Comparative evaluation of strain ratio on sonographic elastography and T2* values on 3 Tesla magnetic resonance imaging in differentiating malignant from benign axillary lymph nodes in breast cancer

Background: The study aimed to assess whether strain ratio and T2* values can improve the sensitivity and specificity of differentiating metastatic from benign axillary lymph nodes in breast cancer patients taking histopathology as reference standard.Methods: The study was done on 43 patients. A multi-echo transverse T2*W MR sequence was obtained with TE = 0.9- 1.5 ms, TR=37.2 ms and flip angle = 25°. Sonographic elastography was done using high frequency linear probe (L3-16 MHz). Manual selection of the region of interest was done on suspicious lymph nodes for calculation of T2* values and strain ratio. ROC curves were obtained for various T2* and strain ratio values in comparison to histopathological findings as gold standard.Results: Correlation with histopathology was better with T2* values than strain ratio. The sensitivity and specificity were calculated using cut off values obtained from ROC curve (31.225 ms for T2* value and 1.85 for SR) and were 70.37%, 68.75% for strain ratio and 96.29%, 93.75% for T2* value respectively. The positive predictive value and negative predictive value were also assessed, values being higher for T2* than strain ratio. Comparison of areas under ROC curve was statistically significant with p=0.018.Conclusions: T2* can be used as a potential biomarker for differentiating metastatic from benign axillary lymph nodes owing to its high sensitivity, specificity and relative ease of performance. Quantitative assessment of changes in T2* values may allow more objective analysis of signal changes with significant differences between benign and malignant lymph nodes, even in case of partial infiltration.

Significance of Correct Diagnosis of Odontogenic Extraoral Sinus: A Report Of Two Cases

Cutaneous draining sinus tracts of odontogenic origin often are a diagnostic challenge. A delay in correctly diagnosing these types of lesions can result in unnecessary antibiotic therapy and surgical treatment. This case report presents the clinical course of two cases with extra-oral sinus tract formation, from diagnosis and treatment to short-term follow-up and evaluation. These facial lesions were initially misdiagnosed as lesions of non-odontogenic origin. Later on an odontogenic cause was identified and endodontic intervention resulted in resolution of the problem, confirming the initial misdiagnosis

Comparative Assessment of Some Target Detection Algorithms for Hyperspectral Images

Target detection is of particular interest in hyperspectral image analysis as many unknown and subtle signals (spectral response) unresolved by multispectral sensors can be discovered in hyperspectral images. The detection of signals in the form of small objects and targets from hyperspectral sensors has a wide range of applications both civilian and military. It has been observed that a number of target detection algorithms are in vogue; each has its own advantages and disadvantages and assumptions. The selection of a particular algorithm may depend on the amount of information available as per the requirement of the algorithm, application area, the computational complexity etc. In the present study, three algorithms, namely, orthogonal subspace projection (OSP), constrained energy minimization (CEM) and a nonlinear version of OSP called kernel orthogonal subspace projection (KOSP), have been investigated for target detection from hyperspectral remote sensing data. The efficacy of algorithms has been examined over two different hyperspectral datasets which include a synthetic image and an AVIRIS image. The quality of target detection from these algorithms has been evaluated through visual interpretation as well as through receiver operating characteristic (ROC) curves. The performance of OSP algorithm has been found to be better than or comparable to CEM algorithm. However, KOSP out performs both the algorithms.Defence Science Journal, 2013, 63(1), pp.53-62, DOI:http://dx.doi.org/10.14429/dsj.63.376

Analysis of maternal deaths over a period of three years at a tertiary care centre of Uttarakhand, India

Background: Globally, about 800 women die every day of preventable causes related to pregnancy and childbirth; 20 per cent of these women are from India. The study is aimed at evaluating maternal deaths over a period of three years at a tertiary care centre of Dehradun, India.Methods: This was a retrospective study conducted in the Department of Obstetrics and Gynecology at SGRRIMHS, Dehradun. The case record files of all maternal deaths from January 2015 to December 2017 was obtained from medical record section of the hospital. Maternal age, parity, educational status, antenatal registration, mode of delivery, admission death interval and causes of each maternal death was noted and analysed statistically.Results: There were 48 maternal deaths from January 2015 to December 2017.Maximum deaths were in the age group of 21-25 years. The maternal mortality ratio over a period of three years was 671 per one lac live births. Most of the maternal deaths were due to direct causes like hemorrhage , eclampsia followed by sepsis.Conclusions: Most of the maternal deaths are preventable. High risk cases should be identified at root level and early referral should be the moto. All women need access to antenatal care in pregnancy, skilled care during childbirth, and care and support in the weeks after childbirth. To avoid maternal deaths, unwanted and too-early pregnancies should be avoided. All women, including adolescents, should have access to contraception, safe abortion services to the full extent of the law, and quality post-abortion care. It is particularly important that all births are attended by skilled health professionals, as timely management and treatment can make the difference between life and death for both the mother and the baby

Detecting Signals of Seasonal Influenza Severity Through Age Dynamics

BACKGROUND: Measures of population-level influenza severity are important for public health planning, but estimates are often based on case-fatality and case-hospitalization risks, which require multiple data sources, are prone to surveillance biases, and are typically unavailable in the early stages of an outbreak. To address the limitations of traditional indicators, we propose a novel severity index based on influenza age dynamics estimated from routine physician diagnosis data that can be used retrospectively and for early warning. METHODS: We developed a quantitative \u27ground truth\u27 severity benchmark that synthesizes multiple traditional severity indicators from publicly available influenza surveillance data in the United States. Observing that the age distribution of cases may signal severity early in an epidemic, we constructed novel retrospective and early warning severity indexes based on the relative risk of influenza-like illness (ILI) among working-age adults to that among school-aged children using weekly outpatient medical claims. We compared our relative risk-based indexes to the composite benchmark and estimated seasonal severity for flu seasons from 2001-02 to 2008-09 at the national and state levels. RESULTS: The severity classifications made by the benchmark were not uniquely captured by any single contributing metric, including pneumonia and influenza mortality; the influenza epidemics of 2003-04 and 2007-08 were correctly identified as the most severe of the study period. The retrospective index was well correlated with the severity benchmark and correctly identified the two most severe seasons. The early warning index performance varied, but it projected 2007-08 as relatively severe 10 weeks prior to the epidemic peak. Influenza severity varied significantly among states within seasons, and four states were identified as possible early warning sentinels for national severity. CONCLUSIONS: Differences in age patterns of ILI may be used to characterize seasonal influenza severity in the United States in real-time and in a spatially resolved way. Future research on antigenic changes among circulating viruses, pre-existing immunity, and changing contact patterns may better elucidate the mechanisms underlying these indexes. Researchers and practitioners should consider the use of composite or ILI-based severity metrics in addition to traditional severity measures to inform epidemiological understanding and situational awareness in future seasonal outbreaks

The Shifting Demographic Landscape of Pandemic Influenza

Shweta Bansal is with Pennsylvania State University and NIH, Babak Pourbohloul is with British Columbia Centre for Disease Control and University of British Columbia, Nathaniel Hupert is with Weill Cornell Medical College and CDC, Bryan Grenfell is with Princeton University, Lauren Ancel Meyers is with UT Austin and Santa Fe Institute.Background -- As Pandemic (H1N1) 2009 influenza spreads around the globe, it strikes school-age children more often than adults. Although there is some evidence of pre-existing immunity among older adults, this alone may not explain the significant gap in age-specific infection rates. Methods and Findings -- Based on a retrospective analysis of pandemic strains of influenza from the last century, we show that school-age children typically experience the highest attack rates in primarily naive populations, with the burden shifting to adults during the subsequent season. Using a parsimonious network-based mathematical model which incorporates the changing distribution of contacts in the susceptible population, we demonstrate that new pandemic strains of influenza are expected to shift the epidemiological landscape in exactly this way. Conclusions -- Our analysis provides a simple demographic explanation for the age bias observed for H1N1/09 attack rates, and suggests that this bias may shift in coming months. These results have significant implications for the allocation of public health resources for H1N1/09 and future influenza pandemics.This work was supported by the Research and Policy for Infectious Disease Dynamics (RAPIDD) program of the Science and Technology Directorate, Department of Homeland Security, and the Fogarty International Center, National Institutes of Health (NIH); grants from the James F. McDonnell Foundation, National Science Foundation (DEB-0749097), and NIH Models of Infectious Disease Agent Study (MIDAS) (U01-GM087719-01) to L.A.M.; and support from the Canadian Institutes of Health Research (PTL97125 and PAP93425) and the Michael Smith Foundation for Health Research to B.P. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Biological Sciences, School o