1
|
Peggs ZJ, Brooke JP, Bolton CE, Hall IP, Francis ST, Gowland PA. Free-Breathing Functional Pulmonary Proton MRI: A Novel Approach Using Voxel-Wise Lung Ventilation (VOLVE) Assessment in Healthy Volunteers and Patients With Chronic Obstructive Pulmonary Disease. J Magn Reson Imaging 2025; 61:663-675. [PMID: 38819593 PMCID: PMC11706312 DOI: 10.1002/jmri.29444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 04/27/2024] [Accepted: 04/30/2024] [Indexed: 06/01/2024] Open
Abstract
BACKGROUND In respiratory medicine, there is a need for sensitive measures of regional lung function that can be performed using standard imaging technology, without the need for inhaled or intravenous contrast agents. PURPOSE To describe VOxel-wise Lung VEntilation (VOLVE), a new method for quantifying regional lung ventilation (V) and perfusion (Q) using free-breathing proton MRI, and to evaluate VOLVE in healthy never-smokers, healthy people with smoking history, and people with chronic obstructive pulmonary disease (COPD). STUDY TYPE Prospective pilot. POPULATION Twelve healthy never-smoker participants (age 30.3 ± 12.5 years, five male), four healthy participants with smoking history (>10 pack-years) (age 42.5 ± 18.3 years, one male), and 12 participants with COPD (age 62.8 ± 11.1 years, seven male). FIELD STRENGTH/SEQUENCE Single-slice free-breathing two-dimensional fast field echo sequence at 3 T. ASSESSMENT A novel postprocessing was developed to evaluate the MR signal changes in the lung parenchyma using a linear regression-based approach, which makes use of all the data in the time series for maximum sensitivity. V/Q-weighted maps were produced by computing the cross-correlation, lag and gradient between the respiratory/cardiac phase time course and lung parenchyma signal time courses. A comparison of histogram median and skewness values and spirometry was performed. STATISTICAL TESTS Kruskal-Wallis tests with Dunn's multiple comparison tests to compare VOLVE metrics between groups; Spearman correlation to assess the correlation between MRI and spirometry-derived parameters; and Bland-Altman analysis and coefficient of variation to evaluate repeatability were used. A P-value <0.05 was considered significant. RESULTS Significant differences between the groups were found for ventilation between healthy never-smoker and COPD groups (median XCCV, LagV, and GradV) and perfusion (median XCCQ, LagQ, and GradQ). Minimal bias and no significant differences between intravisit scans were found (P range = 0.12-0.97). DATA CONCLUSION This preliminary study showed that VOLVE has potential to provide metrics of function quantification. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 1.
Collapse
Affiliation(s)
- Zachary J.T. Peggs
- Sir Peter Mansfield Imaging Centre, School of Physics and AstronomyUniversity of NottinghamNottinghamUK
- Centre for Respiratory ResearchNIHR Nottingham Biomedical Research CentreNottinghamUK
- Centre for Respiratory Research, Translational Medical Sciences, School of MedicineUniversity of NottinghamNottinghamUK
| | - Jonathan P. Brooke
- Centre for Respiratory ResearchNIHR Nottingham Biomedical Research CentreNottinghamUK
- Centre for Respiratory Research, Translational Medical Sciences, School of MedicineUniversity of NottinghamNottinghamUK
- Department of Respiratory MedicineNottingham University Hospitals NHS TrustNottinghamUK
| | - Charlotte E. Bolton
- Centre for Respiratory ResearchNIHR Nottingham Biomedical Research CentreNottinghamUK
- Centre for Respiratory Research, Translational Medical Sciences, School of MedicineUniversity of NottinghamNottinghamUK
- Department of Respiratory MedicineNottingham University Hospitals NHS TrustNottinghamUK
| | - Ian P. Hall
- Centre for Respiratory ResearchNIHR Nottingham Biomedical Research CentreNottinghamUK
- Centre for Respiratory Research, Translational Medical Sciences, School of MedicineUniversity of NottinghamNottinghamUK
- Department of Respiratory MedicineNottingham University Hospitals NHS TrustNottinghamUK
| | - Susan T. Francis
- Sir Peter Mansfield Imaging Centre, School of Physics and AstronomyUniversity of NottinghamNottinghamUK
- Centre for Respiratory ResearchNIHR Nottingham Biomedical Research CentreNottinghamUK
| | - Penny A. Gowland
- Sir Peter Mansfield Imaging Centre, School of Physics and AstronomyUniversity of NottinghamNottinghamUK
- Centre for Respiratory ResearchNIHR Nottingham Biomedical Research CentreNottinghamUK
| |
Collapse
|
2
|
Kizhakke Puliyakote AS, Tedjasaputra V, Petersen GM, Sá RC, Hopkins SR. Assessing the pulmonary vascular responsiveness to oxygen with proton MRI. J Appl Physiol (1985) 2024; 136:853-863. [PMID: 38385182 PMCID: PMC11343071 DOI: 10.1152/japplphysiol.00747.2023] [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: 10/20/2023] [Revised: 02/05/2024] [Accepted: 02/19/2024] [Indexed: 02/23/2024] Open
Abstract
Ventilation-perfusion matching occurs passively and is also actively regulated through hypoxic pulmonary vasoconstriction (HPV). The extent of HPV activity in humans, particularly normal subjects, is uncertain. Current evaluation of HPV assesses changes in ventilation-perfusion relationships/pulmonary vascular resistance with hypoxia and is invasive, or unsuitable for patients because of safety concerns. We used a noninvasive imaging-based approach to quantify the pulmonary vascular response to oxygen as a metric of HPV by measuring perfusion changes between breathing 21% and 30%O2 using arterial spin labeling (ASL) MRI. We hypothesized that the differences between 21% and 30%O2 images reflecting HPV release would be 1) significantly greater than the differences without [Formula: see text] changes (e.g., 21-21% and 30-30%O2) and 2) negatively associated with ventilation-perfusion mismatch. Perfusion was quantified in the right lung in normoxia (baseline), after 15 min of 30% O2 breathing (hyperoxia) and 15 min normoxic recovery (recovery) in healthy subjects (7 M, 7 F; age = 41.4 ± 19.6 yr). Normalized, smoothed, and registered pairs of perfusion images were subtracted and the mean square difference (MSD) was calculated. Separately, regional alveolar ventilation and perfusion were quantified from specific ventilation, proton density, and ASL imaging; the spatial variance of ventilation-perfusion (σ2V̇a/Q̇) distributions was calculated. The O2-responsive MSD was reproducible (R2 = 0.94, P < 0.0001) and greater (0.16 ± 0.06, P < 0.0001) than that from subtracted images collected under the same [Formula: see text] (baseline = 0.09 ± 0.04, hyperoxia = 0.08 ± 0.04, recovery = 0.08 ± 0.03), which were not different from one another (P = 0.2). The O2-responsive MSD was correlated with σ2V̇a/Q̇ (R2 = 0.47, P = 0.007). These data suggest that active HPV optimizes ventilation-perfusion matching in normal subjects. This noninvasive approach could be applied to patients with different disease phenotypes to assess HPV and ventilation-perfusion mismatch.NEW & NOTEWORTHY We developed a new proton MRI method to noninvasively quantify the pulmonary vascular response to oxygen. Using a hyperoxic stimulus to release HPV, we quantified the resulting redistribution of perfusion. The differences between normoxic and hyperoxic images were greater than those between images without [Formula: see text] changes and negatively correlated with ventilation-perfusion mismatch. This suggests that active HPV optimizes ventilation-perfusion matching in normal subjects. This approach is suitable for assessing patients with different disease phenotypes.
Collapse
Affiliation(s)
- Abhilash S Kizhakke Puliyakote
- Pulmonary Imaging Laboratory, UC San Diego Health Sciences, La Jolla, California, United States
- Department of Radiology, University of California, San Diego, La Jolla, California, United States
| | - Vincent Tedjasaputra
- Pulmonary Imaging Laboratory, UC San Diego Health Sciences, La Jolla, California, United States
- Department of Medicine, University of California, San Diego, La Jolla, California, United States
| | - Gregory M Petersen
- Pulmonary Imaging Laboratory, UC San Diego Health Sciences, La Jolla, California, United States
| | - Rui Carlos Sá
- Pulmonary Imaging Laboratory, UC San Diego Health Sciences, La Jolla, California, United States
- Department of Medicine, University of California, San Diego, La Jolla, California, United States
| | - Susan R Hopkins
- Pulmonary Imaging Laboratory, UC San Diego Health Sciences, La Jolla, California, United States
- Department of Radiology, University of California, San Diego, La Jolla, California, United States
| |
Collapse
|
3
|
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.
Collapse
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
| |
Collapse
|
4
|
Hsia CCW, Bates JHT, Driehuys B, Fain SB, Goldin JG, Hoffman EA, Hogg JC, Levin DL, Lynch DA, Ochs M, Parraga G, Prisk GK, Smith BM, Tawhai M, Vidal Melo MF, Woods JC, Hopkins SR. Quantitative Imaging Metrics for the Assessment of Pulmonary Pathophysiology: An Official American Thoracic Society and Fleischner Society Joint Workshop Report. Ann Am Thorac Soc 2023; 20:161-195. [PMID: 36723475 PMCID: PMC9989862 DOI: 10.1513/annalsats.202211-915st] [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: 02/02/2023] Open
Abstract
Multiple thoracic imaging modalities have been developed to link structure to function in the diagnosis and monitoring of lung disease. Volumetric computed tomography (CT) renders three-dimensional maps of lung structures and may be combined with positron emission tomography (PET) to obtain dynamic physiological data. Magnetic resonance imaging (MRI) using ultrashort-echo time (UTE) sequences has improved signal detection from lung parenchyma; contrast agents are used to deduce airway function, ventilation-perfusion-diffusion, and mechanics. Proton MRI can measure regional ventilation-perfusion ratio. Quantitative imaging (QI)-derived endpoints have been developed to identify structure-function phenotypes, including air-blood-tissue volume partition, bronchovascular remodeling, emphysema, fibrosis, and textural patterns indicating architectural alteration. Coregistered landmarks on paired images obtained at different lung volumes are used to infer airway caliber, air trapping, gas and blood transport, compliance, and deformation. This document summarizes fundamental "good practice" stereological principles in QI study design and analysis; evaluates technical capabilities and limitations of common imaging modalities; and assesses major QI endpoints regarding underlying assumptions and limitations, ability to detect and stratify heterogeneous, overlapping pathophysiology, and monitor disease progression and therapeutic response, correlated with and complementary to, functional indices. The goal is to promote unbiased quantification and interpretation of in vivo imaging data, compare metrics obtained using different QI modalities to ensure accurate and reproducible metric derivation, and avoid misrepresentation of inferred physiological processes. The role of imaging-based computational modeling in advancing these goals is emphasized. Fundamental principles outlined herein are critical for all forms of QI irrespective of acquisition modality or disease entity.
Collapse
|
5
|
Xu P, Zhang J, Nan Z, Meersmann T, Wang C. Free-Breathing Phase-Resolved Oxygen-Enhanced Pulmonary MRI Based on 3D Stack-of-Stars UTE Sequence. SENSORS (BASEL, SWITZERLAND) 2022; 22:3270. [PMID: 35590959 PMCID: PMC9105788 DOI: 10.3390/s22093270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 04/15/2022] [Accepted: 04/22/2022] [Indexed: 06/15/2023]
Abstract
Compared with hyperpolarized noble gas MRI, oxygen-enhanced lung imaging is a cost-effective approach to investigate lung function. In this study, we investigated the feasibility of free-breathing phase-resolved oxygen-enhanced pulmonary MRI based on a 3D stack-of-stars ultra-short echo time (UTE) sequence. We conducted both computer simulation and in vivo experiments and calculated percent signal enhancement maps of four different respiratory phases on four healthy volunteers from the end of expiration to the end of inspiration. The phantom experiment was implemented to verify simulation results. The respiratory phase was segmented based on the extracted respiratory signal and sliding window reconstruction, providing phase-resolved pulmonary MRI. Demons registration algorithm was applied to compensate for respiratory motion. The mean percent signal enhancement of the average phase increases from anterior to posterior region, matching previous literature. More details of pulmonary tissues were observed on post-oxygen inhalation images through the phase-resolved technique. Phase-resolved UTE pulmonary MRI shows the potential as a valuable method for oxygen-enhanced MRI that enables the investigation of lung ventilation on middle states of the respiratory cycle.
Collapse
Affiliation(s)
- Pengfei Xu
- Electrical and Electronic Engineering, Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo 315100, China; (P.X.); (J.Z.); (Z.N.)
| | - Jichang Zhang
- Electrical and Electronic Engineering, Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo 315100, China; (P.X.); (J.Z.); (Z.N.)
| | - Zhen Nan
- Electrical and Electronic Engineering, Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo 315100, China; (P.X.); (J.Z.); (Z.N.)
| | - Thomas Meersmann
- Sir Peter Mansfield Magnetic Imaging Center, University of Nottingham, Nottingham NG7 2RD, UK;
| | - Chengbo Wang
- Electrical and Electronic Engineering, Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo 315100, China; (P.X.); (J.Z.); (Z.N.)
- Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, Ningbo 315040, China
| |
Collapse
|
6
|
Bayfield KJ, Douglas TA, Rosenow T, Davies JC, Elborn SJ, Mall M, Paproki A, Ratjen F, Sly PD, Smyth AR, Stick S, Wainwright CE, Robinson PD. Time to get serious about the detection and monitoring of early lung disease in cystic fibrosis. Thorax 2021; 76:1255-1265. [PMID: 33927017 DOI: 10.1136/thoraxjnl-2020-216085] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 02/24/2021] [Accepted: 03/10/2021] [Indexed: 12/26/2022]
Abstract
Structural and functional defects within the lungs of children with cystic fibrosis (CF) are detectable soon after birth and progress throughout preschool years often without overt clinical signs or symptoms. By school age, most children have structural changes such as bronchiectasis or gas trapping/hypoperfusion and lung function abnormalities that persist into later life. Despite improved survival, gains in forced expiratory volume in one second (FEV1) achieved across successive birth cohorts during childhood have plateaued, and rates of FEV1 decline in adolescence and adulthood have not slowed. This suggests that interventions aimed at preventing lung disease should be targeted to mild disease and commence in early life. Spirometry-based classifications of 'normal' (FEV1≥90% predicted) and 'mild lung disease' (FEV1 70%-89% predicted) are inappropriate, given the failure of spirometry to detect significant structural or functional abnormalities shown by more sensitive imaging and lung function techniques. The state and readiness of two imaging (CT and MRI) and two functional (multiple breath washout and oscillometry) tools for the detection and monitoring of early lung disease in children and adults with CF are discussed in this article.Prospective research programmes and technological advances in these techniques mean that well-designed interventional trials in early lung disease, particularly in young children and infants, are possible. Age appropriate, randomised controlled trials are critical to determine the safety, efficacy and best use of new therapies in young children. Regulatory bodies continue to approve medications in young children based on safety data alone and extrapolation of efficacy results from older age groups. Harnessing the complementary information from structural and functional tools, with measures of inflammation and infection, will significantly advance our understanding of early CF lung disease pathophysiology and responses to therapy. Defining clinical utility for these novel techniques will require effective collaboration across multiple disciplines to address important remaining research questions. Future impact on existing management burden for patients with CF and their family must be considered, assessed and minimised.To address the possible role of these techniques in early lung disease, a meeting of international leaders and experts in the field was convened in August 2019 at the Australiasian Cystic Fibrosis Conference. The meeting entitiled 'Shaping imaging and functional testing for early disease detection of lung disease in Cystic Fibrosis', was attended by representatives across the range of disciplines involved in modern CF care. This document summarises the proceedings, key priorities and important research questions highlighted.
Collapse
Affiliation(s)
- Katie J Bayfield
- Department of Respiratory Medicine, Children's Hospital at Westmead, Westmead, New South Wales, Australia
| | - Tonia A Douglas
- Department of Respiratory and Sleep Medicine, Queensland Children's Hospital, South Brisbane, Queensland, Australia.,Child Health Research Centre, The University of Queensland, Brisbane, Queensland, Australia
| | - Tim Rosenow
- Telethon Kids Institute, The University of Western Australia, Perth, Western Australia, Australia.,Centre for Child Health Research, The University of Western Australia, Perth, Western Australia, Australia.,Centre for Microscopy, Characterisation and Analysis, The University of Western Australia, Perth, Western Australia, Australia
| | - Jane C Davies
- National Heart and Lung Institute, Imperial College London, London, UK.,Department of Paediatric Respiratory Medicine, Royal Brompton and Harefield NHS Foundation Trust, London, UK
| | - Stuart J Elborn
- Centre for Infection and Immunity, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK
| | - Marcus Mall
- Department of Pediatric Pulmonology, Immunology, and Critical Care Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany.,Berlin Institute of Health, Berlin, Germany.,Department of Translational Pulmonology, German Center for Lung Research, Berlin, Germany
| | - Anthony Paproki
- The Australian e-Health Research Centre, CSIRO, Brisbane, Queensland, Australia
| | - Felix Ratjen
- Translational Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.,University of Toronto, Toronto, Ontario, Canada
| | - Peter D Sly
- Children's Health and Environment Program, Child Health Research Centre, The University of Queenland, Herston, Queensland, Australia
| | - Alan R Smyth
- Division of Child Health, Obstetrics & Gynaecology. School of Medicine, University of Nottingham, Nottingham, Nottinghamshire, UK
| | - Stephen Stick
- Telethon Kids Institute, The University of Western Australia, Perth, Western Australia, Australia.,Centre for Child Health Research, The University of Western Australia, Perth, Western Australia, Australia.,Department of Respiratory Medicine, Princess Margaret Hospital for Children, Perth, Western Australia, Australia
| | - Claire E Wainwright
- Department of Respiratory and Sleep Medicine, Queensland Children's Hospital, South Brisbane, Queensland, Australia.,Child Health Research Centre, The University of Queensland, Brisbane, Queensland, Australia
| | - Paul D Robinson
- Department of Respiratory Medicine, Children's Hospital at Westmead, Westmead, New South Wales, Australia .,Airway Physiology and Imaging Group, Woolcock Institute of Medical Research, Glebe, New South Wales, Australia.,The Discipline of Paediatrics and Child Health, The University of Sydney, Sydney, New South Wales, Australia
| |
Collapse
|
7
|
Prisk GK, Petersen GM, Geier ET, Sá RC. Ventilatory heterogeneity in the normal human lung is unchanged by controlled breathing. J Appl Physiol (1985) 2020; 129:1152-1160. [PMID: 32853114 DOI: 10.1152/japplphysiol.00278.2020] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Measurement of ventilation heterogeneity with the multiple-breath nitrogen washout (MBW) is usually performed using controlled breathing with a fixed tidal volume and breathing frequency. However, it is unclear whether controlled breathing alters the underlying ventilatory heterogeneity. We hypothesized that the width of the specific ventilation distribution (a measure of heterogeneity) would be greater in tests performed during free breathing compared with those performed using controlled breathing. Eight normal subjects (age range = 23-50 yr, 5 female/3 male) twice underwent MRI-based specific ventilation imaging consisting of five repeated cycles with the inspired gas switching between 21% and 100% O2 every ~2 min (total imaging time = ~20 min). In each session, tests were performed with free breathing (FB, no constraints) and controlled breathing (CB) at a respiratory rate of 12 breaths/min and no tidal volume control. The specific ventilation (SV) distribution in a mid-sagittal slice of the right lung was calculated, and the heterogeneity was calculated as the full width at half max of a Gaussian distribution fitted on a log scale (SV width). Free breathing resulted in a range of breathing frequencies from 8.7 to 15.9 breaths/min (mean = 11.5 ± 2.2, P = 0.62, compared with CB). Heterogeneity (SV width) was unchanged by controlled breathing (FB: 0.38 ± 0.12; CB: 0.34 ± 0.09, P = 0.18, repeated-measures ANOVA). The imposition of a controlled breathing frequency did not significantly affect the heterogeneity of ventilation in the normal lung, suggesting that MBW and specific ventilation imaging as typically performed provide an unperturbed measure of ventilatory heterogeneity.NEW & NOTEWORTHY By using MRI-based specific ventilation imaging (SVI), we showed that the heterogeneity of specific ventilation was not different comparing free breathing and breathing with the imposition of a fixed breathing frequency of 12 breaths/min. Thus, multiple-breath washout and SVI as typically performed provide an unperturbed measure of ventilatory heterogeneity.
Collapse
Affiliation(s)
- G Kim Prisk
- Department of Medicine, University of California, San Diego, California
| | | | - Eric T Geier
- Department of Medicine, University of California, San Diego, California
| | - Rui C Sá
- Department of Medicine, University of California, San Diego, California
| |
Collapse
|
8
|
Hopkins SR. Ventilation/Perfusion Relationships and Gas Exchange: Measurement Approaches. Compr Physiol 2020; 10:1155-1205. [PMID: 32941684 DOI: 10.1002/cphy.c180042] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Ventilation-perfusion ( V ˙ A / Q ˙ ) matching, the regional matching of the flow of fresh gas to flow of deoxygenated capillary blood, is the most important mechanism affecting the efficiency of pulmonary gas exchange. This article discusses the measurement of V ˙ A / Q ˙ matching with three broad classes of techniques: (i) those based in gas exchange, such as the multiple inert gas elimination technique (MIGET); (ii) those derived from imaging techniques such as single-photon emission computed tomography (SPECT), positron emission tomography (PET), magnetic resonance imaging (MRI), computed tomography (CT), and electrical impedance tomography (EIT); and (iii) fluorescent and radiolabeled microspheres. The focus is on the physiological basis of these techniques that provide quantitative information for research purposes rather than qualitative measurements that are used clinically. The fundamental equations of pulmonary gas exchange are first reviewed to lay the foundation for the gas exchange techniques and some of the imaging applications. The physiological considerations for each of the techniques along with advantages and disadvantages are briefly discussed. © 2020 American Physiological Society. Compr Physiol 10:1155-1205, 2020.
Collapse
Affiliation(s)
- Susan R Hopkins
- Departments of Medicine and Radiology, University of California, San Diego, California, USA
| |
Collapse
|
9
|
Thompson AAR, Wilkins MR, Wild JM, Kiely DG, Lawrie A. Editorial: Pulmonary Hypertension: Mechanisms and Management, History and Future. Front Med (Lausanne) 2020; 7:125. [PMID: 32373616 PMCID: PMC7186409 DOI: 10.3389/fmed.2020.00125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Accepted: 03/20/2020] [Indexed: 11/13/2022] Open
Affiliation(s)
- A. A. Roger Thompson
- Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield, United Kingdom
- Sheffield Pulmonary Vascular Disease Unit, Royal Hallamshire Hospital, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, United Kingdom
| | - Martin R. Wilkins
- Department of Medicine and National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Jim M. Wild
- Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield, United Kingdom
- POLARIS, Academic Unit of Radiology, Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom
- INSIGNEO Institute for in silico Medicine, The University of Sheffield, Sheffield, United Kingdom
| | - David G. Kiely
- Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield, United Kingdom
- Sheffield Pulmonary Vascular Disease Unit, Royal Hallamshire Hospital, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, United Kingdom
- INSIGNEO Institute for in silico Medicine, The University of Sheffield, Sheffield, United Kingdom
| | - Allan Lawrie
- Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield, United Kingdom
- INSIGNEO Institute for in silico Medicine, The University of Sheffield, Sheffield, United Kingdom
| |
Collapse
|
10
|
Geier ET, Theilmann RJ, Darquenne C, Prisk GK, Sá RC. Quantitative Mapping of Specific Ventilation in the Human Lung using Proton Magnetic Resonance Imaging and Oxygen as a Contrast Agent. J Vis Exp 2019. [PMID: 31233033 DOI: 10.3791/59579] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Specific ventilation imaging (SVI) is a functional magnetic resonance imaging technique capable of quantifying specific ventilation - the ratio of the fresh gas entering a lung region divided by the region's end-expiratory volume - in the human lung, using only inhaled oxygen as a contrast agent. Regional quantification of specific ventilation has the potential to help identify areas of pathologic lung function. Oxygen in solution in tissue shortens the tissue's longitudinal relaxation time (T1), and thus a change in tissue oxygenation can be detected as a change in T1-weighted signal with an inversion recovery acquired image. Following an abrupt change between two concentrations of inspired oxygen, the rate at which lung tissue within a voxel equilibrates to a new steady-state reflects the rate at which resident gas is being replaced by inhaled gas. This rate is determined by specific ventilation. To elicit this sudden change in oxygenation, subjects alternately breathe 20-breath blocks of air (21% oxygen) and 100% oxygen while in the MRI scanner. A stepwise change in inspired oxygen fraction is achieved through use of a custom three-dimensional (3D)-printed flow bypass system with a manual switch during a short end-expiratory breath hold. To detect the corresponding change in T1, a global inversion pulse followed by a single shot fast spin echo sequence was used to acquire two-dimensional T1-weighted images in a 1.5 T MRI scanner, using an eight-element torso coil. Both single slice and multi-slice imaging are possible, with slightly different imaging parameters. Quantification of specific ventilation is achieved by correlating the time-course of signal intensity for each lung voxel with a library of simulated responses to the air/oxygen stimulus. SVI estimations of specific ventilation heterogeneity have been validated against multiple breath washout and proved to accurately determine the heterogeneity of the specific ventilation distribution.
Collapse
Affiliation(s)
- Eric T Geier
- Pulmonary Imaging Laboratory, Department of Medicine, University of California, San Diego
| | - Rebecca J Theilmann
- Pulmonary Imaging Laboratory, Department of Radiology, University of California, San Diego
| | - Chantal Darquenne
- Pulmonary Imaging Laboratory, Department of Medicine, University of California, San Diego
| | - G Kim Prisk
- Pulmonary Imaging Laboratory, Department of Medicine, University of California, San Diego
| | - Rui Carlos Sá
- Pulmonary Imaging Laboratory, Department of Medicine, University of California, San Diego;
| |
Collapse
|