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Erschienen in: Clinical Neuroradiology 2/2017

21.10.2015 | Original Article

Reliability of Semi-Automated Segmentations in Glioblastoma

verfasst von: T Huber, G Alber, S Bette, T Boeckh-Behrens, J Gempt, F Ringel, E Alberts, C Zimmer, J S Bauer

Erschienen in: Clinical Neuroradiology | Ausgabe 2/2017

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Abstract

Purpose

In glioblastoma, quantitative volumetric measurements of contrast-enhancing or fluid-attenuated inversion recovery (FLAIR) hyperintense tumor compartments are needed for an objective assessment of therapy response. The aim of this study was to evaluate the reliability of a semi-automated, region-growing segmentation tool for determining tumor volume in patients with glioblastoma among different users of the software.

Methods

A total of 320 segmentations of tumor-associated FLAIR changes and contrast-enhancing tumor tissue were performed by different raters (neuroradiologists, medical students, and volunteers). All patients underwent high-resolution magnetic resonance imaging including a 3D-FLAIR and a 3D-MPRage sequence. Segmentations were done using a semi-automated, region-growing segmentation tool. Intra- and inter-rater-reliability were addressed by intra-class-correlation (ICC). Root-mean-square error (RMSE) was used to determine the precision error. Dice score was calculated to measure the overlap between segmentations.

Results

Semi-automated segmentation showed a high ICC (> 0.985) for all groups indicating an excellent intra- and inter-rater-reliability. Significant smaller precision errors and higher Dice scores were observed for FLAIR segmentations compared with segmentations of contrast-enhancement. Single rater segmentations showed the lowest RMSE for FLAIR of 3.3 % (MPRage: 8.2 %). Both, single raters and neuroradiologists had the lowest precision error for longitudinal evaluation of FLAIR changes.

Conclusions

Semi-automated volumetry of glioblastoma was reliably performed by all groups of raters, even without neuroradiologic expertise. Interestingly, segmentations of tumor-associated FLAIR changes were more reliable than segmentations of contrast enhancement. In longitudinal evaluations, an experienced rater can detect progressive FLAIR changes of less than 15 % reliably in a quantitative way which could help to detect progressive disease earlier.
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Metadaten
Titel
Reliability of Semi-Automated Segmentations in Glioblastoma
verfasst von
T Huber
G Alber
S Bette
T Boeckh-Behrens
J Gempt
F Ringel
E Alberts
C Zimmer
J S Bauer
Publikationsdatum
21.10.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
Clinical Neuroradiology / Ausgabe 2/2017
Print ISSN: 1869-1439
Elektronische ISSN: 1869-1447
DOI
https://doi.org/10.1007/s00062-015-0471-2

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