Computational and Mathematical Methods in Medicine
Volume 2013 (2013), Article ID 149608, 12 pages
Spatiotemporal Quantification of Local Drug Delivery Using MRI
1Center for Interventional Biomaterials, School of Biological and Health Systems Engineering, Arizona State University, P.O. Box 879709, Tempe, AZ 85287, USA
2Banner Good Samaritan Medical Center, 901 E Willetta Street, 2nd Floor, Phoenix, AZ 85006, USA
3Image Processing Application Laboratory, School of Biological and Health Systems Engineering, Arizona State University, P.O. Box 879709, Tempe, AZ 85287, USA
Received 20 December 2012; Revised 25 March 2013; Accepted 26 March 2013
Academic Editor: Wenxiang Cong
Copyright © 2013 Morgan B. Giers et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Controlled release formulations for local, in vivo drug delivery are of growing interest to device manufacturers, research scientists, and clinicians; however, most research characterizing controlled release formulations occurs in vitro because the spatial and temporal distribution of drug delivery is difficult to measure in vivo. In this work, in vivo magnetic resonance imaging (MRI) of local drug delivery was performed to visualize and quantify the time resolved distribution of MRI contrast agents. Three-dimensional maps (generated from -weighted images with varied ) were processed using noise-reducing filtering. A segmented region of contrast, from a thresholded image, was converted to concentration maps using the equation , where and are the precontrast and postcontrast map values, respectively. In this technique, a uniform estimated value for was used. Error estimations were performed for each step. The practical usefulness of this method was assessed using comparisons between devices located in different locations both with and without contrast. The method using a uniform , requiring no registration of pre- and postcontrast image volumes, was compared to a method using either affine or deformation registrations.