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

Abstract

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.

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“…10,52 It was found that the average transverse relaxation time (T 2 ) for all samples were lower than $100 ms, while in the absence of any CA, it is $3000 ms for pure water and $2000 ms for normal saline. 55,56 Among the CA samples, the SPIO-Dex-FGO one showed the lowest value for T 2 and so the best SNR.…”

“…6, average longitudinal relaxation times (T 1 ) for all samples were below 1500 ms, while in absence of any CA, it is $3000 ms for pure water and $2000 ms for normal saline. 55,56 In other words, all of the synthesized CAs, especially the SPIO-Dex-FGO, are signicantly capable of T 1 shortening. This is desirable, because based on eqn (2), decrease in T 1 results in increase of the signal intensity.…”

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