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.
Our project proposes to form an academic-industrial partnership to translate a novel lung function imaging modality into radiotherapy clinical care for lung cancer patients. The novel lung function imaging modality is referred to as `4DCT-ventilation,' and uses 4-Dimensional CT data along with image processing techniques to innovatively calculate lung functional maps. 4DCT-ventilation has great potential to reduce toxicity and improve outcomes for lung cancer patients undergoing radiation therapy. Our project will develop methods that will enable widespread clinical integration of this novel imaging modality.
