慢性阻塞性肺疾病组织缺血的影像学预警研究

慢性阻塞性肺疾病（COPD）是小气道气流受限引起的慢性肺组织缺血缺氧性疾病，其发病率高，预后差，造成了严重的社会负担。早期诊断、早期干预是延缓疾病进展、降低COPD病死率的重要环节。早期COPD重要的病理改变是小血管和小气道的重塑，及其引起的肺组织缺血、通气障碍等肺部及全身改变，影像学预警指标对指导临床早期干预具有重要意义。本项目聚焦于COPD早期定量、定性诊断和功能预警，针对小血管、小气道重塑评估，肺气血交换评估及人工智能模型构建三个关键科学问题，拟建立肺小血管和小气道重塑的HRCT定量定性新方法，实现肺微小结构的精准量化评价；通过超极化129Xe肺MRI功能成像，实现肺泡水平肺气血交换的功能和定量评价；通过深度学习人工智能方法，研发COPD诊断与分级系统，有望实现COPD从微观结构到功能评价以及智能分析的早期影像学干预与预警；精准评价其缺血缺氧变化，指导早期治疗，提高诊治水平。

Chronic obstructive pulmonary disease is a chronic and ischemia pulmonary disease due to the airflow limitation. With high incidence and poor prognosis, it has become a serious social burden. Early diagnosis and early intervention are the key to control the progression and reduce the mortality. The small pulmonary vessels and airways remodeling are the important pathological abnormalities, which would cause pulmonary and systemic changes, such as ischemic and dysfunction of ventilation. The early warning of imaging marker is very crucial to instruct the clinic for the early intervention. Focusing on the early quantitative and qualitive diagnosis and warning of function of COPD, 3 key points of COPD are the evaluation of small vessel and airway remodeling of COPD, pulmonary exchange, and building the AI model. The purpose of the program was to develop the latest HRCT or micro-CT quantitative method for the quantitative evaluation of pulmonary microstructure accurately. The hyperpolarized Xe129 MRI can evaluate the pulmonary exchange on the alveolar level. The deep learning technique would be performed to develop the diagnosis and classification system of COPD. Based on these, the early imaging warning and intervention would be accomplished from the microstructure, functional evaluation and intelligent analysis. Therefore, the precise evaluation of pulmonary microstructure and functional change caused by pulmonary ischemic, would instruct the clinic for early intervention, then improve the diagnostic and therapeutic level of COPD in our country.