Classification and Prognostication in Pulmonary Thromboembolism Using Computed Tomography Image Analytics

项目摘要 在西方世界，肺血栓栓塞症仍然是发病率和死亡率的重要原因。而当 急性肺栓塞(PE)的许多初始症状在适当的治疗下都会消失，有 提高对疾病的慢性影响的认识，包括慢性血栓栓塞症的发展 肺动脉高压(CTEPH)到持续性呼吸困难和运动障碍。许多患者最初 被诊断为PE的患者可能已经患有慢性病，并对急性疾病进行了不适当的治疗 病例可能是有害的，并推迟转诊到具有治疗慢性病经验的专门中心。在……上面 另一方面，许多急性PE患者尽管目前正在接受治疗，但仍继续发展为慢性病 确保解决问题的选择和后续行动仍然是一个挑战，特别是在没有能力预测谁会这样做的情况下 患上慢性病。此外，预测和选择治疗方法可能很困难，尤其是 在亚大规模急性PE和CTEPH中，特别是在新出现的治疗选择中。量化 需要一些方法来帮助在疾病表现的早期确定疾病轨迹，帮助指导预测和 治疗并提高我们对这种疾病的病理生理学的理解。 CT成像是评价肺血栓栓塞症的基石。在……里面 对于急性PE，它通常是评估治疗方案的第一种成像方式。作为病人 恢复后，它被用来检测慢性或复发的血栓，指导对慢性病的干预。CT研究进展 图像质量、图像处理(包括深度学习的应用)，再加上 计算能力使得从CT成像中提取大量新的特征成为可能。在这 建议我们寻求将我们团队在CT图像量化方面的经验与多中心纵向 数据开发的CT成像特征，可以识别和预测疾病的慢性化，其对 肺循环及其对治疗的反应。在目标1中，我们使用了来自三个学术机构的纵向数据 医院(布里格姆妇女医院、马萨诸塞州综合医院、西北大学)至 评估CT表现特征，预测慢性病的存在或发展。在目标2中，我们 同时研究演示和随访图像，以建立急性和慢性影响的量化模型 疾病对肺循环的影响，以帮助预测和改进非侵入性方法 预测持续性疾病与患者临床状态的相关性。在目标3中，我们使用了一个组合 CT-EPH手术患者和肺动脉高压患者的纵向显像 高血压，以确定将具有最理想的手术结果的患者。我们相信， 在这些互补目标中开发的功能和模型的组合将提高我们使用 临床可用的CT成像，以改善表型、预测和治疗决策并改善 我们对肺血栓栓塞性疾病纵向进展的理解。

Project Summary Pulmonary thromboembolism remains a significant cause of morbidity and mortality in the western world. While many of the initial symptoms in acute pulmonary embolism (PE) resolves with appropriate treatment, there is increasing awareness of chronic impact of the disease ranging from development of chronic thromboembolic pulmonary hypertension (CTEPH) to persisting dyspnea and exercise impairment. Many patients initially diagnosed with PE may already have chronic disease and inappropriate treatment for acute disease in these cases may be harmful and delay referral to specialized centers with experience in treating chronic disease. On the other hand many patients with acute PE go on to develop chronic disease despite current treatment options and follow-up to insure resolution remains a challenge particularly without the ability to predict who will develop chronic disease. Furthermore, prognostication and selection of treatments can be difficult, particularly in submassive acute PE and CTEPH, particularly with newly emerging treatment choices. Quantitative methods are needed to help define disease trajectories early in presentation, help guide prognostication and treatment and improve our understanding of the pathophysiology of this condition. Computed Tomography (CT) imaging is the cornerstone of evaluation of pulmonary thromboembolism. In acute PE, it is the often the first imaging modality available for assessing treatment options. As the patient recovers, it is used to detect chronic or reoccurring clot guide interventions in chronic disease. Advances in CT imaging quality, image processing (including application of deep learning), coupled with increasing computation power make possible the extraction of a large number of novel features from CT imaging. In this proposal we seek to combine our team’s experience in CT image quantification with multi-center longitudinal data to develop CT imaging features that can identify and predict disease chronicity, its impact on the pulmonary circulation and its response to treatment. In Aim 1 we utilize longitudinal data from three academic hospitals (Brigham and Women’s Hospital, Massachusetts General Hospital, Northwestern University) to assess CT features at presentation that predict the presence or development of chronic disease. In Aim 2, we study both the presentation and follow-up image to build quantitative models of the impact of acute and chronic disease on the pulmonary circulation in order to help with prognostication and improve non-invasive methods of predicting the relevance of persistent disease to the clinical state of patients. In aim 3 we use a combination of longitudinal imaging in CTEPH patients having undergone surgery and patients with pulmonary arterial hypertension to identify patients that would have the most optimal surgical outcomes. We believe that the combination of the features and models developed in these complementary aims will advance our ability to use clinically available CT imaging to improve phenotyping, prognostication and treatment decisions and improve our understanding of the longitudinal progression of pulmonary thromboembolic disease.