Measurements of brain tissue pulsatility can provide information about viscoelastic tissue properties and assess microvasculature blood volume pulsations as a biomarker. VCG-triggered DENSE is capable of acquiring micrometer-level tissue displacements and volumetric strain. However, it is slow and suffers from triggering issues, especially at 7T. In this work, retrospectively-gated DENSE using a pulse oximeter was implemented at 7T. Assessment of its performance showed maintained SNR within half the scan time of triggered DENSE. The high SNR and reduced scan time simplifies its application in future studies assessing the potential of DENSE-derived brain tissue displacements as a biomarker for neurological diseases.
Measurement
Informed consent was obtained from 8 healthy subjects (5 males, mean age:26.8±6) to participate in this study, which was approved by the Ethical Review Board of our institution. A 4D retrospectively-gated DENSE sequence was implemented on a 7T scanner (Philips Healthcare) which was used in conjunction with a 32-channel head coil (Nova Medical) and a POx to measure the cardiac-induced whole brain tissue displacement in the right-left (RL) direction for the entire cardiac cycle. A 3D T1-weighted FFE image was also made of each subject (see Table 1 for all scan parameters). In order to assess the SNR performance of the retrospective DENSE a noise measurement was made by repeating the acquisition without gradients or RFs present.
Analysis
Displacement maps were derived from the raw phase images as previously described4. 3D SNR maps were created for each acquired cardiac phase by dividing the mean magnitude image (derived from 2 dynamics) by the modulus of the standard deviation of the complex noise5, as defined in the equation
$$SNR[p,q,r] = \frac{\textit{mean}\left \{ Mag[i,j,k] \right \}}{\sqrt{\mathit{variance} \left \{ \Re (Noise[i,j,k]) \right \} + \mathit{variance} \left \{ \Im (Noise[i,j,k]) \right \} } } $$
where $$$(i,j,k) \in w$$$, a 15x15x15 window centered around the SNR map at location $$$[p,q,r]$$$.
To create a whole brain tissue mask, the T1-weighted image was first segmented using the Computational Anatomy Toolbox (Jena University Hospital) for SPM12. The tissue mask was then applied to the DENSE and SNR images which were both registered with a rigid transformation to the T1-weighted image space using Elastix6,7. The mean SNR for all voxels contained in the tissue mask was calculated for each cardiac phase. The SNR coefficient of variation (CoV) was also calculated to assess the stability of the acquired signal over the cardiac cycle.
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Table 1. Imaging parameters used in the study.