title: Indexed distribution analysis for improved significance testing of spatially heterogeneous parameter maps: application to dynamic contrast-enhanced MRI biomarkers.
abstract: OBJECTIVE
  To develop significance testing methodology applicable to spatially heterogeneous parametric maps of biophysical and physiological measurements arising from imaging studies.
  
  
  BACKGROUND
  Heterogeneity can confound statistical analyses. Indexed distribution analysis (IDA) transforms a reference distribution, establishing correspondences across parameter maps to which significance tests are applied.
  
  
  METHODS
  Well-controlled simulated and clinical K(trans) data from a dynamic contrast-enhanced magnetic resonance imaging study of bevacizumab were analyzed using conventional significance tests of parameter averages, histogram analysis, and IDA. Repeated pretreatment scans provided negative control; a post treatment scan provided positive control.
  
  
  RESULTS
  Histogram analysis was insensitive to simulated and known effects. Simulation: conventional analysis identified treatment effect (P ≈ 5 × 10(-4)) and direction, but underestimated magnitude (relative error 67-81%); IDA identified treatment effect (P = 0.001), magnitude, direction, and spatial extent (100% accuracy). Bevacizumab: conventional analysis was sensitive to treatment effect (P = 0.01; 95% confidence interval on K(trans) decrease: 23-37%); IDA was sensitive to treatment effect (P < 0.05; K(trans) decrease approximately 25%), inferred its spatial extent to be 94-96%, and inferred that K(trans) decrease is independent of baseline value, an inference that conventional and histogram analyses cannot make.
  
  
  CONCLUSIONS
  In the presence of heterogeneity, IDA can accurately infer the magnitude, direction, and spatial extent of between samples of parametric maps, which can be visualized spatially with respect to the original parameter maps.
authors.affiliation: Centre for Imaging Sciences, Manchester Academic Health Science Centre, The University of Manchester, UK; The University of Manchester Biomedical Imaging Institute, UK.
authors.forename: Chris J
authors.initials: CJ
authors.lastname: Rose
authors.forename: James P B
authors.initials: JP
authors.lastname: O'Connor
authors.forename: Tim F
authors.initials: TF
authors.lastname: Cootes
authors.forename: Chris J
authors.initials: CJ
authors.lastname: Taylor
authors.forename: Gordon C
authors.initials: GC
authors.lastname: Jayson
authors.forename: Geoff J M
authors.initials: GJ
authors.lastname: Parker
authors.forename: John C
authors.initials: JC
authors.lastname: Waterton
mesh_terms: D061067:Antibodies, Monoclonal, Humanized / Q000627:therapeutic use*; D000068258:Bevacizumab; D015415:Biomarkers; D015179:Colorectal Neoplasms / Q000188:drug therapy* / Q000473:pathology*; D003287:Contrast Media; D003627:Data Interpretation, Statistical; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D011379:Prognosis; D015203:Reproducibility of Results; D018401:Sample Size; D012680:Sensitivity and Specificity; D062211:Spatio-Temporal Analysis; D016896:Treatment Outcome
chemical_list: D061067:Antibodies, Monoclonal, Humanized; D015415:Biomarkers; D003287:Contrast Media; D000068258:Bevacizumab