An update on the use of image-derived input functions for human PET studies: new hopes or old illusions?
Blood sampling
High sensitivity
Image-derived input function
Long axial field of view
Total-body PET
Journal
EJNMMI research
ISSN: 2191-219X
Titre abrégé: EJNMMI Res
Pays: Germany
ID NLM: 101560946
Informations de publication
Date de publication:
10 Nov 2023
10 Nov 2023
Historique:
received:
14
09
2023
accepted:
02
11
2023
medline:
10
11
2023
pubmed:
10
11
2023
entrez:
10
11
2023
Statut:
epublish
Résumé
The need for arterial blood data in quantitative PET research limits the wider usability of this imaging method in clinical research settings. Image-derived input function (IDIF) approaches have been proposed as a cost-effective and non-invasive alternative to gold-standard arterial sampling. However, this approach comes with its own limitations-partial volume effects and radiometabolite correction among the most important-and varying rates of success, and the use of IDIF for brain PET has been particularly troublesome. This paper summarizes the limitations of IDIF methods for quantitative PET imaging and discusses some of the advances that may make IDIF extraction more reliable. The introduction of automated pipelines (both commercial and open-source) for clinical PET scanners is discussed as a way to improve the reliability of IDIF approaches and their utility for quantitative purposes. Survey data gathered from the PET community are then presented to understand whether the field's opinion of the usefulness and validity of IDIF is improving. Finally, as the introduction of next-generation PET scanners with long axial fields of view, ultra-high sensitivity, and improved spatial and temporal resolution, has also brought IDIF methods back into the spotlight, a discussion of the possibilities offered by these state-of-the-art scanners-inclusion of large vessels, less partial volume in small vessels, better description of the full IDIF kinetics, whole-body modeling of radiometabolite production-is included, providing a pathway for future use of IDIF. Improvements in PET scanner technology and software for automated IDIF extraction may allow to solve some of the major limitations associated with IDIF, such as partial volume effects and poor temporal sampling, with the exciting potential for accurate estimation of single kinetic rates. Nevertheless, until individualized radiometabolite correction can be performed effectively, IDIF approaches remain confined at best to a few tracers.
Sections du résumé
BACKGROUND
BACKGROUND
The need for arterial blood data in quantitative PET research limits the wider usability of this imaging method in clinical research settings. Image-derived input function (IDIF) approaches have been proposed as a cost-effective and non-invasive alternative to gold-standard arterial sampling. However, this approach comes with its own limitations-partial volume effects and radiometabolite correction among the most important-and varying rates of success, and the use of IDIF for brain PET has been particularly troublesome.
MAIN BODY
METHODS
This paper summarizes the limitations of IDIF methods for quantitative PET imaging and discusses some of the advances that may make IDIF extraction more reliable. The introduction of automated pipelines (both commercial and open-source) for clinical PET scanners is discussed as a way to improve the reliability of IDIF approaches and their utility for quantitative purposes. Survey data gathered from the PET community are then presented to understand whether the field's opinion of the usefulness and validity of IDIF is improving. Finally, as the introduction of next-generation PET scanners with long axial fields of view, ultra-high sensitivity, and improved spatial and temporal resolution, has also brought IDIF methods back into the spotlight, a discussion of the possibilities offered by these state-of-the-art scanners-inclusion of large vessels, less partial volume in small vessels, better description of the full IDIF kinetics, whole-body modeling of radiometabolite production-is included, providing a pathway for future use of IDIF.
CONCLUSION
CONCLUSIONS
Improvements in PET scanner technology and software for automated IDIF extraction may allow to solve some of the major limitations associated with IDIF, such as partial volume effects and poor temporal sampling, with the exciting potential for accurate estimation of single kinetic rates. Nevertheless, until individualized radiometabolite correction can be performed effectively, IDIF approaches remain confined at best to a few tracers.
Identifiants
pubmed: 37947880
doi: 10.1186/s13550-023-01050-w
pii: 10.1186/s13550-023-01050-w
pmc: PMC10638226
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
97Subventions
Organisme : NIMH NIH HHS
ID : ZIA-MH002852
Pays : United States
Informations de copyright
© 2023. The Author(s).
Références
J Nucl Med. 2009 Mar;50(3):461-7
pubmed: 19223421
EJNMMI Res. 2022 Mar 7;12(1):15
pubmed: 35254514
Eur J Nucl Med Mol Imaging. 2023 Feb;50(3):929-936
pubmed: 36334106
Phys Med Biol. 2018 Feb 13;63(4):045012
pubmed: 29339575
EJNMMI Res. 2021 Apr 1;11(1):35
pubmed: 33796956
Med Phys. 2015 Nov;42(11):6736-44
pubmed: 26520763
EJNMMI Phys. 2020 Nov 23;7(1):67
pubmed: 33226522
Eur J Nucl Med Mol Imaging. 2021 Jan;48(1):21-39
pubmed: 32430580
J Nucl Cardiol. 2010 Aug;17(4):600-16
pubmed: 20387135
J Nucl Med. 2023 Nov;64(11):1821-1830
pubmed: 37591539
PLoS One. 2014 Feb 20;9(2):e89101
pubmed: 24586526
Neuroimage. 2004 Feb;21(2):483-93
pubmed: 14980551
Neuroimage. 2022 Jun;253:119079
pubmed: 35276368
Phys Med Biol. 2018 Jul 24;63(15):155004
pubmed: 29847315
Front Neurosci. 2019 Jul 31;13:782
pubmed: 31417346
Eur J Nucl Med Mol Imaging. 2023 May;50(6):1636-1650
pubmed: 36651951
Annu Int Conf IEEE Eng Med Biol Soc. 2022 Jul;2022:243-246
pubmed: 36085666
Neuroimage. 2012 Aug 1;62(1):199-206
pubmed: 22579604
IEEE Trans Radiat Plasma Med Sci. 2019 May;3(3):334-342
pubmed: 31453423
Phys Med Biol. 2013 Mar 21;58(6):1903-23
pubmed: 23442733
J Cereb Blood Flow Metab. 2021 Sep;41(9):2229-2241
pubmed: 33557691
Med Phys. 2014 Nov;41(11):111907
pubmed: 25370640
Neuroimage. 2022 Aug 1;256:119261
pubmed: 35500806
Stroke. 2006 Apr;37(4):1103-5
pubmed: 16497983
EJNMMI Phys. 2023 Sep 12;10(1):54
pubmed: 37698773
J Cereb Blood Flow Metab. 2011 Oct;31(10):1986-98
pubmed: 21811289
Phys Med Biol. 2007 Dec 7;52(23):7055-71
pubmed: 18029993
Med Phys. 2023 Jan 18;:
pubmed: 36651630
Eur J Nucl Med Mol Imaging. 2021 Dec;48(13):4236-4245
pubmed: 34136956
J Nucl Med. 2013 Apr;54(4):571-7
pubmed: 23447656
Front Physiol. 2023 Mar 22;14:1074052
pubmed: 37035658
EJNMMI Res. 2023 Apr 15;13(1):31
pubmed: 37060394
Eur J Nucl Med Mol Imaging. 2022 May;49(6):1997-2009
pubmed: 34981164
J Nucl Med. 2001 May;42(5):808-17
pubmed: 11337581
EJNMMI Phys. 2016 Dec;3(1):5
pubmed: 26911722
J Cereb Blood Flow Metab. 1998 Jul;18(7):716-23
pubmed: 9663501
Neuroimage. 2021 Jun;233:117950
pubmed: 33716159
IEEE Trans Med Imaging. 2019 Mar;38(3):664-674
pubmed: 30222553
J Nucl Med. 2020 Jan;61(1):144-151
pubmed: 31562224
J Nucl Med. 2008 Feb;49(2):206-15
pubmed: 18199613
Eur J Nucl Med Mol Imaging. 2021 Apr;48(4):1040-1069
pubmed: 33135093
J Nucl Med. 2019 Mar;60(3):299-303
pubmed: 30733314
J Nucl Med. 2014 Dec;55(12):1952-8
pubmed: 25429160
CPT Pharmacometrics Syst Pharmacol. 2013 Jul 10;2:e55
pubmed: 23842098
J Nucl Med. 2012 Feb;53(2):171-81
pubmed: 22228795
Neuroimage. 2021 Aug 15;237:118194
pubmed: 34023451
Sci Transl Med. 2016 Jul 20;8(348):348ra96
pubmed: 27440727
J Cereb Blood Flow Metab. 2018 Jan;38(1):126-135
pubmed: 28155582
J Nucl Med. 2023 Jul;64(7):1154-1161
pubmed: 37116916
J Cereb Blood Flow Metab. 2019 Aug;39(8):1516-1530
pubmed: 29790820
J Nucl Med. 2020 Feb;61(2):285-291
pubmed: 31302637
IEEE Trans Biomed Eng. 2005 Feb;52(2):201-10
pubmed: 15709657
IEEE Trans Radiat Plasma Med Sci. 2020 Nov;4(6):663-675
pubmed: 33763624
J Nucl Med. 1998 Oct;39(10):1789-98
pubmed: 9776289
Eur J Nucl Med Mol Imaging. 2023 Oct 4;:
pubmed: 37792025
J Nucl Med. 2001 Nov;42(11):1622-9
pubmed: 11696630
J Nucl Med. 2022 Mar;63(3):476-484
pubmed: 34301780
J Nucl Med. 2007 Nov;48(11):1889-96
pubmed: 17942803
Neuroimage. 1996 Dec;4(3 Pt 1):153-8
pubmed: 9345505
Phys Med Biol. 2021 Mar 12;66(6):06RM01
pubmed: 33339012
IEEE Trans Med Imaging. 2000 Mar;19(3):233-42
pubmed: 10875707
J Cereb Blood Flow Metab. 1991 Jul;11(4):545-56
pubmed: 1904879
Phys Med. 2019 Sep;65:114-120
pubmed: 31450121
Nucl Med Commun. 2012 Sep;33(9):982-9
pubmed: 22760300
Eur J Nucl Med Mol Imaging. 2009 Oct;36(10):1594-602
pubmed: 19408000
J Cereb Blood Flow Metab. 2010 Apr;30(4):816-26
pubmed: 19997119
J Nucl Cardiol. 2016 Jun;23(3):499-510
pubmed: 25995182
Eur J Nucl Med Mol Imaging. 2011 May;38(5):930-9
pubmed: 21271246
EJNMMI Phys. 2022 Nov 17;9(1):78
pubmed: 36394674
Radiology. 1993 Jul;188(1):131-6
pubmed: 8511286
PET Clin. 2007 Apr;2(2):235-49
pubmed: 27157875
Eur J Nucl Med Mol Imaging. 2019 Feb;46(2):501-518
pubmed: 30269154
PET Clin. 2021 Oct;16(4):613-625
pubmed: 34353745
J Cereb Blood Flow Metab. 2007 Sep;27(9):1533-9
pubmed: 17519979