnosis rate of screen detected CIS of the breast underlines the need for further research into lesion and patient characteristics that are related to progression of CIS to invasive disease to better target treatment. © 2012 Springer Science+Business Media, LLC.

High Rates of Detection of Respiratory Viruses in Tonsillar Tissues from Children with Chronic Adenotonsillar Disease

Chronic tonsillar diseases are an important health problem, leading to large numbers of surgical procedures worldwide. Little is known about pathogenesis of these diseases. In order to investigate the role of respiratory viruses in chronic adenotonsillar diseases, we developed a cross-sectional study to determine the rates of viral detections of common respiratory viruses detected by TaqMan real time PCR (qPCR) in nasopharyngeal secretions, tonsillar tissues and peripheral blood from 121 children with chronic tonsillar diseases, without symptoms of acute respiratory infections. At least one respiratory virus was detected in 97.5% of patients. The viral co-infection rate was 69.5%. The most frequently detected viruses were human adenovirus in 47.1%, human enterovirus in 40.5%, human rhinovirus in 38%, human bocavirus in 29.8%, human metapneumovirus in 17.4% and human respiratory syncytial virus in 15.7%. Results of qPCR varied widely between sample sites: human adenovirus, human bocavirus and human enterovirus were predominantly detected in tissues, while human rhinovirus was more frequently detected in secretions. Rates of virus detection were remarkably high in tonsil tissues: over 85% in adenoids and close to 70% in palatine tonsils. In addition, overall virus detection rates were higher in more hypertrophic than in smaller adenoids (p = 0.05), and in the particular case of human enteroviruses, they were detected more frequently (p = 0.05) in larger palatine tonsils than in smaller ones. While persistence/latency of DNA viruses in tonsillar tissues has been documented, such is not the case of RNA viruses. Respiratory viruses are highly prevalent in adenoids and palatine tonsils of patients with chronic tonsillar diseases, and persistence of these viruses in tonsils may stimulate chronic inflammation and play a role in the pathogenesis of these diseases.

Cluster-based Intrusion Detection (CBID) architecture for mobile ad hoc networks

The ad hoc networks are vulnerable to attacks due to distributed nature and lack of infrastructure. Intrusion detection systems (IDS) provide audit and monitoring capabilities that offer the local security to a node and help to perceive the specific trust level of other nodes. The clustering protocols can be taken as an additional advantage in these processing constrained networks to collaboratively detect intrusions with less power usage and minimal overhead. Existing clustering protocols are not suitable for intrusion detection purposes, because they are linked with the routes. The route establishment and route renewal affects the clusters and as a consequence, the processing and traffic overhead increases due to instability of clusters. The ad hoc networks are battery and power constraint, and therefore a trusted monitoring node should be available to detect and respond against intrusions in time. This can be achieved only if the clusters are stable for a long period of time. If the clusters are regularly changed due to routes, the intrusion detection will not prove to be effective. Therefore, a generalized clustering algorithm has been proposed that can run on top of any routing protocol and can monitor the intrusions constantly irrespective of the routes. The proposed simplified clustering scheme has been used to detect intrusions, resulting in high detection rates and low processing and memory overhead irrespective of the routes, connections, traffic types and mobility of nodes in the network. Clustering is also useful to detect intrusions collaboratively since an individual node can neither detect the malicious node alone nor it can take action against that node on its own.

Detection of a putative hemolysin operon, hhdBA, of Haemophilus parasuis from pigs with Glasser disease

The aim of the current study was to investigate whether polymerase chain reaction amplification of 16S ribosomal (r)RNA and a putative hemolysin gene operon, hhdBA, can be used to monitor live pigs for the presence of Haemophilus parasuis and predict the virulence of the strains present. Nasal cavity swabs were taken from 30 live, healthy, 1- to 8-week-old pigs on a weekly cycle from a commercial Thai nursery pig herd. A total of 27 of these pigs (90%) tested positive for H. parasuis as early as week 1 of age. None of the H. parasuis-positive samples from healthy pigs was positive for the hhdBA genes. At the same pig nursery, swab samples from nasal cavity, tonsil, trachea, and lung, and exudate samples from pleural/peritoneal cavity were taken from 30 dead pigs displaying typical pathological lesions consistent with Glasser disease. Twenty-two of 140 samples (15.7%) taken from 30 diseased pigs yielded a positive result for H. parasuis. Samples from the exudate (27%) yielded the most positive results, followed by lung, tracheal swab, tonsil, and nasal swab, respectively. Out of 22 positive samples, 12 samples (54.5%) harbored hhdA and/or hhdB genes. Detection rates of hhdA were higher than hhdB. None of the H. parasuis-positive samples taken from nasal cavity of diseased pigs tested positive for hhdBA genes. More work is required to determine if the detection of hhdBA genes is useful for identifying the virulence potential of H. parasuis field isolates.

False Error Study of On-line Soft Error Detection Mechanisms

With technology scaling, vulnerability to soft errors in random logic is increasing. There is a need for on-line error detection and protection for logic gates even at sea level. The error checker is the key element for an on-line detection mechanism. We compare three different checkers for error detection from the point of view of area, power and false error detection rates. We find that the double sampling checker (used in Razor), is the simplest and most area and power efficient, but suffers from very high false detection rates of 1.15 times the actual error rates. We also find that the alternate approaches of triple sampling and integrate and sample method (I&S) can be designed to have zero false detection rates, but at an increased area, power and implementation complexity. The triple sampling method has about 1.74 times the area and twice the power as compared to the Double Sampling method and also needs a complex clock generation scheme. The I&S method needs about 16% more power with 0.58 times the area as double sampling, but comes with more stringent implementation constraints as it requires detection of small voltage swings.

A Perspective to Adopt Continuous Dynamic Cognition for Malicious Node Detection in Heterogeneous Networks

The current day networks use Proactive networks for adaption to the dynamic scenarios. The use of cognition technique based on the Observe, Orient, Decide and Act loop (OODA) is proposed to construct proactive networks. The network performance degradation in knowledge acquisition and malicious node presence is a problem that exists. The use of continuous time dynamic neural network is considered to achieve cognition. The variance in service rates of user nodes is used to detect malicious activity in heterogeneous networks. The improved malicious node detection rates are proved through the experimental results presented in this paper. (C) 2015 The Authors. Published by Elsevier B.V.

Co-occurrence flow for pedestrian detection

The last few years have seen considerable progress in pedestrian detection. Recent work has established a combination of oriented gradients and optic flow as effective features although the detection rates are still unsatisfactory for practical use. This paper introduces a new type of motion feature, the co-occurrence flow (CoF). The advance is to capture relative movements of different parts of the entire body, unlike existing motion features which extract internal motion in a local fashion. Through evaluations on the TUD-Brussels pedestrian dataset, we show that our motion feature based on co-occurrence flow contributes to boost the performance of existing methods. © 2011 IEEE.

Improved Detection of Mycobacterium bovis in Bovine Tissues Using Immunomagnetic Separation Approaches

Immunomagnetic separation (IMS) represents a simple but effective method of selectively capturing and concentrating Mycobacterium bovis, the causative agent of bovine tuberculosis (bTB), from tissue samples. It is a physical cell separation technique that does not impact cell viability, unlike traditional chemical decontamination prior to culture. IMS is performed with paramagnetic beads coated with M. bovis-specific antibody and peptide binders. Once captured by IMS, M. bovis cells can be detected by either PCR or cultural detection methods. Increased detection rates of M. bovis, particularly from non-visibly lesioned lymph node tissues from bTB reactor animals, have recently been reported when IMS-based methods were employed.

Farmers' attitudes towards techniques for improving oestrus detection in dairy herds in South West England

Unidentified heats contribute to declining fertility rates in English dairy herds. Several techniques have been advocated to improve heat detection rates. Despite demonstrable technical efficacy and cost-effectiveness, uptake is low. A study in South West England used the Theory of Reasoned Action (TORA) to explore dairy farmers' attitudes and beliefs towards heat detection techniques. Few farmers were convinced that following prescribed observation times, milk progesterone testing and using pedometers would fit their system or improve on their current heat detection practices. Perceived difficulty of using a technique was not a constraint on adoption. Without promotion that addresses identified barriers and drivers to adoption, little change in current practice can be expected. (c) 2006 Elsevier B.V. All rights reserved.

Increasing detection rate of user-to-root attacks using genetic algorithms

An extensive set of machine learning and pattern classification techniques trained and tested on KDD dataset failed in detecting most of the user-to-root attacks. This paper aims to provide an approach for mitigating negative aspects of the mentioned dataset, which led to low detection rates. Genetic algorithm is employed to implement rules for detecting various types of attacks. Rules are formed of the features of the dataset identified as the most important ones for each attack type. In this way we introduce high level of generality and thus achieve high detection rates, but also gain high reduction of the system training time. Thenceforth we re-check the decision of the user-to- root rules with the rules that detect other types of attacks. In this way we decrease the false-positive rate. The model was verified on KDD 99, demonstrating higher detection rates than those reported by the state- of-the-art while maintaining low false-positive rate.

Why are fruits colorful? The relative importance of achromatic and chromatic contrasts for detection by birds

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The performance of computer-aided detection when analyzing prior mammograms of newly detected breast cancers with special focus on the time interval from initial imaging to detection

PURPOSE: The clinical role of CAD systems to detect breast cancer, which have not been on cancer containing mammograms not detected by the radiologist was proven retrospectively. METHODS: All patients from 1992 to 2005 with a histologically verified malignant breast lesion and a mammogram at our department, were analyzed in retrospect focussing on the time of detection of the malignant lesion. All prior mammograms were analyzed by CAD (CADx, USA). The resulting CAD printout was matched with the cancer containing images yielding to the radiological diagnosis of breast cancer. CAD performance, sensitivity as well as the association of CAD and radiological features were analyzed. RESULTS: 278 mammograms fulfilled the inclusion criteria. 111 cases showed a retrospectively visible lesion (71 masses, 23 single microcalcification clusters, 16 masses with microcalcifications, in one case two microcalcification clusters). 54/87 masses and 34/41 microcalcifications were detected by CAD. Detection rates varied from 9/20 (ACR 1) to 5/7 (ACR 4) (45% vs. 71%). The detection of microcalcifications was not influenced by breast tissue density. CONCLUSION: CAD might be useful in an earlier detection of subtle breast cancer cases, which might remain otherwise undetected.

Evaluation and Comparison of Anatomical Landmark Detection Methods for Cephalometric X-Ray Images: A Grand Challenge

Cephalometric analysis is an essential clinical and research tool in orthodontics for the orthodontic analysis and treatment planning. This paper presents the evaluation of the methods submitted to the Automatic Cephalometric X-Ray Landmark Detection Challenge, held at the IEEE International Symposium on Biomedical Imaging 2014 with an on-site competition. The challenge was set to explore and compare automatic landmark detection methods in application to cephalometric X-ray images. Methods were evaluated on a common database including cephalograms of 300 patients aged six to 60 years, collected from the Dental Department, Tri-Service General Hospital, Taiwan, and manually marked anatomical landmarks as the ground truth data, generated by two experienced medical doctors. Quantitative evaluation was performed to compare the results of a representative selection of current methods submitted to the challenge. Experimental results show that three methods are able to achieve detection rates greater than 80% using the 4 mm precision range, but only one method achieves a detection rate greater than 70% using the 2 mm precision range, which is the acceptable precision range in clinical practice. The study provides insights into the performance of different landmark detection approaches under real-world conditions and highlights achievements and limitations of current image analysis techniques.