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Yehia D, Leung C, Sin DD. Clinical utilization of airway inflammatory biomarkers in the prediction and monitoring of clinical outcomes in patients with chronic obstructive pulmonary disease. Expert Rev Mol Diagn 2024; 24:409-421. [PMID: 38635513 DOI: 10.1080/14737159.2024.2344777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Accepted: 04/15/2024] [Indexed: 04/20/2024]
Abstract
INTRODUCTION Chronic obstructive pulmonary disease (COPD) accounts for 545 million people living with chronic respiratory disorders and is the third leading cause of morbidity and mortality around the world. COPD is a progressive disease, characterized by episodes of acute worsening of symptoms such as cough, dyspnea, and sputum production. AREAS COVERED Airway inflammation is a prominent feature of COPD. Chronic airway inflammation results in airway structural remodeling and emphysema. Persistent airway inflammation is a treatable trait of COPD and plays a significant role in disease development and progression. In this review, the authors summarize the current and emerging biomarkers that reveal the heterogeneity of airway inflammation subtypes, clinical outcomes, and therapeutic response in COPD. EXPERT OPINION Airway inflammation can be broadly categorized as eosinophilic (type 2 inflammation) and non-eosinophilic (non-type 2 inflammation) in COPD. Currently, blood eosinophil counts are incorporated in clinical practice guidelines to identify COPD patients who are at a higher risk of exacerbations and lung function decline, and who are likely to respond to inhaled corticosteroids. As new therapeutics are being developed for the chronic management of COPD, it is essential to identify biomarkers that will predict treatment response.
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Affiliation(s)
- Dina Yehia
- Centre for Heart Lung Innovation, St. Paul's Hospital, University of British Columbia, Vancouver, BC, Canada
| | - Clarus Leung
- Centre for Heart Lung Innovation, St. Paul's Hospital, University of British Columbia, Vancouver, BC, Canada
- Division of Respiratory Medicine, Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Don D Sin
- Centre for Heart Lung Innovation, St. Paul's Hospital, University of British Columbia, Vancouver, BC, Canada
- Division of Respiratory Medicine, Department of Medicine, University of British Columbia, Vancouver, BC, Canada
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Abe S, Yasuda M, Tobino K, Harada S, Sasano H, Tanabe Y, Sandhu Y, Takeshige T, Matsuno K, Asao T, Sueyasu T, Nishizawa S, Yoshimine K, Ko Y, Yoshimatsu Y, Tsuruno K, Ide H, Takagi H, Ito J, Nagaoka T, Harada N, Takahashi K. Usefulness of Computed Tomography for Evaluating the Effects of Bronchial Thermoplasty in Japanese Patients with Severe Asthma. J Asthma Allergy 2024; 17:325-337. [PMID: 38601883 PMCID: PMC11005926 DOI: 10.2147/jaa.s452865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 03/21/2024] [Indexed: 04/12/2024] Open
Abstract
Background Bronchial thermoplasty (BT) improves clinical outcomes and quality of life for patients with severe asthma and has shown sustained reductions in airway narrowing and air trapping in previous CT studies. However, there is a lack of a comprehensive analysis, including CT evaluation, of clinical outcomes in Japanese patients who have undergone BT for severe asthma. This study aimed to evaluate the impact of BT in Japanese asthma patients, with a focus on the CT metric "WA at Pi10" to assess airway disease. Methods Twelve patients with severe persistent asthma who underwent BT were assessed using ACQ6, AQLQ, pulmonary function tests, FeNO measurement, blood sampling, and chest CT before BT and one year after the third procedure for the upper lobes. Results The median age of the patient was 62.0 years, 7/12 (58.3%) were male, 4/12 (33.3%) used regular oral corticosteroids, and 8/12 (66.7%) received biologics. Median FEV1% was 73.6%, and median peripheral eosinophil count was 163.8/μL. After one year of BT, ACQ6 scores improved from 2.4 to 0.8 points (p = 0.007), and AQLQ scores improved from 4.3 to 5.8 points (p < 0.001). Significant improvements were also observed in asthma exacerbations, unscheduled visits due to exacerbations, FeNO, and √WA at Pi10 (p < 0.05). The baseline mucus score on the CT findings was negatively correlated with FEV1 (r = -0.688, p = 0.013) and with the maximum mid-expiratory flow rate (r = -0.631, p = 0.028), and positively correlated with the peripheral blood eosinophil count (r = -0.719, p = 0.008). Changes in √WA at Pi10 after one year were positively correlated with changes in the mucus score (r = 0.742, p = 0.007). Conclusion This study has limitations, including its single-arm observational design and the small sample size. However, BT led to a symptomatic improvement in patients with severe asthma. The validated "√WA at Pi10" metric on CT effectively evaluated the therapeutic response in Japanese asthma patients after BT.
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Affiliation(s)
- Sumiko Abe
- Department of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
| | - Mina Yasuda
- Department of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
- Department of Respiratory Medicine, Iizuka Hospital, Fukuoka, Japan
| | - Kazunori Tobino
- Department of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
- Department of Respiratory Medicine, Iizuka Hospital, Fukuoka, Japan
| | - Sonoko Harada
- Department of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
- Atopy (Allergy) Research Center, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
| | - Hitoshi Sasano
- Department of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
| | - Yuki Tanabe
- Department of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
| | - Yuuki Sandhu
- Department of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
| | - Tomohito Takeshige
- Department of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
| | - Kei Matsuno
- Department of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
| | - Tetsuhiko Asao
- Department of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
| | - Takuto Sueyasu
- Department of Respiratory Medicine, Iizuka Hospital, Fukuoka, Japan
| | - Saori Nishizawa
- Department of Respiratory Medicine, Iizuka Hospital, Fukuoka, Japan
| | - Kohei Yoshimine
- Department of Respiratory Medicine, Iizuka Hospital, Fukuoka, Japan
| | - Yuki Ko
- Department of Respiratory Medicine, Iizuka Hospital, Fukuoka, Japan
| | - Yuki Yoshimatsu
- Department of Respiratory Medicine, Iizuka Hospital, Fukuoka, Japan
| | - Kosuke Tsuruno
- Department of Respiratory Medicine, Iizuka Hospital, Fukuoka, Japan
| | - Hiromi Ide
- Department of Respiratory Medicine, Iizuka Hospital, Fukuoka, Japan
| | - Haruhi Takagi
- Department of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
| | - Jun Ito
- Department of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
| | - Tetsutaro Nagaoka
- Department of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
| | - Norihiro Harada
- Department of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
- Atopy (Allergy) Research Center, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
- Research Institute for Diseases of Old Age, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
| | - Kazuhisa Takahashi
- Department of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
- Research Institute for Diseases of Old Age, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan
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Kwon OB, Lee HU, Park HE, Choi JY, Kim JW, Lee SH, Yeo CD. Predicting Postoperative Lung Function in Patients with Lung Cancer Using Imaging Biomarkers. Diseases 2024; 12:65. [PMID: 38667523 PMCID: PMC11049658 DOI: 10.3390/diseases12040065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Revised: 03/19/2024] [Accepted: 03/22/2024] [Indexed: 04/28/2024] Open
Abstract
There have been previous studies conducted to predict postoperative lung function with pulmonary function tests (PFTs). Computing tomography (CT) can quantitatively measure small airway walls' thickness, lung volume, pulmonary vessel volume, and emphysema area, which reflect the severity of respiratory diseases. These measurements are considered imaging biomarkers. This study aimed to predict postoperative lung function with imaging biomarkers. A retrospective analysis of 79 patients with lung cancer who had undergone lung surgery was completed. Postoperative lung function measured by forced expiratory volume in one second (FEV1) was defined as an outcome. Preoperative clinico-pathological parameters and imaging biomarkers representing airway walls' thickness, severity of emphysema, total lung volume, and pulmonary vessel volume were measured quantitatively in chest CT by an automated segmentation software, AVIEW COPD. Pi1 was defined as the first percentile along the histogram of lung attenuation that represents the degree of emphysema. Wafw was defined as the airway thickness, which was calculated by the full-width at half-maximum method. Logistic and linear regressions were used to assess these variables. If the actual postoperative FEV1 was higher than the postoperative FEV1 projected by a formula, the group was considered to be preserved. Among the 79 patients, 16 of the patients were grouped as a non-preserved group, and 63 of them were grouped as a preserved group. The patients in the preserved FEV1 group had a higher vessel volume than the non-preserved group. Pi1 and Wafw were independent predictors of postoperative lung function. Imaging biomarkers can be considered significant variables in predicting postoperative lung function in patients with lung cancer.
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Affiliation(s)
- Oh-Beom Kwon
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea; (O.-B.K.); (J.-Y.C.); (J.-W.K.); (S.-H.L.)
- Department of Internal Medicine, Kangwon National University Hospital, Chuncheon 24289, Republic of Korea
| | - Hae-Ung Lee
- Coreline Soft Co., Ltd., Seoul 03991, Republic of Korea; (H.-U.L.); (H.-E.P.)
| | - Ha-Eun Park
- Coreline Soft Co., Ltd., Seoul 03991, Republic of Korea; (H.-U.L.); (H.-E.P.)
| | - Joon-Young Choi
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea; (O.-B.K.); (J.-Y.C.); (J.-W.K.); (S.-H.L.)
| | - Jin-Woo Kim
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea; (O.-B.K.); (J.-Y.C.); (J.-W.K.); (S.-H.L.)
| | - Sang-Haak Lee
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea; (O.-B.K.); (J.-Y.C.); (J.-W.K.); (S.-H.L.)
| | - Chang-Dong Yeo
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea; (O.-B.K.); (J.-Y.C.); (J.-W.K.); (S.-H.L.)
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Choe J, Choi HY, Lee SM, Oh SY, Hwang HJ, Kim N, Yun J, Lee JS, Oh YM, Yu D, Kim B, Seo JB. Evaluation of retrieval accuracy and visual similarity in content-based image retrieval of chest CT for obstructive lung disease. Sci Rep 2024; 14:4587. [PMID: 38403628 PMCID: PMC10894863 DOI: 10.1038/s41598-024-54954-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Accepted: 02/19/2024] [Indexed: 02/27/2024] Open
Abstract
The aim of our study was to assess the performance of content-based image retrieval (CBIR) for similar chest computed tomography (CT) in obstructive lung disease. This retrospective study included patients with obstructive lung disease who underwent volumetric chest CT scans. The CBIR database included 600 chest CT scans from 541 patients. To assess the system performance, follow-up chest CT scans of 50 patients were evaluated as query cases, which showed the stability of the CT findings between baseline and follow-up chest CT, as confirmed by thoracic radiologists. The CBIR system retrieved the top five similar CT scans for each query case from the database by quantifying and comparing emphysema extent and size, airway wall thickness, and peripheral pulmonary vasculatures in descending order from the database. The rates of retrieval of the same pairs of query CT scans in the top 1-5 retrievals were assessed. Two expert chest radiologists evaluated the visual similarities between the query and retrieved CT scans using a five-point scale grading system. The rates of retrieving the same pairs of query CTs were 60.0% (30/50) and 68.0% (34/50) for top-three and top-five retrievals. Radiologists rated 64.8% (95% confidence interval 58.8-70.4) of the retrieved CT scans with a visual similarity score of four or five and at least one case scored five points in 74% (74/100) of all query cases. The proposed CBIR system for obstructive lung disease integrating quantitative CT measures demonstrated potential for retrieving chest CT scans with similar imaging phenotypes. Further refinement and validation in this field would be valuable.
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Affiliation(s)
- Jooae Choe
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 86 Asanbyeongwon-Gil, Songpa-Gu, 05505, Seoul, Korea
| | - Hye Young Choi
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 86 Asanbyeongwon-Gil, Songpa-Gu, 05505, Seoul, Korea
- Department of Radiology, Kyung Hee University Hospital at Gangdong, College of Medicine Kyung, Hee University, Seoul, Korea
| | - Sang Min Lee
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 86 Asanbyeongwon-Gil, Songpa-Gu, 05505, Seoul, Korea.
| | - Sang Young Oh
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 86 Asanbyeongwon-Gil, Songpa-Gu, 05505, Seoul, Korea
| | - Hye Jeon Hwang
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 86 Asanbyeongwon-Gil, Songpa-Gu, 05505, Seoul, Korea
| | - Namkug Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 86 Asanbyeongwon-Gil, Songpa-Gu, 05505, Seoul, Korea
- Department of Convergence Medicine, Biomedical Engineering Research Center, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Jihye Yun
- Department of Convergence Medicine, Biomedical Engineering Research Center, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Jae Seung Lee
- Department of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Yeon-Mok Oh
- Department of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | | | | | - Joon Beom Seo
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 86 Asanbyeongwon-Gil, Songpa-Gu, 05505, Seoul, Korea
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Lim WH, Jeong S, Park CM. Cigarette smoking and disproportionate changes of thoracic skeletal muscles in low-dose chest computed tomography. Sci Rep 2023; 13:20110. [PMID: 37978301 PMCID: PMC10656498 DOI: 10.1038/s41598-023-46360-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 10/31/2023] [Indexed: 11/19/2023] Open
Abstract
Association between smoking intensity and the quantity and quality of thoracic skeletal muscles (TSMs) remains unexplored. Skeletal muscle index (SMI; skeletal muscle area/height2) and percentage of normal attenuation muscle area (NAMA%) were measured to represent the quantity and quality of the skeletal muscles, respectively, and quantification was performed in pectoralis muscle at aortic arch (AA-PM), TSM at carina (C-TSM), erector spinae muscle at T12 (T12-ESM), and skeletal muscle at L1 (L1-SM). Among the 258 men (median age, 62 years [IQR: 58-69]), 183 were current smokers (median smoking intensity, 40 pack-years [IQR: 30-46]). SMI and NAMA% of AA-PM significantly decreased with pack-year (β = - 0.028 and - 0.076; P < 0.001 and P = 0.021, respectively). Smoking intensity was inversely associated with NAMA% of C-TSM (β = - 0.063; P = 0.001), whereas smoking intensity showed a borderline association with SMI of C-TSM (β = - 0.023; P = 0.057). Smoking intensity was associated with the change in NAMA% of L1-SM (β = - 0.040; P = 0.027), but was not associated with SMI of L1-SM (P > 0.05). Neither NAMA% nor SMI of T12-ESM was affected by smoking intensity (P > 0.05). In conclusion, smoking intensity was associated with the change of TSMs. Its association varied according to the location of TSMs, with the most associated parts being the upper (AA-PM) and middle TSMs (C-TSM).
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Affiliation(s)
- Woo Hyeon Lim
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Suhyun Jeong
- Department of Radiology, Namwon Medical Center, 365 Chungjeong-no, Namwon, Jeollabuk-do, 55726, Republic of Korea
| | - Chang Min Park
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
- Department of Radiology, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
- Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.
- Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul, Republic of Korea.
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Bodenberger AL, Konietzke P, Weinheimer O, Wagner WL, Stiller W, Weber TF, Heussel CP, Kauczor HU, Wielpütz MO. Quantification of airway wall contrast enhancement on virtual monoenergetic images from spectral computed tomography. Eur Radiol 2023; 33:5557-5567. [PMID: 36892642 PMCID: PMC10326154 DOI: 10.1007/s00330-023-09514-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 12/31/2022] [Accepted: 02/02/2023] [Indexed: 03/10/2023]
Abstract
OBJECTIVES Quantitative computed tomography (CT) plays an increasingly important role in phenotyping airway diseases. Lung parenchyma and airway inflammation could be quantified by contrast enhancement at CT, but its investigation by multiphasic examinations is limited. We aimed to quantify lung parenchyma and airway wall attenuation in a single contrast-enhanced spectral detector CT acquisition. METHODS For this cross-sectional retrospective study, 234 lung-healthy patients who underwent spectral CT in four different contrast phases (non-enhanced, pulmonary arterial, systemic arterial, and venous phase) were recruited. Virtual monoenergetic images were reconstructed from 40-160 keV, on which attenuations of segmented lung parenchyma and airway walls combined for 5th-10th subsegmental generations were assessed in Hounsfield Units (HU) by an in-house software. The spectral attenuation curve slope between 40 and 100 keV (λHU) was calculated. RESULTS Mean lung density was higher at 40 keV compared to that at 100 keV in all groups (p < 0.001). λHU of lung attenuation was significantly higher in the systemic (1.7 HU/keV) and pulmonary arterial phase (1.3 HU/keV) compared to that in the venous phase (0.5 HU/keV) and non-enhanced (0.2 HU/keV) spectral CT (p < 0.001). Wall thickness and wall attenuation were higher at 40 keV compared to those at 100 keV for the pulmonary and systemic arterial phase (p ≤ 0.001). λHU for wall attenuation was significantly higher in the pulmonary arterial (1.8 HU/keV) and systemic arterial (2.0 HU/keV) compared to that in the venous (0.7 HU/keV) and non-enhanced (0.3 HU/keV) phase (p ≤ 0.002). CONCLUSIONS Spectral CT may quantify lung parenchyma and airway wall enhancement with a single contrast phase acquisition, and may separate arterial and venous enhancement. Further studies are warranted to analyze spectral CT for inflammatory airway diseases. KEY POINTS • Spectral CT may quantify lung parenchyma and airway wall enhancement with a single contrast phase acquisition. • Spectral CT may separate arterial and venous enhancement of lung parenchyma and airway wall. • The contrast enhancement can be quantified by calculating the spectral attenuation curve slope from virtual monoenergetic images.
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Affiliation(s)
- Arndt Lukas Bodenberger
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120, Heidelberg, Germany
| | - Philip Konietzke
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology With Nuclear Medicine, Thoraxklinik at University of Heidelberg, Röntgenstraße 1, 69126, Heidelberg, Germany
| | - Oliver Weinheimer
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology With Nuclear Medicine, Thoraxklinik at University of Heidelberg, Röntgenstraße 1, 69126, Heidelberg, Germany
| | - Willi Linus Wagner
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology With Nuclear Medicine, Thoraxklinik at University of Heidelberg, Röntgenstraße 1, 69126, Heidelberg, Germany
| | - Wolfram Stiller
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology With Nuclear Medicine, Thoraxklinik at University of Heidelberg, Röntgenstraße 1, 69126, Heidelberg, Germany
| | - Tim Frederik Weber
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology With Nuclear Medicine, Thoraxklinik at University of Heidelberg, Röntgenstraße 1, 69126, Heidelberg, Germany
| | - Claus Peter Heussel
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology With Nuclear Medicine, Thoraxklinik at University of Heidelberg, Röntgenstraße 1, 69126, Heidelberg, Germany
| | - Hans-Ulrich Kauczor
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology With Nuclear Medicine, Thoraxklinik at University of Heidelberg, Röntgenstraße 1, 69126, Heidelberg, Germany
| | - Mark Oliver Wielpütz
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany.
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120, Heidelberg, Germany.
- Department of Diagnostic and Interventional Radiology With Nuclear Medicine, Thoraxklinik at University of Heidelberg, Röntgenstraße 1, 69126, Heidelberg, Germany.
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Konietzke P, Brunner C, Konietzke M, Wagner WL, Weinheimer O, Heußel CP, Herth FJF, Trudzinski F, Kauczor HU, Wielpütz MO. GOLD stage-specific phenotyping of emphysema and airway disease using quantitative computed tomography. Front Med (Lausanne) 2023; 10:1184784. [PMID: 37534319 PMCID: PMC10393128 DOI: 10.3389/fmed.2023.1184784] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Accepted: 06/22/2023] [Indexed: 08/04/2023] Open
Abstract
Background In chronic obstructive pulmonary disease (COPD) abnormal lung function is related to emphysema and airway obstruction, but their relative contribution in each GOLD-stage is not fully understood. In this study, we used quantitative computed tomography (QCT) parameters for phenotyping of emphysema and airway abnormalities, and to investigate the relative contribution of QCT emphysema and airway parameters to airflow limitation specifically in each GOLD stage. Methods Non-contrast computed tomography (CT) of 492 patients with COPD former GOLD 0 COPD and COPD stages GOLD 1-4 were evaluated using fully automated software for quantitative CT. Total lung volume (TLV), emphysema index (EI), mean lung density (MLD), and airway wall thickness (WT), total diameter (TD), lumen area (LA), and wall percentage (WP) were calculated for the entire lung, as well as for all lung lobes separately. Results from the 3rd-8th airway generation were aggregated (WT3-8, TD3-8, LA3-8, WP3-8). All subjects underwent whole-body plethysmography (FEV1%pred, VC, RV, TLC). Results EI was higher with increasing GOLD stages with 1.0 ± 1.8% in GOLD 0, 4.5 ± 9.9% in GOLD 1, 19.4 ± 15.8% in GOLD 2, 32.7 ± 13.4% in GOLD 3 and 41.4 ± 10.0% in GOLD 4 subjects (p < 0.001). WP3-8 showed no essential differences between GOLD 0 and GOLD 1, tended to be higher in GOLD 2 with 52.4 ± 7.2%, and was lower in GOLD 4 with 50.6 ± 5.9% (p = 0.010 - p = 0.960). In the upper lobes WP3-8 showed no significant differences between the GOLD stages (p = 0.824), while in the lower lobes the lowest WP3-8 was found in GOLD 0/1 with 49.9 ± 6.5%, while higher values were detected in GOLD 2 with 51.9 ± 6.4% and in GOLD 3/4 with 51.0 ± 6.0% (p < 0.05). In a multilinear regression analysis, the dependent variable FEV1%pred can be predicted by a combination of both the independent variables EI (p < 0.001) and WP3-8 (p < 0.001). Conclusion QCT parameters showed a significant increase of emphysema from GOLD 0-4 COPD. Airway changes showed a different spatial pattern with higher values of relative wall thickness in the lower lobes until GOLD 2 and subsequent lower values in GOLD3/4, whereas there were no significant differences in the upper lobes. Both, EI and WP5-8 are independently correlated with lung function decline.
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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), University of Heidelberg, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Christian Brunner
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Marilisa 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), University of Heidelberg, Heidelberg, Germany
| | - Willi Linus 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), University of Heidelberg, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - 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), University of Heidelberg, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Claus Peter 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), University of Heidelberg, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Felix J. F. Herth
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
- Department of Pulmonology, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Franziska Trudzinski
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
- Department of Pulmonology, 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), University of Heidelberg, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Mark Oliver 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), University of Heidelberg, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
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8
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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.
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9
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Hsia CCW, Bates JHT, Driehuys B, Fain SB, Goldin JG, Hoffman EA, Hogg JC, Levin DL, Lynch DA, Ochs M, Parraga G, Prisk GK, Smith BM, Tawhai M, Vidal Melo MF, Woods JC, Hopkins SR. Quantitative Imaging Metrics for the Assessment of Pulmonary Pathophysiology: An Official American Thoracic Society and Fleischner Society Joint Workshop Report. Ann Am Thorac Soc 2023; 20:161-195. [PMID: 36723475 PMCID: PMC9989862 DOI: 10.1513/annalsats.202211-915st] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
Multiple thoracic imaging modalities have been developed to link structure to function in the diagnosis and monitoring of lung disease. Volumetric computed tomography (CT) renders three-dimensional maps of lung structures and may be combined with positron emission tomography (PET) to obtain dynamic physiological data. Magnetic resonance imaging (MRI) using ultrashort-echo time (UTE) sequences has improved signal detection from lung parenchyma; contrast agents are used to deduce airway function, ventilation-perfusion-diffusion, and mechanics. Proton MRI can measure regional ventilation-perfusion ratio. Quantitative imaging (QI)-derived endpoints have been developed to identify structure-function phenotypes, including air-blood-tissue volume partition, bronchovascular remodeling, emphysema, fibrosis, and textural patterns indicating architectural alteration. Coregistered landmarks on paired images obtained at different lung volumes are used to infer airway caliber, air trapping, gas and blood transport, compliance, and deformation. This document summarizes fundamental "good practice" stereological principles in QI study design and analysis; evaluates technical capabilities and limitations of common imaging modalities; and assesses major QI endpoints regarding underlying assumptions and limitations, ability to detect and stratify heterogeneous, overlapping pathophysiology, and monitor disease progression and therapeutic response, correlated with and complementary to, functional indices. The goal is to promote unbiased quantification and interpretation of in vivo imaging data, compare metrics obtained using different QI modalities to ensure accurate and reproducible metric derivation, and avoid misrepresentation of inferred physiological processes. The role of imaging-based computational modeling in advancing these goals is emphasized. Fundamental principles outlined herein are critical for all forms of QI irrespective of acquisition modality or disease entity.
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10
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Yang D, Kim JW, Jeong H, Kim MS, Lim CW, Lee K, Kim B. Effects of maternal cigarette smoke exposure on the progression of nonalcoholic steatohepatitis in offspring mice. Toxicol Res 2023; 39:91-103. [PMID: 36726830 PMCID: PMC9839905 DOI: 10.1007/s43188-022-00153-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 08/01/2022] [Accepted: 08/22/2022] [Indexed: 02/04/2023] Open
Abstract
Cigarette smoke (CS) is a dominant carcinogenic agent in a variety of human cancers. CS exposure during pregnancy can adversely affect the fetus. Non-alcoholic fatty liver disease (NAFLD) is considered as a hepatic manifestation of a metabolic disorder, and ranges from simple steatosis to cirrhosis leading to hepatocellular carcinoma. Non-alcoholic steatohepatitis (NASH) is a more severe phase of NAFLD. Recently, there is increasing apprehension about the CS-related chronic liver diseases. Therefore, we examined whether maternal CS exposure could affect the pathogenesis of NASH in offspring. Mainstream CS (MSCS) was exposed to pregnant C57BL/6 mice via nose-only inhalation for 2 h/day, 5 days/week for 2 weeks from day 6 to 17 of gestation at 0, 300, or 600 μg/L. Three-week-old male offspring mice were fed methionine and choline-supplemented (MCS) diet or methionine and choline-deficient including high-fat (MCDHF) diet for 6 weeks to induce NASH. Maternal MSCS exposure increased the severity of NASH by increasing serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels, hepatic total cholesterol (TC) and triglyceride (TG) levels, pro-inflammation, fibrosis, and steatosis in offspring mice. Especially, maternal MSCS exposure significantly downregulated the phosphorylation of AMP-activated protein kinase (AMPK) in MCDHF diet-fed offspring mice. Subsequently, the protein levels of sterol regulatory element-binding protein (SREBP)-1c and stearoyl-CoA desaturase-1 (SCD1) were upregulated by maternal MSCS exposure. In conclusion, maternal MSCS exposure exacerbates the progression of NASH by modulating lipogenesis on offspring mice. Supplementary Information The online version contains supplementary material available at 10.1007/s43188-022-00153-1.
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Affiliation(s)
- Daram Yang
- Biosafety Research Institute and Laboratory of Veterinary Pathology, College of Veterinary Medicine, Jeonbuk National University, 79 Gobong-Ro, Iksan-Si, Jeollabuk-Do 54596 Republic of Korea
| | - Jong Won Kim
- Biosafety Research Institute and Laboratory of Veterinary Pathology, College of Veterinary Medicine, Jeonbuk National University, 79 Gobong-Ro, Iksan-Si, Jeollabuk-Do 54596 Republic of Korea
| | - Hyuneui Jeong
- Biosafety Research Institute and Laboratory of Veterinary Pathology, College of Veterinary Medicine, Jeonbuk National University, 79 Gobong-Ro, Iksan-Si, Jeollabuk-Do 54596 Republic of Korea
| | - Min Seok Kim
- Inhalation Toxicology Center, Jeonbuk Department of Inhalation Research, Korea Institute of Toxicology, 30, Baekak 1-Gil, Jeongeup, 56212 Republic of Korea
| | - Chae Woong Lim
- Biosafety Research Institute and Laboratory of Veterinary Pathology, College of Veterinary Medicine, Jeonbuk National University, 79 Gobong-Ro, Iksan-Si, Jeollabuk-Do 54596 Republic of Korea
| | - Kyuhong Lee
- Inhalation Toxicology Center, Jeonbuk Department of Inhalation Research, Korea Institute of Toxicology, 30, Baekak 1-Gil, Jeongeup, 56212 Republic of Korea
| | - Bumseok Kim
- Biosafety Research Institute and Laboratory of Veterinary Pathology, College of Veterinary Medicine, Jeonbuk National University, 79 Gobong-Ro, Iksan-Si, Jeollabuk-Do 54596 Republic of Korea
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11
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Kahnert K, Jörres RA, Kauczor HU, Alter P, Trudzinski FC, Herth F, Jobst B, Weinheimer O, Nauck S, Mertsch P, Kauffmann-Guerrero D, Behr J, Bals R, Watz H, Rabe KF, Welte T, Vogelmeier CF, Biederer J. Standardized airway wall thickness Pi10 from routine CT scans of COPD patients as imaging biomarker for disease severity, lung function decline, and mortality. Ther Adv Respir Dis 2023; 17:17534666221148663. [PMID: 36718763 PMCID: PMC9896094 DOI: 10.1177/17534666221148663] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Chest computed tomography (CT) is increasingly used for phenotyping and monitoring of patients with COPD. The aim of this work was to evaluate the association of Pi10 as a measure of standardized airway wall thickness on CT with exacerbations, mortality, and response to triple therapy. METHODS Patients of GOLD grades 1-4 of the COSYCONET cohort with prospective CT scans were included. Pi10 was automatically computed and analyzed for its relationship to COPD severity, comorbidities, lung function, respiratory therapy, and mortality over a 6-year period, using univariate and multivariate comparisons. RESULTS We included n = 433 patients (61%male). Pi10 was dependent on both GOLD grades 1-4 (p = 0.009) and GOLD groups A-D (p = 0.008); it was particularly elevated in group D, and ROC analysis yielded a cut-off of 0.26 cm. Higher Pi10 was associated to lower FEV1 % predicted and higher RV/TLC, moreover the annual changes of lung function parameters (p < 0.05), as well as to an airway-dominated phenotype and a history of myocardial infarction (p = 0.001). These associations were confirmed in multivariate analyses. Pi10 was lower in patients receiving triple therapy, in particular in patients of GOLD groups C and D. Pi10 was also a significant predictor for mortality (p = 0.006), even after including multiple other predictors. CONCLUSION In summary, Pi10 was found to be predictive for the course of the disease in COPD, in particular mortality. The fact that Pi10 was lower in patients with severe COPD receiving triple therapy might hint toward additional effects of this functional therapy on airway remodeling. REGISTRATION ClinicalTrials.gov, Identifier: NCT01245933.
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Affiliation(s)
- Kathrin Kahnert
- Department of Medicine V, Comprehensive Pneumology Center, Member of the German Center for Lung Research (DZL), University Hospital, LMU Munich, Ziemssenstr. 5, Munich 80336, Germany
| | - Rudolf A Jörres
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Ludwig-Maximilians-Universität München, Munich, Germany
| | - Hans-Ulrich Kauczor
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany.,Translational Lung Research Centre Heidelberg (TLRC), Member of the German Center for Lung Research, Heidelberg, Germany
| | - Peter Alter
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps-University Marburg, Member of the German Center for Lung Research (DZL), Marburg, Germany
| | - Franziska C Trudzinski
- Thoraxklinik-Heidelberg gGmbH, Translational Lung Research Centre.,Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany
| | - Felix Herth
- Thoraxklinik-Heidelberg gGmbH, Translational Lung Research Centre.,Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany
| | - Bertram Jobst
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany.,Translational Lung Research Centre Heidelberg (TLRC), Member of the German Center for Lung Research, Heidelberg, Germany
| | - Oliver Weinheimer
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany.,Translational Lung Research Centre Heidelberg (TLRC), Member of the German Center for Lung Research, Heidelberg, Germany
| | - Sebastian Nauck
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany.,Translational Lung Research Centre Heidelberg (TLRC), Member of the German Center for Lung Research, Heidelberg, Germany
| | - Pontus Mertsch
- Department of Medicine V, Comprehensive Pneumology Center, Member of the German Center for Lung Research (DZL), University Hospital, LMU Munich, Munich, Germany
| | - Diego Kauffmann-Guerrero
- Department of Medicine V, Comprehensive Pneumology Center, Member of the German Center for Lung Research (DZL), University Hospital, LMU Munich, Munich, Germany
| | - Jürgen Behr
- Department of Medicine V, Comprehensive Pneumology Center, Member of the German Center for Lung Research (DZL), University Hospital, LMU Munich, Munich, Germany
| | - Robert Bals
- Department of Internal Medicine V - Pulmonology, Allergology, Respiratory Intensive Care Medicine, Saarland University Hospital, Homburg, Germany.,Helmholtz Institute for Pharmaceutical Research Saarland (HIPS), Helmholtz Centre for Infection Research (HZI), Saarland University Campus, Saarbrücken, Germany
| | - Henrik Watz
- Pulmonary Research Institute at LungenClinic Grosshansdorf, Airway Research Center North (ARCN), Member of the German Center for Lung Research (DZL), Grosshansdorf, Germany
| | - Klaus F Rabe
- Lung Clinic Grosshansdorf, Airway Research Center (ARCN), Grosshansdorf, German.,Faculty of Medicine, Christian-Albrechts-Universität zu Kiel, Kiel, Germany
| | - Tobias Welte
- Department of Pneumology, Hannover Medical School, Hannover, Germany
| | - Claus F Vogelmeier
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps-University Marburg, Member of the German Center for Lung Research (DZL), Marburg, Germany
| | - Jürgen Biederer
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany.,Translational Lung Research Centre Heidelberg (TLRC), Member of the German Center for Lung Research, Heidelberg, Germany.,Faculty of Medicine, Christian-Albrechts-Universität zu Kiel, Kiel, Germany.,University of Latvia, Faculty of Medicine, Raina bulvaris 19, Riga, LV-1586 Latvia
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12
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Quantitative CT analysis of lung parenchyma to improve malignancy risk estimation in incidental pulmonary nodules. Eur Radiol 2022; 33:3908-3917. [PMID: 36538071 PMCID: PMC10181968 DOI: 10.1007/s00330-022-09334-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 11/18/2022] [Accepted: 11/29/2022] [Indexed: 12/24/2022]
Abstract
Abstract
Objectives
To assess the value of quantitative computed tomography (QCT) of the whole lung and nodule-bearing lobe regarding pulmonary nodule malignancy risk estimation.
Methods
A total of 251 subjects (median [IQR] age, 65 (57–73) years; 37% females) with pulmonary nodules on non-enhanced thin-section CT were retrospectively included. Twenty percent of the nodules were malignant, the remainder benign either histologically or at least 1-year follow-up. CT scans were subjected to in-house software, computing parameters such as mean lung density (MLD) or peripheral emphysema index (pEI). QCT variable selection was performed using logistic regression; selected variables were integrated into the Mayo Clinic and the parsimonious Brock Model.
Results
Whole-lung analysis revealed differences between benign vs. malignant nodule groups in several parameters, e.g. the MLD (−766 vs. −790 HU) or the pEI (40.1 vs. 44.7 %). The proposed QCT model had an area-under-the-curve (AUC) of 0.69 (95%-CI, 0.62−0.76) based on all available data. After integrating MLD and pEI into the Mayo Clinic and Brock Model, the AUC of both clinical models improved (AUC, 0.91 to 0.93 and 0.88 to 0.91, respectively). The lobe-specific analysis revealed that the nodule-bearing lobes had less emphysema than the rest of the lung regarding benign (EI, 0.5 vs. 0.7 %; p < 0.001) and malignant nodules (EI, 1.2 vs. 1.7 %; p = 0.001).
Conclusions
Nodules in subjects with higher whole-lung metrics of emphysema and less fibrosis are more likely to be malignant; hereby the nodule-bearing lobes have less emphysema. QCT variables could improve the risk assessment of incidental pulmonary nodules.
Key Points
• Nodules in subjects with higher whole-lung metrics of emphysema and less fibrosis are more likely to be malignant.
• The nodule-bearing lobes have less emphysema compared to the rest of the lung.
• QCT variables could improve the risk assessment of incidental pulmonary nodules.
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13
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Bhatt SP, Bodduluri S, Nakhmani A, Kim YI, Reinhardt JM, Hoffman EA, Motahari A, Wilson CG, Humphries SM, Regan EA, DeMeo DL. Sex Differences in Airways at Chest CT: Results from the COPDGene Cohort. Radiology 2022; 305:699-708. [PMID: 35916677 PMCID: PMC9713451 DOI: 10.1148/radiol.212985] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 05/10/2022] [Accepted: 05/24/2022] [Indexed: 11/11/2022]
Abstract
Background The prevalence of chronic obstructive pulmonary disease (COPD) in women is fast approaching that in men, and women experience greater symptom burden. Although sex differences in emphysema have been reported, differences in airways have not been systematically characterized. Purpose To evaluate whether structural differences in airways may underlie some of the sex differences in COPD prevalence and clinical outcomes. Materials and Methods In a secondary analyses of a multicenter study of never-, current-, and former-smokers enrolled from January 2008 to June 2011 and followed up longitudinally until November 2020, airway disease on CT images was quantified using seven metrics: airway wall thickness, wall area percent, and square root of the wall thickness of a hypothetical airway with internal perimeter of 10 mm (referred to as Pi10) for airway wall; and lumen diameter, airway volume, total airway count, and airway fractal dimension for airway lumen. Least-squares mean values for each airway metric were calculated and adjusted for age, height, ethnicity, body mass index, pack-years of smoking, current smoking status, total lung capacity, display field of view, and scanner type. In ever-smokers, associations were tested between each airway metric and postbronchodilator forced expiratory volume in 1 second (FEV1)-to-forced vital capacity (FVC) ratio, modified Medical Research Council dyspnea scale, St George's Respiratory Questionnaire score, and 6-minute walk distance. Multivariable Cox proportional hazards models were created to evaluate the sex-specific association between each airway metric and mortality. Results In never-smokers (n = 420), men had thicker airway walls than women as quantified on CT images for segmental airway wall area percentage (least-squares mean, 47.68 ± 0.61 [standard error] vs 45.78 ± 0.55; difference, -1.90; P = .02), whereas airway lumen dimensions were lower in women than men after accounting for height and total lung capacity (segmental lumen diameter, 8.05 mm ± 0.14 vs 9.05 mm ± 0.16; difference, -1.00 mm; P < .001). In ever-smokers (n = 9363), men had greater segmental airway wall area percentage (least-squares mean, 52.19 ± 0.16 vs 48.89 ± 0.18; difference, -3.30; P < .001), whereas women had narrower segmental lumen diameter (7.80 mm ± 0.05 vs 8.69 mm ± 0.04; difference, -0.89; P < .001). A unit change in each of the airway metrics (higher wall or lower lumen measure) resulted in lower FEV1-to-FVC ratio, more dyspnea, poorer respiratory quality of life, lower 6-minute walk distance, and worse survival in women compared with men (all P < .01). Conclusion Airway lumen sizes quantified at chest CT were smaller in women than in men after accounting for height and lung size, and these lower baseline values in women conferred lower reserves against respiratory morbidity and mortality for equivalent changes compared with men. © RSNA, 2022 Online supplemental material is available for this article.
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Affiliation(s)
- Surya P. Bhatt
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Sandeep Bodduluri
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Arie Nakhmani
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Young-il Kim
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Joseph M. Reinhardt
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Eric A. Hoffman
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Amin Motahari
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Carla G. Wilson
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Stephen M. Humphries
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Elizabeth A. Regan
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Dawn L. DeMeo
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
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14
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Palm V, Norajitra T, von Stackelberg O, Heussel CP, Skornitzke S, Weinheimer O, Kopytova T, Klein A, Almeida SD, Baumgartner M, Bounias D, Scherer J, Kades K, Gao H, Jäger P, Nolden M, Tong E, Eckl K, Nattenmüller J, Nonnenmacher T, Naas O, Reuter J, Bischoff A, Kroschke J, Rengier F, Schlamp K, Debic M, Kauczor HU, Maier-Hein K, Wielpütz MO. AI-Supported Comprehensive Detection and Quantification of Biomarkers of Subclinical Widespread Diseases at Chest CT for Preventive Medicine. Healthcare (Basel) 2022; 10:2166. [PMID: 36360507 PMCID: PMC9690402 DOI: 10.3390/healthcare10112166] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 10/26/2022] [Accepted: 10/27/2022] [Indexed: 08/12/2023] Open
Abstract
Automated image analysis plays an increasing role in radiology in detecting and quantifying image features outside of the perception of human eyes. Common AI-based approaches address a single medical problem, although patients often present with multiple interacting, frequently subclinical medical conditions. A holistic imaging diagnostics tool based on artificial intelligence (AI) has the potential of providing an overview of multi-system comorbidities within a single workflow. An interdisciplinary, multicentric team of medical experts and computer scientists designed a pipeline, comprising AI-based tools for the automated detection, quantification and characterization of the most common pulmonary, metabolic, cardiovascular and musculoskeletal comorbidities in chest computed tomography (CT). To provide a comprehensive evaluation of each patient, a multidimensional workflow was established with algorithms operating synchronously on a decentralized Joined Imaging Platform (JIP). The results of each patient are transferred to a dedicated database and summarized as a structured report with reference to available reference values and annotated sample images of detected pathologies. Hence, this tool allows for the comprehensive, large-scale analysis of imaging-biomarkers of comorbidities in chest CT, first in science and then in clinical routine. Moreover, this tool accommodates the quantitative analysis and classification of each pathology, providing integral diagnostic and prognostic value, and subsequently leading to improved preventive patient care and further possibilities for future studies.
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Affiliation(s)
- Viktoria Palm
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany
| | - Tobias Norajitra
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
- Pattern Analysis and Learning Group, Department of Radiation Oncology, University Hospital of Heidelberg, Im Neuenheimer Feld 672, 69120 Heidelberg, Germany
| | - Oyunbileg von Stackelberg
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany
| | - Claus P. Heussel
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany
| | - Stephan Skornitzke
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany
| | - Oliver Weinheimer
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany
| | - Taisiya Kopytova
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
| | - Andre Klein
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
- Medical Faculty, University of Heidelberg, Im Neuenheimer Feld 672, 69120 Heidelberg, Germany
| | - Silvia D. Almeida
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
- Medical Faculty, University of Heidelberg, Im Neuenheimer Feld 672, 69120 Heidelberg, Germany
| | - Michael Baumgartner
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
| | - Dimitrios Bounias
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
- Medical Faculty, University of Heidelberg, Im Neuenheimer Feld 672, 69120 Heidelberg, Germany
| | - Jonas Scherer
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
- Medical Faculty, University of Heidelberg, Im Neuenheimer Feld 672, 69120 Heidelberg, Germany
| | - Klaus Kades
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
| | - Hanno Gao
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
| | - Paul Jäger
- Interactive Machine Learning Research Group, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
| | - Marco Nolden
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
- Pattern Analysis and Learning Group, Department of Radiation Oncology, University Hospital of Heidelberg, Im Neuenheimer Feld 672, 69120 Heidelberg, Germany
| | - Elizabeth Tong
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany
| | - Kira Eckl
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany
| | - Johanna Nattenmüller
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology, Medical Center, Faculty of Medicine Freiburg, University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, Germany
| | - Tobias Nonnenmacher
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany
| | - Omar Naas
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany
| | - Julia Reuter
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany
| | - Arved Bischoff
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany
| | - Jonas Kroschke
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany
| | - Fabian Rengier
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany
| | - Kai Schlamp
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany
| | - Manuel Debic
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany
| | - Hans-Ulrich Kauczor
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany
| | - Klaus Maier-Hein
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
- Pattern Analysis and Learning Group, Department of Radiation Oncology, University Hospital of Heidelberg, Im Neuenheimer Feld 672, 69120 Heidelberg, Germany
| | - Mark O. Wielpütz
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany
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15
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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: 3] [Impact Index Per Article: 1.5] [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.
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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
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16
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Do TD, Skornitzke S, Merle U, Kittel M, Hofbaur S, Melzig C, Kauczor HU, Wielpütz MO, Weinheimer O. COVID-19 pneumonia: Prediction of patient outcome by CT-based quantitative lung parenchyma analysis combined with laboratory parameters. PLoS One 2022; 17:e0271787. [PMID: 35905122 PMCID: PMC9337660 DOI: 10.1371/journal.pone.0271787] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 07/07/2022] [Indexed: 12/23/2022] Open
Abstract
Objectives To evaluate the prognostic value of fully automatic lung quantification based on spectral computed tomography (CT) and laboratory parameters for combined outcome prediction in COVID-19 pneumonia. Methods CT images of 53 hospitalized COVID-19 patients including virtual monochromatic reconstructions at 40-140keV were analyzed using a fully automated software system. Quantitative CT (QCT) parameters including mean and percentiles of lung density, fibrosis index (FIBI-700, defined as the percentage of segmented lung voxels ≥-700 HU), quantification of ground-glass opacities and well-aerated lung areas were analyzed. QCT parameters were correlated to laboratory and patient outcome parameters (hospitalization, days on intensive care unit, invasive and non-invasive ventilation). Results Best correlations were found for laboratory parameters LDH (r = 0.54), CRP (r = 0.49), Procalcitonin (r = 0.37) and partial pressure of oxygen (r = 0.35) with the QCT parameter 75th percentile of lung density. LDH, Procalcitonin, 75th percentile of lung density and FIBI-700 were the strongest independent predictors of patients’ outcome in terms of days of invasive ventilation. The combination of LDH and Procalcitonin with either 75th percentile of lung density or FIBI-700 achieved a r2 of 0.84 and 1.0 as well as an area under the receiver operating characteristic curve (AUC) of 0.99 and 1.0 for the prediction of the need of invasive ventilation. Conclusions QCT parameters in combination with laboratory parameters could deliver a feasible prognostic tool for the prediction of invasive ventilation in patients with COVID-19 pneumonia.
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Affiliation(s)
- Thuy D. Do
- Clinic for Diagnostic and Interventional Radiology (DIR), University Hospital Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
| | - Stephan Skornitzke
- Clinic for Diagnostic and Interventional Radiology (DIR), University Hospital Heidelberg, Heidelberg, Germany
| | - Uta Merle
- Department of Internal Medicine IV (Gastroenterology and Infectious Disease), University Hospital Heidelberg, Heidelberg, Germany
| | - Maximilian Kittel
- Institute for Clinical Chemistry, Medical Faculty Mannheim of Heidelberg University, Mannheim, Germany
| | - Stefan Hofbaur
- Clinic for Gastroenterology and Nephrology, Landshut Hospital, Landshut, Germany
| | - Claudius Melzig
- Clinic for Diagnostic and Interventional Radiology (DIR), University Hospital Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
| | - Hans-Ulrich Kauczor
- Clinic for Diagnostic and Interventional Radiology (DIR), University Hospital 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, University Hospital Heidelberg, Heidelberg, Germany
| | - Mark O. Wielpütz
- Clinic for Diagnostic and Interventional Radiology (DIR), University Hospital 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, University Hospital Heidelberg, Heidelberg, Germany
| | - Oliver Weinheimer
- Clinic for Diagnostic and Interventional Radiology (DIR), University Hospital Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
- * E-mail:
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17
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Suzuki Y, Kitaguchi Y, Ueno F, Droma Y, Goto N, Kinjo T, Wada Y, Yasuo M, Hanaoka M. Associations Between Morphological Phenotypes of COPD and Clinical Characteristics in Surgically Resected Patients with COPD and Concomitant Lung Cancer. Int J Chron Obstruct Pulmon Dis 2022; 17:1443-1452. [PMID: 35761955 PMCID: PMC9233490 DOI: 10.2147/copd.s366265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 05/22/2022] [Indexed: 11/23/2022] Open
Abstract
Purpose The associations between morphological phenotypes of COPD based on the chest computed tomography (CT) findings and clinical characteristics in surgically resected patients with COPD and concomitant lung cancer are unclear. The purpose of this study was to clarify the differences in clinical characteristics and prognosis among morphological phenotypes based on the chest CT findings in these patients. Patients and Methods We retrospectively reviewed the medical records of 132 patients with COPD and concomitant lung cancer who had undergone pulmonary resection for primary lung cancer. According to the presence of emphysema and bronchial wall thickness on chest CT, patients were classified into three phenotypes: non-emphysema phenotype, emphysema phenotype, or mixed phenotype. Results The mixed phenotype was associated with poorer performance status, higher score on the modified British Medical Research Council (mMRC) dyspnea scale, higher residual volume in pulmonary function, and higher proportion of squamous cell carcinoma than the other phenotypes. Univariate and multivariate Cox proportional hazards regression analyses showed that the extent of emphysema on chest CT, presented as a low attenuation area (LAA) score, was an independent determinant that predicted prognosis. In the Kaplan-Meier analysis, the Log rank test showed significant differences in survival between the non-emphysema and mixed phenotypes, and between the emphysema and mixed phenotypes. Conclusion The cross-sectional pre-operative LAA score can predict the prognosis in surgically resected patients with COPD and concomitant lung cancer. The COPD phenotype with both emphysema and bronchial wall thickness on chest CT was associated with poorer performance status, greater extent of dyspnea, greater impairment of pulmonary function, and worse prognosis.
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Affiliation(s)
- Yusuke Suzuki
- First Department of Internal Medicine, Shinshu University School of Medicine, Matsumoto, Nagano, Japan
| | - Yoshiaki Kitaguchi
- First Department of Internal Medicine, Shinshu University School of Medicine, Matsumoto, Nagano, Japan
| | - Fumika Ueno
- First Department of Internal Medicine, Shinshu University School of Medicine, Matsumoto, Nagano, Japan
| | - Yunden Droma
- First Department of Internal Medicine, Shinshu University School of Medicine, Matsumoto, Nagano, Japan
| | - Norihiko Goto
- First Department of Internal Medicine, Shinshu University School of Medicine, Matsumoto, Nagano, Japan
| | - Takumi Kinjo
- First Department of Internal Medicine, Shinshu University School of Medicine, Matsumoto, Nagano, Japan
| | - Yosuke Wada
- First Department of Internal Medicine, Shinshu University School of Medicine, Matsumoto, Nagano, Japan
| | - Masanori Yasuo
- Departments of Clinical Laboratory Sciences, Shinshu University School of Health Sciences, Matsumoto, Nagano, Japan
| | - Masayuki Hanaoka
- First Department of Internal Medicine, Shinshu University School of Medicine, Matsumoto, Nagano, Japan
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18
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Zhang L, Jiang B, Wisselink HJ, Vliegenthart R, Xie X. COPD identification and grading based on deep learning of lung parenchyma and bronchial wall in chest CT images. Br J Radiol 2022; 95:20210637. [PMID: 35143286 PMCID: PMC10993953 DOI: 10.1259/bjr.20210637] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 01/20/2022] [Accepted: 02/01/2022] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVE Chest CT can display the main pathogenic factors of chronic obstructive pulmonary disease (COPD), emphysema and airway wall remodeling. This study aims to establish deep convolutional neural network (CNN) models using these two imaging markers to diagnose and grade COPD. METHODS Subjects who underwent chest CT and pulmonary function test (PFT) from one hospital (n = 373) were retrospectively included as the training cohort, and subjects from another hospital (n = 226) were used as the external test cohort. According to the PFT results, all subjects were labeled as Global Initiative for Chronic Obstructive Lung Disease (GOLD) Grade 1, 2, 3, 4 or normal. Two DenseNet-201 CNNs were trained using CT images of lung parenchyma and bronchial wall to generate two corresponding confidence levels to indicate the possibility of COPD, then combined with logistic regression analysis. Quantitative CT was used for comparison. RESULTS In the test cohort, CNN achieved an area under the curve of 0.899 (95%CI: 0.853-0.935) to determine the existence of COPD, and an accuracy of 81.7% (76.2-86.7%), which was significantly higher than the accuracy 68.1% (61.6%-74.2%) using quantitative CT method (p < 0.05). For three-way (normal, GOLD 1-2, and GOLD 3-4) and five-way (normal, GOLD 1, 2, 3, and 4) classifications, CNN reached accuracies of 77.4 and 67.9%, respectively. CONCLUSION CNN can identify emphysema and airway wall remodeling on CT images to infer lung function and determine the existence and severity of COPD. It provides an alternative way to detect COPD using the extensively available chest CT. ADVANCES IN KNOWLEDGE CNN can identify the main pathological changes of COPD (emphysema and airway wall remodeling) based on CT images, to infer lung function and determine the existence and severity of COPD. CNN reached an area under the curve of 0.853 to determine the existence of COPD in the external test cohort. The CNN approach provides an alternative and effective way for early detection of COPD using extensively used chest CT, as an important alternative to pulmonary function test.
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Affiliation(s)
- Lin Zhang
- Radiology Department, Shanghai General Hospital, Shanghai Jiao
Tong University School of Medicine,
Shanghai, China
| | - Beibei Jiang
- Radiology Department, Shanghai General Hospital, Shanghai Jiao
Tong University School of Medicine,
Shanghai, China
| | - Hendrik Joost Wisselink
- Radiology Department, University of Groningen, University
Medical Center Groningen,
Groningen, The Netherlands
| | - Rozemarijn Vliegenthart
- Radiology Department, University of Groningen, University
Medical Center Groningen,
Groningen, The Netherlands
| | - Xueqian Xie
- Radiology Department, Shanghai General Hospital, Shanghai Jiao
Tong University School of Medicine,
Shanghai, China
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19
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Li YZ, Jin GY, Chae KJ, Han YM. Quantitative Assessment of Airway Changes in Fibrotic Interstitial Lung Abnormality Patients by Chest CT According to Cumulative Cigarette Smoking. Tomography 2022; 8:1024-1032. [PMID: 35448716 PMCID: PMC9032598 DOI: 10.3390/tomography8020082] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 03/20/2022] [Accepted: 03/31/2022] [Indexed: 11/16/2022] Open
Abstract
Purpose: The aim of this study was to evaluate the role of Pi10 in patients with fibrotic interstitial lung abnormality (fibrotic ILA) in a chest CT, according to cumulative cigarette smoking. Methods: We retrospectively assessed 54 fibrotic ILA patients and 18 healthy non-smokers (control) who underwent non-enhanced CT and pulmonary function tests. We quantitatively analyzed airway changes (the inner luminal area, airway inner parameter, airway wall thickness, Pi10, skewness, and kurtosis) in the chest CT of fibrotic ILA patients, and the fibrotic ILA patients were categorized into groups based on pack-years: light, moderate, heavy. Airway change data and pulmonary function tests among the three groups of fibrotic ILA patients were compared with those of the control group by one-way ANOVA. Results: Mean skewness (2.58 ± 0.36) and kurtosis (7.64 ± 2.36) in the control group were significantly different from those of the fibrotic ILA patients (1.89 ± 0.37 and 3.62 ± 1.70, respectively, p < 0.001). In fibrotic ILA group, only heavy smokers had significantly increased Pi10 (mean increase 0.04, p = 0.013), increased airway wall thickness of the segmental bronchi (mean increase 0.06 mm, p = 0.005), and decreased lung diffusing capacity for carbon monoxide (p = 0.023). Conclusion: Pi10, as a biomaker of quantitative CT in fibrotic ILA patients, can reveal that smoking affects airway remodeling.
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Affiliation(s)
- Yuan Zhe Li
- Department of Radiology, Jeonbuk National University Medical School, Jeonju 54896, Korea; (Y.Z.L.); (K.J.C.); (Y.M.H.)
| | - Gong Yong Jin
- Department of Radiology, Jeonbuk National University Medical School, Jeonju 54896, Korea; (Y.Z.L.); (K.J.C.); (Y.M.H.)
- Research Institute of Clinical Medicine, Biomedical Research Institute of Jeonbuk National University Hospital, Jeonbuk National University Medical School, Institute of Medical Science, Jeonju 54970, Korea
- Correspondence: ; Tel.: +82-063-250-2307
| | - Kum Ju Chae
- Department of Radiology, Jeonbuk National University Medical School, Jeonju 54896, Korea; (Y.Z.L.); (K.J.C.); (Y.M.H.)
- Research Institute of Clinical Medicine, Biomedical Research Institute of Jeonbuk National University Hospital, Jeonbuk National University Medical School, Institute of Medical Science, Jeonju 54970, Korea
| | - Young Min Han
- Department of Radiology, Jeonbuk National University Medical School, Jeonju 54896, Korea; (Y.Z.L.); (K.J.C.); (Y.M.H.)
- Research Institute of Clinical Medicine, Biomedical Research Institute of Jeonbuk National University Hospital, Jeonbuk National University Medical School, Institute of Medical Science, Jeonju 54970, Korea
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20
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Gereige JD, Xu H, Ortega VE, Cho MH, Liu M, Sakornsakolpat P, Silverman EK, Beaty TH, Miller BE, Bakke P, Gulsvik A, Hersh CP, Morrow JD, Ampleford EJ, Hawkins GA, Bleecker ER, Meyers DA, Peters SP, Celedón JC, Tantisira K, Li J, Dupuis J, O'Connor GT. A genome-wide association study of bronchodilator response in participants of European and African ancestry from six independent cohorts. ERJ Open Res 2022; 8:00484-2021. [PMID: 35769418 PMCID: PMC9234425 DOI: 10.1183/23120541.00484-2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 05/08/2022] [Indexed: 11/30/2022] Open
Abstract
Introduction Bronchodilator response (BDR) is a measurement of acute bronchodilation in response to short-acting β2-agonists, with a heritability between 10 and 40%. Identifying genetic variants associated with BDR may lead to a better understanding of its complex pathophysiology. Methods We performed a genome-wide association study (GWAS) of BDR in six adult cohorts with participants of European ancestry (EA) and African ancestry (AA) including community cohorts and cohorts ascertained on the basis of obstructive pulmonary disease. Validation analysis was carried out in two paediatric asthma cohorts. Results A total of 10 623 EA and 3597 AA participants were included in the analyses. No single nucleotide polymorphism (SNP) was associated with BDR at the conventional genome-wide significance threshold (p<5×10-8). Performing fine mapping and using a threshold of p<5×10-6 to identify suggestive variants of interest, we identified three SNPs with possible biological relevance: rs35870000 (within FREM1), which may be involved in IgE- and IL5-induced changes in airway smooth muscle cell responsiveness; rs10426116 (within ZNF284), a zinc finger protein, which has been implicated in asthma and BDR previously; and rs4782614 (near ATP2C2), involved in calcium transmembrane transport. Validation in paediatric cohorts yielded no significant SNPs, possibly due to age-genotype interaction effects. Conclusion Ancestry-stratified and ancestry-combined GWAS meta-analyses of over 14 000 participants did not identify genetic variants associated with BDR at the genome-wide significance threshold, although a less stringent threshold identified three variants showing suggestive evidence of association. A common definition and protocol for measuring BDR in research may improve future efforts to identify variants associated with BDR.
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Affiliation(s)
- Jessica D. Gereige
- Division of Pulmonary, Allergy, Sleep, and Critical Care Medicine, Boston Medical Center, Boston, MA, USA
- Pulmonary Center, Boston University School of Medicine, Boston, MA, USA
| | - Hanfei Xu
- Dept of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Victor E. Ortega
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Michael H. Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ming Liu
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA, USA
| | - Phuwanat Sakornsakolpat
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Edwin K. Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Terri H. Beaty
- Dept of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - Per Bakke
- Dept of Clinical Science, University of Bergen, Bergen, Norway
| | - Amund Gulsvik
- Dept of Clinical Science, University of Bergen, Bergen, Norway
| | - Craig P. Hersh
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jarrett D. Morrow
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Elizabeth J. Ampleford
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Gregory A. Hawkins
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Eugene R. Bleecker
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Deborah A. Meyers
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Stephen P. Peters
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Juan C. Celedón
- Division of Pediatric Pulmonary Medicine, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kelan Tantisira
- Division of Pediatric Respiratory Medicine, University of California and Rady Children's Hospital, San Diego, CA, USA
| | - Jiang Li
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Research Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, Guangdong, China
| | - Josée Dupuis
- Dept of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - George T. O'Connor
- Division of Pulmonary, Allergy, Sleep, and Critical Care Medicine, Boston Medical Center, Boston, MA, USA
- Pulmonary Center, Boston University School of Medicine, Boston, MA, USA
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21
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Siegfried JM. Sex and Gender Differences in Lung Cancer and Chronic Obstructive Lung Disease. Endocrinology 2022; 163:6470418. [PMID: 34927202 DOI: 10.1210/endocr/bqab254] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Indexed: 11/19/2022]
Abstract
Two highly prevalent pulmonary diseases, lung cancer and chronic obstructive lung disease (COPD), show both sex and gender differences in their presentations and outcomes. Sex differences are defined as biological differences associated with the male vs female genotype, and gender differences are defined as behavioral or social differences that primarily arise because of gender identity. The incidence of both lung cancer and COPD has increased dramatically in women over the past 50 years, and both are associated with chronic pulmonary inflammation. Development of COPD is also a risk factor for lung cancer. In this review, the main differences in lung cancer and COPD biology observed between men and women will be summarized. Potential causative factors will be discussed, including the role of estrogen in promoting pro-growth and inflammatory phenotypes which may contribute to development of both lung cancer and COPD. Response of the innate and adaptive immune system to estrogen is a likely factor in the biology of both lung cancer and COPD. Estrogen available from synthesis by reproductive organs as well as local pulmonary estrogen synthesis may be involved in activating estrogen receptors expressed by multiple cell types in the lung. Estrogenic actions, although more pronounced in women, may also have importance in the biology of lung cancer and COPD in men. Effects of estrogen are also timing and context dependent; the multiple cell types that mediate estrogen action in the lungs may confer both positive and negative effects on disease processes.
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Affiliation(s)
- Jill M Siegfried
- Department of Pharmacology, University of Minnesota, Minneapolis, MN 55455, USA
- Department of Pharmacology & Chemical Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA
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22
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Cardoso J, Ferreira AJ, Guimarães M, Oliveira AS, Simão P, Sucena M. Treatable Traits in COPD - A Proposed Approach. Int J Chron Obstruct Pulmon Dis 2021; 16:3167-3182. [PMID: 34824530 PMCID: PMC8609199 DOI: 10.2147/copd.s330817] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 11/03/2021] [Indexed: 12/20/2022] Open
Abstract
The well-recognized individual heterogeneity within COPD patients has led to a growing interest in greater personalization in the approach of these patients. Thus, the treatable traits strategy has been proposed as a further step towards precision medicine in the management of chronic airway disease, both in stable phase and acute exacerbations. The aim of this paper is to perform a critical review on the treatable traits strategy and propose a guide to approach COPD patients in the light of this new concept. An innovative stepwise approach is proposed - a multidisciplinary model based on two distinct phases, with the potential to be implemented in both primary care and hospital settings. The first phase is the initial and focused assessment of a selected subset of treatable traits, which should be addressed in all COPD patients in both settings (primary care and hospital). As some patients may present with advanced disease at diagnosis or may progress despite this initial treatment requiring a more specialized assessment, they should progress to a second phase, in which a broader approach is recommended. Beyond stable COPD, we explore how the treatable traits strategy may be applied to reduce the risk of future exacerbations and improve the management of COPD exacerbations. Since many treatable traits have already been related to exacerbation risk, the strategy proposed here represents an opportunity to be proactive. Although it still lacks prospective validation, we believe this is the way forward for the future of the COPD approach.
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Affiliation(s)
- João Cardoso
- Pulmonology Department, Centro Hospitalar Universitário de Lisboa Central, Lisboa, Portugal.,NOVA Medical School, Nova University Lisbon, Lisboa, Portugal
| | - António Jorge Ferreira
- Pulmonology Department, Centro Hospitalar Universitário de Coimbra, Coimbra, Portugal.,Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Miguel Guimarães
- Pulmonology Department, Centro Hospitalar Vila Nova de Gaia/Espinho EPE, Vila Nova de Gaia, Portugal
| | - Ana Sofia Oliveira
- Pulmonology Department, Centro Hospitalar Universitário de Lisboa Norte EPE, Lisboa, Portugal
| | - Paula Simão
- Pulmonology Department, Unidade Local de Saúde de Matosinhos EPE, Matosinhos, Portugal
| | - Maria Sucena
- Pulmonology Department, Centro Hospitalar Universitário do Porto EPE, Porto, Portugal.,Lung Function and Ventilation Unit, Centro Hospitalar Universitário do Porto EPE, Porto, Portugal
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23
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Shah DM, Kshatriya RM, Paliwal R. Comparison of demographic, clinical, spirometry, and radiological parameters between smoking and non-smoking COPD patients in rural Gujarat, India. J Family Med Prim Care 2021; 10:3343-3347. [PMID: 34760755 PMCID: PMC8565106 DOI: 10.4103/jfmpc.jfmpc_87_21] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 06/30/2021] [Accepted: 07/09/2021] [Indexed: 11/19/2022] Open
Abstract
Context: A total of 20% of Chronic Obstructive Pulmonary Disease(COPD) patients are non-smokers due to preventable causes, such as biomass fuel exposure, post tuberculous sequelae, occupational exposure, air pollution, persistent chronic asthma, and genetic predisposition. Aims: To compare smokers and non-smokers with COPD. Settings and Design: An observational study was conducted at a tertiary care hospital on 60 patients diagnosed with COPD, (GOLD criteria), who were divided into smoker and non-smoker groups. Subjects and Methods: Demographic data, clinical profile, smoking history, and radiological data were collected and compared. Exclusion criteria were individuals having active pulmonary tuberculosis and reversible air flow limitations. Statistical Analysis Used: Using STATA 14.2, quantitative and qualitative data were presented using descriptive statistics. Results: A total of 100% of smokers were male, whereas 70% of non-smokers were female. Compared to non-smokers (16.67%), smokers (26.6%) presented with higher grade of dyspnea. A statistically significant difference was seen with more smokers diagnosed as severe (40%) and very severe (30%) COPD compared to non-smokers with mild (16.67%) and moderate (46.67%) COPD (P < 0.012), Post bronchodilator FEV1 among smokers (42.63) compared to non-smokers (56.63) (P < 0.01) and decrease in FEV1 as the grade of dyspnea increased (P < 0.002). Compared to 36.67% in non-smokers, 70% smokers showed emphysematous x-rays. Conclusions: In our study we found majority of non-smokers to be female, and smokers had a higher grade of dyspnea, more severe COPD, lower post bronchodilator FEV1, and more emphysematous changes on x-rays.
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Affiliation(s)
- Dhruv M Shah
- Department of Respiratory Medicine, New Cross Hospital, Royal Wolverhampton Trust, Wolverhampton, United Kingdom
| | - Ravish M Kshatriya
- Department of Respiratory Medicine, Parul Institute of Medical Sciences and Research, Parul University, Vadodara, Gujarat, India
| | - Rajiv Paliwal
- Department of Respiratory Medicine, Pramukhswami Medical College, Karamsad, Anand, Gujarat, India
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24
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Tanabe N, Hirai T. Recent advances in airway imaging using micro-computed tomography and computed tomography for chronic obstructive pulmonary disease. Korean J Intern Med 2021; 36:1294-1304. [PMID: 34607419 PMCID: PMC8588974 DOI: 10.3904/kjim.2021.124] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 05/14/2021] [Indexed: 12/13/2022] Open
Abstract
Chronic obstructive pulmonary disease (COPD) is a complex lung disease characterized by a combination of airway disease and emphysema. Emphysema is classified as centrilobular emphysema (CLE), paraseptal emphysema (PSE), or panlobular emphysema (PLE), and airway disease extends from the respiratory, terminal, and preterminal bronchioles to the central segmental airways. Although clinical computed tomography (CT) cannot be used to visualize the small airways, micro-CT has shown that terminal bronchiole disease is more severe in CLE than in PSE and PLE, and micro-CT findings suggest that the loss and luminal narrowing of terminal bronchioles is an early pathological change in CLE. Furthermore, the introduction of ultra-high-resolution CT has enabled direct evaluation of the proximal small (1 to 2-mm diameter) airways, and new CT analytical methods have enabled estimation of small airway disease and prediction of future COPD onset and lung function decline in smokers with and without COPD. This review discusses the literature on micro-CT and the technical advancements in clinical CT analysis for COPD. Hopefully, novel micro-CT findings will improve our understanding of the distinct pathogeneses of the emphysema subtypes to enable exploration of new therapeutic targets, and sophisticated CT imaging methods will be integrated into clinical practice to achieve more personalized management.
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Affiliation(s)
- Naoya Tanabe
- Department of Respiratory Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Toyohiro Hirai
- Department of Respiratory Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
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25
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Waatevik M, Frisk B, Real FG, Hardie JA, Bakke P, Eagan TM, Johannessen A. CT-defined emphysema in COPD patients and risk for change in desaturation status in 6-min walk test. Respir Med 2021; 187:106542. [PMID: 34340175 DOI: 10.1016/j.rmed.2021.106542] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 06/17/2021] [Accepted: 07/14/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND Emphysema and exercise induced desaturation (EID) are both related to poorer COPD prognosis. More knowledge of associations between emphysema and desaturation is needed for more efficient disease management. RESEARCH QUESTION Is emphysema a risk factor for both new and repeated desaturation, and is emphysema of more or less importance than other known risk factors? METHODS 283 COPD patients completed a 6-min walk test (6MWT) at baseline and one year later in the Bergen COPD cohort study 2006-2011. Degree of emphysema was assessed as percent of low attenuation areas (%LAA) under -950 Hounsfield units using high-resolution computed tomography at baseline. We performed multinomial logistic regression analysis, receiver operating curves (ROC) and area under the curve (AUC) estimations. Dominance analysis was used to rank emphysema and risk factors in terms of importance. RESULTS A one percent increase in %LAA increases the relative risk (RR) of new desaturation by 10 % (RR 1.1 (95%CI 1.1, 1.2)) and for repeated desaturation by 20 % (RR 1.2 (95%CI 1.1, 1.3)). Compared with other important desaturation risk factors, %LAA ranked as number one in the dominance analysis, accounting for 50 % and 37 % of the predicted variance for new and repeated desaturators, respectively. FEV1% predicted accounted for 9 % and 24 %, and resting SpO2 accounted for 22 % and 21 % for new and repeated desaturation. CONCLUSION Emphysema increases the risk of developing and repeatedly experiencing EID. Emphysema seems to be a more important risk factor for desaturation than FEV1% predicted and resting saturation.
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Affiliation(s)
- Marie Waatevik
- Centre for Clinical Research, Haukeland University Hospital, Bergen, Norway.
| | - Bente Frisk
- Dept of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway; Dept of Physiotherapy, Haukeland University Hospital, Bergen, Norway
| | - Francisco Gómez Real
- Dept of Clinical Science, University of Bergen, Bergen, Norway; Dept of Gynecology and Obstetrics, Haukeland University Hospital, Bergen, Norway
| | | | - Per Bakke
- Dept of Clinical Science, University of Bergen, Bergen, Norway
| | - Tomas Mikal Eagan
- Dept of Clinical Science, University of Bergen, Bergen, Norway; Dept of Thoracic Medicine, Haukeland University Hospital, Bergen, Norway
| | - Ane Johannessen
- Centre for International Health, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
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26
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Peng J, Bie Z, Li Y, Li B, Guo R, Wang C, Li X. Microwave ablation of lung malignancies with coexisting severe emphysema: a retrospective analysis of safety and efficacy in 26 patients. Int J Hyperthermia 2021; 38:136-143. [PMID: 33541162 DOI: 10.1080/02656736.2021.1876254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
Abstract
PURPOSE This retrospective study aimed to evaluate the safety and efficacy of microwave ablation (MWA) for lung malignancies in patients with severe emphysema. MATERIALS AND METHODS The clinical records of 1075 consecutive patients treated for malignant lung tumors in our department were retrospectively reviewed. Emphysema was assessed based on standard-dose computed tomography (CT) and was considered severe when it occupied ≥25% of the lung. Overall, 26 patients (24 men and 2 women; mean age ± standard deviation [SD]: 71.23 ± 8.18 years, range: 59-88 years) with severe emphysema underwent CT-guided percutaneous MWA for treating 26 tumors (24: non-small cell lung cancer and 2: metastases). The mean tumor size was 3.0 cm (SD: 1.5, range: 1.2-6.5 cm). Follow-up was performed with CT at 1, 3, 6, 12 months after ablation, and every 6 months thereafter. Complications and efficacy were evaluated. RESULTS The median follow-up duration in all patients was 17.5 months (range: 5-37 months, interquartile range: 15.8). The mortality rate was 0% within 30 days after ablation. Major complications including pneumonia, lung abscess and refractory pneumothorax occurred in 19.2% (5/26) patients. The technical success and efficacy rates were 88.5% (23/26) and 87.0% (20/23), respectively, and the local tumor progression rate was 30.0% (6/20). CONCLUSION MWA appears to be a safe and effective therapeutic option for treating lung malignancies in patients with severe emphysema.
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Affiliation(s)
- Jinzhao Peng
- Minimally Invasive Tumor Therapies Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.,Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Zhixin Bie
- Minimally Invasive Tumor Therapies Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Yuanming Li
- Minimally Invasive Tumor Therapies Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Bin Li
- Minimally Invasive Tumor Therapies Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Runqi Guo
- Minimally Invasive Tumor Therapies Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Chengen Wang
- Minimally Invasive Tumor Therapies Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Xiaoguang Li
- Minimally Invasive Tumor Therapies Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.,Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
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27
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Automated Diseased Lung Volume Percentage Calculation in Quantitative CT Evaluation of Chronic Obstructive Pulmonary Disease and Idiopathic Pulmonary Fibrosis. J Comput Assist Tomogr 2021; 45:649-658. [PMID: 34176875 DOI: 10.1097/rct.0000000000001182] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Several software-based quantitative computed tomography (CT) analysis methods have been developed for assessing emphysema and interstitial lung disease. Although the texture classification method appeared to be more successful than the other methods, the software programs are not commercially available, to our knowledge. Therefore, this study aimed to investigate the usefulness of a commercially available software program for quantitative CT analyses. METHODS This prospective cohort study included 80 patients with chronic obstructive pulmonary disease (COPD) or idiopathic pulmonary fibrosis (IPF). RESULTS The percentage of low attenuation volume and high attenuation volume had high sensitivity and high specificity for detecting emphysema and pulmonary fibrosis, respectively. The percentage of diseased lung volume (DLV%) was significantly correlated with the lung diffusion capacity for carbon monoxide in all patients with COPD and IPF patients. CONCLUSIONS The quantitative CT analysis may improve the precision of the assessment of DLV%, which itself could be a useful tool in predicting lung diffusion capacity in patients with the clinical diagnosis of COPD or IPF.
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Tane S, Nishikubo M, Kitazume M, Fujibayashi Y, Kimura K, Kitamura Y, Takenaka D, Nishio W. Cluster analysis of emphysema for predicting pulmonary complications after thoracoscopic lobectomy. Eur J Cardiothorac Surg 2021; 60:607-613. [PMID: 34008011 DOI: 10.1093/ejcts/ezab237] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Revised: 03/22/2021] [Accepted: 04/07/2021] [Indexed: 11/14/2022] Open
Abstract
OBJECTIVES Despite significant advances in surgical techniques, including thoracoscopic approaches and perioperative care, the morbidity rate remains high after lung resection. This study focused on a low attenuation cluster analysis, which represented the size distribution of pulmonary emphysema and assessed its utility for predicting postoperative pulmonary complications after thoracoscopic lobectomy. METHODS From April 2013 to September 2018, lung cancer patients who received spirometry and computed tomography (CT) before surgery and underwent thoracoscopic lobectomy were included. The cumulative size distribution of the low attenuation area (LAA, defined as ≤-950 Hounsfield unit on CT) clusters followed a power-law characterized by an exponent D-value, a measure of the complexity of the alveolar structure. D-value and LAA% (LAA/total lung volume) were calculated using preoperative 3-dimensional CT software. The relationship between pulmonary complications and patient characteristics, including D-value and LAA%, was investigated. RESULTS Among 471 patients, there were 61 respiratory complication cases (12.9%). Receiver operation characteristic curve analysis revealed that the best predictive cut-off value of D-value and LAA% for pulmonary complications was 2.27 and 16.5, respectively, with an area under the curve of 0.72 and 0.58, respectively. D-value was significantly correlated with % forced expiratory volume in 1 s. Per univariate analysis, gender, smoking history, forced expiratory volume in 1 s/forced vital capacity, LAA% and D-value were risk factors for predicting postoperative pulmonary complications. In the multivariate analysis, D-value remained a significant predictive factor. CONCLUSION Preoperative assessment of emphysema cluster analysis may represent the vulnerability of the operated lung and could be the novel predictor for pulmonary complications after thoracoscopic lobectomy.
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Affiliation(s)
- Shinya Tane
- Division of Chest Surgery, Hyogo Cancer Center, Akashi, Japan
| | | | - Mai Kitazume
- Division of Chest Surgery, Hyogo Cancer Center, Akashi, Japan
| | | | - Kenji Kimura
- Division of Chest Surgery, Hyogo Cancer Center, Akashi, Japan
| | | | - Daisuke Takenaka
- Division of Diagnostic Radiology, Hyogo Cancer Center, Akashi, Japan
| | - Wataru Nishio
- Division of Chest Surgery, Hyogo Cancer Center, Akashi, Japan
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Tubío-Pérez RA, Torres-Durán M, Pérez-Ríos M, Fernández-Villar A, Ruano-Raviña A. Lung emphysema and lung cancer: what do we know about it? ANNALS OF TRANSLATIONAL MEDICINE 2020; 8:1471. [PMID: 33313216 PMCID: PMC7723574 DOI: 10.21037/atm-20-1180] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Emphysema and lung cancer (LC) are two diseases which share common risk factors, e.g., smoking. In recent years, many studies have sought to analyse this association. By way of illustration, we conducted a review of the scientific literature of the studies published to date, whose main designated aim was to demonstrate the relationship between emphysema and LC, and this association's influence on the histology, prognosis and molecular mechanisms responsible. We included over 40 studies (ranging from case-control and cohort studies to systematic reviews and meta-analyses), which highlight the association between emphysema and LC, independently of smoking habit. These studies also report a possible influence on histology, with adenocarcinoma being the most frequent lineage, and an association with poor prognosis, which affects both survival and post-operative complications. Oxidative stress, which generates chronic inflammatory status as well as the presence of certain polymorphisms in various genes (CYP1A1, TERT, CLPTM1L, ERK), gives rise-in the case of patients with emphysema-to alteration of cellular repair mechanisms, which in turn favours the proliferation of neoplastic epithelial cells responsible for the origin of LC.
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Affiliation(s)
- Ramón A Tubío-Pérez
- Pulmonary Department, Hospital Álvaro Cunqueiro, EOXI, Vigo, Spain.,NeumoVigoI+i Research Group, Vigo Biomedical Research Institute (IBIV), Galicia, Spain
| | - María Torres-Durán
- Pulmonary Department, Hospital Álvaro Cunqueiro, EOXI, Vigo, Spain.,NeumoVigoI+i Research Group, Vigo Biomedical Research Institute (IBIV), Galicia, Spain
| | - Mónica Pérez-Ríos
- Department of Preventive Medicine and Public Health, University of Santiago de Compostela, Santiago de Compostela, Spain.,CIBER de Epidemiología y Salud Pública, CIBERESP, Madrid, Spain
| | - Alberto Fernández-Villar
- Pulmonary Department, Hospital Álvaro Cunqueiro, EOXI, Vigo, Spain.,NeumoVigoI+i Research Group, Vigo Biomedical Research Institute (IBIV), Galicia, Spain
| | - Alberto Ruano-Raviña
- Department of Preventive Medicine and Public Health, University of Santiago de Compostela, Santiago de Compostela, Spain.,CIBER de Epidemiología y Salud Pública, CIBERESP, Madrid, Spain
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Boulet LP, Boulay ME, Coxson HO, Hague CJ, Milot J, Lepage J, Maltais F. Asthma with Irreversible Airway Obstruction in Smokers and Nonsmokers: Links between Airway Inflammation and Structural Changes. Respiration 2020; 99:1-11. [PMID: 33291112 DOI: 10.1159/000508163] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Accepted: 04/20/2020] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND The development of irreversible airway obstruction (IRAO) in asthma is related to lung/airway inflammatory and structural changes whose characteristics are likely influenced by exposure to tobacco smoke. OBJECTIVE To investigate the interplay between airway and lung structural changes, airway inflammation, and smoking exposure in asthmatics with IRAO. METHODS We studied asthmatics with IRAO who were further classified according to their smoking history, those with ≥20 pack-years of tobacco exposure (asthmatics with smoking-related IRAO [AwS-IRAO]) and those with <5 pack-years of tobacco exposure (asthmatics with nonsmoking-related IRAO [AwNS-IRAO]). In addition to recording baseline clinical and lung function features, all patients had a chest computed tomography (CT) from which airway wall thickness was measured and quantitative and qualitative assessment of emphysema was performed. The airway inflammatory profile was documented from differential inflammatory cell counts on induced sputum. RESULTS Ninety patients were recruited (57 AwS-IRAO and 33 AwNS-IRAO). There were no statistically significant differences in the extent of emphysema and gas trapping between groups on quantitative chest CT analysis, although Pi10, a marker of airway wall thickness, was significantly higher in AwS-IRAO (p = 0.0242). Visual analysis showed a higher prevalence of emphysema (p = 0.0001) and higher emphysema score (p < 0.0001) in AwS-IRAO compared to AwNS-IRAO and distribution of emphysema was different between groups. Correlations between radiological features and lung function were stronger in AwS-IRAO. In a subgroup analysis, we found a correlation between airway neutrophilia and emphysematous features in AwS-IRAO and between eosinophilia and both airway wall thickness and emphysematous changes in AwNS-IRAO. CONCLUSIONS Although bronchial structural changes were relatively similar in smoking and nonsmoking patients with asthma and IRAO, emphysematous changes were more predominant in smokers. However, neutrophils in AwS-IRAO and eosinophils in AwNS-IRAO were associated with lung and airway structural changes.
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Affiliation(s)
- Louis-Philippe Boulet
- Institut Universitaire de Cardiologie et de Pneumologie de Québec-Université Laval, Québec, Québec, Canada,
| | - Marie-Eve Boulay
- Institut Universitaire de Cardiologie et de Pneumologie de Québec-Université Laval, Québec, Québec, Canada
| | - Harvey O Coxson
- Centre for Heart Lung Innovation, St. Paul's Hospital, University of British Columbia, Vancouver, British Columbia, Canada
| | - Cameron J Hague
- Department of Radiology, St. Paul's Hospital, University of British Columbia, Vancouver, British Columbia, Canada
| | - Joanne Milot
- Institut Universitaire de Cardiologie et de Pneumologie de Québec-Université Laval, Québec, Québec, Canada
| | - Johane Lepage
- Institut Universitaire de Cardiologie et de Pneumologie de Québec-Université Laval, Québec, Québec, Canada
| | - François Maltais
- Institut Universitaire de Cardiologie et de Pneumologie de Québec-Université Laval, Québec, Québec, Canada
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Hwang HJ, Lee SM, Seo JB, Lee JS, Kim N, Lee SW, Oh YM. Visual and Quantitative Assessments of Regional Xenon-Ventilation Using Dual-Energy CT in Asthma-Chronic Obstructive Pulmonary Disease Overlap Syndrome: A Comparison with Chronic Obstructive Pulmonary Disease. Korean J Radiol 2020; 21:1104-1113. [PMID: 32691546 PMCID: PMC7371623 DOI: 10.3348/kjr.2019.0936] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 03/11/2020] [Accepted: 03/22/2020] [Indexed: 01/08/2023] Open
Abstract
Objective To assess the regional ventilation in patients with asthma-chronic obstructive pulmonary disease (COPD) overlap syndrome (ACOS) using xenon-ventilation dual-energy CT (DECT), and to compare it to that in patients with COPD. Materials and Methods Twenty-one patients with ACOS and 46 patients with COPD underwent xenon-ventilation DECT. The ventilation abnormalities were visually determined to be 1) peripheral wedge/diffuse defect, 2) diffuse heterogeneous defect, 3) lobar/segmental/subsegmental defect, and 4) no defect on xenon-ventilation maps. Emphysema index (EI), airway wall thickness (Pi10), and mean ventilation values in the whole lung, peripheral lung, and central lung areas were quantified and compared between the two groups using the Student's t test. Results Most patients with ACOS showed the peripheral wedge/diffuse defect (n = 14, 66.7%), whereas patients with COPD commonly showed the diffuse heterogeneous defect and lobar/segmental/subsegmental defect (n = 21, 45.7% and n = 20, 43.5%, respectively). The prevalence of ventilation defect patterns showed significant intergroup differences (p < 0.001). The quantified ventilation values in the peripheral lung areas were significantly lower in patients with ACOS than in patients with COPD (p = 0.045). The quantified Pi10 was significantly higher in patients with ACOS than in patients with COPD (p = 0.041); however, EI was not significantly different between the two groups. Conclusion The ventilation abnormalities on the visual and quantitative assessments of xenon-ventilation DECT differed between patients with ACOS and patients with COPD. Xenon-ventilation DECT may demonstrate the different physiologic changes of pulmonary ventilation in patients with ACOS and COPD.
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Affiliation(s)
- Hye Jeon Hwang
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Sang Min Lee
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
| | - Joon Beom Seo
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Jae Seung Lee
- Department of Pulmonary and Critical Care Medicine, and Clinical Research Center for Chronic Obstructive Airway Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Namkug Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Sei Won Lee
- Department of Pulmonary and Critical Care Medicine, and Clinical Research Center for Chronic Obstructive Airway Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Yeon Mok Oh
- Department of Pulmonary and Critical Care Medicine, and Clinical Research Center for Chronic Obstructive Airway Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
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Gagnat AA, Gjerdevik M, Lie SA, Gulsvik A, Bakke P, Nielsen R. Acute exacerbations of COPD and risk of lung cancer in COPD patients with and without a history of asthma. Eur Clin Respir J 2020; 7:1799540. [PMID: 32944202 PMCID: PMC7480432 DOI: 10.1080/20018525.2020.1799540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Rationale There is limited knowledge on the effect of acute exacerbations in chronic obstructive pulmonary disease (AECOPD) on lung cancer risk in COPD patients with and without a history of asthma. This study aims to examine whether AECOPD is associated with risk of lung cancer, and whether the effect depends on a history of asthma. Methods In the GenKOLS study of 2003–2005, 852 subjects with COPD performed spirometry, and filled out questionnaires on smoking habits, symptoms and disease history. These data were linked to lung cancer data from the Cancer Registry of Norway through 2013. AECOPD, measured at baseline was the main predictor. To quantify differences in lung cancer risk, we performed Cox-proportional hazards regression. We adjusted for sex, age, smoking variables, body mass index, and lung function. Measurements and results During follow-up, 8.8% of the subjects with, and 5.9% of the subjects without exacerbations were diagnosed with lung cancer. Cox regression showed a significant increased risk of lung cancer with one or more exacerbations in COPD patients without a history of asthma, HRR = 2.77 (95% CI 1.39–5.52). We found a significant interaction between a history of asthma and AECOPD on lung cancer. Conclusions AECOPD is associated with an increased risk of lung cancer in COPD patients without a history of asthma.
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Affiliation(s)
- Ane Aamli Gagnat
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Miriam Gjerdevik
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - Stein Atle Lie
- Department of Clinical Dentistry, University of Bergen, Bergen, Norway
| | - Amund Gulsvik
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Per Bakke
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Rune Nielsen
- Department of Clinical Science, University of Bergen, Bergen, Norway.,Department of Thoracic Medicine, Haukeland University Hospital, Bergen, Norway
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Cooper CB, Paine R, Curtis JL, Kanner RE, Martinez CH, Meldrum CA, Bowler R, O'Neal W, Hoffman EA, Couper D, Quibrera M, Criner G, Dransfield MT, Han MK, Hansel NN, Krishnan JA, Lazarus SC, Peters SP, Barr RG, Martinez FJ, Woodruff PG. Novel Respiratory Disability Score Predicts COPD Exacerbations and Mortality in the SPIROMICS Cohort. Int J Chron Obstruct Pulmon Dis 2020; 15:1887-1898. [PMID: 32821092 PMCID: PMC7417644 DOI: 10.2147/copd.s250191] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Accepted: 07/03/2020] [Indexed: 12/24/2022] Open
Abstract
Rationale Some COPD patients develop extreme breathlessness, decreased exercise capacity and poor health status yet respiratory disability is poorly characterized as a distinct phenotype. Objective To define respiratory disability in COPD based on available functional measures and to determine associations with risk for exacerbations and death. Methods We analyzed baseline data from a multi-center observational study (SPIROMICS). This analysis includes 2332 participants (472 with severe COPD, 991 with mild/moderate COPD, 726 smokers without airflow obstruction and 143 non-smoking controls). Measurements We defined respiratory disability by ≥4 of 7 criteria: mMRC dyspnea scale ≥3; Veterans Specific Activity Questionnaire <5; 6-minute walking distance <250 m; St George’s Respiratory Questionnaire activity domain >60; COPD Assessment Test >20; fatigue (FACIT-F Trial Outcome Index) <50; SF-12 <20. Results Using these criteria, respiratory disability was identified in 315 (13.5%) participants (52.1% female). Frequencies were severe COPD 34.5%; mild-moderate COPD 11.2%; smokers without obstruction 5.2% and never-smokers 2.1%. Compared with others, participants with disability had more emphysema (13.2 vs. 6.6%) and air-trapping (37.0 vs. 21.6%) on HRCT (P<0.0001). Using principal components analysis to derive a disability score, two factors explained 71% of variance, and a cut point −1.0 reliably identified disability. This disability score independently predicted future exacerbations (ß=0.34; CI 0.12, 0.64; P=0.003) and death (HR 2.97; CI 1.54, 5.75; P=0.001). Thus, participants with disability by this criterion had almost three times greater mortality compared to those without disability. Conclusion Our novel SPIROMICS respiratory disability score in COPD was associated with worse airflow obstruction as well as airway wall thickening, lung parenchymal destruction and certain inflammatory biomarkers. The disability score also proved to be an independent predictor of future exacerbations and death. These findings validate disability as an important phenotype in the spectrum of COPD.
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Affiliation(s)
- Christopher B Cooper
- Departments of Medicine and Physiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Robert Paine
- Section of Pulmonary and Critical Care Medicine, Department of Veterans Affairs Medical Center, University of Utah, Salt Lake City, UT, USA
| | - Jeffrey L Curtis
- Pulmonary and Critical Care Medicine Division, Department of Internal Medicine, University of Michigan Health System, Ann Arbor, MI, USA.,Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Richard E Kanner
- Section of Pulmonary and Critical Care Medicine, Department of Veterans Affairs Medical Center, University of Utah, Salt Lake City, UT, USA
| | - Carlos H Martinez
- Pulmonary and Critical Care Medicine Division, Department of Internal Medicine, University of Michigan Health System, Ann Arbor, MI, USA
| | - Catherine A Meldrum
- Pulmonary and Critical Care Medicine Division, Department of Internal Medicine, University of Michigan Health System, Ann Arbor, MI, USA
| | - Russell Bowler
- National Jewish Health, University of Colorado School of Medicine, Denver, CO, USA
| | - Wanda O'Neal
- University of North Carolina Marisco Lung Institute, Chapel Hill, NC, USA
| | - Eric A Hoffman
- Department of Radiology, University of Iowa, Iowa City, IA, USA
| | - David Couper
- University of North Carolina Marisco Lung Institute, Chapel Hill, NC, USA
| | - Miguel Quibrera
- University of North Carolina Marisco Lung Institute, Chapel Hill, NC, USA
| | - Gerald Criner
- Department of Pulmonary and Critical Care Medicine, Temple University, Philadelphia, PA, USA
| | - Mark T Dransfield
- Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - MeiLan K Han
- Pulmonary and Critical Care Medicine Division, Department of Internal Medicine, University of Michigan Health System, Ann Arbor, MI, USA
| | - Nadia N Hansel
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jerry A Krishnan
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Stephen C Lazarus
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | | | - R Graham Barr
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Fernando J Martinez
- Joan and Sanford I Weill Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Prescott G Woodruff
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
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Increased Airway Wall Thickness in Interstitial Lung Abnormalities and Idiopathic Pulmonary Fibrosis. Ann Am Thorac Soc 2020; 16:447-454. [PMID: 30543456 DOI: 10.1513/annalsats.201806-424oc] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
RATIONALE There is increasing evidence that aberrant processes occurring in the airways may precede the development of idiopathic pulmonary fibrosis (IPF); however, there has been no prior confirmatory data derived from imaging studies. OBJECTIVES To assess quantitative measures of airway wall thickness (AWT) in populations characterized for interstitial lung abnormalities (ILA) and for IPF. METHODS Computed tomographic imaging of the chest and measures of AWT were available for 6,073, 615, 1,167, and 38 participants from COPDGene (Genetic Epidemiology of COPD study), ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints study), and the Framingham Heart Study (FHS) and in patients with IPF from the Brigham and Women's Hospital Herlihy Registry, respectively. To evaluate these associations, we used multivariable linear regression to compare a standardized measure of AWT (the square root of AWT for airways with an internal perimeter of 10 mm [Pi10]) and characterizations of ILA and IPF by computed tomographic imaging of the chest. RESULTS In COPDGene, ECLIPSE, and FHS, research participants with ILA had increased measures of Pi10 compared with those without ILA. Patients with IPF had mean measures of Pi10 that were even greater than those noted in research participants with ILA. After adjustment for important covariates (e.g., age, sex, race, body mass index, smoking behavior, and chronic obstructive pulmonary disease severity when appropriate), research participants with ILA had increased measures of Pi10 compared with those without ILA (0.03 mm in COPDGene, 95% confidence interval [CI], 0.02-0.03; P < 0.001; 0.02 mm in ECLIPSE, 95% CI, 0.005-0.04; P = 0.01; 0.07 mm in FHS, 95% CI, 0.01-0.1; P = 0.01). Compared with COPDGene participants without ILA older than 60 years of age, patients with IPF were also noted to have increased measures of Pi10 (2.0 mm, 95% CI, 2.0-2.1; P < 0.001). Among research participants with ILA, increases in Pi10 were correlated with reductions in lung volumes in some but not all populations. CONCLUSIONS These results demonstrate that measurable increases in AWT are consistently noted in research participants with ILA and in patients with IPF. These findings suggest that abnormalities of the airways may play a role in, or be correlated with, early pathogenesis of pulmonary fibrosis.
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Vasilescu DM, Phillion AB, Kinose D, Verleden SE, Vanaudenaerde BM, Verleden GM, Van Raemdonck D, Stevenson CS, Hague CJ, Han MK, Cooper JD, Hackett TL, Hogg JC. Comprehensive stereological assessment of the human lung using multiresolution computed tomography. J Appl Physiol (1985) 2020; 128:1604-1616. [PMID: 32298211 DOI: 10.1152/japplphysiol.00803.2019] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
The application of stereology to lung casts and two-dimensional microscopy images is the gold standard for quantification of the human lung anatomy. However, these techniques are labor intensive, involving fixation, embedding, and histological sectioning of samples and thus have prevented comprehensive studies. Our objective was to demonstrate the application of stereology to volumetric multiresolution computed tomography (CT) to efficiently and extensively quantify the human lung anatomy. Nontransplantable donor lungs from individuals with no evidence of respiratory disease (n = 13) were air inflated, frozen at 10 cmH2O, and scanned using CT. Systematic uniform random samples were taken, scanned using micro-CT, and assessed using stereology. The application of stereology to volumetric CT imaging enabled comprehensive quantification of total lung volume, volume fractions of alveolar, alveolar duct, and tissue, mean linear intercept, alveolar surface area, alveolar surface area density, septal wall thickness, alveolar number, number-weighted mean alveolar volume, and the number and morphometry of terminal and transitional bronchioles. With the use of this data set, we found that women and men have the same number of terminal bronchioles (last generation of conducting airways), but men have longer terminal bronchioles, a smaller wall area percentage, and larger lungs due to a greater number of alveoli per acinus. The application of stereology to multiresolution CT imaging enables comprehensive analysis of the human lung parenchyma that identifies differences between men and women. The reported data set of normal donor lungs aged 25-77 yr provides reference data for future studies of chronic lung disease to determine exact changes in tissue pathology.NEW & NOTEWORTHY Stereology has been the gold standard to quantify the three-dimensional lung anatomy using two-dimensional microscopy images. However, such techniques are labor intensive. This study provides a method that applies stereology to volumetric computed tomography images of frozen whole human lungs and systematic uniform random samples. The method yielded a comprehensive data set on the small airways and parenchymal lung structures, highlighting morphometric sex differences and providing a reference data set for future pathological studies.
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Affiliation(s)
- Dragoş M Vasilescu
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada
| | - André B Phillion
- Department of Materials Science and Engineering, McMaster University, Hamilton, Ontario, Canada
| | - Daisuke Kinose
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada
| | - Stijn E Verleden
- Leuven Lung Transplant Unit, Katholieke Universiteit Leuven and Universitair Ziekenhuis Leuven-Gasthuisberg, Leuven, Belgium
| | - Bart M Vanaudenaerde
- Leuven Lung Transplant Unit, Katholieke Universiteit Leuven and Universitair Ziekenhuis Leuven-Gasthuisberg, Leuven, Belgium
| | - Geert M Verleden
- Leuven Lung Transplant Unit, Katholieke Universiteit Leuven and Universitair Ziekenhuis Leuven-Gasthuisberg, Leuven, Belgium
| | - Dirk Van Raemdonck
- Leuven Lung Transplant Unit, Katholieke Universiteit Leuven and Universitair Ziekenhuis Leuven-Gasthuisberg, Leuven, Belgium
| | | | - Cameron J Hague
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - MeiLan K Han
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, Michigan
| | - Joel D Cooper
- Division of Thoracic Surgery, Department of Surgery, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Tillie-Louise Hackett
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada
| | - James C Hogg
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada
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Refaee T, Wu G, Ibrahim A, Halilaj I, Leijenaar RTH, Rogers W, Gietema HA, Hendriks LEL, Lambin P, Woodruff HC. The Emerging Role of Radiomics in COPD and Lung Cancer. Respiration 2020; 99:99-107. [PMID: 31991420 DOI: 10.1159/000505429] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 12/12/2019] [Indexed: 12/24/2022] Open
Abstract
Medical imaging plays a key role in evaluating and monitoring lung diseases such as chronic obstructive pulmonary disease (COPD) and lung cancer. The application of artificial intelligence in medical imaging has transformed medical images into mineable data, by extracting and correlating quantitative imaging features with patients' outcomes and tumor phenotype - a process termed radiomics. While this process has already been widely researched in lung oncology, the evaluation of COPD in this fashion remains in its infancy. Here we outline the main applications of radiomics in lung cancer and briefly review the workflow from image acquisition to the evaluation of model performance. Finally, we discuss the current assessments of COPD and the potential application of radiomics in COPD.
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Affiliation(s)
- Turkey Refaee
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands, .,Department of Diagnostic Radiology, Faculty of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia,
| | - Guangyao Wu
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands
| | - Abdallah Ibrahim
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands.,Department of Radiology and Nuclear Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Centre+, Maastricht, The Netherlands.,Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics, Centre Hospitalier Universitaire de Liège, Liège, Belgium.,Department of Nuclear Medicine and Comprehensive Diagnostic Center Aachen (CDCA), University Hospital RWTH Aachen University, Aachen, Germany
| | - Iva Halilaj
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands
| | - Ralph T H Leijenaar
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands
| | - William Rogers
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands.,Department of Thoracic Oncology, IRCCS Foundation National Cancer Institute, Milan, Italy
| | - Hester A Gietema
- Department of Radiology and Nuclear Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Lizza E L Hendriks
- Department of Pulmonary Diseases, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands
| | - Philippe Lambin
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands.,Department of Radiology and Nuclear Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Henry C Woodruff
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands.,Department of Radiology and Nuclear Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Centre+, Maastricht, The Netherlands
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Quantitative CT detects progression in COPD patients with severe emphysema in a 3-month interval. Eur Radiol 2020; 30:2502-2512. [PMID: 31965260 DOI: 10.1007/s00330-019-06577-y] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Revised: 09/26/2019] [Accepted: 11/07/2019] [Indexed: 10/25/2022]
Abstract
OBJECTIVES Chronic obstructive pulmonary disease (COPD) is characterized by variable contributions of emphysema and airway disease on computed tomography (CT), and still little is known on their temporal evolution. We hypothesized that quantitative CT (QCT) is able to detect short-time changes in a cohort of patients with very severe COPD. METHODS Two paired in- and expiratory CT each from 70 patients with avg. GOLD stage of 3.6 (mean age = 66 ± 7.5, mean FEV1/FVC = 35.28 ± 7.75) were taken 3 months apart and analyzed by fully automatic software computing emphysema (emphysema index (EI), mean lung density (MLD)), air-trapping (ratio expiration to inspiration of mean lung attenuation (E/I MLA), relative volume change between - 856 HU and - 950 HU (RVC856-950)), and parametric response mapping (PRM) parameters for each lobe separately and the whole lung. Airway metrics measured were wall thickness (WT) and lumen area (LA) for each airway generation and the whole lung. RESULTS The average of the emphysema parameters (EI, MLD) increased significantly by 1.5% (p < 0.001) for the whole lung, whereas air-trapping parameters (E/I MLA, RVC856-950) were stable. PRMEmph increased from 34.3 to 35.7% (p < 0.001), whereas PRMNormal decrased from 23.6% to 22.8% (p = 0.012). WT decreased significantly from 1.17 ± 0.18 to 1.14 ± 0.19 mm (p = 0.036) and LA increased significantly from 25.08 ± 4.49 to 25.84 ± 4.87 mm2 (p = 0.041) for the whole lung. The generation-based analysis showed heterogeneous results. CONCLUSION QCT detects short-time progression of emphysema in severe COPD. The changes were partly different among lung lobes and airway generations, indicating that QCT is useful to address the heterogeneity of COPD progression. KEY POINTS • QCT detects short-time progression of emphysema in severe COPD in a 3-month period. • QCT is able to quantify even slight parenchymal changes, which were not detected by spirometry. • QCT is able to address the heterogeneity of COPD, revealing inconsistent changes individual lung lobes and airway generations.
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Computed Tomography Imaging for Novel Therapies of Chronic Obstructive Pulmonary Disease. J Thorac Imaging 2019; 34:202-213. [PMID: 30550404 DOI: 10.1097/rti.0000000000000378] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Novel therapeutic options in chronic obstructive pulmonary disease (COPD) require delicate patient selection and thus demand for expert radiologists visually and quantitatively evaluating high-resolution computed tomography (CT) with additional functional acquisitions such as paired inspiratory-expiratory scans or dynamic airway CT. The differentiation between emphysema-dominant and airway-dominant COPD phenotypes by imaging has immediate clinical value for patient management. Assessment of emphysema severity, distribution patterns, and fissure integrity are essential for stratifying patients for different surgical and endoscopic lung volume reduction procedures. This is supported by quantitative software-based postprocessing of CT data sets, which delivers objective emphysema and airway remodelling metrics. However, the significant impact of scanning and reconstruction parameters, as well as intersoftware variability still hamper comparability between sites and studies. In earlier stage COPD imaging, it is less clear as to what extent quantitative CT might impact decision making and therapy follow-up, as emphysema progression is too slow to realistically be useful as a mid-term outcome measure in an individual, and longitudinal data on airway remodelling are still very limited.
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Su ZQ, Guan WJ, Li SY, Feng JX, Zhou ZQ, Chen Y, Zhong ML, Zhong NS. Evaluation of the Normal Airway Morphology Using Optical Coherence Tomography. Chest 2019; 156:915-925. [DOI: 10.1016/j.chest.2019.06.009] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2019] [Revised: 05/19/2019] [Accepted: 06/12/2019] [Indexed: 10/26/2022] Open
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Park HJ, Lee SM, Choe J, Lee SM, Kim N, Lee JS, Oh YM, Seo JB. Prediction of Treatment Response in Patients with Chronic Obstructive Pulmonary Disease by Determination of Airway Dimensions with Baseline Computed Tomography. Korean J Radiol 2019; 20:304-312. [PMID: 30672170 PMCID: PMC6342755 DOI: 10.3348/kjr.2018.0204] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2018] [Accepted: 08/21/2018] [Indexed: 01/19/2023] Open
Abstract
Objective To determine the predictive factors for treatment responsiveness in patients with chronic obstructive pulmonary disease (COPD) at 1-year follow-up by performing quantitative analyses of baseline CT scans. Materials and Methods COPD patients (n = 226; 212 men, 14 women) were recruited from the Korean Obstructive Lung Disease cohort. Patients received a combination of inhaled long-acting beta-agonists and corticosteroids twice daily for 3 months and subsequently received medications according to the practicing clinician's decision. The emphysema index, air-trapping indices, and airway parameter (Pi10), calculated using both full-width-half-maximum and integral-based half-band (IBHB) methods, were obtained with baseline CT scans. Clinically meaningful treatment response was defined as an absolute increase of ≥ 0.225 L in the forced expiratory volume in 1 second (FEV1) at the one-year follow-up. Multivariate logistic regression analysis was performed to investigate the predictors of an increase in FEV1, and receiver operating characteristic (ROC) analysis was performed to evaluate the performance of the suggested models. Results Treatment response was noted in 47 patients (20.8%). The mean FEV1 increase in responders was 0.36 ± 0.10 L. On univariate analysis, the air-trapping index (ATI) obtained by the subtraction method, ATI of the emphysematous area, and IBHB-measured Pi10 parameter differed significantly between treatment responders and non-responders (p = 0.048, 0.042, and 0.002, respectively). Multivariate analysis revealed that the IBHB-measured Pi10 was the only independent variable predictive of an FEV1 increase (p = 0.003). The adjusted odds ratio was 1.787 (95% confidence interval: 1.220–2.619). The area under the ROC curve was 0.641. Conclusion Measurement of standardized airway dimensions on baseline CT by using a recently validated quantification method can predict treatment responsiveness in COPD patients.
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Affiliation(s)
- Hyo Jung Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Sang Min Lee
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
| | - Jooae Choe
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Sang Min Lee
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Namkug Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Jae Seung Lee
- Department of Pulmonary and Critical Care Medicine, and Clinical Research Center for Chronic Obstructive Airway Diseases, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Yeon Mok Oh
- Department of Pulmonary and Critical Care Medicine, and Clinical Research Center for Chronic Obstructive Airway Diseases, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Joon Beom Seo
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
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Muller PDT, Barbosa GW, O'Donnell DE, Neder JA. Cardiopulmonary and Muscular Interactions: Potential Implications for Exercise (In)tolerance in Symptomatic Smokers Without Chronic Obstructive Pulmonary Disease. Front Physiol 2019; 10:859. [PMID: 31354517 PMCID: PMC6635481 DOI: 10.3389/fphys.2019.00859] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Accepted: 06/20/2019] [Indexed: 12/15/2022] Open
Abstract
Smoking and physical inactivity are important preventable causes of disability and early death worldwide. Reduced exercise tolerance has been described in smokers, even in those who do not fulfill the extant physiological criteria for chronic obstructive pulmonary disease (COPD) and are not particularly sedentary. In this context, it is widely accepted that exercise capacity depends on complex cardio-pulmonary interactions which support oxygen (O2) delivery to muscle mitochondria. Although peripheral muscular factors, O2 transport disturbances (including the effects of increased carboxyhemoglobin) and autonomic nervous system unbalance have been emphasized, other derangements have been more recently described, including early microscopic emphysema, pulmonary microvascular disease, ventilatory and gas exchange inefficiency, and left ventricular diastolic dysfunction. Using an integrative physiological approach, the present review summarizes the recent advances in knowledge on the effects of smoking on the lung-heart-muscle axis under the stress of exercise. Special attention is given to the mechanisms connecting physiological abnormalities such as early cardio-pulmonary derangements, inadequate oxygen delivery and utilization, and generalized bioenergetic disturbances at the muscular level with the negative sensations (sense of heightened muscle effort and breathlessness) that may decrease the tolerance of smokers to physical exercise. A deeper understanding of the systemic effects of smoking in subjects who did not (yet) show evidences of COPD and ischemic heart disease - two devastating smoking related diseases - might prove instrumental to fight their ever-growing burden.
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Affiliation(s)
- Paulo de Tarso Muller
- Laboratory of Respiratory Pathophysiology, Respiratory Division, Department of Medicine, Federal University of Mato Grosso do Sul, Campo Grande, Brazil
| | - Gisele Walter Barbosa
- Laboratory of Respiratory Pathophysiology, Respiratory Division, Department of Medicine, Federal University of Mato Grosso do Sul, Campo Grande, Brazil
| | - Denis E O'Donnell
- Laboratory of Clinical Exercise Physiology, Respiratory Investigation Unit, Division of Respiratory and Critical Care Medicine, Department of Medicine, Queen's University, Kingston, ON, Canada
| | - J Alberto Neder
- Laboratory of Clinical Exercise Physiology, Respiratory Investigation Unit, Division of Respiratory and Critical Care Medicine, Department of Medicine, Queen's University, Kingston, ON, Canada
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Recent Advances in Computed Tomography Imaging in Chronic Obstructive Pulmonary Disease. Ann Am Thorac Soc 2019; 15:281-289. [PMID: 28812906 DOI: 10.1513/annalsats.201705-377fr] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Lung imaging is increasingly being used to diagnose, quantify, and phenotype chronic obstructive pulmonary disease (COPD). Although spirometry is the gold standard for the diagnosis of COPD and for severity staging, the role of computed tomography (CT) imaging has expanded in both clinical practice and research. COPD is a heterogeneous disease with considerable variability in clinical features, radiographic disease, progression, and outcomes. Recent studies have examined the utility of CT imaging in enhancing diagnostic certainty, improving phenotyping, predicting disease progression and prognostication, selecting patients for intervention, and also in furthering our understanding of the complex pathophysiology of this disease. Multiple CT metrics show promise for use as imaging biomarkers in COPD.
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Kirby M, Tanabe N, Tan WC, Zhou G, Obeidat M, Hague CJ, Leipsic J, Bourbeau J, Sin DD, Hogg JC, Coxson HO. Total Airway Count on Computed Tomography and the Risk of Chronic Obstructive Pulmonary Disease Progression. Findings from a Population-based Study. Am J Respir Crit Care Med 2019; 197:56-65. [PMID: 28886252 DOI: 10.1164/rccm.201704-0692oc] [Citation(s) in RCA: 121] [Impact Index Per Article: 24.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
RATIONALE Studies of excised lungs show that significant airway attrition in the "quiet" zone occurs early in chronic obstructive pulmonary disease (COPD). OBJECTIVES To determine if the total number of airways quantified in vivo using computed tomography (CT) reflects early airway-related disease changes and is associated with lung function decline independent of emphysema in COPD. METHODS Participants in the multicenter, population-based, longitudinal CanCOLD (Canadian Chronic Obstructive Lung Disease) study underwent inspiratory/expiratory CT at visit 1; spirometry was performed at four visits over 6 years. Emphysema was quantified as the CT inspiratory low-attenuation areas below -950 Hounsfield units. CT total airway count (TAC) was measured as well as airway inner diameter and wall area using anatomically equivalent airways. MEASUREMENTS AND MAIN RESULTS Participants included never-smokers (n = 286), smokers with normal spirometry at risk for COPD (n = 298), Global Initiative for Chronic Obstructive Lung Disease (GOLD) I COPD (n = 361), and GOLD II COPD (n = 239). TAC was significantly reduced by 19% in both GOLD I and GOLD II compared with never-smokers (P < 0.0001) and by 17% in both GOLD I and GOLD II compared with at-risk participants (P < 0.0001) after adjusting for low-attenuation areas below -950 Hounsfield units. Further analysis revealed parent airways with missing daughter branches had reduced inner diameters (P < 0.0001) and thinner walls (P < 0.0001) compared with those without missing daughter branches. Among all CT measures, TAC had the greatest influence on FEV1 (P < 0.0001), FEV1/FVC (P < 0.0001), and bronchodilator responsiveness (P < 0.0001). TAC was independently associated with lung function decline (FEV1, P = 0.02; FEV1/FVC, P = 0.01). CONCLUSIONS TAC may reflect the airway-related disease changes that accumulate in the "quiet" zone in early/mild COPD, indicating that TAC acquired with commercially available software across various CT platforms may be a biomarker to predict accelerated COPD progression.
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Affiliation(s)
- Miranda Kirby
- 1 The University of British Columbia Centre for Heart Lung Innovation, St. Paul's Hospital, Vancouver, British Columbia, Canada.,2 Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Naoya Tanabe
- 1 The University of British Columbia Centre for Heart Lung Innovation, St. Paul's Hospital, Vancouver, British Columbia, Canada
| | - Wan C Tan
- 1 The University of British Columbia Centre for Heart Lung Innovation, St. Paul's Hospital, Vancouver, British Columbia, Canada
| | - Guohai Zhou
- 1 The University of British Columbia Centre for Heart Lung Innovation, St. Paul's Hospital, Vancouver, British Columbia, Canada
| | - Ma'en Obeidat
- 1 The University of British Columbia Centre for Heart Lung Innovation, St. Paul's Hospital, Vancouver, British Columbia, Canada
| | - Cameron J Hague
- 2 Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Jonathon Leipsic
- 2 Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Jean Bourbeau
- 3 The Montreal Chest Institute, Royal Victoria Hospital, McGill University Health Centre, Montreal, Quebec, Canada; and.,4 Respiratory Epidemiology and Clinical Research Unit, McGill University, Montreal, Quebec, Canada
| | - Don D Sin
- 1 The University of British Columbia Centre for Heart Lung Innovation, St. Paul's Hospital, Vancouver, British Columbia, Canada
| | - James C Hogg
- 1 The University of British Columbia Centre for Heart Lung Innovation, St. Paul's Hospital, Vancouver, British Columbia, Canada
| | - Harvey O Coxson
- 1 The University of British Columbia Centre for Heart Lung Innovation, St. Paul's Hospital, Vancouver, British Columbia, Canada.,2 Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
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Zhang L, Li Z, Meng J, Xie X, Zhang H. Airway quantification using adaptive statistical iterative reconstruction-V on wide-detector low-dose CT: a validation study on lung specimen. Jpn J Radiol 2019; 37:390-398. [PMID: 30820822 DOI: 10.1007/s11604-019-00818-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Accepted: 01/31/2019] [Indexed: 12/31/2022]
Abstract
PURPOSE To evaluate the accuracy of airway quantification of adaptive statistical iterative reconstruction (ASIR)-V on low-dose CT using a human lung specimen. METHOD A lung specimen was scanned on Revolution CT with low-dose settings (20 mAs, 40 mAs and 60 mAs/100 kV) and standard-dose setting (100 mAs/120 kV). CT images were reconstructed using lung kernel with eleven ASIR-V levels from 0 to 100% with 10% interval. ASIR-V level from 0 to 100% with 10% interval was reconstructed on lung kernel. Wall area percentage (%WA) and wall thickness (WT) were measured. RESULTS Radiation dose of 20 mAs, 40 mAs and 60 mAs low-dose settings reduced by 87.6%, 75.2% and 62.8% compared to that on standard dose, respectively. Low-dose settings significantly decreased image SNR (p < 0.05) and increased noise (p < 0.001). ASIR-V level exponentially improved image SNR and linearly decreased image noise (all p < 0.001). The mean airway measurement ratios of low-dose to standard-dose were within 2% variation for %WA and within 3% variation for WT. Most %WA and WT values showed no obvious correlation with ASIR-V levels. CONCLUSION ASIR-V showed to improve image quality in low radiation dose. However, low-dose settings and ASIR-V strength did not significantly influence airway quantification values, although variation in measurements slightly increased with dose reduction.
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Affiliation(s)
- Lin Zhang
- Department of Radiology, Shanghai General Hospital of Nanjing Medical University, No. 100 Haining Road, Shanghai, 200080, People's Republic of China
| | - Zhengyu Li
- Department of Radiology, Shanghai General Hospital of Nanjing Medical University, No. 100 Haining Road, Shanghai, 200080, People's Republic of China
| | - Jie Meng
- Department of Radiology, Shanghai General Hospital of Nanjing Medical University, No. 100 Haining Road, Shanghai, 200080, People's Republic of China
| | - Xueqian Xie
- Department of Radiology, Shanghai General Hospital of Nanjing Medical University, No. 100 Haining Road, Shanghai, 200080, People's Republic of China.
| | - Hao Zhang
- Department of Radiology, Shanghai General Hospital of Nanjing Medical University, No. 100 Haining Road, Shanghai, 200080, People's Republic of China.
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Stoel BC, Stolk J, Bakker ME, Parr DG. Regional lung densities in alpha-1 antitrypsin deficiency compared to predicted values. Respir Res 2019; 20:45. [PMID: 30819163 PMCID: PMC6396535 DOI: 10.1186/s12931-019-1012-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Accepted: 02/20/2019] [Indexed: 12/25/2022] Open
Abstract
Background We developed a method to calculate a standard score for lung tissue mass derived from CT scan images from a control group without respiratory disease. We applied the method to images from subjects with emphysema associated with alpha-1 antitrypsin deficiency (AATD) and used it to study regional patterns of differential tissue mass. Methods We explored different covariates in 76 controls. Standardization was applied to facilitate comparability between different CT scanners and a standard Z-score (Standard Mass Score, SMS) was developed, representing lung tissue loss compared to normal lung mass. This normative data was defined for the entire lungs and for delineated apical, central and basal regions. The agreement with DLCO%pred was explored in a data set of 180 patients with emphysema who participated in a trial of alpha-1-antitrypsin augmentation treatment (RAPID). Results Large differences between emphysematous and normal tissue of more than 10 standard deviations were found. There was reasonable agreement between SMS and DLCO%pred for the global densitometry (κ = 0.252, p < 0.001), varying from κ = 0.138 to κ = 0.219 and 0.264 (p < 0.001), in the apical, central and basal region, respectively. SMS and DLCO%pred correlated consistently across apical, central and basal regions. The SMS distribution over the different lung regions showed a distinct pattern suggesting that emphysema due to severe AATD develops from basal to central and ultimately apical regions. Conclusions Standardization and normalization of lung densitometry is feasible and the adoption of the developed principles helps to characterize the distribution of emphysema, required for clinical decision making. Electronic supplementary material The online version of this article (10.1186/s12931-019-1012-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Berend C Stoel
- Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
| | - Jan Stolk
- Department of Pulmonology, Leiden University Medical Center, Leiden, The Netherlands
| | - M Els Bakker
- Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - David G Parr
- Department of Respiratory Medicine, University Hospitals of Coventry and Warwickshire, Clifford Bridge Road, Coventry, UK
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Gut-Gobert C, Cavaillès A, Dixmier A, Guillot S, Jouneau S, Leroyer C, Marchand-Adam S, Marquette D, Meurice JC, Desvigne N, Morel H, Person-Tacnet C, Raherison C. Women and COPD: do we need more evidence? Eur Respir Rev 2019; 28:28/151/180055. [PMID: 30814138 PMCID: PMC9488562 DOI: 10.1183/16000617.0055-2018] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2018] [Accepted: 09/21/2018] [Indexed: 01/20/2023] Open
Abstract
The increasingly female face of chronic obstructive pulmonary disease (COPD) prevalence among women has equalled that of men since 2008, due in part to increased tobacco use among women worldwide and exposure to biomass fuels. This finding is supported by a number of characteristics. There is evidence of susceptibility to smoking and other airborne contaminants, along with epidemiological and phenotypic manifestations. COPD has thus become the leading cause of death in women in the USA. The clinical presentation is characterised by increasingly pronounced dyspnoea with a marked tendency towards anxiety and depression, undernutrition, nonsmall cell lung cancer (especially adenocarcinoma) and osteoporosis. Quality of life is also more significantly impacted. The theories advanced to explain these differences involve the role played by oestrogens, impaired gas exchange in the lungs and smoking habits. While these differences require appropriate therapeutic responses (smoking cessation, pulmonary rehabilitation, long-term oxygen therapy), barriers to the treatment of women with COPD include greater under-diagnosis than in men, fewer spirometry tests and medical consultations. Faced with this serious public health problem, we need to update and adapt our knowledge to the epidemiological changes. The face of COPD is increasingly female. We need more evidence and a change in how the disease is managed. http://ow.ly/zueL30mWqlS
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Affiliation(s)
- Christophe Gut-Gobert
- G.E.T.B.O. (Groupe d'Etude de la Thrombose de Bretagne Occidentale), Université Européenne de Bretagne, Université de Brest, EA3878, IFR148, Hôpital La Cavale Blanche, Département de Médecine Interne et Pneumologie, Brest, France
| | - Arnaud Cavaillès
- Institut du Thorax, CHU de Nantes, Dept of Pulmonology, Nantes, France
| | - Adrien Dixmier
- Dept of Pulmonology, Orléans Regional Hospital, Orléans, France
| | - Stéphanie Guillot
- Unité d'Explorations Fonctionnelles Respiratoires, CHRU Rennes, Rennes, France
| | - Stéphane Jouneau
- Service de Pneumologie, Hôpital Pontchaillou, Rennes, France.,IRSET UMR 1085, Université de Rennes 1, Rennes, France
| | - Christophe Leroyer
- G.E.T.B.O. (Groupe d'Etude de la Thrombose de Bretagne Occidentale), Université Européenne de Bretagne, Université de Brest, EA3878, IFR148, Hôpital La Cavale Blanche, Département de Médecine Interne et Pneumologie, Brest, France
| | - Sylvain Marchand-Adam
- Université François Rabelais Faculté de Médecine de Tours, Inserm 1100, CHRU de Tours Service de Pneumologie, Tours, France
| | - David Marquette
- Dept of Pulmonary Medicine, Centre Hospitalier Bretagne Atlantique, Vannes, France
| | - Jean-Claude Meurice
- Dept of Pulmonology Centre Hospitalier de l'Université de Poitiers, Poitiers, France
| | | | - Hugues Morel
- Dept of Pulmonology, Orléans Regional Hospital, Orléans, France
| | | | - Chantal Raherison
- Service des Maladies Respiratoires, CHU Bordeaux, Epicene U1219 Université de Bordeaux, Bordeaux, France
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Janssen R, Piscaer I, Franssen FME, Wouters EFM. Emphysema: looking beyond alpha-1 antitrypsin deficiency. Expert Rev Respir Med 2019; 13:381-397. [DOI: 10.1080/17476348.2019.1580575] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Rob Janssen
- Department of Pulmonary Medicine, Canisius-Wilhelmina Hospital, Nijmegen, The Netherlands
| | - Ianthe Piscaer
- Department of Respiratory Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
- NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Frits M. E. Franssen
- Department of Respiratory Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
- NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Center, Maastricht, The Netherlands
- CIRO, Center of Expertise for Chronic Organ Failure, Horn, The Netherlands
| | - Emiel F. M. Wouters
- Department of Respiratory Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
- NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Center, Maastricht, The Netherlands
- CIRO, Center of Expertise for Chronic Organ Failure, Horn, The Netherlands
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Schreuder A, Jacobs C, Gallardo-Estrella L, Prokop M, Schaefer-Prokop CM, van Ginneken B. Predicting all-cause and lung cancer mortality using emphysema score progression rate between baseline and follow-up chest CT images: A comparison of risk model performances. PLoS One 2019; 14:e0212756. [PMID: 30789954 PMCID: PMC6383935 DOI: 10.1371/journal.pone.0212756] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Accepted: 02/10/2019] [Indexed: 02/05/2023] Open
Abstract
Purpose Normalized emphysema score is a protocol-robust CT biomarker of mortality. We aimed to improve mortality prediction by including the emphysema score progression rate–its change over time–into the models. Method and materials CT scans from 6000 National Lung Screening Trial CT arm participants were included. Of these, 1810 died (445 lung cancer-specific). The remaining 4190 survivors were sampled with replacement up to 24432 to approximate the full cohort. Three overlapping subcohorts were formed which required participants to have images from specific screening rounds. Emphysema scores were obtained after resampling, normalization, and bullae cluster analysis of the original images. Base models contained solely the latest emphysema score. Progression models included emphysema score progression rate. Models were adjusted by including baseline age, sex, BMI, smoking status, smoking intensity, smoking duration, and previous COPD diagnosis. Cox proportional hazard models predicting all-cause and lung cancer mortality were compared by calculating the area under the curve per year follow-up. Results In the subcohort of participants with baseline and first annual follow-up scans, the analysis was performed on 4940 participants (23227 after resampling). Area under the curve for all-cause mortality predictions of the base and progression models 6 years after baseline were 0.564 (0.564 to 0.565) and 0.569 (0.568 to 0.569) when unadjusted, and 0.704 (0.703 to 0.704) to 0.705 (0.704 to 0.705) when adjusted. The respective performances predicting lung cancer mortality were 0.638 (0.637 to 0.639) and 0.643 (0.642 to 0.644) when unadjusted, and 0.724 (0.723 to 0.725) and 0.725 (0.725 to 0.726) when adjusted. Conclusion Including emphysema score progression rate into risk models shows no clinically relevant improvement in mortality risk prediction. This is because scan normalization does not adjust for an overall change in lung density. Adjusting for changes in smoking behavior is likely required to make this a clinically useful measure of emphysema progression.
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Affiliation(s)
- Anton Schreuder
- Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands
- * E-mail:
| | - Colin Jacobs
- Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands
| | - Leticia Gallardo-Estrella
- Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands
- Thirona, Nijmegen, the Netherlands
| | - Mathias Prokop
- Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands
| | - Cornelia M. Schaefer-Prokop
- Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands
- Department of Radiology, Meander Medisch Centrum, Amersfoort, the Netherlands
| | - Bram van Ginneken
- Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, the Netherlands
- Fraunhofer MEVIS, Bremen, Germany
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Yu N, Yuan H, Duan HF, Ma JC, Ma GM, Guo YM, Wu F. Determination of vascular alteration in smokers by quantitative computed tomography measurements. Medicine (Baltimore) 2019; 98:e14438. [PMID: 30762753 PMCID: PMC6408080 DOI: 10.1097/md.0000000000014438] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
A new method of quantitative computed tomography (CT) measurements of pulmonary vessels are applicable to morphological studies and may be helpful in defining the progression of emphysema in smokers. However, limited data are available on the relationship between the smoking status and pulmonary vessels alteration established in longitudinal observations. Therefore, we investigated the change of pulmonary vessels on CTs in a longitudinal cohort of smokers.Chest CTs were available for 287 current smokers, 439 non-smokers, and 80 former smokers who quit smoking at least 2 years after the baseline CT. CT images obtained at the baseline and 1 year later were assessed by a new quantitative CT measurement method, computing the total number of pulmonary vessels (TNV), mean lung density (MLD), and the percentage of low-attenuation areas at a threshold of -950 (density attenuation area [LAA]%950). Analysis of variance (ANOVA) and the independent sample t test were used to estimate the influence of the baseline parameters. The t paired test was employed to evaluate the change between the baseline and follow-up results.The current smokers related to have higher whole-lung MLD, as well as less and lower TNV values than the non-smokers (P <.05). But no significant differences in LAA%950 were found between smokers and non-smokers. After one year, the increase in LAA%950 was more rapid in the current (additional 0.3% per year, P <. 05-.01) than in the former smokers (additional 0.2% per year, P = .3). Additionally, the decline in TNV was faster in the current (additional -1.3 per year, P <.05-.01) than that in the former smokers (additional -0.2 per year, P = .6). Current smoke, pack-years, weight, and lung volume independently predicted TNV at baseline (P <.001) in multivariate analysis.The findings of this study reveal that the decline in the pulmonary vessels in smokers can be measured and related to their smoking status.
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Affiliation(s)
- Nan Yu
- Department of Radiology, Affiliated Zhongshan Hospital of Dalian University, Da Lian
- Department of Radiology, The Shaanxi university of Chinese medicine
| | - Hui Yuan
- Department of Radiology, The Shaanxi university of Chinese medicine
| | - Hai-feng Duan
- Department of Radiology, The Shaanxi university of Chinese medicine
| | - Jun-chao Ma
- Department of Radiology, The Shaanxi university of Chinese medicine
| | - Guang-ming Ma
- Department of Radiology, The Shaanxi university of Chinese medicine
| | - You-min Guo
- Department of Radiology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Fei Wu
- Department of Radiology, Affiliated Zhongshan Hospital of Dalian University, Da Lian
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Gagnat AA, Gulsvik A, Bakke P, Gjerdevik M. Comparison of two lung cancer screening scores among patients with chronic obstructive pulmonary disease: A community study. CLINICAL RESPIRATORY JOURNAL 2019; 13:114-119. [PMID: 30597746 DOI: 10.1111/crj.12988] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2018] [Revised: 10/16/2018] [Accepted: 12/24/2018] [Indexed: 12/17/2022]
Abstract
INTRODUCTION Based on the National Lung Cancer Screening Trial (NLST), guidelines on screening programs for lung cancer have recommended low-dose computed tomography (LDCT). De Torres et al made a score for COPD patients (COPD-LUCSS) to improve their selection criteria. OBJECTIVE To examine and compare the discriminating value of both scores in a community-based cohort of COPD patients. METHODS Four hundred and twenty-two ever-smokers with COPD from the GenKOLS study in Bergen were merged with the Cancer Registry of Norway. We divided the patients into groups of high and low risk according to the COPD-LUCSS and the NLST criteria. Cox regression and logistic regression were used to analyse the associations between the scores and lung cancer. We used Harrell's C and area under the curve (AUC) to estimate discriminating values and to compare the models. RESULTS Hazard ratio for the high risk vs the low risk in the COPD-LUCSS was 3.0 (1.4-6.5 95% CI), P < 0.01. Hazard ratio for the NLST criteria was 2.2 (95% CI 1.1-4.5), P < 0.05. Harrell's C was 0.63 for the COPD-LUCSS and 0.59 for the NLST selection criteria. AUC was 0.61 for COPD-LUCSS and 0.59 for NLST criteria. Comparing tests showed no differences (P = 0.76). CONCLUSION Although the COPD-LUCSS and the NLST criteria were associated with increased risk of lung cancer, the AUC and Harrell's C values showed that these models have poor discriminating abilities in our cohort of COPD patients. The COPD-LUCSS was not significantly better than the NLST criteria.
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Affiliation(s)
- Ane Aamli Gagnat
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Amund Gulsvik
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Per Bakke
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Miriam Gjerdevik
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
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