Abstract

What is CT Perfusion?
CT Perfusion (CTP) is a functional study that utilizes continuous CT scan acquisition, over the same slab of tissue during the dynamic administration of a small contrast bolus, in order to evaluate capillary-level hemodynamics (1). Perfusion data can be described using a variety of parameters (Fig. 1); including cerebral blood flow (CBF), cerebral blood volume (CBV) and mean transit time (MTT).

Why perform CT Perfusion?
CT Perfusion expands the traditional anatomic role of CT in the evaluation of the brain parenchyma and major intracranial vessels, to provide additional physiologic information about capillary-level hemodynamics. Such functional characterization may be of value in the work-up of disease processes such as stroke, carotid occlusive disease, vasospasm, and brain tumors (Table 1).

How does CT Perfusion work?
CT perfusion is based on the kinetics of a non-diffusible contrast tracer as it passes through the brain parenchyma (Fig. 2). The first pass of the contrast bolus is monitored using rapid, cine acquisition of images through a stationary slab of tissue, yielding time-density curves (TDC) for each voxel of tissue, as well as for a user-selected feeding artery and draining vein (Fig. 3). Within each voxel of tissue, the passage of contrast yields a curve that begins at a baseline, increases to a peak value as the contrast passes through the parenchyma, and subsequently returns to a baseline, as the bolus of contrast exits through venous drainage pathways. CT perfusion attempts to evaluate this dynamic process - occurring at the capillary level - by obtaining data regarding contrast kinetics on a voxel-by-voxel basis. This data, when entered into a simplified mathematical model describing the relationship between the arterial input, capillary flow, and venous drainage, is used to calculate the summary perfusion parameters of CBF, CBV, and MTT for each voxel in the image. The specific mathematical model used to calculate these parameters varies from vendor to vendor, employing differing assumptions regarding the inflow and outflow of contrast through the tissue bed. As discussed below, the details of the particular model used has important implications for both the interpretation and processing of perfusion data. The greater the discrepancy between the assumptions of the model and the “true” pattern of contrast flow, the less accurate the final CTP results will be.

Pitfalls: Calculation of CT Perfusion Parameters

Measurement of CBF, CBV and MTT is indirect, based on calculations from the time-density-curves for each voxel
Accuracy is limited by the assumptions of the specific mathematical model used for the software calculations

I. Introduction