Figure 4.

The 2D τ_i/K^trans parameter space for three different modelings of the Fig. 1d suspicious ROI points. Each oval (two are 1D) has radii equal to 2SD of the parameter values returned from 400 Monte Carlo fittings with starting magnitudes randomly distributed over the entire plot. [The fitting points (gray) are shown for the FXR-a analysis.] The three models are labeled: the SM(FXL-c) approach [Eqs. (1)-(4), τ_b = τ_i → 0]; the SSM(FXR-a) approach [Eq. (5), ${{\mathrm{R}}_{2\mathrm{S}}}^{\ast }\to \infty ,{{\mathrm{R}}_{2\mathrm{L}}}^{\ast }\to 0$] fittings; and the SSM(SXR-a) approach [Eqs. (5) - (7), ${{\mathrm{R}}_{2\mathrm{S}}}^{\ast }\to \infty ,{{\mathrm{R}}_{2\mathrm{L}}}^{\ast }\to 0$]. The FXL-c and SXR-a ovals are one dimensional. In the former, the τ_i value is constrained to be effectively zero. In the latter, the τ_i values returned are all pegged at the upper bound, 40 s, of the SSM(SXR-a) τ_i iteration (note the ordinate scale break). Neither of these τ_i values is realistic. In contrast, the mean τ_i value returned by FXR-a is 0.41 (± 0.02) s, which is quite reasonable.