Quantification of Lung PET Images: Challenges and Opportunities
Millions of people are affected by respiratory diseases, leading to a significant health burden globally. Because of the current insufficient knowledge of the underlying mechanisms that lead to the development and progression of respiratory diseases, treatment options remain limited. To overcome thi...
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Published in | Journal of Nuclear Medicine Vol. 58; no. 2; pp. 201 - 207 |
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Main Authors | , , , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
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United States
Society of Nuclear Medicine
01.02.2017
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Abstract | Millions of people are affected by respiratory diseases, leading to a significant health burden globally. Because of the current insufficient knowledge of the underlying mechanisms that lead to the development and progression of respiratory diseases, treatment options remain limited. To overcome this limitation and understand the associated molecular changes, noninvasive imaging techniques such as PET and SPECT have been explored for biomarker development, with
F-FDG PET imaging being the most studied. The quantification of pulmonary molecular imaging data remains challenging because of variations in tissue, air, blood, and water fractions within the lungs. The proportions of these components further differ depending on the lung disease. Therefore, different quantification approaches have been proposed to address these variabilities. However, no standardized approach has been developed to date. This article reviews the data evaluating
F-FDG PET quantification approaches in lung diseases, focusing on methods to account for variations in lung components and the interpretation of the derived parameters. The diseases reviewed include acute respiratory distress syndrome, chronic obstructive pulmonary disease, and interstitial lung diseases such as idiopathic pulmonary fibrosis. Based on review of prior literature, ongoing research, and discussions among the authors, suggested considerations are presented to assist with the interpretation of the derived parameters from these approaches and the design of future studies. |
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AbstractList | Millions of people are affected by respiratory diseases, leading to a significant health burden globally. Because of the current insufficient knowledge of the underlying mechanisms that lead to the development and progression of respiratory diseases, treatment options remain limited. To overcome this limitation and understand the associated molecular changes, noninvasive imaging techniques such as PET and SPECT have been explored for biomarker development, with 18F-FDG PET imaging being the most studied. The quantification of pulmonary molecular imaging data remains challenging because of variations in tissue, air, blood, and water fractions within the lungs. The proportions of these components further differ depending on the lung disease. Therefore, different quantification approaches have been proposed to address these variabilities. However, no standardized approach has been developed to date. This article reviews the data evaluating 18F-FDG PET quantification approaches in lung diseases, focusing on methods to account for variations in lung components and the interpretation of the derived parameters. The diseases reviewed include acute respiratory distress syndrome, chronic obstructive pulmonary disease, and interstitial lung diseases such as idiopathic pulmonary fibrosis. Based on review of prior literature, ongoing research, and discussions among the authors, suggested considerations are presented to assist with the interpretation of the derived parameters from these approaches and the design of future studies. Millions of people are affected by respiratory diseases, leading to a significant health burden globally. Because of the current insufficient knowledge of the underlying mechanisms that lead to the development and progression of respiratory diseases, treatment options remain limited. To overcome this limitation and understand the associated molecular changes, noninvasive imaging techniques such as PET and SPECT have been explored for biomarker development, with 18 F-FDG PET imaging being the most studied. The quantification of pulmonary molecular imaging data remains challenging because of variations in tissue, air, blood, and water fractions within the lungs. The proportions of these components further differ depending on the lung disease. Therefore, different quantification approaches have been proposed to address these variabilities. However, no standardized approach has been developed to date. This article reviews the data evaluating 18 F-FDG PET quantification approaches in lung diseases, focusing on methods to account for variations in lung components and the interpretation of the derived parameters. The diseases reviewed include acute respiratory distress syndrome, chronic obstructive pulmonary disease, and interstitial lung diseases such as idiopathic pulmonary fibrosis. Based on review of prior literature, ongoing research, and discussions among the authors, suggested considerations are presented to assist with the interpretation of the derived parameters from these approaches and the design of future studies. Millions of people are affected by respiratory diseases, leading to a significant health burden globally. Because of the current insufficient knowledge of the underlying mechanisms that lead to the development and progression of respiratory diseases, treatment options remain limited. To overcome this limitation and understand the associated molecular changes, noninvasive imaging techniques such as PET and SPECT have been explored for biomarker development, with 18F-FDG PET imaging being the most studied. The quantification of pulmonary molecular imaging data remains challenging because of variations in tissue, air, blood, and water fractions within the lungs. The proportions of these components further differ depending on the lung disease. Therefore, different quantification approaches have been proposed to address these variabilities. However, no standardized approach has been developed to date. This article reviews the data evaluating 18F-FDG PET quantification approaches in lung diseases, focusing on methods to account for variations in lung components and the interpretation of the derived parameters. The diseases reviewed include acute respiratory distress syndrome, chronic obstructive pulmonary disease, and interstitial lung diseases such as idiopathic pulmonary fibrosis. Based on review of prior literature, ongoing research, and discussions among the authors, suggested considerations are presented to assist with the interpretation of the derived parameters from these approaches and the design of future studies.Millions of people are affected by respiratory diseases, leading to a significant health burden globally. Because of the current insufficient knowledge of the underlying mechanisms that lead to the development and progression of respiratory diseases, treatment options remain limited. To overcome this limitation and understand the associated molecular changes, noninvasive imaging techniques such as PET and SPECT have been explored for biomarker development, with 18F-FDG PET imaging being the most studied. The quantification of pulmonary molecular imaging data remains challenging because of variations in tissue, air, blood, and water fractions within the lungs. The proportions of these components further differ depending on the lung disease. Therefore, different quantification approaches have been proposed to address these variabilities. However, no standardized approach has been developed to date. This article reviews the data evaluating 18F-FDG PET quantification approaches in lung diseases, focusing on methods to account for variations in lung components and the interpretation of the derived parameters. The diseases reviewed include acute respiratory distress syndrome, chronic obstructive pulmonary disease, and interstitial lung diseases such as idiopathic pulmonary fibrosis. Based on review of prior literature, ongoing research, and discussions among the authors, suggested considerations are presented to assist with the interpretation of the derived parameters from these approaches and the design of future studies. Millions of people are affected by respiratory diseases, leading to a significant health burden globally. Because of the current insufficient knowledge of the underlying mechanisms that lead to the development and progression of respiratory diseases, treatment options remain limited. To overcome this limitation and understand the associated molecular changes, noninvasive imaging techniques such as PET and SPECT have been explored for biomarker development, with F-FDG PET imaging being the most studied. The quantification of pulmonary molecular imaging data remains challenging because of variations in tissue, air, blood, and water fractions within the lungs. The proportions of these components further differ depending on the lung disease. Therefore, different quantification approaches have been proposed to address these variabilities. However, no standardized approach has been developed to date. This article reviews the data evaluating F-FDG PET quantification approaches in lung diseases, focusing on methods to account for variations in lung components and the interpretation of the derived parameters. The diseases reviewed include acute respiratory distress syndrome, chronic obstructive pulmonary disease, and interstitial lung diseases such as idiopathic pulmonary fibrosis. Based on review of prior literature, ongoing research, and discussions among the authors, suggested considerations are presented to assist with the interpretation of the derived parameters from these approaches and the design of future studies. |
Author | van Beek, Edwin J.R. Tal-Singer, Ruth Wilson, Frederick J. Mohan, Divya Parr, David Subramanian, Deepak Vass, Laurence Gunn, Roger N. Hutton, Brian F. Groves, Ashley M. MacNee, William Wellen, Jeremy W. Connell, Martin Thielemans, Kris Fisk, Marie Chen, Delphine L. Chilvers, Edwin R. Holman, Beverley F. Lee, Sarah Cheriyan, Joseph Choudhury, Gourab Coello, Christopher Wilkinson, Ian |
Author_xml | – sequence: 1 givenname: Delphine L. surname: Chen fullname: Chen, Delphine L. – sequence: 2 givenname: Joseph surname: Cheriyan fullname: Cheriyan, Joseph – sequence: 3 givenname: Edwin R. surname: Chilvers fullname: Chilvers, Edwin R. – sequence: 4 givenname: Gourab surname: Choudhury fullname: Choudhury, Gourab – sequence: 5 givenname: Christopher surname: Coello fullname: Coello, Christopher – sequence: 6 givenname: Martin surname: Connell fullname: Connell, Martin – sequence: 7 givenname: Marie surname: Fisk fullname: Fisk, Marie – sequence: 8 givenname: Ashley M. surname: Groves fullname: Groves, Ashley M. – sequence: 9 givenname: Roger N. surname: Gunn fullname: Gunn, Roger N. – sequence: 10 givenname: Beverley F. surname: Holman fullname: Holman, Beverley F. – sequence: 11 givenname: Brian F. surname: Hutton fullname: Hutton, Brian F. – sequence: 12 givenname: Sarah surname: Lee fullname: Lee, Sarah – sequence: 13 givenname: William surname: MacNee fullname: MacNee, William – sequence: 14 givenname: Divya surname: Mohan fullname: Mohan, Divya – sequence: 15 givenname: David surname: Parr fullname: Parr, David – sequence: 16 givenname: Deepak surname: Subramanian fullname: Subramanian, Deepak – sequence: 17 givenname: Ruth surname: Tal-Singer fullname: Tal-Singer, Ruth – sequence: 18 givenname: Kris surname: Thielemans fullname: Thielemans, Kris – sequence: 19 givenname: Edwin J.R. surname: van Beek fullname: van Beek, Edwin J.R. – sequence: 20 givenname: Laurence surname: Vass fullname: Vass, Laurence – sequence: 21 givenname: Jeremy W. surname: Wellen fullname: Wellen, Jeremy W. – sequence: 22 givenname: Ian surname: Wilkinson fullname: Wilkinson, Ian – sequence: 23 givenname: Frederick J. surname: Wilson fullname: Wilson, Frederick J. |
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Copyright | 2017 by the Society of Nuclear Medicine and Molecular Imaging. Copyright Society of Nuclear Medicine Feb 1, 2017 2017 by the Society of Nuclear Medicine and Molecular Imaging. 2017 |
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Notes | SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 ObjectType-Review-3 content type line 23 Financial Disclosure: Dr. Cheriyan’s salary is funded in part by GlaxoSmithKline for clinical research. Dr. Lee is a consultant to GlaxoSmithKline. Drs. Mohan and Tal-Singer and Mr. Wilson are employees and shareholders of GlaxoSmithKline. Mr. Wilson was previously a consultant to ECNP R&S, GlaxoSmithKline, IPPEC, King’s College London, Lundbeck A/S, Mentis Cura Ehf, and Pfizer, Inc., and has received travel expenses as a guest speaker from Orion Pharma Ltd. Dr. Wellen is an employee and shareholder of Pfizer. Dr. Gunn is a consultant for Abbvie, Biogen, GlaxoSmithKline, UCB, Roche, and Genentech, S.A. Drs. Groves, Holman, Thielemans, and Hutton have research grants from GlaxoSmithKline and receive funding from the National Institute for Health Research University College London Hospitals Biomedical Research Centre. Dr. Chen receives funding from the National Institutes of Health (R01 HL121218). Drs. Cheriyan and Wilkinson receive funding from the National Institute of Health Research (NIHR) Cambridge Comprehensive Biomedical Research Centre. Dr. Gunn is an employee of Imanova and Imperial College London. Dr. Coello is an employee of Imanova. The authors of this article have indicated no other relevant relationships that could be perceived as a real or apparent conflict of interest. CME Credit: SNMMI is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to sponsor continuing education for physicians. SNMMI designates each JNM continuing education article for a maximum of 2.0 AMA PRA Category 1 Credits. Physicians should claim only credit commensurate with the extent of their participation in the activity. For CE credit, SAM, and other credit types, participants can access this activity through the SNMMI website (http://www.snmmilearningcenter.org) through February 2020. Published online Jan. 12, 2017. Learning Objectives: On successful completion of this activity, participants should be able to (1) describe the methods that have been used to quantify 18F-FDG uptake in the lungs using dynamic PET; (2) discuss the interpretation of the outcomes from these methods; and (3) provide suggested considerations on quantification of 18F-FDG uptake in the lungs for future studies. |
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SubjectTerms | Continuing Education Fluorodeoxyglucose F18 Global health Humans Image Interpretation, Computer-Assisted - methods Knowledge Lung - diagnostic imaging Lung Diseases - diagnostic imaging Medical treatment Nuclear medicine Positron-Emission Tomography - methods Radiopharmaceuticals Reproducibility of Results Respiratory diseases Respiratory Function Tests - methods Sensitivity and Specificity |
Title | Quantification of Lung PET Images: Challenges and Opportunities |
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