title: How accurately can the parameters from a model of anisotropic 3He gas diffusion in lung acinar airways be estimated? Bayesian view.
abstract: In the framework of a recently proposed method for in vivo lung morphometry, acinar lung airways are considered as a set of randomly oriented cylinders covered by alveolar sleeves. Diffusion of (3)He in each airway is anisotropic and can be described by distinct longitudinal and transverse diffusion coefficients. This macroscopically isotropic but microscopically anisotropic model allows estimation of these diffusion coefficients from multi b-value MR experiments despite the airways being too small to be resolved by direct imaging. Herein a Bayesian approach is used for analyzing the uncertainties in the model parameter estimates. The approach allows evaluation of relative errors of the parameter estimates as functions of the "true" values of the parameters, the signal-to-noise ratio, the maximum b-value and the total number of b-values used in the experiment. For a given set of the "true" diffusion parameters, the uncertainty in the estimated diffusion coefficients has a minimum as a function of maximum b-value and total number of data points. Choosing the MR pulse sequence parameters corresponding to this minimum optimizes the diffusion MR experiment and gives the best possible estimates of the diffusion coefficients. The mathematical approach presented can be generalized for models containing arbitrary numbers of estimated parameters.
authors.affiliation: Department of Radiology, Washington University, St. Louis, MO 63110, USA. alex@wuchem.wustl.edu
authors.forename: Alexander L
authors.initials: AL
authors.lastname: Sukstanskii
authors.forename: G Larry
authors.initials: GL
authors.lastname: Bretthorst
authors.forename: Yulin V
authors.initials: YV
authors.lastname: Chang
authors.forename: Mark S
authors.initials: MS
authors.lastname: Conradi
authors.forename: Dmitriy A
authors.initials: DA
authors.lastname: Yablonskiy
mesh_terms: D016880:Anisotropy; D001499:Bayes Theorem; D003198:Computer Simulation; D003287:Contrast Media / Q000737:chemistry*; D004058:Diffusion; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008168:Lung / Q000737:chemistry* / Q000473:pathology*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008954:Models, Biological; D011656:Pulmonary Emphysema / Q000175:diagnosis / Q000378:metabolism; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D003287:Contrast Media