Tomography

Vol. 3 No. 3 - Sep 2017

Tomography is a scientific journal for publication of articles in imaging research

Issue link: http://www.cenveomobile.com/i/875450

Contents of this Issue

Navigation

Page 21 of 59

Correcting Nonpathological Variation in Longitudinal Parametric Response Maps of CT Scans in COPD Subjects: SPIROMICS 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, Ann Arbor, MI; 2 Imbio, LLC. Minneapolis, MN; 3 Department of Public Health, University of Michigan, Ann Arbor, MI; 4 Departments of Radiology and Biomedical Engineering, University of Iowa, IA; 5 Department of Medicine, Cornell University, NY; and 6 Department of Internal Medicine, University of Michigan, Ann Arbor, MI Corresponding Author: Craig J. Galbán, PhD Department of Radiology, University of Michigan, BSRB, Room A506, 109 Zina Pitcher Place, Ann Arbor, MI 48109-2200; E-mail: cgalban@med.umich.edu Key Words: COPD, parametric response mapping, longitudinal, computed tomography Abbreviations: Small airways disease (SAD), chronic obstructive pulmonary disease (COPD), parametric response mapping (PRM), computed tomography (CT), high-resolution computed tomography (HRCT), functional SAD (fSAD), Hounsfield unit (HU), forced expiratory volume at 1 second (FEV1), field of view (FOV), body mass index (BMI), index of measurement variability (IMV), interquartile range (IQR) 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 tomogra- phy (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 non- pathological 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 mod- eling variability in longitudinal CT scans, our method could identify, at the voxel-level, shifts in PRM classifi- cation 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 strat- egy of accounting for nonpathological sources of variability in longitudinal PRM may improve the quantifica- tion of COPD phenotypes transitioning with disease progression. INTRODUCTION Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity, mortality, and burden on the world's health and financial systems (1, 2). Advances in the clinical manage- ment of patients with COPD have led to an improved under- standing of the multitude COPD phenotypes. It has been postu- lated that a spectrum of pathological processes may result in unique progression patterns among these patients. Extensive research has been devoted toward identifying surrogate bio- markers of disease progression with a strong emphasis on non- invasive imaging techniques and analytical approaches (3). Parametric response mapping (PRM) is an analytical ap- proach that, when applied to spatially aligned high-resolution computed tomography (HRCT) scans, allows both visualization and quantification of lung parenchyma affected by small air- ways disease (SAD), even when only emphysema is visibly observed (4). This technique quantifies a previously occult com- ponent of COPD and can be applied to retrospective HRCT data. Included in various NIH-funded clinical trials on COPD (5, 6), PRM of functional SAD (fSAD) has been demonstrated as an independent indicator of clinically relevant outcome measures (7). More recent studies have identified PRM as a surrogate of spirometric decline in COPD (7) and also a means for identifying and monitoring the onset of bronchiolitis obliterans syndrome in bone marrow and lung transplant recipients (8-10). In a preliminary study, PRM was evaluated as a marker for monitor- ing change in disease classification (ie, normal, fSAD, and em- physema) from subjects accrued as part of SPIROMICS (5). In this study, "voxel-based tracking," a method for evaluating longitudi- nal changes in PRM classification at the voxel level, has been used. Although this approach when applied to PRM shows promise at providing local disease progression, variability in RESEARCH ARTICLE ABSTRACT © 2017 The Authors. Published by Grapho Publications, LLC This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). ISSN 2379-1381 http://dx.doi.org/10.18383/j.tom.2017.00013 138 TOMOGRAPHY.ORG | VOLUME 3 NUMBER 3 | SEPTEMBER 2017

Articles in this issue

Links on this page

Archives of this issue

view archives of Tomography - Vol. 3 No. 3 - Sep 2017