Fluorine-18-labeled estrogens, progestins and corticosteroids for receptor-based imaging of breast tumors and target areas of the brain

Estrogens can be labeled with the positron-emitting radionuclide fluorine-18 (t$\sb{1/2}$ = 110 min) by fluoride ion (n-Bu$\sb4$N$\sp{18}$F) displacement of a 16$\beta$-trifluoromethanesulfonate (triflate) derivative of the corresponding estrone 3-triflate, and purification by HPLC. That sequence has been used to synthesize the 11$\beta$-methoxy 1 and 11$\beta$-ethyl 2 analogues of the breast tumor imaging agent, 16$\alpha$-($\sp{18}$F) fluoro-17$\beta$-estradiol (FES). Tissue distribution studies of 1 and 2 in immature female rats show high selectivity for target tissue (T, uterus) vs non-target (NT, muscle and lung), with T/NT ratios being 43 and 17 at one hour after injection for 1 and 2, respectively. The parent estrogen FES has previously been shown to display an intermediate value for tissue selectivity.

Using a voxel-based krogh cylinder array to simulate microvascular contrast enhancement

The goal of this study is to better simulate microscopic and voxel-based dynamic contrast enhancement in magnetic resonance imaging. Specifically, errors imposed by the traditional two-compartment model are reduced by introducing a novel Krogh cylinder network. The two-compartment model was developed for macroscopic pharmacokinetic analysis of dynamic contrast enhancement and generalizing it to voxel dimensions, due to the significant decrease in scale, imposes physiologically unrealistic assumptions. In the project, a system of microscopic exchange between plasma and extravascular-extracellular space is built while numerically simulating the local contrast agent flow between and inside image elements. To do this, tissue parameter maps were created, contrast agent was introduced to the tissue via a flow lattice, and various data sets were simulated. The effects of sources, tissue heterogeneity, and the contribution of individual tissue parameters to an image are modeled. Further, the study attempts to demonstrate the effects of a priori flow maps on image contrast, indicating that flow data is as important as permeability data when analyzing tumor contrast enhancement. In addition, the simulations indicate that it may be possible to obtain tumor-type diagnostic information by acquiring both flow and permeability data.