Automated Long Axial Field of View PET Image Processing and Kinetic Modelling with the TurBO Toolbox

Read the full article See related articles

Listed in

This article is not in any list yet, why not save it to one of your lists.
Log in to save this article

Abstract

Long axial field of view (LAFOV) PET imaging requires a high level of automation and standardization, as the large number of target tissues increases the manual workload significantly. We introduce an automated analysis pipeline (TurBO, Turku total-BOdy) for preprocessing and kinetic modelling of LAFOV [ 15 O]H 2 O and [ 18 F]FDG PET data, enabling efficient and reproducible analysis of tissue perfusion and metabolism at regional and voxel-levels. The approach employs automated processing including co-registration, motion correction, automated CT segmentation for region of interest (ROI) delineation, image-derived input determination, and region-specific kinetic modelling of PET data.

Methods

We validated the analysis pipeline using Biograph Vision Quadra (Siemens Healthineers) LAFOV PET/CT scans from 21 subjects scanned with [ 15 O]H 2 O and 16 subjects scanned with [ 18 F]FDG using six segmented CT-based ROIs (cortical brain gray matter, left iliopsoas muscle, right kidney cortex and medulla, pancreas, spleen and liver) representing different levels of blood flow and glucose metabolism.

Results

Model fits showed good quality with consistent parameter estimates at both regional and voxel-levels (R² > 0.83 for [ 15 O]H 2 O, R² > 0.99 for [ 18 F]FDG). Estimates from manual and automated input functions were in concordance (R² > 0.74 for [ 15 O]H 2 O, and R² > 0.78 for [ 18 F]FDG) with minimal bias (<4% for [ 15 O]H 2 O and <10% for [ 18 F]FDG). Manually and automatically (CT-based) extracted ROI level data showed strong agreement (R² > 0.82 for [ 15 O]H 2 O and R² > 0.83 for [ 18 F]FDG), while motion correction had little impact on parameter estimates (R² > 0.71 for [ 15 O]H 2 O and R² > 0.78 for [ 18 F]FDG) compared with uncorrected data.

Conclusion

Our automated analysis pipeline provides reliable and reproducible parameter estimates across different regions, with an approximate processing time of 1-1.5 h per subject. This pipeline completely automates LAFOV PET analysis, reducing manual effort and enabling reproducible studies of inter-organ blood flow and metabolism, including brain-body interactions.

Article activity feed