title: The impact of heterogeneity and uncertainty on prediction of response to therapy using dynamic MRI data.
abstract: A comprehensive framework for predicting response to therapy on the basis of heterogeneity in dceMRI parameter maps is presented. A motion-correction method for dceMRI sequences is extended to incorporate uncertainties in the pharmacokinetic parameter maps using a variational Bayes framework. Simple measures of heterogeneity (with and without uncertainty) in parameter maps for colorectal cancer tumours imaged before therapy are computed, and tested for their ability to distinguish between responders and non-responders to therapy. The statistical analysis demonstrates the importance of using the spatial distribution of parameters, and their uncertainties, when computing heterogeneity measures and using them to predict response on the basis of the pre-therapy scan. The results also demonstrate the benefits of using the ratio of Ktrans with the bolus arrival time as a biomarker.
authors: Institute of Biomedical Engineering (Department of Engineering Science), University of Oxford, UK.
authors: Manav
authors: M
authors: Bhushan
authors: Institute of Biomedical Engineering (Department of Engineering Science), University of Oxford, UK.
authors: Julia A
authors: JA
authors: Schnabel
authors: Institute of Biomedical Engineering (Department of Engineering Science), University of Oxford, UK.
authors: Michael
authors: M
authors: Chappell
authors: Department of Radiology, Churchill Hospital, Oxford, UK
authors: Fergus
authors: F
authors: Gleeson
authors: Department of Radiology, Churchill Hospital, Oxford, UK
authors: Mark
authors: M
authors: Anderson
authors: Department of Radiology, Churchill Hospital, Oxford, UK
authors: Jamie
authors: J
authors: Franklin
authors: Department of Oncology, University of Oxford, UK.
authors: Sir Michael
authors: SM
authors: Brady
authors: The Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, UK
authors: Mark
authors: M
authors: Jenkinson
mesh_terms: D000465:Algorithms; D015179:Colorectal Neoplasms / Q000378:metabolism / Q000473:pathology* / Q000532:radiotherapy*; D003198:Computer Simulation; D003287:Contrast Media / Q000493:pharmacokinetics; D003627:Data Interpretation, Statistical; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008536:Meglumine / Q000031:analogs & derivatives* / Q000493:pharmacokinetics; D008954:Models, Biological; D009942:Organometallic Compounds / Q000493:pharmacokinetics; D017063:Outcome Assessment, Health Care / Q000379:methods*; D011379:Prognosis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016896:Treatment Outcome
chemical_list: D003287:Contrast Media; D009942:Organometallic Compounds; C064572:gadobenic acid; D008536:Meglumine