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Published in: European Journal of Nuclear Medicine and Molecular Imaging 4/2011

01-04-2011 | Original Article

PET functional volume delineation: a robustness and repeatability study

Authors: Mathieu Hatt, Catherine Cheze Le Rest, Nidal Albarghach, Olivier Pradier, Dimitris Visvikis

Published in: European Journal of Nuclear Medicine and Molecular Imaging | Issue 4/2011

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Abstract

Purpose

Current state-of-the-art algorithms for functional uptake volume segmentation in PET imaging consist of threshold-based approaches, whose parameters often require specific optimization for a given scanner and associated reconstruction algorithms. Different advanced image segmentation approaches previously proposed and extensively validated, such as among others fuzzy C-means (FCM) clustering, or fuzzy locally adaptive bayesian (FLAB) algorithm have the potential to improve the robustness of functional uptake volume measurements. The objective of this study was to investigate robustness and repeatability with respect to various scanner models, reconstruction algorithms and acquisition conditions.

Methods and materials

Robustness was evaluated using a series of IEC phantom acquisitions carried out on different PET/CT scanners (Philips Gemini and Gemini Time-of-Flight, Siemens Biograph and GE Discovery LS) with their associated reconstruction algorithms (RAMLA, TF MLEM, OSEM). A range of acquisition parameters (contrast, duration) and reconstruction parameters (voxel size) were considered for each scanner model, and the repeatability of each method was evaluated on simulated and clinical tumours and compared to manual delineation.

Results

For all the scanner models, acquisition parameters and reconstruction algorithms considered, the FLAB algorithm demonstrated higher robustness in delineation of the spheres with low mean errors (10%) and variability (5%), with respect to threshold-based methodologies and FCM. The repeatability provided by all segmentation algorithms considered was very high with a negligible variability of <5% in comparison to that associated with manual delineation (5–35%).

Conclusion

The use of advanced image segmentation algorithms may not only allow high accuracy as previously demonstrated, but also provide a robust and repeatable tool to aid physicians as an initial guess in determining functional volumes in PET.
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Metadata
Title
PET functional volume delineation: a robustness and repeatability study
Authors
Mathieu Hatt
Catherine Cheze Le Rest
Nidal Albarghach
Olivier Pradier
Dimitris Visvikis
Publication date
01-04-2011
Publisher
Springer-Verlag
Published in
European Journal of Nuclear Medicine and Molecular Imaging / Issue 4/2011
Print ISSN: 1619-7070
Electronic ISSN: 1619-7089
DOI
https://doi.org/10.1007/s00259-010-1688-6

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