Fiche publication
Date publication
février 2018
Journal
Healthcare technology letters
Auteurs
Membres identifiés du Cancéropôle Est :
Pr TAILLANDIER Luc
,
Pr MOUREAUX Jean-Marie
Tous les auteurs :
Ben Abdallah M, Blonski M, Wantz-Mézières S, Gaudeau Y, Taillandier L, Moureaux JM
Lien Pubmed
Résumé
Management of diffuse low-grade glioma (DLGG) relies extensively on tumour volume estimation from MRI datasets. Two methods are currently clinically used to define this volume: the commonly used three-diameters solution and the more rarely used software-based volume reconstruction from the manual segmentations approach. The authors conducted an initial study of inter-practitioners' variability of software-based manual segmentations on DLGGs MRI datasets. A panel of 13 experts from various specialties and years of experience delineated 12 DLGGs' MRI scans. A statistical analysis on the segmented tumour volumes and pixels indicated that the individual practitioner, the years of experience and the specialty seem to have no significant impact on the segmentation of DLGGs. This is an interesting result as it had not yet been demonstrated and as it encourages cross-disciplinary collaboration. Their second study was with the three-diameters method, investigating its impact and that of the software-based volume reconstruction from manual segmentations method on tumour volume. They relied on the same dataset and on a participant from the first study. They compared the average of tumour volumes acquired by software reconstruction from manual segmentations method with tumour volumes obtained with the three-diameters method. The authors found that there is no statistically significant difference between the volumes estimated with the two approaches. These results correspond to non-operated and easily delineable DLGGs and are particularly interesting for time-consuming CUBE MRIs. Nonetheless, the three-diameters method has limitations in estimating tumour volumes for resected DLGGs, for which case the software-based manual segmentation method becomes more appropriate.
Mots clés
DLGGs MRI datasets, MRI dataset estimation, biomedical MRI, brain, cancer, delineated DLGGs' MRI scans, diffuse low-grade gliomas, image reconstruction, image segmentation, inter-practitioners variability, manual segmentations approach, manual tumour volume estimation methods, medical image processing, pixels, resected DLGGs, segmented tumour volumes, software-based manual segmentations, software-based volume reconstruction, statistical analysis, three-diameters solution, tumours
Référence
Healthc Technol Lett. 2018 Feb;5(1):13-17
