Functional tissue pulsatility imaging of the brain during visual stimulation

Abstract

Functional tissue pulsatility imaging is a new ultrasonic technique being developed to map brain function by measuring changes in tissue pulsatility as a result of changes in blood flow with neuronal activation. The technique is based in principle on plethysmography, an older, nonultrasound technology for measuring expansion of a whole limb or body part as a result of perfusion. Perfused tissue expands by a fraction of a percent early in each cardiac cycle when arterial inflow exceeds venous outflow, and it relaxes later in the cardiac cycle when venous drainage dominates. Tissue pulsatility imaging (TPI) uses tissue Doppler signal processing methods to measure this pulsatile "plethysmographic" signal from hundreds or thousands of sample volumes in an ultrasound image plane. A feasibility study was conducted to determine if TPI could be used to detect regional brain activation during a visual contrast-reversing checkerboard block paradigm study. During a study, ultrasound data were collected transcranially from the occipital lobe as a subject viewed alternating blocks of a reversing checkerboard (stimulus condition) and a static, gray screen (control condition). Multivariate analysis of variance was used to identify sample volumes with significantly different pulsatility waveforms during the control and stimulus blocks. In 7 of 14 studies, consistent regions of activation were detected from tissue around the major vessels perfusing the visual cortex.

Fig. 1

(a,b) MRI images showing the position and orientation of the US transducer. (c) BMode image from the male subject. The black sector shown in (b) represents the approximate location and extent of the BMode image.

Fig. 2

Data collection hardware schematic.

Fig. 3

Data collection timing diagram. Ten seconds into each block the visual stimulation presentation computer instructed the arbitrary waveform generator to output a 100 ms TTL pulse that triggered acquisition of the US and ECG data.

Fig. 4

Data analysis flow diagram.

Fig. 5

Displacement waveforms and taper. (a) 8 s displacement waveform during a control block for a sample volume near the brain stem after filtering for respiratory motion. The vertical dotted lines indicate the beginnings of the cardiac cycles based on the ECG R-waves. (b) Modified 31 sample Hann window. (c) One cardiac cycle (solid line) from (a) and the waveform after tapering (dotted line).

Fig. 6

Displacement waveforms from one sample volume. (a) Displacement waveforms for four successive blocks. The waveforms have been resampled, tapered to 1 s and placed end-to-end. The entire data set consisted of 31 blocks and 157 cardiac cycles. (b) Mean waveforms from all of the cardiac cycles for the control blocks and the checkerboard blocks for the sample volume. For this sample volume, the p-value testing the hypothesis that the control blocks and checkerboard blocks have the same means was 1.0e-10.

Fig. 7

fTPI results for the 4 successful sessions for the male subject. The left column shows BMode images from one frame collected during each session. The brightest echo in each image at a depth of 80 mm is from the region around the pineal body. The right column shows the p-values for the fTPI data superimposed on the respective BMode images. P-values less that 0.01 are not considered significant and are not shown. The magenta boundary indicates the region-of-interest for the fTPI analysis.

Fig. 8

MRI slice corresponding approximately to the US image plane with superimposed p-values from the male subject, session 5. The fTPI p-values have been drawn as a contour plot with curves every order of magnitude from 10⁻⁹ to 10⁻³.