title: Connectome analysis for pre-operative brain mapping in neurosurgery.
abstract: OBJECTIVE
  Brain mapping has entered a new era focusing on complex network connectivity. Central to this is the search for the connectome or the brains 'wiring diagram'. Graph theory analysis of the connectome allows understanding of the importance of regions to network function, and the consequences of their impairment or excision. Our goal was to apply connectome analysis in patients with brain tumours to characterise overall network topology and individual patterns of connectivity alterations.
  
  
  METHODS
  Resting-state functional MRI data were acquired using multi-echo, echo planar imaging pre-operatively from five participants each with a right temporal-parietal-occipital glioblastoma. Complex networks analysis was initiated by parcellating the brain into anatomically regions amongst which connections were identified by retaining the most significant correlations between the respective wavelet decomposed time-series.
  
  
  RESULTS
  Key characteristics of complex networks described in healthy controls were preserved in these patients, including ubiquitous small world organization. An exponentially truncated power law fit to the degree distribution predicted findings of general network robustness to injury but with a core of hubs exhibiting disproportionate vulnerability. Tumours produced a consistent reduction in local and long-range connectivity with distinct patterns of connection loss depending on lesion location.
  
  
  CONCLUSIONS
  Connectome analysis is a feasible and novel approach to brain mapping in individual patients with brain tumours. Applications to pre-surgical planning include identifying regions critical to network function that should be preserved and visualising connections at risk from tumour resection. In the future one could use such data to model functional plasticity and recovery of cognitive deficits.
authors.affiliation: a Brain Mapping Unit, Department of Psychiatry , University of Cambridge, Sir William Hardy Building , Cambridge , UK ;|b Division of Neurosurgery, Department of Clinical Neurosciences , Cambridge Biomedical Campus , Cambridge , UK ;
authors.forename: Michael G
authors.initials: MG
authors.lastname: Hart
authors.affiliation: b Division of Neurosurgery, Department of Clinical Neurosciences , Cambridge Biomedical Campus , Cambridge , UK ;
authors.forename: Stephen J
authors.initials: SJ
authors.lastname: Price
authors.affiliation: c Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences , Cambridge , UK.
authors.forename: John
authors.initials: J
authors.lastname: Suckling
mesh_terms: D000328:Adult; D000368:Aged; D001931:Brain Mapping / Q000379:methods*; D001932:Brain Neoplasms / Q000000981:diagnostic imaging / Q000601:surgery; D063132:Connectome / Q000379:methods*; D017352:Echo-Planar Imaging; D005260:Female; D005909:Glioblastoma / Q000000981:diagnostic imaging / Q000601:surgery; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007430:Intraoperative Care / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D009493:Neurosurgery / Q000379:methods*; D019635:Neurosurgical Procedures / Q000379:methods; D015203:Reproducibility of Results; D058067:Wavelet Analysis
keywords: Brain mapping; connectome; echo-planar imaging; glioblastoma; magnetic resonance imaging; neurosurgery