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• W3048683996 abstract "HomeRadiologyVol. 297, No. 1 PreviousNext Reviews and CommentaryFree AccessEditorialHyperpolarized Noble Gas Ventilation MRI in COPDMark L. Schiebler , Sean FainMark L. Schiebler , Sean FainAuthor AffiliationsFrom the Departments of Radiology (M.L.S.) and Medical Physics (S.F.), School of Medicine and Public Health, University of Wisconsin–Madison, 600 Highland Ave, Madison, WI 53792.Address correspondence to M.L.S. (e-mail: [email protected]).Mark L. Schiebler Sean FainPublished Online:Aug 11 2020https://doi.org/10.1148/radiol.2020202855MoreSectionsPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In AbstractOnline supplemental material is available for this article.See also the article by Tafti et al in this issue.Dr Schiebler is a professor of cardiothoracic imaging in the Department of Radiology at the University of Wisconsin-Madison. His research interests are small-airways diseases and coronary artery diseases and how imaging biomarkers and computational fluid dynamics can be used for more cost-effective patient outcomes. He is a member of the Fleischner Society, STR, ISMRM, RSNA, and SMRA and is the past chairman of the board of the International Workshop for Pulmonary Functional Imaging. He also serves as the deputy editor of thoracic imaging for Radiology.Download as PowerPointOpen in Image Viewer Dr Fain is a professor of medical physics, radiology, and biomedical engineering and directs the Pulmonary and Metabolic Imaging Center in the Departments of Radiology and Medical Physics at the School of Medicine and Public Health, University of Wisconsin, Madison. His research develops quantitative imaging methods using MRI and CT, including perfusion, blood oxygen level–dependent, hyperpolarized gas (eg. 3He, 129Xe) and 13C MRI to measure lung ventilation and metabolism. He is physics chair of the CT Lung Density Biomarker Committee of QIBA and is working with the COPD Foundation on quantitative CT imaging biomarkers of airway remodeling and parenchymal density to improve phenotyping of obstructive lung disease.Download as PowerPointOpen in Image Viewer Chronic obstructive pulmonary disease (COPD) is an important cause of death (1). Recently, the Global Burden of Disease Chronic Respiratory Disease Collaborators performed a systematic analysis for the burden of COPD in the world and estimated that 3.2 million people died of COPD in 2015 (2). Almost all of this disease is secondary to cigarette smoking and is preventable by simply never starting to smoke. The additional role of air pollution, occupational dust exposure, hut lung, smoking nontobacco products, and vaping products containing nicotine or marijuana derivatives in the development of COPD remains unknown (3). In this editorial, we discuss the pathology and functional imaging metrics of COPD using hyperpolarized noble gas ventilation MRI, CT, and CT augmented by artificial intelligence for the regional assessment of disease and how this compares with traditional pulmonary function tests (PFTs). Determination of the regional involvement of COPD is important because treatment (eg, endobronchial valves and lung volume reduction surgery) depends on knowing the lobar and sublobar distribution of emphysema.A major factor in the loss of lung function and decreased survival in patients with COPD is emphysema (4). Emphysema results from the loss of alveolar tissue due to chronic inflammation and injury that leads to dysregulation of neutrophil elastase. This dysregulation degrades and destroys the alveoli responsible for gas exchange in the lungs, thus imparting both decreased efficiency due to decreased tissue surface area for gas exchange and impaired mechanical airway–parenchymal coupling that contributes to airway collapse leading to air trapping.Recently, the Multiethnic Study of Atherosclerosis (known as MESA) lung study investigators have shown that individuals with a smaller-than-expected airway tree (dysanapsis) are more likely to develop COPD (5). They found that when those in the lowest quartile of airway-to-lung ratio were compared with participants in the highest quartile, those in the lowest quartile had significantly more COPD (9.8 vs 1.2 cases per 1000 person-years). The rate difference between these two quartiles was 8.6 cases per 1000 person-years (95% confidence interval: 7.1, 9.2; P < .001). This important result points to a probable cause for COPD and why some smokers get COPD and some do not.Multiple methods have been developed to attempt to quantify the pathophysiology of COPD due to airway remodeling and emphysema. These methods include CT lung densitometry using thresholding on the Hounsfield unit and global PFTs. Clinical tests for determining the presence of COPD are PFTs and the diffusion capacity of the lung for carbon monoxide (DLco). Carbon monoxide is a proxy for the diffusion of oxygen (O2) into the plasma and measures the ability of the ventilated lung to diffuse carbon monoxide across the tissue-capillary interfaces of the alveoli into the red blood cells. The DLco is of primary interest in COPD as a means to approximate the surface area of functional lung tissue to alveolar volume. This is measured by testing the difference in the partial pressure of carbon monoxide between inspiration and expiration. After diffusion to the blood, carbon monoxide is irreversibly bound to the hemoglobin molecule. Thomas Graham was the first to publish the formula (Graham law) for the rate at which gases diffuse (Appendix E1 [online]). The formula shows that larger gas molecules have slower rates of diffusion.Only a few imaging methods have explored the gas airspace directly as a means to evaluate changes due to emphysema and air trapping in COPD. This is because the gas itself is difficult to visualize and its physical diffusion in the airspaces is difficult to measure. In one of the more interesting experiments for lung tissue characterization, Saam et al (6) and Yablonskiy et al (7) showed that the diffusion of the hyperpolarized helium 3 isotope (3He) could be used in conjunction with diffusion-encoded MRI to study lung microstructure at the alveolar level and estimate the mean size of lung alveoli in an imaging voxel. Yablonskiy et al showed that gas diffusion perpendicular to the terminal bronchiole and acinar airways can be approximated by using the mathematical boundary conditions for the transverse diffusion in open tubes. They used their diffusion formulas to determine the mean airway radius from in vivo hyperpolarized noble gas MRI ventilation in humans. The mean airway radius with this method ranged from 0.35 to 0.38 mm in healthy participants and from 0.44 to 0.79 mm in patients with emphysema (7).In this issue of Radiology, Tafti et al (8) explore the link between standard measures of COPD (eg, PFTs, DLco), lung CT attenuation coefficients (in Hounsfield units), and the apparent diffusion coefficients (ADCs) of diffusion-encoded hyperpolarized 3He MRI and xenon129 (129Xe) MRI. 129Xe is more abundant than 3He and recent advances have made it more suitable for nuclear polarization (9). All imaging tests were performed in the supine position, but PFTs and DLco were performed in the upright position. It is well known that the gravity dependence of the lung tissues affects lung expansion, which leads to differing physiology between the laboratory tests for COPD and imaging. Most CT imaging for clinical use is performed at total lung capacity (the volume of gas at maximum inspiration) and sometimes at residual volume (volume of gas at maximal expiration). To better compare MRI with CT lung density, one of the distinguishing features of this study is the use of 1 L of breath above functional residual capacity as an imaging standard for lung inflation (the normal end of passive expiration for their CT scans). Given the training of artificial intelligence algorithms at 1 L above functional residual capacity, this could become the new standard for lung imaging.Tafti et al visually show that the severity of air trapping on CT can be inferred from the hyperpolarized Xe and He ventilation MRI data, and these data correlate reasonably well with the corresponding PFTs (Figure). They also show that their ADC-based emphysema index had outstanding repeatability (intraclass correlation coefficient >0.99) and was strongly correlated with quantitative CT (r = 0.86 for 3He, r = 0.85 for 129Xe), with high AUC (AUC = 0.93). ADC emphysema indexes were also correlated with DLco (r = −0.81, P < .001; r = −0.80, P < .001) and percentage predicted residual volume divided by total lung capacity (r = 0.65, P < .001; r = 0.61, P < .001). These findings should be useful for further investigations of the primary use of CT in patients with COPD, with confirmation of lung function using hyperpolarized gas MRI ventilation methods.Modified Figure 3 from Miller et al (8) (reproduced with permission) shows more rapid diffusion (apparent diffusion coefficient [ADC]) compared with that in areas of emphysema with hyperpolarized helium (arrow in H and I) versus xenon (arrow in K and L). From left to right, imaging examinations of the three patients are shown: CT, CT with density thresholding highlighted (red is less than −910 HU and yellow is less than −950 HU). In the last two panels, the third panel shows the ADC map overlay on the CT image from the same patient, with higher (yellow) and lower (red) diffusivity values. Black indicates regions of the lung with too low a signal-to-noise ratio (ie, lung that does not have many hyperpolarized molecules) to be analyzed, suggesting low ventilation. Helium diffuses much more quickly than xenon, and the ADC values reflect this physical reality, with the ADC for helium substantially higher (range, 0.2–0.88 cm2/sec) than the ADC for xenon (range, 0.02–0.14 cm2/sec). Imagine the subject breathing in the hyperpolarized gas with that 1 L of gas mix with the existing air in the bronchi and then it slowly physically diffusing out into the alveoli over the several milliseconds of the diffusion MRI measurement. Because of the aforementioned differences in gas diffusivity, helium is able to diffuse into areas where xenon has not had sufficient time to reach. Xenon is a larger molecule and therefore diffuses more slowly than helium. However, this also reveals a limitation of the hyperpolarized gas MRI techniques, in that poorly ventilated emphysematous lung may not get much gas to diffuse into it over the time of the breath hold. Such unventilated regions cannot be evaluated, making areas of air trapping less likely to be detected with this method.Download as PowerPointOpen in Image Viewer Treatment of COPD has begun to move from global therapies to regional assessment of portions of the lung that are the most severely affected. Thus, accurate and reproducible imaging tests that can be used to identify the exact location of the diseased lung to target treatment are needed. Hyperpolarized noble gas MRI ventilation has shown utility in this regard. Moreover, there is the potential to use AI methods to combine data from MRI ventilation with CT airway and density data to create an idealized bronchial tree down to the 30th order of branching (10). By leveraging AI in combination with functional information from hyperpolarized gas data and the spatial anatomic resolution of CT, a comprehensive assessment of regional lung disease in the setting of COPD can be more readily achieved. CT will become an even stronger workhorse in regional assessment of air trapping.The ability of hyperpolarized gases to evaluate physical diffusion of gases within the lung airspaces is unique and reveals regions of pathophysiology due to emphysema. The use of ADCs of hyperpolarized noble gases for ventilation MRI may become a standard of reference in the evaluation of both airspace dimensions and ventilation in one examination. Moreover, pairing of these MRI ventilation data with chest CT could become a useful clinical standard to evaluate the regional distribution of emphysema in the context of targeted therapy approaches.Disclosures of Conflicts of Interest: M.L.S. Activities related to the present article: disclosed no relevant relationships. Activities not related to the present article: disclosed no relevant relationships. Other relationships: is a shareholder in Stemina Biomarker Discovery, X-Vac, and Healthmyne. S.B.F. Activities related to the present article: disclosed no relevant relationships. Activities not related to the present article: receives an honorarium for service on the scientific advisory board from Sanofi/Regeneron; is on the scientific advisory board of Polarean Imaging; institution receives equipment support from GE Healthcare. Other relationships: disclosed no relevant relationships.AcknowledgmentThe authors thank Dmitriy Yablonskiy, PhD, for his assistance with this editorial.References1. Bhatta L, Leivseth L, Mai XM, et al. GOLD Classifications, COPD Hospitalization, and All-Cause Mortality in Chronic Obstructive Pulmonary Disease: The HUNT Study. Int J Chron Obstruct Pulmon Dis 2020;15:225–233. Crossref, Medline, Google Scholar2. GBD 2015 Chronic Respiratory Disease Collaborators. Global, regional, and national deaths, prevalence, disability-adjusted life years, and years lived with disability for chronic obstructive pulmonary disease and asthma, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet Respir Med 2017;5(9):691–706. Medline, Google Scholar3. Gold JA, Jagirdar J, Hay JG, Addrizzo-Harris DJ, Naidich DP, Rom WN. Hut lung. A domestically acquired particulate lung disease. Medicine (Baltimore) 2000;79(5):310–317. Crossref, Medline, Google Scholar4. Washko GR, Dransfield MT, Estépar RS, et al. Airway wall attenuation: a biomarker of airway disease in subjects with COPD. J Appl Physiol (1985) 2009;107(1):185–191. Crossref, Medline, Google Scholar5. Smith BM, Kirby M, Hoffman EA, et al. Association of Dysanapsis With Chronic Obstructive Pulmonary Disease Among Older Adults. JAMA 2020;323(22):2268–2280. Crossref, Medline, Google Scholar6. Saam BT, Yablonskiy DA, Kodibagkar VD, et al. MR imaging of diffusion of (3) He gas in healthy and diseased lungs. Magn Reson Med 2000;44(2):174–179. Crossref, Medline, Google Scholar7. Yablonskiy DA, Sukstanskii AL, Woods JC, et al. Quantification of lung microstructure with hyperpolarized 3He diffusion MRI. J Appl Physiol (1985) 2009;107(4):1258–1265. Crossref, Medline, Google Scholar8. Tafti S, Garrison RJ, Mugler JP III, et al. Emphysema Index Based on Hyperpolarized 3He or 129Xe Diffusion MRI: Performance and Comparison with Quantitative CT and Pulmonary Function Tests. Radiology 2020;297:201–210. Link, Google Scholar9. Mugler JP III, Altes TA. Hyperpolarized 129Xe MRI of the human lung. J Magn Reson Imaging 2013;37(2):313–331. Crossref, Medline, Google Scholar10. Kim M, Doganay O, Matin TN, Povey T, Gleeson FV. CT-based Airway Flow Model to Assess Ventilation in Chronic Obstructive Pulmonary Disease: A Pilot Study. Radiology 2019;293(3):666–673. Link, Google ScholarArticle HistoryReceived: June 24 2020Revision requested: July 6 2020Revision received: July 20 2020Accepted: July 24 2020Published online: Aug 11 2020Published in print: Oct 2020 FiguresReferencesRelatedDetailsAccompanying This ArticleEmphysema Index Based on Hyperpolarized 3He or 129Xe Diffusion MRI: Performance and Comparison with Quantitative CT and Pulmonary Function TestsAug 11 2020RadiologyRecommended Articles Pulmonary Imaging Biomarkers of Gas Trapping and Emphysema in COPD: 3He MR Imaging and CT Parametric Response MapsRadiology2016Volume: 279Issue: 2pp. 597-608Emphysema Index Based on Hyperpolarized 3He or 129Xe Diffusion MRI: Performance and Comparison with Quantitative CT and Pulmonary Function TestsRadiology2020Volume: 297Issue: 1pp. 201-210Chronic Obstructive Pulmonary Disease: Lobar Analysis with Hyperpolarized 129Xe MR ImagingRadiology2016Volume: 282Issue: 3pp. 857-868Pulmonary Functional Imaging: Part 2—State-of-the-Art Clinical Applications and Opportunities for Improved Patient CareRadiology2021Volume: 299Issue: 3pp. 524-538Measuring Regional Pulmonary Function Using Noncontrast CT: More Reasons to Join the FAN BandwagonRadiology2020Volume: 298Issue: 1pp. 210-211See More RSNA Education Exhibits Air trapping in Diffuse Lung Diseases: An Imaging Approach to the Differential Diagnosis with Pathologic Correlation (Mechanisms and Imaging Clues)Digital Posters2022Beyond Pulmonary Embolism (PE): A Pictorial Review of the Mimickers of PE and Incidental Findings on Ventilation/Perfusion (V/Q) ScintigraphyDigital Posters2019Apneic Ventilation Strategies to Limit Respiratory Motion During Percutaneous AblationDigital Posters2019 RSNA Case Collection Hepatic SteatosisRSNA Case Collection2021Congenital lobar overinflationRSNA Case Collection2021Bronchial AtresiaRSNA Case Collection2020 Vol. 297, No. 1 Supplemental MaterialMetrics Altmetric Score PDF download" @default.
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