TY - JOUR

T1 - An update on the use of image-derived input functions for human PET studies

T2 - new hopes or old illusions?

AU - Volpi, Tommaso

AU - Maccioni, Lucia

AU - Colpo, Maria

AU - Debiasi, Giulia

AU - Capotosti, Amedeo

AU - Ciceri, Tommaso

AU - Carson, Richard E.

AU - DeLorenzo, Christine

AU - Hahn, Andreas

AU - Knudsen, Gitte Moos

AU - Lammertsma, Adriaan A.

AU - Price, Julie C.

AU - Sossi, Vesna

AU - Wang, Guobao

AU - Zanotti-Fregonara, Paolo

AU - Bertoldo, Alessandra

AU - Veronese, Mattia

N1 - Publisher Copyright: © 2023, The Author(s).

PY - 2023

Y1 - 2023

N2 - 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: 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: 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.

AB - 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: 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: 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.

KW - Blood sampling

KW - High sensitivity

KW - Image-derived input function

KW - Long axial field of view

KW - Total-body PET

U2 - 10.1186/s13550-023-01050-w

DO - 10.1186/s13550-023-01050-w

M3 - Review

C2 - 37947880

AN - SCOPUS:85176218053

VL - 13

JO - EJNMMI Research

JF - EJNMMI Research

SN - 2191-219X

IS - 1

M1 - 97

ER -