Regional Lung Mechanics by 3D Image Registration

通过 3D 图像配准进行区域肺力学

• 批准号: 7078087
• 负责人: JOSEPH M REINHARDT
• 金额: $ 32.19万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-07-01 至 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7078087
• 关键词: bioimaging /biomedical imaging; biomechanics; chronic obstructive pulmonary disease; clinical research; computed axial tomography; computer assisted diagnosis; human data; human subject; image processing; lung; lung disorder; lung imaging /visualization /scanning; pathologic process; respiratory airway volume; respiratory function; sheep; spirometry; three dimensional imaging /topography; bioimaging /biomedical imaging; biomechanics; chronic obstructive pulmonary disease; clinical research; computed axial tomography; computer assisted diagnosis; human data; human subject; image processing; lung; lung disorder; lung imaging /visualization /scanning; pathologic process; respiratory airway volume; respiratory function; sheep; spirometry; three dimensional imaging /topography

DESCRIPTION (provided by applicant): The goals of this research are to use high-resolution maps of regional lung mechanical properties to detect and follow the progression of lung disease. Pulmonary disease processes, including emphysema, interstitial fibrosis, cancer, pulmonary embolism, acute lung injury and more, alter the material properties of lung tissue and change the mechanics of the respiratory system. Furthermore, while these mechanical changes (and the disease process itself) originate at a local level, they are largely asymptomatic and invisible to currently available global measures of lung function such as pulmonary function tests until they have significantly advanced. We will use image registration to construct a high-resolution 3D map of the regional distribution of lung tissue specific volume change (related to specific compliance) and the lung tissue strain tensor between multiple respiratory-gated volumetric images of the breathing lung. The computational tools to be developed in this project will provide the ability to assess local volume, grayscale, and shape changes for arbitrary regions of interest in the lung parenchyma across the respiratory cycle. We expect that, by tracking the 3D distribution of regional lung specific volume change and the magnitude and direction of lung strain, we can examine the effects that localized pathological processes have on diseased tissue as well as surrounding normal tissue. Such information may provide new insights regarding pulmonary pathophysiology in, for instance, the proliferation of lung destruction in emphysema, the ventilation and perfusion mismatches in pulmonary emboli episodes, the effect of regional airway closure in asthma, and the regional mechanics of acute lung injury and the propagation of ventilator-associated lung injury. This information is now critical to the development and evaluation of new pulmonary disease therapies.

描述（由申请人提供）：这项研究的目标是使用区域肺机械性能的高分辨率图来检测和遵循肺部疾病的进展。肺部疾病过程，包括肺气肿，间质纤维化，癌症，肺栓塞，急性肺损伤等，会改变肺组织的材料特性并改变呼吸系统的力学。此外，尽管这些机械变化（以及疾病过程本身）起源于局部水平，但它们在很大程度上是无症状的，并且对于当前可用的全球肺功能测量，例如肺功能测试，直到它们显着提高为止。我们将使用图像登记来构建肺组织特异性体积变化区域分布的高分辨率3D图（与特定依从性有关）和呼吸呼吸肺的多个呼吸门控体积图像之间的肺组织应变张量。该项目中要开发的计算工具将提供评估整个呼吸周期中肺实质中关注区域的局部体积，灰度和形状变化的能力。我们预计，通过跟踪区域肺特异性体积变化的3D分布以及肺菌株的大小和方向，我们可以检查局部病理过程对患病组织以及周围正常组织的影响。此类信息可能会提供有关肺病理生理学的新见解，例如，肺气肿的肺破坏，肺栓塞的通风和灌注不匹配，哮喘区域气道关闭的影响以及急性肺损伤的区域力学和急性肺损伤的区域力学以及对通风术的传播。现在，此信息对于新的肺部疾病疗法的开发和评估至关重要。