Abbreviated scan protocols to capture 18F-FDG kinetics for long axial FOV PET scanners.

Viswanath, Varsha; Sari, Hasan; Pantel, Austin R; Conti, Maurizio; Daube-Witherspoon, Margaret E; Mingels, Clemens; Alberts, Ian; Eriksson, Lars; Shi, Kuangyu; Rominger, Axel; Karp, Joel S (2022). Abbreviated scan protocols to capture 18F-FDG kinetics for long axial FOV PET scanners. (In Press). European journal of nuclear medicine and molecular imaging Springer 10.1007/s00259-022-05747-3

[img] Text
Viswanath2022_Article_AbbreviatedScanProtocolsToCapt.pdf - Published Version
Restricted to registered users only
Available under License Publisher holds Copyright.
Author holds Copyright

Download (1MB) | Request a copy

PURPOSE

Kinetic parameters from dynamic 18F-fluorodeoxyglucose (FDG) imaging offer complementary insights to the study of disease compared to static clinical imaging. However, dynamic imaging protocols are cumbersome due to the long acquisition time. Long axial field-of-view (LAFOV) PET scanners (> 70 cm) have two advantages for dynamic imaging over clinical PET scanners with a standard axial field-of-view (SAFOV; 16-30 cm). The large axial coverage enables multi-organ dynamic imaging in a single bed position, and the high sensitivity may enable clinically routine abbreviated dynamic imaging protocols.

METHODS

In this work, we studied two abbreviated protocols using data from a 65-min dynamic 18F-FDG scan: (A) dynamic imaging immediately post-injection (p.i.) for variable durations, and (B) dynamic imaging immediately p.i. for variable durations plus a 1-h p.i. (5-min-long) datapoint. Nine cancer patients were imaged on the Biograph Vision Quadra (Siemens Healthineers). Time-activity curves over the lesions (N = 39) were fitted using the Patlak graphical analysis and a 2-tissue-compartment (2C, k4 = 0) model for variable scan durations (5-60 min). Kinetic parameters from the complete dataset served as the reference. Lesions from all cancers were grouped into low, medium, and high flux groups, and bias and precision of Ki (Patlak) and Ki, K1, k2, and k3 (2C) were calculated for each group.

RESULTS

Using only early dynamic data with the 2C (or Patlak) model, accurate quantification of Ki required at least 50 (or 55) min of dynamic data for low flux lesions, at least 30 (or 40) min for medium flux lesions, and at least 15 (or 20) min for high flux lesions to achieve both 10% bias and precision. The addition of the final (5-min) datapoint allowed for accurate quantification of Ki with a bias and precision of 10% using only 10-15 min of early dynamic data for either model.

CONCLUSION

Dynamic imaging for 10-15 min immediately p.i. followed by a 5-min scan at 1-h p.i can accurately and precisely quantify 18F-FDG on a long axial FOV scanner, potentially allowing for more widespread use of dynamic 18F-FDG imaging.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Clinic of Nuclear Medicine

UniBE Contributor:

Mingels, Clemens; Alberts, Ian Leigh; Shi, Kuangyu and Rominger, Axel Oliver

Subjects:

600 Technology > 610 Medicine & health

ISSN:

1619-7089

Publisher:

Springer

Language:

English

Submitter:

Pubmed Import

Date Deposited:

15 Mar 2022 14:54

Last Modified:

15 Mar 2022 15:01

Publisher DOI:

10.1007/s00259-022-05747-3

PubMed ID:

35278108

Uncontrolled Keywords:

18F-FDG flux Dynamic imaging FDG

BORIS DOI:

10.48350/167388

URI:

https://boris.unibe.ch/id/eprint/167388

Actions (login required)

Edit item Edit item
Provide Feedback