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Pesquisa : L01.224.050.375.480 [Categoria DeCS]
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  1 / 1113 MEDLINE  
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[PMID]:29244012
[Au] Autor:Jelínek J; Skoda P; Hoksza D
[Ad] Endereço:Department of Software Engineering, Faculty of Mathematics and Physics, Charles University, Ke Karlovu 3, Prague 2, Czech Republic. jelinek@ksi.mff.cuni.cz.
[Ti] Título:Utilizing knowledge base of amino acids structural neighborhoods to predict protein-protein interaction sites.
[So] Source:BMC Bioinformatics;18(Suppl 15):492, 2017 Dec 06.
[Is] ISSN:1471-2105
[Cp] País de publicação:England
[La] Idioma:eng
[Ab] Resumo:BACKGROUND: Protein-protein interactions (PPI) play a key role in an investigation of various biochemical processes, and their identification is thus of great importance. Although computational prediction of which amino acids take part in a PPI has been an active field of research for some time, the quality of in-silico methods is still far from perfect. RESULTS: We have developed a novel prediction method called INSPiRE which benefits from a knowledge base built from data available in Protein Data Bank. All proteins involved in PPIs were converted into labeled graphs with nodes corresponding to amino acids and edges to pairs of neighboring amino acids. A structural neighborhood of each node was then encoded into a bit string and stored in the knowledge base. When predicting PPIs, INSPiRE labels amino acids of unknown proteins as interface or non-interface based on how often their structural neighborhood appears as interface or non-interface in the knowledge base. We evaluated INSPiRE's behavior with respect to different types and sizes of the structural neighborhood. Furthermore, we examined the suitability of several different features for labeling the nodes. Our evaluations showed that INSPiRE clearly outperforms existing methods with respect to Matthews correlation coefficient. CONCLUSION: In this paper we introduce a new knowledge-based method for identification of protein-protein interaction sites called INSPiRE. Its knowledge base utilizes structural patterns of known interaction sites in the Protein Data Bank which are then used for PPI prediction. Extensive experiments on several well-established datasets show that INSPiRE significantly surpasses existing PPI approaches.
[Mh] Termos MeSH primário: Aminoácidos
Bases de Conhecimento
Mapeamento de Interação de Proteínas/métodos
Proteínas
Software
[Mh] Termos MeSH secundário: Aminoácidos/química
Aminoácidos/metabolismo
Biologia Computacional
Bases de Dados de Proteínas
Modelos Estatísticos
Proteínas/química
Proteínas/metabolismo
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Nm] Nome de substância:
0 (Amino Acids); 0 (Proteins)
[Em] Mês de entrada:1803
[Cu] Atualização por classe:180307
[Lr] Data última revisão:
180307
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:171216
[St] Status:MEDLINE
[do] DOI:10.1186/s12859-017-1921-4


  2 / 1113 MEDLINE  
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[PMID]:28453681
[Au] Autor:Marks C; Nowak J; Klostermann S; Georges G; Dunbar J; Shi J; Kelm S; Deane CM
[Ad] Endereço:Department of Statistics, University of Oxford, Oxford, UK.
[Ti] Título:Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction.
[So] Source:Bioinformatics;33(9):1346-1353, 2017 05 01.
[Is] ISSN:1367-4811
[Cp] País de publicação:England
[La] Idioma:eng
[Ab] Resumo:Motivation: Loops are often vital for protein function, however, their irregular structures make them difficult to model accurately. Current loop modelling algorithms can mostly be divided into two categories: knowledge-based, where databases of fragments are searched to find suitable conformations and ab initio, where conformations are generated computationally. Existing knowledge-based methods only use fragments that are the same length as the target, even though loops of slightly different lengths may adopt similar conformations. Here, we present a novel method, Sphinx, which combines ab initio techniques with the potential extra structural information contained within loops of a different length to improve structure prediction. Results: We show that Sphinx is able to generate high-accuracy predictions and decoy sets enriched with near-native loop conformations, performing better than the ab initio algorithm on which it is based. In addition, it is able to provide predictions for every target, unlike some knowledge-based methods. Sphinx can be used successfully for the difficult problem of antibody H3 prediction, outperforming RosettaAntibody, one of the leading H3-specific ab initio methods, both in accuracy and speed. Availability and Implementation: Sphinx is available at http://opig.stats.ox.ac.uk/webapps/sphinx. Contact: deane@stats.ox.ac.uk. Supplementary information: Supplementary data are available at Bioinformatics online.
[Mh] Termos MeSH primário: Biologia Computacional/métodos
Bases de Conhecimento
Modelos Moleculares
Conformação Proteica
Software
[Mh] Termos MeSH secundário: Algoritmos
Animais
Anticorpos/química
Anticorpos/metabolismo
[Pt] Tipo de publicação:JOURNAL ARTICLE; RESEARCH SUPPORT, NON-U.S. GOV'T
[Nm] Nome de substância:
0 (Antibodies)
[Em] Mês de entrada:1801
[Cu] Atualização por classe:180308
[Lr] Data última revisão:
180308
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170429
[St] Status:MEDLINE
[do] DOI:10.1093/bioinformatics/btw823


  3 / 1113 MEDLINE  
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[PMID]:29221443
[Au] Autor:Yao Y; Gui R; Liu Q; Yi M; Deng H
[Ad] Endereço:Department of Physics, College of Science, Huazhong Agricultural University, Wuhan, 430070, China.
[Ti] Título:Diverse effects of distance cutoff and residue interval on the performance of distance-dependent atom-pair potential in protein structure prediction.
[So] Source:BMC Bioinformatics;18(1):542, 2017 Dec 08.
[Is] ISSN:1471-2105
[Cp] País de publicação:England
[La] Idioma:eng
[Ab] Resumo:BACKGROUND: As one of the most successful knowledge-based energy functions, the distance-dependent atom-pair potential is widely used in all aspects of protein structure prediction, including conformational search, model refinement, and model assessment. During the last two decades, great efforts have been made to improve the reference state of the potential, while other factors that also strongly affect the performance of the potential have been relatively less investigated. RESULTS: Based on different distance cutoffs (from 5 to 22 Å) and residue intervals (from 0 to 15) as well as six different reference states, we constructed a series of distance-dependent atom-pair potentials and tested them on several groups of structural decoy sets collected from diverse sources. A comprehensive investigation has been performed to clarify the effects of distance cutoff and residue interval on the potential's performance. Our results provide a new perspective as well as a practical guidance for optimizing distance-dependent statistical potentials. CONCLUSIONS: The optimal distance cutoff and residue interval are highly related with the reference state that the potential is based on, the measurements of the potential's performance, and the decoy sets that the potential is applied to. The performance of distance-dependent statistical potential can be significantly improved when the best statistical parameters for the specific application environment are adopted.
[Mh] Termos MeSH primário: Biologia Computacional/métodos
Conformação Proteica
Proteínas/química
Proteínas/ultraestrutura
[Mh] Termos MeSH secundário: Bases de Conhecimento
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Nm] Nome de substância:
0 (Proteins)
[Em] Mês de entrada:1803
[Cu] Atualização por classe:180306
[Lr] Data última revisão:
180306
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:171210
[St] Status:MEDLINE
[do] DOI:10.1186/s12859-017-1983-3


  4 / 1113 MEDLINE  
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[PMID]:28973463
[Au] Autor:Peng S; Yang S; Bo X; Li F
[Ad] Endereço:College of Computer Science and Electronic Engineering & National Supercomputer Centre in Changsha, Hunan University, Changsha 410082, China.
[Ti] Título:paraGSEA: a scalable approach for large-scale gene expression profiling.
[So] Source:Nucleic Acids Res;45(17):e155, 2017 Sep 29.
[Is] ISSN:1362-4962
[Cp] País de publicação:England
[La] Idioma:eng
[Ab] Resumo:More studies have been conducted using gene expression similarity to identify functional connections among genes, diseases and drugs. Gene Set Enrichment Analysis (GSEA) is a powerful analytical method for interpreting gene expression data. However, due to its enormous computational overhead in the estimation of significance level step and multiple hypothesis testing step, the computation scalability and efficiency are poor on large-scale datasets. We proposed paraGSEA for efficient large-scale transcriptome data analysis. By optimization, the overall time complexity of paraGSEA is reduced from O(mn) to O(m+n), where m is the length of the gene sets and n is the length of the gene expression profiles, which contributes more than 100-fold increase in performance compared with other popular GSEA implementations such as GSEA-P, SAM-GS and GSEA2. By further parallelization, a near-linear speed-up is gained on both workstations and clusters in an efficient manner with high scalability and performance on large-scale datasets. The analysis time of whole LINCS phase I dataset (GSE92742) was reduced to nearly half hour on a 1000 node cluster on Tianhe-2, or within 120 hours on a 96-core workstation. The source code of paraGSEA is licensed under the GPLv3 and available at http://github.com/ysycloud/paraGSEA.
[Mh] Termos MeSH primário: Algoritmos
Biologia Computacional/métodos
Perfilação da Expressão Gênica/estatística & dados numéricos
Transcriptoma
[Mh] Termos MeSH secundário: Benchmarking
Bases de Dados Genéticas
Conjuntos de Dados como Assunto
Seres Humanos
Bases de Conhecimento
Análise de Sequência com Séries de Oligonucleotídeos
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1710
[Cu] Atualização por classe:171017
[Lr] Data última revisão:
171017
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:171004
[St] Status:MEDLINE
[do] DOI:10.1093/nar/gkx679


  5 / 1113 MEDLINE  
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[PMID]:28892437
[Au] Autor:Savoia E; Lin L; Bernard D; Klein N; James LP; Guicciardi S
[Ad] Endereço:Elena Savoia, Leesa Lin, Dottie Bernard, Noah Klein, Lyndon P. James, and Stefano Guicciardi are with the Emergency Preparedness Research, Evaluation & Practice (EPREP) Program, Division of Policy Translation & Leadership Development, Harvard T. H. Chan School of Public Health, Boston, MA.
[Ti] Título:Public Health System Research in Public Health Emergency Preparedness in the United States (2009-2015): Actionable Knowledge Base.
[So] Source:Am J Public Health;107(S2):e1-e6, 2017 Sep.
[Is] ISSN:1541-0048
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:BACKGROUND: In 2008, the Institute of Medicine released a letter report identifying 4 research priority areas for public health emergency preparedness in public health system research: (1) enhancing the usefulness of training, (2) improving timely emergency communications, (3) creating and maintaining sustainable response systems, and (4) generating effectiveness criteria and metrics. OBJECTIVES: To (1) identify and characterize public health system research in public health emergency preparedness produced in the United States from 2009 to 2015, (2) synthesize research findings and assess the level of confidence in these findings, and (3) describe the evolution of knowledge production in public health emergency preparedness system research. Search Methods and Selection Criteria. We reviewed and included the titles and abstracts of 1584 articles derived from MEDLINE, EMBASE, and gray literature databases that focused on the organizational or financial aspects of public health emergency preparedness activities and were grounded on empirical studies. DATA COLLECTION AND ANALYSIS: We included 156 articles. We appraised the quality of the studies according to the study design. We identified themes during article analysis and summarized overall findings by theme. We determined level of confidence in the findings with the GRADE-CERQual tool. MAIN RESULTS: Thirty-one studies provided evidence on how to enhance the usefulness of training. Results demonstrated the utility of drills and exercises to enhance decision-making capabilities and coordination across organizations, the benefit of cross-sector partnerships for successfully implementing training activities, and the value of integrating evaluation methods to support training improvement efforts. Thirty-six studies provided evidence on how to improve timely communications. Results supported the use of communication strategies that address differences in access to information, knowledge, attitudes, and practices across segments of the population as well as evidence on specific communication barriers experienced by public health and health care personnel. Forty-eight studies provided evidence on how to create and sustain preparedness systems. Results included how to build social capital across organizations and citizens and how to develop sustainable and useful planning efforts that maintain flexibility and rely on available medical data. Twenty-six studies provided evidence on the usefulness of measurement efforts, such as community and organizational needs assessments, and new methods to learn from the response to critical incidents. CONCLUSIONS: In the United States, the field of public health emergency preparedness system research has been supported by the US Centers for Disease Control and Prevention since the release of the 2008 Institute of Medicine letter report. The first definition of public health emergency preparedness appeared in 2007, and before 2008 there was a lack of research and empirical evidence across all 4 research areas identified by the Institute of Medicine. This field can be considered relatively new compared with other research areas in public health; for example, tobacco control research can rely on more than 70 years of knowledge production. However, this review demonstrates that, during the past 7 years, public health emergency preparedness system research has evolved from generic inquiry to the analysis of specific interventions with more empirical studies. Public Health Implications: The results of this review provide an evidence base for public health practitioners responsible for enhancing key components of preparedness and response such as communication, training, and planning efforts.
[Mh] Termos MeSH primário: Pesquisa Biomédica/normas
Centers for Disease Control and Prevention (U.S.)/organização & administração
Planejamento em Desastres/organização & administração
National Academies of Science, Engineering, and Medicine (U.S.) Health and Medicine Division/organização & administração
Saúde Pública/normas
Projetos de Pesquisa/normas
[Mh] Termos MeSH secundário: Defesa Civil
Comunicação
Seres Humanos
Bases de Conhecimento
Determinação de Necessidades de Cuidados de Saúde
Objetivos Organizacionais
Estados Unidos
[Pt] Tipo de publicação:JOURNAL ARTICLE; REVIEW
[Em] Mês de entrada:1709
[Cu] Atualização por classe:170920
[Lr] Data última revisão:
170920
[Sb] Subgrupo de revista:AIM; IM
[Da] Data de entrada para processamento:170912
[St] Status:MEDLINE
[do] DOI:10.2105/AJPH.2017.304051


  6 / 1113 MEDLINE  
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[PMID]:28750030
[Au] Autor:Zhang X
[Ad] Endereço:School of Computer Science and Technology, Tianjin University, Tianjin, China.
[Ti] Título:Minimally inconsistent reasoning in Semantic Web.
[So] Source:PLoS One;12(7):e0181056, 2017.
[Is] ISSN:1932-6203
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Reasoning with inconsistencies is an important issue for Semantic Web as imperfect information is unavoidable in real applications. For this, different paraconsistent approaches, due to their capacity to draw as nontrivial conclusions by tolerating inconsistencies, have been proposed to reason with inconsistent description logic knowledge bases. However, existing paraconsistent approaches are often criticized for being too skeptical. To this end, this paper presents a non-monotonic paraconsistent version of description logic reasoning, called minimally inconsistent reasoning, where inconsistencies tolerated in the reasoning are minimized so that more reasonable conclusions can be inferred. Some desirable properties are studied, which shows that the new semantics inherits advantages of both non-monotonic reasoning and paraconsistent reasoning. A complete and sound tableau-based algorithm, called multi-valued tableaux, is developed to capture the minimally inconsistent reasoning. In fact, the tableaux algorithm is designed, as a framework for multi-valued DL, to allow for different underlying paraconsistent semantics, with the mere difference in the clash conditions. Finally, the complexity of minimally inconsistent description logic reasoning is shown on the same level as the (classical) description logic reasoning.
[Mh] Termos MeSH primário: Lógica
Semântica
[Mh] Termos MeSH secundário: Algoritmos
Animais
Bases de Conhecimento
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1709
[Cu] Atualização por classe:170929
[Lr] Data última revisão:
170929
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170728
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pone.0181056


  7 / 1113 MEDLINE  
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[PMID]:28654725
[Au] Autor:Amberger JS; Hamosh A
[Ad] Endereço:McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
[Ti] Título:Searching Online Mendelian Inheritance in Man (OMIM): A Knowledgebase of Human Genes and Genetic Phenotypes.
[So] Source:Curr Protoc Bioinformatics;58:1.2.1-1.2.12, 2017 Jun 27.
[Is] ISSN:1934-340X
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Online Mendelian Inheritance in Man (OMIM) at OMIM.org is the primary repository of comprehensive, curated information on genes and genetic phenotypes and the relationships between them. This unit provides an overview of the types of information in OMIM and optimal strategies for searching and retrieving the information. OMIM.org has links to many related and complementary databases, providing easy access to more information on a topic. The relationship between genes and genetic disorders is highlighted in this unit. The basic protocol explains searching OMIM both from a gene perspective and a clinical features perspective. Two alternate protocols provide strategies for viewing gene-phenotype relationships: a gene map table and Quick View or Side-by-Side format for clinical features. OMIM.org is updated nightly, and the MIMmatch service, described in the support protocol, provides a convenient way to follow updates to entries, gene-phenotype relationships, and collaborate with other researchers. © 2017 by John Wiley & Sons, Inc.
[Mh] Termos MeSH primário: Biologia Computacional/métodos
Bases de Dados Genéticas
Fenótipo
[Mh] Termos MeSH secundário: Mapeamento Cromossômico
Seres Humanos
Bases de Conhecimento
[Pt] Tipo de publicação:JOURNAL ARTICLE; REVIEW
[Em] Mês de entrada:1711
[Cu] Atualização por classe:171106
[Lr] Data última revisão:
171106
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170628
[St] Status:MEDLINE
[do] DOI:10.1002/cpbi.27


  8 / 1113 MEDLINE  
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[PMID]:28622336
[Au] Autor:Lai EY; Chen YH; Wu KP
[Ad] Endereço:Institute of Biomedical Informatics, National Yang-Ming University, Taipei 11221, Taiwan.
[Ti] Título:A knowledge-based T2-statistic to perform pathway analysis for quantitative proteomic data.
[So] Source:PLoS Comput Biol;13(6):e1005601, 2017 Jun.
[Is] ISSN:1553-7358
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Approaches to identify significant pathways from high-throughput quantitative data have been developed in recent years. Still, the analysis of proteomic data stays difficult because of limited sample size. This limitation also leads to the practice of using a competitive null as common approach; which fundamentally implies genes or proteins as independent units. The independent assumption ignores the associations among biomolecules with similar functions or cellular localization, as well as the interactions among them manifested as changes in expression ratios. Consequently, these methods often underestimate the associations among biomolecules and cause false positives in practice. Some studies incorporate the sample covariance matrix into the calculation to address this issue. However, sample covariance may not be a precise estimation if the sample size is very limited, which is usually the case for the data produced by mass spectrometry. In this study, we introduce a multivariate test under a self-contained null to perform pathway analysis for quantitative proteomic data. The covariance matrix used in the test statistic is constructed by the confidence scores retrieved from the STRING database or the HitPredict database. We also design an integrating procedure to retain pathways of sufficient evidence as a pathway group. The performance of the proposed T2-statistic is demonstrated using five published experimental datasets: the T-cell activation, the cAMP/PKA signaling, the myoblast differentiation, and the effect of dasatinib on the BCR-ABL pathway are proteomic datasets produced by mass spectrometry; and the protective effect of myocilin via the MAPK signaling pathway is a gene expression dataset of limited sample size. Compared with other popular statistics, the proposed T2-statistic yields more accurate descriptions in agreement with the discussion of the original publication. We implemented the T2-statistic into an R package T2GA, which is available at https://github.com/roqe/T2GA.
[Mh] Termos MeSH primário: Interpretação Estatística de Dados
Bases de Conhecimento
Modelos Biológicos
Modelos Estatísticos
Proteoma/metabolismo
Transdução de Sinais/fisiologia
[Mh] Termos MeSH secundário: Algoritmos
Simulação por Computador
Proteômica/métodos
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Nm] Nome de substância:
0 (Proteome)
[Em] Mês de entrada:1708
[Cu] Atualização por classe:170818
[Lr] Data última revisão:
170818
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170617
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pcbi.1005601


  9 / 1113 MEDLINE  
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[PMID]:28604660
[Au] Autor:Mukherjee S; Seshadri R; Varghese NJ; Eloe-Fadrosh EA; Meier-Kolthoff JP; Göker M; Coates RC; Hadjithomas M; Pavlopoulos GA; Paez-Espino D; Yoshikuni Y; Visel A; Whitman WB; Garrity GM; Eisen JA; Hugenholtz P; Pati A; Ivanova NN; Woyke T; Klenk HP; Kyrpides NC
[Ad] Endereço:Department of Energy, Joint Genome Institute, Walnut Creek, California, USA.
[Ti] Título:1,003 reference genomes of bacterial and archaeal isolates expand coverage of the tree of life.
[So] Source:Nat Biotechnol;35(7):676-683, 2017 Jul.
[Is] ISSN:1546-1696
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:We present 1,003 reference genomes that were sequenced as part of the Genomic Encyclopedia of Bacteria and Archaea (GEBA) initiative, selected to maximize sequence coverage of phylogenetic space. These genomes double the number of existing type strains and expand their overall phylogenetic diversity by 25%. Comparative analyses with previously available finished and draft genomes reveal a 10.5% increase in novel protein families as a function of phylogenetic diversity. The GEBA genomes recruit 25 million previously unassigned metagenomic proteins from 4,650 samples, improving their phylogenetic and functional interpretation. We identify numerous biosynthetic clusters and experimentally validate a divergent phenazine cluster with potential new chemical structure and antimicrobial activity. This Resource is the largest single release of reference genomes to date. Bacterial and archaeal isolate sequence space is still far from saturated, and future endeavors in this direction will continue to be a valuable resource for scientific discovery.
[Mh] Termos MeSH primário: Mapeamento Cromossômico/normas
Bases de Dados Genéticas
Genoma Arqueal/genética
Genoma Bacteriano/genética
Sequenciamento de Nucleotídeos em Larga Escala/normas
Bases de Conhecimento
[Mh] Termos MeSH secundário: Sistemas de Gerenciamento de Base de Dados
Conjuntos de Dados como Assunto
Enciclopédias como Assunto
Valores de Referência
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1708
[Cu] Atualização por classe:170818
[Lr] Data última revisão:
170818
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170613
[St] Status:MEDLINE
[do] DOI:10.1038/nbt.3886


  10 / 1113 MEDLINE  
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[PMID]:28580763
[Au] Autor:Pieterman ED; Budde RPJ; Robbers-Visser D; van Domburg RT; Helbing WA
[Ad] Endereço:Department of Pediatrics, Division of Cardiology, Erasmus Medical Center, Sophia Children's Hospital, Rotterdam, The Netherlands.
[Ti] Título:Knowledge-based reconstruction for measurement of right ventricular volumes on cardiovascular magnetic resonance images in a mixed population.
[So] Source:Congenit Heart Dis;12(5):561-569, 2017 Sep.
[Is] ISSN:1747-0803
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:OBJECTIVE: Follow-up of right ventricular performance is important for patients with congenital heart disease. Cardiac magnetic resonance imaging is optimal for this purpose. However, observer-dependency of manual analysis of right ventricular volumes limit its use. Knowledge-based reconstruction is a new semiautomatic analysis tool that uses a database including knowledge of right ventricular shape in various congenital heart diseases. We evaluated whether knowledge-based reconstruction is a good alternative for conventional analysis. DESIGN: To assess the inter- and intra-observer variability and agreement of knowledge-based versus conventional analysis of magnetic resonance right ventricular volumes, analysis was done by two observers in a mixed group of 22 patients with congenital heart disease affecting right ventricular loading conditions (dextro-transposition of the great arteries and right ventricle to pulmonary artery conduit) and a group of 17 healthy children. We used Bland-Altman analysis and coefficient of variation. RESULTS: Comparison between the conventional method and the knowledge-based method showed a systematically higher volume for the latter group. We found an overestimation for end-diastolic volume (bias -40 ± 24 mL, r = .956), end-systolic volume (bias -34 ± 24 mL, r = .943), stroke volume (bias -6 ± 17 mL, r = .735) and an underestimation of ejection fraction (bias 7 ± 7%, r = .671) by knowledge-based reconstruction. The intra-observer variability of knowledge-based reconstruction varied with a coefficient of variation of 9% for end-diastolic volume and 22% for stroke volume. The same trend was noted for inter-observer variability. CONCLUSION: A systematic difference (overestimation) was noted for right ventricular size as assessed with knowledge-based reconstruction compared with conventional methods for analysis. Observer variability for the new method was comparable to what has been reported for the right ventricle in children and congenital heart disease with conventional analysis.
[Mh] Termos MeSH primário: Volume Cardíaco/fisiologia
Cardiopatias Congênitas/diagnóstico
Ventrículos do Coração/diagnóstico por imagem
Interpretação de Imagem Assistida por Computador/métodos
Bases de Conhecimento
Imagem Cinética por Ressonância Magnética/métodos
[Mh] Termos MeSH secundário: Adolescente
Adulto
Criança
Feminino
Seguimentos
Cardiopatias Congênitas/fisiopatologia
Ventrículos do Coração/fisiopatologia
Seres Humanos
Masculino
Curva ROC
Reprodutibilidade dos Testes
Estudos Retrospectivos
Adulto Jovem
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1711
[Cu] Atualização por classe:171102
[Lr] Data última revisão:
171102
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170606
[St] Status:MEDLINE
[do] DOI:10.1111/chd.12484



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