http://www.cnr.it/ontology/cnr/individuo/prodotto/ID10238

Data rebinning and reconstruction in 3D PET/CT oncological studies: a Monte Carlo evaluation. (Articolo in rivista)

Type

Articolo in rivista (Classe)
Prodotto della ricerca (Classe)

Label

Data rebinning and reconstruction in 3D PET/CT oncological studies: a Monte Carlo evaluation. (Articolo in rivista) (literal)

Anno

2006-01-01T00:00:00+01:00 (literal)

Alternative label

Rizzo G. 1, Castiglioni I. 1, Russo G. 1, Gilardi M.C. 1, Panzacchi A 1, Fazio F. 1 (2006)
Data rebinning and reconstruction in 3D PET/CT oncological studies: a Monte Carlo evaluation.
in IEEE transactions on nuclear science
(literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

Rizzo G. 1, Castiglioni I. 1, Russo G. 1, Gilardi M.C. 1, Panzacchi A 1, Fazio F. 1 (literal)

Pagina inizio

139 (literal)

Pagina fine

146 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume

53 (literal)

Rivista

IEEE transactions on nuclear science (Rivista)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#descrizioneSinteticaDelProdotto

Lo scopo dello studio è analizzare linfluenza delle varie tecniche di rebinning dei sinogrammi e di ricostruzione tomografica sulla individuabilità di piccole lesioni neoplastiche in studi PET 3D. I risultati dimostrano che la tecnica di Fourier Rebinning (FORE) associata a ricostruzione tomografica 2D è più adatta rispetto alle tecniche di ricostruzione 3D per quanto riguarda lindividuabilità e la quantificazione delle lesioni. (literal)

Note

ISI Web of Science (WOS) (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

1. IBFM-CNR, Department of Nuclear Medicine, San Raffaele Scientific Institute, University of Milano-Bicocca, Milan, Italy (literal)

Titolo

Data rebinning and reconstruction in 3D PET/CT oncological studies: a Monte Carlo evaluation. (literal)

Abstract

An accurate identification and interpretation of neoplastic lesions by PET is related to PET image quality, and depends on several factors including data processing for image formation. The aim of this work was to assess the influence of data rebinning and reconstruction on lesion detectability and quantification for a high-resolution 3-D PET/CT system, in order to optimize 3-D PET/CT oncological protocols. Oncological 18F-FDG PET studies were Monte Carlo (MC) simulated, based on a normal-weight oncological patient study, varying lesion size, lesion-to-background ratio, statistics, and including or not attenuation and scatter effects. Single slice rebinned (SSR), Fourier rebinned (FORE) and Fully 3-D (3-D) sinograms were considered. Reconstruction was carried out using ordered subset expectation maximization (OSEM) and attenuation weighting OSEM (AWOSEM). Human observers evaluated images in terms of clinical parameters characteristic of lesion detectability and quantification: lesion number and lesion size. By comparison with the known activity map (input for MC simulations), identified lesions were classified as true and false positive; the true positive fraction (TPF) and sensitivity were derived, as indices of lesion detectability. % maximum number of lesions identified with erroneous size (MAXls) and % errors on lesion-to-background ratio (LBR) were calculated as quantitative indices for lesion characterization. The results show that, when images corrected for scatter and attenuation are considered, 2-D rebinning allows more lesions to be identified than 3-D, with the best detectability found using FORE + AWOSEM: in this case, sensitivity was found equal to 0.43, higher than with SSR + OSEM (0.30), SSR+AWOSEM(0.23), FORE+OSEM(0.35) and 3-D (0.18 for both OSEM and AWOSEM). Quantitatively, smaller MAXls and smaller LBRs were found using FORE + AWOSEM, in comparison to 3-D+AWOSEM (p = 0125 for both parameters); FORE + OSEM presented the smallest LBRs. Our findings, from one single simulated patient with lesions in the abdomen, suggest that, in the considered case, FORE is more suitable for lesion detectability and quantification than 3-D, FORE + AWOSEM presenting better performance for lesion detectability and spatial characterization, FORE + OSEM for the quantification of lesion activity concentration. (literal)

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