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Almeida SD, Norajitra T, Lüth CT, Wald T, Weru V, Nolden M, Jäger PF, von Stackelberg O, Heußel CP, Weinheimer O, Biederer J, Kauczor HU, Maier-Hein K. Prediction of disease severity in COPD: a deep learning approach for anomaly-based quantitative assessment of chest CT. Eur Radiol 2024; 34:4379-4392. [PMID: 38150075 PMCID: PMC11213737 DOI: 10.1007/s00330-023-10540-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 11/13/2023] [Accepted: 12/11/2023] [Indexed: 12/28/2023]
Abstract
OBJECTIVES To quantify regional manifestations related to COPD as anomalies from a modeled distribution of normal-appearing lung on chest CT using a deep learning (DL) approach, and to assess its potential to predict disease severity. MATERIALS AND METHODS Paired inspiratory/expiratory CT and clinical data from COPDGene and COSYCONET cohort studies were included. COPDGene data served as training/validation/test data sets (N = 3144/786/1310) and COSYCONET as external test set (N = 446). To differentiate low-risk (healthy/minimal disease, [GOLD 0]) from COPD patients (GOLD 1-4), the self-supervised DL model learned semantic information from 50 × 50 × 50 voxel samples from segmented intact lungs. An anomaly detection approach was trained to quantify lung abnormalities related to COPD, as regional deviations. Four supervised DL models were run for comparison. The clinical and radiological predictive power of the proposed anomaly score was assessed using linear mixed effects models (LMM). RESULTS The proposed approach achieved an area under the curve of 84.3 ± 0.3 (p < 0.001) for COPDGene and 76.3 ± 0.6 (p < 0.001) for COSYCONET, outperforming supervised models even when including only inspiratory CT. Anomaly scores significantly improved fitting of LMM for predicting lung function, health status, and quantitative CT features (emphysema/air trapping; p < 0.001). Higher anomaly scores were significantly associated with exacerbations for both cohorts (p < 0.001) and greater dyspnea scores for COPDGene (p < 0.001). CONCLUSION Quantifying heterogeneous COPD manifestations as anomaly offers advantages over supervised methods and was found to be predictive for lung function impairment and morphology deterioration. CLINICAL RELEVANCE STATEMENT Using deep learning, lung manifestations of COPD can be identified as deviations from normal-appearing chest CT and attributed an anomaly score which is consistent with decreased pulmonary function, emphysema, and air trapping. KEY POINTS • A self-supervised DL anomaly detection method discriminated low-risk individuals and COPD subjects, outperforming classic DL methods on two datasets (COPDGene AUC = 84.3%, COSYCONET AUC = 76.3%). • Our contrastive task exhibits robust performance even without the inclusion of expiratory images, while voxel-based methods demonstrate significant performance enhancement when incorporating expiratory images, in the COPDGene dataset. • Anomaly scores improved the fitting of linear mixed effects models in predicting clinical parameters and imaging alterations (p < 0.001) and were directly associated with clinical outcomes (p < 0.001).
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Affiliation(s)
- Silvia D Almeida
- Division of Medical Image Computing, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.
- Translational Lung Research Center Heidelberg (TLRC), Member of the German Lung Research Center (DZL), Heidelberg, Germany.
- Medical Faculty, Heidelberg University, Heidelberg, Germany.
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Medical Center, Heidelberg, Germany.
| | - Tobias Norajitra
- Division of Medical Image Computing, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), Member of the German Lung Research Center (DZL), Heidelberg, Germany
| | - Carsten T Lüth
- Interactive Machine Learning Group (IML), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Helmholtz Imaging, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Tassilo Wald
- Division of Medical Image Computing, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
- Helmholtz Imaging, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Vivienn Weru
- Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Marco Nolden
- Division of Medical Image Computing, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
- Pattern Analysis and Learning Group, Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Paul F Jäger
- Interactive Machine Learning Group (IML), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Helmholtz Imaging, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Oyunbileg von Stackelberg
- Pattern Analysis and Learning Group, Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Claus Peter Heußel
- Translational Lung Research Center Heidelberg (TLRC), Member of the German Lung Research Center (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Heidelberg, Germany
- Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University Hospital, Heidelberg, Germany
| | - Oliver Weinheimer
- Translational Lung Research Center Heidelberg (TLRC), Member of the German Lung Research Center (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Jürgen Biederer
- Translational Lung Research Center Heidelberg (TLRC), Member of the German Lung Research Center (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Heidelberg, Germany
- Faculty of Medicine, University of Latvia, Raina Bulvaris 19, Riga, LV-1586, Latvia
- Faculty of Medicine, Christian-Albrechts-Universität zu Kiel, D-24098, Kiel, Germany
| | - Hans-Ulrich Kauczor
- Translational Lung Research Center Heidelberg (TLRC), Member of the German Lung Research Center (DZL), Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Klaus Maier-Hein
- Division of Medical Image Computing, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.
- Translational Lung Research Center Heidelberg (TLRC), Member of the German Lung Research Center (DZL), Heidelberg, Germany.
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Medical Center, Heidelberg, Germany.
- Helmholtz Imaging, German Cancer Research Center (DKFZ), Heidelberg, Germany.
- Pattern Analysis and Learning Group, Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.
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Le L, Narula N, Zhou F, Smereka P, Ordner J, Theise N, Moore WH, Girvin F, Azour L, Moreira AL, Naidich DP, Ko JP. Diseases Involving the Lung Peribronchovascular Region: A CT Imaging Pathologic Classification. Chest 2024:S0012-3692(24)00776-1. [PMID: 38909953 DOI: 10.1016/j.chest.2024.05.033] [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: 11/29/2023] [Revised: 04/12/2024] [Accepted: 05/13/2024] [Indexed: 06/25/2024] Open
Abstract
TOPIC IMPORTANCE Chest CT imaging holds a major role in the diagnosis of lung diseases, many of which affect the peribronchovascular region. Identification and categorization of peribronchovascular abnormalities on CT imaging can assist in formulating a differential diagnosis and directing further diagnostic evaluation. REVIEW FINDINGS The peribronchovascular region of the lung encompasses the pulmonary arteries, airways, and lung interstitium. Understanding disease processes associated with structures of the peribronchovascular region and their appearances on CT imaging aids in prompt diagnosis. This article reviews current knowledge in anatomic and pathologic features of the lung interstitium composed of intercommunicating prelymphatic spaces, lymphatics, collagen bundles, lymph nodes, and bronchial arteries; diffuse lung diseases that present in a peribronchovascular distribution; and an approach to classifying diseases according to patterns of imaging presentations. Lung peribronchovascular diseases can appear on CT imaging as diffuse thickening, fibrosis, masses or masslike consolidation, ground-glass or air space consolidation, and cysts, acknowledging some disease may have multiple presentations. SUMMARY A category approach to peribronchovascular diseases on CT imaging can be integrated with clinical features as part of a multidisciplinary approach for disease diagnosis.
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Affiliation(s)
- Linda Le
- Department of Radiology, NYU Langone Health; NYU Grossman School of Medicine, New York, NY
| | - Navneet Narula
- Department of Pathology, NYU Langone Health; NYU Grossman School of Medicine, New York, NY
| | - Fang Zhou
- Department of Pathology, NYU Langone Health; NYU Grossman School of Medicine, New York, NY
| | - Paul Smereka
- Department of Radiology, NYU Langone Health; NYU Grossman School of Medicine, New York, NY
| | - Jeffrey Ordner
- Department of Pathology, NYU Langone Health; NYU Grossman School of Medicine, New York, NY
| | - Neil Theise
- Department of Pathology, NYU Langone Health; NYU Grossman School of Medicine, New York, NY
| | - William H Moore
- Department of Radiology, NYU Langone Health; NYU Grossman School of Medicine, New York, NY
| | - Francis Girvin
- Department of Diagnostic Radiology, Weill Cornell Medicine, New York, NY
| | - Lea Azour
- Department of Radiology, NYU Langone Health; NYU Grossman School of Medicine, New York, NY; Department of Radiological Sciences, UCLA David Geffen School of Medicine, Los Angeles, CA
| | - Andre L Moreira
- Department of Pathology, NYU Langone Health; NYU Grossman School of Medicine, New York, NY
| | - David P Naidich
- Department of Radiology, NYU Langone Health; NYU Grossman School of Medicine, New York, NY
| | - Jane P Ko
- Department of Radiology, NYU Langone Health; NYU Grossman School of Medicine, New York, NY.
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Sadoughi A, Synn S, Chan C, Schecter D, Hernandez Romero G, Virdi S, Sarkar A, Kim M. Ultrathin Bronchoscopy Without Virtual Navigation for Diagnosis of Peripheral Lung Lesions. Lung 2024:10.1007/s00408-024-00695-1. [PMID: 38864890 DOI: 10.1007/s00408-024-00695-1] [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: 12/24/2023] [Accepted: 03/31/2024] [Indexed: 06/13/2024]
Abstract
BACKGROUND The increasing incidence of encountering lung nodules necessitates an ongoing search for improved diagnostic procedures. Various bronchoscopic technologies have been introduced or are in development, but further studies are needed to define a method that fits best in clinical practice and health care systems. RESEARCH QUESTION How do basic bronchoscopic tools including a combination of thin (outer diameter 4.2 mm) and ultrathin bronchoscopes (outer diameter 3.0 mm), radial endobronchial ultrasound (rEBUS) and fluoroscopy perform in peripheral pulmonary lesion diagnosis? STUDY DESIGN AND METHODS This is a retrospective review of the performance of peripheral bronchoscopy using thin and ultrathin bronchoscopy with rEBUS and 2D fluoroscopy without a navigational system for evaluating peripheral lung lesions in a single academic medical center from 11/2015 to 1/2021. We used a strict definition for diagnostic yield and assessed the impact of different variables on diagnostic yield, specifically after employment of the ultrathin bronchoscope. Logistic regression models were employed to assess the independent associations of the most impactful variables. RESULTS A total of 322 patients were included in this study. The median of the long axis diameter was 2.2 cm and the median distance of the center of the lesion from the visceral pleural surface was 1.9 cm. Overall diagnostic yield was 81.3% after employment of the ultrathin bronchoscope, with more detection of concentric rEBUS views (93% vs. 78%, p < 0.001). Sensitivity for detecting malignancy also increased from 60.5% to 74.7% (p = 0.033) after incorporating the ultrathin scope into practice, while bronchus sign and peripheral location of the lesion were not found to affect diagnostic yield. Concentric rEBUS view, solid appearance, upper/middle lobe location and larger size of the nodules were found to be independent predictors of successful achievement of diagnosis at bronchoscopy. INTERPRETATION This study demonstrates a high diagnostic yield of biopsy of lung lesions achieved by utilization of thin and ultrathin bronchoscopes. Direct visualization of small peripheral airways with simultaneous rEBUS confirmation increased localization rate of small lesions in a conventional bronchoscopy setting without virtual navigational planning.
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Affiliation(s)
- Ali Sadoughi
- Division of Pulmonary, Montefiore Medical Center, Albert Einstein College of Medicine, New York City, USA.
| | - Shwe Synn
- Department of Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, New York City, USA
| | - Christine Chan
- Division of Pulmonary, Montefiore Medical Center, Albert Einstein College of Medicine, New York City, USA
| | - David Schecter
- Division of Pulmonary, Montefiore Medical Center, Albert Einstein College of Medicine, New York City, USA
| | | | - Sahil Virdi
- Division of pulmonary and critical care, United Hospital Center, West Virginia University Health System, Charleston, USA
| | - Abhishek Sarkar
- Section of Interventional Pulmonology, Department of Pulmonary, Critical Care, and Sleep Medicine, Westchester Medical Center / New York Medical College, Valhalla, USA
| | - Mimi Kim
- Division of Biostatistics, Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, USA
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Rodriguez K, Hariri LP, VanderLaan P, Abbott GF. Imaging of Small Airways Disease. Clin Chest Med 2024; 45:475-488. [PMID: 38816101 DOI: 10.1016/j.ccm.2024.02.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Abstract
Bronchiolitis refers to a small airways disease and may be classified by etiology and histologic features. In cellular bronchiolitis inflammatory cells involve the small airway wall and peribronchiolar alveoli and manifest on CT as centrilobular nodules of solid or ground glass attenuation. Constrictive bronchiolitis refers to luminal narrowing by concentric fibrosis. Direct CT signs of small airway disease include centrilobular nodules and branching tree-in-bud opacities. An indirect sign is mosaic attenuation that may be exaggerated on expiratory CT and represent air trapping. Imaging findings can be combined with clinical and pathologic data to facilitate a more accurate diagnosis.
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Affiliation(s)
- Karen Rodriguez
- Division of Thoracic Imaging and Intervention, Department of Radiology, Massachusetts General Hospital, Aus 202, 55 Fruit Street, Boston, MA 02114, USA
| | - Lida P Hariri
- Department of Pathology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA
| | - Paul VanderLaan
- Department of Pathology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA 02215, USA
| | - Gerald F Abbott
- Division of Thoracic Imaging and Intervention, Department of Radiology, Massachusetts General Hospital, Aus 202, 55 Fruit Street, Boston, MA 02114, USA.
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5
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Donuru A, Torigian DA, Knollmann F. Uncommon Causes of Interlobular Septal Thickening on CT Images and Their Distinguishing Features. Tomography 2024; 10:574-608. [PMID: 38668402 PMCID: PMC11054070 DOI: 10.3390/tomography10040045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Revised: 04/07/2024] [Accepted: 04/15/2024] [Indexed: 04/29/2024] Open
Abstract
Interlobular septa thickening (ILST) is a common and easily recognized feature on computed tomography (CT) images in many lung disorders. ILST thickening can be smooth (most common), nodular, or irregular. Smooth ILST can be seen in pulmonary edema, pulmonary alveolar proteinosis, and lymphangitic spread of tumors. Nodular ILST can be seen in the lymphangitic spread of tumors, sarcoidosis, and silicosis. Irregular ILST is a finding suggestive of interstitial fibrosis, which is a common finding in fibrotic lung diseases, including sarcoidosis and usual interstitial pneumonia. Pulmonary edema and lymphangitic spread of tumors are the commonly encountered causes of ILST. It is important to narrow down the differential diagnosis as much as possible by assessing the appearance and distribution of ILST, as well as other pulmonary and extrapulmonary findings. This review will focus on the CT characterization of the secondary pulmonary lobule and ILST. Various uncommon causes of ILST will be discussed, including infections, interstitial pneumonia, depositional/infiltrative conditions, inhalational disorders, malignancies, congenital/inherited conditions, and iatrogenic causes. Awareness of the imaging appearance and various causes of ILST allows for a systematic approach, which is important for a timely diagnosis. This study highlights the importance of a structured approach to CT scan analysis that considers ILST characteristics, associated findings, and differential diagnostic considerations to facilitate accurate diagnoses.
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Affiliation(s)
- Achala Donuru
- Division of Cardiothoracic Imaging, Department of Radiology, Hospitals of University of Pennsylvania, Philadelphia, PA 19104, USA; (D.A.T.); (F.K.)
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Lucà S, Pagliuca F, Perrotta F, Ronchi A, Mariniello DF, Natale G, Bianco A, Fiorelli A, Accardo M, Franco R. Multidisciplinary Approach to the Diagnosis of Idiopathic Interstitial Pneumonias: Focus on the Pathologist's Key Role. Int J Mol Sci 2024; 25:3618. [PMID: 38612431 PMCID: PMC11011777 DOI: 10.3390/ijms25073618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 03/14/2024] [Accepted: 03/22/2024] [Indexed: 04/14/2024] Open
Abstract
Idiopathic Interstitial Pneumonias (IIPs) are a heterogeneous group of the broader category of Interstitial Lung Diseases (ILDs), pathologically characterized by the distortion of lung parenchyma by interstitial inflammation and/or fibrosis. The American Thoracic Society (ATS)/European Respiratory Society (ERS) international multidisciplinary consensus classification of the IIPs was published in 2002 and then updated in 2013, with the authors emphasizing the need for a multidisciplinary approach to the diagnosis of IIPs. The histological evaluation of IIPs is challenging, and different types of IIPs are classically associated with specific histopathological patterns. However, morphological overlaps can be observed, and the same histopathological features can be seen in totally different clinical settings. Therefore, the pathologist's aim is to recognize the pathologic-morphologic pattern of disease in this clinical setting, and only after multi-disciplinary evaluation, if there is concordance between clinical and radiological findings, a definitive diagnosis of specific IIP can be established, allowing the optimal clinical-therapeutic management of the patient.
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Affiliation(s)
- Stefano Lucà
- Pathology Unit, Department of Mental and Physical Health and Preventive Medicine, Università degli Studi della Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (S.L.); (F.P.); (A.R.); (M.A.)
| | - Francesca Pagliuca
- Pathology Unit, Department of Mental and Physical Health and Preventive Medicine, Università degli Studi della Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (S.L.); (F.P.); (A.R.); (M.A.)
| | - Fabio Perrotta
- Department of Translational Medical Science, Università degli Studi della Campania “Luigi Vanvitelli”, 80131 Naples, Italy; (F.P.); (D.F.M.); (A.B.)
| | - Andrea Ronchi
- Pathology Unit, Department of Mental and Physical Health and Preventive Medicine, Università degli Studi della Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (S.L.); (F.P.); (A.R.); (M.A.)
| | - Domenica Francesca Mariniello
- Department of Translational Medical Science, Università degli Studi della Campania “Luigi Vanvitelli”, 80131 Naples, Italy; (F.P.); (D.F.M.); (A.B.)
| | - Giovanni Natale
- Division of Thoracic Surgery, Università degli Studi della Campania “Luigi Vanvitelli”, Piazza Miraglia, 2, 80138 Naples, Italy; (G.N.); (A.F.)
| | - Andrea Bianco
- Department of Translational Medical Science, Università degli Studi della Campania “Luigi Vanvitelli”, 80131 Naples, Italy; (F.P.); (D.F.M.); (A.B.)
| | - Alfonso Fiorelli
- Division of Thoracic Surgery, Università degli Studi della Campania “Luigi Vanvitelli”, Piazza Miraglia, 2, 80138 Naples, Italy; (G.N.); (A.F.)
| | - Marina Accardo
- Pathology Unit, Department of Mental and Physical Health and Preventive Medicine, Università degli Studi della Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (S.L.); (F.P.); (A.R.); (M.A.)
| | - Renato Franco
- Pathology Unit, Department of Mental and Physical Health and Preventive Medicine, Università degli Studi della Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (S.L.); (F.P.); (A.R.); (M.A.)
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7
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Triphan SMF, Bauman G, Konietzke P, Konietzke M, Wielpütz MO. Magnetic Resonance Imaging of Lung Perfusion. J Magn Reson Imaging 2024; 59:784-796. [PMID: 37466278 DOI: 10.1002/jmri.28912] [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: 05/26/2023] [Revised: 07/01/2023] [Accepted: 07/03/2023] [Indexed: 07/20/2023] Open
Abstract
"Lung perfusion" in the context of imaging conventionally refers to the delivery of blood to the pulmonary capillary bed through the pulmonary arteries originating from the right ventricle required for oxygenation. The most important physiological mechanism in the context of imaging is the so-called hypoxic pulmonary vasoconstriction (HPV, also known as "Euler-Liljestrand-Reflex"), which couples lung perfusion to lung ventilation. In obstructive airway diseases such as asthma, chronic-obstructive pulmonary disease (COPD), cystic fibrosis (CF), and asthma, HPV downregulates pulmonary perfusion in order to redistribute blood flow to functional lung areas in order to conserve optimal oxygenation. Imaging of lung perfusion can be seen as a reflection of lung ventilation in obstructive airway diseases. Other conditions that primarily affect lung perfusion are pulmonary vascular diseases, pulmonary hypertension, or (chronic) pulmonary embolism, which also lead to inhomogeneity in pulmonary capillary blood distribution. Several magnetic resonance imaging (MRI) techniques either dependent on exogenous contrast materials, exploiting periodical lung signal variations with cardiac action, or relying on intrinsic lung voxel attributes have been demonstrated to visualize lung perfusion. Additional post-processing may add temporal information and provide quantitative information related to blood flow. The most widely used and robust technique, dynamic-contrast enhanced MRI, is available in clinical routine assessment of COPD, CF, and pulmonary vascular disease. Non-contrast techniques are important research tools currently requiring clinical validation and cross-correlation in the absence of a viable standard of reference. First data on many of these techniques in the context of observational studies assessing therapy effects have just become available. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 5.
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Affiliation(s)
- Simon M F Triphan
- 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
| | - Grzegorz Bauman
- Division of Radiological Physics, Department of Radiology, University Hospital of Basel, Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Philip Konietzke
- 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
| | - Marilisa Konietzke
- Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany
- Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, Germany
| | - Mark O Wielpütz
- 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
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8
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Bankier AA, MacMahon H, Colby T, Gevenois PA, Goo JM, Leung AN, Lynch DA, Schaefer-Prokop CM, Tomiyama N, Travis WD, Verschakelen JA, White CS, Naidich DP. Fleischner Society: Glossary of Terms for Thoracic Imaging. Radiology 2024; 310:e232558. [PMID: 38411514 PMCID: PMC10902601 DOI: 10.1148/radiol.232558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 01/17/2024] [Accepted: 01/31/2024] [Indexed: 02/28/2024]
Abstract
Members of the Fleischner Society have compiled a glossary of terms for thoracic imaging that replaces previous glossaries published in 1984, 1996, and 2008, respectively. The impetus to update the previous version arose from multiple considerations. These include an awareness that new terms and concepts have emerged, others have become obsolete, and the usage of some terms has either changed or become inconsistent to a degree that warranted a new definition. This latest glossary is focused on terms of clinical importance and on those whose meaning may be perceived as vague or ambiguous. As with previous versions, the aim of the present glossary is to establish standardization of terminology for thoracic radiology and, thereby, to facilitate communications between radiologists and clinicians. Moreover, the present glossary aims to contribute to a more stringent use of terminology, increasingly required for structured reporting and accurate searches in large databases. Compared with the previous version, the number of images (chest radiography and CT) in the current version has substantially increased. The authors hope that this will enhance its educational and practical value. All definitions and images are hyperlinked throughout the text. Click on each figure callout to view corresponding image. © RSNA, 2024 Supplemental material is available for this article. See also the editorials by Bhalla and Powell in this issue.
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Affiliation(s)
- Alexander A. Bankier
- From the Dept of Radiology, University of Massachusetts Memorial
Health and University of Massachusetts Chan Medical School, 55 Lake Ave N,
Worcester, MA 01655 (A.A.B.); Dept of Radiology, University of Chicago, Chicago,
Ill (H.M.); Dept of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.C.);
Dept of Pulmonology, Université Libre de Bruxelles, Brussels, Belgium
(P.A.G.); Dept of Radiology, Seoul National University Hospital, Seoul, Korea
(J.M.G.); Center for Academic Medicine, Dept of Radiology, Stanford University,
Palo Alto, Calif (A.N.C.L.); Dept of Radiology, National Jewish Medical and
Research Center, Denver, Colo (D.A.L.); Dept of Radiology, Meander Medical
Centre Amersfoort, Amersfoort, the Netherlands (C.M.S.P.); Dept of Radiology,
Osaka University Graduate School of Medicine, Suita, Japan (N.T.); Dept of
Pathology, Memorial Sloan Kettering Cancer Center, New York, NY (W.D.T.); Dept
of Radiology, Catholic University Leuven, University Hospital Gasthuisberg,
Leuven, Belgium (J.A.V.); Dept of Diagnostic Radiology, University of Maryland
Hospital, Baltimore, Md (C.S.W.); and Dept of Radiology, NYU Langone Medical
Center/Tisch Hospital, New York, NY (D.P.N.)
| | - Heber MacMahon
- From the Dept of Radiology, University of Massachusetts Memorial
Health and University of Massachusetts Chan Medical School, 55 Lake Ave N,
Worcester, MA 01655 (A.A.B.); Dept of Radiology, University of Chicago, Chicago,
Ill (H.M.); Dept of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.C.);
Dept of Pulmonology, Université Libre de Bruxelles, Brussels, Belgium
(P.A.G.); Dept of Radiology, Seoul National University Hospital, Seoul, Korea
(J.M.G.); Center for Academic Medicine, Dept of Radiology, Stanford University,
Palo Alto, Calif (A.N.C.L.); Dept of Radiology, National Jewish Medical and
Research Center, Denver, Colo (D.A.L.); Dept of Radiology, Meander Medical
Centre Amersfoort, Amersfoort, the Netherlands (C.M.S.P.); Dept of Radiology,
Osaka University Graduate School of Medicine, Suita, Japan (N.T.); Dept of
Pathology, Memorial Sloan Kettering Cancer Center, New York, NY (W.D.T.); Dept
of Radiology, Catholic University Leuven, University Hospital Gasthuisberg,
Leuven, Belgium (J.A.V.); Dept of Diagnostic Radiology, University of Maryland
Hospital, Baltimore, Md (C.S.W.); and Dept of Radiology, NYU Langone Medical
Center/Tisch Hospital, New York, NY (D.P.N.)
| | - Thomas Colby
- From the Dept of Radiology, University of Massachusetts Memorial
Health and University of Massachusetts Chan Medical School, 55 Lake Ave N,
Worcester, MA 01655 (A.A.B.); Dept of Radiology, University of Chicago, Chicago,
Ill (H.M.); Dept of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.C.);
Dept of Pulmonology, Université Libre de Bruxelles, Brussels, Belgium
(P.A.G.); Dept of Radiology, Seoul National University Hospital, Seoul, Korea
(J.M.G.); Center for Academic Medicine, Dept of Radiology, Stanford University,
Palo Alto, Calif (A.N.C.L.); Dept of Radiology, National Jewish Medical and
Research Center, Denver, Colo (D.A.L.); Dept of Radiology, Meander Medical
Centre Amersfoort, Amersfoort, the Netherlands (C.M.S.P.); Dept of Radiology,
Osaka University Graduate School of Medicine, Suita, Japan (N.T.); Dept of
Pathology, Memorial Sloan Kettering Cancer Center, New York, NY (W.D.T.); Dept
of Radiology, Catholic University Leuven, University Hospital Gasthuisberg,
Leuven, Belgium (J.A.V.); Dept of Diagnostic Radiology, University of Maryland
Hospital, Baltimore, Md (C.S.W.); and Dept of Radiology, NYU Langone Medical
Center/Tisch Hospital, New York, NY (D.P.N.)
| | - Pierre Alain Gevenois
- From the Dept of Radiology, University of Massachusetts Memorial
Health and University of Massachusetts Chan Medical School, 55 Lake Ave N,
Worcester, MA 01655 (A.A.B.); Dept of Radiology, University of Chicago, Chicago,
Ill (H.M.); Dept of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.C.);
Dept of Pulmonology, Université Libre de Bruxelles, Brussels, Belgium
(P.A.G.); Dept of Radiology, Seoul National University Hospital, Seoul, Korea
(J.M.G.); Center for Academic Medicine, Dept of Radiology, Stanford University,
Palo Alto, Calif (A.N.C.L.); Dept of Radiology, National Jewish Medical and
Research Center, Denver, Colo (D.A.L.); Dept of Radiology, Meander Medical
Centre Amersfoort, Amersfoort, the Netherlands (C.M.S.P.); Dept of Radiology,
Osaka University Graduate School of Medicine, Suita, Japan (N.T.); Dept of
Pathology, Memorial Sloan Kettering Cancer Center, New York, NY (W.D.T.); Dept
of Radiology, Catholic University Leuven, University Hospital Gasthuisberg,
Leuven, Belgium (J.A.V.); Dept of Diagnostic Radiology, University of Maryland
Hospital, Baltimore, Md (C.S.W.); and Dept of Radiology, NYU Langone Medical
Center/Tisch Hospital, New York, NY (D.P.N.)
| | - Jin Mo Goo
- From the Dept of Radiology, University of Massachusetts Memorial
Health and University of Massachusetts Chan Medical School, 55 Lake Ave N,
Worcester, MA 01655 (A.A.B.); Dept of Radiology, University of Chicago, Chicago,
Ill (H.M.); Dept of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.C.);
Dept of Pulmonology, Université Libre de Bruxelles, Brussels, Belgium
(P.A.G.); Dept of Radiology, Seoul National University Hospital, Seoul, Korea
(J.M.G.); Center for Academic Medicine, Dept of Radiology, Stanford University,
Palo Alto, Calif (A.N.C.L.); Dept of Radiology, National Jewish Medical and
Research Center, Denver, Colo (D.A.L.); Dept of Radiology, Meander Medical
Centre Amersfoort, Amersfoort, the Netherlands (C.M.S.P.); Dept of Radiology,
Osaka University Graduate School of Medicine, Suita, Japan (N.T.); Dept of
Pathology, Memorial Sloan Kettering Cancer Center, New York, NY (W.D.T.); Dept
of Radiology, Catholic University Leuven, University Hospital Gasthuisberg,
Leuven, Belgium (J.A.V.); Dept of Diagnostic Radiology, University of Maryland
Hospital, Baltimore, Md (C.S.W.); and Dept of Radiology, NYU Langone Medical
Center/Tisch Hospital, New York, NY (D.P.N.)
| | - Ann N.C. Leung
- From the Dept of Radiology, University of Massachusetts Memorial
Health and University of Massachusetts Chan Medical School, 55 Lake Ave N,
Worcester, MA 01655 (A.A.B.); Dept of Radiology, University of Chicago, Chicago,
Ill (H.M.); Dept of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.C.);
Dept of Pulmonology, Université Libre de Bruxelles, Brussels, Belgium
(P.A.G.); Dept of Radiology, Seoul National University Hospital, Seoul, Korea
(J.M.G.); Center for Academic Medicine, Dept of Radiology, Stanford University,
Palo Alto, Calif (A.N.C.L.); Dept of Radiology, National Jewish Medical and
Research Center, Denver, Colo (D.A.L.); Dept of Radiology, Meander Medical
Centre Amersfoort, Amersfoort, the Netherlands (C.M.S.P.); Dept of Radiology,
Osaka University Graduate School of Medicine, Suita, Japan (N.T.); Dept of
Pathology, Memorial Sloan Kettering Cancer Center, New York, NY (W.D.T.); Dept
of Radiology, Catholic University Leuven, University Hospital Gasthuisberg,
Leuven, Belgium (J.A.V.); Dept of Diagnostic Radiology, University of Maryland
Hospital, Baltimore, Md (C.S.W.); and Dept of Radiology, NYU Langone Medical
Center/Tisch Hospital, New York, NY (D.P.N.)
| | - David A. Lynch
- From the Dept of Radiology, University of Massachusetts Memorial
Health and University of Massachusetts Chan Medical School, 55 Lake Ave N,
Worcester, MA 01655 (A.A.B.); Dept of Radiology, University of Chicago, Chicago,
Ill (H.M.); Dept of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.C.);
Dept of Pulmonology, Université Libre de Bruxelles, Brussels, Belgium
(P.A.G.); Dept of Radiology, Seoul National University Hospital, Seoul, Korea
(J.M.G.); Center for Academic Medicine, Dept of Radiology, Stanford University,
Palo Alto, Calif (A.N.C.L.); Dept of Radiology, National Jewish Medical and
Research Center, Denver, Colo (D.A.L.); Dept of Radiology, Meander Medical
Centre Amersfoort, Amersfoort, the Netherlands (C.M.S.P.); Dept of Radiology,
Osaka University Graduate School of Medicine, Suita, Japan (N.T.); Dept of
Pathology, Memorial Sloan Kettering Cancer Center, New York, NY (W.D.T.); Dept
of Radiology, Catholic University Leuven, University Hospital Gasthuisberg,
Leuven, Belgium (J.A.V.); Dept of Diagnostic Radiology, University of Maryland
Hospital, Baltimore, Md (C.S.W.); and Dept of Radiology, NYU Langone Medical
Center/Tisch Hospital, New York, NY (D.P.N.)
| | - Cornelia M. Schaefer-Prokop
- From the Dept of Radiology, University of Massachusetts Memorial
Health and University of Massachusetts Chan Medical School, 55 Lake Ave N,
Worcester, MA 01655 (A.A.B.); Dept of Radiology, University of Chicago, Chicago,
Ill (H.M.); Dept of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.C.);
Dept of Pulmonology, Université Libre de Bruxelles, Brussels, Belgium
(P.A.G.); Dept of Radiology, Seoul National University Hospital, Seoul, Korea
(J.M.G.); Center for Academic Medicine, Dept of Radiology, Stanford University,
Palo Alto, Calif (A.N.C.L.); Dept of Radiology, National Jewish Medical and
Research Center, Denver, Colo (D.A.L.); Dept of Radiology, Meander Medical
Centre Amersfoort, Amersfoort, the Netherlands (C.M.S.P.); Dept of Radiology,
Osaka University Graduate School of Medicine, Suita, Japan (N.T.); Dept of
Pathology, Memorial Sloan Kettering Cancer Center, New York, NY (W.D.T.); Dept
of Radiology, Catholic University Leuven, University Hospital Gasthuisberg,
Leuven, Belgium (J.A.V.); Dept of Diagnostic Radiology, University of Maryland
Hospital, Baltimore, Md (C.S.W.); and Dept of Radiology, NYU Langone Medical
Center/Tisch Hospital, New York, NY (D.P.N.)
| | - Noriyuki Tomiyama
- From the Dept of Radiology, University of Massachusetts Memorial
Health and University of Massachusetts Chan Medical School, 55 Lake Ave N,
Worcester, MA 01655 (A.A.B.); Dept of Radiology, University of Chicago, Chicago,
Ill (H.M.); Dept of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.C.);
Dept of Pulmonology, Université Libre de Bruxelles, Brussels, Belgium
(P.A.G.); Dept of Radiology, Seoul National University Hospital, Seoul, Korea
(J.M.G.); Center for Academic Medicine, Dept of Radiology, Stanford University,
Palo Alto, Calif (A.N.C.L.); Dept of Radiology, National Jewish Medical and
Research Center, Denver, Colo (D.A.L.); Dept of Radiology, Meander Medical
Centre Amersfoort, Amersfoort, the Netherlands (C.M.S.P.); Dept of Radiology,
Osaka University Graduate School of Medicine, Suita, Japan (N.T.); Dept of
Pathology, Memorial Sloan Kettering Cancer Center, New York, NY (W.D.T.); Dept
of Radiology, Catholic University Leuven, University Hospital Gasthuisberg,
Leuven, Belgium (J.A.V.); Dept of Diagnostic Radiology, University of Maryland
Hospital, Baltimore, Md (C.S.W.); and Dept of Radiology, NYU Langone Medical
Center/Tisch Hospital, New York, NY (D.P.N.)
| | - William D. Travis
- From the Dept of Radiology, University of Massachusetts Memorial
Health and University of Massachusetts Chan Medical School, 55 Lake Ave N,
Worcester, MA 01655 (A.A.B.); Dept of Radiology, University of Chicago, Chicago,
Ill (H.M.); Dept of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.C.);
Dept of Pulmonology, Université Libre de Bruxelles, Brussels, Belgium
(P.A.G.); Dept of Radiology, Seoul National University Hospital, Seoul, Korea
(J.M.G.); Center for Academic Medicine, Dept of Radiology, Stanford University,
Palo Alto, Calif (A.N.C.L.); Dept of Radiology, National Jewish Medical and
Research Center, Denver, Colo (D.A.L.); Dept of Radiology, Meander Medical
Centre Amersfoort, Amersfoort, the Netherlands (C.M.S.P.); Dept of Radiology,
Osaka University Graduate School of Medicine, Suita, Japan (N.T.); Dept of
Pathology, Memorial Sloan Kettering Cancer Center, New York, NY (W.D.T.); Dept
of Radiology, Catholic University Leuven, University Hospital Gasthuisberg,
Leuven, Belgium (J.A.V.); Dept of Diagnostic Radiology, University of Maryland
Hospital, Baltimore, Md (C.S.W.); and Dept of Radiology, NYU Langone Medical
Center/Tisch Hospital, New York, NY (D.P.N.)
| | - Johny A. Verschakelen
- From the Dept of Radiology, University of Massachusetts Memorial
Health and University of Massachusetts Chan Medical School, 55 Lake Ave N,
Worcester, MA 01655 (A.A.B.); Dept of Radiology, University of Chicago, Chicago,
Ill (H.M.); Dept of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.C.);
Dept of Pulmonology, Université Libre de Bruxelles, Brussels, Belgium
(P.A.G.); Dept of Radiology, Seoul National University Hospital, Seoul, Korea
(J.M.G.); Center for Academic Medicine, Dept of Radiology, Stanford University,
Palo Alto, Calif (A.N.C.L.); Dept of Radiology, National Jewish Medical and
Research Center, Denver, Colo (D.A.L.); Dept of Radiology, Meander Medical
Centre Amersfoort, Amersfoort, the Netherlands (C.M.S.P.); Dept of Radiology,
Osaka University Graduate School of Medicine, Suita, Japan (N.T.); Dept of
Pathology, Memorial Sloan Kettering Cancer Center, New York, NY (W.D.T.); Dept
of Radiology, Catholic University Leuven, University Hospital Gasthuisberg,
Leuven, Belgium (J.A.V.); Dept of Diagnostic Radiology, University of Maryland
Hospital, Baltimore, Md (C.S.W.); and Dept of Radiology, NYU Langone Medical
Center/Tisch Hospital, New York, NY (D.P.N.)
| | - Charles S. White
- From the Dept of Radiology, University of Massachusetts Memorial
Health and University of Massachusetts Chan Medical School, 55 Lake Ave N,
Worcester, MA 01655 (A.A.B.); Dept of Radiology, University of Chicago, Chicago,
Ill (H.M.); Dept of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.C.);
Dept of Pulmonology, Université Libre de Bruxelles, Brussels, Belgium
(P.A.G.); Dept of Radiology, Seoul National University Hospital, Seoul, Korea
(J.M.G.); Center for Academic Medicine, Dept of Radiology, Stanford University,
Palo Alto, Calif (A.N.C.L.); Dept of Radiology, National Jewish Medical and
Research Center, Denver, Colo (D.A.L.); Dept of Radiology, Meander Medical
Centre Amersfoort, Amersfoort, the Netherlands (C.M.S.P.); Dept of Radiology,
Osaka University Graduate School of Medicine, Suita, Japan (N.T.); Dept of
Pathology, Memorial Sloan Kettering Cancer Center, New York, NY (W.D.T.); Dept
of Radiology, Catholic University Leuven, University Hospital Gasthuisberg,
Leuven, Belgium (J.A.V.); Dept of Diagnostic Radiology, University of Maryland
Hospital, Baltimore, Md (C.S.W.); and Dept of Radiology, NYU Langone Medical
Center/Tisch Hospital, New York, NY (D.P.N.)
| | - David P. Naidich
- From the Dept of Radiology, University of Massachusetts Memorial
Health and University of Massachusetts Chan Medical School, 55 Lake Ave N,
Worcester, MA 01655 (A.A.B.); Dept of Radiology, University of Chicago, Chicago,
Ill (H.M.); Dept of Pathology, Mayo Clinic Scottsdale, Scottsdale, Ariz (T.C.);
Dept of Pulmonology, Université Libre de Bruxelles, Brussels, Belgium
(P.A.G.); Dept of Radiology, Seoul National University Hospital, Seoul, Korea
(J.M.G.); Center for Academic Medicine, Dept of Radiology, Stanford University,
Palo Alto, Calif (A.N.C.L.); Dept of Radiology, National Jewish Medical and
Research Center, Denver, Colo (D.A.L.); Dept of Radiology, Meander Medical
Centre Amersfoort, Amersfoort, the Netherlands (C.M.S.P.); Dept of Radiology,
Osaka University Graduate School of Medicine, Suita, Japan (N.T.); Dept of
Pathology, Memorial Sloan Kettering Cancer Center, New York, NY (W.D.T.); Dept
of Radiology, Catholic University Leuven, University Hospital Gasthuisberg,
Leuven, Belgium (J.A.V.); Dept of Diagnostic Radiology, University of Maryland
Hospital, Baltimore, Md (C.S.W.); and Dept of Radiology, NYU Langone Medical
Center/Tisch Hospital, New York, NY (D.P.N.)
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9
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Gil-García CA, Cueto-Robledo G, Gonzalez-Hermosillo LM, Alfaro-Cruz A, Roldan-Valadez E. Nonthrombotic Pulmonary Embolism Associated With Non-Hodgkin Lymphoma. Curr Probl Cardiol 2023; 48:102001. [PMID: 37506958 DOI: 10.1016/j.cpcardiol.2023.102001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 07/24/2023] [Indexed: 07/30/2023]
Abstract
Nonthrombotic pulmonary embolism (NTPE) challenges the medical community with its diverse etiologies and potential life-threatening implications. The classification section delves into the multifaceted nature of NTPE, which includes various embolic agents that traverse the vascular system. From air and fat emboli to tumor and amniotic fluid emboli, this exploration of diverse etiologies sheds light on the complexity of NTPE. Diagnostic methods play a crucial role in the effective management of NTPE. This article describes a range of traditional and cutting-edge diagnostic techniques, from computed tomography angiography to novel biomarkers, enabling the accurate and timely identification of NTPE. NTPE treatment options are diverse and patient-specific, requiring customized approaches to address varying embolic sources. Anticoagulation, embolus removal, and emerging interventions under study are discussed, providing clinicians with a comprehensive understanding of management strategies. This article uncovers the rare but captivating association between NTPE and non-Hodgkin lymphoma. Although rare, documented cases have sparked curiosity among researchers and medical practitioners. We explore potential pathophysiological connections, discussing challenges and considerations when encountering this unique scenario. In conclusion, this captivating review encapsulates the multifaceted realm of NTPE, covering its classification, diagnostics, and treatment modalities. Moreover, it presents a fascinating connection with non-Hodgkin lymphoma. This article offers a comprehensive and concise review of NTPE, guiding readers through its intricate classification, diagnostic approaches, and therapeutic interventions.
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Affiliation(s)
- Cesar-Alejandro Gil-García
- Faculty of Medicine, Autonomous University of Sinaloa, Los Mochis, Sinaloa, México; Directorate of Research, General Hospital of Mexico "Dr. Eduardo Liceaga," Mexico City, Mexico
| | - Guillermo Cueto-Robledo
- Cardiorespiratory Emergencies, General Hospital of Mexico "Dr. Eduardo Liceaga", Mexico City, Mexico; Pulmonary Circulation Clinic, General Hospital of Mexico "Dr. Eduardo Liceaga", Mexico City, Mexico; Faculty of Medicine, National Autonomous University of Mexico, Mexico City, Mexico.
| | | | - Ana Alfaro-Cruz
- Department of Surgical Pathology, General Hospital of Mexico, "Dr. Eduardo Liceaga," Mexico City, Mexico
| | - Ernesto Roldan-Valadez
- Directorate of Research, General Hospital of Mexico "Dr. Eduardo Liceaga," Mexico City, Mexico; Department of Radiology, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia.
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10
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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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11
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Wielpütz MO. The Proton Is Not Enough: Opportunities of Combined Multinuclear MRI for Lung Functional Imaging. Chest 2023; 164:572-573. [PMID: 37689468 DOI: 10.1016/j.chest.2023.03.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Accepted: 03/28/2023] [Indexed: 09/11/2023] Open
Affiliation(s)
- Mark O Wielpütz
- Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, and Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany.
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12
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Gong J, Yin R, Sun L, Gao N, Wang X, Zhang L, Zhang Z. CT-based radiomics model to predict spread through air space in resectable lung cancer. Cancer Med 2023; 12:18755-18766. [PMID: 37676092 PMCID: PMC10557899 DOI: 10.1002/cam4.6496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 08/21/2023] [Accepted: 08/23/2023] [Indexed: 09/08/2023] Open
Abstract
BACKGROUND Spread through air space (STAS) has been identified as a pathological pattern associated with lung cancer progression. Patients with STAS were related to a worse prognosis compared with patients without STAS. The objective of this study was to establish a radiomics model capable of forecasting STAS before surgery, which can assist surgeons in selecting the most appropriate operation type for patients with STAS. METHOD There were 537 eligible patients retrospectively included in this study. ROI segmentation was performed manually on all CT images to identify the region of interest. From each segmented lesion, a total of 1688 features were extracted. The tumor size, maximum tumor diameters, and tumor type were also recorded. Using Spearman's correlation coefficient to calculate the correlation and redundancy of elements, and redundant features less than 0.80 were removed. In order to reduce the level of overfitting and avoid statistical biases, a dimension reduction process of the dataset was conducted to decrease the number of features. Finally, a radiomics model included 44 features was established to predict STAS. To evaluate the performance of the model, the receiver operating characteristic (ROC) curve was used, and the area under the curve (AUC) was calculated, and the accuracy of the model was verified by 10-fold cross-validation. RESULTS The incidence of STAS was 38.2% (205/537). The tumor type, maximum tumor diameters, and consolidation tumor ratio were significantly different between STAS group and non-STAS group. The training group included 430 patients, while the test group was consisted with 107. The training group achieved an AUC of 0.825 (sensitivity, 0.875; specificity, 0.621; and accuracy, 0.749) and the test group had an AUC of 0.802 (sensitivity, 0.797; specificity,0.688; and accuracy, 0.748). The 10-fold cross-validation had an AUC of 0.834. CONCLUSION CT-based radiomic model can predict STAS effectively, which is of great importance to guide the selection of operation types before surgery.
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Affiliation(s)
- Jialin Gong
- Department of Lung Cancer, Tianjin Lung Cancer Center, Tianjin Medical University Cancer Institute and HospitalNational Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for CancerTianjinChina
| | - Rui Yin
- School of Biomedical Engineering & TechnologyTianjin Medical UniversityTianjinChina
| | - Leina Sun
- Department of Pathology, Tianjin Medical University Cancer Institute and HospitalNational Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for CancerTianjinChina
| | - Na Gao
- Department of Pathology, Tianjin Medical University Cancer Institute and HospitalNational Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for CancerTianjinChina
| | - Xiaofei Wang
- Department of Lung Cancer, Tianjin Lung Cancer Center, Tianjin Medical University Cancer Institute and HospitalNational Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for CancerTianjinChina
| | - Lianmin Zhang
- Department of Lung Cancer, Tianjin Lung Cancer Center, Tianjin Medical University Cancer Institute and HospitalNational Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for CancerTianjinChina
| | - Zhenfa Zhang
- Department of Lung Cancer, Tianjin Lung Cancer Center, Tianjin Medical University Cancer Institute and HospitalNational Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for CancerTianjinChina
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13
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Raoof S, Shah M, Braman S, Agrawal A, Allaqaband H, Bowler R, Castaldi P, DeMeo D, Fernando S, Hall CS, Han MK, Hogg J, Humphries S, Lee HY, Lee KS, Lynch D, Machnicki S, Mehta A, Mehta S, Mina B, Naidich D, Naidich J, Ohno Y, Regan E, van Beek EJR, Washko G, Make B. Lung Imaging in COPD Part 2: Emerging Concepts. Chest 2023; 164:339-354. [PMID: 36907375 PMCID: PMC10475822 DOI: 10.1016/j.chest.2023.02.049] [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: 10/06/2022] [Revised: 02/23/2023] [Accepted: 02/25/2023] [Indexed: 03/13/2023] Open
Abstract
The diagnosis, prognostication, and differentiation of phenotypes of COPD can be facilitated by CT scan imaging of the chest. CT scan imaging of the chest is a prerequisite for lung volume reduction surgery and lung transplantation. Quantitative analysis can be used to evaluate extent of disease progression. Evolving imaging techniques include micro-CT scan, ultra-high-resolution and photon-counting CT scan imaging, and MRI. Potential advantages of these newer techniques include improved resolution, prediction of reversibility, and obviation of radiation exposure. This article discusses important emerging techniques in imaging patients with COPD. The clinical usefulness of these emerging techniques as they stand today are tabulated for the benefit of the practicing pulmonologist.
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Affiliation(s)
- Suhail Raoof
- Northwell Health, Lenox Hill Hospital, New York, NY.
| | - Manav Shah
- Northwell Health, Lenox Hill Hospital, New York, NY
| | - Sidney Braman
- Icahn School of Medicine at Mount Sinai, New York, NY
| | | | | | | | | | - Dawn DeMeo
- Brigham and Women's Hospital, Boston, MA
| | | | | | | | - James Hogg
- University of British Columbia, Vancouver, BC, Canada
| | | | - Ho Yun Lee
- Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea; Department of Health Sciences and Technology, Sungkyunkwan University, ChangWon, South Korea
| | - Kyung Soo Lee
- Sungkyunkwan University School of Medicine, Samsung ChangWon Hospital, ChangWon, South Korea
| | | | | | | | | | - Bushra Mina
- Northwell Health, Lenox Hill Hospital, New York, NY
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14
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Marquis KM, Hammer MM, Steinbrecher K, Henry TS, Lin CY, Shifren A, Raptis CA. CT Approach to Lung Injury. Radiographics 2023; 43:e220176. [PMID: 37289644 DOI: 10.1148/rg.220176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Diffuse alveolar damage (DAD), which represents the pathologic changes seen after acute lung injury, is caused by damage to all three layers of the alveolar wall and can ultimately result in alveolar collapse with loss of the normal pulmonary architecture. DAD has an acute phase that predominantly manifests as airspace disease at CT owing to filling of the alveoli with cells, plasma fluids, and hyaline membranes. DAD then evolves into a heterogeneous organizing phase, with mixed airspace and interstitial disease characterized by volume loss, architectural distortion, fibrosis, and parenchymal loss. Patients with DAD have a severe clinical course and typically require prolonged mechanical ventilation, which may result in ventilator-induced lung injury. In those patients who survive DAD, the lungs will remodel over time, but most will have residual findings at chest CT. Organizing pneumonia (OP) is a descriptive term for a histologic pattern characterized by intra-alveolar fibroblast plugs. The significance and pathogenesis of OP are controversial. Some authors regard it as part of a spectrum of acute lung injury, while others consider it a marker of acute or subacute lung injury. At CT, OP manifests with various forms of airspace disease that are most commonly bilateral and relatively homogeneous in appearance at individual time points. Patients with OP most often have a mild clinical course, although some may have residual findings at CT. In patients with DAD and OP, imaging findings can be combined with clinical information to suggest the diagnosis in many cases, with biopsy reserved for difficult cases with atypical findings or clinical manifestations. To best participate in the multidisciplinary approach to patients with lung injury, radiologists must not only recognize these entities but also describe them with consistent and meaningful terminology, examples of which are emphasized in the article. © RSNA, 2023 See the invited commentary by Kligerman et al in this issue. Quiz questions for this article are available in the supplemental material.
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Affiliation(s)
- Kaitlin M Marquis
- From the Mallinckrodt Institute of Radiology, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.M.M., K.S., C.A.R.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (M.M.H.); Department of Radiology, Duke University, Durham, NC (T.S.H.); and Department of Pathology & Immunology (C.Y.L.) and Department of Pulmonology (A.S.), Washington University, St Louis, Mo
| | - Mark M Hammer
- From the Mallinckrodt Institute of Radiology, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.M.M., K.S., C.A.R.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (M.M.H.); Department of Radiology, Duke University, Durham, NC (T.S.H.); and Department of Pathology & Immunology (C.Y.L.) and Department of Pulmonology (A.S.), Washington University, St Louis, Mo
| | - Kacie Steinbrecher
- From the Mallinckrodt Institute of Radiology, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.M.M., K.S., C.A.R.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (M.M.H.); Department of Radiology, Duke University, Durham, NC (T.S.H.); and Department of Pathology & Immunology (C.Y.L.) and Department of Pulmonology (A.S.), Washington University, St Louis, Mo
| | - Travis S Henry
- From the Mallinckrodt Institute of Radiology, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.M.M., K.S., C.A.R.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (M.M.H.); Department of Radiology, Duke University, Durham, NC (T.S.H.); and Department of Pathology & Immunology (C.Y.L.) and Department of Pulmonology (A.S.), Washington University, St Louis, Mo
| | - Chieh-Yu Lin
- From the Mallinckrodt Institute of Radiology, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.M.M., K.S., C.A.R.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (M.M.H.); Department of Radiology, Duke University, Durham, NC (T.S.H.); and Department of Pathology & Immunology (C.Y.L.) and Department of Pulmonology (A.S.), Washington University, St Louis, Mo
| | - Adrian Shifren
- From the Mallinckrodt Institute of Radiology, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.M.M., K.S., C.A.R.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (M.M.H.); Department of Radiology, Duke University, Durham, NC (T.S.H.); and Department of Pathology & Immunology (C.Y.L.) and Department of Pulmonology (A.S.), Washington University, St Louis, Mo
| | - Constantine A Raptis
- From the Mallinckrodt Institute of Radiology, 510 S Kingshighway Blvd, St Louis, MO 63110 (K.M.M., K.S., C.A.R.); Department of Radiology, Brigham and Women's Hospital, Boston, Mass (M.M.H.); Department of Radiology, Duke University, Durham, NC (T.S.H.); and Department of Pathology & Immunology (C.Y.L.) and Department of Pulmonology (A.S.), Washington University, St Louis, Mo
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15
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Kreniske JS, Kaner RJ, Glesby MJ. Pathogenesis and management of emphysema in people with HIV. Expert Rev Respir Med 2023; 17:873-887. [PMID: 37848398 PMCID: PMC10872640 DOI: 10.1080/17476348.2023.2272702] [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: 03/04/2023] [Accepted: 10/16/2023] [Indexed: 10/19/2023]
Abstract
INTRODUCTION Since early in the HIV epidemic, emphysema has been identified among people with HIV (PWH) and has been associated with increased mortality. Smoking cessation is key to risk reduction. Health maintenance for PWH and emphysema should ensure appropriate vaccination and lung cancer screening. Treatment should adhere to inhaler guidelines for the general population, but inhaled corticosteroid (ICS) should be used with caution. Frontiers in treatment include targeted therapeutics. Major knowledge gaps exist in the epidemiology of and optimal care for PWH and emphysema, particularly in low and middle-income countries (LMIC). AREAS COVERED Topics addressed include risk factors, pathogenesis, current treatment and prevention strategies, and frontiers in research. EXPERT OPINION There are limited data on the epidemiology of emphysema in LMIC, where more than 90% of deaths from COPD occur and where the morbidity of HIV is most heavily concentrated. The population of PWH is aging, and age-related co-morbidities such as emphysema will only increase in salience. Over the next 5 years, the authors anticipate novel trials of targeted therapy for emphysema specific to PWH, and we anticipate a growing body of evidence to inform optimal clinical care for lung health among PWH in LMIC.
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Affiliation(s)
- Jonah S. Kreniske
- Division of Pulmonary and Critical Care Medicine, Weill Cornell Medical College, USA
| | - Robert J. Kaner
- Division of Pulmonary and Critical Care Medicine, Weill Cornell Medical College, USA
- Department of Genetic Medicine, Weill Cornell Medical College, USA
| | - Marshall J. Glesby
- Division of Infectious Diseases, Weill Cornell Medical College, USA
- Department of Population Health Sciences, Weill Cornell Medical College, USA
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16
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Masquelin AH, Alshaabi T, Cheney N, Estépar RSJ, Bates JHT, Kinsey CM. Perinodular Parenchymal Features Improve Indeterminate Lung Nodule Classification. Acad Radiol 2023; 30:1073-1080. [PMID: 35933282 PMCID: PMC9895123 DOI: 10.1016/j.acra.2022.07.001] [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: 04/23/2022] [Revised: 06/24/2022] [Accepted: 07/06/2022] [Indexed: 02/05/2023]
Abstract
BACKGROUND Radiomics, defined as quantitative features extracted from images, provide a non-invasive means of assessing malignant versus benign pulmonary nodules. In this study, we evaluate the consistency with which perinodular radiomics extracted from low-dose computed tomography images serve to identify malignant pulmonary nodules. MATERIALS AND METHODS Using the National Lung Screening Trial (NLST), we selected individuals with pulmonary nodules between 4mm to 20mm in diameter. Nodules were segmented to generate four distinct datasets; 1) a Tumor dataset containing tumor-specific features, 2) a 10 mm Band dataset containing parenchymal features between the segmented nodule boundary and 10mm out from the boundary, 3) a 15mm Band dataset, and 4) a Tumor Size dataset containing the maximum nodule diameter. Models to predict malignancy were constructed using support-vector machine (SVM), random forest (RF), and least absolute shrinkage and selection operator (LASSO) approaches. Ten-fold cross validation with 10 repetitions per fold was used to evaluate the performance of each approach applied to each dataset. RESULTS With respect to the RF, the Tumor, 10mm Band, and 15mm Band datasets achieved areas under the receiver-operator curve (AUC) of 84.44%, 84.09%, and 81.57%, respectively. Significant differences in performance were observed between the Tumor and 15mm Band datasets (adj. p-value <0.001). However, when combining tumor-specific features with perinodular features, the 10mm Band + Tumor and 15mm Band + Tumor datasets (AUC 87.87% and 86.75%, respectively) performed significantly better than the Tumor Size dataset (66.76%) or the Tumor dataset. Similarly, the AUCs from the SVM and LASSO were 84.71% and 88.91%, respectively, for the 10mm Band + Tumor. CONCLUSIONS The combined 10mm Band + Tumor dataset improved the differentiation between benign and malignant lung nodules compared to the Tumor datasets across all methodologies. This demonstrates that parenchymal features capture novel diagnostic information beyond that present in the nodule itself. (data agreement: NLST-163).
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Affiliation(s)
- Axel H Masquelin
- University of Vermont, Electrical and Biomedical Engineering, Burlington, VT, USA.
| | - Thayer Alshaabi
- University of California Berkeley, Advanced Bioimaging Center Berkeley, CA, USA
| | - Nick Cheney
- University of Vermont, Computer Science, Burlington, VT, USA
| | - Raúl San José Estépar
- Brigham and Women's Hospital Department of Radiology, Radiology 1249 Boylston St, Boston, MA, USA 02215
| | - Jason H T Bates
- University of Vermont College of Medicine, Burlington, VT, USA
| | - C Matthew Kinsey
- University of Vermont College of Medicine, Medicine, Pulmonary and Critical Care Given D208, 89 Beaumont Avenue, Burlington, VT, USA, 05405
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17
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Rustam S, Hu Y, Mahjour SB, Rendeiro AF, Ravichandran H, Urso A, D’Ovidio F, Martinez FJ, Altorki NK, Richmond B, Polosukhin V, Kropski JA, Blackwell TS, Randell SH, Elemento O, Shaykhiev R. A Unique Cellular Organization of Human Distal Airways and Its Disarray in Chronic Obstructive Pulmonary Disease. Am J Respir Crit Care Med 2023; 207:1171-1182. [PMID: 36796082 PMCID: PMC10161760 DOI: 10.1164/rccm.202207-1384oc] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 02/15/2023] [Indexed: 02/18/2023] Open
Abstract
Rationale: Remodeling and loss of distal conducting airways, including preterminal and terminal bronchioles (pre-TBs/TBs), underlie progressive airflow limitation in chronic obstructive pulmonary disease (COPD). The cellular basis of these structural changes remains unknown. Objectives: To identify biological changes in pre-TBs/TBs in COPD at single-cell resolution and determine their cellular origin. Methods: We established a novel method of distal airway dissection and performed single-cell transcriptomic profiling of 111,412 cells isolated from different airway regions of 12 healthy lung donors and pre-TBs of 5 patients with COPD. Imaging CyTOF and immunofluorescence analysis of pre-TBs/TBs from 24 healthy lung donors and 11 subjects with COPD were performed to characterize cellular phenotypes at a tissue level. Region-specific differentiation of basal cells isolated from proximal and distal airways was studied using an air-liquid interface model. Measurements and Main Results: The atlas of cellular heterogeneity along the proximal-distal axis of the human lung was assembled and identified region-specific cellular states, including SCGB3A2+ SFTPB+ terminal airway-enriched secretory cells (TASCs) unique to distal airways. TASCs were lost in COPD pre-TBs/TBs, paralleled by loss of region-specific endothelial capillary cells, increased frequency of CD8+ T cells normally enriched in proximal airways, and augmented IFN-γ signaling. Basal cells residing in pre-TBs/TBs were identified as a cellular origin of TASCs. Regeneration of TASCs by these progenitors was suppressed by IFN-γ. Conclusions: Altered maintenance of the unique cellular organization of pre-TBs/TBs, including loss of the region-specific epithelial differentiation in these bronchioles, represents the cellular manifestation and likely the cellular basis of distal airway remodeling in COPD.
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Affiliation(s)
| | - Yang Hu
- Caryl and Israel Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York
| | | | - Andre F. Rendeiro
- Caryl and Israel Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York
| | - Hiranmayi Ravichandran
- Caryl and Israel Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York
| | - Andreacarola Urso
- Department of Surgery, Columbia University Irving Medical Center, New York, New York
| | - Frank D’Ovidio
- Department of Surgery, Columbia University Irving Medical Center, New York, New York
| | | | - Nasser K. Altorki
- Department of Cardiothoracic Surgery, Weill Cornell Medicine, New York, New York
| | - Bradley Richmond
- Department of Veterans Affairs Medical Center, Nashville, Tennessee
- Department of Medicine, Vanderbilt University, Nashville, Tennessee; and
| | | | - Jonathan A. Kropski
- Department of Veterans Affairs Medical Center, Nashville, Tennessee
- Department of Medicine, Vanderbilt University, Nashville, Tennessee; and
| | - Timothy S. Blackwell
- Department of Veterans Affairs Medical Center, Nashville, Tennessee
- Department of Medicine, Vanderbilt University, Nashville, Tennessee; and
| | - Scott H. Randell
- Marsico Lung Institute, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Olivier Elemento
- Caryl and Israel Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York
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18
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Knudsen L, Hummel B, Wrede C, Zimmermann R, Perlman CE, Smith BJ. Acinar micromechanics in health and lung injury: what we have learned from quantitative morphology. Front Physiol 2023; 14:1142221. [PMID: 37025383 PMCID: PMC10070844 DOI: 10.3389/fphys.2023.1142221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 03/09/2023] [Indexed: 04/08/2023] Open
Abstract
Within the pulmonary acini ventilation and blood perfusion are brought together on a huge surface area separated by a very thin blood-gas barrier of tissue components to allow efficient gas exchange. During ventilation pulmonary acini are cyclically subjected to deformations which become manifest in changes of the dimensions of both alveolar and ductal airspaces as well as the interalveolar septa, composed of a dense capillary network and the delicate tissue layer forming the blood-gas barrier. These ventilation-related changes are referred to as micromechanics. In lung diseases, abnormalities in acinar micromechanics can be linked with injurious stresses and strains acting on the blood-gas barrier. The mechanisms by which interalveolar septa and the blood-gas barrier adapt to an increase in alveolar volume have been suggested to include unfolding, stretching, or changes in shape other than stretching and unfolding. Folding results in the formation of pleats in which alveolar epithelium is not exposed to air and parts of the blood-gas barrier are folded on each other. The opening of a collapsed alveolus (recruitment) can be considered as an extreme variant of septal wall unfolding. Alveolar recruitment can be detected with imaging techniques which achieve light microscopic resolution. Unfolding of pleats and stretching of the blood-gas barrier, however, require electron microscopic resolution to identify the basement membrane. While stretching results in an increase of the area of the basement membrane, unfolding of pleats and shape changes do not. Real time visualization of these processes, however, is currently not possible. In this review we provide an overview of septal wall micromechanics with focus on unfolding/folding as well as stretching. At the same time we provide a state-of-the-art design-based stereology methodology to quantify microarchitecture of alveoli and interalveolar septa based on different imaging techniques and design-based stereology.
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Affiliation(s)
- Lars Knudsen
- Institute of Functional and Applied Anatomy, Hannover Medical School, Hannover, Germany
- Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Member of the German Centre for Lung Research (DZL), Hannover, Germany
| | - Benjamin Hummel
- Institute of Functional and Applied Anatomy, Hannover Medical School, Hannover, Germany
| | - Christoph Wrede
- Institute of Functional and Applied Anatomy, Hannover Medical School, Hannover, Germany
- Research Core Unit Electron Microscopy, Hannover Medical School, Hannover, Germany
| | - Richard Zimmermann
- Institute of Functional and Applied Anatomy, Hannover Medical School, Hannover, Germany
| | - Carrie E Perlman
- Department of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ, United States
| | - Bradford J Smith
- Department of Bioengineering, College of Engineering Design and Computing, University of Colorado Denver | Anschutz Medical Campus, Aurora, CO, United States
- Department of Pediatric Pulmonary and Sleep Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
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19
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Ikeda O, Shimizu K, Yamada Y, Sugiura H, Suzuki H, Umetsu S, Sato K, Jinzaki M. Cystic fibrosis with multiple pulmonary arteriovenous malformations: A case report. Radiol Case Rep 2023; 18:1033-1036. [PMID: 36684625 PMCID: PMC9849989 DOI: 10.1016/j.radcr.2022.12.024] [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: 11/23/2022] [Revised: 12/07/2022] [Accepted: 12/10/2022] [Indexed: 01/07/2023] Open
Abstract
Cystic fibrosis is an autosomal recessive genetic disorder that damages the exocrine function of the body, resulting in alterations of multiple organs. In the respiratory system, it is known to cause bronchiectasis, recurrent bronchitis, and pneumonia; however, to the best of our knowledge, there are no reported cases of pulmonary arteriovenous malformations associated with this disease. Herein, we report a case of cystic fibrosis with multiple pulmonary arteriovenous malformations. A 16-year-old girl, who has been monitored since childhood for pancreatitis of unknown cause, experienced respiratory symptoms and hypoxemia (PaO2 = 57 mmHg). At 13 years of age, chest computed tomography revealed bronchiectasis, bronchial wall thickening, and tree-in-bud sign. Genetic testing was performed, and the patient was diagnosed with cystic fibrosis. However, the computed tomography scan also showed incidental nodular lesions in the left superior and both the inferior pulmonary lobes, suggesting multiple arteriovenous malformations. Dynamic computed tomography was performed which, confirmed the presence of 3 pulmonary arteriovenous malformations. Coil embolization was performed on all lesions, and the hypoxemia was corrected. Marked hypoxemia in a patient with cystic fibrosis may not be explained only by the presence of bronchiectasis and/or bronchial wall thickening; in such cases, it may be necessary to examine possible additional findings on computed tomography images, such as arteriovenous malformations.
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Affiliation(s)
- Orito Ikeda
- Department of Radiology, Saiseikai Yokohama-shi Tobu Hospital, Shimosueyoshi 3-6-1, Tsurumi-ku, Yokohama-shi, Kanagawa 230-8765, Japan
| | - Kunihiko Shimizu
- Department of Radiology, Saiseikai Yokohama-shi Tobu Hospital, Shimosueyoshi 3-6-1, Tsurumi-ku, Yokohama-shi, Kanagawa 230-8765, Japan,Corresponding author.
| | - Yoshitake Yamada
- Department of Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Hiroaki Sugiura
- Department of Radiology, National Defense Medical College Hospital, Namiki 3-2, Tokorozawa-shi, Saitama 359-8513, Japan
| | - Hideaki Suzuki
- Department of Radiology, Saiseikai Yokohama-shi Tobu Hospital, Shimosueyoshi 3-6-1, Tsurumi-ku, Yokohama-shi, Kanagawa 230-8765, Japan
| | - Syuichiro Umetsu
- Department of Pediatric Hepatology and Gastroenterology, Saiseikai Yokohama-shi Tobu Hospital, Shimosueyoshi 3-6-1, Tsurumi-ku, Yokohama-shi, Kanagawa 230-8765, Japan
| | - Kozo Sato
- Department of Radiology, Saiseikai Yokohama-shi Tobu Hospital, Shimosueyoshi 3-6-1, Tsurumi-ku, Yokohama-shi, Kanagawa 230-8765, Japan
| | - Masahiro Jinzaki
- Department of Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
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20
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Rodriguez K, Ashby CL, Varela VR, Sharma A. High-Resolution Computed Tomography of Fibrotic Interstitial Lung Disease. Semin Respir Crit Care Med 2022; 43:764-779. [PMID: 36307108 DOI: 10.1055/s-0042-1755563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
While radiography is the first-line imaging technique for evaluation of pulmonary disease, high-resolution computed tomography (HRCT) provides detailed assessment of the lung parenchyma and interstitium, allowing normal anatomy to be differentiated from superimposed abnormal findings. The fibrotic interstitial lung diseases have HRCT features that include reticulation, traction bronchiectasis and bronchiolectasis, honeycombing, architectural distortion, and volume loss. The characterization and distribution of these features result in distinctive CT patterns. The CT pattern and its progression over time can be combined with clinical, serologic, and pathologic data during multidisciplinary discussion to establish a clinical diagnosis. Serial examinations identify progression, treatment response, complications, and can assist in determining prognosis. This article will describe the technique used to perform HRCT, the normal and abnormal appearance of the lung on HRCT, and the CT patterns identified in common fibrotic lung diseases.
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Affiliation(s)
- Karen Rodriguez
- Division of Thoracic Imaging and Intervention, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Christian L Ashby
- School of Medicine, Universidad Central del Caribe School of Medicine, Bayamón, Puerto Rico
| | - Valeria R Varela
- School of Medicine, Universidad Central del Caribe School of Medicine, Bayamón, Puerto Rico
| | - Amita Sharma
- Division of Thoracic Imaging and Intervention, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
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21
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Marrocchio C, Lynch DA. High-Resolution Computed Tomography of Nonfibrotic Interstitial Lung Disease. Semin Respir Crit Care Med 2022; 43:780-791. [PMID: 36442473 DOI: 10.1055/s-0042-1755564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Nonfibrotic interstitial lung diseases include a heterogeneous group of conditions that can result in various patterns of lung involvement. When approaching the computed tomographic (CT) scan of a patient with a suspected or known interstitial lung disease, the use of the appropriate radiological terms and a systematic, structured approach to the interpretation of the imaging findings are essential to reach a confident diagnosis or to limit the list of differentials to few possibilities. The large number of conditions that cause nonfibrotic interstitial lung diseases prevents a thorough discussion of all these entities. Therefore, this article will focus on the most common chronic lung diseases that can cause these CT findings. A pattern-based approach is used, with a discussion of nodular pattern, consolidation, crazy paving, ground-glass opacities, septal thickening, and calcifications. The different clinical conditions will be described based on their predominant pattern, with particular attention to findings that can help in the differential diagnosis.
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Affiliation(s)
| | - David A Lynch
- Department of Radiology, National Jewish Health, Denver, Colorado
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22
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Ackermann M, Kamp JC, Werlein C, Walsh CL, Stark H, Prade V, Surabattula R, Wagner WL, Disney C, Bodey AJ, Illig T, Leeming DJ, Karsdal MA, Tzankov A, Boor P, Kühnel MP, Länger FP, Verleden SE, Kvasnicka HM, Kreipe HH, Haverich A, Black SM, Walch A, Tafforeau P, Lee PD, Hoeper MM, Welte T, Seeliger B, David S, Schuppan D, Mentzer SJ, Jonigk DD. The fatal trajectory of pulmonary COVID-19 is driven by lobular ischemia and fibrotic remodelling. EBioMedicine 2022; 85:104296. [PMID: 36206625 PMCID: PMC9535314 DOI: 10.1016/j.ebiom.2022.104296] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 09/14/2022] [Accepted: 09/16/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND COVID-19 is characterized by a heterogeneous clinical presentation, ranging from mild symptoms to severe courses of disease. 9-20% of hospitalized patients with severe lung disease die from COVID-19 and a substantial number of survivors develop long-COVID. Our objective was to provide comprehensive insights into the pathophysiology of severe COVID-19 and to identify liquid biomarkers for disease severity and therapy response. METHODS We studied a total of 85 lungs (n = 31 COVID autopsy samples; n = 7 influenza A autopsy samples; n = 18 interstitial lung disease explants; n = 24 healthy controls) using the highest resolution Synchrotron radiation-based hierarchical phase-contrast tomography, scanning electron microscopy of microvascular corrosion casts, immunohistochemistry, matrix-assisted laser desorption ionization mass spectrometry imaging, and analysis of mRNA expression and biological pathways. Plasma samples from all disease groups were used for liquid biomarker determination using ELISA. The anatomic/molecular data were analyzed as a function of patients' hospitalization time. FINDINGS The observed patchy/mosaic appearance of COVID-19 in conventional lung imaging resulted from microvascular occlusion and secondary lobular ischemia. The length of hospitalization was associated with increased intussusceptive angiogenesis. This was associated with enhanced angiogenic, and fibrotic gene expression demonstrated by molecular profiling and metabolomic analysis. Increased plasma fibrosis markers correlated with their pulmonary tissue transcript levels and predicted disease severity. Plasma analysis confirmed distinct fibrosis biomarkers (TSP2, GDF15, IGFBP7, Pro-C3) that predicted the fatal trajectory in COVID-19. INTERPRETATION Pulmonary severe COVID-19 is a consequence of secondary lobular microischemia and fibrotic remodelling, resulting in a distinctive form of fibrotic interstitial lung disease that contributes to long-COVID. FUNDING This project was made possible by a number of funders. The full list can be found within the Declaration of interests / Acknowledgements section at the end of the manuscript.
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Affiliation(s)
- Maximilian Ackermann
- Institute of Pathology and Molecular Pathology, Helios University Clinic Wuppertal, University of Witten/Herdecke, Germany
- Institute of Functional and Clinical Anatomy, University Medical Center of the Johannes Gutenberg-University Mainz, Germany
| | - Jan C. Kamp
- Department of Respiratory Medicine, Hannover Medical School, Hannover, Germany
- Member of the German Center for Lung Research (DZL), Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Hannover, Germany
| | - Christopher Werlein
- Member of the German Center for Lung Research (DZL), Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Hannover, Germany
- Institute of Pathology, Hannover Medical School, Hannover, Germany
| | - Claire L. Walsh
- Centre for Advanced Biomedical Imaging, University College London, UK
| | - Helge Stark
- Member of the German Center for Lung Research (DZL), Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Hannover, Germany
- Institute of Pathology, Hannover Medical School, Hannover, Germany
| | - Verena Prade
- Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Rambabu Surabattula
- Institute of Translational Immunology and Research Center for Immune Therapy, University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Willi L. Wagner
- Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany
- Member of the German Center for Lung Research (DZL), Translational Lung Research Center Heidelberg (TLRC), Heidelberg, Germany
| | - Catherine Disney
- Department of Mechanical Engineering, University College London, UK
| | | | - Thomas Illig
- Member of the German Center for Lung Research (DZL), Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Hannover, Germany
- Hannover Unified Biobank, Hannover Medical School, Hannover Medical School, Germany
| | - Diana J. Leeming
- Hannover Unified Biobank, Hannover Medical School, Hannover Medical School, Germany
| | | | - Alexandar Tzankov
- Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland
| | - Peter Boor
- Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany
| | - Mark P. Kühnel
- Member of the German Center for Lung Research (DZL), Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Hannover, Germany
- Institute of Pathology, Hannover Medical School, Hannover, Germany
| | - Florian P. Länger
- Member of the German Center for Lung Research (DZL), Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Hannover, Germany
- Institute of Pathology, Hannover Medical School, Hannover, Germany
| | - Stijn E. Verleden
- Department of Thoracic Surgery, University Hospital Antwerp Edegem, Belgium
| | - Hans M. Kvasnicka
- Institute of Pathology and Molecular Pathology, Helios University Clinic Wuppertal, University of Witten/Herdecke, Germany
| | - Hans H. Kreipe
- Institute of Pathology, Hannover Medical School, Hannover, Germany
| | - Axel Haverich
- Member of the German Center for Lung Research (DZL), Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Hannover, Germany
- Department of Cardiothoracic, Transplantation, and Vascular Surgery, Hannover Medical School, Germany
| | - Stephen M. Black
- Department of Cellular Biology and Pharmacology, Center for Translational Research, Florida International University, USA
| | - Axel Walch
- Nordic Bioscience Biomarkers and Research, Herlev, Denmark
| | - Paul Tafforeau
- European Synchrotron Radiation Facility, Grenoble, France
| | - Peter D. Lee
- Hannover Unified Biobank, Hannover Medical School, Hannover Medical School, Germany
| | - Marius M. Hoeper
- Department of Respiratory Medicine, Hannover Medical School, Hannover, Germany
- Member of the German Center for Lung Research (DZL), Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Hannover, Germany
| | - Tobias Welte
- Department of Respiratory Medicine, Hannover Medical School, Hannover, Germany
- Member of the German Center for Lung Research (DZL), Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Hannover, Germany
| | - Benjamin Seeliger
- Department of Respiratory Medicine, Hannover Medical School, Hannover, Germany
- Member of the German Center for Lung Research (DZL), Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Hannover, Germany
| | - Sascha David
- Institute of Intensive Care Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Detlef Schuppan
- Institute of Translational Immunology and Research Center for Immune Therapy, University Medical Center, Johannes Gutenberg University, Mainz, Germany
- Division of Gastroenterology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
| | - Steven J. Mentzer
- Laboratory of Adaptive and Regenerative Biology, Harvard Medical School, Brigham & Women's Hospital, Boston, United States
| | - Danny D. Jonigk
- Member of the German Center for Lung Research (DZL), Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Hannover, Germany
- Institute of Pathology, Hannover Medical School, Hannover, Germany
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23
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Li F, Choi J, Zhang X, Rajaraman PK, Lee CH, Ko H, Chae KJ, Park EK, Comellas AP, Hoffman EA, Lin CL. Characterizing Subjects Exposed to Humidifier Disinfectants Using Computed-Tomography-Based Latent Traits: A Deep Learning Approach. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:11894. [PMID: 36231196 PMCID: PMC9565839 DOI: 10.3390/ijerph191911894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Revised: 09/09/2022] [Accepted: 09/14/2022] [Indexed: 06/16/2023]
Abstract
Around nine million people have been exposed to toxic humidifier disinfectants (HDs) in Korea. HD exposure may lead to HD-associated lung injuries (HDLI). However, many people who have claimed that they experienced HD exposure were not diagnosed with HDLI but still felt discomfort, possibly due to the unknown effects of HD. Therefore, this study examined HD-exposed subjects with normal-appearing lungs, as well as unexposed subjects, in clusters (subgroups) with distinct characteristics, classified by deep-learning-derived computed-tomography (CT)-based tissue pattern latent traits. Among the major clusters, cluster 0 (C0) and cluster 5 (C5) were dominated by HD-exposed and unexposed subjects, respectively. C0 was characterized by features attributable to lung inflammation or fibrosis in contrast with C5. The computational fluid and particle dynamics (CFPD) analysis suggested that the smaller airway sizes observed in the C0 subjects led to greater airway resistance and particle deposition in the airways. Accordingly, women appeared more vulnerable to HD-associated lung abnormalities than men.
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Affiliation(s)
- Frank Li
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA
- IIHR—Hydroscience & Engineering, University of Iowa, Iowa City, IA 52242, USA
| | - Jiwoong Choi
- Department of Mechanical Engineering, University of Iowa, Iowa City, IA 52242, USA
- Department of Internal Medicine, School of Medicine, University of Kansas, Kansas City, KS 66045, USA
| | - Xuan Zhang
- IIHR—Hydroscience & Engineering, University of Iowa, Iowa City, IA 52242, USA
- Department of Mechanical Engineering, University of Iowa, Iowa City, IA 52242, USA
| | - Prathish K. Rajaraman
- IIHR—Hydroscience & Engineering, University of Iowa, Iowa City, IA 52242, USA
- Department of Mechanical Engineering, University of Iowa, Iowa City, IA 52242, USA
| | - Chang-Hyun Lee
- Department of Radiology, University of Iowa, Iowa City, IA 52242, USA
- Department of Radiology, College of Medicine, Seoul National University, Seoul 100-011, Korea
| | - Hongseok Ko
- Department of Radiology, Kangwon National University Hospital, Chuncheon 200-010, Korea
| | - Kum-Ju Chae
- Department of Radiology, Jeonbuk National University Hospital, Jeonju 560-011, Korea
| | - Eun-Kee Park
- Department of Medical Humanities and Social Medicine, College of Medicine, Kosin University, Busan 600-011, Korea
| | | | - Eric A. Hoffman
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA
- Department of Radiology, University of Iowa, Iowa City, IA 52242, USA
- Department of Internal Medicine, University of Iowa, Iowa City, IA 52242, USA
| | - Ching-Long Lin
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA
- IIHR—Hydroscience & Engineering, University of Iowa, Iowa City, IA 52242, USA
- Department of Mechanical Engineering, University of Iowa, Iowa City, IA 52242, USA
- Department of Radiology, University of Iowa, Iowa City, IA 52242, USA
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24
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Falerno I, Paolini A, Tamburro R, Aste G, De Bonis A, Terragni R, Vignoli M. Imaging and endoscopic diagnosis of lung diseases in small animals. A review. Top Companion Anim Med 2022; 51:100701. [PMID: 36041659 DOI: 10.1016/j.tcam.2022.100701] [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: 12/11/2021] [Revised: 08/10/2022] [Accepted: 08/23/2022] [Indexed: 11/25/2022]
Abstract
Diagnostic imaging plays a fundamental role in the diagnosis of pulmonary diseases. Radiography, ultrasound, computed tomography, and endoscopy are important tools for achieving a diagnosis. The choice of diagnostic procedure varies according to the patient, the suspected diagnosis and the risk/benefit ratio. Culture, cytology and histology are nearly always necessary to obtain a definitive diagnosis. Several biopsy sampling techniques are described. Surgical biopsies are the gold standard for the diagnosis of bronchiolitis or interstitial lung diseases but often not performed due to the high risk. In humans, the introduction of transbronchial cryobiopsies has led to excellent results in the study of interstitial lung diseases.
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Affiliation(s)
- Ilaria Falerno
- Faculty of Veterinary Medicine, University of Teramo, 64100 Teramo, Italy.
| | - Andrea Paolini
- Faculty of Veterinary Medicine, University of Teramo, 64100 Teramo, Italy.
| | - Roberto Tamburro
- Faculty of Veterinary Medicine, University of Teramo, 64100 Teramo, Italy.
| | - Giovanni Aste
- Faculty of Veterinary Medicine, University of Teramo, 64100 Teramo, Italy.
| | - Andrea De Bonis
- Faculty of Veterinary Medicine, University of Teramo, 64100 Teramo, Italy.
| | | | - Massimo Vignoli
- Faculty of Veterinary Medicine, University of Teramo, 64100 Teramo, Italy.
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25
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Liu GY, Khan SS, Colangelo LA, Meza D, Washko GR, Sporn PHS, Jacobs DR, Dransfield MT, Carnethon MR, Kalhan R. Comparing Racial Differences in Emphysema Prevalence Among Adults With Normal Spirometry: A Secondary Data Analysis of the CARDIA Lung Study. Ann Intern Med 2022; 175:1118-1125. [PMID: 35849828 PMCID: PMC9673050 DOI: 10.7326/m22-0205] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Computed tomography (CT) imaging complements spirometry and may provide insight into racial disparities in respiratory health. OBJECTIVE To determine the difference in emphysema prevalence between Black and White adults with different measures of normal spirometry results. DESIGN Observational study using clinical data and spirometry from the CARDIA (Coronary Artery Risk Development in Young Adults) study obtained in 2015 to 2016 and CT scans done in 2010 to 2011. SETTING 4 U.S. centers. PARTICIPANTS Population-based sample of Black and White adults. MEASUREMENTS Self-identified race and visually identified emphysema on CT in participants with different measures of "normal" spirometry results, calculated using standard race-specific and race-neutral reference equations. RESULTS A total of 2674 participants (485 Black men, 762 Black women, 659 White men, and 768 White women) had both a CT scan and spirometry available for analysis. Among participants with a race-specific FEV1 between 80% and 99% of predicted, 6.5% had emphysema. In this group, emphysema prevalence was 3.9-fold (95% CI, 2.1- to 7.1-fold; 15.5% vs. 4.0%) higher among Black men than White men and 1.9-fold (CI, 1.0- to 3.8-fold; 6.6% vs. 3.4%) higher among Black women than White women. Among participants with a race-specific FEV1 between 100% and 120% of predicted, 4.0% had emphysema. In this category, Black men had a 6.4-fold (CI, 2.2- to 18.7-fold; 13.9% vs. 2.2%) higher prevalence of emphysema than White men, whereas Black and White women had a similar prevalence of emphysema (2.6% and 2.0%, respectively). The use of race-neutral equations to identify participants with an FEV1 percent predicted between 80% and 120% attenuated racial differences in emphysema prevalence among men and eliminated racial differences among women. LIMITATION No CT scans were obtained during the most recent study visit (2015 to 2016) when spirometry was done. CONCLUSION Emphysema is often present before spirometry findings become abnormal, particularly among Black men. Reliance on spirometry alone to differentiate lung health from lung disease may result in the underrecognition of impaired respiratory health and exacerbate racial disparities. PRIMARY FUNDING SOURCE National Institutes of Health.
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Affiliation(s)
- Gabrielle Y Liu
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (G.Y.L., D.M., P.H.S.S.)
| | - Sadiya S Khan
- Division of Cardiology, Department of Medicine, and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (S.S.K.)
| | - Laura A Colangelo
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (L.A.C.)
| | - Daniel Meza
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (G.Y.L., D.M., P.H.S.S.)
| | - George R Washko
- Applied Chest Imaging Laboratory and Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts (G.R.W.)
| | - Peter H S Sporn
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (G.Y.L., D.M., P.H.S.S.)
| | - David R Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota (D.R.J.)
| | - Mark T Dransfield
- Lung Health Center, University of Alabama at Birmingham, Birmingham, Alabama (M.T.D.)
| | - Mercedes R Carnethon
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.R.C., R.K.)
| | - Ravi Kalhan
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.R.C., R.K.)
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26
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Xian RP, Walsh CL, Verleden SE, Wagner WL, Bellier A, Marussi S, Ackermann M, Jonigk DD, Jacob J, Lee PD, Tafforeau P. A multiscale X-ray phase-contrast tomography dataset of a whole human left lung. Sci Data 2022; 9:264. [PMID: 35654864 PMCID: PMC9163096 DOI: 10.1038/s41597-022-01353-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 05/03/2022] [Indexed: 11/09/2022] Open
Abstract
Technological advancements in X-ray imaging using bright and coherent synchrotron sources now allows the decoupling of sample size and resolution while maintaining high sensitivity to the microstructures of soft, partially dehydrated tissues. The continuous developments in multiscale X-ray imaging resulted in hierarchical phase-contrast tomography, a comprehensive approach to address the challenge of organ-scale (up to tens of centimeters) soft tissue imaging with resolution and sensitivity down to the cellular level. Using this technique, we imaged ex vivo an entire human left lung at an isotropic voxel size of 25.08 μm along with local zooms down to 6.05-6.5 μm and 2.45-2.5 μm in voxel size. The high tissue contrast offered by the fourth-generation synchrotron source at the European Synchrotron Radiation Facility reveals the complex multiscale anatomical constitution of the human lung from the macroscopic (centimeter) down to the microscopic (micrometer) scale. The dataset provides comprehensive organ-scale 3D information of the secondary pulmonary lobules and delineates the microstructure of lung nodules with unprecedented detail.
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Affiliation(s)
- R Patrick Xian
- Department of Mechanical Engineering, University College London, London, UK.
| | - Claire L Walsh
- Department of Mechanical Engineering, University College London, London, UK
| | - Stijn E Verleden
- Antwerp Surgical Training, Anatomy and Research Centre (ASTARC), University of Antwerp, Wilrijk, Belgium
| | - Willi L Wagner
- Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany
- Translational Lung Research Centre Heidelberg (TLRC), German Lung Research Centre (DZL), Heidelberg, Germany
| | - Alexandre Bellier
- Laboratoire d'Anatomie des Alpes Françaises (LADAF), Université Grenoble Alpes, Grenoble, France
| | - Sebastian Marussi
- Department of Mechanical Engineering, University College London, London, UK
| | - Maximilian Ackermann
- Institute of Pathology and Molecular Pathology, Helios University Clinic Wuppertal, University of Witten/Herdecke, Wuppertal, Germany
- Institute of Functional and Clinical Anatomy, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Danny D Jonigk
- Institute of Pathology, Hannover Medical School, Hannover, Germany
- Biomedical Research in End-stage and Obstructive Lung Disease Hannover (BREATH), German Lung Research Centre (DZL), Hannover, Germany
| | - Joseph Jacob
- Centre for Medical Image Computing, University College London, London, UK
- Department of Radiology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Peter D Lee
- Department of Mechanical Engineering, University College London, London, UK.
| | - Paul Tafforeau
- European Synchrotron Radiation Facility, Grenoble, France.
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27
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Hochhegger1,2,3 B, Marchiori4 E, Rodrigues5 R, Mançano6 A, Jasinowodolinski4 D, Caruso Chate7 R, Soares Souza Jr8 A, Marchini Silva9 A, Sawamura10 M, Furnari6 M, Araujo-Neto11 C, Escuissato12 D, Pinetti13 R, Felipe Nobre14 L, Warszawiak15 D, Szarf16 G, Borges da Silva Telles7 G, Meirelles17 G, Rydz Santana18 P, Antunes13 V, Capobianco19 J, Missrie19 I, Volpon Soares Souza8 L, Koenigkam Santos20 M, Irion21 K, Duarte22 I, Santos23 R, Pinto23 E, Penha23 D. ERRATUM. J Bras Pneumol 2022; 47:e20200595errata. [PMID: 35019060 DOI: 10.36416/1806-3713/e20200595errata] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
[This corrects the article doi: 10.36416/1806-3756/e20200595].
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Affiliation(s)
- Bruno Hochhegger1,2,3
- 1. Pontifícia Universidade Católica do Rio Grande do Sul – PUCRS – Porto Alegre (RS) Brasil. 2. Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre (RS) Brasil. 3. Thoracic Imaging Division, College of Medicine, University of Florida, Gainesville (FL) USA
| | - Edson Marchiori4
- 4. Universidade Federal do Rio de Janeiro – UFRJ – Rio de Janeiro (RJ) Brasil
| | - Rosana Rodrigues5
- 5. Universidade Federal do Rio Grande do Sul – UFRGS – Porto Alegre (RS) Brasil
| | | | | | | | | | | | | | | | | | | | | | | | | | - Gilberto Szarf16
- 16. Universidade Federal de São Paulo – Unifesp – São Paulo (SP) Brasil
| | | | | | | | | | | | | | | | - Marcel Koenigkam Santos20
- 20. Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo – USP – Ribeirão Preto (SP) Brasil
| | - Klaus Irion21
- 21. Manchester National Health Service, Manchester, United Kingdom
| | - Isabel Duarte22
- 22. Instituto Português de Oncologia de Lisboa Francisco Gentil, Lisboa, Portugal
| | | | | | - Diana Penha23
- 23. Universidade da Beira Interior, Covilhã, Portugal
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28
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Spectral Photon-Counting CT Technology in Chest Imaging. J Clin Med 2021; 10:jcm10245757. [PMID: 34945053 PMCID: PMC8704215 DOI: 10.3390/jcm10245757] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 11/30/2021] [Accepted: 12/02/2021] [Indexed: 12/17/2022] Open
Abstract
The X-ray imaging field is currently undergoing a period of rapid technological innovation in diagnostic imaging equipment. An important recent development is the advent of new X-ray detectors, i.e., photon-counting detectors (PCD), which have been introduced in recent clinical prototype systems, called PCD computed tomography (PCD-CT) or photon-counting CT (PCCT) or spectral photon-counting CT (SPCCT) systems. PCD allows a pixel up to 200 microns pixels at iso-center, which is much smaller than that can be obtained with conventional energy integrating detectors (EID). PCDs have also a higher dose efficiency than EID mainly because of electronic noise suppression. In addition, the energy-resolving capabilities of these detectors allow generating spectral basis imaging, such as the mono-energetic images or the water/iodine material images as well as the K-edge imaging of a contrast agent based on atoms of high atomic number. In recent years, studies have therefore been conducted to determine the potential of PCD-CT as an alternative to conventional CT for chest imaging.
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29
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Vindin HJ, Oliver BG, Weiss AS. Elastin in healthy and diseased lung. Curr Opin Biotechnol 2021; 74:15-20. [PMID: 34781101 DOI: 10.1016/j.copbio.2021.10.025] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Revised: 10/12/2021] [Accepted: 10/19/2021] [Indexed: 01/05/2023]
Abstract
Elastic fibers are an essential part of the pulmonary extracellular matrix (ECM). Intact elastin is required for normal function and its damage contributes profoundly to the etiology and pathology of lung disease. This highlights the need for novel lung-specific imaging methodology that enables high-resolution 3D visualization of the ECM. We consider elastin's involvement in chronic respiratory disease and examine recent methods for imaging and modeling of the lung in the context of advances in lung tissue engineering for research and clinical application.
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Affiliation(s)
- Howard J Vindin
- Charles Perkins Centre, The University of Sydney, Sydney 2006, NSW, Australia; School of Life and Environmental Sciences, The University of Sydney, 2006 Sydney, NSW, Australia; The Woolcock Institute, The University of Sydney, Sydney 2006, NSW, Australia
| | - Brian Gg Oliver
- The Woolcock Institute, The University of Sydney, Sydney 2006, NSW, Australia
| | - Anthony S Weiss
- Charles Perkins Centre, The University of Sydney, Sydney 2006, NSW, Australia; School of Life and Environmental Sciences, The University of Sydney, 2006 Sydney, NSW, Australia; Sydney Nano Institute, The University of Sydney, 2006 Sydney, NSW, Australia.
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30
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Ostras O, Soulioti DE, Pinton G. Diagnostic ultrasound imaging of the lung: A simulation approach based on propagation and reverberation in the human body. THE JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2021; 150:3904. [PMID: 34852581 DOI: 10.1121/10.0007273] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 09/23/2021] [Indexed: 06/13/2023]
Abstract
Although ultrasound cannot penetrate a tissue/air interface, it images the lung with high diagnostic accuracy. Lung ultrasound imaging relies on the interpretation of "artifacts," which arise from the complex reverberation physics occurring at the lung surface but appear deep inside the lung. This physics is more complex and less understood than conventional B-mode imaging in which the signal directly reflected by the target is used to generate an image. Here, to establish a more direct relationship between the underlying acoustics and lung imaging, simulations are used. The simulations model ultrasound propagation and reverberation in the human abdomen and at the tissue/air interfaces of the lung in a way that allows for direct measurements of acoustic pressure inside the human body and various anatomical structures, something that is not feasible clinically or experimentally. It is shown that the B-mode images beamformed from these acoustical simulations reproduce primary clinical features that are used in diagnostic lung imaging, i.e., A-lines and B-lines, with a clear relationship to known underlying anatomical structures. Both the oblique and parasagittal views are successfully modeled with the latter producing the characteristic "bat sign," arising from the ribs and intercostal part of the pleura. These simulations also establish a quantitative link between the percentage of fluid in exudative regions and the appearance of B-lines, suggesting that the B-mode may be used as a quantitative imaging modality.
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Affiliation(s)
- Oleksii Ostras
- Joint Department of Biomedical Engineering of the University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill, North Carolina 27514, USA
| | - Danai Eleni Soulioti
- Joint Department of Biomedical Engineering of the University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill, North Carolina 27514, USA
| | - Gianmarco Pinton
- Joint Department of Biomedical Engineering of the University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill, North Carolina 27514, USA
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31
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Hochhegger B, Marchiori E, Rodrigues R, Mançano A, Jasinowodolinski D, Chate RC, Souza AS, Silva AM, Sawamura M, Furnari M, Araujo-Neto C, Escuissato D, Pinetti R, Nobre LF, Warszawiak D, Szarf G, Telles GBDS, Meirelles G, Santana PR, Antunes V, Capobianco J, Missrie I, Souza LVS, Santos MK, Irion K, Duarte I, Santos R, Pinto E, Penha D. Consensus statement on thoracic radiology terminology in Portuguese used in Brazil and in Portugal. JORNAL BRASILEIRO DE PNEUMOLOGIA : PUBLICACAO OFICIAL DA SOCIEDADE BRASILEIRA DE PNEUMOLOGIA E TISILOGIA 2021; 47:e20200595. [PMID: 34669832 PMCID: PMC9013533 DOI: 10.36416/1806-3756/e20200595] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 05/27/2021] [Indexed: 11/17/2022]
Abstract
Effective communication among members of medical teams is an important factor for early and appropriate diagnosis. The terminology used in radiology reports appears in this context as an important link between radiologists and other members of the medical team. Therefore, heterogeneity in the use of terms in reports is an important but little discussed issue. This article is the result of an extensive review of nomenclature in thoracic radiology, including for the first time terms used in X-rays, CT, and MRI, conducted by radiologists from Brazil and Portugal. The objective of this review of medical terminology was to create a standardized language for medical professionals and multidisciplinary teams.
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Affiliation(s)
- Bruno Hochhegger
- . Pontifícia Universidade Católica do Rio Grande do Sul - PUCRS - Porto Alegre (RS) Brasil.,. Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre (RS) Brasil.,. Thoracic Imaging Division, College of Medicine, University of Florida, Gainesville (FL) USA
| | - Edson Marchiori
- . Universidade Federal do Rio de Janeiro - UFRJ - Rio de Janeiro (RJ) Brasil
| | - Rosana Rodrigues
- . Universidade Federal do Rio Grande do Sul - UFRGS - Porto Alegre (RS) Brasil
| | | | | | | | - Arthur Soares Souza
- . Faculdade de Medicina de São José do Rio Preto, São José do Rio Preto (SP) Brasil
| | | | | | | | | | | | | | | | | | - Gilberto Szarf
- . Universidade Federal de São Paulo - Unifesp - São Paulo (SP) Brasil
| | | | | | | | | | | | | | | | - Marcel Koeningan Santos
- . Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo - USP - Ribeirão Preto (SP) Brasil
| | - Klaus Irion
- . Manchester National Health Service, Manchester, United Kingdom
| | - Isabel Duarte
- . Instituto Português de Oncologia de Lisboa Francisco Gentil, Lisboa, Portugal
| | | | - Erique Pinto
- . Universidade da Beira Interior, Covilhã, Portugal
| | - Diana Penha
- . Universidade da Beira Interior, Covilhã, Portugal
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32
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Wielpütz MO. Artificial Intelligence for Interstitial Lung Disease: Proudly Supporting Radiologists Since 2021. Radiology 2021; 302:198-199. [PMID: 34636638 DOI: 10.1148/radiol.2021210731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Mark O Wielpütz
- From the Translational Lung Research Center (TLRC), German Lung Research Center, University of Heidelberg, Heidelberg, Germany; Department of Diagnostic and Interventional Radiology, University of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany; and Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
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33
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Capaccione KM, Austin JHM, Saqi A, Patel N, Padilla M, Salvatore MM. Hypersensitivity pneumonitis: Airway-centered pulmonary fibrosis on chest CT. Respir Investig 2021; 59:845-848. [PMID: 34373236 DOI: 10.1016/j.resinv.2021.06.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Revised: 06/08/2021] [Accepted: 06/14/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND To evaluate the chest CT appearance of patients with a clinicopathologic diagnosis of hypersensitivity pneumonia. METHODS IRB approval was obtained for a retrospective review of patients with a preoperative CT scan, a surgical pathology report from a transbronchial biopsy or wedge resection consistent with hypersensitivity pneumonitis, and a pulmonary consultation, which also supported the diagnosis. The pathology report was evaluated for granulomas, airway-centered fibrosis, microscopic honeycombing, and fibroblast foci. The medical records were reviewed for any known antigen exposure. Patients were separated into two groups; those with and without a known antigen exposure. The CT scans were assessed for distribution of fibrosis: upper lobe or lower lobe predominance, airway-centered versus peripheral distribution, three-density pattern, and honeycombing. RESULTS 264 pathology reports included the term chronic hypersensitivity pneumonitis (CHP). Thirty-eight of the patients had a pulmonologist who gave the patient a working diagnosis of CHP. The average age of these patients was 64 years, and 21/38 were women. Seventeen of the 38 patients had at least one antigen exposure described in the medical records. All the patients had fibrosis along the airways on chest CT. Both known antigen exposure and no known antigen patients had upper and lower lung-predominant fibrosis. There were more patients with hiatal hernias in the unknown antigen group. Honeycombing was an uncommon finding. CONCLUSION Airway-centered fibrosis was present on chest CT in all 38 patients with CHP (100%), with or without known antigen exposure.
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Affiliation(s)
- K M Capaccione
- Department of Radiology, Columbia University Irving Medical Center, New York, NY, USA
| | - John H M Austin
- Department of Radiology, Columbia University Irving Medical Center, New York, NY, USA
| | - Anjali Saqi
- Department of Pathology, Columbia University Irving Medical Center, New York, NY, USA
| | - Nina Patel
- Department of Pulmonary Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Maria Padilla
- Department of Pulmonary Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mary M Salvatore
- Department of Radiology, Columbia University Irving Medical Center, New York, NY, USA.
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34
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Kato S, Ishiwata Y, Aoki R, Iwasawa T, Hagiwara E, Ogura T, Utsunomiya D. Imaging of COVID-19: An update of current evidences. Diagn Interv Imaging 2021; 102:493-500. [PMID: 34088635 PMCID: PMC8148573 DOI: 10.1016/j.diii.2021.05.006] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 05/16/2021] [Accepted: 05/17/2021] [Indexed: 12/15/2022]
Abstract
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been reported as a global emergency. As respiratory dysfunction is a major clinical presentation of COVID-19, chest computed tomography (CT) plays a central role in the diagnosis and management of patients with COVID-19. Recent advances in imaging approaches using artificial intelligence have been essential as a quantification and diagnostic tool to differentiate COVID-19 from other respiratory infectious diseases. Furthermore, cardiovascular involvement in patients with COVID-19 is not negligible and may result in rapid worsening of the disease and sudden death. Cardiac magnetic resonance imaging can accurately depict myocardial involvement in SARS-CoV-2 infection. This review summarizes the role of the radiology department in the management and the diagnosis of COVID-19, with a special emphasis on ultra-high-resolution CT findings, cardiovascular complications and the potential of artificial intelligence.
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Affiliation(s)
- Shingo Kato
- Department of Diagnostic Radiology, Yokohama City University Graduate School of Medicine, 236-0004 Yokohama, Kanagawa, Japan.
| | - Yoshinobu Ishiwata
- Department of Diagnostic Radiology, Yokohama City University Graduate School of Medicine, 236-0004 Yokohama, Kanagawa, Japan
| | - Ryo Aoki
- Department of Diagnostic Radiology, Yokohama City University Medical Center, 232-0024 Yokohama, Kanagawa, Japan
| | - Tae Iwasawa
- Department of Diagnostic Radiology, Kanagawa Cardiovascular and Respiratory Center, 236-0051 Yokohama, Kanagawa, Japan
| | - Eri Hagiwara
- Department of Respiratory Medicine, Kanagawa Cardiovascular and Respiratory Center, 236-0051 Yokohama, Kanagawa, Japan
| | - Takashi Ogura
- Department of Respiratory Medicine, Kanagawa Cardiovascular and Respiratory Center, 236-0051 Yokohama, Kanagawa, Japan
| | - Daisuke Utsunomiya
- Department of Diagnostic Radiology, Yokohama City University Graduate School of Medicine, 236-0004 Yokohama, Kanagawa, Japan
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Ohno Y, Seo JB, Parraga G, Lee KS, Gefter WB, Fain SB, Schiebler ML, Hatabu H. Pulmonary Functional Imaging: Part 1-State-of-the-Art Technical and Physiologic Underpinnings. Radiology 2021; 299:508-523. [PMID: 33825513 DOI: 10.1148/radiol.2021203711] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Over the past few decades, pulmonary imaging technologies have advanced from chest radiography and nuclear medicine methods to high-spatial-resolution or low-dose chest CT and MRI. It is currently possible to identify and measure pulmonary pathologic changes before these are obvious even to patients or depicted on conventional morphologic images. Here, key technological advances are described, including multiparametric CT image processing methods, inhaled hyperpolarized and fluorinated gas MRI, and four-dimensional free-breathing CT and MRI methods to measure regional ventilation, perfusion, gas exchange, and biomechanics. The basic anatomic and physiologic underpinnings of these pulmonary functional imaging techniques are explained. In addition, advances in image analysis and computational and artificial intelligence (machine learning) methods pertinent to functional lung imaging are discussed. The clinical applications of pulmonary functional imaging, including both the opportunities and challenges for clinical translation and deployment, will be discussed in part 2 of this review. Given the technical advances in these sophisticated imaging methods and the wealth of information they can provide, it is anticipated that pulmonary functional imaging will be increasingly used in the care of patients with lung disease. © RSNA, 2021 Online supplemental material is available for this article.
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Affiliation(s)
- Yoshiharu Ohno
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Joon Beom Seo
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Grace Parraga
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Kyung Soo Lee
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Warren B Gefter
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Sean B Fain
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Mark L Schiebler
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Hiroto Hatabu
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
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Li F, Choi J, Zou C, Newell JD, Comellas AP, Lee CH, Ko H, Barr RG, Bleecker ER, Cooper CB, Abtin F, Barjaktarevic I, Couper D, Han M, Hansel NN, Kanner RE, Paine R, Kazerooni EA, Martinez FJ, O'Neal W, Rennard SI, Smith BM, Woodruff PG, Hoffman EA, Lin CL. Latent traits of lung tissue patterns in former smokers derived by dual channel deep learning in computed tomography images. Sci Rep 2021; 11:4916. [PMID: 33649381 PMCID: PMC7921389 DOI: 10.1038/s41598-021-84547-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2020] [Accepted: 02/15/2021] [Indexed: 11/30/2022] Open
Abstract
Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and the traditional variables extracted from computed tomography (CT) images may not be sufficient to describe all the topological features of lung tissues in COPD patients. We employed an unsupervised three-dimensional (3D) convolutional autoencoder (CAE)-feature constructor (FC) deep learning network to learn from CT data and derive tissue pattern-clusters jointly. We then applied exploratory factor analysis (EFA) to discover the unobserved latent traits (factors) among pattern-clusters. CT images at total lung capacity (TLC) and residual volume (RV) of 541 former smokers and 59 healthy non-smokers from the cohort of the SubPopulations and Intermediate Outcome Measures in the COPD Study (SPIROMICS) were analyzed. TLC and RV images were registered to calculate the Jacobian (determinant) values for all the voxels in TLC images. 3D Regions of interest (ROIs) with two data channels of CT intensity and Jacobian value were randomly extracted from training images and were fed to the 3D CAE-FC model. 80 pattern-clusters and 7 factors were identified. Factor scores computed for individual subjects were able to predict spirometry-measured pulmonary functions. Two factors which correlated with various emphysema subtypes, parametric response mapping (PRM) metrics, airway variants, and airway tree to lung volume ratio were discriminants of patients across all severity stages. Our findings suggest the potential of developing factor-based surrogate markers for new COPD phenotypes.
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Affiliation(s)
- Frank Li
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
- IIHR-Hydroscience and Engineering, 2406 Seamans Center for the Engineering Art and Science, University of Iowa, Iowa City, IA, 52242, USA
| | - Jiwoong Choi
- Department of Mechanical Engineering, University of Iowa, Iowa City, IA, USA
- Department of Internal Medicine, School of Medicine, University of Kansas, Kansas City, KS, USA
| | - Chunrui Zou
- IIHR-Hydroscience and Engineering, 2406 Seamans Center for the Engineering Art and Science, University of Iowa, Iowa City, IA, 52242, USA
- Department of Mechanical Engineering, University of Iowa, Iowa City, IA, USA
| | - John D Newell
- Department of Radiology, University of Iowa, Iowa City, IA, USA
| | | | - Chang Hyun Lee
- Department of Radiology, University of Iowa, Iowa City, IA, USA
- Department of Radiology, Seoul National University, Seoul, Republic of Korea
| | - Hongseok Ko
- Department of Radiology, Chungnam National University Sejong Hospital, Sejong, Republic of Korea
| | - R Graham Barr
- Mailman School of Public Health, Columbia University, New York, NY, USA
| | | | | | | | | | - David Couper
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
| | - MeiLan Han
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | | | | | - Robert Paine
- School of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Ella A Kazerooni
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
| | | | - Wanda O'Neal
- School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Stephen I Rennard
- Department of Internal Medicine, University of Nebraska College of Medicine, Omaha, NE, USA
| | - Benjamin M Smith
- Department of Medicine, Columbia University, New York, NY, USA
- Research Institute, McGill University Health Center, Montreal, Canada
| | | | - Eric A Hoffman
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
- Department of Radiology, University of Iowa, Iowa City, IA, USA
- Department of Internal Medicine, University of Iowa, Iowa City, IA, USA
| | - Ching-Long Lin
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA.
- IIHR-Hydroscience and Engineering, 2406 Seamans Center for the Engineering Art and Science, University of Iowa, Iowa City, IA, 52242, USA.
- Department of Mechanical Engineering, University of Iowa, Iowa City, IA, USA.
- Department of Radiology, University of Iowa, Iowa City, IA, USA.
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Abadi E, Paul Segars W, Chalian H, Samei E. Virtual Imaging Trials for Coronavirus Disease (COVID-19). AJR Am J Roentgenol 2021; 216:362-368. [PMID: 32822224 PMCID: PMC8080437 DOI: 10.2214/ajr.20.23429] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVE. The virtual imaging trial is a unique framework that can greatly facilitate the assessment and optimization of imaging methods by emulating the imaging experiment using representative computational models of patients and validated imaging simulators. The purpose of this study was to show how virtual imaging trials can be adapted for imaging studies of coronavirus disease (COVID-19), enabling effective assessment and optimization of CT and radiography acquisitions and analysis tools for reliable imaging and management of COVID-19. MATERIALS AND METHODS. We developed the first computational models of patients with COVID-19 and as a proof of principle showed how they can be combined with imaging simulators for COVID-19 imaging studies. For the body habitus of the models, we used the 4D extended cardiac-torso (XCAT) model that was developed at Duke University. The morphologic features of COVID-19 abnormalities were segmented from 20 CT images of patients who had been confirmed to have COVID-19 and incorporated into XCAT models. Within a given disease area, the texture and material of the lung parenchyma in the XCAT were modified to match the properties observed in the clinical images. To show the utility, three developed COVID-19 computational phantoms were virtually imaged using a scanner-specific CT and radiography simulator. RESULTS. Subjectively, the simulated abnormalities were realistic in terms of shape and texture. Results showed that the contrast-to-noise ratios in the abnormal regions were 1.6, 3.0, and 3.6 for 5-, 25-, and 50-mAs images, respectively. CONCLUSION. The developed toolsets in this study provide the foundation for use of virtual imaging trials in effective assessment and optimization of CT and radiography acquisitions and analysis tools to help manage the COVID-19 pandemic.
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Affiliation(s)
- Ehsan Abadi
- Department of Radiology, Duke University, 2424 Erwin Rd, Ste 302, Durham, NC 27705
- Carl E. Ravin Advanced Imaging Laboratories, Duke University, Durham, NC
| | - W Paul Segars
- Department of Radiology, Duke University, 2424 Erwin Rd, Ste 302, Durham, NC 27705
- Carl E. Ravin Advanced Imaging Laboratories, Duke University, Durham, NC
- Department of Biomedical Engineering, Duke University, Durham, NC
| | - Hamid Chalian
- Department of Radiology, Duke University, 2424 Erwin Rd, Ste 302, Durham, NC 27705
| | - Ehsan Samei
- Department of Radiology, Duke University, 2424 Erwin Rd, Ste 302, Durham, NC 27705
- Carl E. Ravin Advanced Imaging Laboratories, Duke University, Durham, NC
- Department of Biomedical Engineering, Duke University, Durham, NC
- Department of Physics, Duke University, Durham, NC
- Department of Electrical and Computer Engineering, Duke University, Durham, NC
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Rajalingam B, Narayanan E, Nirmalan P, Muthukrishnan K, Sundaram V, Kumaravelu S, Gopalan M, Jeyapal S, Rajalingam B, Khanna V, Dhoss P, Gopinath. Pattern recognition of high-resolution computer tomography (HRCT) chest to guide clinical management in patients with mild to moderate COVID-19. Indian J Radiol Imaging 2021; 31:S110-S118. [PMID: 33814769 PMCID: PMC7996691 DOI: 10.4103/ijri.ijri_774_20] [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: 09/18/2020] [Revised: 12/14/2020] [Accepted: 12/21/2020] [Indexed: 11/26/2022] Open
Abstract
AIM To describe the distribution of lung patterns determined by High Resolution Computed Tomography (HRCT) in COVID patients with mild and moderate lung involvement and outcomes after early identification and management with steroids and anticoagulants. MATERIAL AND METHODS A cross sectional study of COVID-19 patients with mild and moderate lung involvement presenting at 5 healthcare centres in Trichy district of South TamilNadu in India. Patients underwent HRCT to assess patterns and severity of lung involvement, Inflammatory markers (LDH/Ferritin) and D-Dimer assay and clinical correlation with signs and symptoms. Patients were assessed for oxygen, steroid and anticoagulant therapy, clinical recovery or progression on follow up and details on mortality were collected. The RSNA, Fleischer Society guidelines and CORADS score was used for radiological reporting. New potential classification of patterns of percentage of lung parenchyma involvement in Covid patients is being suggested. RESULTS The study included 7,340 patients with suspected COVID and 3,963 (53.9%) patients had lung involvement based on HRCT. RT PCR was positive in 74.1% of the CT Positive cases. Crazy Pavement pattern was predominant (n = 2022, 51.0%) and Ground Glass Opacity (GGO) was found in 1,941 (49.0%) patients in the study. Severe lung involvement was more common in the Crazy Pavement pattern. Patients with GGO in moderate lung involvement were significantly more likely to recover faster compared to Crazy Pavement pattern (P value <0.001). CONCLUSION HRCT chest and assessment of lung patterns can help triage patients to home quarantine and hospital admission. Early initiation of steroids and anticoagulants based on lung patterns can prevent progression to more severe stages and aid early recovery. HRCT can play a major role to triage and guide management especially as RT PCR testing and results are delayed for the benefit of patients and in a social cause to decrease the spread of the virus.
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Affiliation(s)
| | - Ethirajan Narayanan
- Retired Professor, Social & Preventive Medicine, Chidambaram, Trichy, Tamil Nadu, India
| | - Praveen Nirmalan
- MPH, Reasearch Head, Amma Education Research Foundation, Kochi, India
| | | | - Vivek Sundaram
- Sundaram Hospital, Director, Saravana Medical Centre, Singarathope, Trichy, Tamil Nadu, India
| | | | - Mukundhan Gopalan
- ABC Hopsital, Director, GVN Hopsital, Singarathope, Trichy, Tamil Nadu, India
| | - Senthil Jeyapal
- Director, GVN Hopsital, Singarathope, Trichy, Tamil Nadu, India
| | | | - Vijay Khanna
- Consultant Critcal Care, Retna Global Hopsital, Trichy, Tamil Nadu, India
| | - Praveen Dhoss
- Director, Retna Global Hopsital, Trichy, Tamil Nadu, India
| | - Gopinath
- Emergency Medical Officer, Sundaram Hospital, Trichy, Tamil Nadu, India
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Rawashdeh MA, Saade C. Radiation dose reduction considerations and imaging patterns of ground glass opacities in coronavirus: risk of over exposure in computed tomography. LA RADIOLOGIA MEDICA 2021; 126:380-387. [PMID: 32897493 PMCID: PMC7477737 DOI: 10.1007/s11547-020-01271-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 08/23/2020] [Indexed: 01/07/2023]
Abstract
This article aims to summarize the available data on the severe acute respiratory syndrome coronavirus 2 (SAR-CoV-2) imaging patterns as well as reducing radiation dose exposure in chest computed tomography (CT) protocols. First, the general aspects of radiation dose in CT and radiation risk are discussed, followed by the effect of changing parameters on image quality. This article attempts to highlight some of the common chest CT signs that radiologists and emergency physicians are likely to encounter. With the increasing trend of using chest CT scans as an imaging tool to diagnose and monitor SAR-CoV-2, we emphasize that pattern recognition is the key, and this pictorial essay should serve as a guide to help establish correct diagnosis coupled with correct scanner parameters to reduce radiation dose without affecting imaging quality in this tragic pandemic the world is facing.
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Affiliation(s)
- Mohammad Ahmmad Rawashdeh
- grid.37553.370000 0001 0097 5797Department of Allied Medical Sciences, Jordan University of Science and Technology, P.O.Box 3030, Irbid, 22110 Jordan
| | - Charbel Saade
- grid.411654.30000 0004 0581 3406Diagnostic Radiology Department, American University of Beirut Medical Center, P.O.Box 11-0236, Riad El-Solh, Beirut, 1107 2020 Lebanon
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Choi MJ, Kang H. CT Findings of Central Airway Lesions Causing Airway Stenosis-Visualization and Quantification: A Pictorial Essay. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2021; 82:1441-1476. [PMID: 36238875 PMCID: PMC9431977 DOI: 10.3348/jksr.2020.0212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 03/02/2021] [Accepted: 05/25/2021] [Indexed: 11/25/2022]
Abstract
The tracheobronchial tree is a system of airways that allows the passage of air to aerate the lungs and entire body. Several pathological conditions can affect this anatomical region. Multidetector CT (MDCT) helps identify and characterize various large airway diseases. Post-processing tools, such as virtual bronchoscopy and automatic lung analysis, can help enhance the performance of imaging studies. In this pictorial essay review, we provide imaging findings of various bronchial lesions manifested as wall thickening and endoluminal nodules on conventional MDCT and advanced image visualization and analysis.
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Affiliation(s)
- Myeong Jin Choi
- Department of Radiology, Kosin University Gospel Hospital, Kosin University College of Medicine, Busan, Korea
| | - Hee Kang
- Department of Radiology, Kosin University Gospel Hospital, Kosin University College of Medicine, Busan, Korea
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41
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Tao S, Rajendran K, Zhou W, Fletcher JG, McCollough CH, Leng S. Noise reduction in CT image using prior knowledge aware iterative denoising. Phys Med Biol 2020; 65. [PMID: 33065559 DOI: 10.1088/1361-6560/abc231] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 10/16/2020] [Indexed: 11/11/2022]
Abstract
The clinical demand for low image noise often limits the slice thickness used in many CT applications. However, a thick-slice image is more susceptible to longitudinal partial volume effects, which can blur key anatomic structures and pathologies of interest. In this work, we develop a prior-knowledge-aware iterative denoising (PKAID) framework that utilizes spatial data redundancy in the slice increment direction to generate low-noise, thin-slice images, and demonstrate its application in non-contrast head CT exams. The proposed technique takes advantage of the low-noise of thicker images and exploits the structural similarity between the thick- and thin-slice images to reduce noise in the thin-slice image. Phantom data and patient cases (n=3) of head CT were used to assess performance of this method. Images were reconstructed at clinically-utilized slice thickness (5 mm) and thinner slice thickness (2 mm). PKAID was used to reduce image noise in 2 mm images using the 5 mm images as low-noise prior. Noise amplitude, noise power spectra (NPS), modulation transfer function (MTF), and slice sensitivity profiles (SSP) of images before/after denoising were analyzed. The NPS and MTF analysis showed that PKAID preserved noise texture and resolution of the original thin-slice image, while reducing noise to the level of thick-slice image. The SSP analysis showed that the slice thickness of the original thin-slice image was retained. Patient examples demonstrated that PKAID-processed, thin-slice images better delineated brain structures and key pathologies such as subdural hematoma compared to the clinical 5 mm images, while additionally reducing image noise. To test an alternative PKAID utilization for dose reduction, a head exam with 40% dose reduction was simulated using projection-domain noise insertion. The image of 5 mm slice thickness was then denoised using PKAID. The results showed that the PKAID-processed reduced-dose images maintained similar noise and image quality compared to the full-dose images.
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Affiliation(s)
- Shengzhen Tao
- Radiology, Mayo Clinic Minnesota, 200 First St SW, Rochester, Rochester, Minnesota, 55905-0002, UNITED STATES
| | - Kishore Rajendran
- Radiology, Mayo Clinic , 200 First street SW, Rochester, Minnesota, 55905, UNITED STATES
| | - Wei Zhou
- Radiology, University of Colorado Denver, Denver, Colorado, UNITED STATES
| | - Joel G Fletcher
- Radiology, Mayo Clinic , Rochester, Minnesota, UNITED STATES
| | - Cynthia H McCollough
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA, Rochester, Minnesota, UNITED STATES
| | - Shuai Leng
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905, USA, Rochester, UNITED STATES
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42
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Chen L, Ge M. [Advances in Identification of Intersegmental Plane during Pulmonary Segmentectomy]. ZHONGGUO FEI AI ZA ZHI = CHINESE JOURNAL OF LUNG CANCER 2020; 23:818-823. [PMID: 32773009 PMCID: PMC7519953 DOI: 10.3779/j.issn.1009-3419.2020.101.31] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
With the popularity of computed tomography (CT) scan in recent years, early stage lung cancer has been discovered in large numbers of patients and pulmonary segmentectomy has been widely used clinically. Identification of the intersegmental plane is one of the key steps in pulmonary segmentectomy, and current methods for identifying the intersegmental plane are numerous and have their own advantages and disadvantages. We will review relevant methods to help the clinical practice.
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Affiliation(s)
- Liang Chen
- Department of Thoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Mingjian Ge
- Department of Thoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
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43
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Umetani K, Okamoto T, Saito K, Kawata Y, Niki N. 36M-pixel synchrotron radiation micro-CT for whole secondary pulmonary lobule visualization from a large human lung specimen. Eur J Radiol Open 2020; 7:100262. [PMID: 32984451 PMCID: PMC7495051 DOI: 10.1016/j.ejro.2020.100262] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 08/24/2020] [Indexed: 11/30/2022] Open
Abstract
A micro-CT system was developed using a 36M-pixel digital single-lens reflex camera as a cost-effective mode for large human lung specimen imaging. Scientific grade cameras used for biomedical x-ray imaging are much more expensive than consumer-grade cameras. During the past decade, advances in image sensor technology for consumer appliances have spurred the development of biomedical x-ray imaging systems using commercial digital single-lens reflex cameras fitted with high megapixel CMOS image sensors. This micro-CT system is highly specialized for visualizing whole secondary pulmonary lobules in a large human lung specimen. The secondary pulmonary lobule, a fundamental unit of the lung structure, reproduces the lung in miniature. The lung specimen is set in an acrylic cylindrical case of 36 mm diameter and 40 mm height. A field of view (FOV) of the micro-CT is 40.6 mm wide × 15.1 mm high with 3.07 μm pixel size using offset CT scanning for enlargement of the FOV. We constructed a 13,220 × 13,220 × 4912 voxel image with 3.07 μm isotropic voxel size for three-dimensional visualization of the whole secondary pulmonary lobule. Furthermore, synchrotron radiation has proved to be a powerful high-resolution imaging tool. This micro-CT system using a single-lens reflex camera and synchrotron radiation provides practical benefits of high-resolution and wide-field performance, but at low cost.
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Affiliation(s)
- Keiji Umetani
- Spectroscopy and Imaging Division, Japan Synchrotron Radiation Research Institute, 1-1-1 Kouto, Sayo-cho, Sayo-gun, 679-5198, Hyogo, Japan
| | - Toshihiro Okamoto
- Department of Thoracic and Cardiovascular Surgery, Cleveland Clinic, Cleveland, OH, USA
| | - Kurumi Saito
- Department of Optical Science and Technology, Faculty of Engineering, Tokushima University, Tokushima, Japan
| | - Yoshiki Kawata
- Department of Optical Science and Technology, Faculty of Engineering, Tokushima University, Tokushima, Japan
| | - Noboru Niki
- Department of Optical Science and Technology, Faculty of Engineering, Tokushima University, Tokushima, Japan
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44
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Zhang H, Jiang XJ, Liu XH, Ma H, Zhang YH, Rao Y, Li L, Xu HY, Lyu FJ. Chest computed tomography (CT) findings and semiquantitative scoring of 60 patients with coronavirus disease 2019 (COVID-19): A retrospective imaging analysis combining anatomy and pathology. PLoS One 2020; 15:e0238760. [PMID: 32886711 PMCID: PMC7473568 DOI: 10.1371/journal.pone.0238760] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 08/22/2020] [Indexed: 12/24/2022] Open
Abstract
In this study, we ascertained the chest CT data of 60 patients admitted to 3 hospitals in Chongqing with confirmed COVID-19. We conducted anatomical and pathological analyses to elucidate the possible reasons for the distribution, morphology, and characteristics of COVID-19 in chest CT. We also shared a semiquantitative scoring of affected lung segments, which was recommended by our local medical association. This scoring system was applied to quantify the severity of the disease. The most frequent imaging findings of COVID-19 were subpleural ground glass opacities and consolidation; there was a significant difference in semiquantitative scores between the early, progressive, and severe stages of the disease. We conclude that the chest CT findings of COVID-19 showed certain characteristics because of the anatomical features of the human body and pathological changes caused by the virus. Therefore, chest CT is a valuable tool for facilitating the diagnosis of COVID-19 and semiquantitative scoring of affected lung segments may further elucidate diagnosis and assessment of disease severity. This will assist healthcare workers in diagnosing COVID-19 and assessing disease severity, facilitate the selection of appropriate treatment options, which is important for reducing the spread of the virus, saving lives, and controlling the pandemic.
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Affiliation(s)
- Hao Zhang
- Department of Radiology, Dianjiang People’s Hospital of Chongqing, Chongqing, China
| | - Xu-jing Jiang
- Department of General Surgery, Dianjiang People’s Hospital of Chongqing, Chongqing, China
| | - Xiao-hua Liu
- Department of Radiology, Dianjiang People’s Hospital of Chongqing, Chongqing, China
| | - Hong Ma
- Department of Oncology, Dianjiang People’s Hospital of Chongqing, Chongqing, China
| | - Ya-hong Zhang
- Department of Radiology, Changshou People’s Hospital of Chongqing, Chongqing, China
| | - Yue Rao
- Department of Radiology, Zhongxian People’s Hospital of Chongqing, Chongqing, China
| | - Lin Li
- Department of Pharmacy, Dianjiang People’s Hospital of Chongqing, Chongqing, China
| | - Hai-yan Xu
- Department of Gastroenterology, Dianjiang People’s Hospital of Chongqing, Chongqing, China
| | - Fa-jin Lyu
- Department of Radiology, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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45
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Guan CS, Yan S, Lv ZB, Sun L, Ma DQ, Zhang YS, Xie RM, Chen BD. CT imaging and pathological basis of linear shadow connecting pulmonary segmental artery to horizontal fissure. Medicine (Baltimore) 2020; 99:e21239. [PMID: 32702901 PMCID: PMC7373523 DOI: 10.1097/md.0000000000021239] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
To investigate the computed tomography (CT) imaging and pathological basis of the linear shadows connecting pulmonary segmental arteries to horizontal fissure (hereinafter referred to as "linear shadow") on thin-slice CT.Collect 127 clinical cases to analyze the display and morphology of linear shadows on the thin-slice CT and to measure their length, thickness, and angle. Collect 11 autopsy specimens of coal worker's pneumoconiosis to conduct an imaging and pathology basis control study for the linear shadows.There is no correlation between the linear shadow and gender, age, and smoking history. Linear shadows are observed in 54.33% of patients. 93.33% of those linear shadows are straight lines. Generally, the lengths are less than 10 mm, the thicknesses are around 1 mm, and the scopes of angles are wide, range from acute angles to obtuse angles. The linear shadow is a banded structure consisting of loose connective tissue, small blood vessels, and small lymphatic vessels due to the visceral pleura recessed and fused into the lung.Linear shadows are intrinsic to the lung. The linear shadows consist of loose connective tissue, small blood vessels, and small lymphatic vessels.
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Affiliation(s)
| | | | | | - Lei Sun
- Department of Pathology, Beijing Ditan Hospital
| | - Da-Qing Ma
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University
| | - Yan-Song Zhang
- Department of Pathology, National Research Center for Occupational Safety and Health, Beijing, China
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46
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Yang Q, Liu Q, Xu H, Lu H, Liu S, Li H. Imaging of coronavirus disease 2019: A Chinese expert consensus statement. Eur J Radiol 2020; 127:109008. [PMID: 32335426 PMCID: PMC7165105 DOI: 10.1016/j.ejrad.2020.109008] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Revised: 04/07/2020] [Accepted: 04/08/2020] [Indexed: 01/08/2023]
Abstract
Coronavirus disease 2019 (COVID-19) is highly contagious, mainly causing inflammatory lesions in the lungs, and can also cause damage to the intestine and liver. The rapid spread of the virus that causes coronavirus disease 2019 (COVID-19) pneumonia has posed complex challenges to global public health. Early detection, isolation, diagnosis, and treatment are the most effective means of prevention and control. At present, the epidemic situation of new coronavirus infection has tended to be controlled in China, and it is still in a period of rapid rise in much of the world. The current gold standard for the diagnosis of COVID-19 is the detection of coronavirus nucleic acids, but imaging has an important role in the detection of lung lesions, stratification, evaluation of treatment strategies, and differentiation of mixed infections. This Chinese expert consensus statement summarizes the imaging features of COVID-19 pneumonia and may help radiologists across the world to understand this disease better.
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Affiliation(s)
- Qi Yang
- Department of Radiology, Beijing Chao Yang Hospital, Capital Medical University, Beijing, 100020, China
| | - Qiang Liu
- Department of Radiology, Shandong Medical Imaging Reaserch Institute, Shandong University, Jinan, 250021, China
| | - Haibo Xu
- Department of Radiology, Zhongnan Hospital, Wuhan University, Wuhan, 430071, China
| | - Hong Lu
- Department of Radiology, The Seventh People's Hospital, Chongqing, 400054, China
| | - Shiyuan Liu
- Department of Radiology, Changzheng Hospital, Second Military Medical University, Shanghai, 200003, China.
| | - Hongjun Li
- Department of Radiology, Beijing You'an Hospital, Capital Medical University, Beijing, 100069, China.
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Ambrosi F, Lissenberg-Witte B, Comans E, Sprengers R, Dickhoff C, Bahce I, Radonic T, Thunnissen E. Tumor Atelectasis Gives Rise to a Solid Appearance in Pulmonary Adenocarcinomas on High-Resolution Computed Tomography. JTO Clin Res Rep 2020; 1:100018. [PMID: 34589925 PMCID: PMC8474473 DOI: 10.1016/j.jtocrr.2020.100018] [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: 02/11/2020] [Accepted: 02/11/2020] [Indexed: 10/31/2022] Open
Abstract
Introduction Ground-glass opacities in a high-resolution computed tomography (HR-CT) scan correlate, if malignant, with adenocarcinoma in situ. The solid appearance in the HR-CT is often considered indicative of an invasive component. This study aims to compare the radiologic features revealed in the HR-CT and the histologic features of primary adenocarcinomas in resection specimens to find the presence of tumor atelectasis in ground-glass nodules (GGNs) and part-solid and solid nodules. Methods HR-CT imaging was evaluated, and lung nodules were classified as GGNs, part-solid nodules, and solid nodules, whereas adenocarcinomas were classified according to WHO classification. Lepidic growth pattern with collapse was considered if there was reduction of air in the histologic section with maintained pulmonary architecture (without signs of pleural or vascular invasion). Results Radiologic and histologic features were compared in 47 lesions of 41 patients. The number of GGN, part-solid, and solid nodules were two, eight, and 37, respectively. Lepidic growth pattern with collapse was observed in both GGN, seven of the eight part-solid (88%) and 24 of the 37 solid (65%) lesions. Remarkably, more than 50% of the adenocarcinomas with a solid appearance in HR-CT imaging had a preexisting pulmonary architecture with adenocarcinoma with a predominant lepidic growth pattern. In these cases, the solid component can be explained by tumor-related collapse in vivo (tumor atelectasis on radiologic examination). Conclusions Tumor atelectasis is a frequent finding in pulmonary adenocarcinomas and may beside a ground glass opacity also result in a solid appearance in HR-CT imaging. A solid appearance on HR-CT cannot be attributed to invasion alone, as has been the assumption until now.
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Affiliation(s)
- Francesca Ambrosi
- Experimental, Diagnostic, and Specialty Medicine Department, University of Bologna Medical Center, Bologna, Italy
| | - Birgit Lissenberg-Witte
- Department of Epidemiology and Biostatistics, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands
| | - Emile Comans
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands
| | - Ralf Sprengers
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands
| | - Chris Dickhoff
- Department of Surgery and Cardiothoracic Surgery, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands
| | - Idris Bahce
- Department of Pulmonology, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands
| | - Teodora Radonic
- Department of Pathology, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands
| | - Erik Thunnissen
- Department of Pathology, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands
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48
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Liszewski MC, Ciet P, Lee EY. Lung and Pleura. PEDIATRIC BODY MRI 2020. [PMCID: PMC7245516 DOI: 10.1007/978-3-030-31989-2_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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49
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Lai YK, Lindholm P, Guo HH. The Intralobular Gradient as Seen in Re-Expansion Pulmonary Edema. Radiol Cardiothorac Imaging 2019; 1:e190084. [PMID: 33778531 DOI: 10.1148/ryct.2019190084] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 07/24/2019] [Accepted: 08/05/2019] [Indexed: 11/11/2022]
Affiliation(s)
- Yu Kuang Lai
- Department of Medicine, Division of Pulmonary and Critical Care (Y.K.L.) and Department of Radiology and Thoracic Imaging (P.L., H.H.G.), Stanford University School of Medicine, 300 Pasteur Dr, Room S-074A, Stanford, CA 94305; and Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden (P.L.)
| | - Peter Lindholm
- Department of Medicine, Division of Pulmonary and Critical Care (Y.K.L.) and Department of Radiology and Thoracic Imaging (P.L., H.H.G.), Stanford University School of Medicine, 300 Pasteur Dr, Room S-074A, Stanford, CA 94305; and Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden (P.L.)
| | - Haiwei Henry Guo
- Department of Medicine, Division of Pulmonary and Critical Care (Y.K.L.) and Department of Radiology and Thoracic Imaging (P.L., H.H.G.), Stanford University School of Medicine, 300 Pasteur Dr, Room S-074A, Stanford, CA 94305; and Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden (P.L.)
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Thoracic computed tomographic interpretation for clinicians to aid in the diagnosis of dogs and cats with respiratory disease. Vet J 2019; 253:105388. [PMID: 31685132 DOI: 10.1016/j.tvjl.2019.105388] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Revised: 09/19/2019] [Accepted: 09/20/2019] [Indexed: 02/08/2023]
Abstract
In humans, high-resolution computed tomography (CT) is a key diagnostic modality for pulmonary disorders. Its success likely lies in excellent correlation of lung diseases with associated subgross anatomic changes, as assessed by histopathology, and because of a multidisciplinary approach between clinicians, radiologists and pathologists. Although thoracic CT studies have been performed in dogs and cats for nearly three decades, there is a lack of uniformity in both protocols for acquisition and in terminology used to describe lesions. Importantly, terms such as a bronchial, interstitial, and alveolar patterns are inappropriate descriptors for canine and feline thoracic CT imaging changes; instead, lung patterns should be classified as increased or decreased attenuation, nodular patterns, and linear patterns, with specific vocabulary to describe subtypes of lesions. In this manuscript, the authors provide an overview of basic CT principles, strategies to optimize and acquire high-quality diagnostic studies (inclusive of paired inspiratory and expiratory series, contrast and triphasic angiography) and provide a roadmap for systematic interpretation of thoracic CT images.
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