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Tomography
Volume 3
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10.18383/j.tom.2017.00013
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Article

Correcting Nonpathological Variation in Longitudinal Parametric Response Maps of CT Scans in COPD Subjects: SPIROMICS

by
Antonio Fernández-Baldera
1,
Charles R. Hatt
2,
Susan Murray
3,
Eric A. Hoffman
4,
Ella A. Kazerooni
1,
Fernando J. Martinez
5,
MeiLan K. Han
6 and
Craig J. Galbán
1,*
1
Department of Radiology, University of Michigan, BSRB, Room A506, 109 Zina Pitcher Place, Ann Arbor, MI 48109, USA
2
Imbio, LLC. Minneapolis, MN 55402, USA
3
Department of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
4
Departments of Radiology and Biomedical Engineering, University of Iowa, IA 52242, USA
5
Department of Medicine, Cornell University, NY 10021, USA
6
Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA
*
Author to whom correspondence should be addressed.
Tomography 2017, 3(3), 138-145; https://doi.org/10.18383/j.tom.2017.00013
Submission received: 2 June 2017 / Revised: 12 July 2017 / Accepted: 7 August 2017 / Published: 1 September 2017
Versions Notes

Abstract

Small airways disease (SAD) is one of the leading causes of airflow limitations in patients diagnosed with chronic obstructive pulmonary disease (COPD). Parametric response mapping (PRM) of computed tomography (CT) scans allows for the quantification of this previously invisible COPD component. Although PRM is being investigated as a diagnostic tool for COPD, variability in the longitudinal measurements of SAD by PRM has been reported. Here, we show a method for correcting longitudinal PRM data because of nonpathological variations in serial CT scans. In this study, serial whole-lung high-resolution CT scans over a 30-day interval were obtained from 90 subjects with and without COPD accrued as part of SPIROMICS. It was assumed in all subjects that the COPD did not progress between examinations. CT scans were acquired at inspiration and expiration, spatially aligned to a single geometric frame, and analyzed using PRM. By modeling variability in longitudinal CT scans, our method could identify, at the voxel-level, shifts in PRM classification over the 30-day interval. In the absence of any correction, PRM generated serial percent volumes of functional SAD with differences as high as 15%. Applying the correction strategy significantly mitigated this effect with differences ∼1%. At the voxel-level, significant differences were found between baseline PRM classifications and the follow-up map computed with and without correction (P < .01 over GOLD). This strategy of accounting for nonpathological sources of variability in longitudinal PRM may improve the quantification of COPD phenotypes transitioning with disease progression.
Keywords: COPD; parametric response mapping; longitudinal; computed tomography COPD; parametric response mapping; longitudinal; computed tomography

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MDPI and ACS Style

Fernández-Baldera, A.; Hatt, C.R.; Murray, S.; Hoffman, E.A.; Kazerooni, E.A.; Martinez, F.J.; Han, M.K.; Galbán, C.J. Correcting Nonpathological Variation in Longitudinal Parametric Response Maps of CT Scans in COPD Subjects: SPIROMICS. Tomography 2017, 3, 138-145. https://doi.org/10.18383/j.tom.2017.00013

AMA Style

Fernández-Baldera A, Hatt CR, Murray S, Hoffman EA, Kazerooni EA, Martinez FJ, Han MK, Galbán CJ. Correcting Nonpathological Variation in Longitudinal Parametric Response Maps of CT Scans in COPD Subjects: SPIROMICS. Tomography. 2017; 3(3):138-145. https://doi.org/10.18383/j.tom.2017.00013

Chicago/Turabian Style

Fernández-Baldera, Antonio, Charles R. Hatt, Susan Murray, Eric A. Hoffman, Ella A. Kazerooni, Fernando J. Martinez, MeiLan K. Han, and Craig J. Galbán. 2017. "Correcting Nonpathological Variation in Longitudinal Parametric Response Maps of CT Scans in COPD Subjects: SPIROMICS" Tomography 3, no. 3: 138-145. https://doi.org/10.18383/j.tom.2017.00013

APA Style

Fernández-Baldera, A., Hatt, C. R., Murray, S., Hoffman, E. A., Kazerooni, E. A., Martinez, F. J., Han, M. K., & Galbán, C. J. (2017). Correcting Nonpathological Variation in Longitudinal Parametric Response Maps of CT Scans in COPD Subjects: SPIROMICS. Tomography, 3(3), 138-145. https://doi.org/10.18383/j.tom.2017.00013

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