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.

随着糖尿病的全球患病率继续增加，糖尿病性视网膜病（DR）仍然是糖尿病患者最常见的血管并发症。尽管有治疗的进步，但博士仍然是全球工人衰老人视觉丧失的主要原因。为了更好地理解如何防止糖尿病眼睛并发症的视力丧失。在这种情况下，早期DR检测是避免视网膜损害和视力丧失的一种有希望的方法。先前的研究发现，血管病变出现之前的糖尿病眼中血流变化，目前，这是诊断的主要临床体征。因此，我们假设可以通过监测早期血流变化来实现DR早期检测。在最近的一项研究中，我们提出了一种评估视网膜副伏尔瓦维尔地区血流的第一种非侵入性方法（paramount对于中央敏锐的视野的重要性）。我们通过比较我们的计算流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的血液速度来验证了我们的方法。尽管模型估算的准确性，但在DR和对照组之间的比较中，我们无法获得统计学意义。我们假设这主要是由于我们的流模型定义的重要限制引起通过通过BCA速度同化估算模型边界条件来限制。这种方法将使我们能够基于一组粒子跟踪实验读数来定义患者特异性模型。所提出的方法是基于构建约束优化问题的，在这种问题中，模型解决方案场（在这种情况下在这种情况下流体压力和速度）是通过最大程度地减少模型输出速度与单元格跟踪数据之间的不匹配的量度来诊断的。项目，我们将开发一个软件工具，该工具将先前的数值程序应用于从眼睛的高分辨率视网膜图像和通过BCA Tracking获得的体内血液速度测量值重建的微血管网络流模型。前者将依靠作者先前发表的方法。视网膜图像和细胞跟踪数据都已经存在于项目合作伙伴的实验室，并且已成功地用于先前的出版物中。

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