Lambrou, Tryphon and Groves, Ashley and Erlandsson, Kjell and Screaton, Nick and Endozo, Raymondo and Win, Thida and Porter, Joanna and Hutton, Brian (2011) The importance of correction for tissue fraction effects in lung PET: preliminary findings. European Journal of Nuclear Medicine and Molecular Imaging, 38 (12). pp. 2238-2246. ISSN 1619-7070
Full content URL: http://dx.doi.org/10.1007/s00259-011-1906-x
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|Item Status:||Live Archive|
Purpose It has recently been recognized that PET/CT may play a role in diffuse parenchymal lung disease. However, interpretation can be confounded due to the variability in lung density both within and between individuals. To address this issue a novel correction method is proposed.
Methods A CT scan acquired during shallow breathing is registered to a PET study and smoothed so as to match the PET resolution. This is used to derive voxel-based tissue fraction correction factors for the individual. The method was evaluated in a lung phantom study in which the lung was simulated by a Styrofoam/water mixture. The method was further evaluated using (18)F-FDG in 12 subjects free from pulmonary disease where ranges before and after correction were considered.
Results Correction resulted in similar activity concentrations for the lung and background regions, consistent with the experimental phantom set-up. Correction resulted in reduced inter- and intrasubject variability in the estimated SUV. The possible application of the method was further demonstrated in five subjects with interstitial lung changes where increased SUV was demonstrated. Single study pre- and post-treatment studies were also analysed to further illustrate the utility of the method.
Conclusion The proposed tissue fraction correction method is a promising technique to account for variability of density in interpreting lung PET studies.
|Keywords:||Diffuse parenchymal lung disease; PET/CT; (18)F-FDG; Tissue fraction correction|
|Subjects:||F Physical Sciences > F350 Medical Physics|
G Mathematical and Computer Sciences > G740 Computer Vision
|Divisions:||College of Science > School of Computer Science|
|Deposited On:||14 Dec 2012 09:33|
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