title: Comparison of DCE-CT models for quantitative evaluation of K(trans) in larynx tumors.
abstract: Dynamic contrast enhanced CT (DCE-CT) can be used to estimate blood perfusion and vessel permeability in tumors. Tumor induced angiogenesis is generally associated with disorganized microvasculature with increased permeability or leakage. Estimated vascular leakage (K(trans)) values and their reliability greatly depend on the perfusion model used. To identify the preferred model for larynx tumor analysis, several perfusion models frequently used for estimating permeability were compared in this study. DCE-CT scans were acquired for 16 larynx cancer patients. Larynx tumors were delineated based on whole-mount histopathology after laryngectomy. DCE-CT data within these delineated volumes were analyzed using the Patlak and Logan plots, the Extended Tofts Model (ETM), the Adiabatic Approximation to the Tissue Homogeneity model (AATH) and a variant of AATH with fixed transit time (AATHFT). Akaike's Information Criterion (AIC) was used to identify the best fitting model. K(trans) values from all models were compared with this best fitting model. Correlation strength was tested with two-tailed Spearman's rank correlation and further examined using Bland-Altman plots. AATHFT was found to be the best fitting model. The overall median of individual patient medians K(trans) estimates were 14.3, 15.1, 16.1, 2.6 and 22.5 mL/100 g min(  -  1) for AATH, AATHFT, ETM, Patlak and Logan, respectively. K(trans) estimates for all models except Patlak were strongly correlated (P  <  0.001). Bland-Altman plots show large biases but no significant deviating trend for any model other than Patlak. AATHFT was found to be the preferred model among those tested for estimation of K(trans) in larynx tumors.
authors.affiliation: Division of Medical Imaging, University Medical Centre Utrecht, Utrecht, The Netherlands.
authors.forename: J
authors.initials: J
authors.lastname: Oosterbroek
authors.forename: E
authors.initials: E
authors.lastname: Bennink
authors.forename: M E P
authors.initials: ME
authors.lastname: Philippens
authors.forename: C P J
authors.initials: CP
authors.lastname: Raaijmakers
authors.forename: M A
authors.initials: MA
authors.lastname: Viergever
authors.forename: H W A M
authors.initials: HW
authors.lastname: de Jong
mesh_terms: D000465:Algorithms; D003287:Contrast Media; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007822:Laryngeal Neoplasms / Q000175:diagnosis*; D009389:Neovascularization, Pathologic / Q000175:diagnosis*; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D003287:Contrast Media