Volumetric flow rate reconstructionin great vessels

IF 0.3 Q4 MATHEMATICS Annales Mathematicae et Informaticae Pub Date : 2019-01-01 DOI:10.33039/AMI.2019.02.002
A. Lovas, R. Nagy, P. Sótonyi, B. Szilágyi
{"title":"Volumetric flow rate reconstructionin great vessels","authors":"A. Lovas, R. Nagy, P. Sótonyi, B. Szilágyi","doi":"10.33039/AMI.2019.02.002","DOIUrl":null,"url":null,"abstract":"We present a new algorithm to reconstruct the volumetric flux in the aorta. We study a simple 1D blood flow model without viscosity term and sophisticated material model. Using the continuity law, we could reduce the original inverse problem related to a system of PDEs to a parameter iden-tification problem involving a Riccati-type ODE with periodic coefficients. We implemented a block-based optimization algorithm to recover the model parameters. We tested our method on real data obtained using CG-gated CT angiography imaging of the aorta. Local flow rate was calculated in 10 cm long aorta segments which are located 1 cm below the heart. The reconstructed volumetric flux shows a realistic wave-like behavior, where reflections from arteria iliaca can also be observed. Our approach is suitable for estimating the main characteristics of pulsatile flow in the aorta and thereby contributing to a more accurate description of several cardiovascular lesions.","PeriodicalId":43454,"journal":{"name":"Annales Mathematicae et Informaticae","volume":"17 1","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annales Mathematicae et Informaticae","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33039/AMI.2019.02.002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS","Score":null,"Total":0}
引用次数: 0

Abstract

We present a new algorithm to reconstruct the volumetric flux in the aorta. We study a simple 1D blood flow model without viscosity term and sophisticated material model. Using the continuity law, we could reduce the original inverse problem related to a system of PDEs to a parameter iden-tification problem involving a Riccati-type ODE with periodic coefficients. We implemented a block-based optimization algorithm to recover the model parameters. We tested our method on real data obtained using CG-gated CT angiography imaging of the aorta. Local flow rate was calculated in 10 cm long aorta segments which are located 1 cm below the heart. The reconstructed volumetric flux shows a realistic wave-like behavior, where reflections from arteria iliaca can also be observed. Our approach is suitable for estimating the main characteristics of pulsatile flow in the aorta and thereby contributing to a more accurate description of several cardiovascular lesions.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
大血管的体积流速重建
我们提出了一种重建主动脉体积通量的新算法。研究了不含黏度项的一维简单血流模型和复杂的材料模型。利用连续律,我们可以将原微分方程系统的逆问题简化为包含周期系数的riccati型微分方程的参数辨识问题。我们实现了一种基于块的优化算法来恢复模型参数。我们在使用cg门控CT主动脉血管成像获得的真实数据上测试了我们的方法。计算位于心脏下方1cm处的10cm长的主动脉段的局部流速。重建的体积通量显示出真实的波状行为,其中也可以观察到来自髂动脉的反射。我们的方法适用于估计主动脉搏动血流的主要特征,从而有助于更准确地描述几种心血管病变。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
0.90
自引率
0.00%
发文量
0
期刊最新文献
Using irreducible polynomials for random number generation Solving Hungarian natural language processing tasks with multilingual generative models Stability condition of multiclass classical retrials: a revised regenerative proof Sensitivity analysis of a single server finite-source retrial queueing system with two-way communication and catastrophic breakdown using simulation On the generalized Fibonacci like sequences and matrices
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1