BACKGROUND: Gliomas are the most common malignant primary brain tumors. Assessment of the tumor volume represents a crucial point in preoperative and postoperative evaluation. OBJECTIVE: To compare pre- and postoperative tumor volumes obtained with an automated, semi-automatic, and manual segmentation tool. Mean processing time of each segmentation techniques was measured. METHODS: Manual segmentation was performed on preoperative and postoperative magnetic resonance images with the open-source software Horos (Horos Project). “SmartBrush,” a tool of the IPlan Cranial software (Brainlab, Feldkirchen, Germany), was used to carry out the semi-automatic segmentation. The open-source BraTumIA software (NeuroImaging Tools and Resources Collaboratory) was employed for the automated segmentation. Pearson correlation coefficient was used to assess volumetric comparison. Subsequently deviation/range and average discrepancy were determined. The Wilcoxon signed-rank test was used to assess statistical significance. RESULTS: A total of 58 patients with a newly diagnosed high-grade glioma were enrolled. The comparison of the volumes calculated with Horos and IPlan showed a strong agreement both on preoperative and postoperative images (respectively: “enhancing” ρ = 0.99-0.78, “fluid-attenuated inversion recovery”ρ = 0.97-0.92, and “total tumor volume” ρ = 0.98-0.95). Agreement between BraTumIA and the other 2 techniques appeared to be strong for preoperative images, but showed a higher disagreement on postoperative images. Mean time expenditure for tumor segmentation was 27 min with manual segmentation, 17 min with semi-automated, and 8 min with automated software. CONCLUSION: The considered segmentation tools showed high agreement in preoperative volumetric assessment. Both manual and semi-automated software appear adequate for the postoperative quantification of residual volume. The evaluated automated software is not yet reliable. Automated software considerably reduces the time expenditure.

How reliable are volumetric techniques for high-grade gliomas? A comparison study of different available tools

Zeppa P.;Neitzert L.;Mammi M.;Monticelli M.;Altieri R.;Castaldo M.;Cofano F.;Borre A.;Zenga F.;Melcarne A.;Garbossa D.
2020

Abstract

BACKGROUND: Gliomas are the most common malignant primary brain tumors. Assessment of the tumor volume represents a crucial point in preoperative and postoperative evaluation. OBJECTIVE: To compare pre- and postoperative tumor volumes obtained with an automated, semi-automatic, and manual segmentation tool. Mean processing time of each segmentation techniques was measured. METHODS: Manual segmentation was performed on preoperative and postoperative magnetic resonance images with the open-source software Horos (Horos Project). “SmartBrush,” a tool of the IPlan Cranial software (Brainlab, Feldkirchen, Germany), was used to carry out the semi-automatic segmentation. The open-source BraTumIA software (NeuroImaging Tools and Resources Collaboratory) was employed for the automated segmentation. Pearson correlation coefficient was used to assess volumetric comparison. Subsequently deviation/range and average discrepancy were determined. The Wilcoxon signed-rank test was used to assess statistical significance. RESULTS: A total of 58 patients with a newly diagnosed high-grade glioma were enrolled. The comparison of the volumes calculated with Horos and IPlan showed a strong agreement both on preoperative and postoperative images (respectively: “enhancing” ρ = 0.99-0.78, “fluid-attenuated inversion recovery”ρ = 0.97-0.92, and “total tumor volume” ρ = 0.98-0.95). Agreement between BraTumIA and the other 2 techniques appeared to be strong for preoperative images, but showed a higher disagreement on postoperative images. Mean time expenditure for tumor segmentation was 27 min with manual segmentation, 17 min with semi-automated, and 8 min with automated software. CONCLUSION: The considered segmentation tools showed high agreement in preoperative volumetric assessment. Both manual and semi-automated software appear adequate for the postoperative quantification of residual volume. The evaluated automated software is not yet reliable. Automated software considerably reduces the time expenditure.
87
6
E672
E679
Glioma tumor volume; High-grade glioma surgery; Segmentation software; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Neuroimaging; Tumor Burden; Brain Neoplasms; Glioma
Zeppa P.; Neitzert L.; Mammi M.; Monticelli M.; Altieri R.; Castaldo M.; Cofano F.; Borre A.; Zenga F.; Melcarne A.; Garbossa D.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/1848492
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