title: Population-based MRI atlases of spatial distribution are specific to patient and tumor characteristics in glioblastoma.
abstract: In treating glioblastoma (GB), surgical and chemotherapeutic treatment guidelines are, for the most part, independent of tumor location. In this work, we compiled imaging data from a large cohort of GB patients to create statistical atlases illustrating the disease spatial frequency as a function of patient demographics as well as tumor characteristics.
  
  
  
  Two-hundred-six patients with pathology-proven glioblastoma were included. Of those, 65 had pathology-proven recurrence and 113 had molecular subtype and genetic information. We used validated software to segment the tumors in all patients and map them from patient space into a common template. We then created statistical maps that described the spatial location of tumors with respect to demographics and tumor characteristics. We applied a chi-square test to determine whether pattern differences were statistically significant.
  
  
  
  The most frequent location for glioblastoma in our patient population is the right temporal lobe. There are statistically significant differences when comparing patterns using demographic data such as gender (p = 0.0006) and age (p = 0.006). Small and large tumors tend to occur in separate locations (p = 0.0007). The tumors tend to occur in different locations according to their molecular subtypes (p < 10(- 6)). The classical subtype tends to spare the frontal lobes, the neural subtype tend to involve the inferior right frontal lobe. Although the sample size is limited, there was a difference in location according to EGFR VIII genotype (p < 10(- 4)), with a right temporal dominance for EFGR VIII negative tumors, and frontal lobe dominance in EGFR VIII positive tumors.
  
  
  
  Spatial location of GB is an important factor that correlates with demographic factors and tumor characteristics, which should therefore be considered when evaluating a patient with GB and might assist in personalized treatment.
authors.affiliation: Department of Radiology, University of Pennsylvania, Philadelphia, USA.
authors.forename: Michel
authors.initials: M
authors.lastname: Bilello
authors.affiliation: Department of Radiology, University of Pennsylvania, Philadelphia, USA.
authors.forename: Hamed
authors.initials: H
authors.lastname: Akbari
authors.affiliation: Department of Radiology, University of Pennsylvania, Philadelphia, USA.
authors.forename: Xiao
authors.initials: X
authors.lastname: Da
authors.affiliation: Department of Neurosurgery, University of Pennsylvania, Philadelphia, USA.
authors.forename: Jared M
authors.initials: JM
authors.lastname: Pisapia
authors.affiliation: Department of Radiology, University of Pennsylvania, Philadelphia, USA.
authors.forename: Suyash
authors.initials: S
authors.lastname: Mohan
authors.affiliation: Department of Radiology, University of Pennsylvania, Philadelphia, USA.
authors.forename: Ronald L
authors.initials: RL
authors.lastname: Wolf
authors.affiliation: Department of Neurosurgery, University of Pennsylvania, Philadelphia, USA.
authors.forename: Donald M
authors.initials: DM
authors.lastname: O'Rourke
authors.affiliation: Department of Pathology & Laboratory Medicine, University of Pennsylvania, Philadelphia, USA.
authors.forename: Maria
authors.initials: M
authors.lastname: Martinez-Lage
authors.affiliation: Department of Radiology, University of Pennsylvania, Philadelphia, USA.
authors.forename: Christos
authors.initials: C
authors.lastname: Davatzikos
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001271:Atlases as Topic; D001932:Brain Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology*; D005260:Female; D005909:Glioblastoma / Q000000981:diagnostic imaging / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D055815:Young Adult
keywords: Atlas; Glioblastoma; MRI; Spatial; Statistical