1
|
Fat M, Andersen T, Fazio JC, Park SC, Abtin F, Buhr RG, Phillips JE, Belperio J, Tashkin DP, Cooper CB, Barjaktarevic I. Association of bronchial disease on CT imaging and clinical definitions of chronic bronchitis in a single-center COPD phenotyping study. Respir Med 2024; 231:107733. [PMID: 38986793 DOI: 10.1016/j.rmed.2024.107733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 06/09/2024] [Accepted: 07/04/2024] [Indexed: 07/12/2024]
Abstract
INTRODUCTION Chronic Bronchitis (CB) represents a phenotype of chronic obstructive pulmonary disease (COPD). While several definitions have been used for diagnosis, the relationship between clinical definitions and radiologic assessment of bronchial disease (BD) has not been well studied. The aim of this study was to evaluate the relationship between three clinical definitions of CB and radiographic findings of BD in spirometry-defined COPD patients. METHODS A cross-sectional analysis was performed from a COPD phenotyping study. It was a prospective observational cohort. Participants had spirometry-defined COPD and available chest CT imaging. Comparison between CB definitions, Medical Research Council (CBMRC), St. George's Respiratory Questionnaire (CBSGRQ), COPD Assessment Test (CBCAT) and CT findings were performed using Cohen's Kappa, univariate and multivariate logistic regressions. RESULTS Of 112 participants, 83 met inclusion criteria. Demographics included age of 70.1 ± 7.0 years old, predominantly male (59.0 %), 45.8 ± 30.8 pack-year history, 21.7 % actively smoking, and mean FEV1 61.5 ± 21.1 %. With MRC, SGRQ and CAT definitions, 22.9 %, 36.6 % and 28.0 % had CB, respectively. BD was more often present in CB compared to non-CB patients; however, it did not have a statistically significant relationship between any of the CB definitions. CBSGRQ had better agreement with radiographically assessed BD compared to the other two definitions. CONCLUSION Identification of BD on CT was associated with the diagnoses of CB. However, agreement between imaging and definitions were not significant, suggesting radiologic findings of BD and criteria defining CB may not identify the same COPD phenotype. Research to standardize imaging and clinical methods is needed for more objective identification of COPD phenotypes.
Collapse
Affiliation(s)
- Marisa Fat
- Graduate Education, University of California, Los Angeles (UCLA), Los Angeles, CA, USA; Anne Burnett Marion School of Medicine at TCU, Fort Worth, TX, USA
| | - Tyler Andersen
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Jane C Fazio
- Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Seon Cheol Park
- Division of Pulmonology, Department of Internal Medicine, National Health Insurance Service Ilsan Hospital, Goyang, Republic of Korea
| | | | - Russell G Buhr
- Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | | | - John Belperio
- Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Donald P Tashkin
- Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Christopher B Cooper
- Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Exercise Physiology Research Laboratory, Department of Physiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Igor Barjaktarevic
- Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
| |
Collapse
|
2
|
Fletcher JG, Inoue A, Bratt A, Horst KK, Koo CW, Rajiah PS, Baffour FI, Ko JP, Remy-Jardin M, McCollough CH, Yu L. Photon-counting CT in Thoracic Imaging: Early Clinical Evidence and Incorporation Into Clinical Practice. Radiology 2024; 310:e231986. [PMID: 38501953 DOI: 10.1148/radiol.231986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/20/2024]
Abstract
Photon-counting CT (PCCT) is an emerging advanced CT technology that differs from conventional CT in its ability to directly convert incident x-ray photon energies into electrical signals. The detector design also permits substantial improvements in spatial resolution and radiation dose efficiency and allows for concurrent high-pitch and high-temporal-resolution multienergy imaging. This review summarizes (a) key differences in PCCT image acquisition and image reconstruction compared with conventional CT; (b) early evidence for the clinical benefit of PCCT for high-spatial-resolution diagnostic tasks in thoracic imaging, such as assessment of airway and parenchymal diseases, as well as benefits of high-pitch and multienergy scanning; (c) anticipated radiation dose reduction, depending on the diagnostic task, and increased utility for routine low-dose thoracic CT imaging; (d) adaptations for thoracic imaging in children; (e) potential for further quantitation of thoracic diseases; and (f) limitations and trade-offs. Moreover, important points for conducting and interpreting clinical studies examining the benefit of PCCT relative to conventional CT and integration of PCCT systems into multivendor, multispecialty radiology practices are discussed.
Collapse
Affiliation(s)
- Joel G Fletcher
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905 (J.G.F., A.I., A.B., K.K.H., C.W.K., P.S.R., F.I.B., C.H.M., L.Y.); Department of Radiology, Shiga University of Medical Science, Shiga, Japan (A.I.); Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, New York, NY (J.P.K.); and IMALLIANCE-Haut-de-France, Valenciennes, France (M.R.J.)
| | - Akitoshi Inoue
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905 (J.G.F., A.I., A.B., K.K.H., C.W.K., P.S.R., F.I.B., C.H.M., L.Y.); Department of Radiology, Shiga University of Medical Science, Shiga, Japan (A.I.); Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, New York, NY (J.P.K.); and IMALLIANCE-Haut-de-France, Valenciennes, France (M.R.J.)
| | - Alex Bratt
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905 (J.G.F., A.I., A.B., K.K.H., C.W.K., P.S.R., F.I.B., C.H.M., L.Y.); Department of Radiology, Shiga University of Medical Science, Shiga, Japan (A.I.); Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, New York, NY (J.P.K.); and IMALLIANCE-Haut-de-France, Valenciennes, France (M.R.J.)
| | - Kelly K Horst
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905 (J.G.F., A.I., A.B., K.K.H., C.W.K., P.S.R., F.I.B., C.H.M., L.Y.); Department of Radiology, Shiga University of Medical Science, Shiga, Japan (A.I.); Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, New York, NY (J.P.K.); and IMALLIANCE-Haut-de-France, Valenciennes, France (M.R.J.)
| | - Chi Wan Koo
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905 (J.G.F., A.I., A.B., K.K.H., C.W.K., P.S.R., F.I.B., C.H.M., L.Y.); Department of Radiology, Shiga University of Medical Science, Shiga, Japan (A.I.); Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, New York, NY (J.P.K.); and IMALLIANCE-Haut-de-France, Valenciennes, France (M.R.J.)
| | - Prabhakar Shantha Rajiah
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905 (J.G.F., A.I., A.B., K.K.H., C.W.K., P.S.R., F.I.B., C.H.M., L.Y.); Department of Radiology, Shiga University of Medical Science, Shiga, Japan (A.I.); Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, New York, NY (J.P.K.); and IMALLIANCE-Haut-de-France, Valenciennes, France (M.R.J.)
| | - Francis I Baffour
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905 (J.G.F., A.I., A.B., K.K.H., C.W.K., P.S.R., F.I.B., C.H.M., L.Y.); Department of Radiology, Shiga University of Medical Science, Shiga, Japan (A.I.); Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, New York, NY (J.P.K.); and IMALLIANCE-Haut-de-France, Valenciennes, France (M.R.J.)
| | - Jane P Ko
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905 (J.G.F., A.I., A.B., K.K.H., C.W.K., P.S.R., F.I.B., C.H.M., L.Y.); Department of Radiology, Shiga University of Medical Science, Shiga, Japan (A.I.); Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, New York, NY (J.P.K.); and IMALLIANCE-Haut-de-France, Valenciennes, France (M.R.J.)
| | - Martine Remy-Jardin
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905 (J.G.F., A.I., A.B., K.K.H., C.W.K., P.S.R., F.I.B., C.H.M., L.Y.); Department of Radiology, Shiga University of Medical Science, Shiga, Japan (A.I.); Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, New York, NY (J.P.K.); and IMALLIANCE-Haut-de-France, Valenciennes, France (M.R.J.)
| | - Cynthia H McCollough
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905 (J.G.F., A.I., A.B., K.K.H., C.W.K., P.S.R., F.I.B., C.H.M., L.Y.); Department of Radiology, Shiga University of Medical Science, Shiga, Japan (A.I.); Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, New York, NY (J.P.K.); and IMALLIANCE-Haut-de-France, Valenciennes, France (M.R.J.)
| | - Lifeng Yu
- From the Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905 (J.G.F., A.I., A.B., K.K.H., C.W.K., P.S.R., F.I.B., C.H.M., L.Y.); Department of Radiology, Shiga University of Medical Science, Shiga, Japan (A.I.); Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, New York, NY (J.P.K.); and IMALLIANCE-Haut-de-France, Valenciennes, France (M.R.J.)
| |
Collapse
|
3
|
Saha PK, Nadeem SA, Comellas AP. A Survey on Artificial Intelligence in Pulmonary Imaging. WILEY INTERDISCIPLINARY REVIEWS. DATA MINING AND KNOWLEDGE DISCOVERY 2023; 13:e1510. [PMID: 38249785 PMCID: PMC10796150 DOI: 10.1002/widm.1510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Accepted: 06/21/2023] [Indexed: 01/23/2024]
Abstract
Over the last decade, deep learning (DL) has contributed a paradigm shift in computer vision and image recognition creating widespread opportunities of using artificial intelligence in research as well as industrial applications. DL has been extensively studied in medical imaging applications, including those related to pulmonary diseases. Chronic obstructive pulmonary disease, asthma, lung cancer, pneumonia, and, more recently, COVID-19 are common lung diseases affecting nearly 7.4% of world population. Pulmonary imaging has been widely investigated toward improving our understanding of disease etiologies and early diagnosis and assessment of disease progression and clinical outcomes. DL has been broadly applied to solve various pulmonary image processing challenges including classification, recognition, registration, and segmentation. This paper presents a survey of pulmonary diseases, roles of imaging in translational and clinical pulmonary research, and applications of different DL architectures and methods in pulmonary imaging with emphasis on DL-based segmentation of major pulmonary anatomies such as lung volumes, lung lobes, pulmonary vessels, and airways as well as thoracic musculoskeletal anatomies related to pulmonary diseases.
Collapse
Affiliation(s)
- Punam K Saha
- Departments of Radiology and Electrical and Computer Engineering, University of Iowa, Iowa City, IA, 52242
| | | | | |
Collapse
|
4
|
Byon JH, Jin GY, Han YM, Choi EJ, Chae KJ, Park EH. Quantitative CT Analysis Based on Smoking Habits and Chronic Obstructive Pulmonary Disease in Patients with Normal Chest CT. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2023; 84:900-910. [PMID: 37559818 PMCID: PMC10407071 DOI: 10.3348/jksr.2022.0130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 10/26/2022] [Accepted: 11/13/2022] [Indexed: 08/11/2023]
Abstract
PURPOSE To assess normal CT scans with quantitative CT (QCT) analysis based on smoking habits and chronic obstructive pulmonary disease (COPD). MATERIALS AND METHODS From January 2013 to December 2014, 90 male patients with normal chest CT and quantification analysis results were enrolled in our study [non-COPD never-smokers (n = 38) and smokers (n = 45), COPD smokers (n = 7)]. In addition, an age-matched cohort study was performed for seven smokers with COPD. The square root of the wall area of a hypothetical bronchus of internal perimeter 10 mm (Pi10), skewness, kurtosis, mean lung attenuation (MLA), and percentage of low attenuation area (%LAA) were evaluated. RESULTS Among patients without COPD, the Pi10 of smokers (4.176 ± 0.282) was about 0.1 mm thicker than that of never-smokers (4.070 ± 0.191, p = 0.047), and skewness and kurtosis of smokers (2.628 ± 0.484 and 6.448 ± 3.427) were lower than never-smokers (2.884 ± 0.624, p = 0.038 and 8.594 ± 4.944, p = 0.02). The Pi10 of COPD smokers (4.429 ± 0.435, n = 7) was about 0.4 mm thicker than never-smokers without COPD (3.996 ± 0.115, n = 14, p = 0.005). There were no significant differences in MLA and %LAA between groups (p > 0.05). CONCLUSION Even on normal CT scans, QCT showed that the airway walls of smokers are thicker than never-smokers regardless of COPD and it preceded lung parenchymal changes.
Collapse
|
5
|
Weikert T, Friebe L, Wilder-Smith A, Yang S, Sperl JI, Neumann D, Balachandran A, Bremerich J, Sauter AW. Automated quantification of airway wall thickness on chest CT using retina U-Nets - Performance evaluation and application to a large cohort of chest CTs of COPD patients. Eur J Radiol 2022; 155:110460. [PMID: 35963191 DOI: 10.1016/j.ejrad.2022.110460] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Revised: 07/17/2022] [Accepted: 07/31/2022] [Indexed: 12/24/2022]
Abstract
PURPOSE Airway wall thickening is a consequence of chronic inflammatory processes and usually only qualitatively described in CT radiology reports. The purpose of this study is to automatically quantify airway wall thickness in multiple airway generations and assess the diagnostic potential of this parameter in a large cohort of patients with Chronic Obstructive Pulmonary Disease (COPD). MATERIALS AND METHODS This retrospective, single-center study included a series of unenhanced chest CTs. Inclusion criteria were the mentioning of an explicit COPD GOLD stage in the written radiology report and time period (01/2019-12/2021). A control group included chest CTs with completely unremarkable lungs according to the report. The DICOM images of all cases (axial orientation; slice-thickness: 1 mm; soft-tissue kernel) were processed by an AI algorithm pipeline consisting of (A) a 3D-U-Net for det detection and tracing of the bronchial tree centerlines (B) extraction of image patches perpendicular to the centerlines of the bronchi, and (C) a 2D U-Net for segmentation of airway walls on those patches. The performance of centerline detection and wall segmentation was assessed. The imaging parameter average wall thickness was calculated for bronchus generations 3-8 (AWT3-8) across the lungs. Mean AWT3-8 was compared between five groups (control, COPD Gold I-IV) using non-parametric statistics. Furthermore, the established emphysema score %LAV-950 was calculated and used to classify scans (normal vs. COPD) alone and in combination with AWT3-8. RESULTS: A total of 575 chest CTs were processed. Algorithm performance was very good (airway centerline detection sensitivity: 86.9%; airway wall segmentation Dice score: 0.86). AWT3-8 was statistically significantly greater in COPD patients compared to controls (2.03 vs. 1.87 mm, p < 0.001) and increased with COPD stage. The classifier that combined %LAV-950 and AWT3-8 was superior to the classifier using only %LAV-950 (AUC = 0.92 vs. 0.79). CONCLUSION Airway wall thickness increases in patients suffering from COPD and is automatically quantifiable. AWT3-8 could become a CT imaging parameter in COPD complementing the established emphysema biomarker %LAV-950. CLINICAL RELEVANCE STATEMENT Quantitative measurements considering the complete visible bronchial tree instead of qualitative description could enhance radiology reports, allow for precise monitoring of disease progression and diagnosis of early stages of disease.
Collapse
Affiliation(s)
- Thomas Weikert
- Department of Radiology, University Hospital Basel, University of Basel, Petersgraben 4, 4031 Basel, Switzerland.
| | - Liene Friebe
- Department of Radiology, University Hospital Basel, University of Basel, Petersgraben 4, 4031 Basel, Switzerland
| | - Adrian Wilder-Smith
- Department of Radiology, University Hospital Basel, University of Basel, Petersgraben 4, 4031 Basel, Switzerland
| | - Shan Yang
- Department of Radiology, University Hospital Basel, University of Basel, Petersgraben 4, 4031 Basel, Switzerland
| | | | - Dominik Neumann
- Siemens Healthineers, Henkestrasse 127, 91052 Erlangen, Germany
| | | | - Jens Bremerich
- Department of Radiology, University Hospital Basel, University of Basel, Petersgraben 4, 4031 Basel, Switzerland
| | - Alexander W Sauter
- Department of Radiology, University Hospital Basel, University of Basel, Petersgraben 4, 4031 Basel, Switzerland
| |
Collapse
|
6
|
Zhao Y, Hernandez AM, Boone JM, Molloi S. Quantification of Airway Dimensions using a High-Resolution CT Scanner: A Phantom Study. Med Phys 2021; 48:5874-5883. [PMID: 34287955 DOI: 10.1002/mp.15103] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 06/27/2021] [Accepted: 06/28/2021] [Indexed: 11/11/2022] Open
Abstract
PURPOSE Small airways with inner diameters less than 2 mm are sites of major airflow limitations in patients with chronic obstructive pulmonary disease (COPD) and asthma. The purpose of this study is to investigate the limitations for accurate assessment of small airway dimensions using both high-resolution CT (HRCT) and conventional normal-resolution CT at low dose levels. METHODS To model the normal human airways from the 3rd to 20th generations, a cylindrical polyurethane phantom with 14 airway tubes of inner diameters (ID) ranging from 0.3 to 3.4 mm and wall thicknesses (WT) ranging from 0.15 to 1.6 mm was placed within an Anthropomorphic QRM-Thorax phantom. The Aquilion Precision (Canon Medical Systems Corporation) HRCT scanner was used to acquire images at 80, 100 and 120 kV using high resolution mode (HR, 0.25 mm x 160 detector configuration) and normal resolution mode (NR, 0.5 mm x 80 detector configuration). The HR data were reconstructed using 1024 x 1024 matrix (0.22 x 0.22 x 0.25 mm voxel size) and the NR data were reconstructed using a 512 x 512 matrix (0.43 x 0.43 x 0.50 mm). Two reconstruction algorithms (filtered back projection; FBP and an adaptive iterative dose reduction 3D algorithm; AIDR 3D) and three reconstruction kernels (FC30, FC52 and FC56) were investigated. The CTDIvol dose values ranged from 0.2 to 6.2 mGy. A refined automated full-width half-maximum (FWHM) method was used for the measurement of airway dimensions, where the density profiles were computed by radial oversampling using a polar coordinate system. Both ID and WT were compared to the known dimensions using a regression model, and the root-mean-squared-error (RMSE) and average error were computed across all 14 airway tubes. RESULTS The results indicate that the ID can be measured within a 15% error down to approximately 0.8 mm and 2.0 mm using the HR and NR modes, respectively. The overall RMSE (and average error) of ID measurements for HR and NR were 0.10 mm (-0.70%) and 0.31 mm (-2.63%), respectively. The RMSE (and average error) of WT measurements using HR and NR were 0.10 mm (23.27%) and 0.27 mm (53.56%), respectively. The WT measurement using HR yielded a factor of two improvement in accuracy as compared to NR. CONCLUSIONS High-resolution CT can provide more accurate measurements of airway dimensions as compared with normal resolution CT, potentially improving quantitative assessment of pathologies such as COPD and asthma. The high resolution mode acquired and reconstructed with AIDR3D and the FC52 kernel provides most accurate measurement of airway dimensions. Low-dose high resolution measurements at dose level above 0.9 mGy can provide improved accuracy on both inner diameters and wall thicknesses compared to full dose normal resolution airway phantom measurements.
Collapse
Affiliation(s)
- Yixiao Zhao
- Department of Radiological Sciences, University of California Irvine, Irvine, CA, USA
| | - Andrew M Hernandez
- Department of Radiology, University of California Davis, Sacramento, CA, USA
| | - John M Boone
- Department of Radiology, University of California Davis, Sacramento, CA, USA.,Department of Biomedical Engineering, University of California Davis, Davis, CA, USA
| | - Sabee Molloi
- Department of Radiological Sciences, University of California Irvine, Irvine, CA, USA
| |
Collapse
|
7
|
Benlala I, Dournes G, Girodet PO, Benkert T, Laurent F, Berger P. Evaluation of bronchial wall thickness in asthma using magnetic resonance imaging. Eur Respir J 2021; 59:13993003.00329-2021. [PMID: 34049945 DOI: 10.1183/13993003.00329-2021] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 05/20/2021] [Indexed: 11/05/2022]
Abstract
BACKGROUND Bronchial thickening is a pathological feature of asthma that has been evaluated using computed tomography (CT), an ionised radiation technique. Magnetic Resonance Imaging (MRI) with Ultrashort Echo Time (UTE) pulse sequences could be an alternative to CT. OBJECTIVES To measure bronchial dimensions using MRI-UTE in asthmatic patients, by evaluating the accuracy and agreement with CT, by comparing severe and non-severe asthma and by correlating with pulmonary function tests. METHODS We assessed bronchial dimensions (wall area (WA), lumen area (LA), normalised wall area (WA%), and wall thickness (WT)) by MRI-UTE and CT in 15 non-severe and 15 age- and sex-matched severe asthmatic patients (NCT03089346). Accuracy and agreement between MRI and CT was evaluated by paired t-tests and Bland-Altman analysis. Reproducibility was assessed by intra-class correlation coefficient and Bland-Altman analysis. Comparison between non-severe and severe asthmatic parameters was performed by Student-t, Mann-Whitney or Fisher's Exact tests. Correlations were assessed by Pearson or Spearman coefficients. RESULTS LA, WA%, and WT were not significantly different between MRI-UTE and CT, with good correlations and concordance. Inter- and intra-observer reproducibility was moderate to good. WA% and WT were both higher in severe than in non-severe asthmatic patients. WA, WA% and WT were all negatively correlated with FEV1. CONCLUSION We demonstrated that MRI-UTE is an accurate and reliable radiation-free method to assess bronchial wall dimensions in asthma, with enough spatial resolution to differentiate severe from non-severe asthma.
Collapse
Affiliation(s)
- Ilyes Benlala
- Univ. Bordeaux, Centre de Recherche Cardio-thoracique de Bordeaux, Bordeaux, France.,CHU Bordeaux, Service de Radiologie et d'imagerie diagnostique et interventionnelle, CIC-P 1401, Service d'Exploration Fonctionnelle Respiratoire, Bordeaux, France.,INSERM, Centre de Recherche Cardio-thoracique de Bordeaux (U1045), Centre d'Investigation Clinique (CIC-P 1401), Bordeaux, France
| | - Gaël Dournes
- Univ. Bordeaux, Centre de Recherche Cardio-thoracique de Bordeaux, Bordeaux, France.,CHU Bordeaux, Service de Radiologie et d'imagerie diagnostique et interventionnelle, CIC-P 1401, Service d'Exploration Fonctionnelle Respiratoire, Bordeaux, France.,INSERM, Centre de Recherche Cardio-thoracique de Bordeaux (U1045), Centre d'Investigation Clinique (CIC-P 1401), Bordeaux, France
| | - Pierre-Olivier Girodet
- Univ. Bordeaux, Centre de Recherche Cardio-thoracique de Bordeaux, Bordeaux, France.,CHU Bordeaux, Service de Radiologie et d'imagerie diagnostique et interventionnelle, CIC-P 1401, Service d'Exploration Fonctionnelle Respiratoire, Bordeaux, France.,INSERM, Centre de Recherche Cardio-thoracique de Bordeaux (U1045), Centre d'Investigation Clinique (CIC-P 1401), Bordeaux, France
| | - Thomas Benkert
- MR application predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - François Laurent
- Univ. Bordeaux, Centre de Recherche Cardio-thoracique de Bordeaux, Bordeaux, France.,CHU Bordeaux, Service de Radiologie et d'imagerie diagnostique et interventionnelle, CIC-P 1401, Service d'Exploration Fonctionnelle Respiratoire, Bordeaux, France.,INSERM, Centre de Recherche Cardio-thoracique de Bordeaux (U1045), Centre d'Investigation Clinique (CIC-P 1401), Bordeaux, France
| | - Patrick Berger
- Univ. Bordeaux, Centre de Recherche Cardio-thoracique de Bordeaux, Bordeaux, France .,CHU Bordeaux, Service de Radiologie et d'imagerie diagnostique et interventionnelle, CIC-P 1401, Service d'Exploration Fonctionnelle Respiratoire, Bordeaux, France.,INSERM, Centre de Recherche Cardio-thoracique de Bordeaux (U1045), Centre d'Investigation Clinique (CIC-P 1401), Bordeaux, France
| |
Collapse
|
8
|
Chassagnon G, Burgel PR. Mucus Plugs in Medium-sized Airways: A Novel Imaging Biomarker for Phenotyping Chronic Obstructive Pulmonary Disease. Am J Respir Crit Care Med 2021; 203:932-934. [PMID: 33264069 PMCID: PMC8048760 DOI: 10.1164/rccm.202011-4178ed] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Affiliation(s)
- Guillaume Chassagnon
- Cochin Hospital Assistance Publique Hôpitaux de Paris Paris, France
- Université de Paris Paris, France and
| | - Pierre-Régis Burgel
- Cochin Hospital Assistance Publique Hôpitaux de Paris Paris, France
- Institut Cochin, Inserm U1016 Université de Paris Paris, France
| |
Collapse
|
9
|
Benlala I, Laurent F, Dournes G. Structural and functional changes in COPD: What we have learned from imaging. Respirology 2021; 26:731-741. [PMID: 33829593 DOI: 10.1111/resp.14047] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Chronic obstructive pulmonary disease (COPD) is the third leading cause of mortality worldwide. It is a heterogeneous disease involving different components of the lung to varying extents. Developments in medical imaging and image analysis techniques provide new insights in the assessment of the structural and functional changes of the disease. This article reviews the leading imaging techniques: CT and MRI of the lung in research settings and clinical routine. Both visual and quantitative methods are reviewed, emphasizing their relevance to patient phenotyping and outcome prediction.
Collapse
Affiliation(s)
- Ilyes Benlala
- Centre de recherche Cardio-Thoracique de Bordeaux, University of Bordeaux, INSERM, Bordeaux, France
| | - François Laurent
- Centre de recherche Cardio-Thoracique de Bordeaux, University of Bordeaux, INSERM, Bordeaux, France
| | - Gael Dournes
- Centre de recherche Cardio-Thoracique de Bordeaux, University of Bordeaux, INSERM, Bordeaux, France
| |
Collapse
|
10
|
Konietzke P, Weinheimer O, Wagner WL, Wuennemann F, Hintze C, Biederer J, Heussel CP, Kauczor HU, Wielpütz MO. Optimizing airway wall segmentation and quantification by reducing the influence of adjacent vessels and intravascular contrast material with a modified integral-based algorithm in quantitative computed tomography. PLoS One 2020; 15:e0237939. [PMID: 32813730 PMCID: PMC7437894 DOI: 10.1371/journal.pone.0237939] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Accepted: 08/05/2020] [Indexed: 11/18/2022] Open
Abstract
Introduction Quantitative analysis of multi-detector computed tomography (MDCT) plays an increasingly important role in assessing airway disease. Depending on the algorithms used, airway dimensions may be over- or underestimated, primarily if contrast material was used. Therefore, we tested a modified integral-based method (IBM) to address this problem. Methods Temporally resolved cine-MDCT was performed in seven ventilated pigs in breath-hold during iodinated contrast material (CM) infusion over 60s. Identical slices in non-enhanced (NE), pulmonary-arterial (PA), systemic-arterial (SA), and venous phase (VE) were subjected to an in-house software using a standard and a modified IBM. Total diameter (TD), lumen area (LA), wall area (WA), and wall thickness (WT) were measured for ten extra- and six intrapulmonary airways. Results The modified IBM significantly reduced TD by 7.6%, LA by 12.7%, WA by 9.7%, and WT by 3.9% compared to standard IBM on non-enhanced CT (p<0.05). Using standard IBM, CM led to a decrease of all airway parameters compared to NE. For example, LA decreased from 80.85±49.26mm2 at NE, to 75.14±47.96mm2 (-7.1%) at PA (p<0.001), 74.96±48.55mm2 (-7.3%) at SA (p<0.001), and to 78.95±48.94mm2 (-2.4%) at VE (p = 0.200). Using modified IBM, the differences were reduced to -3.1% at PA, -2.9% at SA and -0.7% at VE (p<0.001; p<0.001; p = 1.000). Conclusions The modified IBM can optimize airway wall segmentation and reduce the influence of CM on quantitative CT. This allows a more precise measurement as well as potentially the comparison of enhanced with non-enhanced scans in inflammatory airway disease.
Collapse
Affiliation(s)
- Philip Konietzke
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
- * E-mail:
| | - Oliver Weinheimer
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Willi L. Wagner
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Felix Wuennemann
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Christian Hintze
- Department of Diagnostic Radiology, University Hospital Schleswig-Holstein, Kiel, Germany
- Department of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Radiologie Rein-Nahe, Bingen, Germany
| | - Juergen Biederer
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Claus P. Heussel
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Hans-Ulrich Kauczor
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Mark O. Wielpütz
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| |
Collapse
|
11
|
Mikayama R, Shirasaka T, Yabuuchi H, Sakai Y, Kojima T, Kondo M, Yoshikawa H, Kato T. Effect of scan mode and focal spot size in airway dimension measurements for ultra-high-resolution computed tomography of chronic obstructive pulmonary disease: A COPDGene phantom study. Phys Med 2020; 70:102-108. [DOI: 10.1016/j.ejmp.2019.12.025] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2019] [Revised: 12/30/2019] [Accepted: 12/30/2019] [Indexed: 11/29/2022] Open
|
12
|
Coste F, Benlala I, Dournes G, Girodet PO, Laurent F, Berger P. Assessing pulmonary hypertension in COPD. Is there a role for computed tomography? Int J Chron Obstruct Pulmon Dis 2019; 14:2065-2079. [PMID: 31564854 PMCID: PMC6732516 DOI: 10.2147/copd.s207363] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2019] [Accepted: 06/10/2019] [Indexed: 12/22/2022] Open
Abstract
Pulmonary hypertension (PH) is a common complication of chronic obstructive pulmonary disease (COPD) and is associated with increased morbidity and mortality. Reference standard method to diagnose PH is right heart catheterization. Several non-invasive imaging techniques have been employed in the detection of PH. Among them, computed tomography (CT) is the most commonly used for phenotyping and detecting complications of COPD. Several CT findings have also been described in patients with severe PH. Nevertheless, CT analysis is currently based on visual findings which can lead to reproducibility failure. Therefore, there is a need for quantification in order to assess objective criteria. In this review, progresses in automated analyses of CT parameters and their values in predicting PH and COPD outcomes are presented.
Collapse
Affiliation(s)
- Florence Coste
- University Bordeaux, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, Bordeaux, F-33000 France.,Inserm, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, CIC1401, Bordeaux, F-33000 France
| | - Ilyes Benlala
- University Bordeaux, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, Bordeaux, F-33000 France.,Inserm, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, CIC1401, Bordeaux, F-33000 France.,CHU de Bordeaux, Service d'Imagerie Thoracique et Cardiovasculaire, Service des Maladies Respiratoires, CIC1401, Service d'Explorations Fonctionnelles Respiratoires, Pessac, F-33600 France
| | - Gaël Dournes
- University Bordeaux, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, Bordeaux, F-33000 France.,Inserm, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, CIC1401, Bordeaux, F-33000 France.,CHU de Bordeaux, Service d'Imagerie Thoracique et Cardiovasculaire, Service des Maladies Respiratoires, CIC1401, Service d'Explorations Fonctionnelles Respiratoires, Pessac, F-33600 France
| | - Pierre-Olivier Girodet
- University Bordeaux, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, Bordeaux, F-33000 France.,Inserm, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, CIC1401, Bordeaux, F-33000 France.,CHU de Bordeaux, Service d'Imagerie Thoracique et Cardiovasculaire, Service des Maladies Respiratoires, CIC1401, Service d'Explorations Fonctionnelles Respiratoires, Pessac, F-33600 France
| | - François Laurent
- University Bordeaux, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, Bordeaux, F-33000 France.,Inserm, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, CIC1401, Bordeaux, F-33000 France.,CHU de Bordeaux, Service d'Imagerie Thoracique et Cardiovasculaire, Service des Maladies Respiratoires, CIC1401, Service d'Explorations Fonctionnelles Respiratoires, Pessac, F-33600 France
| | - Patrick Berger
- University Bordeaux, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, Bordeaux, F-33000 France.,Inserm, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, CIC1401, Bordeaux, F-33000 France.,CHU de Bordeaux, Service d'Imagerie Thoracique et Cardiovasculaire, Service des Maladies Respiratoires, CIC1401, Service d'Explorations Fonctionnelles Respiratoires, Pessac, F-33600 France
| |
Collapse
|
13
|
Automatic proximal airway volume segmentation using optical coherence tomography for assessment of inhalation injury. J Trauma Acute Care Surg 2019; 87:S132-S137. [PMID: 31246917 DOI: 10.1097/ta.0000000000002277] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Acute respiratory distress syndrome (ARDS) is a severe form of acute lung injury with a mortality rate of up to 40%. Early management of ARDS has been difficult due to the lack of sensitive imaging tools and robust analysis software. We previously designed an optical coherence tomography (OCT) system to evaluate mucosa thickness (MT) after smoke inhalation, but the analysis relied on manual segmentation. The aim of this study is to assess in vivo proximal airway volume (PAV) after inhalation injury using automated OCT segmentation and correlate the PAV to lung function for rapid indication of ARDS. METHODS Anesthetized female Yorkshire pigs (n = 14) received smoke inhalation injury (SII) and 40% total body surface area thermal burns. Measurements of PaO2-to-FiO2 ratio (PFR), peak inspiratory pressure (PIP), dynamic compliance, airway resistance, and OCT bronchoscopy were performed at baseline, postinjury, 24 hours, 48 hours, 72 hours after injury. A tissue segmentation algorithm based on graph theory was used to reconstruct a three-dimensional (3D) model of lower respiratory tract and estimate PAV. Proximal airway volume was correlated with PFR, PIP, compliance, resistance, and MT measurement using a linear regression model. RESULTS Proximal airway volume decreased after the SII: the group mean of proximal airway volume at baseline, postinjury, 24 hours, 48 hours, 72 hours were 20.86 cm (±1.39 cm), 17.61 cm (±0.99 cm), 14.83 cm (±1.20 cm), 14.88 cm (±1.21 cm), and 13.11 cm (±1.59 cm), respectively. The decrease in the PAV was more prominent in the animals that developed ARDS after 24 hours after the injury. PAV was significantly correlated with PIP (r = 0.48, p < 0.001), compliance (r = 0.55, p < 0.001), resistance (r = 0.35, p < 0.01), MT (r = 0.60, p < 0.001), and PFR (r = 0.34, p < 0.01). CONCLUSION Optical coherence tomography is a useful tool to quantify changes in MT and PAV after SII and burns, which can be used as predictors of developing ARDS at an early stage. LEVEL OF EVIDENCE Prognostic, level III.
Collapse
|
14
|
Karayama M, Inui N, Yasui H, Kono M, Hozumi H, Suzuki Y, Furuhashi K, Hashimoto D, Enomoto N, Fujisawa T, Nakamura Y, Watanabe H, Suda T. Clinical features of three-dimensional computed tomography-based radiologic phenotypes of chronic obstructive pulmonary disease. Int J Chron Obstruct Pulmon Dis 2019; 14:1333-1342. [PMID: 31296985 PMCID: PMC6598936 DOI: 10.2147/copd.s207267] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 05/30/2019] [Indexed: 12/24/2022] Open
Abstract
Purpose The diagnosis and severity of chronic obstructive pulmonary disease (COPD) are defined by airflow limitation using spirometry. However, COPD has diverse clinical features, and several phenotypes based on non-spirometric data have been investigated. To identify novel phenotypes of COPD using radiologic data obtained by three-dimensional computed tomography (3D-CT). Patients and methods The inner luminal area and wall thickness of third- to sixth-generation bronchi and the percentage of the low-attenuation area (less than −950 HU) of the lungs were measured using 3D-CT in patients with COPD. Using the radiologic data, hierarchical clustering was performed. Respiratory reactance and resistance were measured to evaluate functional differences among the clusters. Results Four clusters were identified among 167 patients with COPD: Cluster I, mild emphysema with severe airway changes, severe airflow limitation, and high exacerbation risk; Cluster II, mild emphysema with moderate airway changes, mild airflow limitation, and mild dyspnea; Cluster III, severe emphysema with moderate airway changes, severe airflow limitation, and increased dyspnea; and Cluster IV, moderate emphysema with mild airway changes, mild airflow limitation, low exacerbation risk, and mild dyspnea. Cluster I had the highest respiratory resistance among the four clusters. Clusters I and III had higher respiratory reactance than Clusters II and IV. Conclusions The 3D-CT-based radiologic phenotypes were associated with the clinical features of COPD. Measurement of respiratory resistance and reactance may help to identify phenotypic differences.
Collapse
Affiliation(s)
- Masato Karayama
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu 431-3192, Japan
| | - Naoki Inui
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu 431-3192, Japan.,Department of Clinical Pharmacology and Therapeutics, Hamamatsu University School of Medicine, Hamamatsu 431-3192, Japan
| | - Hideki Yasui
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu 431-3192, Japan
| | - Masato Kono
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu 431-3192, Japan
| | - Hironao Hozumi
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu 431-3192, Japan
| | - Yuzo Suzuki
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu 431-3192, Japan
| | - Kazuki Furuhashi
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu 431-3192, Japan
| | - Dai Hashimoto
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu 431-3192, Japan
| | - Noriyuki Enomoto
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu 431-3192, Japan
| | - Tomoyuki Fujisawa
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu 431-3192, Japan
| | - Yutaro Nakamura
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu 431-3192, Japan
| | - Hiroshi Watanabe
- Department of Clinical Pharmacology and Therapeutics, Hamamatsu University School of Medicine, Hamamatsu 431-3192, Japan
| | - Takafumi Suda
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu 431-3192, Japan
| |
Collapse
|
15
|
Coste F, Benlala I, Dournes G, Dromer C, Blanchard E, Girodet PO, Montaudon M, Baldacci F, Picard F, Marthan R, Laurent F, Berger P. Quantitative CT assessment of bronchial and vascular alterations in severe precapillary pulmonary hypertension. Int J Chron Obstruct Pulmon Dis 2019; 14:381-389. [PMID: 30809092 PMCID: PMC6377046 DOI: 10.2147/copd.s177638] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Background Little is known about in vivo alterations at bronchial and vascular levels in severe pulmonary hypertension (PH) of different etiologies. We aimed to compare quantitative computed tomography (CT) data from the following three groups of severe precapillary PH patients: COPD, idiopathic pulmonary arterial hypertension (iPAH), and chronic thromboembolic PH (CTEPH). Patients and methods This study was approved by the institutional review board. Severe PH patients (mean pulmonary arterial pressure [mPAP] ≥35 mmHg) with COPD, iPAH, or CTEPH (n=24, 16, or 16, respectively) were included retrospectively between January 2008 and January 2017. Univariate analysis of mPAP was performed in each severe PH group. Bronchial wall thickness (WT) and percentage of cross sectional area of pulmonary vessels less than 5 mm2 normalized by lung area (%CSA<5) were measured and compared using CT, and then combined to arterial partial pressure of oxygen (PaO2) to generate a “paw score” compared within the three groups using Kruskal–Wallis and its sensitivity using Fisher’s exact test. Results WT was higher and %CSA<5 was lower in the COPD group compared to iPAH and CTEPH groups. Mosaic pattern was higher in CTEPH group than in others. In severe PH patients secondary to COPD, mPAP was positively correlated to %CSA<5. By contrast, in severe iPAH, this correlation was negative, or not correlated in severe CTEPH groups. In the COPD group, “paw score” showed higher sensitivity than in the other two groups. Conclusion Unlike in severe iPAH and CTEPH, severe PH with COPD can be predicted by “paw score” reflecting bronchial and vascular morphological differential alterations.
Collapse
Affiliation(s)
- Florence Coste
- Université de Bordeaux, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, F-33000 Bordeaux, France, .,Centre de Recherche Cardio-Thoracique de Bordeaux, INSERM, U1045, Université de Bordeaux, CIC1401, F-33000 Bordeaux, France,
| | - Ilyes Benlala
- Université de Bordeaux, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, F-33000 Bordeaux, France, .,Centre de Recherche Cardio-Thoracique de Bordeaux, INSERM, U1045, Université de Bordeaux, CIC1401, F-33000 Bordeaux, France,
| | - Gaël Dournes
- Université de Bordeaux, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, F-33000 Bordeaux, France, .,Centre de Recherche Cardio-Thoracique de Bordeaux, INSERM, U1045, Université de Bordeaux, CIC1401, F-33000 Bordeaux, France, .,CHU de Bordeaux, Service d'Imagerie Thoracique et Cardiovasculaire, Service des Maladies Respiratoires, Service de Cardiologie, CIC1401, Service d'Explorations Fonctionnelles Respiratoires, F-33600 Pessac, France
| | - Claire Dromer
- CHU de Bordeaux, Service d'Imagerie Thoracique et Cardiovasculaire, Service des Maladies Respiratoires, Service de Cardiologie, CIC1401, Service d'Explorations Fonctionnelles Respiratoires, F-33600 Pessac, France
| | - Elodie Blanchard
- CHU de Bordeaux, Service d'Imagerie Thoracique et Cardiovasculaire, Service des Maladies Respiratoires, Service de Cardiologie, CIC1401, Service d'Explorations Fonctionnelles Respiratoires, F-33600 Pessac, France
| | - Pierre-Olivier Girodet
- Université de Bordeaux, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, F-33000 Bordeaux, France, .,Centre de Recherche Cardio-Thoracique de Bordeaux, INSERM, U1045, Université de Bordeaux, CIC1401, F-33000 Bordeaux, France, .,CHU de Bordeaux, Service d'Imagerie Thoracique et Cardiovasculaire, Service des Maladies Respiratoires, Service de Cardiologie, CIC1401, Service d'Explorations Fonctionnelles Respiratoires, F-33600 Pessac, France
| | - Michel Montaudon
- Université de Bordeaux, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, F-33000 Bordeaux, France, .,Centre de Recherche Cardio-Thoracique de Bordeaux, INSERM, U1045, Université de Bordeaux, CIC1401, F-33000 Bordeaux, France, .,CHU de Bordeaux, Service d'Imagerie Thoracique et Cardiovasculaire, Service des Maladies Respiratoires, Service de Cardiologie, CIC1401, Service d'Explorations Fonctionnelles Respiratoires, F-33600 Pessac, France
| | - Fabien Baldacci
- Université de Bordeaux, LaBRI, F-33405 Talence Cedex, France
| | - François Picard
- CHU de Bordeaux, Service d'Imagerie Thoracique et Cardiovasculaire, Service des Maladies Respiratoires, Service de Cardiologie, CIC1401, Service d'Explorations Fonctionnelles Respiratoires, F-33600 Pessac, France
| | - Roger Marthan
- Université de Bordeaux, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, F-33000 Bordeaux, France, .,Centre de Recherche Cardio-Thoracique de Bordeaux, INSERM, U1045, Université de Bordeaux, CIC1401, F-33000 Bordeaux, France, .,CHU de Bordeaux, Service d'Imagerie Thoracique et Cardiovasculaire, Service des Maladies Respiratoires, Service de Cardiologie, CIC1401, Service d'Explorations Fonctionnelles Respiratoires, F-33600 Pessac, France
| | - François Laurent
- Université de Bordeaux, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, F-33000 Bordeaux, France, .,Centre de Recherche Cardio-Thoracique de Bordeaux, INSERM, U1045, Université de Bordeaux, CIC1401, F-33000 Bordeaux, France, .,CHU de Bordeaux, Service d'Imagerie Thoracique et Cardiovasculaire, Service des Maladies Respiratoires, Service de Cardiologie, CIC1401, Service d'Explorations Fonctionnelles Respiratoires, F-33600 Pessac, France
| | - Patrick Berger
- Université de Bordeaux, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, F-33000 Bordeaux, France, .,Centre de Recherche Cardio-Thoracique de Bordeaux, INSERM, U1045, Université de Bordeaux, CIC1401, F-33000 Bordeaux, France, .,CHU de Bordeaux, Service d'Imagerie Thoracique et Cardiovasculaire, Service des Maladies Respiratoires, Service de Cardiologie, CIC1401, Service d'Explorations Fonctionnelles Respiratoires, F-33600 Pessac, France
| |
Collapse
|
16
|
Uncontrolled asthma phenotypes defined from parameters using quantitative CT analysis. Eur Radiol 2019; 29:2848-2858. [PMID: 30617489 DOI: 10.1007/s00330-018-5913-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2018] [Revised: 09/20/2018] [Accepted: 11/23/2018] [Indexed: 10/27/2022]
Abstract
OBJECTIVE Asthma is a heterogeneous disease with diverse clinical phenotypes that have been identified via cluster analyses. However, the classification of phenotypes based on quantitative CT (qCT) is poorly understood. The study was conducted to investigate CT determination of uncontrolled asthma phenotypes. METHODS Sixty-five patients with uncontrolled asthma (37 with severe asthma, 28 with non-severe asthma) underwent detailed clinical, laboratory, and pulmonary function tests, as well as qCT analysis. Twenty-five healthy subjects were also included in this study and underwent clinical physical examinations, pulmonary function tests, and low-dose CT scans. RESULTS The mean lumen area/body surface area ratio was smaller in patients with severe uncontrolled asthma compared with that in healthy subjects (9.84 mm2 [SD, 2.57 mm2], 11.96 mm2 [SD, 3.09 mm2]; p = 0.026). However, the percentage of mean wall area (WA) was greater (64.39% [SD, 2.55%], 62.09% [SD, 3.81%], p = 0.011). Air trapping (measured based on mean lung density and VI-856 [%] on expiratory scan) was greater in patients with severe uncontrolled asthma than in those with non-severe uncontrolled asthma and was higher in all patients with uncontrolled asthma than that in healthy subjects (all p < 0.001). Three CT-determined uncontrolled asthma phenotypes were identified. Cluster 1 had mild air trapping with or without proximal airway remodeling. Cluster 2 had moderate air trapping with or without proximal airway remodeling. Cluster 3 had severe air trapping with proximal airway remodeling. CONCLUSIONS There was obvious air trapping and proximal airway remodeling in patients with severe uncontrolled asthma. The three CT-determined uncontrolled asthma phenotypes might reflect underlying mechanisms of disease in patient stratification and in the different stages of disease development. KEY POINTS • Obvious air trapping and proximal airway remodeling were present in patients with severe uncontrolled asthma. • CT air trapping indices showed a good correlation with disease duration, total IgE, atopy, and OCS and ICS doses, and were even more strongly correlated with clinical lung function. • Three CT-determined uncontrolled asthma phenotypes were identified, which might reflect underlying mechanisms of disease in patient stratification and in the different stages of disease development.
Collapse
|
17
|
Karayama M, Inui N, Mori K, Kono M, Hozumi H, Suzuki Y, Furuhashi K, Hashimoto D, Enomoto N, Fujisawa T, Nakamura Y, Watanabe H, Suda T. Respiratory impedance is correlated with airway narrowing in asthma using three-dimensional computed tomography. Clin Exp Allergy 2018; 48:278-287. [PMID: 29315896 DOI: 10.1111/cea.13083] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Revised: 11/15/2017] [Accepted: 12/21/2017] [Indexed: 01/20/2023]
Abstract
BACKGROUND Respiratory impedance comprises the resistance and reactance of the respiratory system and can provide detailed information on respiratory function. However, details of the relationship between impedance and morphological airway changes in asthma are unknown. OBJECTIVE We aimed to evaluate the correlation between imaging-based airway changes and respiratory impedance in patients with asthma. METHODS Respiratory impedance and spirometric data were evaluated in 72 patients with asthma and 29 reference subjects. We measured the intraluminal area (Ai) and wall thickness (WT) of third- to sixth-generation bronchi using three-dimensional computed tomographic analyses, and values were adjusted by body surface area (BSA, Ai/BSA, and WT/the square root (√) of BSA). RESULTS Asthma patients had significantly increased respiratory impedance, decreased Ai/BSA, and increased WT/√BSA, as was the case in those without airflow limitation as assessed by spirometry. Ai/BSA was inversely correlated with respiratory resistance at 5 Hz (R5) and 20 Hz (R20). R20 had a stronger correlation with Ai/BSA than did R5. Ai/BSA was positively correlated with forced expiratory volume in 1 second/forced vital capacity ratio, percentage predicted forced expiratory volume in 1 second, and percentage predicted mid-expiratory flow. WT/√BSA had no significant correlation with spirometry or respiratory impedance. CONCLUSIONS & CLINICAL RELEVANCE Respiratory resistance is associated with airway narrowing.
Collapse
Affiliation(s)
- M Karayama
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - N Inui
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu, Japan.,Department of Clinical Pharmacology and Therapeutics, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - K Mori
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - M Kono
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - H Hozumi
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Y Suzuki
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - K Furuhashi
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - D Hashimoto
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - N Enomoto
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - T Fujisawa
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Y Nakamura
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - H Watanabe
- Department of Clinical Pharmacology and Therapeutics, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - T Suda
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu, Japan
| |
Collapse
|
18
|
Relationship between fraction of exhaled nitric oxide and airway morphology assessed by three-dimensional CT analysis in asthma. Sci Rep 2017; 7:10187. [PMID: 28860527 PMCID: PMC5579255 DOI: 10.1038/s41598-017-10504-w] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2017] [Accepted: 08/09/2017] [Indexed: 11/09/2022] Open
Abstract
Fraction of exhaled nitric oxide (FeNO) provides information about chronic inflammation in asthma. However, its relationship with structural changes in the airways is unknown. We aimed to evaluate the correlation between computer-based airway changes and FeNO in patients with asthma. The wall area (WA) and airway inner luminal area (Ai) of the third- to sixth-generation bronchi were measured using three-dimensional computed tomography in asthmatic patients. Each value was corrected by body surface area (BSA). Relationships between FeNO and WA/BSA and Ai/BSA were evaluated. Forty-one clinically stable patients with asthma were evaluated. FeNO was significantly correlated with WA/BSA of the third-, fourth-, fifth- and sixth-generation bronchi (Spearman correlation coefficient (ρ) = 0.326, p = 0.041; ρ = 0.356, p = 0.025; ρ = 0.496, p = 0.002; and ρ = 0.529, p < 0.001, respectively). The correlation with sixth-generation bronchi was significantly greater than with the third-generation bronchi (p = 0.047). Partial rank correlation analysis indicated FeNO was significantly correlated with WA/BSA of the sixth-generation bronchi, independent from confounding factors of Ai/BSA, age, duration of asthma, dose of inhaled corticosteroid, blood eosinophil percentage, and blood IgE (ρ = 0.360, p = 0.034). In contrast, there was no correlation between FeNO and Ai/BSA. FeNO correlates with bronchial wall thickening in asthma patients. Measurement of FeNO may be useful to detect airway remodeling in asthma.
Collapse
|
19
|
Karayama M, Inui N, Mori K, Kono M, Hozumi H, Suzuki Y, Furuhashi K, Hashimoto D, Enomoto N, Fujisawa T, Nakamura Y, Watanabe H, Suda T. Respiratory impedance is correlated with morphological changes in the lungs on three-dimensional CT in patients with COPD. Sci Rep 2017; 7:41709. [PMID: 28176815 PMCID: PMC5296866 DOI: 10.1038/srep41709] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2016] [Accepted: 12/23/2016] [Indexed: 11/09/2022] Open
Abstract
The forced oscillation technique provides information concerning respiratory impedance, which comprises resistance and reactance of the respiratory system. However, its relationship with morphological changes of the lungs in chronic obstructive pulmonary disease (COPD) remains unclear. Respiratory impedance and spirometric data were evaluated in 98 patients with COPD and 49 reference subjects. Wall thickness (WT) and airway intraluminal area (Ai) of third- to sixth-generation bronchi, and percentage low-attenuation area with less than -950 HU (%LAA) of lungs were measured using three-dimensional computed tomography. COPD patients had higher respiratory impedance, decreased Ai, and increased %LAA compared with reference subjects. Indices of respiratory resistance and reactance and forced expiratory volume in 1 second (FEV1) were correlated with Ai, and the association between percent predicted FEV1 and Ai was predominant in distal bronchi. The difference in respiratory resistance between 5 Hz and 20 Hz (R5-R20) and FEV1/forced vital capacity ratio (FEV1/FVC) were correlated with WT. The %LAA was correlated with the FEV1/FVC ratio and respiratory reactance. Airway function measurements with the forced oscillation technique provide complementary information to spirometry in COPD.
Collapse
Affiliation(s)
- Masato Karayama
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, 1-20-1 Handayama, Hamamatsu 431-3192, Japan.,Department of Clinical Oncology, Hamamatsu University School of Medicine, 1-20-1 Handayama, Hamamatsu 431-3192, Japan
| | - Naoki Inui
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, 1-20-1 Handayama, Hamamatsu 431-3192, Japan.,Department of Clinical Pharmacology and Therapeutics, Hamamatsu University School of Medicine, 1-20-1 Handayama, Hamamatsu 431-3192, Japan
| | - Kazutaka Mori
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, 1-20-1 Handayama, Hamamatsu 431-3192, Japan
| | - Masato Kono
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, 1-20-1 Handayama, Hamamatsu 431-3192, Japan
| | - Hironao Hozumi
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, 1-20-1 Handayama, Hamamatsu 431-3192, Japan
| | - Yuzo Suzuki
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, 1-20-1 Handayama, Hamamatsu 431-3192, Japan
| | - Kazuki Furuhashi
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, 1-20-1 Handayama, Hamamatsu 431-3192, Japan
| | - Dai Hashimoto
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, 1-20-1 Handayama, Hamamatsu 431-3192, Japan
| | - Noriyuki Enomoto
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, 1-20-1 Handayama, Hamamatsu 431-3192, Japan
| | - Tomoyuki Fujisawa
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, 1-20-1 Handayama, Hamamatsu 431-3192, Japan
| | - Yutaro Nakamura
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, 1-20-1 Handayama, Hamamatsu 431-3192, Japan
| | - Hiroshi Watanabe
- Department of Clinical Pharmacology and Therapeutics, Hamamatsu University School of Medicine, 1-20-1 Handayama, Hamamatsu 431-3192, Japan
| | - Takafumi Suda
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, 1-20-1 Handayama, Hamamatsu 431-3192, Japan
| |
Collapse
|
20
|
Telenga ED, Oudkerk M, van Ooijen PMA, Vliegenthart R, Ten Hacken NHT, Postma DS, van den Berge M. Airway wall thickness on HRCT scans decreases with age and increases with smoking. BMC Pulm Med 2017; 17:27. [PMID: 28143620 PMCID: PMC5286807 DOI: 10.1186/s12890-017-0363-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2016] [Accepted: 01/10/2017] [Indexed: 11/10/2022] Open
Abstract
Background To investigate if age, gender and smoking are associated with airway wall thickness (AWT) measured by high resolution computed tomography (HRCT) and if higher AWT is associated with lower levels of pulmonary function in healthy current- and never-smokers with a wide age range. Methods HRCT scans were performed in 99 subjects (48 never- and 51 current-smokers, median age 39 years [IQR 22 – 54], 57% males). The AWT at an internal perimeter of 10 mm (AWT Pi10) was calculated as an overall measurement of AWT, based on all measurements throughout the lungs. Extensive pulmonary function testing was performed in all subjects. Results Higher age was associated with a lower AWT Pi10 (b = −0.003, p < 0.001). Current-smokers had a higher AWT Pi10 than never-smokers (mean 0.49 mm versus 0.44 mm, p = 0.022). In multivariate analysis, age and current-smoking were independently associated with AWT Pi10 (age b = −0.002, p < 0.001, current-smoking b = 0.041, p = 0.021), whereas gender was not (b = 0.011, p = 0.552). Higher AWT Pi10 was associated with a lower FEV1, FEV1/FVC, FEF25–75 and higher R5, R20 and X5. Conclusions AWT decreases with higher age, possibly reflecting structural changes of the airways. Additionally, current-smokers have a higher AWT, possibly due to remodeling or inflammation. Finally, higher AWT is associated with a lower level of pulmonary function, even in this population of healthy subjects. Trial registration This Study was registered at www.clinicaltrials.gov with number NCT00848406 on 19 February 2009. Electronic supplementary material The online version of this article (doi:10.1186/s12890-017-0363-0) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Eef D Telenga
- Department of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB, Groningen, The Netherlands.,GRIAC Research Institute, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Matthijs Oudkerk
- Center for Medical Imaging North East Netherlands, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Peter M A van Ooijen
- Center for Medical Imaging North East Netherlands, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.,Department of Radiology, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB, Groningen, The Netherlands
| | - Rozemarijn Vliegenthart
- Center for Medical Imaging North East Netherlands, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.,Department of Radiology, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB, Groningen, The Netherlands
| | - Nick H T Ten Hacken
- Department of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB, Groningen, The Netherlands.,GRIAC Research Institute, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Dirkje S Postma
- Department of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB, Groningen, The Netherlands.,GRIAC Research Institute, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Maarten van den Berge
- Department of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB, Groningen, The Netherlands. .,GRIAC Research Institute, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
| |
Collapse
|
21
|
Choi S, Hoffman EA, Wenzel SE, Castro M, Fain S, Jarjour N, Schiebler ML, Chen K, Lin CL. Quantitative computed tomographic imaging-based clustering differentiates asthmatic subgroups with distinctive clinical phenotypes. J Allergy Clin Immunol 2017; 140:690-700.e8. [PMID: 28143694 DOI: 10.1016/j.jaci.2016.11.053] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Revised: 10/15/2016] [Accepted: 11/21/2016] [Indexed: 12/27/2022]
Abstract
BACKGROUND Imaging variables, including airway diameter, wall thickness, and air trapping, have been found to be important metrics when differentiating patients with severe asthma from those with nonsevere asthma and healthy subjects. OBJECTIVE The objective of this study was to identify imaging-based clusters and to explore the association of the clusters with existing clinical metrics. METHODS We performed an imaging-based cluster analysis using quantitative computed tomography-based structural and functional variables extracted from the respective inspiration and expiration scans of 248 asthmatic patients. The imaging-based metrics included a broader set of multiscale variables, such as inspiratory airway dimension, expiratory air trapping, and registration-based lung deformation (inspiration vs expiration). Asthma subgroups derived from a clustering method were associated with subject demographics, questionnaire results, medication history, and biomarker variables. RESULTS Cluster 1 was composed of younger patients with early-onset nonsevere asthma and reversible airflow obstruction and normal airway structure. Cluster 2 was composed of patients with a mix of patients with nonsevere and severe asthma with marginal inflammation who exhibited airway luminal narrowing without wall thickening. Clusters 3 and 4 were dominated by patients with severe asthma. Cluster 3 patients were obese female patients with reversible airflow obstruction who exhibited airway wall thickening without airway narrowing. Cluster 4 patients were late-onset older male subjects with persistent airflow obstruction who exhibited significant air trapping and reduced regional deformation. Cluster 3 and 4 patients also showed decreased lymphocyte and increased neutrophil counts, respectively. CONCLUSIONS Four image-based clusters were identified and shown to be correlated with clinical characteristics. Such clustering serves to differentiate asthma subgroups that can be used as a basis for the development of new therapies.
Collapse
Affiliation(s)
- Sanghun Choi
- Department of Mechanical and Industrial Engineering, University of Iowa, Iowa City, Iowa; IIHR-Hydroscience and Engineering, University of Iowa, Iowa City, Iowa; Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa
| | - Eric A Hoffman
- Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa; Department of Radiology, University of Iowa, Iowa City, Iowa; Department of Internal Medicine, University of Iowa, Iowa City, Iowa
| | - Sally E Wenzel
- Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pa
| | - Mario Castro
- Departments of Internal Medicine and Pediatrics, Washington University School of Medicine, St Louis, Mo
| | - Sean Fain
- School of Medicine & Public Health, University of Wisconsin, Madison, Wis
| | - Nizar Jarjour
- School of Medicine & Public Health, University of Wisconsin, Madison, Wis
| | - Mark L Schiebler
- School of Medicine & Public Health, University of Wisconsin, Madison, Wis
| | - Kun Chen
- Department of Statistics, University of Connecticut, Storrs, Conn
| | - Ching-Long Lin
- Department of Mechanical and Industrial Engineering, University of Iowa, Iowa City, Iowa; IIHR-Hydroscience and Engineering, University of Iowa, Iowa City, Iowa; Department of Radiology, University of Iowa, Iowa City, Iowa.
| |
Collapse
|
22
|
|
23
|
Nambu A, Zach J, Schroeder J, Jin G, Kim SS, Kim YI, Schnell C, Bowler R, Lynch DA. Quantitative computed tomography measurements to evaluate airway disease in chronic obstructive pulmonary disease: Relationship to physiological measurements, clinical index and visual assessment of airway disease. Eur J Radiol 2016; 85:2144-2151. [PMID: 27776670 DOI: 10.1016/j.ejrad.2016.09.010] [Citation(s) in RCA: 61] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2016] [Revised: 09/11/2016] [Accepted: 09/12/2016] [Indexed: 10/21/2022]
Abstract
PURPOSE To correlate currently available quantitative CT measurements for airway disease with physiological indices and the body-mass index, airflow obstruction, dyspnea, and exercise capacity (BODE) index in patients with chronic obstructive pulmonary disease (COPD). MATERIALS AND METHODS This study was approved by our institutional review board (IRB number 2778). Written informed consent was obtained from all subjects. The subjects included 188 current and former cigarette smokers from the COPDGene cohort who underwent inspiratory and expiratory CT and also had physiological measurements for the evaluation of airflow limitation, including FEF25-75%, airway resistance (Raw), and specific airway conductance (sGaw). The BODE index was used as the index of clinical symptoms. Quantitative CT measures included % low attenuation areas [% voxels≤950 Hounsfield unit (HU) on inspiratory CT, %LAA-950ins], percent gas trapping (% voxels≤-856HU on expiratory CT, %LAA -856exp), relative inspiratory to expiratory volume change of voxels with attenuation values from -856 to -950HU [Relative Volume Change (RVC)-856 to -950], expiratory to inspiratory ratio of mean lung density (E/I-ratio MLD), Pi10, and airway wall thickness (WT), luminal diameter (LD) and airway wall area percent (WA%) in the segmental, subsegmental and subsubsegmental bronchi on inspiratory CT. Correlation coefficients were calculated between the QCT measurements and physiological measurements in all subjects and in the subjects with mild emphysema (%LAA-950ins <10%). Univariate and multiple variable analysis for the BODE index were also performed. Adjustments were made for age, gender, smoking pack years, FEF25-75%, Raw, and sGaw. RESULTS Quantitative CT measurements had significant correlations with physiological indices. Among them, E/I-ratio MLD had the strongest correlations with FEF25-75% (r=-0.648, <0.001) and sGaw (r=-0.624, <0.001) while in the subjects with mild emphysema subsegmental WA% and segmental WA% had the strongest correlation with FEF25-75% (r=-0.669, <0.001) and sGaw (r=-0.638, <0.001), respectively. The multiple variable analyses showed that RVC-856 to -950 was an independent predictor of the BODE index showing the highest R2 (0.468) as an independent variable among the QCT measurements. CONCLUSION Quantitative CT measurements of gas trapping such as E/I-ratio MLD, correlate better with physiological indices for airway disease than those of airway such as WA% or LD. In mild emphysema, however, quantitative CT measurements of airway correlate better with the physiological indices. RVC-856 to -950 is a predictor of the BODE index.
Collapse
Affiliation(s)
- Atsushi Nambu
- Department of Radiology, National Jewish Health, 1400 Jackson Street, Denver, CO, 80206, USA.
| | - Jordan Zach
- Department of Radiology, National Jewish Health, 1400 Jackson Street, Denver, CO, 80206, USA.
| | - Joyce Schroeder
- Department of Radiology, National Jewish Health, 1400 Jackson Street, Denver, CO, 80206, USA.
| | - Gongyoung Jin
- Department of Radiology, National Jewish Health, 1400 Jackson Street, Denver, CO, 80206, USA.
| | - Song Soo Kim
- Department of Radiology, National Jewish Health, 1400 Jackson Street, Denver, CO, 80206, USA.
| | - Yu-Il Kim
- Department of Medicine, National Jewish Health, Denver, CO, USA.
| | | | - Russell Bowler
- Division of Pulmonary Medicine, Department of Medicine, National Jewish Health, USA.
| | - David A Lynch
- Department of Radiology, National Jewish Health, 1400 Jackson Street, Denver, CO, 80206, USA.
| |
Collapse
|
24
|
Thomson NC, Shepherd M, Spears M, Chaudhuri R. Corticosteroid insensitivity in smokers with asthma : clinical evidence, mechanisms, and management. ACTA ACUST UNITED AC 2016; 5:467-81. [PMID: 17154674 DOI: 10.2165/00151829-200605060-00010] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Corticosteroids are the most effective treatment for asthma, but the therapeutic response varies considerably between individuals. Several clinical studies have found that smokers with asthma are insensitive to the beneficial effects of short- to medium-term inhaled corticosteroid treatment compared with non-smokers with asthma. It is estimated that 25% of adults in most industrialized countries smoke cigarettes, and similar surveys amongst asthmatic individuals suggest that the prevalence of smoking in this grouping mirrors that found in the general population. Therefore, cigarette smoking is probably the most common cause of corticosteroid insensitivity in asthma. Cigarette smoking and asthma are also associated with poor symptom control and an accelerated rate of decline in lung function. The mechanism of corticosteroid insensitivity in smokers with asthma is currently unexplained but could be due to alterations in airway inflammatory cell phenotypes, changes in glucocorticoid receptor alpha/beta ratio, and/or reduced histone deacetylase activity. Smoking cessation should be encouraged in all smokers with asthma. Short-term benefits include improvements in lung function and asthma control. However, the numbers of sustained quitters is disappointingly small. Additional or alternative drugs need to be identified to treat those individuals who are unable to stop smoking or who have persistent symptoms following smoking cessation.
Collapse
Affiliation(s)
- Neil C Thomson
- Department of Respiratory Medicine, Division of Immunology, Infection and Inflammation, University of Glasgow, Glasgow, Scotland
| | | | | | | |
Collapse
|
25
|
Coste F, Dournes G, Dromer C, Blanchard E, Freund-Michel V, Girodet PO, Montaudon M, Baldacci F, Picard F, Marthan R, Berger P, Laurent F. CT evaluation of small pulmonary vessels area in patients with COPD with severe pulmonary hypertension. Thorax 2016; 71:830-7. [DOI: 10.1136/thoraxjnl-2015-207696] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2015] [Accepted: 03/15/2016] [Indexed: 02/02/2023]
|
26
|
Is bronchial wall imaging affected by temporal resolution? comparative evaluation at 140 and 75 ms in 90 patients. Eur Radiol 2016; 26:469-77. [DOI: 10.1007/s00330-015-3819-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2015] [Revised: 04/10/2015] [Accepted: 04/22/2015] [Indexed: 11/26/2022]
|
27
|
Comparison of a New Integral-Based Half-Band Method for CT Measurement of Peripheral Airways in COPD With a Conventional Full-Width Half-Maximum Method Using Both Phantom and Clinical CT Images. J Comput Assist Tomogr 2015; 39:428-36. [PMID: 25700223 DOI: 10.1097/rct.0000000000000218] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVES To compare a new integral-based half-band method (IBHB) and a conventional full-width half-maximum (FWHM) method in measuring peripheral airway dimensions at airway phantoms and thin-section computed tomography of chronic obstructive pulmonary disease (COPD). METHODS The IBHB was validated and compared using airway phantoms and 50 patients with COPD. Airway parameters (wall area percentage [WA%], mean lumen radius, and mean wall thickness) were measured at fourth to sixth generations of the right apical bronchus. Matched results from 2 methods were compared and correlated with forced expiratory volume (FEV) in 1 second (FEV1), FEV1 / forced vital capacity (FVC), and global initiative for chronic obstructive lung disease (GOLD) stage. Linear regression analysis was performed using airway dimensions and emphysema index. RESULTS The IBHB generated more accurate measurements at phantom study. Measured airway parameters by both methods at thin-section computed tomography study were significantly different (all P < 0.05, paired t test). The IBHB method-measured WA% and wall thickness were significantly smaller. Mean WA% with IBHB also showed better correlation than that with FWHM (FEV1, r = -0.52 vs -0.28; FEV1 / FVC, r = -0.41 vs r = -0.20; GOLD, 0.52 vs 0.33, respectively). Linear regression analysis revealed fifth-generation WA% measured by IBHB was an independent variable, and addition to emphysema index increased predictability (FEV1, r = 0.63; FEV1 / FVC, r = 0.61; GOLD, r = 0.70). CONCLUSIONS The new IBHB measured peripheral airway dimensions differently than FWHM and showed better correlations with functional parameters in COPD.
Collapse
|
28
|
Girodet PO, Dournes G, Thumerel M, Begueret H, Dos Santos P, Ozier A, Dupin I, Trian T, Montaudon M, Laurent F, Marthan R, Berger P. Calcium channel blocker reduces airway remodeling in severe asthma. A proof-of-concept study. Am J Respir Crit Care Med 2015; 191:876-83. [PMID: 25633090 DOI: 10.1164/rccm.201410-1874oc] [Citation(s) in RCA: 58] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
RATIONALE Severe asthma is a major public health issue throughout the world. Increased bronchial smooth muscle (BSM) mass, a characteristic feature of airway remodeling in severe asthma, is associated with resistance to high-intensity treatment and poor prognosis. In vitro, the Ca(2+)-channel blocker gallopamil decreased the proliferation of BSM cells from patients with severe asthma. OBJECTIVES We conducted a double-blind, randomized, placebo-controlled study to evaluate the effect of gallopamil on airway remodeling in patients with severe asthma. METHODS Subjects received either gallopamil (n = 16) or placebo (n = 15) for 1 year and were monitored for an additional 3-month period. Airway remodeling was analyzed at baseline and after treatment phase using both fiberoptic bronchoscopy and computed tomography scan. The primary end point was the BSM area. Secondary end points included normalized BSM thickness and frequency of asthma exacerbations. MEASUREMENTS AND MAIN RESULTS BSM area was reduced in the gallopamil group (baseline vs. end of treatment) but was unchanged in the placebo group. Between-group differences in BSM area were not significantly different in gallopamil versus placebo groups. By contrast, between-group differences in normalized BSM thickness were significantly different between the two groups. The mean number of exacerbations per month was not different during the treatment phase in gallopamil versus placebo group but was significantly lower in patients previously treated with gallopamil during the follow-up period. There were no differences between the groups with respect to overall side effects. CONCLUSIONS Gallopamil treatment for 12 months reduces BSM remodeling and prevents the occurrence of asthma exacerbations. Clinical trial registered with www.clinicaltrials.gov (NCT 00896428).
Collapse
Affiliation(s)
- Pierre-Olivier Girodet
- 1 Université de Bordeaux, Centre de Recherche Cardio-thoracique de Bordeaux, U1045, Département de Pharmacologie, CIC1401, Bordeaux, France
| | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
29
|
Hackx M, Gyssels E, Severo Garcia T, De Meulder I, Alard S, Bruyneel M, Van Muylem A, Ninane V, Gevenois PA. Chronic Obstructive Pulmonary Disease: CT Quantification of Airway Dimensions, Numbers of Airways to Measure, and Effect of Bronchodilation. Radiology 2015; 277:853-62. [PMID: 25989594 DOI: 10.1148/radiol.2015140949] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
PURPOSE To determine the effect of bronchodilation on airway indexes reflecting airway disease in patients with chronic obstructive pulmonary disease (COPD) and to determine the minimum number of segmental and subsegmental airways required. MATERIALS AND METHODS This study was approved by the local ethical committee, and written informed consent was obtained from all subjects. Twenty patients with COPD who had undergone pre- and postbronchodilator pulmonary function tests and computed tomographic (CT) examinations were prospectively included. Eight healthy volunteers underwent two CT examinations. Luminal area and wall thickness (WT) of third- and fourth-generation airways were measured twice by three readers. The percentage of total airway area occupied by the wall and the square root of wall area at an internal perimeter of 10 mm (√WAPi10) were calculated. The effects of pathologic status, session, reader, bronchodilation, and CT examination were assessed by using mixed linear model analyses. The number of airways to measure for a definite percentage error of √WAPi10 was computed by using a bootstrap method. RESULTS There were no significant session, reader, or bronchodilation effects on WT in third-generation airways and √WAPi10 in patients with COPD (P values ranging from .187 to >.999). WT in third-generation airways and √WAPi10 were significantly different in patients with COPD and control subjects (P = .018 and <.001, respectively). Measuring 12 third- or fourth-generation airways ensured a maximal 10% error of √WAPi10. CONCLUSION WT in third-generation airways and √WAPi10 are not significantly different before and after bronchodilation and are different in patients with COPD and control subjects. Twelve is the minimum number of third- or fourth-generation airways required to ensure a maximal 10% error of √WAPi10. (©) RSNA, 2015 Clinical trial registration no. NCT01142531 Online supplemental material is available for this article.
Collapse
Affiliation(s)
- Maxime Hackx
- From the Departments of Radiology (M.H., E.G., T.S.G., P.A.G.) and Pneumology (A.V.M.), Hôpital Erasme, Université Libre de Bruxelles, 808 Route de Lennik, 1070 Brussels, Belgium; and Departments of Radiology (S.A.) and Pneumology (I.D., M.B., V.N.), Centre Hospitalier Universitaire Saint-Pierre, Université Libre de Bruxelles, Brussels, Belgium
| | - Elodie Gyssels
- From the Departments of Radiology (M.H., E.G., T.S.G., P.A.G.) and Pneumology (A.V.M.), Hôpital Erasme, Université Libre de Bruxelles, 808 Route de Lennik, 1070 Brussels, Belgium; and Departments of Radiology (S.A.) and Pneumology (I.D., M.B., V.N.), Centre Hospitalier Universitaire Saint-Pierre, Université Libre de Bruxelles, Brussels, Belgium
| | - Tiago Severo Garcia
- From the Departments of Radiology (M.H., E.G., T.S.G., P.A.G.) and Pneumology (A.V.M.), Hôpital Erasme, Université Libre de Bruxelles, 808 Route de Lennik, 1070 Brussels, Belgium; and Departments of Radiology (S.A.) and Pneumology (I.D., M.B., V.N.), Centre Hospitalier Universitaire Saint-Pierre, Université Libre de Bruxelles, Brussels, Belgium
| | - Isabelle De Meulder
- From the Departments of Radiology (M.H., E.G., T.S.G., P.A.G.) and Pneumology (A.V.M.), Hôpital Erasme, Université Libre de Bruxelles, 808 Route de Lennik, 1070 Brussels, Belgium; and Departments of Radiology (S.A.) and Pneumology (I.D., M.B., V.N.), Centre Hospitalier Universitaire Saint-Pierre, Université Libre de Bruxelles, Brussels, Belgium
| | - Stéphane Alard
- From the Departments of Radiology (M.H., E.G., T.S.G., P.A.G.) and Pneumology (A.V.M.), Hôpital Erasme, Université Libre de Bruxelles, 808 Route de Lennik, 1070 Brussels, Belgium; and Departments of Radiology (S.A.) and Pneumology (I.D., M.B., V.N.), Centre Hospitalier Universitaire Saint-Pierre, Université Libre de Bruxelles, Brussels, Belgium
| | - Marie Bruyneel
- From the Departments of Radiology (M.H., E.G., T.S.G., P.A.G.) and Pneumology (A.V.M.), Hôpital Erasme, Université Libre de Bruxelles, 808 Route de Lennik, 1070 Brussels, Belgium; and Departments of Radiology (S.A.) and Pneumology (I.D., M.B., V.N.), Centre Hospitalier Universitaire Saint-Pierre, Université Libre de Bruxelles, Brussels, Belgium
| | - Alain Van Muylem
- From the Departments of Radiology (M.H., E.G., T.S.G., P.A.G.) and Pneumology (A.V.M.), Hôpital Erasme, Université Libre de Bruxelles, 808 Route de Lennik, 1070 Brussels, Belgium; and Departments of Radiology (S.A.) and Pneumology (I.D., M.B., V.N.), Centre Hospitalier Universitaire Saint-Pierre, Université Libre de Bruxelles, Brussels, Belgium
| | - Vincent Ninane
- From the Departments of Radiology (M.H., E.G., T.S.G., P.A.G.) and Pneumology (A.V.M.), Hôpital Erasme, Université Libre de Bruxelles, 808 Route de Lennik, 1070 Brussels, Belgium; and Departments of Radiology (S.A.) and Pneumology (I.D., M.B., V.N.), Centre Hospitalier Universitaire Saint-Pierre, Université Libre de Bruxelles, Brussels, Belgium
| | - Pierre Alain Gevenois
- From the Departments of Radiology (M.H., E.G., T.S.G., P.A.G.) and Pneumology (A.V.M.), Hôpital Erasme, Université Libre de Bruxelles, 808 Route de Lennik, 1070 Brussels, Belgium; and Departments of Radiology (S.A.) and Pneumology (I.D., M.B., V.N.), Centre Hospitalier Universitaire Saint-Pierre, Université Libre de Bruxelles, Brussels, Belgium
| |
Collapse
|
30
|
Thomson NC, Chaudhuri R, Spears M, Messow CM, MacNee W, Connell M, Murchison JT, Sproule M, McSharry C. Poor symptom control is associated with reduced CT scan segmental airway lumen area in smokers with asthma. Chest 2015; 147:735-744. [PMID: 25356950 DOI: 10.1378/chest.14-1119] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Cigarette smoking is associated with worse symptoms in asthma and abnormal segmental airways in healthy subjects. We tested the hypothesis that current symptom control in smokers with asthma is associated with altered segmental airway dimensions measured by CT scan. METHODS In 93 subjects with mild, moderate, and severe asthma (smokers and never smokers), we recorded Asthma Control Questionnaire-6 (ACQ-6) score, spirometry (FEV1; forced expiratory flow rate, midexpiratory phase [FEF(25%-75%)]), residual volume (RV), total lung capacity (TLC), and CT scan measures of the right bronchial (RB) and left bronchial (LB) segmental airway dimensions (wall thickness, mm; lumen area, mm²) in the RB3/LB3, RB6/LB6, and RB10/LB10 (smaller) airways. RESULTS The CT scan segmental airway (RB10 and LB10) lumen area was reduced in smokers with asthma compared with never smokers with asthma; RB10, 16.6 mm² (interquartile range, 12.4-19.2 mm²) vs 19.6 mm² (14.7-24.2 mm²) (P = .01); LB10, 14.8 mm² (12.1-19.0 mm²) vs 19.9 mm² (14.5-25.0 mm²) (P = .003), particularly in severe disease, with no differences in wall thickness or in larger airway (RB3 and LB3) dimensions. In smokers with asthma, a reduced lumen area in fifth-generation airways (RB10 or LB10) was associated with poor symptom control (higher ACQ-6 score) (-0.463 [-0.666 to -0.196], P = .001, and -0.401 [-0.619 to -0.126], P = .007, respectively) and reduced postbronchodilator FEF(25%-75%) (0.521 [0.292-0.694], P < .001, and [0.471 [0.236-0.654], P = .001, respectively) and higher RV/TLC %. CONCLUSIONS The CT scan segmental airway lumen area is reduced in smokers with asthma compared with never smokers with asthma, particularly in severe disease, and is associated with worse current symptom control and small airway dysfunction.
Collapse
Affiliation(s)
- Neil C Thomson
- Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow.
| | - Rekha Chaudhuri
- Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow
| | - Mark Spears
- Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow
| | | | - William MacNee
- UoE/MRC Centre for Inflammation Research, Medical Physics and Clinical Radiology, University of Edinburgh, Edinburgh
| | - Martin Connell
- UoE/MRC Centre for Inflammation Research, Medical Physics and Clinical Radiology, University of Edinburgh, Edinburgh
| | - John T Murchison
- UoE/MRC Centre for Inflammation Research, Medical Physics and Clinical Radiology, University of Edinburgh, Edinburgh
| | - Michael Sproule
- Department of Radiology, Gartnavel General Hospital, Glasgow, Scotland
| | - Charles McSharry
- Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow
| |
Collapse
|
31
|
Lynch DA, Austin JHM, Hogg JC, Grenier PA, Kauczor HU, Bankier AA, Barr RG, Colby TV, Galvin JR, Gevenois PA, Coxson HO, Hoffman EA, Newell JD, Pistolesi M, Silverman EK, Crapo JD. CT-Definable Subtypes of Chronic Obstructive Pulmonary Disease: A Statement of the Fleischner Society. Radiology 2015; 277:192-205. [PMID: 25961632 DOI: 10.1148/radiol.2015141579] [Citation(s) in RCA: 365] [Impact Index Per Article: 40.6] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
The purpose of this statement is to describe and define the phenotypic abnormalities that can be identified on visual and quantitative evaluation of computed tomographic (CT) images in subjects with chronic obstructive pulmonary disease (COPD), with the goal of contributing to a personalized approach to the treatment of patients with COPD. Quantitative CT is useful for identifying and sequentially evaluating the extent of emphysematous lung destruction, changes in airway walls, and expiratory air trapping. However, visual assessment of CT scans remains important to describe patterns of altered lung structure in COPD. The classification system proposed and illustrated in this article provides a structured approach to visual and quantitative assessment of COPD. Emphysema is classified as centrilobular (subclassified as trace, mild, moderate, confluent, and advanced destructive emphysema), panlobular, and paraseptal (subclassified as mild or substantial). Additional important visual features include airway wall thickening, inflammatory small airways disease, tracheal abnormalities, interstitial lung abnormalities, pulmonary arterial enlargement, and bronchiectasis.
Collapse
Affiliation(s)
- David A Lynch
- From the Departments of Radiology (D.A.L.) and Medicine (J.D.C.), National Jewish Health, 1400 Jackson St, Denver, CO 80206; Department of Radiology, Columbia University, New York, NY (J.H.M.A.); Department of Pathology, University of British Columbia, Vancouver, BC, Canada (J.C.H.); Department of Radiology, Hôpital Pitié-Salpêtrière, Paris, France (P.A.G.); Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany (H.U.K.); Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (A.A.B.); Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY (R.G.B.); Department of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.V.C.); Department of Chest Imaging, American Institute for Radiologic Pathology, Silver Spring, Md (J.R.G.); Department of Radiology, Hôpital Erasme, Brussels, Belgium (P.A.G.); Department of Radiology, Vancouver General Hospital, Vancouver, BC, Canada (H.C.); Department of Radiology, Division of Physiological Imaging, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa (E.A.H., J.D.N.); Respiratory Unit, Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy (M.P.); and Channing Laboratory, Brigham and Women's Hospital, Boston, Mass (E.K.S.)
| | - John H M Austin
- From the Departments of Radiology (D.A.L.) and Medicine (J.D.C.), National Jewish Health, 1400 Jackson St, Denver, CO 80206; Department of Radiology, Columbia University, New York, NY (J.H.M.A.); Department of Pathology, University of British Columbia, Vancouver, BC, Canada (J.C.H.); Department of Radiology, Hôpital Pitié-Salpêtrière, Paris, France (P.A.G.); Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany (H.U.K.); Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (A.A.B.); Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY (R.G.B.); Department of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.V.C.); Department of Chest Imaging, American Institute for Radiologic Pathology, Silver Spring, Md (J.R.G.); Department of Radiology, Hôpital Erasme, Brussels, Belgium (P.A.G.); Department of Radiology, Vancouver General Hospital, Vancouver, BC, Canada (H.C.); Department of Radiology, Division of Physiological Imaging, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa (E.A.H., J.D.N.); Respiratory Unit, Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy (M.P.); and Channing Laboratory, Brigham and Women's Hospital, Boston, Mass (E.K.S.)
| | - James C Hogg
- From the Departments of Radiology (D.A.L.) and Medicine (J.D.C.), National Jewish Health, 1400 Jackson St, Denver, CO 80206; Department of Radiology, Columbia University, New York, NY (J.H.M.A.); Department of Pathology, University of British Columbia, Vancouver, BC, Canada (J.C.H.); Department of Radiology, Hôpital Pitié-Salpêtrière, Paris, France (P.A.G.); Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany (H.U.K.); Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (A.A.B.); Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY (R.G.B.); Department of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.V.C.); Department of Chest Imaging, American Institute for Radiologic Pathology, Silver Spring, Md (J.R.G.); Department of Radiology, Hôpital Erasme, Brussels, Belgium (P.A.G.); Department of Radiology, Vancouver General Hospital, Vancouver, BC, Canada (H.C.); Department of Radiology, Division of Physiological Imaging, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa (E.A.H., J.D.N.); Respiratory Unit, Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy (M.P.); and Channing Laboratory, Brigham and Women's Hospital, Boston, Mass (E.K.S.)
| | - Philippe A Grenier
- From the Departments of Radiology (D.A.L.) and Medicine (J.D.C.), National Jewish Health, 1400 Jackson St, Denver, CO 80206; Department of Radiology, Columbia University, New York, NY (J.H.M.A.); Department of Pathology, University of British Columbia, Vancouver, BC, Canada (J.C.H.); Department of Radiology, Hôpital Pitié-Salpêtrière, Paris, France (P.A.G.); Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany (H.U.K.); Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (A.A.B.); Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY (R.G.B.); Department of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.V.C.); Department of Chest Imaging, American Institute for Radiologic Pathology, Silver Spring, Md (J.R.G.); Department of Radiology, Hôpital Erasme, Brussels, Belgium (P.A.G.); Department of Radiology, Vancouver General Hospital, Vancouver, BC, Canada (H.C.); Department of Radiology, Division of Physiological Imaging, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa (E.A.H., J.D.N.); Respiratory Unit, Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy (M.P.); and Channing Laboratory, Brigham and Women's Hospital, Boston, Mass (E.K.S.)
| | - Hans-Ulrich Kauczor
- From the Departments of Radiology (D.A.L.) and Medicine (J.D.C.), National Jewish Health, 1400 Jackson St, Denver, CO 80206; Department of Radiology, Columbia University, New York, NY (J.H.M.A.); Department of Pathology, University of British Columbia, Vancouver, BC, Canada (J.C.H.); Department of Radiology, Hôpital Pitié-Salpêtrière, Paris, France (P.A.G.); Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany (H.U.K.); Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (A.A.B.); Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY (R.G.B.); Department of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.V.C.); Department of Chest Imaging, American Institute for Radiologic Pathology, Silver Spring, Md (J.R.G.); Department of Radiology, Hôpital Erasme, Brussels, Belgium (P.A.G.); Department of Radiology, Vancouver General Hospital, Vancouver, BC, Canada (H.C.); Department of Radiology, Division of Physiological Imaging, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa (E.A.H., J.D.N.); Respiratory Unit, Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy (M.P.); and Channing Laboratory, Brigham and Women's Hospital, Boston, Mass (E.K.S.)
| | - Alexander A Bankier
- From the Departments of Radiology (D.A.L.) and Medicine (J.D.C.), National Jewish Health, 1400 Jackson St, Denver, CO 80206; Department of Radiology, Columbia University, New York, NY (J.H.M.A.); Department of Pathology, University of British Columbia, Vancouver, BC, Canada (J.C.H.); Department of Radiology, Hôpital Pitié-Salpêtrière, Paris, France (P.A.G.); Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany (H.U.K.); Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (A.A.B.); Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY (R.G.B.); Department of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.V.C.); Department of Chest Imaging, American Institute for Radiologic Pathology, Silver Spring, Md (J.R.G.); Department of Radiology, Hôpital Erasme, Brussels, Belgium (P.A.G.); Department of Radiology, Vancouver General Hospital, Vancouver, BC, Canada (H.C.); Department of Radiology, Division of Physiological Imaging, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa (E.A.H., J.D.N.); Respiratory Unit, Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy (M.P.); and Channing Laboratory, Brigham and Women's Hospital, Boston, Mass (E.K.S.)
| | - R Graham Barr
- From the Departments of Radiology (D.A.L.) and Medicine (J.D.C.), National Jewish Health, 1400 Jackson St, Denver, CO 80206; Department of Radiology, Columbia University, New York, NY (J.H.M.A.); Department of Pathology, University of British Columbia, Vancouver, BC, Canada (J.C.H.); Department of Radiology, Hôpital Pitié-Salpêtrière, Paris, France (P.A.G.); Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany (H.U.K.); Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (A.A.B.); Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY (R.G.B.); Department of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.V.C.); Department of Chest Imaging, American Institute for Radiologic Pathology, Silver Spring, Md (J.R.G.); Department of Radiology, Hôpital Erasme, Brussels, Belgium (P.A.G.); Department of Radiology, Vancouver General Hospital, Vancouver, BC, Canada (H.C.); Department of Radiology, Division of Physiological Imaging, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa (E.A.H., J.D.N.); Respiratory Unit, Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy (M.P.); and Channing Laboratory, Brigham and Women's Hospital, Boston, Mass (E.K.S.)
| | - Thomas V Colby
- From the Departments of Radiology (D.A.L.) and Medicine (J.D.C.), National Jewish Health, 1400 Jackson St, Denver, CO 80206; Department of Radiology, Columbia University, New York, NY (J.H.M.A.); Department of Pathology, University of British Columbia, Vancouver, BC, Canada (J.C.H.); Department of Radiology, Hôpital Pitié-Salpêtrière, Paris, France (P.A.G.); Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany (H.U.K.); Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (A.A.B.); Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY (R.G.B.); Department of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.V.C.); Department of Chest Imaging, American Institute for Radiologic Pathology, Silver Spring, Md (J.R.G.); Department of Radiology, Hôpital Erasme, Brussels, Belgium (P.A.G.); Department of Radiology, Vancouver General Hospital, Vancouver, BC, Canada (H.C.); Department of Radiology, Division of Physiological Imaging, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa (E.A.H., J.D.N.); Respiratory Unit, Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy (M.P.); and Channing Laboratory, Brigham and Women's Hospital, Boston, Mass (E.K.S.)
| | - Jeffrey R Galvin
- From the Departments of Radiology (D.A.L.) and Medicine (J.D.C.), National Jewish Health, 1400 Jackson St, Denver, CO 80206; Department of Radiology, Columbia University, New York, NY (J.H.M.A.); Department of Pathology, University of British Columbia, Vancouver, BC, Canada (J.C.H.); Department of Radiology, Hôpital Pitié-Salpêtrière, Paris, France (P.A.G.); Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany (H.U.K.); Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (A.A.B.); Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY (R.G.B.); Department of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.V.C.); Department of Chest Imaging, American Institute for Radiologic Pathology, Silver Spring, Md (J.R.G.); Department of Radiology, Hôpital Erasme, Brussels, Belgium (P.A.G.); Department of Radiology, Vancouver General Hospital, Vancouver, BC, Canada (H.C.); Department of Radiology, Division of Physiological Imaging, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa (E.A.H., J.D.N.); Respiratory Unit, Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy (M.P.); and Channing Laboratory, Brigham and Women's Hospital, Boston, Mass (E.K.S.)
| | - Pierre Alain Gevenois
- From the Departments of Radiology (D.A.L.) and Medicine (J.D.C.), National Jewish Health, 1400 Jackson St, Denver, CO 80206; Department of Radiology, Columbia University, New York, NY (J.H.M.A.); Department of Pathology, University of British Columbia, Vancouver, BC, Canada (J.C.H.); Department of Radiology, Hôpital Pitié-Salpêtrière, Paris, France (P.A.G.); Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany (H.U.K.); Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (A.A.B.); Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY (R.G.B.); Department of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.V.C.); Department of Chest Imaging, American Institute for Radiologic Pathology, Silver Spring, Md (J.R.G.); Department of Radiology, Hôpital Erasme, Brussels, Belgium (P.A.G.); Department of Radiology, Vancouver General Hospital, Vancouver, BC, Canada (H.C.); Department of Radiology, Division of Physiological Imaging, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa (E.A.H., J.D.N.); Respiratory Unit, Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy (M.P.); and Channing Laboratory, Brigham and Women's Hospital, Boston, Mass (E.K.S.)
| | - Harvey O Coxson
- From the Departments of Radiology (D.A.L.) and Medicine (J.D.C.), National Jewish Health, 1400 Jackson St, Denver, CO 80206; Department of Radiology, Columbia University, New York, NY (J.H.M.A.); Department of Pathology, University of British Columbia, Vancouver, BC, Canada (J.C.H.); Department of Radiology, Hôpital Pitié-Salpêtrière, Paris, France (P.A.G.); Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany (H.U.K.); Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (A.A.B.); Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY (R.G.B.); Department of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.V.C.); Department of Chest Imaging, American Institute for Radiologic Pathology, Silver Spring, Md (J.R.G.); Department of Radiology, Hôpital Erasme, Brussels, Belgium (P.A.G.); Department of Radiology, Vancouver General Hospital, Vancouver, BC, Canada (H.C.); Department of Radiology, Division of Physiological Imaging, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa (E.A.H., J.D.N.); Respiratory Unit, Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy (M.P.); and Channing Laboratory, Brigham and Women's Hospital, Boston, Mass (E.K.S.)
| | - Eric A Hoffman
- From the Departments of Radiology (D.A.L.) and Medicine (J.D.C.), National Jewish Health, 1400 Jackson St, Denver, CO 80206; Department of Radiology, Columbia University, New York, NY (J.H.M.A.); Department of Pathology, University of British Columbia, Vancouver, BC, Canada (J.C.H.); Department of Radiology, Hôpital Pitié-Salpêtrière, Paris, France (P.A.G.); Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany (H.U.K.); Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (A.A.B.); Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY (R.G.B.); Department of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.V.C.); Department of Chest Imaging, American Institute for Radiologic Pathology, Silver Spring, Md (J.R.G.); Department of Radiology, Hôpital Erasme, Brussels, Belgium (P.A.G.); Department of Radiology, Vancouver General Hospital, Vancouver, BC, Canada (H.C.); Department of Radiology, Division of Physiological Imaging, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa (E.A.H., J.D.N.); Respiratory Unit, Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy (M.P.); and Channing Laboratory, Brigham and Women's Hospital, Boston, Mass (E.K.S.)
| | - John D Newell
- From the Departments of Radiology (D.A.L.) and Medicine (J.D.C.), National Jewish Health, 1400 Jackson St, Denver, CO 80206; Department of Radiology, Columbia University, New York, NY (J.H.M.A.); Department of Pathology, University of British Columbia, Vancouver, BC, Canada (J.C.H.); Department of Radiology, Hôpital Pitié-Salpêtrière, Paris, France (P.A.G.); Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany (H.U.K.); Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (A.A.B.); Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY (R.G.B.); Department of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.V.C.); Department of Chest Imaging, American Institute for Radiologic Pathology, Silver Spring, Md (J.R.G.); Department of Radiology, Hôpital Erasme, Brussels, Belgium (P.A.G.); Department of Radiology, Vancouver General Hospital, Vancouver, BC, Canada (H.C.); Department of Radiology, Division of Physiological Imaging, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa (E.A.H., J.D.N.); Respiratory Unit, Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy (M.P.); and Channing Laboratory, Brigham and Women's Hospital, Boston, Mass (E.K.S.)
| | - Massimo Pistolesi
- From the Departments of Radiology (D.A.L.) and Medicine (J.D.C.), National Jewish Health, 1400 Jackson St, Denver, CO 80206; Department of Radiology, Columbia University, New York, NY (J.H.M.A.); Department of Pathology, University of British Columbia, Vancouver, BC, Canada (J.C.H.); Department of Radiology, Hôpital Pitié-Salpêtrière, Paris, France (P.A.G.); Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany (H.U.K.); Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (A.A.B.); Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY (R.G.B.); Department of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.V.C.); Department of Chest Imaging, American Institute for Radiologic Pathology, Silver Spring, Md (J.R.G.); Department of Radiology, Hôpital Erasme, Brussels, Belgium (P.A.G.); Department of Radiology, Vancouver General Hospital, Vancouver, BC, Canada (H.C.); Department of Radiology, Division of Physiological Imaging, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa (E.A.H., J.D.N.); Respiratory Unit, Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy (M.P.); and Channing Laboratory, Brigham and Women's Hospital, Boston, Mass (E.K.S.)
| | - Edwin K Silverman
- From the Departments of Radiology (D.A.L.) and Medicine (J.D.C.), National Jewish Health, 1400 Jackson St, Denver, CO 80206; Department of Radiology, Columbia University, New York, NY (J.H.M.A.); Department of Pathology, University of British Columbia, Vancouver, BC, Canada (J.C.H.); Department of Radiology, Hôpital Pitié-Salpêtrière, Paris, France (P.A.G.); Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany (H.U.K.); Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (A.A.B.); Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY (R.G.B.); Department of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.V.C.); Department of Chest Imaging, American Institute for Radiologic Pathology, Silver Spring, Md (J.R.G.); Department of Radiology, Hôpital Erasme, Brussels, Belgium (P.A.G.); Department of Radiology, Vancouver General Hospital, Vancouver, BC, Canada (H.C.); Department of Radiology, Division of Physiological Imaging, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa (E.A.H., J.D.N.); Respiratory Unit, Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy (M.P.); and Channing Laboratory, Brigham and Women's Hospital, Boston, Mass (E.K.S.)
| | - James D Crapo
- From the Departments of Radiology (D.A.L.) and Medicine (J.D.C.), National Jewish Health, 1400 Jackson St, Denver, CO 80206; Department of Radiology, Columbia University, New York, NY (J.H.M.A.); Department of Pathology, University of British Columbia, Vancouver, BC, Canada (J.C.H.); Department of Radiology, Hôpital Pitié-Salpêtrière, Paris, France (P.A.G.); Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany (H.U.K.); Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (A.A.B.); Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY (R.G.B.); Department of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.V.C.); Department of Chest Imaging, American Institute for Radiologic Pathology, Silver Spring, Md (J.R.G.); Department of Radiology, Hôpital Erasme, Brussels, Belgium (P.A.G.); Department of Radiology, Vancouver General Hospital, Vancouver, BC, Canada (H.C.); Department of Radiology, Division of Physiological Imaging, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa (E.A.H., J.D.N.); Respiratory Unit, Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy (M.P.); and Channing Laboratory, Brigham and Women's Hospital, Boston, Mass (E.K.S.)
| |
Collapse
|
32
|
Dournes G, Laurent F, Coste F, Dromer C, Blanchard E, Picard F, Baldacci F, Montaudon M, Girodet PO, Marthan R, Berger P. Computed Tomographic Measurement of Airway Remodeling and Emphysema in Advanced Chronic Obstructive Pulmonary Disease. Correlation with Pulmonary Hypertension. Am J Respir Crit Care Med 2015; 191:63-70. [DOI: 10.1164/rccm.201408-1423oc] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
|
33
|
Szabo D, Sutherland-Smith J, Barton B, Rozanski EA, Taeymans O. Accuracy of a computed tomography bronchial wall thickness to pulmonary artery diameter ratio for assessing bronchial wall thickening in dogs. Vet Radiol Ultrasound 2014; 56:264-71. [PMID: 25376985 DOI: 10.1111/vru.12216] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2014] [Accepted: 08/27/2014] [Indexed: 11/30/2022] Open
Abstract
Computed tomography is increasingly being used in veterinary medicine to evaluate animals with pulmonary signs such as coughing, tachypnea, and exercise intolerance, however, a quantitative measure of bronchial wall thickening has yet to be validated in veterinary medicine. Canine chronic bronchitis is a disease that is characterized histologically by thickening of the bronchial walls. Thoracic CT images of 16 dogs with chronic bronchitis and 72 dogs presenting for conditions unrelated to cough were evaluated. A ratio comparing the bronchial wall thickness to the adjacent pulmonary artery diameter was obtained in the right and left cranial and caudal lung lobes. There was no significant difference in dogs with chronic bronchitis or unaffected dogs between the left and right hemithorax, patient weight, patient age, image slice thickness, or CT machine used. Dogs with chronic bronchitis were found to have a significantly greater ratio than unaffected dogs (P < 0.001). The ratios in the cranial lung lobes were found to be significantly greater than the caudal lung lobes in both chronic bronchitis and unaffected dogs (P < 0.001). A receiver operating characteristic curve of the ratios in the cranial lung lobes had an area under the curve of 0.912, indicating high accuracy in predicting for bronchial wall thickening. A ratio of ≥ 0.6 in the cranial lung lobes was found to have a sensitivity of 77% and specificity of 100% in predicting for the presence of chronic bronchitis, and we propose using this cut-off as supportive of bronchial wall thickening on CT.
Collapse
Affiliation(s)
- David Szabo
- Cummings School of Veterinary Medicine at Tufts University, Department of Clinical Sciences, 200 Westboro Road, North Grafton, MA, 01536
| | | | | | | | | |
Collapse
|
34
|
Smith BM, Hoffman EA, Rabinowitz D, Bleecker E, Christenson S, Couper D, Donohue KM, Han MK, Hansel NN, Kanner RE, Kleerup E, Rennard S, Barr RG. Comparison of spatially matched airways reveals thinner airway walls in COPD. The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study and the Subpopulations and Intermediate Outcomes in COPD Study (SPIROMICS). Thorax 2014; 69:987-96. [PMID: 24928812 PMCID: PMC4198462 DOI: 10.1136/thoraxjnl-2014-205160] [Citation(s) in RCA: 99] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
BACKGROUND COPD is characterised by reduced airway lumen dimensions and fewer peripheral airways. Most studies of airway properties sample airways based upon lumen dimension or at random, which may bias comparisons given reduced airway lumen dimensions and number in COPD. We sought to compare central airway wall dimensions on CT in COPD and controls using spatially matched airways, thereby avoiding selection bias of airways in the lung. METHODS The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study and Subpopulations and Intermediate Outcomes in COPD Study (SPIROMICS) recruited smokers with COPD and controls aged 50-79 years and 40-80 years, respectively. COPD was defined by current guidelines. Using CT image data, airway dimensions were measured for all central airway segments (generations 0-6) following 5 standardised paths into the lungs. Case-control airway comparisons were spatially matched by generation and adjusted for demographics, body size, smoking, CT dose, per cent emphysema, airway length and lung volume. RESULTS Among 311 MESA COPD participants, airway wall areas at generations 3-6 were smaller in COPD compared with controls (all p<0.001). Among 1248 SPIROMICS participants, airway wall areas at generations 1-6 were smaller (all p<0.001), and this reduction was monotonic with increasing COPD severity (p<0.001). In both studies, sampling airways by lumen diameter or randomly resulted in a comparison of more proximal airways in COPD to more peripheral airways in controls (p<0.001) resulting in the appearance of thicker walls in COPD (p<0.02). CONCLUSIONS Airway walls are thinner in COPD when comparing spatially matched central airways. Other approaches to airway sampling result in comparisons of more proximal to more distal airways and potentially biased assessment of airway properties in COPD.
Collapse
Affiliation(s)
- Benjamin M. Smith
- Department of Medicine, College of Physicians and Surgeons, Columbia University, New York, NY
- Department of Medicine, McGill University, Montreal, Canada
| | - Eric A. Hoffman
- Departments of Radiology, Medicine and Biomedical Engineering, University of Iowa, Iowa City, IA
| | - Dan Rabinowitz
- Department of Statistics, Columbia University, New York, NY
| | - Eugene Bleecker
- Department of Medicine, Wake Forest University, Winston-Salem, NC
| | | | - David Couper
- Deparment of Biostatistics, University of North Carolina Chapel Hill, Chapel Hill, NC
| | - Kathleen M. Donohue
- Department of Medicine, College of Physicians and Surgeons, Columbia University, New York, NY
| | - Meilan K. Han
- Department of Medicine, University of Michigan, Ann Arbor, MI
| | - Nadia N. Hansel
- Department of Medicine, Johns Hopkins University, Baltimore, MD
| | | | - Eric Kleerup
- Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, CA
| | - Stephen Rennard
- Department of Medicine, University of Nebraska Medical Center, Omaha, NE
| | - R. Graham Barr
- Department of Medicine, College of Physicians and Surgeons, Columbia University, New York, NY
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY
| |
Collapse
|
35
|
McNulty W, Usmani OS. Techniques of assessing small airways dysfunction. Eur Clin Respir J 2014; 1:25898. [PMID: 26557240 PMCID: PMC4629724 DOI: 10.3402/ecrj.v1.25898] [Citation(s) in RCA: 138] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2014] [Accepted: 09/11/2014] [Indexed: 11/17/2022] Open
Abstract
The small airways are defined as those less than 2 mm in diameter. They are a major site of pathology in many lung diseases, not least chronic obstructive pulmonary disease (COPD) and asthma. The small airways are frequently involved early in the course of these diseases, with significant pathology demonstrable often before the onset of symptoms or changes in spirometry and imaging. Despite their importance, they have proven relatively difficult to study. This is in part due to their relative inaccessibility to biopsy and their small size which makes their imaging difficult. Traditional lung function tests may only become abnormal once there is a significant burden of disease within them. This has led to the term 'the quiet zone' of the lung. In recent years, more specialised tests have been developed which may detect these changes earlier, perhaps offering the possibility of earlier diagnosis and intervention. These tests are now moving from the realms of clinical research laboratories into routine clinical practice and are increasingly useful in the diagnosis and monitoring of respiratory diseases. This article gives an overview of small airways physiology and some of the routine and more advanced tests of airway function.
Collapse
Affiliation(s)
- William McNulty
- National Heart and lung Institute, Imperial College London and Royal Brompton Hospital, London, UK
| | | |
Collapse
|
36
|
Ratios of peripheral-to-central airway lumen area and percentage wall area as predictors of severity of chronic obstructive pulmonary disease. AJR Am J Roentgenol 2014; 203:78-84. [PMID: 24951198 DOI: 10.2214/ajr.13.11748] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
OBJECTIVE The purpose of this study was to assess the ability of the ratios of peripheral-to-central airway lumen area (hereafter referred to as LA) and percentage wall area (hereafter referred to as %WA) to predict the severity of chronic obstructive pulmonary disease (COPD) according to Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines. SUBJECTS AND METHODS We examined 32 patients (27 men and five women; mean age ± SD, 70.0 ± 6.8 years; seven GOLD stage 0 [at risk for COPD], 19 GOLD stage 1-2 [mild to moderate airflow limitation], and six GOLD stage 3-4 [severe to very severe airflow limitation]) using inspiratory CT. Mean LA and %WA were measured for the first (main bronchi), third, and fifth generations of five bronchi in each lobe and the ratios of peripheral to central airways were calculated (third to first, fifth to first, and fifth to third) and statistically compared. RESULTS The fifth-generation LA, LA fifth to first, and LA fifth to third significantly decreased and fifth %WA, %WA fifth to first, and %WA fifth to third also increased with progression of GOLD stage (p < 0.05), but central measurements, including first and third generations, did not. There were significant differences between GOLD 0 and GOLD 1-2 for %WA fifth to third and LA fifth to third and between GOLD 0 and GOLD 3-4 for all six parameters (p < 0.05); %WA fifth to third had the best cutoff value of 1.02 (sensitivity, 92%; specificity, 86%) for diagnosis of COPD (GOLD 1-4). The %WA fifth to first of 1.51 (sensitivity, 83%; specificity, 89%) was best for diagnosis of GOLD 3-4. CONCLUSION Ratios of peripheral-to-central airway LA and %WA show improved correlation with COPD severity.
Collapse
|
37
|
Fetita C, Ortner M, Brillet PY, Preteux F, Grenier PA. Volumetric quantification of airway wall in CT via collision-free active surface model: application to asthma assessment. IEEE TRANSACTIONS ON MEDICAL IMAGING 2014; 33:1512-1526. [PMID: 24723624 DOI: 10.1109/tmi.2014.2316115] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Emerging idea in asthma phenotyping, incorporating local morphometric information on the airway wall thickness would be able to better account for the process of airway remodeling as indicator of pathology or therapeutic impact. It is thus important that such information be provided uniformly along the airway tree, not on a sparse (cross-section) sampling basis. The volumetric segmentation of the airway wall from CT data is the issue addressed in this paper by exploiting a patient-specific surface active model. An original aspect taken into account in the proposed deformable model is the management of auto-collisions for this complex morphology. The analysis of several solutions ended up with the design of a motion vector field specific to the patient geometry to guide the deformation. The segmentation result, presented as two embedded inner/outer surfaces of the wall, allows the quantification of the tissue thickness based on a locally-defined measure sensitive to even small surface irregularities. The method is validated with respect to several ground truth simulations of pulmonary CT data with different airway geometries and acquisition protocols showing accuracy within the CT resolution range. Results from an ongoing clinical study on moderate and severe asthma are presented and discussed.
Collapse
|
38
|
Multidetector Computed Tomographic Imaging in Chronic Obstructive Pulmonary Disease. Radiol Clin North Am 2014; 52:137-54. [DOI: 10.1016/j.rcl.2013.09.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
|
39
|
Lutey BA, Conradi SH, Atkinson JJ, Zheng J, Schechtman KB, Senior RM, Gierada DS. Accurate measurement of small airways on low-dose thoracic CT scans in smokers. Chest 2013; 143:1321-1329. [PMID: 23172175 DOI: 10.1378/chest.12-0034] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Partial volume averaging and tilt relative to the scan plane on transverse images limit the accuracy of airway wall thickness measurements on CT scan, confounding assessment of the relationship between airway remodeling and clinical status in COPD. The purpose of this study was to assess the effect of partial volume averaging and tilt corrections on airway wall thickness measurement accuracy and on relationships between airway wall thickening and clinical status in COPD. METHODS Airway wall thickness measurements in 80 heavy smokers were obtained on transverse images from low-dose CT scan using the open-source program Airway Inspector. Measurements were corrected for partial volume averaging and tilt effects using an attenuation- and geometry-based algorithm and compared with functional status. RESULTS The algorithm reduced wall thickness measurements of smaller airways to a greater degree than larger airways, increasing the overall range. When restricted to analyses of airways with an inner diameter < 3.0 mm, for a theoretical airway of 2.0 mm inner diameter, the wall thickness decreased from 1.07 ± 0.07 to 0.29 ± 0.10 mm, and the square root of the wall area decreased from 3.34 ± 0.15 to 1.58 ± 0.29 mm, comparable to histologic measurement studies. Corrected measurements had higher correlation with FEV₁, differed more between BMI, airflow obstruction, dyspnea, and exercise capacity (BODE) index scores, and explained a greater proportion of FEV1 variability in multivariate models. CONCLUSIONS Correcting for partial volume averaging improves accuracy of airway wall thickness estimation, allowing direct measurement of the small airways to better define their role in COPD.
Collapse
Affiliation(s)
- Barbara A Lutey
- Division of Medical Education, Washington University School of Medicine, St Louis, MO.
| | - Susan H Conradi
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO
| | - Jeffrey J Atkinson
- Division of Pulmonary and Critical Care Medicine, Washington University School of Medicine, St Louis, MO
| | - Jie Zheng
- Division of Biostatistics, Washington University School of Medicine, St Louis, MO
| | - Kenneth B Schechtman
- Division of Biostatistics, Washington University School of Medicine, St Louis, MO
| | - Robert M Senior
- Division of Pulmonary and Critical Care Medicine, Washington University School of Medicine, St Louis, MO
| | - David S Gierada
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO
| |
Collapse
|
40
|
Han F, Zhang B. Characterizing cell-cell interactions induced spatial organization of cell phenotypes: application to density-dependent protein nucleocytoplasmic distribution. Cell Biochem Biophys 2013; 65:163-72. [PMID: 22915253 DOI: 10.1007/s12013-012-9412-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Cell-cell interactions play an important role in spatial organization (pattern formation) during the development of multicellular organisms. An understanding of these biological roles requires identifying cell phenotypes that are regulated by cell-cell interactions and characterizing the spatial organizations of the phenotypes. However, conventional methods for assaying cell-cell interactions are mainly applicable at a cell population level. These measures are incapable of elucidating the spatial organizations of the phenotypes, resulting in an incomplete view of cell-cell interactions. To overcome this issue, we developed an automated image-based method to investigate cell-cell interactions based on spatial localizations of cells. We demonstrated this method in cultured cells using cell density-dependent nucleocytoplasmic distribution of β-catenin and aryl hydrocarbon receptor as the phenotype. This novel method was validated by comparing with a conventional population-based method, and proved to be more sensitive and reliable. The application of the method characterized how the phenotypes were spatially organized in a population of cultured cells. We further showed that the spatial organization was governed by cell density and was protein-specific. This automated method is very simple, and will be applicable to study cell-cell interactions in different systems from prokaryotic colonies to multicellular organisms. We envision that the ability to extract and interpret how cell-cell interactions determine the spatial organization of a cell phenotype will provide new insights into biology that may be missed by traditional population-averaged studies.
Collapse
Affiliation(s)
- Fujun Han
- Cancer Center, The First Hospital of Jilin University, Changchun, People's Republic of China.
| | | |
Collapse
|
41
|
Mumcuoğlu EU, Long FR, Castile RG, Gurcan MN. Image analysis for cystic fibrosis: computer-assisted airway wall and vessel measurements from low-dose, limited scan lung CT images. J Digit Imaging 2013; 26:82-96. [PMID: 22549245 PMCID: PMC3553364 DOI: 10.1007/s10278-012-9476-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022] Open
Abstract
Cystic fibrosis (CF) is a life-limiting genetic disease that affects approximately 30,000 Americans. When compared to those of normal children, airways of infants and young children with CF have thicker walls and are more dilated in high-resolution computed tomographic (CT) imaging. In this study, we develop computer-assisted methods for assessment of airway and vessel dimensions from axial, limited scan CT lung images acquired at low pediatric radiation doses. Two methods (threshold- and model-based) were developed to automatically measure airway and vessel sizes for pairs identified by a user. These methods were evaluated on chest CT images from 16 pediatric patients (eight infants and eight children) with different stages of mild CF related lung disease. Results of threshold-based, corrected with regression analysis, and model-based approaches correlated well with both electronic caliper measurements made by experienced observers and spirometric measurements of lung function. While the model-based approach results correlated slightly better with the human measurements than those of the threshold method, a hybrid method, combining these two methods, resulted in the best results.
Collapse
Affiliation(s)
- Erkan U Mumcuoğlu
- Health Informatics Department, Informatics Institute, Middle East Technical University, Ankara, Turkey.
| | | | | | | |
Collapse
|
42
|
Reader variability in identifying pulmonary nodules on chest radiographs from the national lung screening trial. J Thorac Imaging 2012; 27:249-54. [PMID: 22627615 DOI: 10.1097/rti.0b013e318256951e] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
PURPOSE To measure reader variability related to the evaluation of screening chest radiographs (CXRs) for findings of primary lung cancer. MATERIALS AND METHODS From the National Lung Screening Trial (NLST), 100 cases were randomly selected from baseline CXR examinations for retrospective interpretation by 9 NLST radiologists; images with noncalcified lung nodules (NCNs) or other abnormalities suspicious for lung cancer as determined by the original NLST reader were oversampled. Agreement on the presence of pulmonary nodules and abnormalities suspicious for cancer and recommendations for follow-up were assessed by the multirater κ statistic. RESULTS The multirater κ statistic for interreader agreement on the presence of at least 1 NCN was 0.38. Rates at which readers reported the presence of at least 1 NCN ranged from 32% to 63% (mean, 41%); among 16 subjects with NCN and a cancer diagnosis within 1 year of the CXR examination, an average of 87% (range, 81% to 94%) of cases were classified as suspicious for cancer across all readers. The multirater κ for agreement on follow-up recommendations was 0.34; pairwise κ values ranged from 0.15 to 0.64 (mean, 0.36). For all subjects, readers recommended a follow-up procedure classified as high level (computed tomography, fluorodeoxyglucose-positron emission tomography, or biopsy) 42% of the time on average (range, 30% to 67%); this increased to 84% (range, 52% to 100%) when readers reported an NCN and 88% (range, 82% to 94%) for subjects with cancer. CONCLUSION Reader agreement for screening CXR interpretation and follow-up recommendations is fair overall but is high for malignant lesions.
Collapse
|
43
|
Hackx M, Bankier AA, Gevenois PA. Chronic obstructive pulmonary disease: CT quantification of airways disease. Radiology 2012; 265:34-48. [PMID: 22993219 DOI: 10.1148/radiol.12111270] [Citation(s) in RCA: 65] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Chronic obstructive pulmonary disease (COPD) is an increasing cause of morbidity and mortality worldwide and results in substantial social and economic burdens. COPD is a heterogeneous disease with both extrapulmonary and pulmonary components. The pulmonary component is characterized by an airflow limitation that is not fully reversible. In the authors' opinion, none of the currently available classifications combining airflow limitation measurements with clinical parameters is sufficient to determine the prognosis and treatment of a particular patient with COPD. With regard to the causes of airflow limitation, CT can be used to quantify the two main contributions to COPD: emphysema, and small airways disease (a narrowing of the airways). CT quantification--with subsequent COPD phenotyping--can contribute to improved patient care, assessment of COPD progression, and identification of severe COPD with increasing risk of mortality. Small airways disease can be quantified through measurements reflecting morphology, quantification of obstruction, and changes in airways walls. This article details these three approaches and concludes with perspectives and directions for further research.
Collapse
Affiliation(s)
- Maxime Hackx
- Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, 808 Route de Lennik, 1070 Brussels, Belgium
| | | | | |
Collapse
|
44
|
Gu S, Fuhrman C, Meng X, Siegfried JM, Gur D, Leader JK, Sciurba FC, Pu J. Computerized identification of airway wall in CT examinations using a 3D active surface evolution approach. Med Image Anal 2012; 17:283-96. [PMID: 23260997 DOI: 10.1016/j.media.2012.11.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2012] [Revised: 11/06/2012] [Accepted: 11/14/2012] [Indexed: 11/18/2022]
Abstract
Airway diseases (e.g., asthma, emphysema, and chronic bronchitis) are extremely common worldwide. Any morphological variations (abnormalities) of airways may physically change airflow and ultimately affect the ability of the lungs in gas exchange. In this study, we describe a novel algorithm aimed to automatically identify airway walls depicted on CT images. The underlying idea is to place a three-dimensional (3D) surface model within airway regions and thereafter allow this model to evolve (deform) under predefined external and internal forces automatically to the location where these forces reach a state of balance. By taking advantage of the geometric and the density characteristics of airway walls, the evolution procedure is performed in a distance gradient field and ultimately stops at regions with the highest contrast. The performance of this scheme was quantitatively evaluated from several perspectives. First, we assessed the accuracy of the developed scheme using a dedicated lung phantom in airway wall estimation and compared it with the traditional full-width at half maximum (FWHM) method. The phantom study shows that the developed scheme has an error ranging from 0.04 mm to 0.36 mm, which is much smaller than the FWHM method with an error ranging from 0.16 mm to 0.84 mm. Second, we compared the results obtained by the developed scheme with those manually delineated by an experienced (>30 years) radiologist on clinical chest CT examinations, showing a mean difference of 0.084 mm. In particular, the sensitivity of the scheme to different reconstruction kernels was evaluated on real chest CT examinations. For the 'lung', 'bone' and 'standard' kernels, the average airway wall thicknesses computed by the developed scheme were 1.302 mm, 1.333 mm and 1.339 mm, respectively. Our preliminary experiments showed that the scheme had a reasonable accuracy in airway wall estimation. For a clinical chest CT examination, it took around 4 min for this scheme to identify the inner and outer airway walls on a modern PC.
Collapse
Affiliation(s)
- Suicheng Gu
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | | | | | | | | | | | | | | |
Collapse
|
45
|
Lo P, van Ginneken B, Reinhardt JM, Yavarna T, de Jong PA, Irving B, Fetita C, Ortner M, Pinho R, Sijbers J, Feuerstein M, Fabijańska A, Bauer C, Beichel R, Mendoza CS, Wiemker R, Lee J, Reeves AP, Born S, Weinheimer O, van Rikxoort EM, Tschirren J, Mori K, Odry B, Naidich DP, Hartmann I, Hoffman EA, Prokop M, Pedersen JH, de Bruijne M. Extraction of airways from CT (EXACT'09). IEEE TRANSACTIONS ON MEDICAL IMAGING 2012; 31:2093-2107. [PMID: 22855226 DOI: 10.1109/tmi.2012.2209674] [Citation(s) in RCA: 99] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
This paper describes a framework for establishing a reference airway tree segmentation, which was used to quantitatively evaluate fifteen different airway tree extraction algorithms in a standardized manner. Because of the sheer difficulty involved in manually constructing a complete reference standard from scratch, we propose to construct the reference using results from all algorithms that are to be evaluated. We start by subdividing each segmented airway tree into its individual branch segments. Each branch segment is then visually scored by trained observers to determine whether or not it is a correctly segmented part of the airway tree. Finally, the reference airway trees are constructed by taking the union of all correctly extracted branch segments. Fifteen airway tree extraction algorithms from different research groups are evaluated on a diverse set of twenty chest computed tomography (CT) scans of subjects ranging from healthy volunteers to patients with severe pathologies, scanned at different sites, with different CT scanner brands, models, and scanning protocols. Three performance measures covering different aspects of segmentation quality were computed for all participating algorithms. Results from the evaluation showed that no single algorithm could extract more than an average of 74% of the total length of all branches in the reference standard, indicating substantial differences between the algorithms. A fusion scheme that obtained superior results is presented, demonstrating that there is complementary information provided by the different algorithms and there is still room for further improvements in airway segmentation algorithms.
Collapse
|
46
|
Bronchial wall thickness measurement in computed tomography: Effect of intravenous contrast agent and reconstruction kernel. Eur J Radiol 2012; 81:3606-13. [DOI: 10.1016/j.ejrad.2012.04.026] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2011] [Revised: 03/13/2012] [Accepted: 04/25/2012] [Indexed: 11/19/2022]
|
47
|
Van Tho N, Wada H, Ogawa E, Nakano Y. Recent findings in chronic obstructive pulmonary disease by using quantitative computed tomography. Respir Investig 2012; 50:78-87. [PMID: 23021766 DOI: 10.1016/j.resinv.2012.08.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2012] [Revised: 07/27/2012] [Accepted: 08/08/2012] [Indexed: 11/17/2022]
Abstract
Chronic obstructive pulmonary disease (COPD) is characterized by an incompletely reversible airflow limitation that results from a combination of airway wall remodeling and emphysematous lung destruction. Forced expiratory volume in 1s (FEV(1)) has been considered the gold standard for diagnosis, classification, and follow-up in patients with COPD, but it has certain limitations and it is still necessary to find other noninvasive modalities to complement FEV(1) to evaluate the effect of therapeutic interventions and the pathogenesis of COPD. Quantitative computed tomography (CT) has partly met this demand. The extent of emphysema and airway dimensions measured using quantitative CT are associated with morphological and functional changes and clinical symptoms in patients with COPD. Phenotyping COPD based on quantitative CT has facilitated interventional and genotypic studies. Recent advances in COPD findings with quantitative CT are discussed in this review.
Collapse
Affiliation(s)
- Nguyen Van Tho
- Division of Respiratory Medicine, Department of Medicine, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192, Japan
| | | | | | | |
Collapse
|
48
|
Pu J, Gu S, Liu S, Zhu S, Wilson D, Siegfried JM, Gur D. CT based computerized identification and analysis of human airways: a review. Med Phys 2012; 39:2603-16. [PMID: 22559631 DOI: 10.1118/1.4703901] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
As one of the most prevalent chronic disorders, airway disease is a major cause of morbidity and mortality worldwide. In order to understand its underlying mechanisms and to enable assessment of therapeutic efficacy of a variety of possible interventions, noninvasive investigation of the airways in a large number of subjects is of great research interest. Due to its high resolution in temporal and spatial domains, computed tomography (CT) has been widely used in clinical practices for studying the normal and abnormal manifestations of lung diseases, albeit there is a need to clearly demonstrate the benefits in light of the cost and radiation dose associated with CT examinations performed for the purpose of airway analysis. Whereas a single CT examination consists of a large number of images, manually identifying airway morphological characteristics and computing features to enable thorough investigations of airway and other lung diseases is very time-consuming and susceptible to errors. Hence, automated and semiautomated computerized analysis of human airways is becoming an important research area in medical imaging. A number of computerized techniques have been developed to date for the analysis of lung airways. In this review, we present a summary of the primary methods developed for computerized analysis of human airways, including airway segmentation, airway labeling, and airway morphometry, as well as a number of computer-aided clinical applications, such as virtual bronchoscopy. Both successes and underlying limitations of these approaches are discussed, while highlighting areas that may require additional work.
Collapse
Affiliation(s)
- Jiantao Pu
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
| | | | | | | | | | | | | |
Collapse
|
49
|
|
50
|
Han F, Fan L, Wang X, Li W. Sulforhodamine B restaining as a whole-cell label allows visualizing one more fluorochrome and its application in assaying protein nucleocytoplasmic distribution. Cytometry A 2012; 81:532-40. [DOI: 10.1002/cyto.a.22057] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2011] [Revised: 03/03/2012] [Accepted: 03/28/2012] [Indexed: 11/10/2022]
|