title: Clinical Evaluation of a Fully-automatic Segmentation Method for Longitudinal Brain Tumor Volumetry.
abstract: Information about the size of a tumor and its temporal evolution is needed for diagnosis as well as treatment of brain tumor patients. The aim of the study was to investigate the potential of a fully-automatic segmentation method, called BraTumIA, for longitudinal brain tumor volumetry by comparing the automatically estimated volumes with ground truth data acquired via manual segmentation. Longitudinal Magnetic Resonance (MR) Imaging data of 14 patients with newly diagnosed glioblastoma encompassing 64 MR acquisitions, ranging from preoperative up to 12 month follow-up images, was analysed. Manual segmentation was performed by two human raters. Strong correlations (R = 0.83-0.96, p < 0.001) were observed between volumetric estimates of BraTumIA and of each of the human raters for the contrast-enhancing (CET) and non-enhancing T2-hyperintense tumor compartments (NCE-T2). A quantitative analysis of the inter-rater disagreement showed that the disagreement between BraTumIA and each of the human raters was comparable to the disagreement between the human raters. In summary, BraTumIA generated volumetric trend curves of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments comparable to estimates of human raters. These findings suggest the potential of automated longitudinal tumor segmentation to substitute manual volumetric follow-up of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments.
authors.affiliation: Institute for Surgical Technology &Biomechanics, University of Bern, Bern, Switzerland.
authors.forename: Raphael
authors.initials: R
authors.lastname: Meier
authors.affiliation: Support Center for Advanced Neuroimaging - Institute for Diagnostic and Interventional Neuroradiology, University Hospital and University of Bern, Bern, Switzerland.
authors.forename: Urspeter
authors.initials: U
authors.lastname: Knecht
authors.affiliation: Support Center for Advanced Neuroimaging - Institute for Diagnostic and Interventional Neuroradiology, University Hospital and University of Bern, Bern, Switzerland.
authors.forename: Tina
authors.initials: T
authors.lastname: Loosli
authors.affiliation: Institute for Surgical Technology &Biomechanics, University of Bern, Bern, Switzerland.|Support Center for Advanced Neuroimaging - Institute for Diagnostic and Interventional Neuroradiology, University Hospital and University of Bern, Bern, Switzerland.
authors.forename: Stefan
authors.initials: S
authors.lastname: Bauer
authors.affiliation: Support Center for Advanced Neuroimaging - Institute for Diagnostic and Interventional Neuroradiology, University Hospital and University of Bern, Bern, Switzerland.
authors.forename: Johannes
authors.initials: J
authors.lastname: Slotboom
authors.affiliation: Support Center for Advanced Neuroimaging - Institute for Diagnostic and Interventional Neuroradiology, University Hospital and University of Bern, Bern, Switzerland.
authors.forename: Roland
authors.initials: R
authors.lastname: Wiest
authors.affiliation: Institute for Surgical Technology &Biomechanics, University of Bern, Bern, Switzerland.
authors.forename: Mauricio
authors.initials: M
authors.lastname: Reyes
mesh_terms: D001331:Automation; D001921:Brain / Q000033:anatomy & histology*; D006801:Humans; D008137:Longitudinal Studies; D008279:Magnetic Resonance Imaging; D011446:Prospective Studies