Computational and Mathematical Methods in Medicine
Volume 2012 (2012), Article ID 482565, 6 pages
Research Article

Theoretical Compartment Modeling of DCE-MRI Data Based on the Transport across Physiological Barriers in the Brain

1Department of Biomedical Physics, Physics Faculty, Babes-Bolyai University, No. 1 M. Kogalniceanu Street, 400084 Cluj-Napoca, Romania
2Department of Radiology, Cluj County Emergency Hospital, No. 3-5, Clinicilor Street, 400006 Cluj-Napoca, Romania
3Faculty of Pharmacy, University of Salerno, Via Ponte Don Melilo, 84084 Fisciano, Italy

Received 29 September 2011; Accepted 18 February 2012

Academic Editor: Maria Crisan

Copyright © 2012 Laura Fanea 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.


Neurological disorders represent major causes of lost years of healthy life and mortality worldwide. Development of their quantitative interdisciplinary in vivo evaluation is required. Compartment modeling (CM) of brain data acquired in vivo using magnetic resonance imaging techniques with clinically available contrast agents can be performed to quantitatively assess brain perfusion. Transport of 1H spins in water molecules across physiological compartmental brain barriers in three different pools was mathematically modeled and theoretically evaluated in this paper and the corresponding theoretical compartment modeling of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data was analyzed. The pools considered were blood, tissue, and cerebrospinal fluid (CSF). The blood and CSF data were mathematically modeled assuming continuous flow of the 1H spins in these pools. Tissue data was modeled using three CMs. Results in this paper show that transport across physiological brain barriers such as the blood to brain barrier, the extracellular space to the intracellular space barrier, or the blood to CSF barrier can be evaluated quantitatively. Statistical evaluations of this quantitative information may be performed to assess tissue perfusion, barriers' integrity, and CSF flow in vivo in the normal or disease-affected brain or to assess response to therapy.