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Effective Image Resolution for Partial Volume Correction in FDG-PET Brain Imaging: A Proof of Concept

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00384301" target="_blank" >RIV/68407700:21230/25:00384301 - isvavai.cz</a>

  • Alternative codes found

    RIV/00098892:_____/25:10159438

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/11068065" target="_blank" >https://ieeexplore.ieee.org/document/11068065</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/MeMeA65319.2025.11068065" target="_blank" >10.1109/MeMeA65319.2025.11068065</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Effective Image Resolution for Partial Volume Correction in FDG-PET Brain Imaging: A Proof of Concept

  • Original language description

    Neuroimaging of subtle hypometabolic epileptogenic lesions using 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is challenging due to its limited spatial resolution, which causes partial volume effects (PVE), leading to image blurring and underestimation of radiotracer activity. Partial volume correction (PVC) post-processing compensates for the blurring, but relies on accurate knowledge of the point spread function (PSF), which must be provided as an input parameter. However, no guidelines exist for determining an appropriate PSF value, which varies with scanner type, reconstruction algorithm, and scanned object properties. We conducted phantom measurements on Siemens Biograph mCT 40 and Vision 600 scanners using a clinical reconstruction protocol to compare two PSF estimation methods: one based on capillary phantom (following NEMA) and another using effective image resolution (EIR) of Hoffman phantom images (following EARL guideline). The impact of the PSF estimation method on PVC performance was assessed using image quality metrics: gray matter recovery coefficient (GMRC), gray matter edge recovery coefficient (GMERC), and gray matter coefficient of variation (GMCOV). PVC with both PSF estimation methods improved image quality compared to the original images. However, PVC with input PSF estimated by EIR showed better performance than PVC with capillary-based estimate: GMRC was 92-94% vs. 85-86%, GMERC was 85-90% vs. 78-79%, and lower GMCOV: 18-22% vs. 20-23%. These findings suggest that the estimation of input PSF by EIR could be a more reliable and practical approach for PVC in clinical FDG-PET brain imaging, especially since it is already used in the EARL F/C Brain PET/CT Accreditation.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20601 - Medical engineering

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    2025 IEEE Medical Measurements & Applications

  • ISBN

    979-8-3315-2347-3

  • ISSN

    2837-5874

  • e-ISSN

    2837-5882

  • Number of pages

    6

  • Pages from-to

  • Publisher name

    IEEE Industrial Electronic Society

  • Place of publication

    Vienna

  • Event location

    Chania

  • Event date

    May 28, 2025

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article