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Rao Q, Li H, Zhou Q, Zhang M, Zhao X, Shi L, Xie J, Fan L, Han Y, Guo F, Liu S, Zhou X. Assessment of pulmonary physiological changes caused by aging, cigarette smoking, and COPD with hyperpolarized 129Xe magnetic resonance. Eur Radiol 2024; 34:7450-7459. [PMID: 38748243 DOI: 10.1007/s00330-024-10800-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 03/14/2024] [Accepted: 04/05/2024] [Indexed: 06/01/2024]
Abstract
OBJECTIVE To comprehensively assess the impact of aging, cigarette smoking, and chronic obstructive pulmonary disease (COPD) on pulmonary physiology using 129Xe MR. METHODS A total of 90 subjects were categorized into four groups, including healthy young (HY, n = 20), age-matched control (AMC, n = 20), asymptomatic smokers (AS, n = 28), and COPD patients (n = 22). 129Xe MR was utilized to obtain pulmonary physiological parameters, including ventilation defect percent (VDP), alveolar sleeve depth (h), apparent diffusion coefficient (ADC), total septal wall thickness (d), and ratio of xenon signal from red blood cells and interstitial tissue/plasma (RBC/TP). RESULTS Significant differences were found in the measured VDP (p = 0.035), h (p = 0.003), and RBC/TP (p = 0.003) between the HY and AMC groups. Compared with the AMC group, higher VDP (p = 0.020) and d (p = 0.048) were found in the AS group; higher VDP (p < 0.001), d (p < 0.001) and ADC (p < 0.001), and lower h (p < 0.001) and RBC/TP (p < 0.001) were found in the COPD group. Moreover, significant differences were also found in the measured VDP (p < 0.001), h (p < 0.001), ADC (p < 0.001), d (p = 0.008), and RBC/TP (p = 0.032) between the AS and COPD groups. CONCLUSION Our findings indicate that pulmonary structure and functional changes caused by aging, cigarette smoking, and COPD are various, and show a progressive deterioration with the accumulation of these risk factors, including cigarette smoking and COPD. CLINICAL RELEVANCE STATEMENT Pathophysiological changes can be difficult to comprehensively understand due to limitations in common techniques and multifactorial etiologies. 129Xe MRI can demonstrate structural and functional changes caused by several common factors and can be used to better understand patients' underlying pathology. KEY POINTS Standard techniques for assessing pathophysiological lung function changes, spirometry, and chest CT come with limitations. 129Xe MR demonstrated progressive deterioration with accumulation of the investigated risk factors, without these limitations. 129Xe MR can assess lung changes related to these risk factors to stage and evaluate the etiology of the disease.
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Affiliation(s)
- Qiuchen Rao
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430071, China
| | - Haidong Li
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430071, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Qian Zhou
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430071, China
| | - Ming Zhang
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430071, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiuchao Zhao
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430071, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lei Shi
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430071, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Junshuai Xie
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430071, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Li Fan
- Department of Radiology, Changzheng Hospital of the Second Military Medical University, Shanghai, 200003, China
| | - Yeqing Han
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430071, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Fumin Guo
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430071, China
| | - Shiyuan Liu
- Department of Radiology, Changzheng Hospital of the Second Military Medical University, Shanghai, 200003, China
| | - Xin Zhou
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430071, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- School of Biomedical Engineering, Hainan University, Haikou, 570228, China.
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Bdaiwi AS, Svoboda AM, Murdock KE, Hendricks A, Hossain MM, Kramer EL, Brewington JJ, Willmering MM, Woods JC, Walkup LL, Cleveland ZI. Quantifying abnormal alveolar microstructure in cystic fibrosis lung disease via hyperpolarized 129Xe diffusion MRI. J Cyst Fibros 2024; 23:926-935. [PMID: 38997823 PMCID: PMC11410525 DOI: 10.1016/j.jcf.2024.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 06/05/2024] [Accepted: 07/01/2024] [Indexed: 07/14/2024]
Abstract
RATIONALE Cystic Fibrosis (CF) progresses through recurrent infection and inflammation, causing permanent lung function loss and airway remodeling. CT scans reveal abnormally low-density lung parenchyma in CF, but its microstructural nature remains insufficiently explored due to clinical CT limitations. To this end, diffusion-weighted 129Xe MRI is a non-invasive and validated measure of lung microstructure. In this work, we investigate microstructural changes in people with CF (pwCF) relative to age-matched, healthy subjects using comprehensive imaging and analysis involving pulmonary-function tests (PFTs), and 129Xe MRI. METHODS 38 healthy subjects (age 6-40; 17.2 ± 9.5 years) and 39 pwCF (age 6-40; 15.6 ± 8.0 years) underwent 129Xe-diffusion MRI and PFTs. The distribution of diffusion measurements (i.e., apparent diffusion coefficients (ADC) and morphometric parameters) was assessed via linear binning (LB). The resulting volume percentages of bins were compared between controls and pwCF. Mean ADC and morphometric parameters were also correlated with PFTs. RESULTS Mean whole-lung ADC correlated significantly with age (P < 0.001) for both controls and CF, and with PFTs (P < 0.05) specifically for pwCF. Although there was no significant difference in mean ADC between controls and pwCF (P = 0.334), age-adjusted LB indicated significant voxel-level diffusion (i.e., ADC and morphometric parameters) differences in pwCF compared to controls (P < 0.05). CONCLUSIONS 129Xe diffusion MRI revealed microstructural abnormalities in CF lung disease. Smaller microstructural size may reflect compression from overall higher lung density due to interstitial inflammation, fibrosis, or other pathological changes. While elevated microstructural size may indicate emphysema-like remodeling due to chronic inflammation and infection.
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Affiliation(s)
- Abdullah S Bdaiwi
- Center for Pulmonary Imaging Research, Division of Pulmonary Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, United States; Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH 45221, United States
| | - Alexandra M Svoboda
- Center for Pulmonary Imaging Research, Division of Pulmonary Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, United States; College of Medicine, University of Cincinnati, Cincinnati, OH 45221, United States
| | - Kyle E Murdock
- Imaging Research Center, Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, United States
| | - Alexandra Hendricks
- Center for Pulmonary Imaging Research, Division of Pulmonary Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, United States; Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH 45221, United States
| | - Md M Hossain
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, United States; Department of Pediatrics, University of Cincinnati, Cincinnati, OH, United States
| | - Elizabeth L Kramer
- Center for Pulmonary Imaging Research, Division of Pulmonary Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, United States; Department of Pediatrics, University of Cincinnati, Cincinnati, OH, United States
| | - John J Brewington
- Center for Pulmonary Imaging Research, Division of Pulmonary Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, United States; Department of Pediatrics, University of Cincinnati, Cincinnati, OH, United States
| | - Matthew M Willmering
- Center for Pulmonary Imaging Research, Division of Pulmonary Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, United States
| | - Jason C Woods
- Center for Pulmonary Imaging Research, Division of Pulmonary Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, United States; Imaging Research Center, Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, United States; Department of Pediatrics, University of Cincinnati, Cincinnati, OH, United States; Department of Physics, University of Cincinnati, Cincinnati, United States
| | - Laura L Walkup
- Center for Pulmonary Imaging Research, Division of Pulmonary Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, United States; Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH 45221, United States; Imaging Research Center, Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, United States; Department of Pediatrics, University of Cincinnati, Cincinnati, OH, United States
| | - Zackary I Cleveland
- Center for Pulmonary Imaging Research, Division of Pulmonary Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, United States; Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH 45221, United States; Imaging Research Center, Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, United States; Department of Pediatrics, University of Cincinnati, Cincinnati, OH, United States.
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Ancer-Rodríguez J, Gopar-Cuevas Y, García-Aguilar K, Chávez-Briones MDL, Miranda-Maldonado I, Ancer-Arellano A, Ortega-Martínez M, Jaramillo-Rangel G. Cell Proliferation and Apoptosis-Key Players in the Lung Aging Process. Int J Mol Sci 2024; 25:7867. [PMID: 39063108 PMCID: PMC11276691 DOI: 10.3390/ijms25147867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2024] [Revised: 07/12/2024] [Accepted: 07/15/2024] [Indexed: 07/28/2024] Open
Abstract
Currently, the global lifespan has increased, resulting in a higher proportion of the population over 65 years. Changes that occur in the lung during aging increase the risk of developing acute and chronic lung diseases, such as acute respiratory distress syndrome, chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, and lung cancer. During normal tissue homeostasis, cell proliferation and apoptosis create a dynamic balance that constitutes the physiological cell turnover. In basal conditions, the lungs have a low rate of cell turnover compared to other organs. During aging, changes in the rate of cell turnover in the lung are observed. In this work, we review the literature that evaluates the role of molecules involved in cell proliferation and apoptosis in lung aging and in the development of age-related lung diseases. The list of molecules that regulate cell proliferation, apoptosis, or both processes in lung aging includes TNC, FOXM1, DNA-PKcs, MicroRNAs, BCL-W, BCL-XL, TCF21, p16, NOX4, NRF2, MDM4, RPIA, DHEA, and MMP28. However, despite the studies carried out to date, the complete signaling pathways that regulate cell turnover in lung aging are still unknown. More research is needed to understand the changes that lead to the development of age-related lung diseases.
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Affiliation(s)
| | | | | | | | | | | | | | - Gilberto Jaramillo-Rangel
- Department of Pathology, School of Medicine, Autonomous University of Nuevo León, Monterrey 64460, Mexico; (J.A.-R.); (Y.G.-C.); (M.-d.-L.C.-B.); (I.M.-M.); (A.A.-A.); (M.O.-M.)
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Wang Y, Huang X, Luo G, Xu Y, Deng X, Lin Y, Wang Z, Zhou S, Wang S, Chen H, Tao T, He L, Yang L, Yang L, Chen Y, Jin Z, He C, Han Z, Zhang X. The aging lung: microenvironment, mechanisms, and diseases. Front Immunol 2024; 15:1383503. [PMID: 38756780 PMCID: PMC11096524 DOI: 10.3389/fimmu.2024.1383503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 04/16/2024] [Indexed: 05/18/2024] Open
Abstract
With the development of global social economy and the deepening of the aging population, diseases related to aging have received increasing attention. The pathogenesis of many respiratory diseases remains unclear, and lung aging is an independent risk factor for respiratory diseases. The aging mechanism of the lung may be involved in the occurrence and development of respiratory diseases. Aging-induced immune, oxidative stress, inflammation, and telomere changes can directly induce and promote the occurrence and development of lung aging. Meanwhile, the occurrence of lung aging also further aggravates the immune stress and inflammatory response of respiratory diseases; the two mutually affect each other and promote the development of respiratory diseases. Explaining the mechanism and treatment direction of these respiratory diseases from the perspective of lung aging will be a new idea and research field. This review summarizes the changes in pulmonary microenvironment, metabolic mechanisms, and the progression of respiratory diseases associated with aging.
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Affiliation(s)
- Yanmei Wang
- School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Institute of Traditional Chinese Medicine of Sichuan Academy of Chinese Medicine Sciences (Sichuan Second Hospital of T.C.M), Chengdu, China
| | - Xuewen Huang
- School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Guofeng Luo
- School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Yunying Xu
- School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Xiqian Deng
- School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Yumeng Lin
- Eye School of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Zhanzhan Wang
- Department of Respiratory and Critical Care Medicine, The First People’s Hospital of Lianyungang, Lianyungang, China
| | - Shuwei Zhou
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Siyu Wang
- Department of Gastroenterology, The First Hospital of Hunan University of Chinese Medicine, Changsha, China
| | - Haoran Chen
- School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Tao Tao
- Institute of Traditional Chinese Medicine of Sichuan Academy of Chinese Medicine Sciences (Sichuan Second Hospital of T.C.M), Chengdu, China
| | - Lei He
- Institute of Traditional Chinese Medicine of Sichuan Academy of Chinese Medicine Sciences (Sichuan Second Hospital of T.C.M), Chengdu, China
| | - Luchuan Yang
- Institute of Traditional Chinese Medicine of Sichuan Academy of Chinese Medicine Sciences (Sichuan Second Hospital of T.C.M), Chengdu, China
| | - Li Yang
- Institute of Traditional Chinese Medicine of Sichuan Academy of Chinese Medicine Sciences (Sichuan Second Hospital of T.C.M), Chengdu, China
| | - Yutong Chen
- The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China
| | - Zi Jin
- Department of Anesthesiology and Pain Rehabilitation, Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai, China
| | - Chengshi He
- Department of Respiratory, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Zhongyu Han
- School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Xiaohong Zhang
- Department of Emergency Medicine Center, Sichuan Province People’s Hospital University of Electronic Science and Technology of China, Chengdu, China
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Ruan Z, Li D, Huang D, Liang M, Xu Y, Qiu Z, Chen X. Relationship between an ageing measure and chronic obstructive pulmonary disease, lung function: a cross-sectional study of NHANES, 2007-2010. BMJ Open 2023; 13:e076746. [PMID: 37918922 PMCID: PMC10626813 DOI: 10.1136/bmjopen-2023-076746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 09/28/2023] [Indexed: 11/04/2023] Open
Abstract
OBJECTIVES Chronic obstructive pulmonary disease (COPD) is a disease associated with ageing. However, actual age does not accurately reflect the degree of biological ageing. Phenotypic age (PhenoAge) is a new indicator of biological ageing, and phenotypic age minus actual age is known as phenotypic age acceleration (PhenoAgeAccel). This research aimed to analyse the relationship between PhenoAgeAccel and lung function and COPD. DESIGN A cross-sectional study. PARTICIPANTS Data for the study were obtained from the National Health and Nutrition Examination Survey (NHANES) 2007-2010. We defined people with forced expiratory volume in 1 s/forced vital capacity <0.70 after inhaled bronchodilators as COPD and the rest of the population as non-COPD. Adults aged 40 years or older were enrolled in the study. PRIMARY AND SECONDARY OUTCOME MEASURES Linear and logistic regression were used to investigate the relationship between PhenoAgeAccel, lung function and COPD. Subgroup analysis was performed by gender, age, ethnicity and smoking index COPD. In addition, we analysed the relationship between the smoking index, respiratory symptoms and PhenoAgeAccel. Multiple models were used to reduce confounding bias. RESULTS 5397 participants were included in our study, of which 1042 had COPD. Compared with PhenoAgeAccel Quartile1, Quartile 4 had a 52% higher probability of COPD; elevated PhenoAgeAccel was also significantly associated with reduced lung function. Further subgroup analysis showed that high levels of PhenoAgeAccel had a more significant effect on lung function in COPD, older adults and whites (P for interaction <0.05). Respiratory symptoms and a high smoking index were related to higher indicators of ageing. CONCLUSIONS Our study found that accelerated ageing is associated with the development of COPD and impaired lung function. Smoking cessation and anti-ageing therapy have potential significance in COPD.
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Affiliation(s)
- Zhishen Ruan
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Dan Li
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Di Huang
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Minghao Liang
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Yifei Xu
- Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Zhanjun Qiu
- Shandong University of Traditional Chinese Medicine Affiliated Hospital, Jinan, Shandong, China
| | - Xianhai Chen
- Shandong University of Traditional Chinese Medicine Affiliated Hospital, Jinan, Shandong, China
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Bao H, Cao J, Chen M, Chen M, Chen W, Chen X, Chen Y, Chen Y, Chen Y, Chen Z, Chhetri JK, Ding Y, Feng J, Guo J, Guo M, He C, Jia Y, Jiang H, Jing Y, Li D, Li J, Li J, Liang Q, Liang R, Liu F, Liu X, Liu Z, Luo OJ, Lv J, Ma J, Mao K, Nie J, Qiao X, Sun X, Tang X, Wang J, Wang Q, Wang S, Wang X, Wang Y, Wang Y, Wu R, Xia K, Xiao FH, Xu L, Xu Y, Yan H, Yang L, Yang R, Yang Y, Ying Y, Zhang L, Zhang W, Zhang W, Zhang X, Zhang Z, Zhou M, Zhou R, Zhu Q, Zhu Z, Cao F, Cao Z, Chan P, Chen C, Chen G, Chen HZ, Chen J, Ci W, Ding BS, Ding Q, Gao F, Han JDJ, Huang K, Ju Z, Kong QP, Li J, Li J, Li X, Liu B, Liu F, Liu L, Liu Q, Liu Q, Liu X, Liu Y, Luo X, Ma S, Ma X, Mao Z, Nie J, Peng Y, Qu J, Ren J, Ren R, Song M, Songyang Z, Sun YE, Sun Y, Tian M, Wang S, Wang S, Wang X, Wang X, Wang YJ, Wang Y, Wong CCL, Xiang AP, Xiao Y, Xie Z, Xu D, Ye J, Yue R, Zhang C, Zhang H, Zhang L, Zhang W, Zhang Y, Zhang YW, Zhang Z, Zhao T, Zhao Y, Zhu D, Zou W, Pei G, Liu GH. Biomarkers of aging. SCIENCE CHINA. LIFE SCIENCES 2023; 66:893-1066. [PMID: 37076725 PMCID: PMC10115486 DOI: 10.1007/s11427-023-2305-0] [Citation(s) in RCA: 99] [Impact Index Per Article: 99.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 02/27/2023] [Indexed: 04/21/2023]
Abstract
Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need. Here, we summarize our current knowledge of biomarkers developed for cellular, organ, and organismal levels of aging, comprising six pillars: physiological characteristics, medical imaging, histological features, cellular alterations, molecular changes, and secretory factors. To fulfill all these requisites, we propose that aging biomarkers should qualify for being specific, systemic, and clinically relevant.
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Affiliation(s)
- Hainan Bao
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Jiani Cao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Mengting Chen
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Min Chen
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Wei Chen
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China
| | - Xiao Chen
- Department of Nuclear Medicine, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Yanhao Chen
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yu Chen
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Yutian Chen
- The Department of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Zhiyang Chen
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China
| | - Jagadish K Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Yingjie Ding
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Junlin Feng
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jun Guo
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China
| | - Mengmeng Guo
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China
| | - Chuting He
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Yujuan Jia
- Department of Neurology, First Affiliated Hospital, Shanxi Medical University, Taiyuan, 030001, China
| | - Haiping Jiang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Ying Jing
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Dingfeng Li
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China
| | - Jiaming Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jingyi Li
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Qinhao Liang
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China
| | - Rui Liang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China
| | - Feng Liu
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China
| | - Xiaoqian Liu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Zuojun Liu
- School of Life Sciences, Hainan University, Haikou, 570228, China
| | - Oscar Junhong Luo
- Department of Systems Biomedical Sciences, School of Medicine, Jinan University, Guangzhou, 510632, China
| | - Jianwei Lv
- School of Life Sciences, Xiamen University, Xiamen, 361102, China
| | - Jingyi Ma
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Kehang Mao
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China
| | - Jiawei Nie
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xinhua Qiao
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xinpei Sun
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China
| | - Xiaoqiang Tang
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Jianfang Wang
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Qiaoran Wang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Siyuan Wang
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China
| | - Xuan Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China
| | - Yaning Wang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yuhan Wang
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Rimo Wu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China
| | - Kai Xia
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Fu-Hui Xiao
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Lingyan Xu
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Yingying Xu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Haoteng Yan
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Liang Yang
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China
| | - Ruici Yang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yuanxin Yang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China
| | - Yilin Ying
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China
| | - Le Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Weiwei Zhang
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China
| | - Wenwan Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xing Zhang
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Zhuo Zhang
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Min Zhou
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Qingchen Zhu
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Zhengmao Zhu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Feng Cao
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China.
| | - Zhongwei Cao
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Piu Chan
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
| | - Chang Chen
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Guobing Chen
- Department of Microbiology and Immunology, School of Medicine, Jinan University, Guangzhou, 510632, China.
- Guangdong-Hong Kong-Macau Great Bay Area Geroscience Joint Laboratory, Guangzhou, 510000, China.
| | - Hou-Zao Chen
- Department of Biochemistryand Molecular Biology, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
| | - Jun Chen
- Peking University Research Center on Aging, Beijing Key Laboratory of Protein Posttranslational Modifications and Cell Function, Department of Biochemistry and Molecular Biology, Department of Integration of Chinese and Western Medicine, School of Basic Medical Science, Peking University, Beijing, 100191, China.
| | - Weimin Ci
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
| | - Bi-Sen Ding
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Qiurong Ding
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Feng Gao
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Kai Huang
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
| | - Zhenyu Ju
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China.
| | - Qing-Peng Kong
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
| | - Ji Li
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China.
| | - Jian Li
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China.
| | - Xin Li
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Baohua Liu
- School of Basic Medical Sciences, Shenzhen University Medical School, Shenzhen, 518060, China.
| | - Feng Liu
- Metabolic Syndrome Research Center, The Second Xiangya Hospital, Central South Unversity, Changsha, 410011, China.
| | - Lin Liu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China.
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
- Institute of Translational Medicine, Tianjin Union Medical Center, Nankai University, Tianjin, 300000, China.
- State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, 300350, China.
| | - Qiang Liu
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China.
| | - Qiang Liu
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China.
- Tianjin Institute of Immunology, Tianjin Medical University, Tianjin, 300070, China.
| | - Xingguo Liu
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China.
| | - Yong Liu
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China.
| | - Xianghang Luo
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China.
| | - Shuai Ma
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Xinran Ma
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
| | - Zhiyong Mao
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Jing Nie
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Yaojin Peng
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jing Qu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jie Ren
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Ruibao Ren
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Center for Aging and Cancer, Hainan Medical University, Haikou, 571199, China.
| | - Moshi Song
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Zhou Songyang
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China.
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China.
| | - Yi Eve Sun
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China.
| | - Yu Sun
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Department of Medicine and VAPSHCS, University of Washington, Seattle, WA, 98195, USA.
| | - Mei Tian
- Human Phenome Institute, Fudan University, Shanghai, 201203, China.
| | - Shusen Wang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China.
| | - Si Wang
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
| | - Xia Wang
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China.
| | - Xiaoning Wang
- Institute of Geriatrics, The second Medical Center, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100853, China.
| | - Yan-Jiang Wang
- Department of Neurology and Center for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China.
| | - Yunfang Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China.
| | - Catherine C L Wong
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China.
| | - Andy Peng Xiang
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China.
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Yichuan Xiao
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Zhengwei Xie
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China.
- Beijing & Qingdao Langu Pharmaceutical R&D Platform, Beijing Gigaceuticals Tech. Co. Ltd., Beijing, 100101, China.
| | - Daichao Xu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China.
| | - Jing Ye
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China.
| | - Rui Yue
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Cuntai Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China.
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Hongbo Zhang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Liang Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Weiqi Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Yong Zhang
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Yun-Wu Zhang
- Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, School of Medicine, Xiamen University, Xiamen, 361102, China.
| | - Zhuohua Zhang
- Key Laboratory of Molecular Precision Medicine of Hunan Province and Center for Medical Genetics, Institute of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, 410078, China.
- Department of Neurosciences, Hengyang Medical School, University of South China, Hengyang, 421001, China.
| | - Tongbiao Zhao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Yuzheng Zhao
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China.
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China.
| | - Dahai Zhu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Weiguo Zou
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Gang Pei
- Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Biomedicine, The Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200070, China.
| | - Guang-Hui Liu
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
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Foo CT, Langton D, Thompson BR, Thien F. Functional lung imaging using novel and emerging MRI techniques. Front Med (Lausanne) 2023; 10:1060940. [PMID: 37181360 PMCID: PMC10166823 DOI: 10.3389/fmed.2023.1060940] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 04/03/2023] [Indexed: 05/16/2023] Open
Abstract
Respiratory diseases are leading causes of death and disability in the world. While early diagnosis is key, this has proven difficult due to the lack of sensitive and non-invasive tools. Computed tomography is regarded as the gold standard for structural lung imaging but lacks functional information and involves significant radiation exposure. Lung magnetic resonance imaging (MRI) has historically been challenging due to its short T2 and low proton density. Hyperpolarised gas MRI is an emerging technique that is able to overcome these difficulties, permitting the functional and microstructural evaluation of the lung. Other novel imaging techniques such as fluorinated gas MRI, oxygen-enhanced MRI, Fourier decomposition MRI and phase-resolved functional lung imaging can also be used to interrogate lung function though they are currently at varying stages of development. This article provides a clinically focused review of these contrast and non-contrast MR imaging techniques and their current applications in lung disease.
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Affiliation(s)
- Chuan T. Foo
- Department of Respiratory Medicine, Eastern Health, Melbourne, VIC, Australia
- Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia
| | - David Langton
- Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia
- Department of Thoracic Medicine, Peninsula Health, Frankston, VIC, Australia
| | - Bruce R. Thompson
- Melbourne School of Health Science, Melbourne University, Melbourne, VIC, Australia
| | - Francis Thien
- Department of Respiratory Medicine, Eastern Health, Melbourne, VIC, Australia
- Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia
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8
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Knudsen L, Hummel B, Wrede C, Zimmermann R, Perlman CE, Smith BJ. Acinar micromechanics in health and lung injury: what we have learned from quantitative morphology. Front Physiol 2023; 14:1142221. [PMID: 37025383 PMCID: PMC10070844 DOI: 10.3389/fphys.2023.1142221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 03/09/2023] [Indexed: 04/08/2023] Open
Abstract
Within the pulmonary acini ventilation and blood perfusion are brought together on a huge surface area separated by a very thin blood-gas barrier of tissue components to allow efficient gas exchange. During ventilation pulmonary acini are cyclically subjected to deformations which become manifest in changes of the dimensions of both alveolar and ductal airspaces as well as the interalveolar septa, composed of a dense capillary network and the delicate tissue layer forming the blood-gas barrier. These ventilation-related changes are referred to as micromechanics. In lung diseases, abnormalities in acinar micromechanics can be linked with injurious stresses and strains acting on the blood-gas barrier. The mechanisms by which interalveolar septa and the blood-gas barrier adapt to an increase in alveolar volume have been suggested to include unfolding, stretching, or changes in shape other than stretching and unfolding. Folding results in the formation of pleats in which alveolar epithelium is not exposed to air and parts of the blood-gas barrier are folded on each other. The opening of a collapsed alveolus (recruitment) can be considered as an extreme variant of septal wall unfolding. Alveolar recruitment can be detected with imaging techniques which achieve light microscopic resolution. Unfolding of pleats and stretching of the blood-gas barrier, however, require electron microscopic resolution to identify the basement membrane. While stretching results in an increase of the area of the basement membrane, unfolding of pleats and shape changes do not. Real time visualization of these processes, however, is currently not possible. In this review we provide an overview of septal wall micromechanics with focus on unfolding/folding as well as stretching. At the same time we provide a state-of-the-art design-based stereology methodology to quantify microarchitecture of alveoli and interalveolar septa based on different imaging techniques and design-based stereology.
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Affiliation(s)
- Lars Knudsen
- Institute of Functional and Applied Anatomy, Hannover Medical School, Hannover, Germany
- Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Member of the German Centre for Lung Research (DZL), Hannover, Germany
| | - Benjamin Hummel
- Institute of Functional and Applied Anatomy, Hannover Medical School, Hannover, Germany
| | - Christoph Wrede
- Institute of Functional and Applied Anatomy, Hannover Medical School, Hannover, Germany
- Research Core Unit Electron Microscopy, Hannover Medical School, Hannover, Germany
| | - Richard Zimmermann
- Institute of Functional and Applied Anatomy, Hannover Medical School, Hannover, Germany
| | - Carrie E Perlman
- Department of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ, United States
| | - Bradford J Smith
- Department of Bioengineering, College of Engineering Design and Computing, University of Colorado Denver | Anschutz Medical Campus, Aurora, CO, United States
- Department of Pediatric Pulmonary and Sleep Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
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9
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Zhou Q, Li H, Rao Q, Zhang M, Zhao X, Shen L, Fang Y, Li H, Liu X, Xiao S, Shi L, Han Y, Ye C, Zhou X. Assessment of pulmonary morphometry using hyperpolarized 129 Xe diffusion-weighted MRI with variable-sampling-ratio compressed sensing patterns. Med Phys 2023; 50:867-878. [PMID: 36196039 DOI: 10.1002/mp.16018] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 08/26/2022] [Accepted: 09/24/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Hyperpolarized (HP) 129 Xe multiple b-values diffusion-weighted magnetic resonance imaging (DW-MRI) has been widely used for quantifying pulmonary microstructural morphometry. However, the technique requires long acquisition times, making it hard to apply in patients with severe pulmonary diseases, who cannot sustain long breath holds. PURPOSE To develop and evaluate the technique of variable-sampling-ratio compressed sensing (VCS) patterns for accelerating HP 129 Xe multiple b-values DW-MRI in humans. METHODS Optimal variable sampling ratios and corresponding k-space undersampling patterns for each b-value were obtained by retrospective simulations based on the fully sampled (FS) DW-MRI dataset acquired from six young healthy volunteers. Then, the FS datasets were retrospectively undersampled using both VCS patterns and conventional compressed sensing (CS) pattern with a similar average acceleration factor. The quality of reconstructed images with retrospective VCS (rVCS) and CS (rCS) datasets were quantified using mean absolute error (MAE) and structural similarity (SSIM). Pulmonary morphometric parameters were also evaluated between rVCS and FS datasets. In addition, prospective VCS multiple b-values 129 Xe DW-MRI datasets were acquired from 14 cigarette smokers and 13 age-matched healthy volunteers. The differences of lung morphological parameters obtained with the proposed method were compared between the groups using independent samples t-test. Pearson correlation coefficient was also utilized for evaluating the correlation of the pulmonary physiological parameters obtained with VCS DW-MRI and pulmonary function tests. RESULTS Lower MAE and higher SSIM values were found in the reconstructed images with rVCS measurement when compared to those using conventional rCS measurement. The details and quality of the images obtained with rVCS and FS measurements were found to be comparable. The mean values of the morphological parameters derived from rVCS and FS datasets showed no significant differences (p > 0.05), and the mean differences of measured acinar duct radius, mean linear intercept, surface-to-volume ratio, and apparent diffusion coefficient with cylinder model were -0.87%, -2.42%, 2.04%, and -0.50%, respectively. By using the VCS technique, significant differences were delineated between the pulmonary morphometric parameters of healthy volunteers and cigarette smokers (p < 0.001), while the acquisition time was reduced by four times. CONCLUSION A fourfold reduction in acquisition time was achieved using the proposed VCS method while preserving good image quality. Our preliminary results demonstrated that the proposed method can be used for evaluating pulmonary injuries caused by cigarette smoking and may prove to be helpful in diagnosing lung diseases in clinical practice.
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Affiliation(s)
- Qian Zhou
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Wuhan, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Haidong Li
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Wuhan, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Qiuchen Rao
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Wuhan, China
| | - Ming Zhang
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Wuhan, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Xiuchao Zhao
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Wuhan, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Luyang Shen
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Wuhan, China
| | - Yuan Fang
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Wuhan, China
| | - Hongchuang Li
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Wuhan, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Xiaoling Liu
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Wuhan, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Sa Xiao
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Wuhan, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Lei Shi
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Wuhan, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Yeqing Han
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Wuhan, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Chaohui Ye
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Wuhan, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Xin Zhou
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Wuhan, China.,University of Chinese Academy of Sciences, Beijing, China
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10
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Immunosenescence, Inflammaging, and Lung Senescence in Asthma in the Elderly. Biomolecules 2022; 12:biom12101456. [PMID: 36291665 PMCID: PMC9599177 DOI: 10.3390/biom12101456] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 10/02/2022] [Accepted: 10/04/2022] [Indexed: 11/24/2022] Open
Abstract
Prevalence of asthma in older adults is growing along with increasing global life expectancy. Due to poor clinical consequences such as high mortality, advancement in understanding the pathophysiology of asthma in older patients has been sought to provide prompt treatment for them. Age-related alterations of functions in the immune system and lung parenchyma occur throughout life. Alterations with advancing age are promoted by various stimuli, including pathobionts, fungi, viruses, pollutants, and damage-associated molecular patterns derived from impaired cells, abandoned cell debris, and senescent cells. Age-related changes in the innate and adaptive immune response, termed immunosenescence, includes impairment of phagocytosis and antigen presentation, enhancement of proinflammatory mediator generation, and production of senescence-associated secretory phenotype. Immnunosenescence could promote inflammaging (chronic low-grade inflammation) and contribute to late-onset adult asthma and asthma in the elderly, along with age-related pulmonary disease, such as chronic obstructive pulmonary disease and pulmonary fibrosis, due to lung parenchyma senescence. Aged patients with asthma exhibit local and systemic type 2 and non-type 2 inflammation, associated with clinical manifestations. Here, we discuss immunosenescence’s contribution to the immune response and the combination of type 2 inflammation and inflammaging in asthma in the elderly and present an overview of age-related features in the immune system and lung structure.
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11
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Stewart NJ, Smith LJ, Chan HF, Eaden JA, Rajaram S, Swift AJ, Weatherley ND, Biancardi A, Collier GJ, Hughes D, Klafkowski G, Johns CS, West N, Ugonna K, Bianchi SM, Lawson R, Sabroe I, Marshall H, Wild JM. Lung MRI with hyperpolarised gases: current & future clinical perspectives. Br J Radiol 2022; 95:20210207. [PMID: 34106792 PMCID: PMC9153706 DOI: 10.1259/bjr.20210207] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
The use of pulmonary MRI in a clinical setting has historically been limited. Whilst CT remains the gold-standard for structural lung imaging in many clinical indications, technical developments in ultrashort and zero echo time MRI techniques are beginning to help realise non-ionising structural imaging in certain lung disorders. In this invited review, we discuss a complementary technique - hyperpolarised (HP) gas MRI with inhaled 3He and 129Xe - a method for functional and microstructural imaging of the lung that has great potential as a clinical tool for early detection and improved understanding of pathophysiology in many lung diseases. HP gas MRI now has the potential to make an impact on clinical management by enabling safe, sensitive monitoring of disease progression and response to therapy. With reference to the significant evidence base gathered over the last two decades, we review HP gas MRI studies in patients with a range of pulmonary disorders, including COPD/emphysema, asthma, cystic fibrosis, and interstitial lung disease. We provide several examples of our experience in Sheffield of using these techniques in a diagnostic clinical setting in challenging adult and paediatric lung diseases.
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Affiliation(s)
- Neil J Stewart
- POLARIS, Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Laurie J Smith
- POLARIS, Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Ho-Fung Chan
- POLARIS, Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - James A Eaden
- POLARIS, Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Smitha Rajaram
- POLARIS, Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Andrew J Swift
- POLARIS, Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Nicholas D Weatherley
- POLARIS, Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Alberto Biancardi
- POLARIS, Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Guilhem J Collier
- POLARIS, Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - David Hughes
- Sheffield Children's NHS Foundation Trust, Sheffield, UK
| | | | - Christopher S Johns
- POLARIS, Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Noreen West
- Sheffield Children's NHS Foundation Trust, Sheffield, UK
| | - Kelechi Ugonna
- Sheffield Children's NHS Foundation Trust, Sheffield, UK
| | - Stephen M Bianchi
- Directorate of Respiratory Medicine, Sheffield Teaching Hospitals NHS Trust, Sheffield, UK
| | - Rod Lawson
- Directorate of Respiratory Medicine, Sheffield Teaching Hospitals NHS Trust, Sheffield, UK
| | - Ian Sabroe
- Directorate of Respiratory Medicine, Sheffield Teaching Hospitals NHS Trust, Sheffield, UK
| | - Helen Marshall
- POLARIS, Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
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12
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Grover S. Challenges in physiotherapy of managing respiratory diseases in elderly population. Indian J Tuberc 2022; 69 Suppl 2:S280-S286. [PMID: 36400524 DOI: 10.1016/j.ijtb.2022.10.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 10/25/2022] [Indexed: 11/06/2022]
Abstract
INTRODUCTION Lung function is a convincing prognosticator of longevity. With advancing age, there are many irreversible functional and anatomic changes in the body, making elderly susceptible to disease processes. As people age, the respiratory system experiences a number of anatomical, physiological, and immunological changes, predisposing risk of many chronic lung diseases (CLDs). Respiratory tract infections, TB, chronic obstructive pulmonary disease (COPD), and interstitial pulmonary disease are examples of common respiratory diseases (CRDs). The risk factors are mainly smoking, exposure to air pollution both indoors and outdoors, allergies, occupational exposure, poor diet, obesity, inactivity. Between 25 and 80 years the lung function and aerobic capacity each decline by ∼40% limiting physical function and promoting multimorbidity. In elderly, skeletal muscle dysfunction causes age-related multifactorial health disorders such sarcopenia and frailty, a recognised symptom of chronic respiratory disease. METHODS This perspective article highlights the importance of pulmonary physiotherapy in elderly with chronic lung disease and other chronic respiratory disorders. Common symptoms frequently experienced are dyspnoea, fatigue, decreased exercise tolerance, peripheral muscle dysfunction, and mental disturbances. An individual's symptoms, physical functioning, quality of life (QoL), hospitalisation, and morbidity goals are all addressed by a pulmonary rehabilitation programme (PRP). Pulmonary physiotherapy, an extensive patient-tailored intervention as exercise training, education, and life style modification is prescribed on the basis of a thorough personalised assessment. RESULT Through pulmonary physiotherapy, the goal is to restore the quality of life of elderly with chronic respiratory diseases and to encourage their long-term adherence to health-improving behaviour. The older patients learn to accept and overcome the reality of their illness rather than sticking to its limits. CONCLUSION Multidisciplinary approach with a customized and comprehensive program makes the difference between living a fulfilling life and living a life with pulmonary disabilities.
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Affiliation(s)
- Seema Grover
- Indrapratha Apollo Hospital, Mathura Rd, New Delhi, 110076, India.
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13
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Redox Regulation in Aging Lungs and Therapeutic Implications of Antioxidants in COPD. Antioxidants (Basel) 2021; 10:antiox10091429. [PMID: 34573061 PMCID: PMC8470212 DOI: 10.3390/antiox10091429] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Revised: 08/27/2021] [Accepted: 09/01/2021] [Indexed: 12/23/2022] Open
Abstract
Mammals, including humans, are aerobic organisms with a mature respiratory system to intake oxygen as a vital source of cellular energy. Despite the essentiality of reactive oxygen species (ROS) as byproducts of aerobic metabolism for cellular homeostasis, excessive ROS contribute to the development of a wide spectrum of pathological conditions, including chronic lung diseases such as COPD. In particular, epithelial cells in the respiratory system are directly exposed to and challenged by exogenous ROS, including ozone and cigarette smoke, which results in detrimental oxidative stress in the lungs. In addition, the dysfunction of redox regulation due to cellular aging accelerates COPD pathogenesis, such as inflammation, protease anti-protease imbalance and cellular apoptosis. Therefore, various drugs targeting oxidative stress-associated pathways, such as thioredoxin and N-acetylcysteine, have been developed for COPD treatment to precisely regulate the redox system. In this review, we present the current understanding of the roles of redox regulation in the respiratory system and COPD pathogenesis. We address the insufficiency of current COPD treatment as antioxidants and discuss future directions in COPD therapeutics targeting oxidative stress while avoiding side effects such as tumorigenesis.
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14
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Niedbalski PJ, Cochran AS, Freeman MS, Guo J, Fugate EM, Davis CB, Dahlke J, Quirk JD, Varisco BM, Woods JC, Cleveland ZI. Validating in vivo hyperpolarized 129 Xe diffusion MRI and diffusion morphometry in the mouse lung. Magn Reson Med 2021; 85:2160-2173. [PMID: 33017076 PMCID: PMC8544163 DOI: 10.1002/mrm.28539] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 08/27/2020] [Accepted: 09/14/2020] [Indexed: 02/03/2023]
Abstract
PURPOSE Diffusion and lung morphometry imaging using hyperpolarized gases are promising tools to quantify pulmonary microstructure noninvasively in humans and in animal models. These techniques assume the motion encoded is exclusively diffusive gas displacement, but the impact of cardiac motion on measurements has never been explored. Furthermore, although diffusion morphometry has been validated against histology in humans and mice using 3 He, it has never been validated in mice for 129 Xe. Here, we examine the effect of cardiac motion on diffusion imaging and validate 129 Xe diffusion morphometry in mice. THEORY AND METHODS Mice were imaged using gradient-echo-based diffusion imaging, and apparent diffusion-coefficient (ADC) maps were generated with and without cardiac gating. Diffusion-weighted images were fit to a previously developed theoretical model using Bayesian probability theory, producing morphometric parameters that were compared with conventional histology. RESULTS Cardiac gating had no significant impact on ADC measurements (dual-gating: ADC = 0.020 cm2 /s, single-gating: ADC = 0.020 cm2 /s; P = .38). Diffusion-morphometry-generated maps of ADC (mean, 0.0165 ± 0.0001 cm2 /s) and acinar dimensions (alveolar sleeve depth [h] = 44 µm, acinar duct radii [R] = 99 µm, mean linear intercept [Lm ] = 74 µm) that agreed well with conventional histology (h = 45 µm, R = 108 µm, Lm = 63 µm). CONCLUSION Cardiac motion has negligible impact on 129 Xe ADC measurements in mice, arguing its impact will be similarly minimal in humans, where relative cardiac motion is reduced. Hyperpolarized 129 Xe diffusion morphometry accurately and noninvasively maps the dimensions of lung microstructure, suggesting it can quantify the pulmonary microstructure in mouse models of lung disease.
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Affiliation(s)
- Peter J. Niedbalski
- Center for Pulmonary Imaging Research, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
| | - Alexander S. Cochran
- Center for Pulmonary Imaging Research, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH
| | - Matthew S. Freeman
- Center for Pulmonary Imaging Research, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH
| | - Jinbang Guo
- Center for Pulmonary Imaging Research, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
| | - Elizabeth M. Fugate
- Imaging Research Center, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
| | - Cory B. Davis
- Center for Pulmonary Imaging Research, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- Department of Physics, West Texas A&M University, Canyon, TX
| | - Jerry Dahlke
- Department of Radiology, Duke University School of Medicine, Durham, NC
| | - James D. Quirk
- Department of Radiology, Washington University, St. Louis, MO
| | - Brian M. Varisco
- Division of Critical Care Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- Department of Pediatrics, University of Cincinnati, Cincinnati, OH
| | - Jason C. Woods
- Center for Pulmonary Imaging Research, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- Imaging Research Center, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- Department of Radiology, Washington University, St. Louis, MO
- Department of Pediatrics, University of Cincinnati, Cincinnati, OH
| | - Zackary I. Cleveland
- Center for Pulmonary Imaging Research, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH
- Imaging Research Center, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- Department of Pediatrics, University of Cincinnati, Cincinnati, OH
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15
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Airspace Dimension Assessment (AiDA) by inhaled nanoparticles: benchmarking with hyperpolarised 129Xe diffusion-weighted lung MRI. Sci Rep 2021; 11:4721. [PMID: 33633165 PMCID: PMC7907057 DOI: 10.1038/s41598-021-83975-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 02/10/2021] [Indexed: 11/26/2022] Open
Abstract
Enlargements of distal airspaces can indicate pathological changes in the lung, but accessible and precise techniques able to measure these regions are lacking. Airspace Dimension Assessment with inhaled nanoparticles (AiDA) is a new method developed for in vivo measurement of distal airspace dimensions. The aim of this study was to benchmark the AiDA method against quantitative measurements of distal airspaces from hyperpolarised 129Xe diffusion-weighted (DW)-lung magnetic resonance imaging (MRI). AiDA and 129Xe DW-MRI measurements were performed in 23 healthy volunteers who spanned an age range of 23–70 years. The relationship between the 129Xe DW-MRI and AiDA metrics was tested using Spearman’s rank correlation coefficient. Significant correlations were observed between AiDA distal airspace radius (rAiDA) and mean 129Xe apparent diffusion coefficient (ADC) (p < 0.005), distributed diffusivity coefficient (DDC) (p < 0.001) and distal airspace dimension (LmD) (p < 0.001). A mean bias of − 1.2 µm towards rAiDA was observed between 129Xe LmD and rAiDA, indicating that rAiDA is a measure of distal airspace dimension. The AiDA R0 intercept correlated with MRI 129Xe α (p = 0.02), a marker of distal airspace heterogeneity. This study demonstrates that AiDA has potential to characterize the distal airspace microstructures and may serve as an alternative method for clinical examination of the lungs.
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16
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Chan HF, Collier GJ, Parra-Robles J, Wild JM. Finite element simulations of hyperpolarized gas DWI in micro-CT meshes of acinar airways: validating the cylinder and stretched exponential models of lung microstructural length scales. Magn Reson Med 2021; 86:514-525. [PMID: 33624325 DOI: 10.1002/mrm.28703] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 12/07/2020] [Accepted: 01/07/2021] [Indexed: 12/24/2022]
Abstract
PURPOSE This work assesses the accuracy of the stretched exponential (SEM) and cylinder models of lung microstructural length scales that can be derived from hyperpolarized gas DWI. This was achieved by simulating 3 He and 129 Xe DWI signals within two micro-CT-derived realistic acinar airspace meshes that represent healthy and idiopathic pulmonary fibrosis lungs. METHODS The healthy and idiopathic pulmonary fibrosis acinar airway meshes were derived from segmentations of 3D micro-CT images of excised human lungs and meshed for finite element simulations of the Bloch-Torrey equations. 3 He and 129 Xe multiple b value DWI experiments across a range of diffusion times (3 He Δ = 1.6 ms; 129 Xe Δ = 5 to 20 ms) were simulated in each mesh. Global SEM mean diffusive length scale and cylinder model mean chord length value was derived from each finite element simulation and compared against each mesh's mean linear intercept length, calculated from intercept length measurements within micro-CT segmentation masks. RESULTS The SEM-derived mean diffusive length scale was within ±10% of the mean linear intercept length for simulations with both 3 He (Δ = 1.6 ms) and 129 Xe (Δ = 7 to 13 ms) in the healthy mesh, and with 129 Xe (Δ = 13 to 20 ms) for the idiopathic pulmonary fibrosis mesh, whereas for the cylinder model-derived mean chord length the closest agreement with mean linear intercept length (11.7% and 22.6% difference) was at 129 Xe Δ = 20 ms for both healthy and IPF meshes, respectively. CONCLUSION This work validates the use of the SEM for accurate estimation of acinar dimensions and indicates that the SEM is relatively robust across a range of experimental conditions and acinar length scales.
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Affiliation(s)
- Ho-Fung Chan
- POLARIS, Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom
| | - Guilhem J Collier
- POLARIS, Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom
| | - Juan Parra-Robles
- POLARIS, Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom.,Faculty of Pharmacy, Universidad Complutense de Madrid, Madrid, Spain
| | - Jim M Wild
- POLARIS, Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom.,Insigneo, Institute for in Silico Medicine, University of Sheffield, Sheffield, United Kingdom
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17
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Maunder A, Chan HF, Hughes PJC, Collier G, Norquay G, Rodgers O, Thelwall P, Robb F, Rao M, Wild JM. MR properties of 19 F C 3 F 8 gas in the lungs of healthy volunteers: T 2 ∗ and apparent diffusion coefficient at 1.5T and T 2 ∗ at 3T. Magn Reson Med 2020; 85:1561-1570. [PMID: 32926448 DOI: 10.1002/mrm.28511] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Revised: 08/08/2020] [Accepted: 08/17/2020] [Indexed: 01/07/2023]
Abstract
PURPOSE To measure the transverse relaxation time ( T 2 ∗ ) and apparent diffusion coefficient (ADC) of 19 F-C3 F8 gas in vivo in human lungs at 1.5T and 3T, and to determine the representative distribution of values of these parameters in a cohort of healthy volunteers. METHODS Mapping of ADC at lung inflation levels of functional residual capacity (FRC) and total lung capacity (TLC) was performed with inhaled 19 F-C3 F8 (eight subjects) and 129 Xe (six subjects) at 1.5T. T 2 ∗ mapping with 19 F-C3 F8 was performed at 1.5T (at FRC and TLC) for 8 subjects and at 3T (at TLC for seven subjects). RESULTS At both FRC and TLC, the 19 F-C3 F8 ADC was smaller than the free diffusion coefficient demonstrating airway microstructural diffusion restriction. From FRC to TLC, the mean ADC significantly increased from 1.56 mm2 /s to 1.83 mm2 /s (P = .0017) for 19 F-C3 F8, and from 2.49 mm2 /s to 3.38 mm2 /s (P = .0015) for 129 Xe. The posterior-to-anterior gradient in ADC for FRC versus TLC in the superior half of the lungs was measured as 0.0308 mm2 /s per cm versus 0.0168 mm2 /s per cm for 19 F-C3 F8 and 0.0871 mm2 /s per cm versus 0.0326 mm2 /s per cm for 129 Xe. A consistent distribution of 19 F-C3 F8 T 2 ∗ values was observed in the lungs, with low values observed near the diaphragm and large pulmonary vessels. The mean T 2 ∗ across volunteers was 4.48 ms at FRC and 5.33 ms at TLC for 1.5T, and 3.78 ms at TLC for 3T. CONCLUSION In this feasibility study, values of physiologically relevant parameters of lung microstructure measurable by MRI ( T 2 ∗ , and ADC) were established for C3 F8 in vivo lung imaging in healthy volunteers.
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Affiliation(s)
- Adam Maunder
- POLARIS, Imaging Group, Department of IICD, University of Sheffield, Sheffield, United Kingdom
| | - Ho-Fung Chan
- POLARIS, Imaging Group, Department of IICD, University of Sheffield, Sheffield, United Kingdom
| | - Paul J C Hughes
- POLARIS, Imaging Group, Department of IICD, University of Sheffield, Sheffield, United Kingdom
| | - Guillhem Collier
- POLARIS, Imaging Group, Department of IICD, University of Sheffield, Sheffield, United Kingdom
| | - Graham Norquay
- POLARIS, Imaging Group, Department of IICD, University of Sheffield, Sheffield, United Kingdom
| | - Oliver Rodgers
- POLARIS, Imaging Group, Department of IICD, University of Sheffield, Sheffield, United Kingdom
| | - Peter Thelwall
- Newcastle Magnetic Resonance Centre, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Fraser Robb
- POLARIS, Imaging Group, Department of IICD, University of Sheffield, Sheffield, United Kingdom.,GE Healthcare, Aurora, Ohio, USA
| | - Madhwesha Rao
- POLARIS, Imaging Group, Department of IICD, University of Sheffield, Sheffield, United Kingdom
| | - Jim M Wild
- POLARIS, Imaging Group, Department of IICD, University of Sheffield, Sheffield, United Kingdom
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18
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Dong M, Yang W, Tamaresis JS, Chan FP, Zucker EJ, Kumar S, Rabinovitch M, Marsden AL, Feinstein JA. Image-based scaling laws for somatic growth and pulmonary artery morphometry from infancy to adulthood. Am J Physiol Heart Circ Physiol 2020; 319:H432-H442. [PMID: 32618514 DOI: 10.1152/ajpheart.00123.2020] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Pulmonary artery (PA) morphometry has been extensively explored in adults, with particular focus on intra-acinar arteries. However, scaling law relationships for length and diameter of extensive preacinar PAs by age have not been previously reported for in vivo human data. To understand preacinar PA growth spanning children to adults, we performed morphometric analyses of all PAs visible in the computed tomography (CT) and magnetic resonance (MR) images from a healthy subject cohort [n = 16; age: 1-51 yr; body surface area (BSA): 0.49-2.01 m2]. Subject-specific anatomic PA models were constructed from CT and MR images, and morphometric information-diameter, length, tortuosity, bifurcation angle, and connectivity-was extracted and sorted into diameter-defined Strahler orders. Validation of Murray's law, describing optimal scaling exponents of radii for branching vessels, was performed to determine how closely PAs conform to this classical relationship. Using regression analyses of vessel diameters and lengths against orders and patient metrics (BSA, age, height), we found that diameters increased exponentially with order and allometrically with patient metrics. Length increased allometrically with patient metrics, albeit weakly. The average tortuosity index of all vessels was 0.026 ± 0.024, average bifurcation angle was 28.2 ± 15.1°, and average Murray's law exponent was 2.92 ± 1.07. We report a set of scaling laws for vessel diameter and length, along with other morphometric information. These provide an initial understanding of healthy structural preacinar PA development with age, which can be used for computational modeling studies and comparison with diseased PA anatomy.NEW & NOTEWORTHY Pulmonary artery (PA) morphometry studies to date have focused primarily on large arteries and intra-acinar arteries in either adults or children, neglecting preacinar arteries in both populations. Our study is the first to quantify in vivo preacinar PA morphometry changes spanning infants to adults. For preacinar arteries > 1 mm in diameter, we identify scaling laws for vessel diameters and lengths with patient metrics of growth and establish a healthy PA morphometry baseline for most preacinar PAs.
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Affiliation(s)
- Melody Dong
- Department of Bioengineering, Stanford University, Stanford, California
| | - Weiguang Yang
- Department of Pediatrics-Cardiology, Stanford University, Stanford, California
| | - John S Tamaresis
- Department of Biomedical Data Science, Stanford University, Stanford, California
| | - Frandics P Chan
- Department of Radiology, Stanford University, Stanford, California
| | - Evan J Zucker
- Department of Radiology, Stanford University, Stanford, California
| | - Sahana Kumar
- Department of Pediatrics-Cardiology, Stanford University, Stanford, California
| | - Marlene Rabinovitch
- Department of Pediatrics-Cardiology, Stanford University, Stanford, California
| | - Alison L Marsden
- Department of Bioengineering, Stanford University, Stanford, California.,Department of Pediatrics-Cardiology, Stanford University, Stanford, California
| | - Jeffrey A Feinstein
- Department of Bioengineering, Stanford University, Stanford, California.,Department of Pediatrics-Cardiology, Stanford University, Stanford, California
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19
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Topping GJ, Hundshammer C, Nagel L, Grashei M, Aigner M, Skinner JG, Schulte RF, Schilling F. Acquisition strategies for spatially resolved magnetic resonance detection of hyperpolarized nuclei. MAGMA (NEW YORK, N.Y.) 2020; 33:221-256. [PMID: 31811491 PMCID: PMC7109201 DOI: 10.1007/s10334-019-00807-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 10/08/2019] [Accepted: 11/21/2019] [Indexed: 12/13/2022]
Abstract
Hyperpolarization is an emerging method in magnetic resonance imaging that allows nuclear spin polarization of gases or liquids to be temporarily enhanced by up to five or six orders of magnitude at clinically relevant field strengths and administered at high concentration to a subject at the time of measurement. This transient gain in signal has enabled the non-invasive detection and imaging of gas ventilation and diffusion in the lungs, perfusion in blood vessels and tissues, and metabolic conversion in cells, animals, and patients. The rapid development of this method is based on advances in polarizer technology, the availability of suitable probe isotopes and molecules, improved MRI hardware and pulse sequence development. Acquisition strategies for hyperpolarized nuclei are not yet standardized and are set up individually at most sites depending on the specific requirements of the probe, the object of interest, and the MRI hardware. This review provides a detailed introduction to spatially resolved detection of hyperpolarized nuclei and summarizes novel and previously established acquisition strategies for different key areas of application.
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Affiliation(s)
- Geoffrey J Topping
- Department of Nuclear Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Christian Hundshammer
- Department of Nuclear Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Luca Nagel
- Department of Nuclear Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Martin Grashei
- Department of Nuclear Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Maximilian Aigner
- Department of Nuclear Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Jason G Skinner
- Department of Nuclear Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | | | - Franz Schilling
- Department of Nuclear Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
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20
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Schulte H, Mühlfeld C, Brandenberger C. Age-Related Structural and Functional Changes in the Mouse Lung. Front Physiol 2019; 10:1466. [PMID: 31866873 PMCID: PMC6904284 DOI: 10.3389/fphys.2019.01466] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Accepted: 11/14/2019] [Indexed: 01/01/2023] Open
Abstract
Lung function declines with advancing age. To improve our understanding of the structure-function relationships leading to this decline, we investigated structural alterations in the lung and their impact on micromechanics and lung function in the aging mouse. Lung function analysis was performed in 3, 6, 12, 18, and 24 months old C57BL/6 mice (n = 7-8/age), followed by lung fixation and stereological sample preparation. Lung parenchymal volume, total, ductal and alveolar airspace volume, alveolar volume and number, septal volume, septal surface area and thickness were quantified by stereology as well as surfactant producing alveolar epithelial type II (ATII) cell volume and number. Parenchymal volume, total and ductal airspace volume increased in old (18 and 24 months) compared with middle-aged (6 and 12 months) and young (3 months) mice. While the alveolar number decreased from young (7.5 × 106) to middle-aged (6 × 106) and increased again in old (9 × 106) mice, the mean alveolar volume and mean septal surface area per alveolus conversely first increased in middle-aged and then declined in old mice. The ATII cell number increased from middle-aged (8.8 × 106) to old (11.8 × 106) mice, along with the alveolar number, resulting in a constant ratio of ATII cells per alveolus in all age groups (1.4 ATII cells per alveolus). Lung compliance and inspiratory capacity increased, whereas tissue elastance and tissue resistance decreased with age, showing greatest changes between young and middle-aged mice. In conclusion, alveolar size declined significantly in old mice concomitant with a widening of alveolar ducts and late alveolarization. These changes may partly explain the functional alterations during aging. Interestingly, despite age-related lung remodeling, the number of ATII cells per alveolus showed a tightly controlled relation in all age groups.
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Affiliation(s)
- Henri Schulte
- Institute of Functional and Applied Anatomy, Hannover Medical School, Hanover, Germany
| | - Christian Mühlfeld
- Institute of Functional and Applied Anatomy, Hannover Medical School, Hanover, Germany.,Cluster of Excellence REBIRTH (From Regenerative Biology to Reconstructive Therapy), Hanover, Germany.,Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Member of the German Center for Lung Research (DZL), Hanover, Germany
| | - Christina Brandenberger
- Institute of Functional and Applied Anatomy, Hannover Medical School, Hanover, Germany.,Cluster of Excellence REBIRTH (From Regenerative Biology to Reconstructive Therapy), Hanover, Germany.,Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Member of the German Center for Lung Research (DZL), Hanover, Germany
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21
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Ouriadov A, Guo F, McCormack DG, Parraga G. Accelerated 129 Xe MRI morphometry of terminal airspace enlargement: Feasibility in volunteers and those with alpha-1 antitrypsin deficiency. Magn Reson Med 2019; 84:416-426. [PMID: 31765497 DOI: 10.1002/mrm.28091] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Revised: 10/29/2019] [Accepted: 10/30/2019] [Indexed: 12/21/2022]
Abstract
PURPOSE Multi-b diffusion-weighted hyperpolarized inhaled-gas MRI provides imaging biomarkers of terminal airspace enlargement including ADC and mean linear intercept (Lm ), but clinical translation has been limited because image acquisition requires relatively long or multiple breath-holds that are not well-tolerated by patients. Therefore, we aimed to accelerate single breath-hold 3D multi-b diffusion-weighted 129 Xe MRI, using k-space undersampling in imaging direction using a different undersampling pattern for different b-values combined with the stretched exponential model to generate maps of ventilation, apparent transverse relaxation time constant ( T 2 ∗ ), ADC, and Lm values in a single, short breath-hold; accelerated and non-accelerated measurements were directly compared. METHODS We evaluated multi-b (0, 12, 20, 30, and 45.5 s/cm2 ) diffusion-weighted 129 Xe T 2 ∗ /ADC/morphometry estimates using acceleration factor (AF = 1 and 7) and multi-breath sampling in 3 volunteers (HV), and 6 participants with alpha-1 antitrypsin deficiency (AATD). RESULTS For the HV subgroup, mean differences of 5%, 2%, and 8% were observed between fully sampled and undersampled k-space for ADC, Lm , and T 2 ∗ values, respectively. For the AATD subgroup, mean differences were 9%, 6%, and 12% between fully sampled and undersampled k-space for ADC, Lm and T 2 ∗ values, respectively. Although mean differences of 1% and 4.5% were observed between accelerated and multi-breath sampled ADC and Lm values, respectively, mean ADC/Lm estimates were not significantly different from corresponding mean ADCM /Lm M or mean ADCA /Lm A estimates (all P > 0.60 , A = undersampled and M = multi-breath sampled). CONCLUSIONS Accelerated multi-b diffusion-weighted 129 Xe MRI is feasible at AF = 7 for generating pulmonary ADC and Lm in AATD and normal lung.
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Affiliation(s)
- Alexei Ouriadov
- Department of Physics and Astronomy, The University of Western Ontario, London, Canada.,Lawson Health Research Institute, London, Canada
| | - Fumin Guo
- Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - David G McCormack
- Division of Respirology, Department of Medicine, The University of Western Ontario, London, Canada
| | - Grace Parraga
- Division of Respirology, Department of Medicine, The University of Western Ontario, London, Canada.,Robarts Research Institute, The University of Western Ontario, London, Canada.,Department of Medical Biophysics, The University of Western Ontario, London, Canada
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22
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Abstract
People worldwide are living longer, and it is estimated that by 2050, the proportion of the world's population over 60 years of age will nearly double. Natural lung aging is associated with molecular and physiological changes that cause alterations in lung function, diminished pulmonary remodeling and regenerative capacity, and increased susceptibility to acute and chronic lung diseases. As the aging population rapidly grows, it is essential to examine how alterations in cellular function and cell-to-cell interactions of pulmonary resident cells and systemic immune cells contribute to a higher risk of increased susceptibility to infection and development of chronic diseases, such as chronic obstructive pulmonary disease and interstitial pulmonary fibrosis. This review provides an overview of physiological, structural, and cellular changes in the aging lung and immune system that facilitate the development and progression of disease.
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Affiliation(s)
- Soo Jung Cho
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA;
| | - Heather W Stout-Delgado
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA;
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23
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Using Hyperpolarized Xenon-129 MRI to Quantify Early-Stage Lung Disease in Smokers. Acad Radiol 2019; 26:355-366. [PMID: 30522808 DOI: 10.1016/j.acra.2018.11.005] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Revised: 09/04/2018] [Accepted: 11/16/2018] [Indexed: 12/25/2022]
Abstract
RATIONALE AND OBJECTIVES Hyperpolarized xenon-129 magnetic resonance (MR) provides sensitive tools that may detect early stages of lung disease in smokers before it has progressed to chronic obstructive pulmonary disease (COPD) apparent to conventional spirometric measures. We hypothesized that the functional alveolar wall thickness as assessed by hyperpolarized xenon-129 MR spectroscopy would be elevated in clinically healthy smokers before xenon MR diffusion measurements would indicate emphysematous tissue destruction. MATERIALS AND METHODS Using hyperpolarized xenon-129 MR we measured the functional septal wall thickness and apparent diffusion coefficient of the gas phase in 16 subjects with smoking-related COPD, 9 clinically healthy current or former smokers, and 10 healthy never smokers. All subjects were age-matched and characterized by conventional pulmonary function tests. A total of 11 data sets from younger healthy never smokers were added to determine the age dependence of the septal wall thickness measurements. RESULTS In healthy never smokers the septal wall thickness increased by 0.04 μm per year of age. The healthy smoker cohort exhibited normal pulmonary function test measures that did not significantly differ from the never-smoker cohort. The age-corrected septal wall thickness correlated well with diffusion capacity for carbon monoxide (R2 = 0.56) and showed a highly significant difference between healthy subjects and COPD patients (8.8 μm vs 12.3 μm; p < 0.001), but was the only measure that actually discriminated healthy subjects from healthy smokers (8.8 μm vs 10.6 μm; p < 0.006). CONCLUSION Functional alveolar wall thickness assessed by hyperpolarized xenon-129 MR allows discrimination between healthy subjects and healthy smokers and could become a powerful new measure of early-stage lung disease.
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24
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Aghasafari P, Heise RL, Reynolds A, Pidaparti RM. Aging Effects on Alveolar Sacs Under Mechanical Ventilation. J Gerontol A Biol Sci Med Sci 2019; 74:139-146. [PMID: 29746613 PMCID: PMC6333941 DOI: 10.1093/gerona/gly097] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Accepted: 04/26/2018] [Indexed: 11/14/2022] Open
Abstract
Alveolar sacs are primarily responsible for gas exchange in the human respiratory system and lose their functionality with aging. Three-dimensional (3D) models of young and old human alveolar sacs were constructed and fluid-solid interaction was employed to investigate the contribution of age-related changes to decline in alveolar sacs function under mechanical ventilation (MV). Simulation results illustrated that compliance and pressure reduced in the alveolar sacs of the elderly adults, and they have to work harder to breathe. Morphological changes were found to be mainly responsible for the decline in alveolar sacs function. Influence of individual differences on the alveolar sacs function was negligible and 95% confidence intervals for compliance and work of breathing (WOB) using measures from different individuals also support this finding. Moreover, higher mortality risk was recorded for elderly adults who undergo MV. Specifically, ventilator devices setting has been identified as a potential parameter for compromising respiratory function in the elderly adults. Volume-controlled ventilation applied less pressure, whereas, pressure-controlled ventilation resulted in higher compliance in the alveolar sacs and decreased WOB. Sensitivity of alveolar sacs to ventilator setting under the volume-controlled mode illustrated that increasing breathing frequency and decreasing the ratio of inhalation to exhalation times and TV caused an increase in alveolar sacs expansion and compliance in older patients. Results from this study can help clinicians to develop individualized and effective ventilator protocols and to improve respiratory function in the elderly adults.
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Affiliation(s)
- Parya Aghasafari
- Department of Mechanical Engineering, University of Georgia, Athens
| | - Rebeca L Heise
- Department of Biomedical Engineering, Virginia Commonwealth University, Richmond
- VCU Johnson Center for Critical Care and Pulmonary Research, Virginia Commonwealth University, Richmond
| | - Angela Reynolds
- Department of Mathematics & Applied Mathematics, Virginia Commonwealth University, Richmond
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25
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Westcott A, McCormack DG, Parraga G, Ouriadov A. Advanced pulmonary MRI to quantify alveolar and acinar duct abnormalities: Current status and future clinical applications. J Magn Reson Imaging 2019; 50:28-40. [PMID: 30637857 DOI: 10.1002/jmri.26623] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2018] [Revised: 12/04/2018] [Accepted: 12/05/2018] [Indexed: 12/23/2022] Open
Abstract
There are serious clinical gaps in our understanding of chronic lung disease that require novel, sensitive, and noninvasive in vivo measurements of the lung parenchyma to measure disease pathogenesis and progressive changes over time as well as response to treatment. Until recently, our knowledge and appreciation of the tissue changes that accompany lung disease has depended on ex vivo biopsy and concomitant histological and stereological measurements. These measurements have revealed the underlying pathologies that drive lung disease and have provided important observations about airway occlusion, obliteration of the terminal bronchioles and airspace enlargement, or fibrosis and their roles in disease initiation and progression. ex vivo tissue stereology and histology are the established gold standards and, more recently, micro-computed tomography (CT) measurements of ex vivo tissue samples has also been employed to reveal new mechanistic findings about the progression of obstructive lung disease in patients. While these approaches have provided important understandings using ex vivo analysis of excised samples, recently developed hyperpolarized noble gas MRI methods provide an opportunity to noninvasively measure acinar duct and terminal airway dimensions and geometry in vivo, and, without radiation burden. Therefore, in this review we summarize emerging pulmonary MRI morphometry methods that provide noninvasive in vivo measurements of the lung in patients with bronchopulmonary dysplasia and chronic obstructive pulmonary disease, among others. We discuss new findings, future research directions, as well as clinical opportunities to address current gaps in patient care and for testing of new therapies. Level of Evidence: 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019;50:28-40.
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Affiliation(s)
- Andrew Westcott
- Robarts Research Institute, University of Western Ontario, London, Canada.,Department of Medical Biophysics, University of Western Ontario, London, Canada
| | - David G McCormack
- Division of Respirology, Department of Medicine, University of Western Ontario, London, Canada
| | - Grace Parraga
- Robarts Research Institute, University of Western Ontario, London, Canada.,Department of Medical Biophysics, University of Western Ontario, London, Canada.,Division of Respirology, Department of Medicine, University of Western Ontario, London, Canada
| | - Alexei Ouriadov
- Department of Physics and Astronomy, University of Western Ontario, London, Canada
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26
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Zhang H, Xie J, Xiao S, Zhao X, Zhang M, Shi L, Wang K, Wu G, Sun X, Ye C, Zhou X. Lung morphometry using hyperpolarized
129
Xe multi‐
b
diffusion
MRI
with compressed sensing in healthy subjects and patients with
COPD. Med Phys 2018; 45:3097-3108. [DOI: 10.1002/mp.12944] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2017] [Revised: 04/18/2018] [Accepted: 04/19/2018] [Indexed: 12/11/2022] Open
Affiliation(s)
- Huiting Zhang
- School of Physics Huazhong University of Science and Technology Wuhan 430074China
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics National Center for Magnetic Resonance in Wuhan Wuhan Institute of Physics and Mathematics Chinese Academy of Sciences Wuhan 430071China
| | - Junshuai Xie
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics National Center for Magnetic Resonance in Wuhan Wuhan Institute of Physics and Mathematics Chinese Academy of Sciences Wuhan 430071China
| | - Sa Xiao
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics National Center for Magnetic Resonance in Wuhan Wuhan Institute of Physics and Mathematics Chinese Academy of Sciences Wuhan 430071China
| | - Xiuchao Zhao
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics National Center for Magnetic Resonance in Wuhan Wuhan Institute of Physics and Mathematics Chinese Academy of Sciences Wuhan 430071China
| | - Ming Zhang
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics National Center for Magnetic Resonance in Wuhan Wuhan Institute of Physics and Mathematics Chinese Academy of Sciences Wuhan 430071China
| | - Lei Shi
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics National Center for Magnetic Resonance in Wuhan Wuhan Institute of Physics and Mathematics Chinese Academy of Sciences Wuhan 430071China
| | - Ke Wang
- Department of Magnetic Resonance Imaging Zhongnan Hospital of Wuhan University Wuhan 430071 China
| | - Guangyao Wu
- Department of Magnetic Resonance Imaging Zhongnan Hospital of Wuhan University Wuhan 430071 China
| | - Xianping Sun
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics National Center for Magnetic Resonance in Wuhan Wuhan Institute of Physics and Mathematics Chinese Academy of Sciences Wuhan 430071China
| | - Chaohui Ye
- School of Physics Huazhong University of Science and Technology Wuhan 430074China
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics National Center for Magnetic Resonance in Wuhan Wuhan Institute of Physics and Mathematics Chinese Academy of Sciences Wuhan 430071China
| | - Xin Zhou
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics National Center for Magnetic Resonance in Wuhan Wuhan Institute of Physics and Mathematics Chinese Academy of Sciences Wuhan 430071China
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27
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Hecker L. Mechanisms and consequences of oxidative stress in lung disease: therapeutic implications for an aging populace. Am J Physiol Lung Cell Mol Physiol 2017; 314:L642-L653. [PMID: 29351446 DOI: 10.1152/ajplung.00275.2017] [Citation(s) in RCA: 80] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
The rapid expansion of the elderly population has led to the recent epidemic of age-related diseases, including increased incidence and mortality of chronic and acute lung diseases. Numerous studies have implicated aging and oxidative stress in the pathogenesis of various pulmonary diseases; however, despite recent advances in these fields, the specific contributions of aging and oxidative stress remain elusive. This review will discuss the consequences of aging on lung morphology and physiology, and how redox imbalance with aging contributes to lung disease susceptibility. Here, we focus on three lung diseases for which aging is a significant risk factor: acute respiratory distress syndrome (ARDS), chronic obstructive pulmonary disease (COPD), and idiopathic pulmonary fibrosis (IPF). Preclinical and clinical development for redox- and senescence-altering therapeutic strategies are discussed, as well as scientific advancements that may direct current and future therapeutic development. A deeper understanding of how aging impacts normal lung function, redox balance, and injury-repair processes will inspire the development of new therapies to prevent and/or reverse age-associated pulmonary diseases, and ultimately increase health span and longevity. This review is intended to encourage basic, clinical, and translational research that will bridge knowledge gaps at the intersection of aging, oxidative stress, and lung disease to fuel the development of more effective therapeutic strategies for lung diseases that disproportionately afflict the elderly.
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Affiliation(s)
- Louise Hecker
- Division of Pulmonary, Allergy and Critical Care and Sleep Medicine, University of Arizona , Tucson, Arizona and Southern Arizona Veterans Affairs Health Care System, Tucson, Arizona
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28
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Hoffman EA, Weibel ER. Multiscale Lung Imaging Provides New Insights into Disease Progression in the Chronic Obstructive Pulmonary Disease Lung. Am J Respir Crit Care Med 2017; 195:551-552. [PMID: 28248140 DOI: 10.1164/rccm.201611-2323ed] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Affiliation(s)
- Eric A Hoffman
- 1 Department of Radiology.,2 Department of Medicine.,3 Department of Biomedical Engineering University of Iowa Iowa City, Iowa and
| | - Ewald R Weibel
- 4 Institute of Anatomy University of Bern Bern, Switzerland
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29
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Lessard E, Young HM, Bhalla A, Pike D, Sheikh K, McCormack DG, Ouriadov A, Parraga G. Pulmonary 3He Magnetic Resonance Imaging Biomarkers of Regional Airspace Enlargement in Alpha-1 Antitrypsin Deficiency. Acad Radiol 2017. [PMID: 28645458 DOI: 10.1016/j.acra.2017.05.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
RATIONALE AND OBJECTIVES Thoracic x-ray computed tomography (CT) and hyperpolarized 3He magnetic resonance imaging (MRI) provide quantitative measurements of airspace enlargement in patients with emphysema. For patients with panlobular emphysema due to alpha-1 antitrypsin deficiency (AATD), sensitive biomarkers of disease progression and response to therapy have been difficult to develop and exploit, especially those biomarkers that correlate with outcomes like quality of life. Here, our objective was to generate and compare CT and diffusion-weighted inhaled-gas MRI measurements of emphysema including apparent diffusion coefficient (ADC) and MRI-derived mean linear intercept (Lm) in patients with AATD, chronic obstructive pulmonary disease (COPD) ex-smokers, and elderly never-smokers. MATERIALS AND METHODS We enrolled patients with AATD (n = 8; 57 ± 7 years), ex-smokers with COPD (n = 8; 77 ± 6 years), and a control group of never-smokers (n = 5; 64 ± 2 years) who underwent thoracic CT, MRI, spirometry, plethysmography, the St. George's Respiratory Questionnaire, and the 6-minute walk test during a single 2-hour visit. MRI-derived ADC, Lm, surface-to-volume ratio, and ventilation defect percent were generated for the apical, basal, and whole lung as was CT lung area ≤-950 Hounsfield units (RA950), low attenuating clusters, and airway count. RESULTS In patients with AATD, there was a significantly different MRI-derived ADC (P = .03), Lm (P < .0001), and surface-to-volume ratio (P < .0001), but not diffusing capacity of carbon monoxide, residual volume or total lung capacity, or CT RA950 (P > .05) compared to COPD ex-smokers with a significantly different St. George's Respiratory Questionnaire. CONCLUSIONS In this proof-of-concept demonstration, we evaluated CT and MRI lung emphysema measurements and observed significantly worse MRI biomarkers of emphysema in patients with AATD compared to patients with COPD, although CT RA950 and diffusing capacity of carbon monoxide were not significantly different, underscoring the sensitivity of MRI measurements of AATD emphysema.
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Affiliation(s)
- Eric Lessard
- Robarts Research Institute, 1151 Richmond Street North, London, ON, Canada N6A 5B7; Department of Medical Biophysics, The University of Western Ontario, 1151 Richmond St North, London, ON, Canada N6A 5C1
| | - Heather M Young
- Robarts Research Institute, 1151 Richmond Street North, London, ON, Canada N6A 5B7; Department of Medical Biophysics, The University of Western Ontario, 1151 Richmond St North, London, ON, Canada N6A 5C1
| | - Anurag Bhalla
- Robarts Research Institute, 1151 Richmond Street North, London, ON, Canada N6A 5B7
| | - Damien Pike
- Robarts Research Institute, 1151 Richmond Street North, London, ON, Canada N6A 5B7; Department of Medical Biophysics, The University of Western Ontario, 1151 Richmond St North, London, ON, Canada N6A 5C1
| | - Khadija Sheikh
- Robarts Research Institute, 1151 Richmond Street North, London, ON, Canada N6A 5B7; Department of Medical Biophysics, The University of Western Ontario, 1151 Richmond St North, London, ON, Canada N6A 5C1
| | - David G McCormack
- Division of Respirology, Department of Medicine, The University of Western Ontario, London, Ontario, Canada
| | - Alexei Ouriadov
- Robarts Research Institute, 1151 Richmond Street North, London, ON, Canada N6A 5B7; Department of Medical Biophysics, The University of Western Ontario, 1151 Richmond St North, London, ON, Canada N6A 5C1
| | - Grace Parraga
- Robarts Research Institute, 1151 Richmond Street North, London, ON, Canada N6A 5B7; Department of Medical Biophysics, The University of Western Ontario, 1151 Richmond St North, London, ON, Canada N6A 5C1.
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30
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Chan HF, Stewart NJ, Norquay G, Collier GJ, Wild JM. 3D diffusion-weighted 129 Xe MRI for whole lung morphometry. Magn Reson Med 2017; 79:2986-2995. [PMID: 29034509 PMCID: PMC5888195 DOI: 10.1002/mrm.26960] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2017] [Revised: 09/14/2017] [Accepted: 09/19/2017] [Indexed: 12/27/2022]
Abstract
Purpose To obtain whole lung morphometry measurements from 129Xe in a single breath‐hold with 3D multiple b‐value 129Xe diffusion‐weighted MRI (DW‐MRI) with an empirically optimized diffusion time and compressed sensing for scan acceleration. Methods Prospective three‐fold undersampled 3D multiple b‐value hyperpolarized 129Xe DW‐MRI datasets were acquired, and the diffusion time (Δ) was iterated so as to provide diffusive length scale (LmD) estimates from the stretched exponential model (SEM) that are comparable to those from 3He. The empirically optimized 129Xe diffusion time was then implemented with a four‐fold undersampling scheme and was prospectively benchmarked against 3He measurements in a cohort of five healthy volunteers, six ex‐smokers, and two chronic obstructive pulmonary disease patients using both SEM‐derived LmD and cylinder model (CM)‐derived mean chord length (Lm). Results Good agreement between the mean 129Xe and 3He LmD (mean difference, 2.2%) and Lm (mean difference, 1.1%) values was obtained in all subjects at an empirically optimized 129Xe Δ = 8.5 ms. Conclusion Compressed sensing has facilitated single‐breath 3D multiple b‐value 129Xe DW‐MRI acquisitions, and results at 129Xe Δ = 8.5 ms indicate that 129Xe provides a viable alternative to 3He for whole lung morphometry mapping with either the SEM or CM. Magn Reson Med 79:2986–2995, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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Affiliation(s)
- Ho-Fung Chan
- POLARIS, Academic Unit of Radiology, University of Sheffield, Sheffield, UK
| | - Neil J Stewart
- POLARIS, Academic Unit of Radiology, University of Sheffield, Sheffield, UK
| | - Graham Norquay
- POLARIS, Academic Unit of Radiology, University of Sheffield, Sheffield, UK
| | - Guilhem J Collier
- POLARIS, Academic Unit of Radiology, University of Sheffield, Sheffield, UK
| | - Jim M Wild
- POLARIS, Academic Unit of Radiology, University of Sheffield, Sheffield, UK
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Zhong J, Zhang H, Ruan W, Xie J, Li H, Deng H, Han Y, Sun X, Ye C, Zhou X. Simultaneous assessment of both lung morphometry and gas exchange function within a single breath-hold by hyperpolarized 129 Xe MRI. NMR IN BIOMEDICINE 2017; 30:e3730. [PMID: 28508450 DOI: 10.1002/nbm.3730] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2016] [Revised: 03/13/2017] [Accepted: 03/14/2017] [Indexed: 06/07/2023]
Abstract
During the measurement of hyperpolarized 129 Xe magnetic resonance imaging (MRI), the diffusion-weighted imaging (DWI) technique provides valuable information for the assessment of lung morphometry at the alveolar level, whereas the chemical shift saturation recovery (CSSR) technique can evaluate the gas exchange function of the lungs. To date, the two techniques have only been performed during separate breaths. However, the request for multiple breaths increases the cost and scanning time, limiting clinical application. Moreover, acquisition during separate breath-holds will increase the measurement error, because of the inconsistent physiological status of the lungs. Here, we present a new method, referred to as diffusion-weighted chemical shift saturation recovery (DWCSSR), in order to perform both DWI and CSSR within a single breath-hold. Compared with sequential single-breath schemes (namely the 'CSSR + DWI' scheme and the 'DWI + CSSR' scheme), the DWCSSR scheme is able to significantly shorten the breath-hold time, as well as to obtain high signal-to-noise ratio (SNR) signals in both DWI and CSSR data. This scheme enables comprehensive information on lung morphometry and function to be obtained within a single breath-hold. In vivo experimental results demonstrate that DWCSSR has great potential for the evaluation and diagnosis of pulmonary diseases.
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Affiliation(s)
- Jianping Zhong
- School of Physics, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China
| | - Huiting Zhang
- School of Physics, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China
| | - Weiwei Ruan
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China
| | - Junshuai Xie
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China
| | - Haidong Li
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China
| | - He Deng
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China
| | - Yeqing Han
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China
| | - Xianping Sun
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China
| | - Chaohui Ye
- School of Physics, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China
| | - Xin Zhou
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China
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Sheikh K, Bhalla A, Ouriadov A, Young HM, Yamashita CM, Luu TM, Katz S, Parraga G. Pulmonary magnetic resonance imaging biomarkers of lung structure and function in adult survivors of bronchopulmonary dysplasia with COPD. COGENT MEDICINE 2017. [DOI: 10.1080/2331205x.2017.1282033] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
Affiliation(s)
- Khadija Sheikh
- Robarts Research Institute, The University of Western Ontario, 1151 Richmond St, London, Canada N6A 5B7
- Department of Medical Biophysics, The University of Western Ontario, 1151 Richmond St, London, Canada N6A 5B7
| | - Anurag Bhalla
- Robarts Research Institute, The University of Western Ontario, 1151 Richmond St, London, Canada N6A 5B7
| | - Alexei Ouriadov
- Robarts Research Institute, The University of Western Ontario, 1151 Richmond St, London, Canada N6A 5B7
| | - Heather M. Young
- Robarts Research Institute, The University of Western Ontario, 1151 Richmond St, London, Canada N6A 5B7
- Department of Medical Biophysics, The University of Western Ontario, 1151 Richmond St, London, Canada N6A 5B7
| | - Cory M. Yamashita
- Division of Respirology, Department of Medicine, The University of Western Ontario, 1151 Richmond St, London, Canada N6A 5B7
| | - Thuy Mai Luu
- Department of Pediatrics, CHU Sainte Justine, Université de Montréal, Montréal, Canada
| | - Sherri Katz
- Children’s Hospital of Eastern Ontario, University of Ottawa, Ottawa, Canada
| | - Grace Parraga
- Robarts Research Institute, The University of Western Ontario, 1151 Richmond St, London, Canada N6A 5B7
- Department of Medical Biophysics, The University of Western Ontario, 1151 Richmond St, London, Canada N6A 5B7
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Ruan W, Zhong J, Wang K, Wu G, Han Y, Sun X, Ye C, Zhou X. Detection of the mild emphysema by quantification of lung respiratory airways with hyperpolarized xenon diffusion MRI. J Magn Reson Imaging 2016; 45:879-888. [PMID: 27472552 DOI: 10.1002/jmri.25408] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2016] [Accepted: 07/15/2016] [Indexed: 11/06/2022] Open
Abstract
PURPOSE To demonstrate the feasibility to quantify the lung respiratory airway in vivo with hyperpolarized xenon diffusion magnetic resonance imaging (MRI), which is able to detect mild emphysema in the rat model. MATERIALS AND METHODS The lung respiratory airways were quantified in vivo using hyperpolarized xenon diffusion MRI (7T) with eight b values (5, 10, 15, 20, 25, 30, 35, 40 s/cm2 ) in five control rats and five mild emphysematous rats, which were induced by elastase. The morphological results from histology were acquired and used for comparison. RESULTS The parameters DL (longitudinal diffusion coefficient), r (internal radius), h (alveolar sleeve depth), Lm (mean linear intercept), and S/V (surface area to lung volume ratio) derived from the hyperpolarized xenon diffusion MRI in the emphysematous group showed significant differences from those in the control group (P < 0.05). Additionally, these parameters correlated well with the Lm obtained by the traditional histological sections (Pearson's correlation coefficients >0.8). CONCLUSION The lung respiratory airways can be quantified by hyperpolarized xenon diffusion MRI, showing the potential for mild emphysema diagnosis. Also, the study suggested that the hyperpolarized xenon DL is more sensitive than DT (transverse diffusion coefficient) to detect mild emphysema. LEVEL OF EVIDENCE 1 J. Magn. Reson. Imaging 2017;45:879-888.
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Affiliation(s)
- Weiwei Ruan
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, P.R. China
| | - Jianping Zhong
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, P.R. China
| | - Ke Wang
- Department of Magnetic Resonance Imaging, Zhongnan Hospital of Wuhan University, Wuhan, P.R. China
| | - Guangyao Wu
- Department of Magnetic Resonance Imaging, Zhongnan Hospital of Wuhan University, Wuhan, P.R. China
| | - Yeqing Han
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, P.R. China
| | - Xianping Sun
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, P.R. China
| | - Chaohui Ye
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, P.R. China
| | - Xin Zhou
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, P.R. China
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