Parametric Response Mapping Monitors Temporal Changes on Lung CT Scans in the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)

Jennifer L Boes; Benjamin A Hoff; Maria Bule; Timothy D Johnson; Alnawaz Rehemtulla; Ryan Chamberlain; Eric A Hoffman; Ella A Kazerooni; Fernando J Martinez; Meilan K Han; Brian D Ross; Craig J Galbán

doi:10.1016/j.acra.2014.08.015

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Parametric Response Mapping Monitors Temporal Changes on Lung CT Scans in the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)

Journal article

Peer reviewed

Parametric Response Mapping Monitors Temporal Changes on Lung CT Scans in the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)

Jennifer L Boes, Benjamin A Hoff, Maria Bule, Timothy D Johnson, Alnawaz Rehemtulla, Ryan Chamberlain, Eric A Hoffman, Ella A Kazerooni, Fernando J Martinez, Meilan K Han, …

Academic radiology, Vol.22(2), pp.186-194

02/2015

DOI: 10.1016/j.acra.2014.08.015

PMCID: PMC4289437

PMID: 25442794

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https://www.ncbi.nlm.nih.gov/pmc/articles/4289437View

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Abstract

The longitudinal relationship between regional air trapping and emphysema remains unexplored. We have sought to demonstrate the utility of parametric response mapping (PRM), a computed tomography (CT)–based biomarker, for monitoring regional disease progression in chronic obstructive pulmonary disease (COPD) patients, linking expiratory- and inspiratory-based CT metrics over time. Inspiratory and expiratory lung CT scans were acquired from 89 COPD subjects with varying Global Initiative for Chronic Obstructive Lung Disease (GOLD) status at 30 days (n = 13) or 1 year (n = 76) from baseline as part of the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) clinical trial. PRMs of CT data were used to quantify the relative volumes of normal parenchyma (PRMNormal), emphysema (PRMEmph), and functional small airways disease (PRMfSAD). PRM measurement variability was assessed using the 30-day interval data. Changes in PRM metrics over a 1-year period were correlated to pulmonary function (forced expiratory volume at 1 second [FEV1]). A theoretical model that simulates PRM changes from COPD was compared to experimental findings. PRM metrics varied by ∼6.5% of total lung volume for PRMNormal and PRMfSAD and 1% for PRMEmph when testing 30-day repeatability. Over a 1-year interval, only PRMEmph in severe COPD subjects produced significant change (19%–21%). However, 11 of 76 subjects showed changes in PRMfSAD greater than variations observed from analysis of 30-day data. Mathematical model simulations agreed with experimental PRM results, suggesting fSAD is a transitional phase from normal parenchyma to emphysema. PRM of lung CT scans in COPD patients provides an opportunity to more precisely characterize underlying disease phenotypes, with the potential to monitor disease status and therapy response.

Computed Tomography

parametric response map

small airways disease

Chronic obstructive pulmonary disease

disease progression

voxel-wise analysis

diagnostic imaging

Details

Title: Subtitle: Parametric Response Mapping Monitors Temporal Changes on Lung CT Scans in the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)
Creators: Jennifer L Boes - Department of Radiology, University of Michigan, Center for Molecular Imaging, Ann Arbor, MI 48109
Benjamin A Hoff - Department of Radiology, University of Michigan, Center for Molecular Imaging, Ann Arbor, MI 48109
Maria Bule - Department of Radiology, University of Michigan, Center for Molecular Imaging, Ann Arbor, MI 48109
Timothy D Johnson - Department of Biostatistics, University of Michigan, Center for Molecular Imaging, Ann Arbor, Michigan
Alnawaz Rehemtulla - Department of Radiation Oncology, University of Michigan, Center for Molecular Imaging, Ann Arbor, MI
Ryan Chamberlain - Imbio, LLC, Minneapolis, Minnesota
Eric A Hoffman - Department of Radiology, University of Iowa, Iowa City, Iowa
Ella A Kazerooni - Department of Radiology, University of Michigan, Center for Molecular Imaging, Ann Arbor, MI 48109
Fernando J Martinez - Department of Medicine, Weill Cornell Medical College, New York, New York
Meilan K Han - Department of Internal Medicine, University of Michigan, Center for Molecular Imaging, Ann Arbor, Michigan
Brian D Ross - Department of Radiology, University of Michigan, Center for Molecular Imaging, Ann Arbor, MI 48109
Craig J Galbán - Department of Radiology, University of Michigan, Center for Molecular Imaging, Ann Arbor, MI 48109
Resource Type: Journal article
Publication Details: Academic radiology, Vol.22(2), pp.186-194
DOI: 10.1016/j.acra.2014.08.015
PMID: 25442794
PMCID: PMC4289437
NLM abbreviation: Acad Radiol
ISSN: 1076-6332
eISSN: 1878-4046
Publisher: Elsevier Inc
Grant note: HHSN268200900013C; HHSN268200900014C; HHSN268200900015C; HHSN268200900016C; HHSN268200900017C; HHSN268200900018C; HHSN2682009000019C; HHSN268200900020C / National Heart, Lung, and Blood Institute (http://dx.doi.org/10.13039/100000050) R01HL122438; P50CA93990; P01CA085878; R44HL118837 / National Institutes of Health (http://dx.doi.org/10.13039/100000002) T32EB005172 / National Institutes of Health (http://dx.doi.org/10.13039/100000002)
Language: English
Date published: 02/2015
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Radiology; Internal Medicine
Record Identifier: 9984051995002771

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