Harmonisation of standard uptake values in long-axial field-of-view PET/CT: an exploratory study

SUV harmonisation was proposed to reduce discrepancies in SUV measurements and ensure SUV comparability across different PET scanners. A SUV harmonisation protocol has been established based on short-axial field-of-view (SAFOV) PET. However, long-axial field-of-view (LAFOV) PET features a different scanning mode and clinical workflow compared with SAFOV PET, and no dedicated SUV harmonisation protocol has yet been developed. This study aimed to perform an exploratory investigation of SUV harmonisation on LAFOV PET.

The long-axial detector was divided into five segments based on typical patient anatomical positioning. A NEMA IEC body phantom filled with ¹⁸F-FDG solution was sequentially scanned at each detector position. SUV harmonisation was performed separately in accordance with the EARL 1 and EARL 2 standards using post-reconstruction Gaussian filters. Position-specific optimal Gaussian full width at half maximum (FWHM) values, as well as a general harmonisation filter applicable across all positions, were derived. Recovery coefficients (RCs) were determined, and root mean square error (RMSE) between the harmonised RCs and the expected EARL reference values (EARL_expect ) was used to evaluate harmonisation performance. To assess the necessity of the detector-splitting phantom scanning strategy, the optimal Gaussian filters derived from a single detector position were applied to other positions, and the corresponding RMSE values were recalculated. A clinical case was further evaluated as a proof-of-concept application.

The position-specific optimal harmonisation filter parameters under EARL 1 were nearly identical across all detector positions, whereas under EARL 2 differences were observed. A general Gaussian filter derived by jointly considering all detector positions was sufficient to achieve EARL-compliant SUV harmonisation across the entire axial field of view. Moreover, when optimal filters derived from a single detector position were applied to other positions, harmonisation remained compliant with EARL 1, while deviations from EARL_expect increased under EARL 2 for some cases. When the proposed harmonisation strategy was applied to a clinical case, the SUV deviation in follow-up imaging caused by a change in PET scanner was eliminated.

The study proposes a detector-splitting phantom scanning strategy as a practical framework for robust SUV harmonisation for LAFOV PET systems. Position-specific or jointly optimized harmonisation filters applicable across all axial detector positions may be beneficial for ensuring reliable and comparable SUV measurements, particularly in longitudinal follow-up and multi-scanner clinical settings.