Journal Article10.1186/s40658-024-00628-0
Validation of image-derived input function using a long axial field of view PET/CT scanner for two different tracers
Xavier Palard-Novello,Denise Visser,Nelleke Tolboom,Charlotte L C Smith,G.J.C. Zwezerijnen,Elsmarieke van de Giessen,Marijke den Hollander,F. Barkhof,Albert D. Windhorst,Bart N.M. van Berckel,R. Boellaard,Maqsood Yaqub +11 more
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TL;DR: This study validates the use of image-derived input functions (IDIFs) from a long axial field of view PET/CT scanner for two tracers, [18F]FDG and [18F]DPA-714, with varying reconstruction settings and IDIF locations, demonstrating high accuracy and precision for [18F]FDG but not [18F]DPA-714 without calibration.
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Abstract: Accurate image-derived input function (IDIF) from highly sensitive large axial field of view (LAFOV) PET/CT scanners could avoid the need of invasive blood sampling for kinetic modelling. The aim is to validate the use of IDIF for two kinds of tracers, 3 different IDIF locations and 9 different reconstruction settings.Eight [18F]FDG and 10 [18F]DPA-714 scans were acquired respectively during 70 and 60 min on the Vision Quadra PET/CT system. PET images were reconstructed using various reconstruction settings. IDIFs were taken from ascending aorta (AA), descending aorta (DA), and left ventricular cavity (LV). The calibration factor (CF) extracted from the comparison between the IDIFs and the manual blood samples as reference was used for IDIFs accuracy and precision assessment. To illustrate the effect of various calibrated-IDIFs on Patlak linearization for [18F]FDG and Logan linearization for [18F]DPA-714, the same target time-activity curves were applied for each calibrated-IDIF.For [18F]FDG, the accuracy and precision of the IDIFs were high (mean CF ≥ 0.82, SD ≤ 0.06). Compared to the striatum influx (Ki) extracted using calibrated AA IDIF with the updated European Association of Nuclear Medicine Research Ltd. standard reconstruction (EARL2), Ki mean differences were < 2% using the other calibrated IDIFs. For [18F]DPA714, high accuracy of the IDIFs was observed (mean CF ≥ 0.86) except using absolute scatter correction, DA and LV (respectively mean CF = 0.68, 0.47 and 0.44). However, the precision of the AA IDIFs was low (SD ≥ 0.10). Compared to the distribution volume (VT) in a frontal region obtained using calibrated continuous arterial sampler input function as reference, VT mean differences were small using calibrated AA IDIFs (for example VT mean difference = -5.3% using EARL2), but higher using calibrated DA and LV IDIFs (respectively + 12.5% and + 19.1%).For [18F]FDG, IDIF do not need calibration against manual blood samples. For [18F]DPA-714, AA IDIF can replace continuous arterial sampling for simplified kinetic quantification but only with calibration against arterial blood samples. The accuracy and precision of IDIF from LAFOV PET/CT system depend on tracer, reconstruction settings and IDIF VOI locations, warranting careful optimization.
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Citations
SNMMI Procedure Standard/EANM Practice Guideline for Brain [<sup>18</sup>F]FDG PET Imaging, Version 2.0
Javier Arbizu,Silvia Morbelli,Satoshi Minoshima,Henryk Barthel,Philip H. Kuo,Donatienne Van Weehaeghe,Neil Horner,Patrick M. Colletti,Éric Guedj +8 more
TL;DR: The SNMMI and EANM release Version 2.0 of the Brain [18F]FDG PET Imaging guideline, outlining best practices for safe and effective use of diagnostic nuclear medicine imaging, emphasizing education and flexibility in clinical decision-making.
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Validation of cardiac image-derived input functions for functional PET quantification
Murray Bruce Reed,Patricia Handschuh,Clemens Schmidt,Matej Murgaš,David Gomola,Christian Milz,Sebastian Klug,Benjamin Eggerstorfer,L. Aichinger,Godber Mathis Godbersen,Lukas Nics,Tatjana Traub-Weidinger,Marcus Hacker,Rupert Lanzenberger,Andreas Hahn +14 more
TL;DR: Validation of cardiac image-derived input functions for functional PET quantification accurately estimates arterial input function with high spatial resolution and improved quantification of task-specific changes.
Validation of cardiac image derived input functions for functional PET quantification
Murray B. Reed,Patricia Handschuh,C. Schmidt,Matej Murgas,David Gomola,Christian Milz,Sebastian Klug,Benjamin Eggerstorfer,Lisa Aichinger,Godber M Godbersen,Lukas Nics,Tatjana Traub-Weidinger,Marcus Hacker,Rupert Lanzenberger,Andreas Hahn,Prof. Rupert Lanzenberger +15 more
TL;DR: The proposed protocol enables accurate non-invasive estimation of the input function with full quantification of task-specific changes, addressing the limitations of IDIF for brain imaging by sampling larger blood pools over the thorax.
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