Quantification of lung PET images: Challenges and opportunities

Delphine L. Chen, Joseph Cheriyan, Edwin R. Chilvers, Gourab Choudhury, Christopher Coello, Martin Connell, Marie Fisk, Ashley M. Groves, Roger N. Gunn, Beverley F. Holman, Brian F. Hutton, Sarah Lee, William MacNee, Divya Mohan, David Parr, Deepak Subramanian, Ruth Tal-Singer, Kris Thielemans, Edwin J.R. Van Beek, Laurence VassJeremy W. Wellen, Ian Wilkinson, Frederick J. Wilson

Research output: Contribution to journalArticlepeer-review

60 Scopus citations

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 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.

Original languageEnglish
Pages (from-to)201-207
Number of pages7
JournalJournal of Nuclear Medicine
Volume58
Issue number2
DOIs
StatePublished - Feb 1 2017

Keywords

  • Lung inflammation
  • Molecular imaging
  • Positron emission tomography
  • Pulmonary

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