Title :

Impact of consensus contours from multiple PET segmentation methods on the accuracy of functional volume delineation

Author(s) :

Schaefer, A [Auteur]
Vermandel, Maximilien [Auteur]
Thérapies Assistées par Lasers et Immunothérapies pour l'Oncologie - U 1189 [OncoThAI]
Thérapies Lasers Assistées par l'Image pour l'Oncologie (ONCO-THAI) - U1189
Baillet, Clio [Auteur]
Groupe de Recherche sur les formes Injectables et les Technologies Associées - ULR 7365 [GRITA]
Dewalle-Vignion A, S [Auteur]
Modzelewski, R [Auteur]
Vera, P [Auteur]
Massoptier, L [Auteur]
Parcq, C [Auteur]
Gibon, D [Auteur]
Fechter, T [Auteur]
Nemer, U [Auteur]
Gardin, I [Auteur]
Nestle, U [Auteur]

Journal title :

European journal of nuclear medicine and molecular imaging

Abbreviated title :

Eur. J. Nucl. Med. Mol. Imaging

Volume number :

43

Pages :

911-924

Publication date :

2016

HAL domain(s) :

Sciences du Vivant [q-bio]

English abstract : [en]

PURPOSE: The aim of this study was to evaluate the impact of consensus algorithms on segmentation results when applied to clinical PET images. In particular, whether the use of the majority vote or STAPLE algorithm could ...
Show more >PURPOSE: The aim of this study was to evaluate the impact of consensus algorithms on segmentation results when applied to clinical PET images. In particular, whether the use of the majority vote or STAPLE algorithm could improve the accuracy and reproducibility of the segmentation provided by the combination of three semiautomatic segmentation algorithms was investigated. METHODS: Three published segmentation methods (contrast-oriented, possibility theory and adaptive thresholding) and two consensus algorithms (majority vote and STAPLE) were implemented in a single software platform (Artiview®). Four clinical datasets including different locations (thorax, breast, abdomen) or pathologies (primary NSCLC tumours, metastasis, lymphoma) were used to evaluate accuracy and reproducibility of the consensus approach in comparison with pathology as the ground truth or CT as a ground truth surrogate. RESULTS: Variability in the performance of the individual segmentation algorithms for lesions of different tumour entities reflected the variability in PET images in terms of resolution, contrast and noise. Independent of location and pathology of the lesion, however, the consensus method resulted in improved accuracy in volume segmentation compared with the worst-performing individual method in the majority of cases and was close to the best-performing method in many cases. In addition, the implementation revealed high reproducibility in the segmentation results with small changes in the respective starting conditions. There were no significant differences in the results with the STAPLE algorithm and the majority vote algorithm. CONCLUSION: This study showed that combining different PET segmentation methods by the use of a consensus algorithm offers robustness against the variable performance of individual segmentation methods and this approach would therefore be useful in radiation oncology. It might also be relevant for other scenarios such as the merging of expert recommendations in clinical routine and trials or the multiobserver generation of contours for standardization of automatic contouring.Show less >

Language :

Anglais

Audience :

Internationale

Popular science :

Non

Administrative institution(s) :

Université de Lille
CHU Lille

Collections :

• Groupe de Recherche sur les formes Injectables et les Technologies Associées (GRITA) - ULR 7365

Research team(s) :

Innovation/évaluation des médicaments injectables

Submission date :

2019-02-26T17:07:30Z