Laryngoscopic Image Stitching for View Enhancement and Documentation - First Experiences

One known problem within laryngoscopy is the spatially limited view onto the hypopharynx and the larynx through the endoscope. To examine the complete larynx and hypopharynx, the laryngoscope can be rotated about its main axis, and hence the physician obtains a complete view. If such examinations are captured using endoscopic video, the examination can be reviewed in detail at a later time. Nevertheless, in order to document the examination with a single representative image, a panorama image can be computed for archiving and enhanced documentation. Twenty patients with various clinical findings were examined with a 70 rigid laryngoscope, and the video sequences were digitally stored. The image sequence for each patient was then post-processed using an image stitching tool based on SIFT features, the RANSAC approach and blending. As a result, endoscopic panorama images of the larynx and pharynx were obtained for each video sequence. The proposed approach of image stitching for laryngoscopic video sequences offers a new tool for enhanced visual examination and documentation of morphologic characteristics of the larynx and the hypopharynx

a targeted metabolomic approach in two German prospective cohorts

Metabolomic approaches in prospective cohorts may offer a unique snapshot into early metabolic perturbations that are associated with a higher risk of cardiovascular diseases (CVD) in healthy people. We investigated the association of 105 serum metabolites, including acylcarnitines, amino acids, phospholipids and hexose, with risk of myocardial infarction (MI) and ischemic stroke in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam (27,548 adults) and Heidelberg (25,540 adults) cohorts. Using case-cohort designs, we measured metabolites among individuals who were free of CVD and diabetes at blood draw but developed MI (n = 204 and n = 228) or stroke (n = 147 and n = 121) during follow-up (mean, 7.8 and 7.3 years) and among randomly drawn subcohorts (n = 2214 and n = 770). We used Cox regression analysis and combined results using meta-analysis. Independent of classical CVD risk factors, ten metabolites were associated with risk of MI in both cohorts, including sphingomyelins, diacyl-phosphatidylcholines and acyl-alkyl- phosphatidylcholines with pooled relative risks in the range of 1.21–1.40 per one standard deviation increase in metabolite concentrations. The metabolites showed positive correlations with total- and LDL-cholesterol (r ranged from 0.13 to 0.57). When additionally adjusting for total-, LDL- and HDL- cholesterol, triglycerides and C-reactive protein, acyl-alkyl- phosphatidylcholine C36:3 and diacyl-phosphatidylcholines C38:3 and C40:4 remained associated with risk of MI. When added to classical CVD risk models these metabolites further improved CVD prediction (c-statistics increased from 0.8365 to 0.8384 in EPIC-Potsdam and from 0.8344 to 0.8378 in EPIC- Heidelberg). None of the metabolites was consistently associated with stroke risk. Alterations in sphingomyelin and phosphatidylcholine metabolism, and particularly metabolites of the arachidonic acid pathway are independently associated with risk of MI in healthy adults

Effectiveness and efficiency of primary care based case management for chronic diseases: rationale and design of a systematic review and meta-analysis of randomized and non-randomized trials [CRD32009100316]

Contains fulltext : 88751.pdf (publisher's version ) (Open Access)BACKGROUND: Case management is an important component of structured and evidence-based primary care for chronically ill patients. Its effectiveness and efficiency has been evaluated in numerous clinical trials. This protocol describes aims and methods of a systematic review of research on the effectiveness and efficiency of case management in primary care. METHODS/DESIGN: According to this protocol Medline, Embase, CINAHL, PsychInfo, the Cochrane Central Register of Controlled trials, DARE, NHS EED, Science Citation Index, The Royal College of Nursing Database, Dissertation Abstracts, registers of clinical trials and the reference lists of retrieved articles will be searched to identify reports on randomized and non-randomized controlled trials of case management interventions in a primary care setting without limitations on language or publication date. We will further ask experts in the field to avoid missing relevant evidence. Study inclusion and data extraction will be performed independently by two reviewers. After assessing risk of bias according to predefined standards, included studies will be described qualitatively. Subgroup analyses are planned for different chronic diseases and intervention strategies. If appropriate, a quantitative synthesis of data will be performed to provide conclusive evidence about the effectiveness and efficiency of primary care based case management in chronic care. REVIEW REGISTRATION: Centre for Reviews and Dissemination (University of York): CRD32009100316

A rare mutation in SMAD9 associated with high bone mass identifies the SMAD-dependent BMP signalling pathway as a potential anabolic target for osteoporosis

Novel anabolic drug targets are needed to treat osteoporosis. Having established a large national cohort with unexplained high bone mass (HBM), we aimed to identify a novel monogenic cause of HBM and provide insight into a regulatory pathway potentially amenable to therapeutic intervention. We investigated a pedigree with unexplained HBM in whom previous sequencing had excluded known causes of monogenic HBM. Whole exome sequencing identified a rare (minor allele frequency 0.0023), highly evolutionarily conserved missense mutation in SMAD9 (c.65T>C, p.Leu22Pro) segregating with HBM in this autosomal dominant family. The same mutation was identified in another two unrelated individuals both with HBM. In silico protein modeling predicts the mutation severely disrupts the MH1 DNA-binding domain of SMAD9. Affected individuals have bone mineral density (BMD) Z-scores +3 to +5, mandible enlargement, a broad frame, torus palatinus/mandibularis, pes planus, increased shoe size, and a tendency to sink when swimming. Peripheral quantitative computed tomography (pQCT) measurement demonstrates increased trabecular volumetric BMD and increased cortical thickness conferring greater predicted bone strength; bone turnover markers are low/normal. Notably, fractures and nerve compression are not found. Both genome-wide and gene-based association testing involving estimated BMD measured at the heel in 362,924 white British subjects from the UK Biobank Study showed strong associations with SMAD9 (P-GWAS = 6 x 10(-16); P-GENE = 8 x 10(-17)). Furthermore, we found Smad9 to be highly expressed in both murine cortical bone-derived osteocytes and skeletal elements of zebrafish larvae. Our findings support SMAD9 as a novel HBM gene and a potential novel osteoanabolic target for osteoporosis therapeutics. SMAD9 is thought to inhibit bone morphogenetic protein (BMP)-dependent target gene transcription to reduce osteoblast activity. Thus, we hypothesize SMAD9 c.65T>C is a loss-of-function mutation reducing BMP inhibition. Lowering SMAD9 as a potential novel anabolic mechanism for osteoporosis therapeutics warrants further investigation. (c) 2019 The Authors. Journal of Bone and Mineral Research published by American Society for Bone and Mineral Research

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe

Joint Analysis Of Psychiatric Disorders Increases Accuracy Of Risk Prediction For Schizophrenia, Bipolar Disorder, And Major Depressive Disorder

Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk

Image based reconstruction for cystoscopy

This paper summarizes our initial efforts to reconstruct the urinary bladder from endoscopic images acquired in the clinical routine. We found that up to now, only very few attempts have been reported which achieve a true 3D reconstruction of the human bladder. One promising approach which yields a geometric reconstruction up to scale from a monocular stream of images is highlighted and our initial results obtained from adapting the method for its use in clinical cystoscopy are presented