title: Serial MR diffusion to predict treatment response in high-grade pediatric brain tumors: a comparison of regional and voxel-based diffusion change metrics.
abstract: BACKGROUND
  Assessment of treatment response by measuring tumor size is known to be a late and potentially confounded response index. Serial diffusion MRI has shown potential for allowing earlier and possibly more reliable response assessment in adult patients, with limited experience in clinical settings and in pediatric brain cancer. We present a retrospective study of clinical MRI data in children with high-grade brain tumors to assess and compare the values of several diffusion change metrics to predict treatment response.
  
  
  METHODS
  Eighteen patients (age range, 1.9-20.6 years) with high-grade brain tumors and serial diffusion MRI (pre- and posttreatment interval range, 1-16 weeks posttreatment) were identified after obtaining parental consent. The following diffusion change metrics were compared with the clinical response status assessed at 6 months: (1) regional change in absolute and normalized apparent diffusivity coefficient (ADC), (2) voxel-based fractional volume of increased (fiADC) and decreased ADC (fdADC), and (3) a new metric based on the slope of the first principal component of functional diffusion maps (fDM).
  
  
  RESULTS
  Responders (n = 12) differed significantly from nonresponders (n = 6) in all 3 diffusional change metrics demonstrating higher regional ADC increase, larger fiADC, and steeper slopes (P < .05). The slope method allowed the best response prediction (P < .01, η(2) = 0.78) with a classification accuracy of 83% for a slope of 58° using receiver operating characteristic (ROC) analysis.
  
  
  CONCLUSIONS
  We demonstrate that diffusion change metrics are suitable response predictors for high-grade pediatric tumors, even in the presence of variable clinical diffusion imaging protocols.
authors.affiliation: Division of Radiological and Imaging Sciences, University of Nottingham, Nottingham, United Kingdom.
authors.forename: Daniel
authors.initials: D
authors.lastname: Rodriguez Gutierrez
authors.forename: Muftah
authors.initials: M
authors.lastname: Manita
authors.forename: Tim
authors.initials: T
authors.lastname: Jaspan
authors.forename: Robert A
authors.initials: RA
authors.lastname: Dineen
authors.forename: Richard G
authors.initials: RG
authors.lastname: Grundy
authors.forename: Dorothee P
authors.initials: DP
authors.lastname: Auer
mesh_terms: D000293:Adolescent; D000328:Adult; D015415:Biomarkers / Q000032:analysis*; D001932:Brain Neoplasms / Q000175:diagnosis / Q000628:therapy*; D059248:Chemoradiotherapy; D002648:Child; D002675:Child, Preschool; D003287:Contrast Media; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007223:Infant; D008297:Male; D060787:Neoplasm Grading; D009364:Neoplasm Recurrence, Local / Q000175:diagnosis*; D025341:Principal Component Analysis; D011379:Prognosis; D012372:ROC Curve; D055815:Young Adult
chemical_list: D015415:Biomarkers; D003287:Contrast Media
keywords: ADC; fDM; pediatric tumor; response prediction; serial diffusion