title: Parametric response mapping monitors temporal changes on lung CT scans in the subpopulations and intermediate outcome measures in COPD Study (SPIROMICS).
abstract: OBJECTIVE
  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.
  
  
  METHODS
  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 (PRM(Normal)), emphysema (PRM(Emph)), and functional small airways disease (PRM(fSAD)). 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.
  
  
  RESULTS
  PRM metrics varied by ∼6.5% of total lung volume for PRM(Normal) and PRM(fSAD) and 1% for PRM(Emph) when testing 30-day repeatability. Over a 1-year interval, only PRM(Emph) in severe COPD subjects produced significant change (19%-21%). However, 11 of 76 subjects showed changes in PRM(fSAD) 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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Radiology, University of Michigan, Center for Molecular Imaging, Ann Arbor, MI 48109.
authors.forename: Jennifer L
authors.initials: JL
authors.lastname: Boes
authors.affiliation: Department of Radiology, University of Michigan, Center for Molecular Imaging, Ann Arbor, MI 48109.
authors.forename: Benjamin A
authors.initials: BA
authors.lastname: Hoff
authors.affiliation: Department of Radiology, University of Michigan, Center for Molecular Imaging, Ann Arbor, MI 48109.
authors.forename: Maria
authors.initials: M
authors.lastname: Bule
authors.affiliation: Department of Biostatistics, University of Michigan, Center for Molecular Imaging, Ann Arbor, Michigan.
authors.forename: Timothy D
authors.initials: TD
authors.lastname: Johnson
authors.affiliation: Department of Radiation Oncology, University of Michigan, Center for Molecular Imaging, Ann Arbor, MI.
authors.forename: Alnawaz
authors.initials: A
authors.lastname: Rehemtulla
authors.affiliation: Imbio, LLC, Minneapolis, Minnesota.
authors.forename: Ryan
authors.initials: R
authors.lastname: Chamberlain
authors.affiliation: Department of Radiology, University of Iowa, Iowa City, Iowa.
authors.forename: Eric A
authors.initials: EA
authors.lastname: Hoffman
authors.affiliation: Department of Radiology, University of Michigan, Center for Molecular Imaging, Ann Arbor, MI 48109.
authors.forename: Ella A
authors.initials: EA
authors.lastname: Kazerooni
authors.affiliation: Department of Medicine, Weill Cornell Medical College, New York, New York.
authors.forename: Fernando J
authors.initials: FJ
authors.lastname: Martinez
authors.affiliation: Department of Internal Medicine, University of Michigan, Center for Molecular Imaging, Ann Arbor, Michigan.
authors.forename: Meilan K
authors.initials: MK
authors.lastname: Han
authors.affiliation: Department of Radiology, University of Michigan, Center for Molecular Imaging, Ann Arbor, MI 48109.
authors.forename: Brian D
authors.initials: BD
authors.lastname: Ross
authors.affiliation: Department of Radiology, University of Michigan, Center for Molecular Imaging, Ann Arbor, MI 48109. Electronic address: cgalban@med.umich.edu.
authors.forename: Craig J
authors.initials: CJ
authors.lastname: Galbán
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D018450:Disease Progression; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008168:Lung / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D029424:Pulmonary Disease, Chronic Obstructive / Q000000981:diagnostic imaging*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*
keywords: Chronic obstructive pulmonary disease; computed tomography; diagnostic imaging; disease progression; parametric response map; small airways disease; voxel-wise analysis