Literature DB >> 18581114

Initial clinical results for breath-hold CT-based processing of respiratory-gated PET acquisitions.

Loïc Fin1, Joël Daouk, Julie Morvan, Pascal Bailly, Isabelle El Esper, Lazhar Saidi, Marc-Etienne Meyer.   

Abstract

PURPOSE: Respiratory motion causes uptake in positron emission tomography (PET) images of chest structures to spread out and misregister with the CT images. This misregistration can alter the attenuation correction and thus the quantisation of PET images. In this paper, we present the first clinical results for a respiratory-gated PET (RG-PET) processing method based on a single breath-hold CT (BH-CT) acquisition, which seeks to improve diagnostic accuracy via better PET-to-CT co-registration. We refer to this method as "CT-based" RG-PET processing.
METHODS: Thirteen lesions were studied. Patients underwent a standard clinical PET protocol and then the CT-based protocol, which consists of a 10-min List Mode RG-PET acquisition, followed by a shallow end-expiration BH-CT. The respective performances of the CT-based and clinical PET methods were evaluated by comparing the distances between the lesions' centroids on PET and CT images. SUV(MAX) and volume variations were also investigated.
RESULTS: The CT-based method showed significantly lower (p = 0.027) centroid distances (mean change relative to the clinical method = -49%; range = -100% to 0%). This led to higher SUV(MAX) (mean change = +33%; range = -4% to 69%). Lesion volumes were significantly lower (p = 0.022) in CT-based PET volumes (mean change = -39%: range = -74% to -1%) compared with clinical ones.
CONCLUSIONS: A CT-based RG-PET processing method can be implemented in clinical practice with a small increase in radiation exposure. It improves PET-CT co-registration of lung lesions and should lead to more accurate attenuation correction and thus SUV measurement.

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Year:  2008        PMID: 18581114     DOI: 10.1007/s00259-008-0858-2

Source DB:  PubMed          Journal:  Eur J Nucl Med Mol Imaging        ISSN: 1619-7070            Impact factor:   9.236


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