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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：
10066325
负责人：
Edward Castillo
金额：
$ 7.57万
依托单位：
UNIVERSITY OF COLORADO DENVER
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-01-01 至 2021-04-05
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10066325
关键词：
Address Algorithms Anatomy Cancer Patient Characteristics Chest Clinic Clinical Clinical Data Clinical Trials 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 image processing imaging modality imaging program improved improved outcome industry partner innovation knowledge base machine learning method novel novel imaging technique 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 4DCT- ventilation 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 4DCT- ventilation 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.

我们的项目提出了一个学术-工业合作伙伴关系，以翻译一种新的肺功能成像