Biomedical Engineering and Computational Biology最新文献_第5页

Multifidelity Analysis for Predicting Rare Events in Stochastic Computational Models of Complex Biological Systems. 复杂生物系统随机计算模型中罕见事件预测的多保真度分析。

IF 2.8

Biomedical Engineering and Computational Biology Pub Date : 2018-08-03 eCollection Date: 2018-01-01 DOI: 10.1177/1179597218790253

Elsje Pienaar

{"title":"Multifidelity Analysis for Predicting Rare Events in Stochastic Computational Models of Complex Biological Systems.","authors":"Elsje Pienaar","doi":"10.1177/1179597218790253","DOIUrl":"https://doi.org/10.1177/1179597218790253","url":null,"abstract":"Rare events such as genetic mutations or cell-cell interactions are important contributors to dynamics in complex biological systems, eg, in drug-resistant infections. Computational approaches can help analyze rare events that are difficult to study experimentally. However, analyzing the frequency and dynamics of rare events in computational models can also be challenging due to high computational resource demands, especially for high-fidelity stochastic computational models. To facilitate analysis of rare events in complex biological systems, we present a multifidelity analysis approach that uses medium-fidelity analysis (Monte Carlo simulations) and/or low-fidelity analysis (Markov chain models) to analyze high-fidelity stochastic model results. Medium-fidelity analysis can produce large numbers of possible rare event trajectories for a single high-fidelity model simulation. This allows prediction of both rare event dynamics and probability distributions at much lower frequencies than high-fidelity models. Low-fidelity analysis can calculate probability distributions for rare events over time for any frequency by updating the probabilities of the rare event state space after each discrete event of the high-fidelity model. To validate the approach, we apply multifidelity analysis to a high-fidelity model of tuberculosis disease. We validate the method against high-fidelity model results and illustrate the application of multifidelity analysis in predicting rare event trajectories, performing sensitivity analyses and extrapolating predictions to very low frequencies in complex systems. We believe that our approach will complement ongoing efforts to enable accurate prediction of rare event dynamics in high-fidelity computational models.","PeriodicalId":42484,"journal":{"name":"Biomedical Engineering and Computational Biology","volume":"9 ","pages":"1179597218790253"},"PeriodicalIF":2.8,"publicationDate":"2018-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1179597218790253","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36380396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Granular Cell Tumor Imaging Using Optical Coherence Tomography. 利用光学相干断层扫描进行颗粒细胞肿瘤成像。

IF 2.8

Biomedical Engineering and Computational Biology Pub Date : 2018-08-02 eCollection Date: 2018-01-01 DOI: 10.1177/1179597218790250

David Tes, Ahmed Aber, Mohsin Zafar, Luke Horton, Audrey Fotouhi, Qiuyun Xu, Ali Moiin, Andrew D Thompson, Tatiana Cristina Moraes Pinto Blumetti, Steven Daveluy, Wei Chen, Mohammadreza Nasiriavanaki

{"title":"Granular Cell Tumor Imaging Using Optical Coherence Tomography.","authors":"David Tes, Ahmed Aber, Mohsin Zafar, Luke Horton, Audrey Fotouhi, Qiuyun Xu, Ali Moiin, Andrew D Thompson, Tatiana Cristina Moraes Pinto Blumetti, Steven Daveluy, Wei Chen, Mohammadreza Nasiriavanaki","doi":"10.1177/1179597218790250","DOIUrl":"10.1177/1179597218790250","url":null,"abstract":"Background: Granular cell tumor (GCT) is a relatively uncommon tumor that may affect the skin. The tumor can develop anywhere on the body, although it is predominately seen in oral cavities and in the head and neck regions. Here, we present the results of optical coherence tomography (OCT) imaging of a large GCT located on the abdomen of a patient. We also present an analytical method to differentiate between healthy tissue and GCT tissues.Materials and methods: A multibeam, Fourier domain, swept source OCT was used for imaging. The OCT had a central wavelength of 1305 ± 15 nm and lateral and axial resolutions of 7.5 and 10 µm, respectively. Qualitative and quantitative analyses of the tumor and healthy skin are reported.Results: Abrupt changes in architectures of the dermal and epidermal layers in the GCT lesion were observed. These architectural changes were not observed in healthy skin.Discussion: To quantitatively differentiate healthy skin from tumor regions, an optical attenuation coefficient analysis based on single-scattering formulation was performed. The methodology introduced here could have the capability to delineate boundaries of a tumor prior to surgical excision.","PeriodicalId":42484,"journal":{"name":"Biomedical Engineering and Computational Biology","volume":"9 ","pages":"1179597218790250"},"PeriodicalIF":2.8,"publicationDate":"2018-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/5b/e2/10.1177_1179597218790250.PMC6088518.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36405562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development and Optimization of a Fluorescent Imaging System to Detect Amyloid-β Proteins: Phantom Study. 淀粉样蛋白-β荧光成像系统的开发与优化:幻影研究。

IF 2.8

Biomedical Engineering and Computational Biology Pub Date : 2018-06-18 eCollection Date: 2018-01-01 DOI: 10.1177/1179597218781081

David Tes, Karl Kratkiewicz, Ahmed Aber, Luke Horton, Mohsin Zafar, Nour Arafat, Afreen Fatima, Mohammad Rn Avanaki

引用次数: 0

Application of a Causal Discovery Algorithm to the Analysis of Arthroplasty Registry Data. 应用因果发现算法分析关节成形术登记数据。

IF 2.8

Biomedical Engineering and Computational Biology Pub Date : 2018-02-22 eCollection Date: 2018-01-01 DOI: 10.1177/1179597218756896

Camden Cheek, Huiyong Zheng, Brian R Hallstrom, Richard E Hughes

{"title":"Application of a Causal Discovery Algorithm to the Analysis of Arthroplasty Registry Data.","authors":"Camden Cheek, Huiyong Zheng, Brian R Hallstrom, Richard E Hughes","doi":"10.1177/1179597218756896","DOIUrl":"10.1177/1179597218756896","url":null,"abstract":"Improving the quality of care for hip arthroplasty (replacement) patients requires the systematic evaluation of clinical performance of implants and the identification of \"outlier\" devices that have an especially high risk of reoperation (\"revision\"). Postmarket surveillance of arthroplasty implants, which rests on the analysis of large patient registries, has been effective in identifying outlier implants such as the ASR metal-on-metal hip resurfacing device that was recalled. Although identifying an implant as an outlier implies a causal relationship between the implant and revision risk, traditional signal detection methods use classical biostatistical methods. The field of probabilistic graphical modeling of causal relationships has developed tools for rigorous analysis of causal relationships in observational data. The purpose of this study was to evaluate one causal discovery algorithm (PC) to determine its suitability for hip arthroplasty implant signal detection. Simulated data were generated using distributions of patient and implant characteristics, and causal discovery was performed using the TETRAD software package. Two sizes of registries were simulated: (1) a statewide registry in Michigan and (2) a nationwide registry in the United Kingdom. The results showed that the algorithm performed better for the simulation of a large national registry. The conclusion is that the causal discovery algorithm used in this study may be a useful tool for implant signal detection for large arthroplasty registries; regional registries may only be able to only detect implants that perform especially poorly.","PeriodicalId":42484,"journal":{"name":"Biomedical Engineering and Computational Biology","volume":"9 ","pages":"1179597218756896"},"PeriodicalIF":2.8,"publicationDate":"2018-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/9c/ed/10.1177_1179597218756896.PMC5826097.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35889049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development and Retrospective Clinical Assessment of a Patient-Specific Closed-Form Integro-Differential Equation Model of Plasma Dilution. 血浆稀释患者特异性闭式积分-微分方程模型的建立和回顾性临床评估。

IF 2.8

Biomedical Engineering and Computational Biology Pub Date : 2017-10-26 eCollection Date: 2017-01-01 DOI: 10.1177/1179597217730305

Glen Atlas, John K-J Li, Shawn Amin, Robert G Hahn

{"title":"Development and Retrospective Clinical Assessment of a Patient-Specific Closed-Form Integro-Differential Equation Model of Plasma Dilution.","authors":"Glen Atlas, John K-J Li, Shawn Amin, Robert G Hahn","doi":"10.1177/1179597217730305","DOIUrl":"https://doi.org/10.1177/1179597217730305","url":null,"abstract":"A closed-form integro-differential equation (IDE) model of plasma dilution (PD) has been derived which represents both the intravenous (IV) infusion of crystalloid and the postinfusion period. Specifically, PD is mathematically represented using a combination of constant ratio, differential, and integral components. Furthermore, this model has successfully been applied to preexisting data, from a prior human study, in which crystalloid was infused for a period of 30 minutes at the beginning of thyroid surgery. Using Euler's formula and a Laplace transform solution to the IDE, patients could be divided into two distinct groups based on their response to PD during the infusion period. Explicitly, Group 1 patients had an infusion-based PD response which was modeled using an exponentially decaying hyperbolic sine function, whereas Group 2 patients had an infusion-based PD response which was modeled using an exponentially decaying trigonometric sine function. Both Group 1 and Group 2 patients had postinfusion PD responses which were modeled using the same combination of hyperbolic sine and hyperbolic cosine functions. Statistically significant differences, between Groups 1 and 2, were noted with respect to the area under their PD curves during both the infusion and postinfusion periods. Specifically, Group 2 patients exhibited a response to PD which was most likely consistent with a preoperative hypovolemia. Overall, this IDE model of PD appears to be highly \"adaptable\" and successfully fits clinically-obtained human data on a patient-specific basis, during both the infusion and postinfusion periods. In addition, patient-specific IDE modeling of PD may be a useful adjunct in perioperative fluid management and in assessing clinical volume kinetics, of crystalloid solutions, in real time.","PeriodicalId":42484,"journal":{"name":"Biomedical Engineering and Computational Biology","volume":"8 ","pages":"1179597217730305"},"PeriodicalIF":2.8,"publicationDate":"2017-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1179597217730305","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35594652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Diffusion in Tube Dialyzer. 管内扩散透析器。

IF 2.8

Biomedical Engineering and Computational Biology Pub Date : 2017-09-29 eCollection Date: 2017-01-01 DOI: 10.1177/1179597217732006

Yohannes Nigatie

{"title":"Diffusion in Tube Dialyzer.","authors":"Yohannes Nigatie","doi":"10.1177/1179597217732006","DOIUrl":"https://doi.org/10.1177/1179597217732006","url":null,"abstract":"Nowadays, kidney failure is a problem of many peoples in the world. We know that the main function of kidney is maintaining the chemical quality of blood particularly removing urea through urine. But when they malfunction, the pathologic state known as uremia results in a condition in which the urea is retained in the body. Failure of the kidney results in building up of harmful wastes and excess fluids in the body. Kidney diseases (failures) can be due to infections, high blood pressure (hypertension), diabetes, and/or extensive use of medication. The best form of treatment is the implantation of a healthy kidney from a donor. However, this is often not possible due to the limited availability of human organs. Chronic kidney failure requires the treatment using a tube dialyzer called dialysis. Blood is taken out of the body and passes through a special membrane that removes waste and extra fluids. The clean blood is then returned to the body. The process is controlled by a dialysis machine (tube dialyzer) which is equipped with a blood pump and monitoring systems to ensure safety. So this article investigates the real application of mathematics (diffusion) in medical science, and it also contains the mathematical formulation and interpretation of tube dialyzer in relation to diffusion.","PeriodicalId":42484,"journal":{"name":"Biomedical Engineering and Computational Biology","volume":"8 ","pages":"1179597217732006"},"PeriodicalIF":2.8,"publicationDate":"2017-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1179597217732006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35483329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Optical Coherence Tomography Technology and Quality Improvement Methods for Optical Coherence Tomography Images of Skin: A Short Review. 光学相干断层扫描技术和皮肤光学相干断层扫描图像质量改进方法：简评。

IF 2.8

Biomedical Engineering and Computational Biology Pub Date : 2017-06-12 eCollection Date: 2017-01-01 DOI: 10.1177/1179597217713475

Saba Adabi, Zahra Turani, Emad Fatemizadeh, Anne Clayton, Mohammadreza Nasiriavanaki

引用次数: 0

FSI Simulations of Pulse Wave Propagation in Human Abdominal Aortic Aneurysm: The Effects of Sac Geometry and Stiffness. 脉冲波在人腹主动脉瘤内传播的FSI模拟:囊腔几何形状和刚度的影响。

IF 2.8

Biomedical Engineering and Computational Biology Pub Date : 2016-07-18 eCollection Date: 2016-01-01 DOI: 10.4137/BECB.S40094

Han Li, Kexin Lin, Danial Shahmirzadi

{"title":"FSI Simulations of Pulse Wave Propagation in Human Abdominal Aortic Aneurysm: The Effects of Sac Geometry and Stiffness.","authors":"Han Li, Kexin Lin, Danial Shahmirzadi","doi":"10.4137/BECB.S40094","DOIUrl":"https://doi.org/10.4137/BECB.S40094","url":null,"abstract":"This study aims to quantify the effects of geometry and stiffness of aneurysms on the pulse wave velocity (PWV) and propagation in fluid-solid interaction (FSI) simulations of arterial pulsatile flow. Spatiotemporal maps of both the wall displacement and fluid velocity were generated in order to obtain the pulse wave propagation through fluid and solid media, and to examine the interactions between the two waves. The results indicate that the presence of abdominal aortic aneurysm (AAA) sac and variations in the sac modulus affect the propagation of the pulse waves both qualitatively (eg, patterns of change of forward and reflective waves) and quantitatively (eg, decreasing of PWV within the sac and its increase beyond the sac as the sac stiffness increases). The sac region is particularly identified on the spatiotemporal maps with a region of disruption in the wave propagation with multiple short-traveling forward/reflected waves, which is caused by the change in boundary conditions within the saccular region. The change in sac stiffness, however, is more pronounced on the wall displacement spatiotemporal maps compared to those of fluid velocity. We conclude that the existence of the sac can be identified based on the solid and fluid pulse waves, while the sac properties can also be estimated. This study demonstrates the initial findings in numerical simulations of FSI dynamics during arterial pulsations that can be used as reference for experimental and in vivo studies. Future studies are needed to demonstrate the feasibility of the method in identifying very mild sacs, which cannot be detected from medical imaging, where the material property degradation exists under early disease initiation. ","PeriodicalId":42484,"journal":{"name":"Biomedical Engineering and Computational Biology","volume":"7 ","pages":"25-36"},"PeriodicalIF":2.8,"publicationDate":"2016-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4137/BECB.S40094","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34721844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

IMAGE AND VIDEO ACQUISITION AND PROCESSING FOR CLINICAL APPLICATIONS. 临床应用的图像和视频采集与处理。

IF 2.8

Biomedical Engineering and Computational Biology Pub Date : 2016-06-16 eCollection Date: 2016-01-01 DOI: 10.4137/BECB.S40272

Elie Zakhem, Sean V Murphy, Matthew L Davis, Shreya Raghavan, Mai T Lam

引用次数: 1

Fluorescent Cell Imaging in Regenerative Medicine. 再生医学中的荧光细胞成像。

IF 2.8

Biomedical Engineering and Computational Biology Pub Date : 2016-05-02 eCollection Date: 2016-01-01 DOI: 10.4137/BECB.S39045

Etai Sapoznik, Guoguang Niu, Yu Zhou, Sean V Murphy, Shay Soker

引用次数: 3