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Impact of the EARL harmonization program on automatic delineation of metabolic active tumour volumes (MATVs).


ABSTRACT: BACKGROUND:The clinical validation of the EARL harmonization program for standardised uptake value (SUV) metrics is well documented; however, its potential for defining metabolic active tumour volume (MATV) has not yet been investigated. We aimed to compare delineation of MATV on images reconstructed using conventional ordered subset expectation maximisation (OSEM) with those reconstructed using point spread function modelling (PSF-reconstructed images), and either optimised for diagnostic potential (PSF) or filtered to meet the EANM/EARL harmonising standards (PSF7). METHODS:Images from 18 stage IIIA-IIIB lung cancer patients were reconstructed using all the three methods. MATVs were then delineated using both a 40% isocontour and a gradient-based method. MATVs were compared by means of Bland-Altman analyses, and Dice coefficients and concordance indices based on the unions and intersections between each pair of reconstructions (PSF vs OSEM, PSF7 vs PSF and PSF7 vs OSEM). RESULTS:Using the 40% isocontour method and taking the MATVs delineated on OSEM images as a reference standard, the use of PSF7 images led to significantly higher Dice coefficients (median value?=?0.96 vs 0.77; P?

SUBMITTER: Lasnon C 

PROVIDER: S-EPMC5374086 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Impact of the EARL harmonization program on automatic delineation of metabolic active tumour volumes (MATVs).

Lasnon Charline C   Enilorac Blandine B   Popotte Hosni H   Aide Nicolas N  

EJNMMI research 20170331 1


<h4>Background</h4>The clinical validation of the EARL harmonization program for standardised uptake value (SUV) metrics is well documented; however, its potential for defining metabolic active tumour volume (MATV) has not yet been investigated. We aimed to compare delineation of MATV on images reconstructed using conventional ordered subset expectation maximisation (OSEM) with those reconstructed using point spread function modelling (PSF-reconstructed images), and either optimised for diagnost  ...[more]

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