Improved partial volume correction method for detecting brain activation in disease using Arterial Spin Labeling (ASL) fMRI.

Abstract

The insight provided by fMRI, particularly BOLD fMRI, has been critical to the understanding of human brain function. Unfortunately, the application of fMRI techniques in clinical research has been held back by several factors. In order for the clinical field to successfully apply fMRI, two main challenges posed by aging and diseased brains need to be overcome: (1) difficulties in signal measurement and interpretation, and (2) partial voluming effects (PVE). Recent work has addressed the first challenge by developing fMRI methods that, in contrast to BOLD, provide a direct measurement of a physiological correlate of function. One such method is Arterial Spin Labeling (ASL) fMRI, which provides images of cerebral blood flow (CBF) in physiologically meaningful units. Although the problems caused by PVE can be mitigated to some degree through the acquisition of high spatial resolution fMRI data, both hardware and experimental design considerations limit this solution. Our team has developed a PVE correction (PVEc) algorithm that produces CBF images that are theoretically independent of tissue content and the associated PVE. The main drawback of the current PVEc method is that it introduces an inherent smoothing of the functional data. This smoothing effect can reduce the sensitivity of the method, complicating the detection of local changes in CBF, such as those due to stroke or activation. Here, we present results from an improved PVEc algorithm (ssPVEc), which uses high-resolution structural space information to correct for the tissue-driven heterogeneity in the ASL signal. We tested the ssPVEc method on ASL images obtained on patients with asymptomatic carotid occlusive disease during rest and motor activation. Our results showed that the sensitivity of the ssPVEc method (defined as the average T-value in the activated region) was at least 1.5 times greater than that of the original, functional space, fsPVEc, for all patients.