title: Prospective analysis of parametric response map-derived MRI biomarkers: identification of early and distinct glioma response patterns not predicted by standard radiographic assessment.
abstract: OBJECTIVE
  Currently, radiologic response of brain tumors is assessed according to the Macdonald criteria 10 weeks from the start of therapy. There exists a critical need to identify nonresponding patients early in the course of their therapy for consideration of alternative treatment strategies. Our study assessed the effectiveness of the parametric response map (PRM) imaging biomarker to provide for an earlier measure of patient survival prediction.
  
  
  METHODS
  Forty-five high-grade glioma patients received concurrent chemoradiation. Quantitative MRI including apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) maps were acquired pretreatment and 3 weeks midtreatment on a prospective institutional-approved study. PRM, a voxel-by-voxel image analysis method, was evaluated as an early prognostic biomarker of overall survival. Clinical and conventional MR parameters were also evaluated.
  
  
  RESULTS
  Multivariate analysis showed that PRM(ADC+) in combination with PRM(rCBV-) obtained at week 3 had a stronger correlation to 1-year and overall survival rates than any baseline clinical or treatment response imaging metric. The composite biomarker identified three distinct patient groups, nonresponders [median survival (MS) of 5.5 months, 95% CI: 4.4-6.6 months], partial responders (MS of 16 months, 95% CI: 8.6-23.4 months), and responders (MS has not yet been reached).
  
  
  CONCLUSIONS
  Inclusion of PRM(ADC+) and PRM(rCBV-) into a single imaging biomarker metric provided early identification of patients resistant to standard chemoradiation. In comparison to the current standard of assessment of response at 10 weeks (Macdonald criteria), the composite PRM biomarker potentially provides a useful opportunity for clinicians to identify patients who may benefit from alternative treatment strategies.
authors.affiliation: Department of Radiology, University of Michigan, Center for Molecular Imaging, Ann Arbor, Michigan 48109, USA.
authors.forename: Craig J
authors.initials: CJ
authors.lastname: Galbán
authors.forename: Thomas L
authors.initials: TL
authors.lastname: Chenevert
authors.forename: Charles R
authors.initials: CR
authors.lastname: Meyer
authors.forename: Christina
authors.initials: C
authors.lastname: Tsien
authors.forename: Theodore S
authors.initials: TS
authors.lastname: Lawrence
authors.forename: Daniel A
authors.initials: DA
authors.lastname: Hamstra
authors.forename: Larry
authors.initials: L
authors.lastname: Junck
authors.forename: Pia C
authors.initials: PC
authors.lastname: Sundgren
authors.forename: Timothy D
authors.initials: TD
authors.lastname: Johnson
authors.forename: Stefanie
authors.initials: S
authors.lastname: Galbán
authors.forename: Judith S
authors.initials: JS
authors.lastname: Sebolt-Leopold
authors.forename: Alnawaz
authors.initials: A
authors.lastname: Rehemtulla
authors.forename: Brian D
authors.initials: BD
authors.lastname: Ross
mesh_terms: D015415:Biomarkers; D001932:Brain Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000401:mortality; D005910:Glioma / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000401:mortality; D006801:Humans; D053208:Kaplan-Meier Estimate; D008279:Magnetic Resonance Imaging; D008875:Middle Aged; D015233:Models, Statistical; D009367:Neoplasm Staging; D011379:Prognosis; D011446:Prospective Studies; D011859:Radiography
chemical_list: D015415:Biomarkers