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Iwasawa T, Matsushita S, Hirayama M, Baba T, Ogura T. Quantitative Analysis for Lung Disease on Thin-Section CT. Diagnostics (Basel) 2023; 13:2988. [PMID: 37761355 PMCID: PMC10528918 DOI: 10.3390/diagnostics13182988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 08/30/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023] Open
Abstract
Thin-section computed tomography (CT) is widely employed not only for assessing morphology but also for evaluating respiratory function. Three-dimensional images obtained from thin-section CT provide precise measurements of lung, airway, and vessel volumes. These volumetric indices are correlated with traditional pulmonary function tests (PFT). CT also generates lung histograms. The volume ratio of areas with low and high attenuation correlates with PFT results. These quantitative image analyses have been utilized to investigate the early stages and disease progression of diffuse lung diseases, leading to the development of novel concepts such as pre-chronic obstructive pulmonary disease (pre-COPD) and interstitial lung abnormalities. Quantitative analysis proved particularly valuable during the COVID-19 pandemic when clinical evaluations were limited. In this review, we introduce CT analysis methods and explore their clinical applications in the context of various lung diseases. We also highlight technological advances, including images with matrices of 1024 × 1024 and slice thicknesses of 0.25 mm, which enhance the accuracy of these analyses.
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Affiliation(s)
- Tae Iwasawa
- Department of Radiology, Kanagawa Cardiovascular & Respiratory Center, 6-16-1 Tomioka-higashi, Kanazawa-ku, Yokohama 236-0051, Japan; (S.M.); (M.H.)
| | - Shoichiro Matsushita
- Department of Radiology, Kanagawa Cardiovascular & Respiratory Center, 6-16-1 Tomioka-higashi, Kanazawa-ku, Yokohama 236-0051, Japan; (S.M.); (M.H.)
| | - Mariko Hirayama
- Department of Radiology, Kanagawa Cardiovascular & Respiratory Center, 6-16-1 Tomioka-higashi, Kanazawa-ku, Yokohama 236-0051, Japan; (S.M.); (M.H.)
| | - Tomohisa Baba
- Department of Respiratory Medicine, Kanagawa Cardiovascular & Respiratory Center, 6-16-1 Tomioka-higashi, Kanazawa-ku, Yokohama 236-0051, Japan; (T.B.); (T.O.)
| | - Takashi Ogura
- Department of Respiratory Medicine, Kanagawa Cardiovascular & Respiratory Center, 6-16-1 Tomioka-higashi, Kanazawa-ku, Yokohama 236-0051, Japan; (T.B.); (T.O.)
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Similarities in Quantitative Computed Tomography Imaging of the Lung in Severe Asthma with Persistent Airflow Limitation and Chronic Obstructive Pulmonary Disease. J Clin Med 2021; 10:jcm10215058. [PMID: 34768576 PMCID: PMC8584690 DOI: 10.3390/jcm10215058] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 10/19/2021] [Accepted: 10/26/2021] [Indexed: 11/21/2022] Open
Abstract
Background: Severe asthma with persistent airflow limitation (SA-PAL) and chronic obstructive pulmonary disease (COPD) are characterised by irreversible airflow limitation and the remodelling of the airways. The phenotypes of the diseases overlap and may cause diagnostic and therapeutic concerns. Methods: There were 10 patients with SA-PAL, 11 patients with COPD, and 10 healthy volunteers (HV) enrolled in this study. The patients were examined with a 128-multislice scanner at full inspiration. Measurements were taken from the third to ninth bronchial generations. Results: The thickness of the bronchial wall was greater in the SA-PAL than in the COPD group for most bronchial generations (p < 0.05). The mean lung density was the lowest in the SA-PAL group (−846 HU), followed by the COPD group (−836 HU), with no statistical difference between these two groups. The low-attenuation volume percentage (LAV% < −950 HU) was significantly higher in the SA-PAL group (15.8%) and COPD group (10.4%) compared with the HV group (7%) (p = 0.03). Conclusion: Severe asthma with persistent airflow limitation and COPD become similar with time within the functional and morphological dimensions. Emphysema qualities are present in COPD and in SA-PAL patients.
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Li T, Zhou HP, Zhou ZJ, Guo LQ, Zhou L. Computed tomography-identified phenotypes of small airway obstructions in chronic obstructive pulmonary disease. Chin Med J (Engl) 2021; 134:2025-2036. [PMID: 34517376 PMCID: PMC8440009 DOI: 10.1097/cm9.0000000000001724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Indexed: 12/02/2022] Open
Abstract
ABSTRACT Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease characteristic of small airway inflammation, obstruction, and emphysema. It is well known that spirometry alone cannot differentiate each separate component. Computed tomography (CT) is widely used to determine the extent of emphysema and small airway involvement in COPD. Compared with the pulmonary function test, small airway CT phenotypes can accurately reflect disease severity in patients with COPD, which is conducive to improving the prognosis of this disease. CT measurement of central airway morphology has been applied in clinical, epidemiologic, and genetic investigations as an inference of the presence and severity of small airway disease. This review will focus on presenting the current knowledge and methodologies in chest CT that aid in identifying discrete COPD phenotypes.
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Affiliation(s)
- Tao Li
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu 210029, China
- Department of Respiratory Medicine, Xuzhou First People's Hospital, Xuzhou, Jiangsu 221116, China
| | - Hao-Peng Zhou
- Department of Medicine, Jiangsu University School of Medicine, Zhenjiang, Jiangsu 212013, China
| | - Zhi-Jun Zhou
- Institute of Radio Frequency & Optical Electronics-Integrated Circuits, School of Information and Engineering, Southeast University, Nanjing, Jiangsu 210096, China
| | - Li-Quan Guo
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China
| | - Linfu Zhou
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu 210029, China
- Institute of Integrative Medicine, Nanjing Medical University, Nanjing, Jiangsu 210029, China
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Ippolito D, Ragusi M, Gandola D, Maino C, Pecorelli A, Terrani S, Peroni M, Giandola T, Porta M, Talei Franzesi C, Sironi S. Computed tomography semi-automated lung volume quantification in SARS-CoV-2-related pneumonia. Eur Radiol 2021; 31:2726-2736. [PMID: 33125559 PMCID: PMC7596627 DOI: 10.1007/s00330-020-07271-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 08/20/2020] [Accepted: 09/08/2020] [Indexed: 02/08/2023]
Abstract
OBJECTIVES To evaluate a semi-automated segmentation and ventilated lung quantification on chest computed tomography (CT) to assess lung involvement in patients affected by SARS-CoV-2. Results were compared with clinical and functional parameters and outcomes. METHODS All images underwent quantitative analyses with a dedicated workstation using a semi-automatic lung segmentation software to compute ventilated lung volume (VLV), Ground-glass opacity (GGO) volume (GGO-V), and consolidation volume (CONS-V) as absolute volume and as a percentage of total lung volume (TLV). The ratio between CONS-V, GGO-V, and VLV (CONS-V/VLV and GGO-V/VLV, respectively), TLV (CONS-V/TLV, GGO-V/TLV, and GGO-V + CONS-V/TLV respectively), and the ratio between VLV and TLV (VLV/TLV) were calculated. RESULTS A total of 108 patients were enrolled. GGO-V/TLV significantly correlated with WBC (r = 0.369), neutrophils (r = 0.446), platelets (r = 0.182), CRP (r = 0.190), PaCO2 (r = 0.176), HCO3- (r = 0.284), and PaO2/FiO2 (P/F) values (r = - 0.344). CONS-V/TLV significantly correlated with WBC (r = 0.294), neutrophils (r = 0.300), lymphocytes (r = -0.225), CRP (r = 0.306), PaCO2 (r = 0.227), pH (r = 0.162), HCO3- (r = 0.394), and P/F (r = - 0.419) values. Statistically significant differences between CONS-V, GGO-V, GGO-V/TLV, CONS-V/TLV, GGO-V/VLV, CONS-V/VLV, GGO-V + CONS-V/TLV, VLV/TLV, CT score, and invasive ventilation by ET were found (all p < 0.05). CONCLUSION The use of quantitative semi-automated algorithm for lung CT elaboration effectively correlates the severity of SARS-CoV-2-related pneumonia with laboratory parameters and the need for invasive ventilation. KEY POINTS • Pathological lung volumes, expressed both as GGO-V and as CONS-V, can be considered a useful tool in SARS-CoV-2-related pneumonia. • All lung volumes, expressed themselves and as ratio with TLV and VLV, correlate with laboratory data, in particular C-reactive protein and white blood cell count. • All lung volumes correlate with patient's outcome, in particular concerning invasive ventilation.
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Affiliation(s)
- Davide Ippolito
- Department of Diagnostic Radiology, San Gerardo Hospital, University of Milano-Bicocca, Via Pergolesi 33, Monza, MB, 20900, Italy.
- School of Medicine, University of Milano-Bicocca, Via Cadore 48, Monza, MB, 20900, Italy.
| | - Maria Ragusi
- Department of Diagnostic Radiology, San Gerardo Hospital, University of Milano-Bicocca, Via Pergolesi 33, Monza, MB, 20900, Italy
- School of Medicine, University of Milano-Bicocca, Via Cadore 48, Monza, MB, 20900, Italy
| | - Davide Gandola
- Department of Diagnostic Radiology, San Gerardo Hospital, University of Milano-Bicocca, Via Pergolesi 33, Monza, MB, 20900, Italy
- School of Medicine, University of Milano-Bicocca, Via Cadore 48, Monza, MB, 20900, Italy
| | - Cesare Maino
- Department of Diagnostic Radiology, San Gerardo Hospital, University of Milano-Bicocca, Via Pergolesi 33, Monza, MB, 20900, Italy
- School of Medicine, University of Milano-Bicocca, Via Cadore 48, Monza, MB, 20900, Italy
| | - Anna Pecorelli
- Department of Diagnostic Radiology, San Gerardo Hospital, University of Milano-Bicocca, Via Pergolesi 33, Monza, MB, 20900, Italy
- School of Medicine, University of Milano-Bicocca, Via Cadore 48, Monza, MB, 20900, Italy
| | - Simone Terrani
- Philips Healthcare, Viale Sacra 235, Milan, MI, 20126, Italy
| | - Marta Peroni
- Philips Healthcare, Viale Sacra 235, Milan, MI, 20126, Italy
| | - Teresa Giandola
- Department of Diagnostic Radiology, San Gerardo Hospital, University of Milano-Bicocca, Via Pergolesi 33, Monza, MB, 20900, Italy
- School of Medicine, University of Milano-Bicocca, Via Cadore 48, Monza, MB, 20900, Italy
| | - Marco Porta
- Department of Diagnostic Radiology, San Gerardo Hospital, University of Milano-Bicocca, Via Pergolesi 33, Monza, MB, 20900, Italy
- School of Medicine, University of Milano-Bicocca, Via Cadore 48, Monza, MB, 20900, Italy
| | - Cammillo Talei Franzesi
- Department of Diagnostic Radiology, San Gerardo Hospital, University of Milano-Bicocca, Via Pergolesi 33, Monza, MB, 20900, Italy
- School of Medicine, University of Milano-Bicocca, Via Cadore 48, Monza, MB, 20900, Italy
| | - Sandro Sironi
- Department of Diagnostic Radiology, San Gerardo Hospital, University of Milano-Bicocca, Via Pergolesi 33, Monza, MB, 20900, Italy
- Department of Diagnostic Radiology, H Papa Giovanni XXIII, Piazza OMS 1, Bergamo, BG, 24127, Italy
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Wisselink HJ, Pelgrim GJ, Rook M, Imkamp K, van Ooijen PMA, van den Berge M, de Bock GH, Vliegenthart R. Ultra-low-dose CT combined with noise reduction techniques for quantification of emphysema in COPD patients: An intra-individual comparison study with standard-dose CT. Eur J Radiol 2021; 138:109646. [PMID: 33721769 DOI: 10.1016/j.ejrad.2021.109646] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Revised: 03/05/2021] [Accepted: 03/08/2021] [Indexed: 10/21/2022]
Abstract
PURPOSE Phantom studies in CT emphysema quantification show that iterative reconstruction and deep learning-based noise reduction (DLNR) allow lower radiation dose. We compared emphysema quantification on ultra-low-dose CT (ULDCT) with and without noise reduction, to standard-dose CT (SDCT) in chronic obstructive pulmonary disease (COPD). METHOD Forty-nine COPD patients underwent ULDCT (third generation dual-source CT; 70ref-mAs, Sn-filter 100kVp; median CTDIvol 0.38 mGy) and SDCT (64-multidetector CT; 40mAs, 120kVp; CTDIvol 3.04 mGy). Scans were reconstructed with filtered backprojection (FBP) and soft kernel. For ULDCT, we also applied advanced modelled iterative reconstruction (ADMIRE), levels 1/3/5, and DLNR, levels 1/3/5/9. Emphysema was quantified as Low Attenuation Value percentage (LAV%, ≤-950HU). ULDCT measures were compared to SDCT as reference standard. RESULTS For ULDCT, the median radiation dose was 84 % lower than for SDCT. Median extent of emphysema was 18.6 % for ULD-FBP and 15.4 % for SDCT (inter-quartile range: 11.8-28.4 % and 9.2 %-28.7 %, p = 0.002). Compared to SDCT, the range in limits of agreement of emphysema quantification as measure of variability was 14.4 for ULD-FBP, 11.0-13.1 for ULD-ADMIRE levels and 10.1-13.9 for ULD-DLNR levels. Optimal settings were ADMIRE 3 and DLNR 3, reducing variability of emphysema quantification by 24 % and 27 %, at slight underestimation of emphysema extent (-1.5 % and -2.9 %, respectively). CONCLUSIONS Ultra-low-dose CT in COPD patients allows dose reduction by 84 %. State-of-the-art noise reduction methods in ULDCT resulted in slight underestimation of emphysema compared to SDCT. Noise reduction methods (especially ADMIRE 3 and DLNR 3) reduced variability of emphysema quantification in ULDCT by up to 27 % compared to FBP.
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Affiliation(s)
- H J Wisselink
- University of Groningen, University Medical Center Groningen, Department of Radiology, Groningen, the Netherlands
| | - G J Pelgrim
- University of Groningen, University Medical Center Groningen, Department of Radiology, Groningen, the Netherlands
| | - M Rook
- University of Groningen, University Medical Center Groningen, Department of Radiology, Groningen, the Netherlands; Martini Hospital Groningen, Department of Radiology, Groningen, the Netherlands
| | - K Imkamp
- University of Groningen, University Medical Center Groningen, Department of Pulmonology, Groningen, the Netherlands
| | - P M A van Ooijen
- University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, Groningen, the Netherlands
| | - M van den Berge
- University of Groningen, University Medical Center Groningen, Department of Pulmonology, Groningen, the Netherlands
| | - G H de Bock
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
| | - R Vliegenthart
- University of Groningen, University Medical Center Groningen, Department of Radiology, Groningen, the Netherlands.
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Qin S, Yu X, Ma Q, Lin L, Li Q, Liu H, Zhang L, Leng S, Han W. Quantitative CT Analysis of Small Airway Remodeling in Patients with Chronic Obstructive Pulmonary Disease by a New Image Post-Processing System. Int J Chron Obstruct Pulmon Dis 2021; 16:535-544. [PMID: 33688178 PMCID: PMC7936712 DOI: 10.2147/copd.s295320] [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: 12/02/2020] [Accepted: 02/07/2021] [Indexed: 12/02/2022] Open
Abstract
Purpose To explore a practical marker for quantitatively analyzing the small airway remodeling in COPD by HRCT. Patients and Methods Twenty-four patients with COPD (GOLD I, n = 7; GOLD II, n = 8; GOLD III+IV, n = 9) and 14 healthy controls (7 normal pulmonary function; 7 small-airway disease (SAD)) were enrolled in the study as five groups, GOLD I, GOLD II, GOLD III+IV, normal and SAD. All subjects underwent HRCT and spirometry. With ISP 9.0, whole emphysema index (EI) and the airway parameters, including wall area (WA), lumen area (LA), airway area (AA) of the 3rd, 5th and 9th generations of bronchi, were measured successively. The ratio of LA/AA and WA/AA in the 3rd, 5th and 9th generations of bronchi were calculated and compared among groups. Results For the five groups, EI was increased only in GOLD III+IV group (P < 0.05), while the ratio of LA/AA (9-LA/AA) and WA/AA (9-WA/AA) in 9th generation of bronchi have significantly changed since SAD group (P < 0.05). There were significant correlation between FEV1generations of bronchi (r3 = 0.429, r5 = 0.583, r9 = 0.592, respectively, P < 0.05); FEV1% and WA/AA (r3 = –0.428, r5 = –0.532, r9 = –0.570, respectively, P < 0.05); as well as MMEF% and LA/AA (r3 = 0.421, r5 = 0.566, r9 = 0.610, respectively, P < 0.05); MMEF% and WA/AA (r3 = –0.421, r5 = –0.529, r9 = –0.593, respectively, P < 0.05). Conclusion Small airway remodeling has occurred in the early stage of COPD, while emphysema in the late stage of COPD. The 9-LA/AA and 9-WA/AA are accurate and practical markers for small airway remodeling of COPD.
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Affiliation(s)
- Shuyi Qin
- Department of Pulmonary and Critical Care Medicine, Qingdao Municipal Hospital, School of Medicine, Qingdao University, Qingdao, Shandong, People's Republic of China.,Respiratory Disease Key Laboratory of Qingdao, Qingdao Municipal Hospital, Qingdao, Shandong, People's Republic of China
| | - Xinjuan Yu
- Department of Pulmonary and Critical Care Medicine, Qingdao Municipal Hospital, School of Medicine, Qingdao University, Qingdao, Shandong, People's Republic of China.,Respiratory Disease Key Laboratory of Qingdao, Qingdao Municipal Hospital, Qingdao, Shandong, People's Republic of China
| | - Qianli Ma
- Department of Radiology, Qingdao Municipal Hospital, Qingdao, Shandong, People's Republic of China
| | - Li Lin
- Department of Pulmonary Medicine, Shandong Provincial Chest Hospital, Jinan, Shandong, People's Republic of China
| | - Qinghai Li
- Department of Pulmonary and Critical Care Medicine, Qingdao Municipal Hospital, School of Medicine, Qingdao University, Qingdao, Shandong, People's Republic of China.,Respiratory Disease Key Laboratory of Qingdao, Qingdao Municipal Hospital, Qingdao, Shandong, People's Republic of China
| | - Hong Liu
- Department of Pulmonary and Critical Care Medicine, Qingdao Municipal Hospital, School of Medicine, Qingdao University, Qingdao, Shandong, People's Republic of China.,Respiratory Disease Key Laboratory of Qingdao, Qingdao Municipal Hospital, Qingdao, Shandong, People's Republic of China
| | - Lei Zhang
- Department of Hospital Infection, Qingdao Municipal Hospital, Qingdao, Shandong, People's Republic of China
| | - Shuguang Leng
- Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - Wei Han
- Department of Pulmonary and Critical Care Medicine, Qingdao Municipal Hospital, School of Medicine, Qingdao University, Qingdao, Shandong, People's Republic of China.,Respiratory Disease Key Laboratory of Qingdao, Qingdao Municipal Hospital, Qingdao, Shandong, People's Republic of China
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