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Ohno Y, Ozawa Y, Nagata H, Ueda T, Yoshikawa T, Takenaka D, Koyama H. Lung Magnetic Resonance Imaging: Technical Advancements and Clinical Applications. Invest Radiol 2024; 59:38-52. [PMID: 37707840 DOI: 10.1097/rli.0000000000001017] [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: 09/15/2023]
Abstract
ABSTRACT Since lung magnetic resonance imaging (MRI) became clinically available, limited clinical utility has been suggested for applying MRI to lung diseases. Moreover, clinical applications of MRI for patients with lung diseases or thoracic oncology may vary from country to country due to clinical indications, type of health insurance, or number of MR units available. Because of this situation, members of the Fleischner Society and of the Japanese Society for Magnetic Resonance in Medicine have published new reports to provide appropriate clinical indications for lung MRI. This review article presents a brief history of lung MRI in terms of its technical aspects and major clinical indications, such as (1) what is currently available, (2) what is promising but requires further validation or evaluation, and (3) which developments warrant research-based evaluations in preclinical or patient studies. We hope this article will provide Investigative Radiology readers with further knowledge of the current status of lung MRI and will assist them with the application of appropriate protocols in routine clinical practice.
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Affiliation(s)
- Yoshiharu Ohno
- From the Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y. Ohno); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y. Ohno and H.N.); Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y. Ozawa and T.U.); Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi, Hyogo, Japan (T.Y., D.T.); and Department of Radiology, Advanced Diagnostic Medical Imaging, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (H.K.)
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Xu P, Meersmann T, Wang J, Wang C. Review of oxygen-enhanced lung mri: Pulse sequences for image acquisition and T 1 measurement. Med Phys 2023; 50:5987-6007. [PMID: 37345214 DOI: 10.1002/mp.16553] [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: 08/17/2021] [Revised: 03/23/2023] [Accepted: 05/16/2023] [Indexed: 06/23/2023] Open
Abstract
Oxygen-enhanced MR imaging (OE-MRI) is a special proton imaging technique that can be performed without modifying the scanner hardware. Many fundamental studies have been conducted following the initial reporting of this technique in 1996, illustrating the high potential for its clinical application. This review aims to summarise and analyse current pulse sequences and T1 measurement methods for OE-MRI, including fundamental theories, existing pulse sequences applied to OE-MRI acquisition and T1 mapping. Wash-in and wash-out time identify lung function and are sensitive to ventilation; thus, dynamic OE-MRI is also discussed in this review. We compare OE-MRI with the primary competitive technique, hyperpolarised gas MRI. Finally, an overview of lower-field applications of OE-MRI is highlighted, as relatively recent publications demonstrated positive results. Lower-field OE-MRI, which is lower than 1.5 T, could be an alternative modality for detecting lung diseases. This educational review is aimed at researchers who want a quick summary of the steps needed to perform pulmonary OE-MRI with a particular focus on sequence design, settings, and quantification methods.
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Affiliation(s)
- Pengfei Xu
- Department of Electrical and Electronic Engineering, Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo, China
| | - Thomas Meersmann
- Sir Peter Mansfield Magnetic Imaging Centre, University of Nottingham, Nottingham, UK
- Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, Ningbo, China
| | - Jing Wang
- Department of Electrical and Electronic Engineering, Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo, China
- Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, Ningbo, China
| | - Chengbo Wang
- Department of Electrical and Electronic Engineering, Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo, China
- Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, Ningbo, China
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Wieslander B, Seemann F, Javed A, Bruce CG, Ramasawmy R, Jaimes A, Lucas K, Frasier V, O'Brien KJ, Potersnak A, Khan JM, Schenke WH, Chen MY, Lederman RJ, Campbell-Washburn AE. Impact of Vasodilation on Oxygen-Enhanced Functional Lung MRI at 0.55 T. Invest Radiol 2023; 58:663-672. [PMID: 36822664 PMCID: PMC10947575 DOI: 10.1097/rli.0000000000000958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Abstract
BACKGROUND Oxygen-enhanced magnetic resonance imaging (OE-MRI) can be used to assess regional lung function without ionizing radiation. Inhaled oxygen acts as a T1-shortening contrast agent to increase signal in T1-weighted (T1w) images. However, increase in proton density from pulmonary hyperoxic vasodilation may also contribute to the measured signal enhancement. Our aim was to quantify the relative contributions of the T1-shortening and vasodilatory effects of oxygen to signal enhancement in OE-MRI in both swine and healthy volunteers. METHODS We imaged 14 anesthetized female swine (47 ± 8 kg) using a prototype 0.55 T high-performance MRI system while experimentally manipulating oxygenation and blood volume independently through oxygen titration, partial occlusion of the vena cava for volume reduction, and infusion of colloid fluid (6% hydroxyethyl starch) for volume increase. Ten healthy volunteers were imaged before, during, and after hyperoxia. Two proton density-weighted (PDw) and 2 T1w ultrashort echo time images were acquired per experimental state. The median PDw and T1w percent signal enhancement (PSE), compared with baseline room air, was calculated after image registration and correction for lung volume changes. Differences in median PSE were compared using Wilcoxon signed rank test. RESULTS The PSE in PDw images after 100% oxygen was similar in swine (1.66% ± 1.41%, P = 0.01) and in healthy volunteers (1.99% ± 1.79%, P = 0.02), indicating that oxygen-induced pulmonary vasodilation causes ~2% lung proton density increase. The PSE in T1w images after 100% oxygen was also similar (swine, 9.20% ± 1.68%, P < 0.001; healthy volunteers, 10.10% ± 3.05%, P < 0.001). The PSE in T1w enhancement was oxygen dose-dependent in anesthetized swine, and we measured a dose-dependent PDw image signal increase from infused fluids. CONCLUSIONS The contribution of oxygen-induced vasodilation to T1w OE-MRI signal was measurable using PDw imaging and was found to be ~2% in both anesthetized swine and in healthy volunteers. This finding may have implications for patients with regional or global hypoxia or vascular dysfunction undergoing OE-MRI and suggest that PDw imaging may be useful to account for oxygen-induced vasodilation in OE-MRI.
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Affiliation(s)
| | - Felicia Seemann
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Ahsan Javed
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Christopher G Bruce
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Rajiv Ramasawmy
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Andrea Jaimes
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Katherine Lucas
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Victoria Frasier
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Kendall J O'Brien
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Amanda Potersnak
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Jaffar M Khan
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - William H Schenke
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Marcus Y Chen
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Robert J Lederman
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Adrienne E Campbell-Washburn
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
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Tanaka Y, Ohno Y, Hanamatsu S, Obama Y, Ueda T, Ikeda H, Iwase A, Fukuba T, Hattori H, Murayama K, Yoshikawa T, Takenaka D, Koyama H, Toyama H. State-of-the-art MR Imaging for Thoracic Diseases. Magn Reson Med Sci 2021; 21:212-234. [PMID: 33952785 PMCID: PMC9199970 DOI: 10.2463/mrms.rev.2020-0184] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Since thoracic MR imaging was first used in a clinical setting, it has been suggested that MR imaging has limited clinical utility for thoracic diseases, especially lung diseases, in comparison with x-ray CT and positron emission tomography (PET)/CT. However, in many countries and states and for specific indications, MR imaging has recently become practicable. In addition, recently developed pulmonary MR imaging with ultra-short TE (UTE) and zero TE (ZTE) has enhanced the utility of MR imaging for thoracic diseases in routine clinical practice. Furthermore, MR imaging has been introduced as being capable of assessing pulmonary function. It should be borne in mind, however, that these applications have so far been academically and clinically used only for healthy volunteers, but not for patients with various pulmonary diseases in Japan or other countries. In 2020, the Fleischner Society published a new report, which provides consensus expert opinions regarding appropriate clinical indications of pulmonary MR imaging for not only oncologic but also pulmonary diseases. This review article presents a brief history of MR imaging for thoracic diseases regarding its technical aspects and major clinical indications in Japan 1) in terms of what is currently available, 2) promising but requiring further validation or evaluation, and 3) developments warranting research investigations in preclinical or patient studies. State-of-the-art MR imaging can non-invasively visualize lung structural and functional abnormalities without ionizing radiation and thus provide an alternative to CT. MR imaging is considered as a tool for providing unique information. Moreover, prospective, randomized, and multi-center trials should be conducted to directly compare MR imaging with conventional methods to determine whether the former has equal or superior clinical relevance. The results of these trials together with continued improvements are expected to update or modify recommendations for the use of MRI in near future.
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Affiliation(s)
- Yumi Tanaka
- Department of Radiology, Fujita Health University School of Medicine
| | - Yoshiharu Ohno
- Department of Radiology, Fujita Health University School of Medicine.,Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine
| | - Satomu Hanamatsu
- Department of Radiology, Fujita Health University School of Medicine
| | - Yuki Obama
- Department of Radiology, Fujita Health University School of Medicine
| | - Takahiro Ueda
- Department of Radiology, Fujita Health University School of Medicine
| | - Hirotaka Ikeda
- Department of Radiology, Fujita Health University School of Medicine
| | - Akiyoshi Iwase
- Department of Radiology, Fujita Health University Hospital
| | - Takashi Fukuba
- Department of Radiology, Fujita Health University Hospital
| | - Hidekazu Hattori
- Department of Radiology, Fujita Health University School of Medicine
| | - Kazuhiro Murayama
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine
| | | | | | | | - Hiroshi Toyama
- Department of Radiology, Fujita Health University School of Medicine
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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: 7.0] [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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Ohno Y, Hanamatsu S, Obama Y, Ueda T, Ikeda H, Hattori H, Murayama K, Toyama H. Overview of MRI for pulmonary functional imaging. Br J Radiol 2021; 95:20201053. [PMID: 33529053 DOI: 10.1259/bjr.20201053] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Morphological evaluation of the lung is important in the clinical evaluation of pulmonary diseases. However, the disease process, especially in its early phases, may primarily result in changes in pulmonary function without changing the pulmonary structure. In such cases, the traditional imaging approaches to pulmonary morphology may not provide sufficient insight into the underlying pathophysiology. Pulmonary imaging community has therefore tried to assess pulmonary diseases and functions utilizing not only nuclear medicine, but also CT and MR imaging with various technical approaches. In this review, we overview state-of-the art MR methods and the future direction of: (1) ventilation imaging, (2) perfusion imaging and (3) biomechanical evaluation for pulmonary functional imaging.
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Affiliation(s)
- Yoshiharu Ohno
- Department of Radiology, Fujita Health University, School of Medicine, Toyoake, Japan.,Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Japan
| | - Satomu Hanamatsu
- Department of Radiology, Fujita Health University, School of Medicine, Toyoake, Japan
| | - Yuki Obama
- Department of Radiology, Fujita Health University, School of Medicine, Toyoake, Japan
| | - Takahiro Ueda
- Department of Radiology, Fujita Health University, School of Medicine, Toyoake, Japan
| | - Hirotaka Ikeda
- Department of Radiology, Fujita Health University, School of Medicine, Toyoake, Japan
| | - Hidekazu Hattori
- Department of Radiology, Fujita Health University, School of Medicine, Toyoake, Japan
| | - Kazuhiro Murayama
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Japan
| | - Hiroshi Toyama
- Department of Radiology, Fujita Health University, School of Medicine, Toyoake, Japan
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Debray MP, Ghanem M, Khalil A, Taillé C. [Lung imaging in severe asthma]. Rev Mal Respir 2021; 38:41-57. [PMID: 33423858 DOI: 10.1016/j.rmr.2020.09.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 09/02/2020] [Indexed: 01/15/2023]
Abstract
INTRODUCTION Asthma is a common disease whose diagnosis does not typically rely on the results of imaging. However, chest CT has gained a key place over the last decade to support the management of patients with difficult to treat and severe asthma. STATE OF THE ART Bronchial wall thickening and mild dilatation or narrowing of bronchial lumen are frequently observed on chest CT in people with asthma. Bronchial wall thickening is correlated to the degree of obstruction and to bronchial wall remodeling and inflammation. Diverse conditions which can mimic asthma should be recognized on CT, including endobronchial tumours, interstitial pneumonias, bronchiectasis and bronchiolitis. Ground-glass opacities and consolidation may be related to transient eosinophilic infiltrates, infection or an associated disease (vasculitis, chronic eosinophilic pneumonia). Hyperdense mucous plugging is highly specific for allergic bronchopulmonary aspergillosis. PERSPECTIVES Airway morphometry, air trapping and quantitative analysis of ventilatory defects, with CT or MRI, can help to identify different morphological subgroups of patients with different functional or inflammatory characteristics. These imaging tools could emerge as new biomarkers for the evaluation of treatment response. CONCLUSION Chest CT is indicated in people with severe asthma to search for additional or alternative diagnoses. Quantitative imaging may contribute to phenotyping this patient group.
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Affiliation(s)
- M-P Debray
- Service de Radiologie, Assistance Publique-Hôpitaux de Paris, Hôpital Bichat, 46, rue Henri Huchard, 75018 Paris; Inserm UMR1152, France.
| | - M Ghanem
- Service de Pneumologie et Centre de Référence constitutif des Maladies Pulmonaires Rares, Assistance Publique-Hôpitaux de Paris, Hôpital Bichat, France
| | - A Khalil
- Service de Radiologie, Assistance Publique-Hôpitaux de Paris, Hôpital Bichat, 46, rue Henri Huchard, 75018 Paris; Université de Paris, Inserm UMR1152, France
| | - C Taillé
- Service de Pneumologie et Centre de Référence constitutif des Maladies Pulmonaires Rares, Assistance Publique-Hôpitaux de Paris, Hôpital Bichat, France; Département Hospitalo-Universitaire FIRE ; Université de Paris ; Inserm UMR 1152 ; LabEx Inflamex, 75018 Paris, France
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Ohno Y, Yui M, Yoshikawa T, Seki S, Takenaka D, Kassai Y, Hattori H, Murayama K, Toyama H. 3D Oxygen-Enhanced MRI at 3T MR System: Comparison With Thin-Section CT of Quantitative Capability for Pulmonary Functional Loss Assessment and Clinical Stage Classification of COPD in Smokers. J Magn Reson Imaging 2020; 53:1042-1051. [PMID: 33205499 DOI: 10.1002/jmri.27441] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Revised: 10/25/2020] [Accepted: 10/27/2020] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Oxygen (O2 )-enhanced MRI is mainly performed by a 2D sequence using 1.5T MR systems but trying to be obtained by a 3D sequence using a 3T MR system. PURPOSE To compare the capability of 3D O2 -enhanced MRI and that of thin-section computed tomography (CT) for pulmonary functional loss assessment and clinical stage classification of chronic obstructive pulmonary disease (COPD) in smokers. STUDY TYPE Prospective study. POPULATION Fifty six smokers were included. FIELD STRENGTH/ SEQUENCE 3T, 3D O2 -enhanced MRIs were performed with a 3D T1 -weighted fast field echo pulse sequence using the multiple flip angles. ASSESSMENTS Smokers were classified into four stages ("Without COPD," "Mild COPD," "Moderate COPD," "Severe or very severe COPD"). Maps of regional changes in T1 values were generated from O2 -enhanced MR data. Regions of interest (ROIs) were then placed over the lung on all slices and averaged to determine mean T1 value change (ΔT1 ). Quantitative CT used the percentage of low attenuation areas within the entire lung (LAA%). STATISTICAL TESTS ΔT1 and LAA% were correlated with pulmonary functional parameters, and compared for four stages using Tukey's Honestly Significant Difference test. Discrimination analyses were performed and McNemar's test was used for a comparison of the accuracy of the indexes. RESULTS There were significantly higher correlations between ΔT1 and pulmonary functional parameters (-0.83 ≤ r ≤ -0.71, P < 0.05) than between LAA% and the same pulmonary functional parameters (-0.76 ≤ r ≤ -0.69, P < 0.05). ΔT1 and LAA% of the "Mild COPD" and "Moderate COPD" groups were significantly different from those of the "Severe or Very Severe COPD" group (P < 0.05). Discriminatory accuracy of ΔT1 (62.5%) and ΔT1 with LAA% (67.9%) was significantly greater than that of LAA% (48.2%, P < 0.05). DATA CONCLUSION Compared with thin-section CT, 3D O2 -enhanced MRI has a similar capability for pulmonary functional assessment but better potential for clinical stage classification in smokers. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Yoshiharu Ohno
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Japan.,Joint Laboratory Research of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Japan.,Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Masao Yui
- Canon Medical Systems Corporation, Otawara, Japan
| | - Takeshi Yoshikawa
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan.,Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi, Japan
| | - Shinichiro Seki
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Daisuke Takenaka
- Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi, Japan
| | | | - Hidekazu Hattori
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Japan
| | - Kazuhiro Murayama
- Joint Laboratory Research of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Japan
| | - Hiroshi Toyama
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Japan
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Quantitative computed tomography measurement of cross-sectional area of small pulmonary vessels in asthmatic patients. Chin Med J (Engl) 2020; 132:1903-1908. [PMID: 31369430 PMCID: PMC6708698 DOI: 10.1097/cm9.0000000000000367] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Background: Cross-sectional area (CSA) for small pulmonary vessels is considered a parameter of pulmonary vessel alterations in patients with chronic obstructive pulmonary disease. This study was to evaluate the correlation of CSA with airflow obstruction parameters in asthma. Furthermore, we aimed to measure the difference in vascular alteration between asthma phenotypes and evaluate its relation with cytokine levels. Methods: We consecutively enrolled 20 adult asthmatic patients (13 women: age range, 26–80 years) and 20 healthy controls (8 women: age range, 23–61 years) from Peking University Third Hospital. Total CSA <5 mm2 (CSA<5) was measured with 64-slice spiral computed tomography, and the percentage CSA <5 for the lung area (%CSA<5) was calculated. Data were corrected for body surface area to obtain sixth-generation airway luminal diameter (LDcor), luminal area (Aicor), and airway wall thickness, and airway wall area percentage (WA%) was calculated. Enzyme-linked immunosorbent assay was used to detect the expression of leptin, total immunoglobulin E, periostin, and transforming growth factor β1 in serum and matrix metalloproteinase 9 in induced sputum supernatant of asthmatic patients. The differences in %CSA<5 between subgroups were assessed by independent samples Student's t test, and Spearman correlation analysis was used to analyze the correlation of %CSA<5 with clinical indexes and inflammatory cytokine levels. Results: Patients with asthma and controls did not differ in %CSA<5. In asthma patients, %CSA<5 was lower with initial onset age ≤12 years old, airflow restriction and uncontrolled Global Initiative for Asthma classification (all P < 0.05). Moreover, it was positively correlated with forced vital capacity ratio in 1 s (FEV1)/forced expiratory volume ratio, FEV1%, LDcor, Aicor, and serum leptin level (all P < 0.05) and negatively with total lung WA% (P = 0.007). Conclusions: %CSA<5 of pulmonary small vessels was well correlated with airflow limitation indexes and sixth-generation airway parameters. It has certain significance in predicting the clinical control of asthma.
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Zha W, Fain SB, Schiebler ML, Nagle SK, Liu F. Deep convolutional neural networks with multiplane consensus labeling for lung function quantification using UTE proton MRI. J Magn Reson Imaging 2019; 50:1169-1181. [PMID: 30945385 PMCID: PMC7039686 DOI: 10.1002/jmri.26734] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Revised: 03/15/2019] [Accepted: 03/15/2019] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Ultrashort echo time (UTE) proton MRI has gained popularity for assessing lung structure and function in pulmonary imaging; however, the development of rapid biomarker extraction and regional quantification has lagged behind due to labor-intensive lung segmentation. PURPOSE To evaluate a deep learning (DL) approach for automated lung segmentation to extract image-based biomarkers from functional lung imaging using 3D radial UTE oxygen-enhanced (OE) MRI. STUDY TYPE Retrospective study aimed to evaluate a technical development. POPULATION Forty-five human subjects, including 16 healthy volunteers, 5 asthma, and 24 patients with cystic fibrosis. FIELD STRENGTH/SEQUENCE 1.5T MRI, 3D radial UTE (TE = 0.08 msec) sequence. ASSESSMENT Two 3D radial UTE volumes were acquired sequentially under normoxic (21% O2 ) and hyperoxic (100% O2 ) conditions. Automated segmentation of the lungs using 2D convolutional encoder-decoder based DL method, and the subsequent functional quantification via adaptive K-means were compared with the results obtained from the reference method, supervised region growing. STATISTICAL TESTS Relative to the reference method, the performance of DL on volumetric quantification was assessed using Dice coefficient with 95% confidence interval (CI) for accuracy, two-sided Wilcoxon signed-rank test for computation time, and Bland-Altman analysis on the functional measure derived from the OE images. RESULTS The DL method produced strong agreement with supervised region growing for the right (Dice: 0.97; 95% CI = [0.96, 0.97]; P < 0.001) and left lungs (Dice: 0.96; 95% CI = [0.96, 0.97]; P < 0.001). The DL method averaged 46 seconds to generate the automatic segmentations in contrast to 1.93 hours using the reference method (P < 0.001). Bland-Altman analysis showed nonsignificant intermethod differences of volumetric (P ≥ 0.12) and functional measurements (P ≥ 0.34) in the left and right lungs. DATA CONCLUSION DL provides rapid, automated, and robust lung segmentation for quantification of regional lung function using UTE proton MRI. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1169-1181.
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Affiliation(s)
- Wei Zha
- Department of Medical Physics, University of Wisconsin-Madison
| | - Sean B. Fain
- Department of Medical Physics, University of Wisconsin-Madison
- Department of Radiology, University of Wisconsin-Madison
- Department of Biomedical Engineering, University of Wisconsin-Madison
| | | | - Scott K. Nagle
- Department of Medical Physics, University of Wisconsin-Madison
- Department of Radiology, University of Wisconsin-Madison
- Department of Pediatrics, University of Wisconsin-Madison
| | - Fang Liu
- Department of Radiology, University of Wisconsin-Madison
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Young HM, Eddy RL, Parraga G. MRI and CT lung biomarkers: Towards an in vivo understanding of lung biomechanics. Clin Biomech (Bristol, Avon) 2019; 66:107-122. [PMID: 29037603 DOI: 10.1016/j.clinbiomech.2017.09.016] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2017] [Revised: 09/22/2017] [Accepted: 09/27/2017] [Indexed: 02/07/2023]
Abstract
BACKGROUND The biomechanical properties of the lung are necessarily dependent on its structure and function, both of which are complex and change over time and space. This makes in vivo evaluation of lung biomechanics and a deep understanding of lung biomarkers, very challenging. In patients and animal models of lung disease, in vivo evaluations of lung structure and function are typically made at the mouth and include spirometry, multiple-breath gas washout tests and the forced oscillation technique. These techniques, and the biomarkers they provide, incorporate the properties of the whole organ system including the parenchyma, large and small airways, mouth, diaphragm and intercostal muscles. Unfortunately, these well-established measurements mask regional differences, limiting their ability to probe the lung's gross and micro-biomechanical properties which vary widely throughout the organ and its subcompartments. Pulmonary imaging has the advantage in providing regional, non-invasive measurements of healthy and diseased lung, in vivo. Here we summarize well-established and emerging lung imaging tools and biomarkers and how they may be used to generate lung biomechanical measurements. METHODS We review well-established and emerging lung anatomical, microstructural and functional imaging biomarkers generated using synchrotron x-ray tomographic-microscopy (SRXTM), micro-x-ray computed-tomography (micro-CT), clinical CT as well as magnetic resonance imaging (MRI). FINDINGS Pulmonary imaging provides measurements of lung structure, function and biomechanics with high spatial and temporal resolution. Imaging biomarkers that reflect the biomechanical properties of the lung are now being validated to provide a deeper understanding of the lung that cannot be achieved using measurements made at the mouth.
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Affiliation(s)
- Heather M Young
- Robarts Research Institute, Western University, London, Canada; Department of Medical Biophysics, Western University, London, Canada
| | - Rachel L Eddy
- Robarts Research Institute, Western University, London, Canada; Department of Medical Biophysics, Western University, London, Canada
| | - Grace Parraga
- Robarts Research Institute, Western University, London, Canada; Department of Medical Biophysics, Western University, London, Canada; Graduate Program in Biomedical Engineering, Western University, London, Canada.
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12
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Torres L, Kammerman J, Hahn AD, Zha W, Nagle SK, Johnson K, Sandbo N, Meyer K, Schiebler M, Fain SB. "Structure-Function Imaging of Lung Disease Using Ultrashort Echo Time MRI". Acad Radiol 2019; 26:431-441. [PMID: 30658930 DOI: 10.1016/j.acra.2018.12.007] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2018] [Revised: 12/19/2018] [Accepted: 12/21/2018] [Indexed: 12/14/2022]
Abstract
RATIONALE AND OBJECTIVES The purpose of this review is to acquaint the reader with recent advances in ultrashort echo time (UTE) magnetic resonance imaging (MRI) of the lung and its implications for pulmonary MRI when used in conjunction with functional MRI technique. MATERIALS AND METHODS We provide an overview of recent technical advances of UTE and explore the advantages of combined structure-function pulmonary imaging in the context of restrictive and obstructive pulmonary diseases such as idiopathic pulmonary fibrosis (IPF) and cystic fibrosis (CF). RESULTS UTE MRI clearly shows the lung parenchymal changes due to IPF and CF. The use of UTE MRI, in conjunction with established functional lung MRI in chronic lung diseases, will serve to mitigate the need for computed tomography in children. CONCLUSION Current limitations of UTE MRI include long scan times, poor delineation of thin-walled structures (e.g. cysts and reticulation) due to limited spatial resolution, low signal to noise ratio, and imperfect motion compensation. Despite these limitations, UTE MRI can now be considered as an alternative to multidetector computed tomography for the longitudinal follow-up of the morphological changes from lung diseases in neonates, children, and young adults, particularly as a complement to the unique functional capabilities of MRI.
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Abstract
PURPOSE OF REVIEW The present review aims to summarize the most recent evidence related to imaging and severe asthma, both with regard to advances in imaging research and to their current and potential clinical implications. RECENT FINDINGS Recent work in imaging in severe asthma has principally been using computed tomography (CT) and MRI, as well as the integration of the two. Some of the most notable findings include the use of CT imaging biomarkers to create unique clusters of asthmatics, and the use of co-registration to link CT images of airways with regional variation in ventilation in MRI. In addition, temporal studies have shown that some the ventilation defects found using MRI in asthmatics are intermittent and others are persistent, but both are associated with lower lung function. SUMMARY The role of imaging in severe asthma currently is primarily in the exclusion of comorbid or other conditions, or in the assessment for complications in the setting of acute decompensation. A rapidly expanding body of literature using CT and MRI suggests that these tools may soon be of utility in the chronic management of the disease.
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Comparison of Xenon-Enhanced Area-Detector CT and Krypton Ventilation SPECT/CT for Assessment of Pulmonary Functional Loss and Disease Severity in Smokers. AJR Am J Roentgenol 2017; 210:W45-W53. [PMID: 29220212 DOI: 10.2214/ajr.17.18709] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
OBJECTIVE The objective of this study was to compare the capability of xenon-enhanced area-detector CT (ADCT) performed with a subtraction technique and coregistered 81mKr-ventilation SPECT/CT for the assessment of pulmonary functional loss and disease severity in smokers. SUBJECTS AND METHODS Forty-six consecutive smokers (32 men and 14 women; mean age, 67.0 years) underwent prospective unenhanced and xenon-enhanced ADCT, 81mKr-ventilation SPECT/CT, and pulmonary function tests. Disease severity was evaluated according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification. CT-based functional lung volume (FLV), the percentage of wall area to total airway area (WA%), and ventilated FLV on xenon-enhanced ADCT and SPECT/CT were calculated for each smoker. All indexes were correlated with percentage of forced expiratory volume in 1 second (%FEV1) using step-wise regression analyses, and univariate and multivariate logistic regression analyses were performed. In addition, the diagnostic accuracy of the proposed model was compared with that of each radiologic index by means of McNemar analysis. RESULTS Multivariate logistic regression showed that %FEV1 was significantly affected (r = 0.77, r2 = 0.59) by two factors: the first factor, ventilated FLV on xenon-enhanced ADCT (p < 0.0001); and the second factor, WA% (p = 0.004). Univariate logistic regression analyses indicated that all indexes significantly affected GOLD classification (p < 0.05). Multivariate logistic regression analyses revealed that ventilated FLV on xenon-enhanced ADCT and CT-based FLV significantly influenced GOLD classification (p < 0.0001). The diagnostic accuracy of the proposed model was significantly higher than that of ventilated FLV on SPECT/CT (p = 0.03) and WA% (p = 0.008). CONCLUSION Xenon-enhanced ADCT is more effective than 81mKr-ventilation SPECT/CT for the assessment of pulmonary functional loss and disease severity.
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Zha W, Kruger SJ, Johnson KM, Cadman RV, Bell LC, Liu F, Hahn AD, Evans MD, Nagle SK, Fain SB. Pulmonary ventilation imaging in asthma and cystic fibrosis using oxygen-enhanced 3D radial ultrashort echo time MRI. J Magn Reson Imaging 2017; 47:1287-1297. [PMID: 29086454 DOI: 10.1002/jmri.25877] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2017] [Accepted: 10/10/2017] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND A previous study demonstrated the feasibility of using 3D radial ultrashort echo time (UTE) oxygen-enhanced MRI (UTE OE-MRI) for functional imaging of healthy human lungs. The repeatability of quantitative measures from UTE OE-MRI needs to be established prior to its application in clinical research. PURPOSE To evaluate repeatability of obstructive patterns in asthma and cystic fibrosis (CF) with UTE OE-MRI with isotropic spatial resolution and full chest coverage. STUDY TYPE Volunteer and patient repeatability. POPULATION Eighteen human subjects (five asthma, six CF, and seven normal subjects). FIELD STRENGTH/SEQUENCE Respiratory-gated free-breathing 3D radial UTE (80 μs) sequence at 1.5T. ASSESSMENT Two 3D radial UTE volumes were acquired sequentially under normoxic and hyperoxic conditions. A subset of subjects underwent repeat acquisitions on either the same day or ≤15 days apart. Asthma and CF subjects also underwent spirometry. A workflow including deformable registration and retrospective lung density correction was used to compute 3D isotropic percent signal enhancement (PSE) maps. Median PSE (MPSE) and ventilation defect percent (VDP) of the lung were measured from the PSE map. STATISTICAL TESTS The relations between MPSE, VDP, and spirometric measures were assessed using Spearman correlations. The test-retest repeatability was evaluated using Bland-Altman analysis and intraclass correlation coefficients (ICC). RESULTS Ventilation measures in normal subjects (MPSE = 8.0%, VDP = 3.3%) were significantly different from those in asthma (MPSE = 6.0%, P = 0.042; VDP = 21.7%, P = 0.018) and CF group (MPSE = 4.5%, P = 0.0006; VDP = 27.2%, P = 0.002). MPSE correlated significantly with forced expiratory lung volume in 1 second percent predicted (ρ = 0.72, P = 0.017). The ICC of the test-retest VDP and MPSE were both ≥0.90. In all subject groups, an anterior/posterior gradient was observed with higher MPSE and lower VDP in the posterior compared to anterior regions (P ≤ 0.0021 for all comparisons). DATA CONCLUSION 3D radial UTE OE-MRI supports quantitative differentiation of diseased vs. healthy lungs using either whole lung VDP or MPSE with excellent test-retest repeatability. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:1287-1297.
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Affiliation(s)
- Wei Zha
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Stanley J Kruger
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Kevin M Johnson
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Robert V Cadman
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Laura C Bell
- Division of Imaging Research, Barrow Neurological Institute, Phoenix, Arizona, USA
| | - Fang Liu
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Andrew D Hahn
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Michael D Evans
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Scott K Nagle
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Pediatrics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Sean B Fain
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
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DeBoer EM, Spielberg DR, Brody AS. Clinical potential for imaging in patients with asthma and other lung disorders. J Allergy Clin Immunol 2016; 139:21-28. [PMID: 27871877 DOI: 10.1016/j.jaci.2016.11.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2016] [Revised: 11/10/2016] [Accepted: 11/10/2016] [Indexed: 12/12/2022]
Abstract
The ability of lung imaging to phenotype patients, determine prognosis, and predict response to treatment is expanding in clinical and translational research. The purpose of this perspective is to describe current imaging modalities that might be useful clinical tools in patients with asthma and other lung disorders and to explore some of the new developments in imaging modalities of the lung. These imaging modalities include chest radiography, computed tomography, lung magnetic resonance imaging, electrical impedance tomography, bronchoscopy, and others.
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Affiliation(s)
- Emily M DeBoer
- University of Colorado Anschutz Medical Campus, Department of Pediatrics, and Breathing Institute, Children's Hospital Colorado, Aurora, Colo.
| | - David R Spielberg
- Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | - Alan S Brody
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
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Balbinot F, da Costa Batista Guedes Á, Nascimento DZ, Zampieri JF, Alves GRT, Marchiori E, Rubin AS, Hochhegger B. Advances in Imaging and Automated Quantification of Pulmonary Diseases in Non-neoplastic Diseases. Lung 2016; 194:871-879. [PMID: 27663257 DOI: 10.1007/s00408-016-9940-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2016] [Accepted: 09/03/2016] [Indexed: 10/21/2022]
Abstract
Histological examination has always been the gold standard for the detection and quantification of lung remodeling. However, this method has some limitations regarding the invasiveness of tissue acquisition. Quantitative imaging methods enable the acquisition of valuable information on lung structure and function without the removal of tissue from the body; thus, they are useful for disease identification and follow-up. This article reviews the various quantitative imaging modalities used currently for the non-invasive study of chronic obstructive pulmonary disease, asthma, and interstitial lung diseases. Some promising computer-aided diagnosis methods are also described.
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Affiliation(s)
- Fernanda Balbinot
- Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil. .,, Rua Coronel Vicente, 451, Centro, Porto Alegre, RS, 90030041, Brazil. .,Irmandade Santa Casa de Misericórdia de Porto Alegre, LABIMED - Laboratório de Pesquisas em Imagens Médicas, Rua Prof. Annes Dias, 28, Centro, Porto Alegre, RS, 90020090, Brazil.
| | - Álvaro da Costa Batista Guedes
- Irmandade Santa Casa de Misericórdia de Porto Alegre, LABIMED - Laboratório de Pesquisas em Imagens Médicas, Rua Prof. Annes Dias, 28, Centro, Porto Alegre, RS, 90020090, Brazil
| | - Douglas Zaione Nascimento
- Irmandade Santa Casa de Misericórdia de Porto Alegre, LABIMED - Laboratório de Pesquisas em Imagens Médicas, Rua Prof. Annes Dias, 28, Centro, Porto Alegre, RS, 90020090, Brazil
| | - Juliana Fischman Zampieri
- Irmandade Santa Casa de Misericórdia de Porto Alegre, LABIMED - Laboratório de Pesquisas em Imagens Médicas, Rua Prof. Annes Dias, 28, Centro, Porto Alegre, RS, 90020090, Brazil
| | | | - Edson Marchiori
- Federal University of Rio de Janeiro, Rua Thomaz Cameron, 43, Valparaíso, Petrópolis, RJ, 25685120, Brazil
| | - Adalberto Sperb Rubin
- Irmandade Santa Casa de Misericórdia de Porto Alegre, LABIMED - Laboratório de Pesquisas em Imagens Médicas, Rua Prof. Annes Dias, 28, Centro, Porto Alegre, RS, 90020090, Brazil
| | - Bruno Hochhegger
- Irmandade Santa Casa de Misericórdia de Porto Alegre, LABIMED - Laboratório de Pesquisas em Imagens Médicas, Rua Prof. Annes Dias, 28, Centro, Porto Alegre, RS, 90020090, Brazil
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Kruger SJ, Nagle SK, Couch MJ, Ohno Y, Albert M, Fain SB. Functional imaging of the lungs with gas agents. J Magn Reson Imaging 2016; 43:295-315. [PMID: 26218920 PMCID: PMC4733870 DOI: 10.1002/jmri.25002] [Citation(s) in RCA: 82] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2015] [Accepted: 06/26/2015] [Indexed: 12/22/2022] Open
Abstract
This review focuses on the state-of-the-art of the three major classes of gas contrast agents used in magnetic resonance imaging (MRI)-hyperpolarized (HP) gas, molecular oxygen, and fluorinated gas--and their application to clinical pulmonary research. During the past several years there has been accelerated development of pulmonary MRI. This has been driven in part by concerns regarding ionizing radiation using multidetector computed tomography (CT). However, MRI also offers capabilities for fast multispectral and functional imaging using gas agents that are not technically feasible with CT. Recent improvements in gradient performance and radial acquisition methods using ultrashort echo time (UTE) have contributed to advances in these functional pulmonary MRI techniques. The relative strengths and weaknesses of the main functional imaging methods and gas agents are compared and applications to measures of ventilation, diffusion, and gas exchange are presented. Functional lung MRI methods using these gas agents are improving our understanding of a wide range of chronic lung diseases, including chronic obstructive pulmonary disease, asthma, and cystic fibrosis in both adults and children.
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Affiliation(s)
- Stanley J. Kruger
- Department of Medical Physics, University of Wisconsin – Madison, WI, U.S.A
| | - Scott K. Nagle
- Department of Medical Physics, University of Wisconsin – Madison, WI, U.S.A
- Department of Radiology, University of Wisconsin – Madison, WI, U.S.A
- Department of Pediatrics, University of Wisconsin – Madison, WI, U.S.A
| | - Marcus J. Couch
- Thunder Bay Regional Research Institute, Thunder Bay, ON, Canada
- Biotechnology Program, Lakehead University, Thunder Bay, ON, Canada
| | - Yoshiharu Ohno
- Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Mitchell Albert
- Thunder Bay Regional Research Institute, Thunder Bay, ON, Canada
- Department of Chemistry, Lakehead University, Thunder Bay, ON, Canada
| | - Sean B. Fain
- Department of Medical Physics, University of Wisconsin – Madison, WI, U.S.A
- Department of Radiology, University of Wisconsin – Madison, WI, U.S.A
- Department of Biomedical Engineering, University of Wisconsin – Madison, WI, U.S.A
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