UCL  IRIS
Institutional Research Information Service
UCL Logo
Please report any queries concerning the funding data grouped in the sections named "Externally Awarded" or "Internally Disbursed" (shown on the profile page) to your Research Finance Administrator. Your can find your Research Finance Administrator at https://www.ucl.ac.uk/finance/research/rs-contacts.php by entering your department
Please report any queries concerning the student data shown on the profile page to:

Email: portico-services@ucl.ac.uk

Help Desk: http://www.ucl.ac.uk/ras/portico/helpdesk
Publication Detail
Air Fraction Correction Optimisation in PET Imaging of Lung Disease
  • Publication Type:
    Conference
  • Authors:
    Leek F, Robinson AP, Moss RM, Wilson FJ, Hutton BF, Thielemans K
  • Publisher:
    IEEE
  • Publication date:
    12/08/2021
  • Published proceedings:
    2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)
  • Status:
    Published
  • Name of conference:
    2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)
  • Conference start date:
    31/10/2020
  • Conference finish date:
    07/11/2020
Abstract
Accurate quantification of radiopharmaceutical uptake from lung PET/CT is challenging due to large variations in fractions of tissue, air, blood and water. Air fraction correction (AFC) uses voxel-wise air fractions, which can be determined from the CT acquired for attenuation correction (AC). However, resolution effects can cause artefacts in either of these corrections. In this work, we hypothesise that the resolution of the CT image used for AC should match that of the intrinsic resolution of the PET scanner but should approximate the reconstructed PET image resolution for AFC. Simulations and reconstructions were performed with the Synergistic Image Reconstruction Framework (SIRF) using phantoms with inhomogeneous attenuation (mu) maps, mimicking the densities observed in lung pathologies. Poisson noise was added to the projection data prior to OSEM reconstruction. AC was performed with a smoothed mu-map, the full-width-half-maximum (FWHM) of the 3D Gaussian kernel was varied (0 - 10 mm). Post-filters were applied to the reconstructed AC images (FWHM: 0 - 8 mm). The simulated mu-map was independently convolved with another set of 3D Gaussian kernels, of varying FWHM (0 - 12 mm), for AFC. The coefficient of variation (CV) in the lung region, designed to be homogeneous post-AFC with optimised kernels, and the mean AFC-standardized uptake value (AFC-SUV) in the regions of simulated pathologies were determined. The spatial resolution of each post-filtered image was determined via a point-source insertion-and-subtraction method on noiseless data. Results showed that the CV was minimised when the kernel applied to the mu-map for AC matched that for the simulated PET scanner and the kernel applied to the mu-map for AFC matched the spatial resolution of the reconstructed PET image. This was observed for all post-reconstruction filters and supports the hypothesis. Initial results from Monte Carlo simulations validate these findings.
Publication data is maintained in RPS. Visit https://rps.ucl.ac.uk
 More search options
UCL Researchers Show More
Author
Div of Medicine
Author
Dept of Med Phys & Biomedical Eng
Author
Dept of Med Phys & Biomedical Eng
Author
Department of Imaging
University College London - Gower Street - London - WC1E 6BT Tel:+44 (0)20 7679 2000

© UCL 1999–2011

Search by