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Abstract/Summary
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<jats:title>Abstract</jats:title><jats:sec>
<jats:title>Aim</jats:title>
<jats:p>In addition to significant improvements in sensitivity and image quality, the recent introduction of long axial field-of-view (LAFOV) PET/CT scanners has enabled dynamic whole-body imaging for the first time. We aim herein to determine an appropriate acquisition time range for static low-dose [<jats:sup>18</jats:sup>F]PSMA-1007 PET imaging and to investigate the whole-body pharmacokinetics of [<jats:sup>18</jats:sup>F]PSMA-1007 by dynamic PET with the LAFOV Biograph Vision Quadra PET/CT in a group of prostate cancer patients.</jats:p>
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<jats:title>Methodology</jats:title>
<jats:p>In total, 38 prostate cancer patients were enrolled in the analysis for staging or re-staging purposes. Thirty-four patients underwent dynamic whole-body PET/CT (60 min) followed by static whole-body PET/CT and four patients underwent static whole-body PET/CT only. The activity applied was 2 MBq/kg [<jats:sup>18</jats:sup>F]PSMA-1007. The static PET images of 10-min duration (PET-10) were reconstructed and further split into 8-min (PET-8), 6-min (PET-6), 5-min (PET-5), 4-min (PET-4), and 2-min (PET-2) duration groups. Comparisons were made between the different reconstructed scan times in terms of lesion detection rate and image quality based on SUV calculations of tumor lesions and the spleen, which served as background. Analysis of the dynamic PET/CT data was based on a two-tissue compartment model using an image-derived input function obtained from the descending aorta.</jats:p>
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<jats:title>Results</jats:title>
<jats:p>Analysis of lesion detection rate showed no significant differences when reducing PET acquisitions from 10 up to 5 min. In particular, a total of 169 lesions were counted with PET-10, and the corresponding lesion detection rates (95% CI for the 90% quantile of the differences in tumor lesions) for shorter acquisitions were 100% (169/169) for PET-8 (95% CI: 0–0), 98.8% (167/169) for PET-6 (95% CI: 0–1), 95.9% (162/169) for PET-5 (95% CI: 0–3), 91.7% (155/169) for PET-4 (95% CI: 1–2), and 85.2% (144/169) for PET-2 (95% CI: 1–6). With the exception of PET-2, the differences observed between PET-10 and the other shorter acquisition protocols would have no impact on any patient in terms of clinical management. Objective evaluation of PET/CT image quality showed no significant decrease in tumor-to-background ratio (TBR) with shorter acquisition times, despite a gradual decrease in signal-to-noise ratio (SNR) in the spleen. Whole-body quantitative [<jats:sup>18</jats:sup>F]PSMA-1007 pharmacokinetic analysis acquired with full dynamic PET scanning was feasible in all patients. Two-tissue compartment modeling revealed significantly higher values for the parameter <jats:italic>k</jats:italic><jats:sub>3</jats:sub> in tumor lesions and parotid gland compared to liver and spleen, reflecting a higher specific tracer binding to the PSMA molecule and internalization rate in these tissues, a finding also supported by the respective time-activity curves. Furthermore, correlation analysis demonstrated a significantly strong positive correlation (<jats:italic>r</jats:italic> = 0.72) between SUV and <jats:italic>k</jats:italic><jats:sub>3</jats:sub> in tumor lesions.</jats:p>
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<jats:title>Conclusions</jats:title>
<jats:p>In prostate cancer, low-dose (2 MBq/kg) [<jats:sup>18</jats:sup>F]PSMA-1007 LAFOV PET/CT can reduce static scan time by 50% without significantly compromising lesion detection rate and objective image quality. In addition, dynamic PET can elucidate molecular pathways related to the physiology of [<jats:sup>18</jats:sup>F]PSMA-1007 in both tumor lesions and normal organs at the whole-body level. These findings unfold many of the potentials of the new LAFOV PET/CT technology in the field of PSMA-based diagnosis and theranostics of prostate cancer.</jats:p>
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Hinweis
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DeepGreen-ID: 576c614728a742df8252f71203f3ab27 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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