title: DCE-MRI model selection for investigating disruption of microvascular function in livers with metastatic disease.
abstract: OBJECTIVE
  To evaluate the Akaike information criterion (AIC) model selection technique as a method for detecting differences in microvascular characteristics between tumorous and non-tumor liver tissue.
  
  
  METHODS
  The AIC was applied to six patient datasets with liver metastases to determine, on a per voxel basis, which of two physiologically plausible candidate models gave a more appropriate description of the data. The dual-input single-compartment Materne model, extended to incorporate a novel portal input function estimation method, was chosen to represent liver tissue and the single-input dual-compartment extended Kety model was used for tumor.
  
  
  RESULTS
  Median AIC probabilities when comparing tumor versus liver and tumor versus tumor-margins were significantly different (P ≤ 0.01) in five of the six patient datasets. Comparisons between tumor margins and liver regions were significantly different in four datasets. Median AIC probabilities selected for the extended Kety model in all tumor regions, with the Materne model being progressively more probable through tumor margins into liver.
  
  
  CONCLUSIONS
  We present a viable method for assessing the spatially varying microvascular characteristics of tumor-bearing livers, with possible applications in lesion detection, assessment of tumor invasion, and measurement of drug efficacy.
authors: Imaging Sciences, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
authors: Anita
authors: A
authors: Banerji
authors: Josephine H
authors: JH
authors: Naish
authors: Yvonne
authors: Y
authors: Watson
authors: Gordon C
authors: GC
authors: Jayson
authors: Giovanni A
authors: GA
authors: Buonaccorsi
authors: Geoffrey J M
authors: GJ
authors: Parker
mesh_terms: D003287:Contrast Media / Q000494:pharmacology*; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D008099:Liver / Q000473:pathology*; D008113:Liver Neoplasms / Q000175:diagnosis* / Q000473:pathology* / Q000556:secondary; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008833:Microcirculation; D015233:Models, Statistical; D009362:Neoplasm Metastasis; D019047:Phantoms, Imaging; D011336:Probability; D012189:Retrospective Studies; D012984:Software
chemical_list: D003287:Contrast Media