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Connecting Lung Structure and Function in Cystic Fibrosis Through Physiological Modelling, Image Analysis, and Uncertainty Quantification

通过生理建模、图像分析和不确定性量化将囊性纤维化的肺结构和功能联系起来

基本信息

批准号：
MR/R024944/1
负责人：
Carl Whitfield
金额：
$ 33.35万
依托单位：
University of Manchester
依托单位国家：
英国
项目类别：
Fellowship
财政年份：
2017
资助国家：
英国
起止时间：
2017 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=MR%2FR024944%2F1
关键词：
Connecting Lung Structure Function Cystic

项目摘要

The human lung is a very complex organ comprised of millions of airways that range from several centimetres down to micrometers in length. This complexity makes it difficult to reliably relate the outcomes of lung function tests to underlying physical changes in the lung structure. Cystic Fibrosis is a genetic condition that currently affects around 9000 people in the UK. Changes in the lung structure (e.g. airway blockages) of cystic fibrosis patients can indicate progression of an infection associated with the disease that requires treatment. Therefore, catching such changes early is paramount to improving patient care. Currently, spirometry tests (which effectively measure the size and strength of the lungs by monitoring the flow rate during forced breathing through the device) are most commonly used to detect these changes, but these have been shown to be relatively insensitive to the changes associated with early Cystic Fibrosis progression. The Multiple-Breath Washout test (which involves a patient breathing in a gas mixture through a mask that traces the flow rate and gas concentrations) contains much more information than spirometry. Various formulae and indices exist to summarise lung function from this test data, but it remains unclear how these relate to the underlying structural changes. The goal of this project is to use mathematical and computational modelling to make this connection clearer and develop tools to quantify these changes. I will develop software that can simulate gas flow in lungs with structural changes that are associated with early Cystic Fibrosis. These simulations will be compared directly with data from Multiple-Breath Washout tests and MRI data which images the gas distribution within the lungs as a patient is breathing.Using the simulations developed we will gain an understanding of the effects of early Cystic Fibrosis progression on these lung function tests, which can be used to develop more sensitive and reliable measures of structural change. Further on, I will develop software tools that can be used to automatically whether a patient's condition is worsening directly from these datasets. Additionally, this project will feed into future research collaborations by expanding these approaches to other disease groups, notably lung transplant patients, COPD and asthma. This project incorporates training in specific expertise in state-of-the-art lung modelling and the necessary advanced mathematical techniques.

人类的肺是一个非常复杂的器官，由数百万条从几厘米到微米长的呼吸道组成。这种复杂性使得很难可靠地将肺功能测试的结果与肺结构的潜在物理变化联系起来。囊性纤维化是一种遗传性疾病，目前在英国约有9000人受到影响。囊性纤维化患者肺结构的变化(例如，呼吸道阻塞)可能表明与需要治疗的疾病相关的感染的进展。因此，及早捕捉这些变化对改善患者护理至关重要。目前，肺活量测定测试(通过监测通过该装置用力呼吸时的流速，有效地测量肺的大小和强度)最常用于检测这些变化，但已被证明对与早期囊性纤维化进展相关的变化相对不敏感。多次呼吸冲洗试验(患者通过面罩呼吸混合气体，跟踪流速和气体浓度)包含的信息比肺活量测定法多得多。存在各种公式和指数来总结这项测试数据的肺功能，但尚不清楚这些与潜在的结构变化之间的关系。这个项目的目标是使用数学和计算模型来使这种联系更加清晰，并开发工具来量化这些变化。我将开发一种软件，可以模拟肺部气体流动的结构变化，这些变化与早期囊性纤维化有关。这些模拟将直接与多次呼吸冲洗测试的数据和MRI数据进行比较，这些数据成像患者呼吸时肺部的气体分布。使用开发的模拟，我们将了解早期囊性纤维化进展对这些肺功能测试的影响，这些测试可用于开发更敏感和可靠的结构变化测量方法。进一步，我将开发软件工具，可以直接根据这些数据集自动判断患者的病情是否恶化。此外，该项目将通过将这些方法扩展到其他疾病群体，特别是肺移植患者、慢性阻塞性肺病和哮喘，为未来的研究合作提供支持。该项目结合了在国家最先进的肺建模和必要的高级数学技术方面的具体专门知识的培训。