|Title||GBM volumetry using the 3D Slicer medical image computing platform.|
|Publication Type||Journal Article|
|Year of Publication||2013|
|Authors||Egger, J, Kapur, T, Fedorov, A, Pieper, S, Miller, JV, Veeraraghavan, H, Freisleben, B, Golby, AJ, Nimsky, C, Kikinis, R|
Volumetric change in glioblastoma multiforme (GBM) over time is a critical factor in treatment decisions. Typically, the tumor volume is computed on a slice-by-slice basis using MRI scans obtained at regular intervals. (3D)Slicer - a free platform for biomedical research - provides an alternative to this manual slice-by-slice segmentation process, which is significantly faster and requires less user interaction. In this study, 4 physicians segmented GBMs in 10 patients, once using the competitive region-growing based GrowCut segmentation module of Slicer, and once purely by drawing boundaries completely manually on a slice-by-slice basis. Furthermore, we provide a variability analysis for three physicians for 12 GBMs. The time required for GrowCut segmentation was on an average 61% of the time required for a pure manual segmentation. A comparison of Slicer-based segmentation with manual slice-by-slice segmentation resulted in a Dice Similarity Coefficient of 88.43 ± 5.23% and a Hausdorff Distance of 2.32 ± 5.23 mm.
|Alternate Journal||Sci Rep|
|PubMed Central ID||PMC3586703|
|Grant List||P41 EB015902 / EB / NIBIB NIH HHS / United States |
P41EB015898 / EB / NIBIB NIH HHS / United States
P41RR019703 / RR / NCRR NIH HHS / United States
R03EB013792 / EB / NIBIB NIH HHS / United States
U54 EB005149 / EB / NIBIB NIH HHS / United States
U54EB005149 / EB / NIBIB NIH HHS / United States
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