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Automatic assimilation of particle velocimetry data into computational blood flow models

将粒子测速数据自动同化为计算血流模型

基本信息

批准号：
EP/R021600/1
负责人：
Miguel Bernabeu Llinares
金额：
$ 12.49万
依托单位：
University of Edinburgh
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2018
资助国家：
英国
起止时间：
2018 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FR021600%2F1
关键词：
Automatic assimilation particle velocimetry data

项目摘要

As the worldwide prevalence of diabetes mellitus continues to increase, diabetic retinopathy (DR) remains the most common vascular complication in diabetic patients. Despite advances in treatment, DR remains a leading cause of visual loss in working-aged people worldwide. New approaches are necessary in order to better understand how to prevent vision loss from diabetic eye complications.In this context, early DR detection is a promising approach to avoiding retinal damage and vision loss. Previous studies have found changes in blood flow in the diabetic eyes preceding the appearance of vascular lesions, which are currently the main clinical signs for diagnosis. Therefore, we hypothesise that DR early detection can be achieved via monitoring of early blood flow changes.In a recent study, we proposed the first-ever non-invasive method for the assessment of blood flow in the parafoveal region of the retina (of paramount importance for central sharp vision). We validated our approach by comparing the blood velocity predicted by our computational flow models with in vivo blood velocity measurements obtained by tracking blood cell aggregations (BCA) visible in the retinal scans. Despite the accuracy in the model estimates, we could not achieve statistical significance in the comparison between the DR and control groups. We hypothesise that this is primarily caused by an important limitation in the definition of our flow models: the use of non-patient-specific flow boundary conditions, which we anticipate differing substantially in both groups.In the current proposal we aim to address this model limitation by estimating the model boundary conditions via BCA velocity assimilation. This approach will allow us to define patient-specific models based on a small set of particle tracking experimental readouts. The proposed approach is based on constructing a constrained optimisation problem, whereby the model solution fields (fluid pressure and velocity in this case) are diagnosed by minimising a measure of the mismatch between the model output velocity and the cell tracking data.As part of the project, we will develop a software tool that applies the previous numerical procedure to microvascular network flow models reconstructed from high resolution retinal images of the parafoveal region of the eye and in vivo blood velocity measurements obtained by BCA tracking. The former will rely on methodology previously published by the authors. Both retinal images and cell tracking data already exist at the laboratory of a project partner and were successfully employed in a previous publication.

随着全球糖尿病患病率的持续增加，糖尿病视网膜病变（DR）仍然是糖尿病患者最常见的血管并发症。尽管在治疗方面取得了进展，但DR仍然是全球工作年龄人群视力丧失的主要原因。为了更好地了解如何预防糖尿病眼部并发症导致的视力丧失，需要新的方法。在这种情况下，早期DR检测是避免视网膜损伤和视力丧失的一种有前途的方法。先前的研究已经发现在血管病变出现之前糖尿病眼睛中的血流变化，这是目前诊断的主要临床体征。因此，我们假设DR的早期检测可以通过监测早期血流变化来实现。在最近的一项研究中，我们提出了有史以来第一个非侵入性的方法来评估视网膜旁区域的血流（对中央锐利视觉至关重要）。我们通过比较我们的计算流动模型预测的血液速度与通过跟踪视网膜扫描中可见的血细胞聚集（BCA）获得的体内血液速度测量值来验证我们的方法。尽管模型估计的准确性，但我们在DR组和对照组之间的比较中无法达到统计学显着性。我们假设，这主要是由一个重要的限制，在我们的流量模型的定义：使用非患者特定的流量边界条件，我们预计在这两个groups.In目前的建议，我们的目标是解决这个模型的限制，通过估计模型边界条件，通过BCA速度同化。这种方法将使我们能够根据一小组粒子跟踪实验读数来定义患者特定的模型。所提出的方法是基于构建一个约束优化问题，从而模型的解决方案领域通过最小化模型输出速度和细胞跟踪数据之间的失配的测量来诊断细胞的运动（在这种情况下是流体压力和速度）。作为该项目的一部分，我们将开发一个软件工具，将以前的数值程序应用于从高分辨率视网膜重建的微血管网络流动模型。眼旁区域的图像和通过BCA跟踪获得的体内血流速度测量。前者将依赖于作者以前发表的方法。视网膜图像和细胞跟踪数据已经存在于项目合作伙伴的实验室中，并在以前的出版物中成功应用。

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Emergent cell-free layer asymmetry and biased haematocrit partition in a biomimetic vascular network of successive bifurcations.

DOI：
10.1039/d0sm01845g
发表时间：
2021-01
期刊：
Soft matter
影响因子：
3.4
作者：
Qi Zhou;J. Fidalgo;M. Bernabeu;Mónica S. A. Oliveira;T. Krüger
通讯作者：
Qi Zhou;J. Fidalgo;M. Bernabeu;Mónica S. A. Oliveira;T. Krüger

Spatiotemporal Dynamics of Dilute Red Blood Cell Suspensions in Low-Inertia Microchannel Flow.

低惯性微通道流中稀释红细胞悬浮液的时空动力学。

DOI：
10.1016/j.bpj.2020.03.019
发表时间：
2020
期刊：
Biophysical journal
影响因子：
3.4
作者：
Zhou Q
通讯作者：
Zhou Q

Automated Calculation of Higher Order Partial Differential Equation Constrained Derivative Information

高阶偏微分方程约束导数信息的自动计算

DOI：
10.1137/18m1209465
发表时间：
2019
期刊：
SIAM Journal on Scientific Computing
影响因子：
3.1
作者：
Maddison J
通讯作者：
Maddison J

Compressed vessels bias red blood cell partitioning at bifurcations in a hematocrit-dependent manner: Implications in tumor blood flow

DOI：
10.1073/pnas.2025236118
发表时间：
2021-06-22
期刊：
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
影响因子：
11.1
作者：
Enjalbert, Romain;Hardman, David;Bernabeu, Miguel O.
通讯作者：
Bernabeu, Miguel O.

Red blood cell lingering modulates hematocrit distribution in the microcirculation

DOI：
10.1101/2022.08.16.504126
发表时间：
2022-08
期刊：
Biophysical Journal
影响因子：
3.4
作者：
Yazdan Rashidi;G. Simionato;Qi Zhou;Thomas John;Alexander Kihm;Mohammed Bendaoud;T. Krüger;M. Bernabeu;L. Kaestner;M. Laschke;M. Menger;C. Wagner;A. Darras
通讯作者：
Yazdan Rashidi;G. Simionato;Qi Zhou;Thomas John;Alexander Kihm;Mohammed Bendaoud;T. Krüger;M. Bernabeu;L. Kaestner;M. Laschke;M. Menger;C. Wagner;A. Darras