Functional Imaging: Dynamic Contrast-Enhanced CT using a Distributed-Parameter Physiologic Model for Accessing Stroke and Intracranial Tumor.

Functional imaging has the potential to be a practical and widely-available method of studying the pathphysiology of disease using modern CT and MRI technologies. With the high temporal resolution achievable by these technologies, a two-compartment distributed-parameter model, which more accurate represents the tracer concentration within the vascular space, was applied on two patients' data with intracranial tumor and stroke. The parametric maps successfully generated were more informative than the current commercial software packages and the commonly used lumped-parameter compartmental models.

Dynamic contrast-enhanced CT of intracranial meningioma: comparison of distributed and compartmental tracer kinetic models--initial results.

Dynamic contrast material-enhanced computed tomographic images of intracranial meningioma were analyzed by using both distributed-parameter and conventional compartmental tracer kinetic models. The distributed-parameter models were found to yield consistently better fitting of data sets than were conventional compartmental models. Although linear correlations were found between the kinetic parameters of the two models, some of these parameters (such as perfusion and mean transit time) did not correspond quantitatively. For all models, the kinetic parameters associated with the extravasation of tracer were found to be distinctly higher in meningiomas than in normal white- and gray-matter tissues.