Automated long axial field of view PET image processing and kinetic modelling with the TurBO toolbox.
Purpose: Long axial field of view (LAFOV) PET imaging requires extensive automation due to the large number of target tissues. Therefore, we introduce an open-source analysis pipeline (TurBO, Turku total-BOdy) for automated preprocessing and kinetic modelling of LAFOV [15O]H2O and [18F]FDG PET data....
| Publicado en: | European Journal of Nuclear Medicine & Molecular Imaging Vol. 53; no. 6; pp. 4162 - 4175 |
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| Autores principales: | , , , , , , , , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
May2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=193283658&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 193283658 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16197070 NPC jtl: European Journal of Nuclear Medicine & Molecular Imaging issn: 16197070 maglogo: N pubinfo: dt: May2026 vid: 53 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 193283658 191201295 10.1007/s00259-026-07769-7 193283658 ppf: 4162 ppct: 13 formats: tig: atl: Automated long axial field of view PET image processing and kinetic modelling with the TurBO toolbox. aug: au: Tuisku, Jouni Palonen, Santeri Kärpijoki, Henri Latva-Rasku, Aino Tuomola, Nelli Harju, Harri Nesterov, Sergey V. Oikonen, Vesa Iida, Hidehiro Teuho, Jarmo Han, Chunlei Karjalainen, Tomi Kirjavainen, Anna K. Rajader, Johan Klén, Riku Nuutila, Pirjo Knuuti, Juhani Nummenmaa, Lauri affil: https://ror.org/05vghhr25 Turku PET Centre, University of Turku, Turku, Finland sug: ab: Purpose: Long axial field of view (LAFOV) PET imaging requires extensive automation due to the large number of target tissues. Therefore, we introduce an open-source analysis pipeline (TurBO, Turku total-BOdy) for automated preprocessing and kinetic modelling of LAFOV [15O]H2O and [18F]FDG PET data. TurBO enables efficient, reproducible quantification of tissue perfusion and metabolism at regional- and voxel-levels through automated co-registration, motion correction, CT-based region of interest (ROI) segmentation, image-derived input function (IDIF) extraction, and region-specific kinetic modelling. Methods: The pipeline was validated with Biograph Vision Quadra (Siemens Healthineers) LAFOV PET/CT data from 21 subjects scanned with [15O]H2O and 16 subjects scanned with [18F]FDG. Six CT-segmented ROIs (cortical brain gray matter, left iliopsoas muscle, right kidney cortex and medulla, pancreas, spleen and liver) were used to assess different levels of tissue perfusion and glucose metabolism. Results: Model fits showed high quality with consistent estimates at regional and voxel-levels (R2 > 0.83 for [15O]H2O, R2 > 0.99 for [18F]FDG). Manual and automated IDIFs were in concordance (R2 > 0.74 for [15O]H2O, and R2 > 0.78 for [18F]FDG) with minimal bias (< 4% and < 10%, respectively). Manual and CT-segmented ROIs showed strong agreement (R2 > 0.82 for [15O]H2O and R2 > 0.83 for [18F]FDG). Motion correction had little impact on estimates (R2 > 0.71 for [15O]H2O and R2 > 0.78 for [18F]FDG) compared with uncorrected data. Conclusion: The TurBO pipeline provides fully automated and reliable quantification for LAFOV PET data. It substantially reduces manual workload and enables standardized, reproducible assessment of inter-organ perfusion and metabolism. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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