1
|
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.
Collapse
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
| |
Collapse
|
2
|
Wielpütz MO, Mall MA. Therapeutic improvement of CFTR function and reversibility of bronchiectasis in cystic fibrosis. Eur Respir J 2024; 63:2400234. [PMID: 38548272 DOI: 10.1183/13993003.00234-2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 02/14/2024] [Indexed: 04/02/2024]
Affiliation(s)
- Mark O Wielpütz
- Department of Diagnostic and Interventional Radiology, 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 at University Hospital Heidelberg, Heidelberg, Germany
| | - Marcus A Mall
- Department of Pediatric Respiratory Medicine, Immunology and Critical Care Medicine, Charité-Universitätsmedizin Berlin, Berlin, Germany
- German Center for Lung Research (DZL), associated partner site, Berlin, Germany
- Berlin Institute of Health (BIH) at Charité-Universitätsmedizin Berlin, Berlin, Germany
| |
Collapse
|
3
|
Zhang M, Wu Y, Zhang H, Qin Y, Zheng H, Tang W, Arnold C, Pei C, Yu P, Nan Y, Yang G, Walsh S, Marshall DC, Komorowski M, Wang P, Guo D, Jin D, Wu Y, Zhao S, Chang R, Zhang B, Lu X, Qayyum A, Mazher M, Su Q, Wu Y, Liu Y, Zhu Y, Yang J, Pakzad A, Rangelov B, Estepar RSJ, Espinosa CC, Sun J, Yang GZ, Gu Y. Multi-site, Multi-domain Airway Tree Modeling. Med Image Anal 2023; 90:102957. [PMID: 37716199 DOI: 10.1016/j.media.2023.102957] [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: 03/27/2023] [Revised: 06/07/2023] [Accepted: 09/04/2023] [Indexed: 09/18/2023]
Abstract
Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach of pulmonary airway segmentation that is closer to the limit of image resolution. Since EXACT'09 pulmonary airway segmentation, limited effort has been directed to the quantitative comparison of newly emerged algorithms driven by the maturity of deep learning based approaches and extensive clinical efforts for resolving finer details of distal airways for early intervention of pulmonary diseases. Thus far, public annotated datasets are extremely limited, hindering the development of data-driven methods and detailed performance evaluation of new algorithms. To provide a benchmark for the medical imaging community, we organized the Multi-site, Multi-domain Airway Tree Modeling (ATM'22), which was held as an official challenge event during the MICCAI 2022 conference. ATM'22 provides large-scale CT scans with detailed pulmonary airway annotation, including 500 CT scans (300 for training, 50 for validation, and 150 for testing). The dataset was collected from different sites and it further included a portion of noisy COVID-19 CTs with ground-glass opacity and consolidation. Twenty-three teams participated in the entire phase of the challenge and the algorithms for the top ten teams are reviewed in this paper. Both quantitative and qualitative results revealed that deep learning models embedded with the topological continuity enhancement achieved superior performance in general. ATM'22 challenge holds as an open-call design, the training data and the gold standard evaluation are available upon successful registration via its homepage (https://atm22.grand-challenge.org/).
Collapse
Affiliation(s)
- Minghui Zhang
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, China; Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, 200240, China; Department of Automation, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Yangqian Wu
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, China; Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, 200240, China; Department of Automation, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Hanxiao Zhang
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Yulei Qin
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Hao Zheng
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Wen Tang
- InferVision Medical Technology Co., Ltd., Beijing, China
| | | | - Chenhao Pei
- InferVision Medical Technology Co., Ltd., Beijing, China
| | - Pengxin Yu
- InferVision Medical Technology Co., Ltd., Beijing, China
| | - Yang Nan
- Imperial College London, London, UK
| | | | | | | | | | - Puyang Wang
- Alibaba DAMO Academy, 969 West Wen Yi Road, Hangzhou, Zhejiang, China
| | - Dazhou Guo
- Alibaba DAMO Academy USA, 860 Washington Street, 8F, NY, USA
| | - Dakai Jin
- Alibaba DAMO Academy USA, 860 Washington Street, 8F, NY, USA
| | - Ya'nan Wu
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
| | - Shuiqing Zhao
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
| | - Runsheng Chang
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
| | - Boyu Zhang
- A.I R&D Center, Sanmed Biotech Inc., No. 266 Tongchang Road, Xiangzhou District, Zhuhai, Guangdong, China
| | - Xing Lu
- A.I R&D Center, Sanmed Biotech Inc., T220 Trade st. SanDiego, CA, USA
| | - Abdul Qayyum
- ENIB, UMR CNRS 6285 LabSTICC, Brest, 29238, France
| | - Moona Mazher
- Department of Computer Engineering and Mathematics, University Rovira I Virgili, Tarragona, Spain
| | - Qi Su
- Shanghai Jiao Tong University, Shanghai, China
| | - Yonghuang Wu
- School of Information Science and Technology, Fudan University, Shanghai, China
| | - Ying'ao Liu
- University of Science and Technology of China, Hefei, Anhui, China
| | | | - Jiancheng Yang
- Dianei Technology, Shanghai, China; EPFL, Lausanne, Switzerland
| | - Ashkan Pakzad
- Medical Physics and Biomedical Engineering Department, University College London, London, UK
| | - Bojidar Rangelov
- Center for Medical Image Computing, University College London, London, UK
| | | | | | - Jiayuan Sun
- Department of Respiratory and Critical Care Medicine, Department of Respiratory Endoscopy, Shanghai Chest Hospital, Shanghai, China.
| | - Guang-Zhong Yang
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, China.
| | - Yun Gu
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, China; Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, 200240, China; Department of Automation, Shanghai Jiao Tong University, Shanghai, 200240, China.
| |
Collapse
|
4
|
Dettmer S, Weinheimer O, Sauer-Heilborn A, Lammers O, Wielpütz MO, Fuge J, Welte T, Wacker F, Ringshausen FC. Qualitative and quantitative evaluation of computed tomography changes in adults with cystic fibrosis treated with elexacaftor-tezacaftor-ivacaftor: a retrospective observational study. Front Pharmacol 2023; 14:1245885. [PMID: 37808186 PMCID: PMC10552920 DOI: 10.3389/fphar.2023.1245885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 09/11/2023] [Indexed: 10/10/2023] Open
Abstract
Introduction: The availability of highly effective triple cystic fibrosis transmembrane conductance regulator (CFTR) modulator combination therapy with elexacaftor-tezacaftor-ivacaftor (ETI) has improved pulmonary outcomes and quality of life of people with cystic fibrosis (pwCF). The aim of this study was to assess computed tomography (CT) changes under ETI visually with the Brody score and quantitatively with dedicated software, and to correlate CT measures with parameters of clinical response. Methods: Twenty two adult pwCF with two consecutive CT scans before and after ETI treatment initiation were retrospectively included. CT was assessed visually employing the Brody score and quantitatively by YACTA, a well-evaluated scientific software computing airway dimensions and lung parenchyma with wall percentage (WP), wall thickness (WT), lumen area (LA), bronchiectasis index (BI), lung volume and mean lung density (MLD) as parameters. Changes in CT metrics were evaluated and the visual and quantitative parameters were correlated with each other and with clinical changes in sweat chloride concentration, spirometry [percent predicted of forced expiratory volume in one second (ppFEV1)] and body mass index (BMI). Results: The mean (SD) Brody score improved with ETI [55 (12) vs. 38 (15); p < 0.001], incl. sub-scores for mucus plugging, peribronchial thickening, and parenchymal changes (all p < 0.001), but not for bronchiectasis (p = 0.281). Quantitatve WP (p < 0.001) and WT (p = 0.004) were reduced, conversely LA increased (p = 0.003), and BI improved (p = 0.012). Lung volume increased (p < 0.001), and MLD decreased (p < 0.001) through a reduction of ground glass opacity areas (p < 0.001). Changes of the Brody score correlated with those of quantitative parameters, exemplarily WT with the sub-score for mucus plugging (r = 0.730, p < 0.001) and peribronchial thickening (r = 0.552, p = 0.008). Changes of CT parameters correlated with those of clinical response parameters, in particular ppFEV1 with the Brody score (r = -0.606, p = 0.003) and with WT (r = -0.538, p = 0.010). Discussion: Morphological treatment response to ETI can be assessed using the Brody score as well as quantitative CT parameters. Changes in CT correlated with clinical improvements. The quantitative analysis with YACTA proved to be an objective, reproducible and simple method for monitoring lung disease, particularly with regard to future interventional clinical trials.
Collapse
Affiliation(s)
- Sabine Dettmer
- Institute of Diagnostic and Interventional Radiology, Hannover Medical School, Hannover, Germany
- Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Member of the German Center for Lung Research (DZL), Hannover, Germany
| | - Oliver Weinheimer
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
| | - Annette Sauer-Heilborn
- Department of Respiratory Medicine and Infectious Diseases, Hannover Medical School, Hannover, Germany
| | - Oliver Lammers
- Institute of Diagnostic and Interventional Radiology, Hannover Medical School, Hannover, Germany
| | - Mark O. Wielpütz
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
| | - Jan Fuge
- Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Member of the German Center for Lung Research (DZL), Hannover, Germany
- Department of Respiratory Medicine and Infectious Diseases, Hannover Medical School, Hannover, Germany
| | - Tobias Welte
- Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Member of the German Center for Lung Research (DZL), Hannover, Germany
- Department of Respiratory Medicine and Infectious Diseases, Hannover Medical School, Hannover, Germany
| | - Frank Wacker
- Institute of Diagnostic and Interventional Radiology, Hannover Medical School, Hannover, Germany
- Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Member of the German Center for Lung Research (DZL), Hannover, Germany
| | - Felix C. Ringshausen
- Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Member of the German Center for Lung Research (DZL), Hannover, Germany
- Department of Respiratory Medicine and Infectious Diseases, Hannover Medical School, Hannover, Germany
- European Reference Network on Rare and Complex Respiratory Diseases (ERN-LUNG), Frankfurt, Germany
| |
Collapse
|
5
|
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.
Collapse
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.
| |
Collapse
|
6
|
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.
Collapse
Affiliation(s)
- Philip Konietzke
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), 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
| |
Collapse
|
7
|
FitzMaurice TS, McCann C, Nazareth D, Hawkes S, Shaw M, McNamara PS, Walshaw M. Feasibility of dynamic chest radiography to calculate lung volumes in adult people with cystic fibrosis: a pilot study. BMJ Open Respir Res 2023; 10:e001309. [PMID: 37147023 PMCID: PMC10163553 DOI: 10.1136/bmjresp-2022-001309] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 04/21/2023] [Indexed: 05/07/2023] Open
Abstract
INTRODUCTION Dynamic chest radiography (DCR) is a novel, low-dose, real-time digital imaging system where software identifies moving thoracic structures and can automatically calculate lung areas. In an observational, prospective, non-controlled, single-centre pilot study, we compared it with whole-body plethysmography (WBP) in the measurement of lung volume subdivisions in people with cystic fibrosis (pwCF). METHODS Lung volume subdivisions were estimated by DCR using projected lung area (PLA) during deep inspiration, tidal breathing and full expiration, and compared with same-day WBP in 20 adult pwCF attending routine review. Linear regression models to predict lung volumes from PLA were developed. RESULTS Total lung area (PLA at maximum inspiration) correlated with total lung capacity (TLC) (r=0.78, p<0.001), functional residual lung area with functional residual capacity (FRC) (r=0.91, p<0.001), residual lung area with residual volume (RV) (r=0.82, p=0.001) and inspiratory lung area with inspiratory capacity (r=0.72, p=0.001). Despite the small sample size, accurate models were developed for predicting TLC, RV and FRC. CONCLUSION DCR is a promising new technology that can be used to estimate lung volume subdivisions. Plausible correlations between plethysmographic lung volumes and DCR lung areas were identified. Further studies are needed to build on this exploratory work in both pwCF and individuals without CF. TRIAL REGISTRATION NUMBER ISRCTN64994816.
Collapse
Affiliation(s)
- Thomas Simon FitzMaurice
- Department of Respiratory Medicine, Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, UK
- Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
| | - Caroline McCann
- Department of Radiology, Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, UK
| | - Dilip Nazareth
- Department of Respiratory Medicine, Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, UK
- Institute of Infection and Global Health, University of Liverpool, Liverpool, UK
| | - Scott Hawkes
- Department of Pulmonary Physiology, Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, UK
| | - Matthew Shaw
- Research Department, Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, UK
| | - Paul Stephen McNamara
- Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
- Department of Child Health (University of Liverpool), Institute in the Park, Alder Hey Children's Hospital NHS Foundation Trust, Liverpool, UK
| | - Martin Walshaw
- Department of Respiratory Medicine, Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, UK
- Institute of Infection and Global Health, University of Liverpool, Liverpool, UK
| |
Collapse
|
8
|
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.
Collapse
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
| |
Collapse
|
9
|
Weinheimer O, Konietzke P, Wagner WL, Weber D, Newman B, Galbán CJ, Kauczor HU, Mall MA, Robinson TE, Wielpütz MO. MDCT-based longitudinal automated airway and air trapping analysis in school-age children with mild cystic fibrosis lung disease. Front Pediatr 2023; 11:1068103. [PMID: 36816383 PMCID: PMC9932328 DOI: 10.3389/fped.2023.1068103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 01/03/2023] [Indexed: 02/05/2023] Open
Abstract
OBJECTIVES Quantitative computed tomography (QCT) offers some promising markers to quantify cystic fibrosis (CF)-lung disease. Air trapping may precede irreversible bronchiectasis; therefore, the temporal interdependencies of functional and structural lung disease need to be further investigated. We aim to quantify airway dimensions and air trapping on chest CT of school-age children with mild CF-lung disease over two years. METHODS Fully-automatic software analyzed 144 serial spirometer-controlled chest CT scans of 36 children (median 12.1 (10.2-13.8) years) with mild CF-lung disease (median ppFEV1 98.5 (90.8-103.3) %) at baseline, 3, 12 and 24 months. The airway wall percentage (WP5-10), bronchiectasis index (BEI), as well as severe air trapping (A3) were calculated for the total lung and separately for all lobes. Mixed linear models were calculated, considering the lobar distribution of WP5-10, BEI and A3 cross-sectionally and longitudinally. RESULTS WP5-10 remained stable (P = 0.248), and BEI changed from 0.41 (0.28-0.7) to 0.54 (0.36-0.88) (P = 0.156) and A3 from 2.26% to 4.35% (P = 0.086) showing variability over two years. ppFEV1 was also stable (P = 0.276). A robust mixed linear model showed a cross-sectional, regional association between WP5-10 and A3 at each timepoint (P < 0.001). Further, BEI showed no cross-sectional, but another mixed model showed short-term longitudinal interdependencies with air trapping (P = 0.003). CONCLUSIONS Robust linear/beta mixed models can still reveal interdependencies in medical data with high variability that remain hidden with simpler statistical methods. We could demonstrate cross-sectional, regional interdependencies between wall thickening and air trapping. Further, we show short-term regional interdependencies between air trapping and an increase in bronchiectasis. The data indicate that regional air trapping may precede the development of bronchiectasis. Quantitative CT may capture subtle disease progression and identify regional and temporal interdependencies of distinct manifestations of CF-lung disease.
Collapse
Affiliation(s)
- Oliver Weinheimer
- Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany.,Translational Lung Research Center (TLRC), German Lung Research Center (DZL), University of Heidelberg, Heidelberg, Germany.,Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Philip Konietzke
- Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany.,Translational Lung Research Center (TLRC), German Lung Research Center (DZL), University of Heidelberg, Heidelberg, Germany.,Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Willi L Wagner
- Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany.,Translational Lung Research Center (TLRC), German Lung Research Center (DZL), University of Heidelberg, Heidelberg, Germany.,Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Dorothea Weber
- Translational Lung Research Center (TLRC), German Lung Research Center (DZL), University of Heidelberg, Heidelberg, Germany.,Institute of Medical Biometry and Informatics (IMBI), University of Heidelberg, Heidelberg, Germany
| | - Beverly Newman
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, United States
| | - Craig J Galbán
- Department of Radiology, University of Michigan, Ann Arbor, United States
| | - Hans-Ulrich Kauczor
- Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany.,Translational Lung Research Center (TLRC), German Lung Research Center (DZL), University of Heidelberg, Heidelberg, Germany.,Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Marcus A Mall
- Department of Pediatric Pulmonology, Immunology and Intensive Care Medicine, Charité-Universitätsmedizin Berlin, Berlin, Germany.,Berlin Institute of Health @ Charité-Universitätsmedizin Berlin, Berlin, Germany.,German Center for Lung Research (DZL), Associated Partner Site, Berlin, Germany
| | - Terry E Robinson
- Department of Pediatrics, Center of Excellence in Pulmonary Biology, Stanford University School of Medicine, Stanford, CA, United States
| | - Mark O Wielpütz
- Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany.,Translational Lung Research Center (TLRC), German Lung Research Center (DZL), University of Heidelberg, Heidelberg, Germany.,Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| |
Collapse
|
10
|
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.
Collapse
|
11
|
Kahnert K, Jörres RA, Jobst B, Wielpütz MO, Seefelder A, Hackl CM, Trudzinski FC, Watz H, Bals R, Behr J, Rabe KF, Vogelmeier CF, Alter P, Welte T, Herth F, Kauczor H, Biederer J. Association of coronary artery calcification with clinical and physiological characteristics in patients with COPD: Results from COSYCONET. Respir Med 2022; 204:107014. [DOI: 10.1016/j.rmed.2022.107014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 09/28/2022] [Accepted: 10/13/2022] [Indexed: 10/31/2022]
|
12
|
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.
Collapse
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
| |
Collapse
|
13
|
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.
Collapse
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:
| |
Collapse
|
14
|
Perossi J, Koenigkam-Santos M, Perossi L, dos Santos DO, Simoni LHDS, de Souza HCD, Gastaldi AC. Correlation among clinical, functional and morphological indexes of the respiratory system in non-cystic fibrosis bronchiectasis patients. PLoS One 2022; 17:e0269897. [PMID: 35793286 PMCID: PMC9258820 DOI: 10.1371/journal.pone.0269897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 05/29/2022] [Indexed: 12/01/2022] Open
Abstract
BACKGROUND Non-cystic fibrosis bronchiectasis (NCFB) is a heterogeneous disease, which assessment and severity can't be defined by one particular instrument but using a multidimensional score. Thus, in additional to traditional methods, alternative tools have been developed to assist these patients' evaluation. OBJECTIVE To correlate functional and morphological indexes with severity and dyspnea in NCFB patients, focusing on the correlation between the impulse oscillometry system (IOS) and the quantitative analysis of computed tomography (CT). METHODS Clinically stable NCFB patients, between 18 and 80 years old were submitted to clinical, functional and morphological evaluations assessed by Bronchiectasis Severity Index (BSI) and Medical Research Council (MRC) scale; spirometry and IOS; and subjective and quantitative Chest CT scans analysis, respectively. RESULTS This study included 38 patients. The best correlations obtained between functional and morphological airway indexes were: resistance at 5 Hz-R5 and the normalized thickness of bronchial walls-Pi10 (r = 0.57), and the mean forced expiratory flow (FEF25-75%) and CT score (r = -0.39). BSI as well as MRC showed higher correlations with the quantitative automated analysis of CT (BSI and Pi10: r = 0.41; MRC and Pi10: r = 0.35) than with subjective CT score (BSI and CT score: r = 0.41; MRC and CT score: r = 0.15); and moderate and weak correlations were obtained on both functional airway indexes (BSI and peripheral airways resistance - R5-R20: r = 0.53; BSI and forced expiratory volume at the first second-FEV1: R = -0,64; MRC and R5-R20: r = 0.42; and MRC and VEF1: r = -0.45). CONCLUSION In NCFB patients, compartmentalized methods for assessing the respiratory system (IOS and the automated quantitative CT analysis) have a good correlation with severity and dyspnea.
Collapse
Affiliation(s)
- Jéssica Perossi
- Department of Health Sciences, Graduate Program in Functional Performance, Ribeirão Preto Medical School, Ribeirão Preto, São Paulo, Brazil
| | - Marcel Koenigkam-Santos
- Department of Medical Imaging, Hematology and Clinical Oncology, Ribeirão Preto Medical School, Ribeirão Preto, São Paulo, Brazil
| | - Larissa Perossi
- Department of Health Sciences, Graduate Program in Functional Performance, Ribeirão Preto Medical School, Ribeirão Preto, São Paulo, Brazil
| | - Daniele Oliveira dos Santos
- Department of Health Sciences, Graduate Program in Functional Performance, Ribeirão Preto Medical School, Ribeirão Preto, São Paulo, Brazil
| | - Letícia Helena de Souza Simoni
- Department of Health Sciences, Graduate Program in Functional Performance, Ribeirão Preto Medical School, Ribeirão Preto, São Paulo, Brazil
| | - Hugo Celso Dutra de Souza
- Department of Health Sciences, Graduate Program in Functional Performance, Ribeirão Preto Medical School, Ribeirão Preto, São Paulo, Brazil
| | - Ada Clarice Gastaldi
- Department of Health Sciences, Graduate Program in Functional Performance, Ribeirão Preto Medical School, Ribeirão Preto, São Paulo, Brazil
| |
Collapse
|
15
|
Ciet P, Bertolo S, Ros M, Casciaro R, Cipolli M, Colagrande S, Costa S, Galici V, Gramegna A, Lanza C, Lucca F, Macconi L, Majo F, Paciaroni A, Parisi GF, Rizzo F, Salamone I, Santangelo T, Scudeller L, Saba L, Tomà P, Morana G. State-of-the-art review of lung imaging in cystic fibrosis with recommendations for pulmonologists and radiologists from the "iMAging managEment of cySTic fibROsis" (MAESTRO) consortium. Eur Respir Rev 2022; 31:31/163/210173. [PMID: 35321929 DOI: 10.1183/16000617.0173-2021] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 12/20/2021] [Indexed: 12/15/2022] Open
Abstract
OBJECTIVE Imaging represents an important noninvasive means to assess cystic fibrosis (CF) lung disease, which remains the main cause of morbidity and mortality in CF patients. While the development of new imaging techniques has revolutionised clinical practice, advances have posed diagnostic and monitoring challenges. The authors aim to summarise these challenges and make evidence-based recommendations regarding imaging assessment for both clinicians and radiologists. STUDY DESIGN A committee of 21 experts in CF from the 10 largest specialist centres in Italy was convened, including a radiologist and a pulmonologist from each centre, with the overall aim of developing clear and actionable recommendations for lung imaging in CF. An a priori threshold of at least 80% of the votes was required for acceptance of each statement of recommendation. RESULTS After a systematic review of the relevant literature, the committee convened to evaluate 167 articles. Following five RAND conferences, consensus statements were developed by an executive subcommittee. The entire consensus committee voted and approved 28 main statements. CONCLUSIONS There is a need for international guidelines regarding the appropriate timing and selection of imaging modality for patients with CF lung disease; timing and selection depends upon the clinical scenario, the patient's age, lung function and type of treatment. Despite its ubiquity, the use of the chest radiograph remains controversial. Both computed tomography and magnetic resonance imaging should be routinely used to monitor CF lung disease. Future studies should focus on imaging protocol harmonisation both for computed tomography and for magnetic resonance imaging. The introduction of artificial intelligence imaging analysis may further revolutionise clinical practice by providing fast and reliable quantitative outcomes to assess disease status. To date, there is no evidence supporting the use of lung ultrasound to monitor CF lung disease.
Collapse
Affiliation(s)
- Pierluigi Ciet
- Radiology and Nuclear Medicine Dept, Erasmus MC, Rotterdam, The Netherlands .,Pediatric Pulmonology and Allergology Dept, Erasmus MC, Sophia Children's Hospital, Rotterdam, The Netherlands.,Depts of Radiology and Medical Science, University of Cagliari, Cagliari, Italy
| | - Silvia Bertolo
- Radiology Dept, Ca'Foncello S. Maria Hospital, Treviso, Italy
| | - Mirco Ros
- Dept of Pediatrics, Ca'Foncello S. Maria Hospital, Treviso, Italy
| | - Rosaria Casciaro
- Dept of Pediatrics, IRCCS Institute "Giannina Gaslini", Cystic Fibrosis Centre, Genoa, Italy
| | - Marco Cipolli
- Regional Reference Cystic Fibrosis center, University hospital of Verona, Verona, Italy
| | - Stefano Colagrande
- Dept of Experimental and Clinical Biomedical Sciences, Radiodiagnostic Unit n. 2, University of Florence- Careggi Hospital, Florence, Italy
| | - Stefano Costa
- Dept of Pediatrics, Gaetano Martino Hospital, Messina, Italy
| | - Valeria Galici
- Cystic Fibrosis Centre, Dept of Paediatric Medicine, Anna Meyer Children's University Hospital, Florence, Italy
| | - Andrea Gramegna
- Respiratory Disease and Adult Cystic Fibrosis Centre, Internal Medicine Dept, IRCCS Ca' Granda, Milan, Italy.,Dept of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Cecilia Lanza
- Radiology Dept, University Hospital Ospedali Riuniti, Ancona, Italy
| | - Francesca Lucca
- Regional Reference Cystic Fibrosis center, University hospital of Verona, Verona, Italy
| | - Letizia Macconi
- Radiology Dept, Tuscany Reference Cystic Fibrosis Centre, Meyer Children's Hospital, Florence, Italy
| | - Fabio Majo
- Dept of Pediatrics, IRCCS Bambino Gesù Children's Hospital, Rome, Italy
| | | | - Giuseppe Fabio Parisi
- Pediatric Pulmonology Unit, Dept of Clinical and Experimental Medicine, University of Catania, Catania, Italy
| | - Francesca Rizzo
- Radiology Dept, IRCCS Institute "Giannina Gaslini", Cystic Fibrosis Center, Genoa, Italy
| | | | - Teresa Santangelo
- Dept of Radiology, IRCCS Bambino Gesù Children's Hospital, Rome, Italy
| | - Luigia Scudeller
- Clinical Epidemiology, IRCCS Azienda Ospedaliera Universitaria di Bologna, Bologna, Italy
| | - Luca Saba
- Depts of Radiology and Medical Science, University of Cagliari, Cagliari, Italy
| | - Paolo Tomà
- Dept of Radiology, IRCCS Bambino Gesù Children's Hospital, Rome, Italy
| | - Giovanni Morana
- Radiology Dept, Ca'Foncello S. Maria Hospital, Treviso, Italy
| |
Collapse
|
16
|
Pakzad A, Jacob J. Radiology of Bronchiectasis. Clin Chest Med 2022; 43:47-60. [PMID: 35236560 DOI: 10.1016/j.ccm.2021.11.004] [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: 11/26/2022]
Abstract
Bronchiectasis is a radiological diagnosis made using computed tomographic (CT) imaging. Although visual CT assessment is necessary for the diagnosis of bronchiectasis, visual assessment of disease severity and progression is challenging. Computer tools offer the potential to improve the characterization of lung damage in patients with bronchiectasis. Newer imaging techniques such as MRI with hyperpolarized gas inhalation have the potential to identify early forms of disease and are without the constraints of requiring ionizing radiation exposure.
Collapse
Affiliation(s)
- Ashkan Pakzad
- Departments of Medical Physics and Biomedical Engineering, and Computer Science, University College London, UK; Centre for Medical Image Computing, University College London, London, UK.
| | - Joseph Jacob
- Centre for Medical Image Computing, University College London, London, UK; UCL Respiratory, University College London, London, UK
| |
Collapse
|
17
|
Correlations between Volumetric Capnography and Automated Quantitative Computed Tomography Analysis in Patients with Severe COPD. JOURNAL OF RESPIRATION 2022. [DOI: 10.3390/jor2010002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Background: In chronic obstructive pulmonary disease (COPD), morphological analysis made by computed tomography (CT) is usually correlated with spirometry as the main functional tool. In this study, quantitative CT analysis (QCT) was compared with volumetric capnography (VCap), alongside spirometry and the 6-min walk test (6MWT). Methods: Twenty-seven patients with severe/very severe COPD were included, compared with nineteen control subjects. All participants performed spirometry and chest high resolution CT scans that were analyzed with fully-automated software. The COPD group was also submitted to VCap and 6MWT. Results: COPD patients (65.07 ± 8.25 years) showed an average FEV1 of 1.2 L (44% of the predicted) and the control group (34.36 ± 8.78 years). VCap × QCT: positive correlations were observed with bronchial wall thickening and negative correlations with diameter and area of the bronchial lumen. Spirometry × QCT: positive correlations were observed between post-BD FVC, FEV1 and FEF 25–75% and diameter and luminal area of the airways and FVC and lung and vascular volumes (emphysema). Negative correlation was observed between post-BD FVC and FEV1 when compared with Pi10 (internal perimeter of 10 mm). 6MWT vs. QCT: negative correlations were observed between the distance covered with relative wall thickness (airways) and vascular volume and peripheral vascular volume (vasculature). Conclusion: Relevant correlations between QCT and pulmonary function variables were found, including the VCap, highlighting the importance of structural analysis in conjunction with a multidimensional functional assessment. This is the first study to correlate airway and parenchyma QCT with VCap.
Collapse
|
18
|
Röhrich M, Leitz D, Glatting FM, Wefers AK, Weinheimer O, Flechsig P, Kahn N, Mall MA, Giesel FL, Kratochwil C, Huber PE, Deimling AV, Heußel CP, Kauczor HU, Kreuter M, Haberkorn U. Fibroblast Activation Protein-Specific PET/CT Imaging in Fibrotic Interstitial Lung Diseases and Lung Cancer: A Translational Exploratory Study. J Nucl Med 2022; 63:127-133. [PMID: 34272325 PMCID: PMC8717194 DOI: 10.2967/jnumed.121.261925] [Citation(s) in RCA: 67] [Impact Index Per Article: 33.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 05/27/2021] [Indexed: 11/16/2022] Open
Abstract
Interstitial lung diseases (ILDs) comprise over 200 parenchymal lung disorders. Among them, fibrosing ILDs, especially idiopathic pulmonary fibrosis, are associated with a poor prognosis, whereas some other ILDs, such as sarcoidosis, have a much better prognosis. A high proportion manifests as fibrotic ILD (fILD). Lung cancer (LC) is a frequent complication of fILD. Activated fibroblasts are crucial for fibrotic processes in fILD. The aim of this exploratory study was to evaluate the imaging properties of static and dynamic fibroblast activation protein (FAP) inhibitor (FAPI) PET/CT in various types of fILD and to confirm FAP expression in fILD lesions by FAP immunohistochemistry of human fILD biopsy samples and of lung sections of genetically engineered (Nedd4-2-/- ) mice with an idiopathic pulmonary fibrosislike lung disease. Methods: PET scans of 15 patients with fILD and suspected LC were acquired 10, 60, and 180 min after the administration of 150-250 MBq of a 68Ga-labeled FAPI tracer (FAPI-46). In 3 patients, dynamic scans over 40 min were performed instead of imaging after 10 min. The SUVmax and SUVmean of fibrotic lesions and LC were measured and CT-density-corrected. Target-to-background ratios (TBRs) were calculated. PET imaging was correlated with CT-based fibrosis scores. Time-activity curves derived from dynamic imaging were analyzed. FAP immunohistochemistry of 4 human fILD biopsy samples and of fibrotic lungs of Nedd4-2-/- mice was performed. Results: fILD lesions as well as LC showed markedly elevated 68Ga-FAPI uptake (density-corrected SUVmax and SUVmean 60 min after injection: 11.12 ± 6.71 and 4.29 ± 1.61, respectively, for fILD lesions and 16.69 ± 9.35 and 6.44 ± 3.29, respectively, for LC) and high TBR (TBR of density-corrected SUVmax and SUVmean 60 min after injection: 2.30 ± 1.47 and 1.67 ± 0.79, respectively, for fILD and 3.90 ± 2.36 and 2.37 ± 1.14, respectively, for LC). SUVmax and SUVmean decreased over time, with a stable TBR for fILD and a trend toward an increasing TBR in LC. Dynamic imaging showed differing time-activity curves for fILD and LC. 68Ga-FAPI uptake showed a positive correlation with the CT-based fibrosis index. Immunohistochemistry of human biopsy samples and the lungs of Nedd4-2-/- mice showed a patchy expression of FAP in fibrotic lesions, preferentially in the transition zone to healthy lung parenchyma. Conclusion:68Ga-FAPI PET/CT imaging is a promising new imaging modality for fILD and LC. Its potential clinical value for monitoring and therapy evaluation of fILD should be investigated in future studies.
Collapse
Affiliation(s)
- Manuel Röhrich
- Department of Nuclear Medicine, University Hospital Heidelberg, Heidelberg, Germany;
| | - Dominik Leitz
- Translational Lung Research Center Heidelberg, Member of the German Center for Lung Research DZL, Heidelberg, Germany
| | - Frederik M Glatting
- Clinical Cooperation Unit Molecular and Radiation Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Annika K Wefers
- Department of Neuropathology, Institute of Pathology, University of Heidelberg, Heidelberg, Germany
| | - Oliver Weinheimer
- Translational Lung Research Center Heidelberg, Member of the German Center for Lung Research DZL, Heidelberg, Germany
| | - Paul Flechsig
- Department of Nuclear Medicine, University Hospital Heidelberg, Heidelberg, Germany
| | - Nicolas Kahn
- Centre for Interstitial and Rare Lung Diseases, Pneumology and Respiratory Critical Care Medicine, Thorax Clinic, University of Heidelberg, Heidelberg, Germany; and
| | - Marcus A Mall
- Translational Lung Research Center Heidelberg, Member of the German Center for Lung Research DZL, Heidelberg, Germany
| | - Frederik L Giesel
- Department of Nuclear Medicine, University Hospital Heidelberg, Heidelberg, Germany
| | - Clemens Kratochwil
- Department of Nuclear Medicine, University Hospital Heidelberg, Heidelberg, Germany
| | - Peter E Huber
- Clinical Cooperation Unit Molecular and Radiation Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Andreas von Deimling
- Department of Neuropathology, Institute of Pathology, University of Heidelberg, Heidelberg, Germany
| | - Claus Peter Heußel
- Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik, University of Heidelberg, Heidelberg, Germany
| | - Hans Ulrich Kauczor
- Translational Lung Research Center Heidelberg, Member of the German Center for Lung Research DZL, Heidelberg, Germany
| | - Michael Kreuter
- Translational Lung Research Center Heidelberg, Member of the German Center for Lung Research DZL, Heidelberg, Germany
| | - Uwe Haberkorn
- Department of Nuclear Medicine, University Hospital Heidelberg, Heidelberg, Germany
| |
Collapse
|
19
|
Zheng H, Qin Y, Gu Y, Xie F, Yang J, Sun J, Yang GZ. Alleviating Class-Wise Gradient Imbalance for Pulmonary Airway Segmentation. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:2452-2462. [PMID: 33970858 DOI: 10.1109/tmi.2021.3078828] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Automated airway segmentation is a prerequisite for pre-operative diagnosis and intra-operative navigation for pulmonary intervention. Due to the small size and scattered spatial distribution of peripheral bronchi, this is hampered by a severe class imbalance between foreground and background regions, which makes it challenging for CNN-based methods to parse distal small airways. In this paper, we demonstrate that this problem is arisen by gradient erosion and dilation of the neighborhood voxels. During back-propagation, if the ratio of the foreground gradient to background gradient is small while the class imbalance is local, the foreground gradients can be eroded by their neighborhoods. This process cumulatively increases the noise information included in the gradient flow from top layers to the bottom ones, limiting the learning of small structures in CNNs. To alleviate this problem, we use group supervision and the corresponding WingsNet to provide complementary gradient flows to enhance the training of shallow layers. To further address the intra-class imbalance between large and small airways, we design a General Union loss function that obviates the impact of airway size by distance-based weights and adaptively tunes the gradient ratio based on the learning process. Extensive experiments on public datasets demonstrate that the proposed method can predict the airway structures with higher accuracy and better morphological completeness than the baselines.
Collapse
|
20
|
Ledda RE, Balbi M, Milone F, Ciuni A, Silva M, Sverzellati N, Milanese G. Imaging in non-cystic fibrosis bronchiectasis and current limitations. BJR Open 2021; 3:20210026. [PMID: 34381953 PMCID: PMC8328081 DOI: 10.1259/bjro.20210026] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Revised: 07/05/2021] [Accepted: 07/06/2021] [Indexed: 01/21/2023] Open
Abstract
Non-cystic fibrosis bronchiectasis represents a heterogenous spectrum of disorders characterised by an abnormal and permanent dilatation of the bronchial tree associated with respiratory symptoms. To date, diagnosis relies on computed tomography (CT) evidence of dilated airways. Nevertheless, definite radiological criteria and standardised CT protocols are still to be defined. Although largely used, current radiological scoring systems have shown substantial drawbacks, mostly failing to correlate morphological abnormalities with clinical and prognostic data. In limited cases, bronchiectasis morphology and distribution, along with associated CT features, enable radiologists to confidently suggest an underlying cause. Quantitative imaging analyses have shown a potential to overcome the limitations of the current radiological criteria, but their application is still limited to a research setting. In the present review, we discuss the role of imaging and its current limitations in non-cystic fibrosis bronchiectasis. The potential of automatic quantitative approaches and artificial intelligence in such a context will be also mentioned.
Collapse
Affiliation(s)
- Roberta Eufrasia Ledda
- Scienze Radiologiche, Department of Medicine and Surgery (DiMeC), University of Parma, Parma, Italy
| | - Maurizio Balbi
- Scienze Radiologiche, Department of Medicine and Surgery (DiMeC), University of Parma, Parma, Italy
| | - Francesca Milone
- Scienze Radiologiche, Department of Medicine and Surgery (DiMeC), University of Parma, Parma, Italy
| | - Andrea Ciuni
- Scienze Radiologiche, Department of Medicine and Surgery (DiMeC), University of Parma, Parma, Italy
| | - Mario Silva
- Scienze Radiologiche, Department of Medicine and Surgery (DiMeC), University of Parma, Parma, Italy
| | - Nicola Sverzellati
- Scienze Radiologiche, Department of Medicine and Surgery (DiMeC), University of Parma, Parma, Italy
| | - Gianluca Milanese
- Scienze Radiologiche, Department of Medicine and Surgery (DiMeC), University of Parma, Parma, Italy
| |
Collapse
|
21
|
Triphan SMF, Weinheimer O, Gutberlet M, Heußel CP, Vogel-Claussen J, Herth F, Vogelmeier CF, Jörres RA, Kauczor HU, Wielpütz MO, Biederer J, Jobst BJ. Echo Time-Dependent Observed Lung T 1 in Patients With Chronic Obstructive Pulmonary Disease in Correlation With Quantitative Imaging and Clinical Indices. J Magn Reson Imaging 2021; 54:1562-1571. [PMID: 34050576 DOI: 10.1002/jmri.27746] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 05/11/2021] [Accepted: 05/12/2021] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND There is a clinical need for imaging-derived biomarkers for the management of chronic obstructive pulmonary disease (COPD). Observed pulmonary T1 (T1 (TE)) depends on the echo-time (TE) and reflects regional pulmonary function. PURPOSE To investigate the potential diagnostic value of T1 (TE) for the assessment of lung disease in COPD patients by determining correlations with clinical parameters and quantitative CT. STUDY TYPE Prospective non-randomized diagnostic study. POPULATION Thirty COPD patients (67.7 ± 6.6 years). Data from a previous study (15 healthy volunteers [26.2 ± 3.9 years) were used as reference. FIELD STRENGTH/SEQUENCE Study participants were examined at 1.5 T using dynamic contrast-enhanced three-dimensional gradient echo keyhole perfusion sequence and a multi-echo inversion recovery two-dimensional UTE (ultra-short TE) sequence for T1 (TE) mapping at TE1-5 = 70 μsec, 500 μsec, 1200 μsec, 1650 μsec, and 2300 μsec. ASSESSMENT Perfusion images were scored by three radiologists. T1 (TE) was automatically quantified. Computed tomography (CT) images were quantified in software (qCT). Clinical parameters including pulmonary function testing were also acquired. STATISTICAL TESTS Spearman rank correlation coefficients (ρ) were calculated between T1 (TE) and perfusion scores, clinical parameters and qCT. A P-value <0.05 was considered statistically significant. RESULTS Median values were T1 (TE1-5 ) = 644 ± 78 msec, 835 ± 92 msec, 835 ± 87 msec, 831 ± 131 msec, 893 ± 220 msec, all significantly shorter than previously reported in healthy subjects. A significant increase of T1 was observed from TE1 to TE2 , with no changes from TE2 to TE3 (P = 0.48), TE3 to TE4 (P = 0.94) or TE4 to TE5 (P = 0.02) which demonstrates an increase at shorter TEs than in healthy subjects. Moderate to strong Spearman's correlations between T1 and parameters including the predicted diffusing capacity for carbon monoxide (DLCO, ρ < 0.70), mean lung density (MLD, ρ < 0.72) and the perfusion score (ρ > -0.69) were found. Overall, correlations were strongest at TE2 , weaker at TE1 and rarely significant at TE4 -TE5 . DATA CONCLUSION In COPD patients, the increase of T1 (TE) with TE occurred at shorter TEs than previously found in healthy subjects. Together with the lack of correlation between T1 and clinical parameters of disease at longer TEs, this suggests that T1 (TE) quantification in COPD patients requires shorter TEs. The TE-dependence of correlations implies that T1 (TE) mapping might be developed further to provide diagnostic information beyond T1 at a single TE. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 1.
Collapse
Affiliation(s)
- Simon M F Triphan
- Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany.,Translational Lung Research Center Heidelberg, Member of the German Lung Research Center, 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 of Heidelberg, Heidelberg, Germany.,Translational Lung Research Center Heidelberg, Member of the German Lung Research Center, Heidelberg, Germany.,Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Marcel Gutberlet
- Institute for Diagnostic and Interventional Radiology, Hannover Medical School, Hannover, Germany.,Biomedical Research in Endstage and Obstructive Lung Disease Hannover, Member of the German Center for Lung Research, Hannover, Germany
| | - Claus P Heußel
- Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany.,Translational Lung Research Center Heidelberg, Member of the German Lung Research Center, Heidelberg, Germany.,Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Jens Vogel-Claussen
- Institute for Diagnostic and Interventional Radiology, Hannover Medical School, Hannover, Germany.,Biomedical Research in Endstage and Obstructive Lung Disease Hannover, Member of the German Center for Lung Research, Hannover, Germany
| | - Felix Herth
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany.,Department of Pneumology and Critical Care Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Claus F Vogelmeier
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Member of the German Center for Lung Research, Marburg, Germany
| | - Rudolf A Jörres
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Hans-Ulrich Kauczor
- Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany.,Translational Lung Research Center Heidelberg, Member of the German Lung Research Center, Heidelberg, Germany.,Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Mark O Wielpütz
- Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany.,Translational Lung Research Center Heidelberg, Member of the German Lung Research Center, Heidelberg, Germany.,Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Jürgen Biederer
- Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany.,Translational Lung Research Center Heidelberg, Member of the German Lung Research Center, Heidelberg, Germany.,Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Bertram J Jobst
- Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany.,Translational Lung Research Center Heidelberg, Member of the German Lung Research Center, Heidelberg, Germany.,Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | | |
Collapse
|
22
|
Mondéjar-López P, Horsley A, Ratjen F, Bertolo S, de Vicente H, Asensio de la Cruz Ò. A multimodal approach to detect and monitor early lung disease in cystic fibrosis. Expert Rev Respir Med 2021; 15:761-772. [PMID: 33843417 DOI: 10.1080/17476348.2021.1908131] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Introduction: In the early stages, lung involvement in cystic fibrosis (CF) can be silent, with disease progression occurring in the absence of clinical symptoms. Irreversible airway damage is present in the early stages of disease; however, reliable biomarkers of early damage due to inflammation and infection that are universally applicable in day-to-day patient management have yet to be identified.Areas covered: At present, the main methods of detecting and monitoring early lung disease in CF are the lung clearance index (LCI), computed tomography (CT), and magnetic resonance imaging (MRI). LCI can be used to detect patients who may require more intense monitoring, identify exacerbations, and monitor responses to new interventions. High-resolution CT detects structural alterations in the lungs of CF patients with the best resolution of current imaging techniques. MRI is a radiation-free imaging alternative that provides both morphological and functional information. The role of MRI for short-term follow-up and pulmonary exacerbations is currently being investigated.Expert opinion: The roles of LCI and MRI are expected to expand considerably over the next few years. Meanwhile, closer collaboration between pulmonology and radiology specialties is an important goal toward improving care and optimizing outcomes in young patients with CF.
Collapse
Affiliation(s)
- Pedro Mondéjar-López
- Pediatric Pulmonologist, Pediatric Pulmonology and Cystic Fibrosis Unit, University Hospital Virgen de la Arrixaca, Murcia, Spain
| | - Alexander Horsley
- Honorary Consultant, Respiratory Research Group, Division of Infection, Immunity & Respiratory Medicine, University of Manchester, Manchester, UK
| | - Felix Ratjen
- Head, Division of Respiratory Medicine, Department of Pediatrics, Translational Medicine, Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Silvia Bertolo
- Radiologist, Department of Radiology, Ca'Foncello Regional Hospital, Treviso, Italy
| | | | - Òscar Asensio de la Cruz
- Pediatric Pulmonologist, Pediatric Unit, University Hospital Parc Taulí de Sabadell, Sabadell, Spain
| |
Collapse
|
23
|
Magnetic Resonance Imaging Detects Chronic Rhinosinusitis in Infants and Preschool Children with Cystic Fibrosis. Ann Am Thorac Soc 2021; 17:714-723. [PMID: 32142375 DOI: 10.1513/annalsats.201910-777oc] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Rationale: Chronic rhinosinusitis (CRS) contributes to disease burden of patients with cystic fibrosis (CF). However, its onset and progression in infants and preschool children with CF remain poorly understood.Objectives: To determine the prevalence and extent of CRS in young children with CF using magnetic resonance imaging (MRI).Methods: MRI was performed in sedation in 67 infants and preschool children with CF (mean age 2.3 ± 2.1 yr; range 0-6 yr) and 30 non-CF control subjects (3.5 ± 2.0 yr; range 0-6 yr). Paranasal sinus dimensions and structural abnormalities, including mucosal swelling; mucopyoceles; and nasal polyps of the maxillary, frontal, sphenoid, and ethmoid sinuses; and, in addition, medial maxillary sinus wall deformation, were assessed using a dedicated CRS MRI scoring system.Results: Pneumatization and dimensions of paranasal sinuses did not differ between the two groups. MRI detected an increased prevalence of mucosal swelling (83% vs. 17%; P < 0.001), mucopyoceles (75% vs. 2%; P < 0.001), polyps (26% vs. 7%; P < 0.001), and maxillary sinus wall deformation (68% vs. 2%; P < 0.001) in infants and preschool children with CF compared with age-matched control subjects. Furthermore, the extent of these abnormalities was also increased with a MRI sum score of 22.9 ± 10.9 in CF compared with 4.5 ± 7.6 in non-CF control subjects (P < 0.001).Conclusions: MRI detected normal dimensions of paranasal sinuses, and a high prevalence and severity of paranasal sinus abnormalities due to CRS in infants and preschool children with CF without radiation exposure. Our results support the development of MRI for sensitive noninvasive diagnosis and monitoring of CRS in young children with CF, and as outcome measures for clinical trials.Clinical trial registered with www.clinicaltrials.gov (NCT00760071).
Collapse
|
24
|
Goralski JL, Stewart NJ, Woods JC. Novel imaging techniques for cystic fibrosis lung disease. Pediatr Pulmonol 2021; 56 Suppl 1:S40-S54. [PMID: 32592531 PMCID: PMC7808406 DOI: 10.1002/ppul.24931] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Accepted: 06/25/2020] [Indexed: 12/24/2022]
Abstract
With an increasing number of patients with cystic fibrosis (CF) receiving highly effective CFTR (cystic fibrosis transmembrane regulator protein) modulator therapy, particularly at a young age, there is an increasing need to identify imaging tools that can detect and regionally visualize mild CF lung disease and subtle changes in disease state. In this review, we discuss the latest developments in imaging modalities for both structural and functional imaging of the lung available to CF clinicians and researchers, from the widely available, clinically utilized imaging methods for assessing CF lung disease-chest radiography and computed tomography-to newer techniques poised to become the next phase of clinical tools-structural/functional proton and hyperpolarized gas magnetic resonance imaging (MRI). Finally, we provide a brief discussion of several newer lung imaging techniques that are currently available only in selected research settings, including chest tomosynthesis, and fluorinated gas MRI. We provide an update on the clinical and/or research status of each technique, with a focus on sensitivity, early disease detection, and possibilities for monitoring treatment efficacy.
Collapse
Affiliation(s)
- Jennifer L Goralski
- UNC Cystic Fibrosis Center, Marsico Lung Institute, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.,Division of Pulmonary and Critical Care Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.,Division of Pediatric Pulmonology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Neil J Stewart
- Center for Pulmonary Imaging Research, Cincinnati Children's Hospital, Cincinnati, Ohio.,Department of Infection, Immunity & Cardiovascular Disease, POLARIS Group, Imaging Sciences, University of Sheffield, Sheffield, UK
| | - Jason C Woods
- Center for Pulmonary Imaging Research, Cincinnati Children's Hospital, Cincinnati, Ohio.,Department of Pediatrics, University of Cincinnati, Cincinnati, Ohio.,Department of Radiology, Cincinnati Children's Hospital, Cincinnati, Ohio
| |
Collapse
|
25
|
Pennati F, Borzani I, Moroni L, Russo MC, Faelli N, Aliverti A, Colombo C. Longitudinal Assessment of Patients With Cystic Fibrosis Lung Disease With Multivolume Noncontrast
MRI
and Spirometry. J Magn Reson Imaging 2020; 53:1570-1580. [DOI: 10.1002/jmri.27461] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 11/20/2020] [Accepted: 11/24/2020] [Indexed: 12/26/2022] Open
Affiliation(s)
- Francesca Pennati
- Dipartimento di Elettronica, Informazione e Bioingegneria Politecnico di Milano Milan Italy
| | - Irene Borzani
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico Pediatric Radiology Milan Italy
| | - Laura Moroni
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico Università degli Studi di Milano, Centro Fibrosi Cistica Milan Italy
| | - Maria Chiara Russo
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico Università degli Studi di Milano, Centro Fibrosi Cistica Milan Italy
| | - Nadia Faelli
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico Università degli Studi di Milano, Centro Fibrosi Cistica Milan Italy
| | - Andrea Aliverti
- Dipartimento di Elettronica, Informazione e Bioingegneria Politecnico di Milano Milan Italy
| | - Carla Colombo
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico Università degli Studi di Milano, Centro Fibrosi Cistica Milan Italy
| |
Collapse
|
26
|
Woods JC, Wild JM, Wielpütz MO, Clancy JP, Hatabu H, Kauczor HU, van Beek EJ, Altes TA. Current state of the art MRI for the longitudinal assessment of cystic fibrosis. J Magn Reson Imaging 2020; 52:1306-1320. [PMID: 31846139 PMCID: PMC7297663 DOI: 10.1002/jmri.27030] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 12/02/2019] [Accepted: 12/02/2019] [Indexed: 12/13/2022] Open
Abstract
Pulmonary MRI can now provide high-resolution images that are sensitive to early disease and specific to inflammation in cystic fibrosis (CF) lung disease. With specificity and function limited via computed tomography (CT), there are significant advantages to MRI. Many of the modern MRI techniques can be performed throughout life, and can be employed to understand changes over time, in addition to quantification of treatment response. Proton density and T1 /T2 contrast images can be obtained within a single breath-hold, providing depiction of structural abnormalities and active inflammation. Modern radial and/or spiral ultrashort echo-time (UTE) techniques rival CT in resolution for depiction and quantification of structure, for both airway and parenchymal abnormalities. Contrast perfusion MRI techniques are now utilized routinely to visualize changes in pulmonary and bronchial circulation that routinely occur in CF lung disease, and noncontrast techniques are moving closer to clinical translation. Functional information can be obtained from noncontrast proton images alone, using techniques such as Fourier decomposition. Hyperpolarized-gas MRI, increasingly using 129 Xe, is now becoming more widespread and has been demonstrated to have high sensitivity to early airway obstruction in CF via ventilation MRI. The sensitivity of 129 Xe MRI promises future use in personalized medicine, management of early CF lung disease, and in future clinical trials. By combining structural and functional techniques, with or without hyperpolarized gases, regional structure-function relationships can be obtained, giving insight into the pathophysiology of disease and improved clinical management. This article reviews the modern MRI techniques that can routinely be employed for CF lung disease in nearly any large medical center. Level of Evidence: 4 Technical Efficacy Stage: 5 J. Magn. Reson. Imaging 2019.
Collapse
Affiliation(s)
- Jason C. Woods
- Center for Pulmonary Imaging Research, Division of Pulmonary Medicine and Department of Radiology, Cincinnati Children’s Hospital and University of Cincinnati; Cincinnati OH, USA
| | - Jim M. Wild
- Department of Radiology, University of Sheffield, Sheffield UK
| | - Mark O. Wielpütz
- Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center (TLRC) Heidelberg, German Center for lung Research (DZL), Heidelberg, Germany
| | - John P. Clancy
- Center for Pulmonary Imaging Research, Division of Pulmonary Medicine and Department of Radiology, Cincinnati Children’s Hospital and University of Cincinnati; Cincinnati OH, USA
| | - Hiroto Hatabu
- Center for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Hans-Ulrich Kauczor
- Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center (TLRC) Heidelberg, German Center for lung Research (DZL), Heidelberg, Germany
| | - Edwin J.R. van Beek
- Edinburgh Imaging, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Talissa A Altes
- Department of Radiology, University of Missouri, Columbia, MO, USA
| |
Collapse
|
27
|
Schmitt VH, Schmitt C, Hollemann D, Mamilos A, Wagner W, Weinheimer O, Brochhausen C. Comparison of histological and computed tomographic measurements of pig lung bronchi. ERJ Open Res 2020; 6:00500-2020. [PMID: 33313303 PMCID: PMC7720685 DOI: 10.1183/23120541.00500-2020] [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: 07/15/2020] [Accepted: 09/14/2020] [Indexed: 12/03/2022] Open
Abstract
AIM Light microscopy is used as template in the evaluation and further development of medical imaging methods. Tissue shrinkage caused by histological processing is known to influence lung tissue dimensions. In diagnosis of COPD, computed tomography (CT) is widely used for automated airway measurement. The aim of this study was to compare histological and computed tomographic measurements of pig lung bronchi. METHODS Airway measurements of pig lungs were performed after freezing under controlled inflation pressure in a liquid nitrogen bath. The wall thickness of seven bronchi was measured via Micro-CT and CT using the integral-based method (IBM) and the full-width-at-half-maximum method (FWHM) automatically and histologically on frozen and paraffin sections. Statistical analysis was performed using the Wilcoxon test, Pearson's correlation coefficient with a significance level at p<0.05, scatter plots and Bland-Altman plots. RESULTS Bronchial wall thickness was smallest in frozen sections (median 0.71 mm) followed by paraffin sections (median 0.75 mm), Micro-CT (median 0.84 mm), and CT measurements using IBM (median 0.68 mm) and FWHM (median 1.69 mm). Statistically significant differences were found among all tested groups (p<0.05) except for CT IBM and paraffin and frozen sections and Micro-CT. There was high correlation between all parameters with statistical significance (p<0.05). CONCLUSIONS Significant differences in airway measurement were found among the different methods. The absolute measurements with CT IBM were closest to the histological results followed by Micro-CT, whereas CT FWHM demonstrated a distinct divergence from the other groups.
Collapse
Affiliation(s)
- Volker H. Schmitt
- Dept of Cardiology, University Medical Centre, Johannes Gutenberg University of Mainz, Mainz, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Rhine Main, Mainz, Germany
- Joint first authors
| | | | - David Hollemann
- Institute of Clinical and Molecular Pathology, State Hospital Horn, Horn, Austria
| | - Andreas Mamilos
- REPAIR-lab, Institute of Pathology, University of Regensburg, Regensburg, Germany
| | - Willi Wagner
- Dept of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany
- Translational Lung Research Centre Heidelberg (TLRC), German Lung Research Centre (DZL), Heidelberg, Germany
| | - Oliver Weinheimer
- Dept of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany
- Translational Lung Research Centre Heidelberg (TLRC), German Lung Research Centre (DZL), Heidelberg, Germany
- Joint senior authors
| | - Christoph Brochhausen
- REPAIR-lab, Institute of Pathology, University of Regensburg, Regensburg, Germany
- Central Biobank Regensburg, University Regensburg and University Hospital Regensburg, Regensburg, Germany
- Joint senior authors
| |
Collapse
|
28
|
[Cystic fibrosis and computed tomography of the lungs]. Radiologe 2020; 60:791-801. [PMID: 32621155 DOI: 10.1007/s00117-020-00713-2] [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: 10/23/2022]
Abstract
With its high detail of morphological changes in lung parenchyma and airways as well as the possibilities for three-dimensional reconstruction, computed tomography (CT) represents a solid tool for the diagnosis and follow-up in patients suffering from cystic fibrosis (CF). Guidelines for standardized CT image acquisition in CF patients are still missing. In the mostly younger CF patients, an important issue is the well-considered use of radiation in CT imaging. The use of intravenous contrast agent is mainly restricted to acute emergency diagnostics. Typical morphological findings in CF lung disease are bronchiectasis, mucus plugging, or signs of decreased ventilation (air trapping) which can be detected with CT even in early stages. Various scoring systems that have become established over time are used to grade disease severity and for structured follow-up, e.g., in clinical research studies. With the technical development of CT, a number of postprocessing software tools were developed to help clinical reporting and overcome interreader differences for a standardized quantification. As an imaging modality free of ionizing radiation, magnetic resonance imaging (MRI) is becoming increasingly important in the diagnosis and follow-up of CF patients and is already frequently a substitute for CT for long-term follow-up at numerous specialized centers.
Collapse
|
29
|
Konietzke P, Weinheimer O, Wagner WL, Wuennemann F, Hintze C, Biederer J, Heussel CP, Kauczor HU, Wielpütz MO. Optimizing airway wall segmentation and quantification by reducing the influence of adjacent vessels and intravascular contrast material with a modified integral-based algorithm in quantitative computed tomography. PLoS One 2020; 15:e0237939. [PMID: 32813730 PMCID: PMC7437894 DOI: 10.1371/journal.pone.0237939] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Accepted: 08/05/2020] [Indexed: 11/18/2022] Open
Abstract
Introduction Quantitative analysis of multi-detector computed tomography (MDCT) plays an increasingly important role in assessing airway disease. Depending on the algorithms used, airway dimensions may be over- or underestimated, primarily if contrast material was used. Therefore, we tested a modified integral-based method (IBM) to address this problem. Methods Temporally resolved cine-MDCT was performed in seven ventilated pigs in breath-hold during iodinated contrast material (CM) infusion over 60s. Identical slices in non-enhanced (NE), pulmonary-arterial (PA), systemic-arterial (SA), and venous phase (VE) were subjected to an in-house software using a standard and a modified IBM. Total diameter (TD), lumen area (LA), wall area (WA), and wall thickness (WT) were measured for ten extra- and six intrapulmonary airways. Results The modified IBM significantly reduced TD by 7.6%, LA by 12.7%, WA by 9.7%, and WT by 3.9% compared to standard IBM on non-enhanced CT (p<0.05). Using standard IBM, CM led to a decrease of all airway parameters compared to NE. For example, LA decreased from 80.85±49.26mm2 at NE, to 75.14±47.96mm2 (-7.1%) at PA (p<0.001), 74.96±48.55mm2 (-7.3%) at SA (p<0.001), and to 78.95±48.94mm2 (-2.4%) at VE (p = 0.200). Using modified IBM, the differences were reduced to -3.1% at PA, -2.9% at SA and -0.7% at VE (p<0.001; p<0.001; p = 1.000). Conclusions The modified IBM can optimize airway wall segmentation and reduce the influence of CM on quantitative CT. This allows a more precise measurement as well as potentially the comparison of enhanced with non-enhanced scans in inflammatory airway disease.
Collapse
Affiliation(s)
- Philip Konietzke
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
- * E-mail:
| | - Oliver Weinheimer
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Willi L. Wagner
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Felix Wuennemann
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Christian Hintze
- Department of Diagnostic Radiology, University Hospital Schleswig-Holstein, Kiel, Germany
- Department of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Radiologie Rein-Nahe, Bingen, Germany
| | - Juergen Biederer
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Claus P. Heussel
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Hans-Ulrich Kauczor
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Mark O. Wielpütz
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| |
Collapse
|
30
|
Selvan R, Kipf T, Welling M, Juarez AGU, Pedersen JH, Petersen J, Bruijne MD. Graph refinement based airway extraction using mean-field networks and graph neural networks. Med Image Anal 2020; 64:101751. [DOI: 10.1016/j.media.2020.101751] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Revised: 06/03/2020] [Accepted: 06/04/2020] [Indexed: 01/22/2023]
|
31
|
Tiddens HAWM, Meerburg JJ, van der Eerden MM, Ciet P. The radiological diagnosis of bronchiectasis: what's in a name? Eur Respir Rev 2020; 29:29/156/190120. [PMID: 32554759 PMCID: PMC9489191 DOI: 10.1183/16000617.0120-2019] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2019] [Accepted: 01/02/2020] [Indexed: 12/31/2022] Open
Abstract
Diagnosis of bronchiectasis is usually made using chest computed tomography (CT) scan, the current gold standard method. A bronchiectatic airway can show abnormal widening and thickening of its airway wall. In addition, it can show an irregular wall and lack of tapering, and/or can be visible in the periphery of the lung. Its diagnosis is still largely expert based. More recently, it has become clear that airway dimensions on CT and therefore the diagnosis of bronchiectasis are highly dependent on lung volume. Hence, control of lung volume is required during CT acquisition to standardise the evaluation of airways. Automated image analysis systems are in development for the objective analysis of airway dimensions and for the diagnosis of bronchiectasis. To use these systems, clear and objective definitions for the diagnosis of bronchiectasis are needed. Furthermore, the use of these systems requires standardisation of CT protocols and of lung volume during chest CT acquisition. In addition, sex- and age-specific reference values are needed for image analysis outcome parameters. This review focusses on today's issues relating to the radiological diagnosis of bronchiectasis using state-of-the-art CT imaging techniques. Bronchiectasis diagnosis is expert based. Clear definitions, standardisation of lung volume and CT protocols, and reference values are needed to allow automated image analysis for its diagnosis and to be used for clinical management and clinical studies.http://bit.ly/35vASqz
Collapse
Affiliation(s)
- Harm A W M Tiddens
- Dept of Paediatric Pulmonology and Allergology, Erasmus Medical Centre (MC)-Sophia Children's Hospital, Rotterdam, The Netherlands .,Dept of Radiology and Nuclear Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Jennifer J Meerburg
- Dept of Paediatric Pulmonology and Allergology, Erasmus Medical Centre (MC)-Sophia Children's Hospital, Rotterdam, The Netherlands.,Dept of Radiology and Nuclear Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | | | - Pierluigi Ciet
- Dept of Paediatric Pulmonology and Allergology, Erasmus Medical Centre (MC)-Sophia Children's Hospital, Rotterdam, The Netherlands.,Dept of Radiology and Nuclear Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| |
Collapse
|
32
|
Meerburg JJ, Veerman GDM, Aliberti S, Tiddens HAWM. Diagnosis and quantification of bronchiectasis using computed tomography or magnetic resonance imaging: A systematic review. Respir Med 2020; 170:105954. [PMID: 32843159 DOI: 10.1016/j.rmed.2020.105954] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Revised: 03/27/2020] [Accepted: 03/31/2020] [Indexed: 12/27/2022]
Abstract
BACKGROUND Bronchiectasis is an irreversible dilatation of the airways caused by inflammation and infection. To diagnose bronchiectasis in clinical care and to use bronchiectasis as outcome parameter in clinical trials, a radiological definition with exact cut-off values along with image analysis methods to assess its severity are needed. The aim of this study was to review diagnostic criteria and quantification methods for bronchiectasis. METHODS A systematic literature search was performed using Embase, Medline Ovid, Web of Science, Cochrane and Google Scholar. English written, clinical studies that included bronchiectasis as outcome measure and used image quantification methods were selected. Criteria for bronchiectasis, quantification methods, patient demographics, and data on image acquisition were extracted. RESULTS We screened 4182 abstracts, selected 972 full texts, and included 122 studies. The most often used criterion for bronchiectasis was an inner airway-artery ratio ≥1.0 (42%), however no validation studies for this cut-off value were found. Importantly, studies showed that airway-artery ratios are influenced by age. To quantify bronchiectasis, 42 different scoring methods were described. CONCLUSION Different diagnostic criteria for bronchiectasis are being used, but no validation studies were found to support these criteria. To use bronchiectasis as outcome in future studies, validated and age-specific cut-off values are needed.
Collapse
Affiliation(s)
- Jennifer J Meerburg
- Department of Paediatric Pulmonology and Allergology, Erasmus Medical Centre -Sophia Children's Hospital, Wytemaweg 80, 3015CN, Rotterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus Medical Centre, Wytemaweg 80, 3015CN, Rotterdam, the Netherlands.
| | - G D Marijn Veerman
- Department of Medical Oncology, Erasmus MC Cancer Institute, Erasmus Medical Centre, Wytemaweg 80, 3015CN, Rotterdam, the Netherlands.
| | - Stefano Aliberti
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Respiratory Unit and Adult Cystic Fibrosis Center, Dept of Pathophysiology and Transplantation, University of Milan, Milan, Italy.
| | - Harm A W M Tiddens
- Department of Paediatric Pulmonology and Allergology, Erasmus Medical Centre -Sophia Children's Hospital, Wytemaweg 80, 3015CN, Rotterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus Medical Centre, Wytemaweg 80, 3015CN, Rotterdam, the Netherlands.
| |
Collapse
|
33
|
Robinson TE, Goris ML, Moss RB, Tian L, Kan P, Yilma M, McCoy KS, Newman B, de Jong PA, Long FR, Brody AS, Behrje R, Yates DP, Cornfield DN. Mucus plugging, air trapping, and bronchiectasis are important outcome measures in assessing progressive childhood cystic fibrosis lung disease. Pediatr Pulmonol 2020; 55:929-938. [PMID: 31962004 DOI: 10.1002/ppul.24646] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 12/30/2019] [Indexed: 11/09/2022]
Abstract
OBJECTIVE To determine which outcome measures could detect early progression of disease in school-age children with mild cystic fibrosis (CF) lung disease over a two-year time interval utilizing chest computed tomography (CT) scores, quantitative CT air trapping (QAT), and spirometric measurements. METHODS Thirty-six school-age children with mild CF lung disease (median [interquartile range] age 12 [3.7] years; percent predicted forced expiratory volume in 1 second (ppFEV1 ) 99 [12.5]) were evaluated by serial spirometer-controlled chest CT scans and spirometry at baseline, 3-month, 1- and 2-years. RESULTS No significant changes were noted at 3-month for any variable except for decreased ppFEV1 . Mucus plugging score (MPS) and QATA1andA2 increased at 1- and 2-years. The bronchiectasis score (BS), and total score (TS) were increased at 2-year. All variables tested with the exception of bronchial wall thickness score, parenchymal score (PS), and ppFEV1 , were consistent with longitudinal worsening of lung disease. Multivariate analysis revealed baseline PS, baseline TS, and 1-year changes in BS and air trapping score were predictive of 2-year changes in BS. CONCLUSIONS MPS and QATA1-A2 were the most sensitive indicators of progressive childhood CF lung disease. The 1-year change in the bronchiectasis score had the most positive predictive power for 2-year change in bronchiectasis.
Collapse
Affiliation(s)
- Terry E Robinson
- Department of Pediatrics, Center of Excellence in Pulmonary Biology, Stanford University School of Medicine, Stanford, California
| | - Michael L Goris
- Division of Nuclear Medicine/Radiology, Stanford University School of Medicine, Stanford, California
| | - Richard B Moss
- Department of Pediatrics, Center of Excellence in Pulmonary Biology, Stanford University School of Medicine, Stanford, California
| | - Lu Tian
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California
| | - Peiyi Kan
- Department of Pediatrics Research and Statistical Unit, Stanford University School of Medicine, Stanford, California
| | - Mignote Yilma
- Department of Pediatrics, Center of Excellence in Pulmonary Biology, Stanford University School of Medicine, Stanford, California
| | - Karen S McCoy
- Division of Pulmonary Medicine, Department of Pediatrics, Nationwide Children's Hospital, Columbus, Ohio
| | - Beverley Newman
- Department of Radiology, Stanford University School of Medicine, Stanford, California
| | - Pim A de Jong
- Department of Radiology, University Medical Center Utrecht, The Netherlands
| | - Frederick R Long
- Department of Radiology, Nationwide Children's Hospital, Columbus, Ohio
| | - Alan S Brody
- Department of Radiology, Cincinnati Children's Hospital, Cincinnati, Ohio
| | - Rhett Behrje
- Department of Global Development, Takeda Pharmaceuticals, Cambridge, Massachusetts
| | - Denise P Yates
- Department of Biomarker Development, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts
| | - David N Cornfield
- Department of Pediatrics, Center of Excellence in Pulmonary Biology, Stanford University School of Medicine, Stanford, California
| |
Collapse
|
34
|
Airway tapering: an objective image biomarker for bronchiectasis. Eur Radiol 2020; 30:2703-2711. [PMID: 32025831 PMCID: PMC7160094 DOI: 10.1007/s00330-019-06606-w] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 11/13/2019] [Accepted: 12/03/2019] [Indexed: 12/15/2022]
Abstract
Purpose To estimate airway tapering in control subjects and to assess the usability of tapering as a bronchiectasis biomarker in paediatric populations. Methods Airway tapering values were semi-automatically quantified in 156 children with control CTs collected in the Normal Chest CT Study Group. Airway tapering as a biomarker for bronchiectasis was assessed on spirometer-guided inspiratory CTs from 12 patients with bronchiectasis and 12 age- and sex-matched controls. Semi-automatic image analysis software was used to quantify intra-branch tapering (reduction in airway diameter along the branch), inter-branch tapering (reduction in airway diameter before and after bifurcation) and airway-artery ratios on chest CTs. Biomarkers were further stratified in small, medium and large airways based on three equal groups of the accompanying vessel size. Results Control subjects showed intra-branch tapering of 1% and inter-branch tapering of 24–39%. Subjects with bronchiectasis showed significantly reduced intra-branch of 0.8% and inter-branch tapering of 19–32% and increased airway–artery ratios compared with controls (p < 0.01). Tapering measurements were significantly different between diseased and controls across all airway sizes. Difference in airway–artery ratio was only significant in small airways. Conclusion Paediatric normal values for airway tapering were established in control subjects. Tapering showed to be a promising biomarker for bronchiectasis as subjects with bronchiectasis show significantly less airway tapering across all airway sizes compared with controls. Detecting less tapering in larger airways could potentially lead to earlier diagnosis of bronchiectasis. Additionally, compared with the conventional airway–artery ratio, this novel biomarker has the advantage that it does not require pairing with pulmonary arteries. Key Points • Tapering is a promising objective image biomarker for bronchiectasis that can be extracted semi-automatically and has good correlation with validated visual scoring methods. • Less airway tapering was observed in patients with bronchiectasis and can be observed sensitively throughout the bronchial tree, even in the more central airways. • Tapering values seemed to be less influenced by variety in scanning protocols and lung volume making it a more robust biomarker for bronchiectasis detection. Electronic supplementary material The online version of this article (10.1007/s00330-019-06606-w) contains supplementary material, which is available to authorized users.
Collapse
|
35
|
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: 27] [Impact Index Per Article: 6.8] [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.
Collapse
|
36
|
Automatic Quantitative Computed Tomography Evaluation of the Lungs in Patients With Systemic Sclerosis Treated With Autologous Stem Cell Transplantation. J Clin Rheumatol 2019; 26:S158-S164. [PMID: 31868835 DOI: 10.1097/rhu.0000000000001242] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
BACKGROUND/OBJECTIVE Interstitial lung disease stands among the leading causes of death in systemic sclerosis (SSc) patients. Autologous hematopoietic stem cell transplantation (AHSCT) has been proven superior to conventional immunosuppressive therapy in severe and progressive SSc. Here, pulmonary quantitative measurements were obtained in high-resolution computed tomography (HRCT) scans of patients with SSc before and after AHSCT. METHODS The medical records of thirthy-three patients who underwent AHSCT between 2011 and 2017 were evaluated for clinical and tomographic features at baseline (pre-AHCST) and 18 months after the procedure. Quantitative analysis of HRCT images by a fully automated program calculated lung volumes, densities, attenuation percentiles, and vascular volume. Patients were divided into 2 groups, according to changes in forced vital capacity (FVC). The "best response" group included patients that had an increased FVC of 10% or greater, and the "stable response" group included those who had a decreased or an increased FVC of less than 10%. RESULTS In the best response group (15 patients), there was reduction (p < 0.05) of mean lung density and density percentile values after AHSCT. In the stable response group (18 patients), there were no significant changes in lung volumes and pulmonary densities after AHSCT. Pulmonary HRCT densities showed moderate/strong correlation with function. CONCLUSIONS Quantitative HRCT analysis identified significant reduction in pulmonary densities in patients with improved pulmonary function after AHSCT. Lung density, as evaluated by the quantitative HRCT analysis tool, has potential to become a biomarker in the evaluation of interstitial lung disease treatment in patients with SSc.
Collapse
|
37
|
Weinheimer O, Hoff BA, Fortuna AB, Fernández-Baldera A, Konietzke P, Wielpütz MO, Robinson TE, Galbán CJ. Influence of Inspiratory/Expiratory CT Registration on Quantitative Air Trapping. Acad Radiol 2019; 26:1202-1214. [PMID: 30545681 DOI: 10.1016/j.acra.2018.11.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Revised: 10/25/2018] [Accepted: 11/03/2018] [Indexed: 12/21/2022]
Abstract
RATIONALE AND OBJECTIVES The aim of this study was to assess variability in quantitative air trapping (QAT) measurements derived from spatially aligned expiration CT scans. MATERIALS AND METHODS Sixty-four paired CT examinations, from 16 school-age cystic fibrosis subjects examined at four separate time intervals, were used in this study. For each pair, visually inspected lobe segmentation maps were generated and expiration CT data were registered to the inspiration CT frame. Measurements of QAT, the percentage of voxels on the expiration CT scan below a set threshold were calculated for each lobe and whole-lung from the registered expiration CT and compared to the true values from the unregistered data. RESULTS A mathematical model, which simulates the effect of variable regions of lung deformation on QAT values calculated from aligned to those from unaligned data, showed the potential for large bias. Assessment of experimental QAT measurements using Bland-Altman plots corroborated the model simulations, demonstrating biases greater than 5% when QAT was approximately 40% of lung volume. These biases were removed when calculating QAT from aligned expiration CT data using the determinant of the Jacobian matrix. We found, by Dice coefficient analysis, good agreement between aligned expiration and inspiration segmentation maps for the whole-lung and all but one lobe (Dice coefficient > 0.9), with only the lingula generating a value below 0.9 (mean and standard deviation of 0.85 ± 0.06). CONCLUSION The subtle and predictable variability in corrected QAT observed in this study suggests that image registration is reliable in preserving the accuracy of the quantitative metrics.
Collapse
Affiliation(s)
- Oliver Weinheimer
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, 69120 Heidelberg, Germany; Translational Lung Research Center, Heidelberg (TLRC), German Lung Research Center (DZL), 69120 Heidelberg, Germany
| | - Benjamin A Hoff
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109
| | - Aleksa B Fortuna
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109
| | | | - Philip Konietzke
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, 69120 Heidelberg, Germany; Translational Lung Research Center, Heidelberg (TLRC), German Lung Research Center (DZL), 69120 Heidelberg, Germany
| | - Mark O Wielpütz
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, 69120 Heidelberg, Germany; Translational Lung Research Center, Heidelberg (TLRC), German Lung Research Center (DZL), 69120 Heidelberg, Germany
| | - Terry E Robinson
- Center of Excellence in Pulmonary Biology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94304
| | - Craig J Galbán
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109.
| |
Collapse
|
38
|
Longitudinal airway remodeling in active and past smokers in a lung cancer screening population. Eur Radiol 2018; 29:2968-2980. [PMID: 30552475 DOI: 10.1007/s00330-018-5890-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Revised: 10/07/2018] [Accepted: 11/13/2018] [Indexed: 10/27/2022]
Abstract
OBJECTIVES To longitudinally investigate smoking cessation-related changes of quantitative computed tomography (QCT)-based airway metrics in a group of heavy smokers. METHODS CT scans were acquired in a lung cancer screening population over 4 years at 12-month intervals in 284 long-term ex-smokers (ES), 405 continuously active smokers (CS), and 31 subjects who quitted smoking within 2 years after baseline CT (recent quitters, RQ). Total diameter (TD), lumen area (LA), and wall percentage (WP) of 1st-8th generation airways were computed using airway analysis software. Inter-group comparison was performed using Mann-Whitney U test or Student's t test (two groups), and ANOVA or ANOVA on ranks with Dunn's multiple comparison test (more than two groups), while Fisher's exact test or chi-squared test was used for categorical data. Multiple linear regression was used for multivariable analysis. RESULTS At any time, TD and LA were significantly higher in ES than CS, for example, in 5th-8th generation airways at baseline with 6.24 mm vs. 5.93 mm (p < 0.001) and 15.23 mm2 vs. 13.51 mm2 (p < 0.001), respectively. RQ showed higher TD (6.15 mm vs. 5.93 mm, n.s.) and significantly higher LA (14.77 mm2 vs. 13.51 mm2, p < 0.001) than CS after 3 years, and after 4 years. In multivariate analyses, smoking status independently predicted TD, LA, and WP at baseline, at 3 years and 4 years (p < 0.01-0.001), with stronger impact than pack years. CONCLUSIONS Bronchial dimensions depend on the smoking status. Smoking-induced airway remodeling can be partially reversible after smoking cessation even in long-term heavy smokers. Therefore, QCT-based airway metrics in clinical trials should consider the current smoking status besides pack years. KEY POINTS • Airway lumen and diameter are decreased in active smokers compared to ex-smokers, and there is a trend towards increased airway wall thickness in active smokers. • Smoking-related airway changes improve within 2 years after smoking cessation. • Smoking status is an independent predictor of airway dimensions.
Collapse
|
39
|
Chassagnon G, Brun AL, Bennani S, Chergui N, Freche G, Revel MP. [Bronchiectasis imaging]. REVUE DE PNEUMOLOGIE CLINIQUE 2018; 74:299-314. [PMID: 30348546 DOI: 10.1016/j.pneumo.2018.09.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Bronchiectasis are defined as an irreversible focal or diffuse dilatation of the bronchi and can be associated with significant morbidity. The prevalence is currently increasing, probably due to an increased use of thoracic computed tomography (CT). Indeed, the diagnosis relies on imaging and chest CT is the gold standard technique. The main diagnosis criterion is an increased bronchial diameter as compared to that of the companion artery. However, false positives are possible when the artery diameter is decreased, which is called pseudo-bronchiectasis. Other features such as the lack of bronchial tapering, and visibility of bronchi within 1cm of the pleural surface are also diagnostic criteria, and other CT features of bronchial disease are commonly seen. Thoracic imaging also allows severity assessment and long-term monitoring of structural abnormalities. The distribution pattern and the presence of associated findings on chest CT help identifying specific causes of bronchiectasis. Lung MRI and ultra-low dose CT and are promising imaging modalities that may play a role in the future. The objectives of this review are to describe imaging features for the diagnosis and severity assessment of bronchiectasis, to review findings suggesting the cause of bronchiectasis, and to present the new developments in bronchiectasis imaging.
Collapse
Affiliation(s)
- G Chassagnon
- Unité d'imagerie thoracique, groupe hospitalier Cochin-Broca-Hôtel-Dieu, AP-HP, 27, rue du Faubourg-Saint-Jacques, 75014 Paris, France.
| | - A-L Brun
- Unité d'imagerie thoracique, groupe hospitalier Cochin-Broca-Hôtel-Dieu, AP-HP, 27, rue du Faubourg-Saint-Jacques, 75014 Paris, France
| | - S Bennani
- Unité d'imagerie thoracique, groupe hospitalier Cochin-Broca-Hôtel-Dieu, AP-HP, 27, rue du Faubourg-Saint-Jacques, 75014 Paris, France
| | - N Chergui
- Unité d'imagerie thoracique, groupe hospitalier Cochin-Broca-Hôtel-Dieu, AP-HP, 27, rue du Faubourg-Saint-Jacques, 75014 Paris, France
| | - G Freche
- Unité d'imagerie thoracique, groupe hospitalier Cochin-Broca-Hôtel-Dieu, AP-HP, 27, rue du Faubourg-Saint-Jacques, 75014 Paris, France
| | - M-P Revel
- Unité d'imagerie thoracique, groupe hospitalier Cochin-Broca-Hôtel-Dieu, AP-HP, 27, rue du Faubourg-Saint-Jacques, 75014 Paris, France
| |
Collapse
|
40
|
Konietzke P, Weinheimer O, Wielpütz MO, Wagner WL, Kaukel P, Eberhardt R, Heussel CP, Kauczor HU, Herth FJ, Schuhmann M. Quantitative CT detects changes in airway dimensions and air-trapping after bronchial thermoplasty for severe asthma. Eur J Radiol 2018; 107:33-38. [PMID: 30292270 DOI: 10.1016/j.ejrad.2018.08.007] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Revised: 07/29/2018] [Accepted: 08/09/2018] [Indexed: 01/03/2023]
Abstract
OBJECTIVES Bronchial thermoplasty (BT) can be considered in the treatment of severe asthma to reduce airway smooth muscle mass and bronchoconstriction. We hypothesized that BT may thus have long-term effects on airway dimensions and air-trapping detectable by quantitative computed tomography (QCT). METHODS Paired in- and expiratory CT and inspiratory CT were acquired in 17 patients with severe asthma before and up to two years after bronchial thermoplasty and in 11 additional conservatively treated patients with serve asthma, respectively. A fully automatic software calculated the airways metrics for wall thickness (WT), wall percentage (WP), lumen area (LA) and total diameter (TD). Furthermore, lung air-trapping was quantified by determining the quotient of mean lung attenuation in expiration vs. inspiration (E/I MLA) and relative volume change in the Hounsfield interval -950 to -856 in expiration to inspiration (RVC856-950) in a generation- and lobe-based approach, respectively. RESULTS BT reduced WT for the combined analysis of the 2nd-7th airway generation significantly by 0.06 mm (p = 0.026) and WP by 2.05% (p < 0.001), whereas LA and TD did not change significantly (p = 0.147, p = 0.706). No significant changes were found in the control group. Furthermore, E/I MLA and RVC856-950 decreased significantly after BT by 12.65% and 1.77% (p < 0.001), respectively. CONCLUSION BT significantly reduced airway narrowing and air-trapping in patients with severe asthma. This can be interpreted as direct therapeutic effects caused by a reduction in airway-smooth muscle mass and changes in innervation. A reduction in air-trapping indicates an influence on more peripheral airways not directly treated by the BT procedure.
Collapse
Affiliation(s)
- Philip Konietzke
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany; Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, 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, University Hospital of Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany; Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, 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 O Wielpütz
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany; Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, 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 L Wagner
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany; Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, 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
| | - Philine Kaukel
- Department of Respiratory and Critical Care Medicine, Thoraxklinik at University of Heidelberg, Röntgenstraße 1, 69126 Heidelberg, Germany
| | - Ralf Eberhardt
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Im Neuenheimer Feld 156, 69120 Heidelberg, Germany; Department of Respiratory and Critical Care Medicine, Thoraxklinik at University of Heidelberg, Röntgenstraße 1, 69126 Heidelberg, Germany
| | - Claus P Heussel
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany; Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, 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, University Hospital of Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany; Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, 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
| | - Felix J Herth
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Im Neuenheimer Feld 156, 69120 Heidelberg, Germany; Department of Respiratory and Critical Care Medicine, Thoraxklinik at University of Heidelberg, Röntgenstraße 1, 69126 Heidelberg, Germany
| | - Maren Schuhmann
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Im Neuenheimer Feld 156, 69120 Heidelberg, Germany; Department of Respiratory and Critical Care Medicine, Thoraxklinik at University of Heidelberg, Röntgenstraße 1, 69126 Heidelberg, Germany
| |
Collapse
|
41
|
Chassagnon G, Martin C, Burgel PR, Hubert D, Fajac I, Paragios N, Zacharaki EI, Legmann P, Coste J, Revel MP. An automated computed tomography score for the cystic fibrosis lung. Eur Radiol 2018; 28:5111-5120. [PMID: 29869171 DOI: 10.1007/s00330-018-5516-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2017] [Revised: 04/16/2018] [Accepted: 04/26/2018] [Indexed: 01/25/2023]
Abstract
OBJECTIVES To develop an automated density-based computed tomography (CT) score evaluating high-attenuating lung structural abnormalities in patients with cystic fibrosis (CF). METHODS Seventy adult CF patients were evaluated. The development cohort comprised 17 patients treated with ivacaftor, with 45 pre-therapeutic and follow-up chest CT scans. Another cohort of 53 patients not treated with ivacaftor was used for validation. CT-density scores were calculated using fixed and adapted thresholds based on histogram characteristics, such as the mode and standard deviation. Visual CF-CT score was also calculated. Correlations between the CT scores and forced expiratory volume in 1 s (FEV1% pred), and between their changes over time were assessed. RESULTS On cross-sectional evaluation, the correlation coefficients between FEV1%pred and the automated scores were slightly lower to that of the visual score in the development and validation cohorts (R = up to -0.68 and -0.61, versus R = -0.72 and R = -0.64, respectively). Conversely, the correlation to FEV1%pred tended to be higher for automated scores (R = up to -0.61) than for visual score (R = -0.49) on longitudinal follow-up. Automated scores based on Mode + 3 SD and Mode +300 HU showed the highest cross-sectional (R = -0.59 to -0.68) and longitudinal (R = -0.51 to -0.61) correlation coefficients to FEV1%pred. CONCLUSIONS The developed CT-density score reliably quantifies high-attenuating lung structural abnormalities in CF. KEY POINTS • Automated CT score shows moderate to good cross-sectional correlations with FEV 1 %pred . • CT score has potential to be integrated into the standard reporting workflow.
Collapse
Affiliation(s)
- Guillaume Chassagnon
- Radiology Department, Groupe Hospitalier Cochin-Hotel Dieu, Université Paris Descartes, 27 Rue du Faubourg Saint-Jacques, 75014, Paris, France.
- Centre for Visual Computing, Ecole Centrale Paris, Grande Voie des Vignes, 92290, Chatenay Malabry, France.
| | - Clémence Martin
- Pulmonary Department and Adult CF Centre, Groupe Hospitalier Cochin-Hotel Dieu, Université Paris Descartes, 27 Rue du Faubourg Saint-Jacques, 75014, Paris, France
| | - Pierre-Régis Burgel
- Pulmonary Department and Adult CF Centre, Groupe Hospitalier Cochin-Hotel Dieu, Université Paris Descartes, 27 Rue du Faubourg Saint-Jacques, 75014, Paris, France
| | - Dominique Hubert
- Pulmonary Department and Adult CF Centre, Groupe Hospitalier Cochin-Hotel Dieu, Université Paris Descartes, 27 Rue du Faubourg Saint-Jacques, 75014, Paris, France
| | - Isabelle Fajac
- Physiology Department, Groupe Hospitalier Cochin-Hotel Dieu, Université Paris Descartes, 27 Rue du Faubourg Saint-Jacques, 75014, Paris, France
| | - Nikos Paragios
- Centre for Visual Computing, Ecole Centrale Paris, Grande Voie des Vignes, 92290, Chatenay Malabry, France
| | - Evangelia I Zacharaki
- Centre for Visual Computing, Ecole Centrale Paris, Grande Voie des Vignes, 92290, Chatenay Malabry, France
| | - Paul Legmann
- Radiology Department, Groupe Hospitalier Cochin-Hotel Dieu, Université Paris Descartes, 27 Rue du Faubourg Saint-Jacques, 75014, Paris, France
| | - Joel Coste
- Biostatistics and Epidemiology Department, Groupe Hospitalier Cochin-Hotel Dieu, Université Paris Descartes, 27 Rue du Faubourg Saint-Jacques, 75014, Paris, France
| | - Marie-Pierre Revel
- Radiology Department, Groupe Hospitalier Cochin-Hotel Dieu, Université Paris Descartes, 27 Rue du Faubourg Saint-Jacques, 75014, Paris, France
| |
Collapse
|
42
|
Validation of automated lobe segmentation on paired inspiratory-expiratory chest CT in 8-14 year-old children with cystic fibrosis. PLoS One 2018; 13:e0194557. [PMID: 29630630 PMCID: PMC5890971 DOI: 10.1371/journal.pone.0194557] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Accepted: 03/06/2018] [Indexed: 01/02/2023] Open
Abstract
Objectives Densitometry on paired inspiratory and expiratory multidetector computed tomography (MDCT) for the quantification of air trapping is an important approach to assess functional changes in airways diseases such as cystic fibrosis (CF). For a regional analysis of functional deficits, an accurate lobe segmentation algorithm applicable to inspiratory and expiratory scans is beneficial. Materials and methods We developed a fully automated lobe segmentation algorithm, and subsequently validated automatically generated lobe masks (ALM) against manually corrected lobe masks (MLM). Paired inspiratory and expiratory CTs from 16 children with CF (mean age 11.1±2.4) acquired at 4 time-points (baseline, 3mon, 12mon, 24mon) with 2 kernels (B30f, B60f) were segmented, resulting in 256 ALM. After manual correction spatial overlap (Dice index) and mean differences in lung volume and air trapping were calculated for ALM vs. MLM. Results The mean overlap calculated with Dice index between ALM and MLM was 0.98±0.02 on inspiratory, and 0.86±0.07 on expiratory CT. If 6 lobes were segmented (lingula treated as separate lobe), the mean overlap was 0.97±0.02 on inspiratory, and 0.83±0.08 on expiratory CT. The mean differences in lobar volumes calculated in accordance with the approach of Bland and Altman were generally low, ranging on inspiratory CT from 5.7±52.23cm3 for the right upper lobe to 17.41±14.92cm3 for the right lower lobe. Higher differences were noted on expiratory CT. The mean differences for air trapping were even lower, ranging from 0±0.01 for the right upper lobe to 0.03±0.03 for the left lower lobe. Conclusions Automatic lobe segmentation delivers excellent results for inspiratory and good results for expiratory CT. It may become an important component for lobe-based quantification of functional deficits in cystic fibrosis lung disease, reducing necessity for user-interaction in CT post-processing.
Collapse
|
43
|
Wada DT, de Pádua AI, Lima Filho MO, Marin Neto JA, Elias Júnior J, Baddini-Martinez J, Santos MK. Use of computed tomography and automated software for quantitative analysis of the vasculature of patients with pulmonary hypertension. Radiol Bras 2017; 50:351-358. [PMID: 29307924 PMCID: PMC5746878 DOI: 10.1590/0100-3984.2016.0163] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Objective To perform a quantitative analysis of the lung parenchyma and pulmonary
vasculature of patients with pulmonary hypertension (PH) on computed
tomography angiography (CTA) images, using automated software. Materials and Methods We retrospectively analyzed the CTA findings and clinical records of 45
patients with PH (17 males and 28 females), in comparison with a control
group of 20 healthy individuals (7 males and 13 females); the mean age
differed significantly between the two groups (53 ± 14.7 vs. 35
± 9.6 years; p = 0.0001). Results The automated analysis showed that, in comparison with the controls, the
patients with PH showed lower 10th percentile values for lung density,
higher vascular volumes in the right upper lung lobe, and higher vascular
volume ratios between the upper and lower lobes. In our quantitative
analysis, we found no differences among the various PH subgroups. We
inferred that a difference in the 10th percentile values indicates areas of
hypovolemia in patients with PH and that a difference in pulmonary vascular
volumes indicates redistribution of the pulmonary vasculature and an
increase in pulmonary vasculature resistance. Conclusion Automated analysis of pulmonary vessels on CTA images revealed alterations
and could represent an objective diagnostic tool for the evaluation of
patients with PH.
Collapse
Affiliation(s)
- Danilo Tadao Wada
- MSc, Attending Physician at the Centro de Ciências das Imagens e Física Médica (CCIFM) of the Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (HCFMRP-USP), Ribeirão Preto, SP, Brazil
| | - Adriana Ignácio de Pádua
- PhD, Attending Physician in the Pulmonology Department of the Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (HCFMRP-USP), Ribeirão Preto, SP, Brazil
| | - Moyses Oliveira Lima Filho
- PhD, Attending Physician in the Cardiology Department of the Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (HCFMRP-USP), Ribeirão Preto, SP, Brazil
| | - José Antonio Marin Neto
- PhD, Professor in the Department of Internal Medicine of the Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (HCFMRP-USP), Ribeirão Preto, SP, Brazil
| | - Jorge Elias Júnior
- PhD, Professor in the Department of Internal Medicine of the Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (HCFMRP-USP), Ribeirão Preto, SP, Brazil
| | - José Baddini-Martinez
- PhD, Professor in the Department of Internal Medicine of the Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (HCFMRP-USP), Ribeirão Preto, SP, Brazil
| | - Marcel Koenigkam Santos
- PhD, Collaborating Professor in the Department of Internal Medicine of the Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (HCFMRP-USP), Ribeirão Preto, SP, Brazil
| |
Collapse
|
44
|
Jobst BJ, Weinheimer O, Trauth M, Becker N, Motsch E, Groß ML, Tremper J, Delorme S, Eigentopf A, Eichinger M, Kauczor HU, Wielpütz MO. Effect of smoking cessation on quantitative computed tomography in smokers at risk in a lung cancer screening population. Eur Radiol 2017; 28:807-815. [DOI: 10.1007/s00330-017-5030-6] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2016] [Revised: 05/10/2017] [Accepted: 08/10/2017] [Indexed: 01/17/2023]
|
45
|
Leutz-Schmidt P, Weinheimer O, Jobst BJ, Dinkel J, Biederer J, Kauczor HU, Puderbach MU, Wielpütz MO. Influence of exposure parameters and iterative reconstruction on automatic airway segmentation and analysis on MDCT-An ex vivo phantom study. PLoS One 2017; 12:e0182268. [PMID: 28767732 PMCID: PMC5540604 DOI: 10.1371/journal.pone.0182268] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Accepted: 07/14/2017] [Indexed: 11/18/2022] Open
Abstract
OBJECTIVES To evaluate the influence of exposure parameters and raw-data-based iterative reconstruction (IR) on computer-aided segmentation and quantitative analysis of the tracheobronchial tree on multidetector computed tomography (MDCT). MATERIAL AND METHODS 10 porcine heart-lung-explants were mounted inside a dedicated chest phantom. MDCT was performed at 120kV and 80kV with 120, 60, 30 and 12 mAs each. All scans were reconstructed with filtered back projection (FBP) or IR, resulting in a total of 160 datasets. The maximum number of detected airway segments, most peripheral airway generation detected, generation-specific airway wall thickness (WT), total diameter (TD) and normalized wall thickness (pi10) were compared. RESULTS The number of detected airway segments decreased slightly with dose (324.8±118 at 120kV/120mAs vs. 288.9±130 at 80kV/30mAs with FBP, p<0.05) and was not changed by IR. The 20th generation was constantly detected as most peripheral. WT did not change significantly with exposure parameters and reconstruction algorithm across all generations: range 1st generation 2.4-2.7mm, 5th 1.0-1.1mm, and 10th 0.7mm with FBP; 1st 2.3-2.4mm, 5th 1.0-1.1mm, and 10th 0.7-0.8mm with IR. pi10 was not affected as well (range 0.32-0.34mm). CONCLUSIONS Exposure parameters and IR had no relevant influence on measured airway parameters even for WT <1mm. Thus, no systematic errors would be expected using automatic airway analysis with low-dose MDCT and IR.
Collapse
Affiliation(s)
- Patricia Leutz-Schmidt
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center (TLRC) Heidelberg, Member of the German Center for Lung Research (DZL), 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 (TLRC) Heidelberg, Member of the German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Bertram J. Jobst
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center (TLRC) Heidelberg, Member of the German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Julien Dinkel
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center (TLRC) Heidelberg, Member of the German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Jürgen Biederer
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center (TLRC) Heidelberg, Member of the German Center for Lung Research (DZL), Heidelberg, Germany
- Radiologie Darmstadt, Gross-Gerau County Hospital, Gross-Gerau, Germany
- Department of Radiology, German Cancer Research Center (dkfz), Heidelberg, Germany
| | - Hans-Ulrich Kauczor
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center (TLRC) Heidelberg, Member of the German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Michael U. Puderbach
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center (TLRC) Heidelberg, Member of the German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
- Department of Radiology, German Cancer Research Center (dkfz), Heidelberg, Germany
| | - Mark O. Wielpütz
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center (TLRC) Heidelberg, Member of the German Center for Lung Research (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
- Department of Radiology, German Cancer Research Center (dkfz), Heidelberg, Germany
| |
Collapse
|
46
|
Athanazio R, Pereira MC, Gramblicka G, Cavalcanti-Lundgren F, de Figueiredo MF, Arancibia F, Rached S, de la Rosa D, Máiz-Carro L, Girón R, Olveira C, Prados C, Martinez-Garcia MA. Latin America validation of FACED score in patients with bronchiectasis: an analysis of six cohorts. BMC Pulm Med 2017; 17:73. [PMID: 28446170 PMCID: PMC5406918 DOI: 10.1186/s12890-017-0417-3] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2016] [Accepted: 04/19/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The FACED score is an easy-to-use multidimensional grading system that has demonstrated an excellent prognostic value for mortality in patients with bronchiectasis. A Spanish group developed the score but no multicenter international validation has yet been published. METHODS Retrospective and multicenter study conducted in six historical cohorts of patients from Latin America including 651 patients with bronchiectasis. Clinical, microbiological, functional, and radiological variables were collected, following the same criteria used in the original FACED score study. The vital status of all patients was determined in the fifth year of follow-up. The area under ROC curve (AUC-ROC) was used to calculate the predictive power of the FACED score for all-cause and respiratory deaths and both number and severity of exacerbations. The discriminatory power to divide patients into three groups of increasing severity was also analyzed. RESULTS Mean (SD) age of 48.2 (16), 32.9% of males. The mean FACED score was 2.35 (1.68). During the follow up, 95 patients (14.6%) died (66% from respiratory causes). The AUC ROC to predict all-cause and respiratory mortality were 0.81 (95% CI: 0.77 to 0.85) 0.84 (95% CI: 0.80 to 0.88) respectively, and 0.82 (95% CI: 078-0.87) for at least one hospitalization per year. The division into three score groups separated bronchiectasis into distinct mortality groups (mild: 3.7%; moderate: 20.7% and severe: 48.5% mortality; p < 0.001). CONCLUSIONS The FACED score was confirmed as an excellent predictor of all-cause and respiratory mortality and severe exacerbations, as well as having excellent discriminative capacity for different degrees of severity in various bronchiectasis populations.
Collapse
Affiliation(s)
- Rodrigo Athanazio
- Pulmonary Division, Heart Institute (InCor) do Hospital das Clinicas da Faculdade de Medicina da Universidade de São Paulo, Av Dr Eneas de Carvalho Aguiar, 44 – 5 andar (Pneumologia), São Paulo, 05403-900 Brazil
| | | | - Georgina Gramblicka
- Pneumology Service, Hospital del Tórax. Dr A. Cetrángolo, Buenos Aires, Argentina
| | | | | | | | - Samia Rached
- Pulmonary Division, Heart Institute (InCor) do Hospital das Clinicas da Faculdade de Medicina da Universidade de São Paulo, Av Dr Eneas de Carvalho Aguiar, 44 – 5 andar (Pneumologia), São Paulo, 05403-900 Brazil
| | | | - Luis Máiz-Carro
- Pneumology Service, Hospital Universitario Ramón y Cajal, Madrid, Spain
| | - Rosa Girón
- Pneumology Service, Hospital Universtario La Princesa, Madrid, Spain
| | - Casilda Olveira
- Pneumology Service, Hospital General de Málaga, Málaga, Spain
| | - Concepción Prados
- Pneumology Service, Hopital Universitario La Paz-Carlos III, Madrid, Spain
| | | |
Collapse
|
47
|
|
48
|
Santos MK, Cruvinel DL, de Menezes MB, Teixeira SR, Vianna EDO, Elias Júnior J, Martinez JAB. Quantitative computed tomography analysis of the airways in patients with cystic fibrosis using automated software: correlation with spirometry in the evaluation of severity. Radiol Bras 2016; 49:351-357. [PMID: 28100929 PMCID: PMC5238409 DOI: 10.1590/0100-3984.2015.0145] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Objective To perform a quantitative analysis of the airways using automated software,
in computed tomography images of patients with cystic fibrosis, correlating
the results with spirometric findings. Materials and Methods Thirty-four patients with cystic fibrosis were studied-20 males and 14
females; mean age 18 ± 9 years-divided into two groups according to
the spirometry findings: group I (n = 21), without severe
airflow obstruction (forced expiratory volume in first second [FEV1] >
50% predicted), and group II (n = 13), with severe
obstruction (FEV1 ≤ 50% predicted). The following tracheobronchial
tree parameters were obtained automatically: bronchial diameter, area,
thickness, and wall attenuation. Results On average, 52 bronchi per patient were studied. The number of bronchi
analyzed was higher in group II. The correlation with spirometry findings,
especially between the relative wall thickness of third to eighth bronchial
generation and predicted FEV1, was better in group I. Conclusion Quantitative analysis of the airways by computed tomography can be useful for
assessing disease severity in cystic fibrosis patients. In patients with
severe airflow obstruction, the number of bronchi studied by the method is
higher, indicating more bronchiectasis. In patients without severe
obstruction, the relative bronchial wall thickness showed a good correlation
with the predicted FEV1.
Collapse
Affiliation(s)
- Marcel Koenigkam Santos
- PhD, MD, Radiologist, Collaborating Professor at the Center for Imaging Sciences and Medical Physics of the Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (HCFMRP-USP), Ribeirão Preto, SP, Brazil
| | - Danilo Lemos Cruvinel
- MD, Radiology Specialist at the Center for Imaging Sciences and Medical Physics of the Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (HCFMRP-USP), Ribeirão Preto, SP, Brazil
| | - Marcelo Bezerra de Menezes
- PhD, MD, Attending Pulmonologist in the Pulmonology Sector of the Department of Clinical Medicine of the Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (FMRP-USP), Ribeirão Preto, SP, Brazil
| | - Sara Reis Teixeira
- PhD, MD, Attending Radiologist at the Center for Imaging Sciences and Medical Physics of the Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (HCFMRP-USP), Ribeirão Preto, SP, Brazil
| | - Elcio de Oliveira Vianna
- PhD, MD, Pulmonologist, Professor in the Pulmonology Sector of the Department of Clinical Medicine of the Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (FMRP-USP), Ribeirão Preto, SP, Brazil
| | - Jorge Elias Júnior
- PhD, MD, Radiologist, Professor at the Center for Imaging Sciences and Medical Physics of the Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (HCFMRP-USP), Ribeirão Preto, SP, Brazil
| | - José Antonio Baddini Martinez
- PhD, MD, Pulmonologist, Professor in the Pulmonology Sector of the Department of Clinical Medicine of the Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (FMRP-USP), Ribeirão Preto, SP, Brazil
| |
Collapse
|
49
|
Perez-Rovira A, Kuo W, Petersen J, Tiddens HAWM, de Bruijne M. Automatic airway-artery analysis on lung CT to quantify airway wall thickening and bronchiectasis. Med Phys 2016; 43:5736. [DOI: 10.1118/1.4963214] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
|
50
|
Kuo W, Kemner-van de Corput MP, Perez-Rovira A, de Bruijne M, Fajac I, Tiddens HA, van Straten M. Multicentre chest computed tomography standardisation in children and adolescents with cystic fibrosis: the way forward. Eur Respir J 2016; 47:1706-17. [DOI: 10.1183/13993003.01601-2015] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2015] [Accepted: 03/02/2016] [Indexed: 12/13/2022]
Abstract
Progressive cystic fibrosis (CF) lung disease is the main cause of mortality in CF patients. CF lung disease starts in early childhood. With current standards of care, respiratory function remains largely normal in children and more sensitive outcome measures are needed to monitor early CF lung disease. Chest CT is currently the most sensitive imaging modality to monitor pulmonary structural changes in children and adolescents with CF. To quantify structural lung disease reliably among multiple centres, standardisation of chest CT protocols is needed. SCIFI CF (Standardised Chest Imaging Framework for Interventions and Personalised Medicine in CF) was founded to characterise chest CT image quality and radiation doses among 16 participating European CF centres in 10 different countries. We aimed to optimise CT protocols in children and adolescents among several CF centres. A large variety was found in CT protocols, image quality and radiation dose usage among the centres. However, the performance of all CT scanners was found to be very similar, when taking spatial resolution and radiation dose into account. We conclude that multicentre standardisation of chest CT in children and adolescents with CF can be achieved for future clinical trials.
Collapse
|