Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Sep;51(11):3346-3359.
doi: 10.1007/s00259-024-06745-3. Epub 2024 May 20.

Optimization and impact of sensitivity mode on abbreviated scan protocols with population-based input function for parametric imaging of [18F]-FDG for a long axial FOV PET scanner

Affiliations

Optimization and impact of sensitivity mode on abbreviated scan protocols with population-based input function for parametric imaging of [18F]-FDG for a long axial FOV PET scanner

W Lan et al. Eur J Nucl Med Mol Imaging. 2024 Sep.

Abstract

Background: The long axial field of view, combined with the high sensitivity of the Biograph Vision Quadra PET/CT scanner enables the precise deviation of an image derived input function (IDIF) required for parametric imaging. Traditionally, this requires an hour-long dynamic PET scan for [18F]-FDG, which can be significantly reduced by using a population-based input function (PBIF). In this study, we expand these examinations and include the scanner's ultra-high sensitivity (UHS) mode in comparison to the high sensitivity (HS) mode and evaluate the potential for further shortening of the scan time.

Methods: Patlak Ki and DV estimates were determined by the indirect and direct Patlak methods using dynamic [18F]-FDG data of 6 oncological patients with 26 lesions (0-65 min p.i.). Both sensitivity modes for different number/duration of PET data frames were compared, together with the potential of using abbreviated scan durations of 20, 15 and 10 min by using a PBIF. The differences in parametric images and tumour-to-background ratio (TBR) due to the shorter scans using the PBIF method and between the sensitivity modes were assessed.

Results: A difference of 3.4 ± 7.0% (Ki) and 1.2 ± 2.6% (DV) was found between both sensitivity modes using indirect Patlak and the full IDIF (0-65 min). For the abbreviated protocols and indirect Patlak, the UHS mode resulted in a lower bias and higher precision, e.g., 45-65 min p.i. 3.8 ± 4.4% (UHS) and 6.4 ± 8.9% (HS), allowing shorter scan protocols, e.g. 50-65 min p.i. 4.4 ± 11.2% (UHS) instead of 7.3 ± 20.0% (HS). The variation of Ki and DV estimates for both Patlak methods was comparable, e.g., UHS mode 3.8 ± 4.4% and 2.7 ± 3.4% (Ki) and 14.4 ± 2.7% and 18.1 ± 7.5% (DV) for indirect and direct Patlak, respectively. Only a minor impact of the number of Patlak frames was observed for both sensitivity modes and Patlak methods. The TBR obtained with direct Patlak and PBIF was not affected by the sensitivity mode, was higher than that derived from the SUV image (6.2 ± 3.1) and degraded from 20.2 ± 12.0 (20 min) to 10.6 ± 5.4 (15 min). Ki and DV estimate images showed good agreement (UHS mode, RC: 6.9 ± 2.3% (Ki), 0.1 ± 3.1% (DV), peak signal-to-noise ratio (PSNR): 64.5 ± 3.3 dB (Ki), 61.2 ± 10.6 dB (DV)) even for abbreviated scan protocols of 50-65 min p.i.

Conclusions: Both sensitivity modes provide comparable results for the full 65 min dynamic scans and abbreviated scans using the direct Patlak reconstruction method, with good Ki and DV estimates for 15 min short scans. For the indirect Patlak approach the UHS mode improved the Ki estimates for the abbreviated scans.

Keywords: LAFOV PET; Parametric imaging; Patlak; Population-based input function; Total-body PET.

PubMed Disclaimer

Conflict of interest statement

Hasan Sari is a full-time employee of Siemens Healthineers. Fabian P. Schmidt and Christian la Fougère received a research grant from Siemens Healthineers. Axel Rominger has received research support and speaker honoraria from Siemens Healthineers. There are no other conflicts of interest to report.

Figures

Fig. 1
Fig. 1
(a) Example of single patient IDIF obtained by HS and UHS mode; (b): enlarged view for the IDIF peak region; (c): enlarged view for 30–65 min p.i.; (d): Mean IDIF of 6 patients obtained by HS and UHS mode; (e) enlarged view for the mean IDIF peak region; (f) enlarged view of the mean IDIF for 30–65 min p.i
Fig. 2
Fig. 2
Ki (a) and DV (b) values obtained by HS and UHS mode with linear regression and axial position of lesions binned into intervals of 0–10 cm, 10–20 cm, 20–30 cm and 30–53 cm
Fig. 3
Fig. 3
Bias and precision for Ki (a) and DV (b) values for both sensitivity modes and for different number of Patlak frames with reference to values obtained with 4 Patlak frames and t*=45 min
Fig. 4
Fig. 4
Bias and precision for Ki (a) and DV (b) values for indirect Patlak with sPBIF, both sensitivity modes, t*=45, 50 and 55 min with reference to IDIF based estimation (t*=45 min, 8 Patlak frames)
Fig. 5
Fig. 5
Bias and precision for Ki (a) and DV (b) values for indirect Patlak with sPBIF, both sensitivity modes, t*=45, 50 and 55 min with reference to IDIF based estimation (t*=45 min, 8 Patlak frames)
Fig. 6
Fig. 6
Bias and precision for Ki (a) and DV (b) values for direct Patlak with sPBIF, both sensitivity modes, different number of Patlak frames and t*=45, 50 and 55 min with reference to IDIF based estimation with the same settings
Fig. 7
Fig. 7
Coronal (a) and transversal (b) views for SUV and direct Patlak Ki images for abbreviated scan times in UHS mode. Sagittal (c) view of CT image with 1.68 cm3 aortic VOI for IDIF in the thoracic aorta obtained by SnakeVOI. Coronal (d) and transversal (e) views of absolute relative difference image of Ki estimates (left to right: sPBIF (t*=45 min, 45–65 min p.i.), sPBIF (t*=50 min, 50–65 min p.i.) and sPBIF (t*=55 min, 55–65 min p.i.)) with reference to patient-individual IDIF (t*=45 min, 45–65 min p.i.)

Similar articles

Cited by

References

    1. Surti S, Pantel AR, Karp JS, Total Body PET. Why, how, what for? IEEE Trans Radiat Plasma Med Sci. 2020;4:283–92. 10.1109/TRPMS.2020.2985403 - DOI - PMC - PubMed
    1. Kitson SL, Cuccurullo V, Ciarmiello A, Salvo D, Mansi L. Clinical applications of Positron Emission Tomography (PET) imaging in Medicine: Oncology, Brain diseases and Cardiology. Curr Radiopharm 2:224–53.
    1. Boellaard R. Standards for PET Image Acquisition and Quantitative Data Analysis. J Nucl Med. 2009;50:S11–20.10.2967/jnumed.108.057182 - DOI - PubMed
    1. Boellaard R, Oyen WJG, Hoekstra CJ, Hoekstra OS, Visser EP, Willemsen AT, et al. The Netherlands protocol for standardisation and quantification of FDG whole body PET studies in multi-centre trials. Eur J Nucl Med Mol Imaging. 2008;35:2320–33. 10.1007/s00259-008-0874-2 - DOI - PubMed
    1. Dias AH, Pedersen MF, Danielsen H, Munk OL, Gormsen LC. Clinical feasibility and impact of fully automated multiparametric PET imaging using direct patlak reconstruction: evaluation of 103 dynamic whole-body 18F-FDG PET/CT scans. Eur J Nucl Med Mol Imaging. 2021;48:837–50. 10.1007/s00259-020-05007-2 - DOI - PubMed

MeSH terms

Substances