Multi-modal glioblastoma segmentation: man versus machine.
Multi-modal glioblastoma segmentation: man versus machine.
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DOI：
10.1371/journal.pone.0096873
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Wiest R
中科院分区：
文献类型：
--
作者：
Porz N;Bauer S;Pica A;Schucht P;Beck J;Verma RK;Slotboom J;Reyes M;Wiest R
脑肿瘤磁共振图像的可重复性分割是一个重要的临床需要。本研究的目的是评估一种新的全自动分割工具的可靠性，用于脑肿瘤图像分析，比较人工定义的肿瘤分割。我们前瞻性地评估了25例胶质母细胞瘤患者的术前MR图像。两名独立的评估专家进行了手动分割。使用脑肿瘤图像分析软件（BraTumIA）进行自动分割。为了研究不同的肿瘤腔室，分别鉴定肿瘤体积全TV（增强部分加非增强部分加肿瘤坏死核心）、TV+ （TV +水肿）和增强肿瘤体积ctv。我们通过计算直径测量值、Dice系数、正预测值、灵敏度、相对体积误差和绝对体积误差来量化人工和自动分割的重叠。自动与人工提取二维直径测量值的比较显示无显著差异（p = 0.29）。自动分割与人工分割的体积分割比较，TV+和TV的Dice重叠系数差异有统计学意义（p<0.05），而CETV的Dice重叠系数差异无统计学意义（p<0.05）。TV+、TV和ctv的Spearman等级相关系数ρ在自动分割和人工分割之间呈极显著相关。肿瘤定位不影响分割的准确性。总之，我们证明BraTumIA通过提供基于横截面直径的肿瘤扩展的准确测量来支持放射科医生和临床医生。自动体积测量与人工肿瘤描绘的CETV肿瘤体积相当，并且在重叠和敏感性方面优于评分间的可变性。
Reproducible segmentation of brain tumors on magnetic resonance images is an important clinical need. This study was designed to evaluate the reliability of a novel fully automated segmentation tool for brain tumor image analysis in comparison to manually defined tumor segmentations. We prospectively evaluated preoperative MR Images from 25 glioblastoma patients. Two independent expert raters performed manual segmentations. Automatic segmentations were performed using the Brain Tumor Image Analysis software (BraTumIA). In order to study the different tumor compartments, the complete tumor volume TV (enhancing part plus non-enhancing part plus necrotic core of the tumor), the TV+ (TV plus edema) and the contrast enhancing tumor volume CETV were identified. We quantified the overlap between manual and automated segmentation by calculation of diameter measurements as well as the Dice coefficients, the positive predictive values, sensitivity, relative volume error and absolute volume error. Comparison of automated versus manual extraction of 2-dimensional diameter measurements showed no significant difference (p = 0.29). Comparison of automated versus manual segmentation of volumetric segmentations showed significant differences for TV+ and TV (p<0.05) but no significant differences for CETV (p>0.05) with regard to the Dice overlap coefficients. Spearman's rank correlation coefficients (ρ) of TV+, TV and CETV showed highly significant correlations between automatic and manual segmentations. Tumor localization did not influence the accuracy of segmentation. In summary, we demonstrated that BraTumIA supports radiologists and clinicians by providing accurate measures of cross-sectional diameter-based tumor extensions. The automated volume measurements were comparable to manual tumor delineation for CETV tumor volumes, and outperformed inter-rater variability for overlap and sensitivity.
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影响因子：
2.5
作者：
Heckel, Frank;Moltz, Jan H.;Hahn, Horst K.
通讯作者：
Hahn, Horst K.
影响因子：
4.1
作者：
DEVAUX, BC;OFALLON, JR;KELLY, PJ
通讯作者：
KELLY, PJ
影响因子：
19.7
作者：
Gutman, David A.;Cooper, Lee A. D.;Brat, Daniel J.
通讯作者：
Brat, Daniel J.
影响因子：
2.5
作者：
Fedorov, Andriy;Beichel, Reinhard;Kalpathy-Cramer, Jayashree;Finet, Julien;Fillion-Robin, Jean-Christophe;Pujol, Sonia;Bauer, Christian;Jennings, Dominique;Fennessy, Fiona;Sonka, Milan;Buatti, John;Aylward, Stephen;Miller, James V.;Pieper, Steve;Kikinis, Ron
通讯作者：
Kikinis, Ron
影响因子：
3.5
作者：
Deeley MA;Chen A;Datteri R;Noble JH;Cmelak AJ;Donnelly EF;Malcolm AW;Moretti L;Jaboin J;Niermann K;Yang ES;Yu DS;Yei F;Koyama T;Ding GX;Dawant BM
通讯作者：
Dawant BM