Chronic obstructive pulmonary disease (COPD) is a highly and increasingly prevalent disorder characterized by incomplete reversible airflow limitations. It is presently the third leading cause of death in the US, with over 13 million peopl suffering from the disease. Pulmonary function tests are used to identify global lung function impairment;however, determining the specific cause of decreased lung function is necessary in order to choose the best treatment strategy. We have recently developed the Parametric Response Map (PRM) as a CT-based imaging biomarker capable of diagnosing the two major phenotypes in COPD: functional small airways disease (fSAD) and emphysema. This diagnostic biomarker is a game-changer for radiological and pulmonary medicine practice, but in order for its impact to be fully realized, a commercial, FDA-approved diagnostic analysis and reporting software application must be developed. We propose to develop PRM as a CT-imaging biomarker for assessment and diagnosis of COPD phenotypes and for visualizing detailed spatial information related to disease location. The goals of this proposal will focus on development of a commercial PRM diagnostic software application, including its validation as a surrogate marker of patient health status, using images and patient information obtained from the NIH-sponsored clinical trial COPDGene. First, the PRM algorithm will be developed into a commercially viable software package. After validating the output of each individual component of the commercial PRM software against the in-house analysis of the inventors of PRM at the University of Michigan, the complete PRM analysis of 194 patients by the new software will be compared to previously published results to confirm that the commercial software gives accurate PRM results. Then the CT images from 500 patients will be analyzed to optimize the input parameters of the PRM analysis to ensure that the PRM results accurately predict COPD progression. Overall, it is anticipated that the successful outcome of this effort will significanty improve the diagnostic capability of CT imaging for COPD, leading to improved patient care and a reduction in cost to the healthcare system.
This proposal will develop a commercial software package that performs a Parametric Response Map analysis on CT images of patients with chronic obstructive pulmonary disease (COPD), presently the third leading cause of death in the US, in order to give physicians a more detailed description of the underlying cause of COPD for that patient. The successful outcome of this effort will give physicians greater insight into which course of treatment is appropriate for each individual patient, leading to improved patient care and a reduction in cost to the healthcare system.
|Fernández-Baldera, Antonio; Hatt, Charles R; Murray, Susan et al. (2017) Correcting Nonpathological Variation in Longitudinal Parametric Response Maps of CT Scans in COPD Subjects: SPIROMICS. Tomography 3:138-145|
|Martinez, Carlos H; Diaz, Alejandro A; Meldrum, Catherine et al. (2017) Age and Small Airway Imaging Abnormalities in Subjects with and without Airflow Obstruction in SPIROMICS. Am J Respir Crit Care Med 195:464-472|
|Belloli, Elizabeth A; Degtiar, Irina; Wang, Xin et al. (2017) Parametric Response Mapping as an Imaging Biomarker in Lung Transplant Recipients. Am J Respir Crit Care Med 195:942-952|
|Hoff, Benjamin A; Pompe, Esther; Galbán, Stefanie et al. (2017) CT-Based Local Distribution Metric Improves Characterization of COPD. Sci Rep 7:2999|
|Fernandes, Lalita; Gulati, Nandani; Fernandes, Yasmin et al. (2017) Small airway imaging phenotypes in biomass- and tobacco smoke-exposed patients with COPD. ERJ Open Res 3:|
|Bhatt, Surya P; Soler, Xavier; Wang, Xin et al. (2016) Association between Functional Small Airway Disease and FEV1 Decline in Chronic Obstructive Pulmonary Disease. Am J Respir Crit Care Med 194:178-84|
|Verleden, S E; Vos, R; Vandermeulen, E et al. (2016) Parametric Response Mapping of Bronchiolitis Obliterans Syndrome Progression After Lung Transplantation. Am J Transplant 16:3262-3269|
|Boes, Jennifer L; Hoff, Benjamin A; Bule, Maria et al. (2015) Parametric response mapping monitors temporal changes on lung CT scans in the subpopulations and intermediate outcome measures in COPD Study (SPIROMICS). Acad Radiol 22:186-94|
|Boudewijn, Ilse M; Postma, Dirkje S; Telenga, Eef D et al. (2015) Effects of ageing and smoking on pulmonary computed tomography scans using parametric response mapping. Eur Respir J 46:1193-6|
|Boes, Jennifer L; Bule, Maria; Hoff, Benjamin A et al. (2015) The Impact of Sources of Variability on Parametric Response Mapping of Lung CT Scans. Tomography 1:69-77|