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Monte-Carlo simulations of clinically realistic respiratory gated (18)F-FDG PET: application to lesion detectability and volume measurements.

Authors :
Vauclin S
Michel C
Buvat I
Doyeux K
Edet-Sanson A
Vera P
Gardin I
Hapdey S
Source :
Computer methods and programs in biomedicine [Comput Methods Programs Biomed] 2015 Jan; Vol. 118 (1), pp. 84-93. Date of Electronic Publication: 2014 Oct 12.
Publication Year :
2015

Abstract

In PET/CT thoracic imaging, respiratory motion reduces image quality. A solution consists in performing respiratory gated PET acquisitions. The aim of this study was to generate clinically realistic Monte-Carlo respiratory PET data, obtained using the 4D-NCAT numerical phantom and the GATE simulation tool, to assess the impact of respiratory motion and respiratory-motion compensation in PET on lesion detection and volume measurement. To obtain reconstructed images as close as possible to those obtained in clinical conditions, a particular attention was paid to apply to the simulated data the same correction and reconstruction processes as those applied to real clinical data. The simulations required 140,000h (CPU) generating 1.5 To of data (98 respiratory gated and 49 ungated scans). Calibration phantom and patient reconstructed images from the simulated data were visually and quantitatively very similar to those obtained in clinical studies. The lesion detectability was higher when the better trade-off between lesion movement limitation (compared to ungated acquisitions) and image statistic preservation is considered (respiratory cycle sampling in 3 frames). We then compared the lesion volumes measured on conventional PET acquisitions versus respiratory gated acquisitions, using an automatic segmentation method and a 40%-threshold approach. A time consuming initial manual exclusion of noisy structures needed with the 40%-threshold was not necessary when the automatic method was used. The lesion detectability along with the accuracy of tumor volume estimates was largely improved with the gated compared to ungated PET images.<br /> (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

Details

Language :
English
ISSN :
1872-7565
Volume :
118
Issue :
1
Database :
MEDLINE
Journal :
Computer methods and programs in biomedicine
Publication Type :
Academic Journal
Accession number :
25459525
Full Text :
https://doi.org/10.1016/j.cmpb.2014.10.003