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Development of a Novel Lung Function Imaging Modality for comprehensive management of lung cancer

开发用于肺癌综合管理的新型肺功能成像模式

基本信息

批准号：
10747688
负责人：
Edward Castillo
金额：
$ 10.24万
依托单位：
THOMAS JEFFERSON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-05-29 至 2025-12-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10747688
关键词：
Address Algorithms Anatomy Cancer Patient Characteristics Chest Clinic Clinical Clinical Data Clinical Trials Commercial grade Computer software Data Data Set Development Dose Engineering Environment Evaluation Feasibility Studies Four-dimensional Generations Heterogeneity Image Imaging Techniques Individual Industrialization Institution Life Lung Malignant neoplasm of lung Maps Methods Patients Performance Physiological Quality of life Radiation Radiation Pneumonitis Radiation therapy Research Resolution Retrospective Studies Seminal Software Tools Study models System Techniques Toxic effect Translating Treatment Side Effects Validation automated segmentation clinical care clinical practice clinically significant community center early phase trial experience four-dimensional computed tomography image processing imaging modality improved improved outcome industry partner innovation knowledge base machine learning method novel novel imaging technique programs prospective pulmonary function quality assurance side effect software development standard of care tool ventilation

项目摘要

Our project proposes an academic-industrial partnership to translate a novel lung function imaging modality into clinical care for lung cancer patients receiving radiation therapy. Lung cancer patients being treated with radiation can experience serious and sometimes life threatening thoracic side effects from treatment. There is emerging data demonstrating that a novel lung function imaging modality can reduce side-effects and improve quality of life for lung cancer patients undergoing radiation therapy. The novel lung function imaging modality, referred to as `4DCT-ventilation,' uses 4DCT data along with image processing techniques to innovatively calculate lung ventilation maps. 4DCT-ventilation can improve outcomes for lung cancer patients by enabling the generation of functional avoidance radiotherapy plans. Functional avoidance uses 4DCT-ventilation to avoid functional portions of the lung, with the hypothesis that reducing dose to functional lung will reduce thoracic side effects. Our 4DCT-ventilation research has progressed from retrospective studies to an early- phase trial using 4DCT-ventilation for functional avoidance radiotherapy. The early promising toxicity results from 4DCTventilation clinical trials is providing a strong rationale for national trials and expanded clinical integration across individual clinics. The problem is that expanded clinical integration of 4DCT-ventilation is currently not possible due to a lack of consistent, efficient, and clinically validated methods. We propose an academic-industry partnership with MIM Software to address these challenges precluding clinical integration of 4DCT-ventilation. The purpose of our study is to develop methods that enable safe, efficient, and clinically validated methods for clinical integration of 4DCT-ventilation functional avoidance. Our overarching hypothesis is that the 4DCT-ventilation functional avoidance innovations we develop will be demonstrated to reduce lung toxicity in clinics with no prior 4DCT-ventilation experience. The project will be carried out in 3 aims. Aim 1 will develop methods that enable automated 4DCT-ventilation calculations including auto-segmentation, statistically-robust calculation methods, and clinically-efficient quality assurance tools. Aim 2 will develop methods for 4DCTventilation functional avoidance radiotherapy including image heterogeneity assessment, development of knowledge-based functional planning methods, and evaluation of metrics most critical in reducing toxicity. In conjunction with our industry partner, the developed methods from Aims 1 and 2 will be integrated in a commercial-grade software tool. Aim 3 will evaluate feasibility by assessing whether 4DCT- ventilation functional avoidance can be demonstrated to reduce toxicity in clinics with no prior 4DCT-ventilation experience. Our project will generate both the tools and data needed to provide guidance on how to properly incorporate 4DCT-ventilation into clinical care. The methods and data will culminate in a commercial-grade platform suitable for busy clinics. 4DCT-ventilation has great potential to improve outcomes for lung cancer patients and our project will enable the integration of this novel imaging modality into clinical care.

我们的项目提出了学术-工业合作伙伴关系，以转化一种新型的肺功能成像模式进入接受放射治疗的肺癌患者的临床护理。正在接受治疗的肺癌患者放射治疗可能会产生严重的、有时甚至危及生命的胸部副作用。有新出现的数据表明，一种新型的肺功能成像方式可以减少副作用并改善接受放射治疗的肺癌患者的生活质量。新颖的肺功能成像模式，被称为“4DCT-通风”，使用 4DCT 数据和图像处理技术创新地计算肺通气图。 4DCT 通气可以改善肺癌患者的预后功能性避免放射治疗计划的生成。功能性回避使用 4DCT 通气来避免肺的功能部分，假设减少功能肺的剂量会减少胸部副作用。我们的 4DCT 通气研究已从回顾性研究进展到早期研究使用 4DCT 通气进行功能性避免放射治疗的阶段试验。早期有希望的毒性结果 4DCT 通气临床试验为国家试验和扩大临床试验提供了强有力的依据各个诊所之间的整合。问题是 4DCT 通气的临床整合扩展是由于缺乏一致、有效和经过临床验证的方法，目前尚不可能。我们提出一个学术界与 MIM Software 合作，解决这些阻碍临床整合的挑战 4DCT-通风。我们研究的目的是开发能够安全、高效、临床应用的方法 4DCT-通气功能性避免临床整合的经过验证的方法。我们的总体假设我们开发的 4DCT 通气功能回避创新将被证明可以减少肺损伤在没有 4DCT 通气经验的诊所中的毒性。该项目将实现3个目标。目标1将开发能够实现自动 4DCT 通气计算的方法，包括自动分段、统计稳健的计算方法和临床有效的质量保证工具。目标2将发展 4DCT通气功能性避免放射治疗的方法，包括图像异质性评估，开发基于知识的功能规划方法，以及评估最关键的指标减少毒性。与我们的行业合作伙伴一起，目标 1 和 2 开发的方法将是集成在商业级软件工具中。目标 3 将通过评估 4DCT 是否可行来评估可行性在没有事先进行 4DCT 通气的诊所中，通气功能性避免可以被证明可以减少毒性经验。我们的项目将生成所需的工具和数据，为如何正确地提供指导将 4DCT 通气纳入临床护理。这些方法和数据最终将形成商业级适合繁忙诊所的平台。 4DCT 通气在改善肺癌预后方面具有巨大潜力患者和我们的项目将使这种新颖的成像方式整合到临床护理中。