ABSTRACT
DCE-MRI is a diagnostic method that can visualize neoangiogenic-induced vascular changes. Typically, the analysis of these data is time-consuming and the visualization of the quantitative information on tumor vasculature, derivable from DCE-MRI, is not easy and comfortable. In this study, we propose a method to accelerate computation and analysis of DCE-MRI data, while making easy to use the functional information obtained from model-based functional analysis.
Subject(s)
Breast Neoplasms/pathology , Diffusion Magnetic Resonance Imaging/methods , Image Interpretation, Computer-Assisted , Breast Neoplasms/blood supply , Contrast Media , Female , Gadolinium DTPA , Humans , Neoplasm StagingABSTRACT
Passive diffusion samplers were employed in San Miguel (Buenos Aires Metropolitan Area) for a preliminary air pollution monitoring. The highest loads were observed in downtown, compared with an urban background site. Total suspended particulate matter (TSPM) varied from 0.257 to 0.033 mg cm(-2) month(-1); dust was examined for particle nature and size distribution. A similar trend was observed for nitrogen dioxide (NO2) and TSPM spatial distribution, suggesting that traffic is the major pollution source. Sulphur dioxide (SO2) values were low and rather homogeneous. Levels for the investigated pollutants are below EPA's guide line values. Geographic (flat area, near to Rio de La Plata) and climatologic factors (rainfalls and variable wind directions) contribute to disperse pollutants.
