| Literature DB >> 33339012 |
Steven R Meikle1,2, Vesna Sossi3, Emilie Roncali4, Simon R Cherry4,5, Richard Banati1,2,6, David Mankoff7, Terry Jones5, Michelle James8,9, Julie Sutcliffe4,10, Jinsong Ouyang11, Yoann Petibon11, Chao Ma11, Georges El Fakhri11, Suleman Surti7, Joel S Karp7, Ramsey D Badawi4,5, Taiga Yamaya12, Go Akamatsu12, Georg Schramm13, Ahmadreza Rezaei13, Johan Nuyts13, Roger Fulton2,14, André Kyme2,15, Cristina Lois11, Hasan Sari16,17, Julie Price16,17, Ronald Boellaard18, Robert Jeraj19,20, Dale L Bailey1,21,22, Enid Eslick21, Kathy P Willowson21,22, Joyita Dutta23.
Abstract
Positron emission tomography (PET) plays an increasingly important role in research and clinical applications, catalysed by remarkable technical advances and a growing appreciation of the need for reliable, sensitive biomarkers of human function in health and disease. Over the last 30 years, a large amount of the physics and engineering effort in PET has been motivated by the dominant clinical application during that period, oncology. This has led to important developments such as PET/CT, whole-body PET, 3D PET, accelerated statistical image reconstruction, and time-of-flight PET. Despite impressive improvements in image quality as a result of these advances, the emphasis on static, semi-quantitative 'hot spot' imaging for oncologic applications has meant that the capability of PET to quantify biologically relevant parameters based on tracer kinetics has not been fully exploited. More recent advances, such as PET/MR and total-body PET, have opened up the ability to address a vast range of new research questions, from which a future expansion of applications and radiotracers appears highly likely. Many of these new applications and tracers will, at least initially, require quantitative analyses that more fully exploit the exquisite sensitivity of PET and the tracer principle on which it is based. It is also expected that they will require more sophisticated quantitative analysis methods than those that are currently available. At the same time, artificial intelligence is revolutionizing data analysis and impacting the relationship between the statistical quality of the acquired data and the information we can extract from the data. In this roadmap, leaders of the key sub-disciplines of the field identify the challenges and opportunities to be addressed over the next ten years that will enable PET to realise its full quantitative potential, initially in research laboratories and, ultimately, in clinical practice.Entities:
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Year: 2021 PMID: 33339012 PMCID: PMC9358699 DOI: 10.1088/1361-6560/abd4f7
Source DB: PubMed Journal: Phys Med Biol ISSN: 0031-9155 Impact factor: 4.174