title: Expert-validated CSF segmentation of MNI atlas enhances accuracy of virtual glioma growth patterns.
abstract: Biomathematical modeling of glioma growth has been developed to optimize treatments delivery and to evaluate their efficacy. Simulations currently make use of anatomical knowledge from standard MRI atlases. For example, cerebrospinal fluid (CSF) spaces are obtained by automatic thresholding of the MNI atlas, leading to an approximate representation of real anatomy. To correct such inaccuracies, an expert-revised CSF segmentation map of the MNI atlas was built. Several virtual glioma growth patterns of different locations were generated, with and without using the expert-revised version of the MNI atlas. The adequacy between virtual and radiologically observed growth patterns was clearly higher when simulations were based on the expert-revised atlas. This work emphasizes the need for close collaboration between clinicians and researchers in the field of brain tumor modeling.
authors.affiliation: Neurosurgery Department, Hôpital Lariboisière, Paris, France.
authors.forename: A
authors.initials: A
authors.lastname: Amelot
authors.forename: E
authors.initials: E
authors.lastname: Stretton
authors.forename: H
authors.initials: H
authors.lastname: Delingette
authors.forename: N
authors.initials: N
authors.lastname: Ayache
authors.forename: S
authors.initials: S
authors.lastname: Froelich
authors.forename: E
authors.initials: E
authors.lastname: Mandonnet
mesh_terms: D001271:Atlases as Topic; D001921:Brain / Q000473:pathology* / Q000503:physiopathology; D001932:Brain Neoplasms / Q000473:pathology* / Q000503:physiopathology; D002555:Cerebrospinal Fluid; D003198:Computer Simulation; D018450:Disease Progression; D005910:Glioma / Q000473:pathology* / Q000503:physiopathology; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods; D008954:Models, Biological