A 128-channel receive array for cortical brain imaging at 7 T

Abstract

Purpose: A 128-channel receive-only array for brain imaging at 7 T was simulated, designed, constructed, and tested within a high-performance head gradient designed for high-resolution functional imaging.

Methods: The coil used a tight-fitting helmet geometry populated with 128 loop elements and preamplifiers to fit into a 39 cm diameter space inside a built-in gradient. The signal-to-noise ratio (SNR) and parallel imaging performance (1/g) were measured in vivo and simulated using electromagnetic modeling. The histogram of 1/g factors was analyzed to assess the range of performance. The array's performance was compared to the industry-standard 32-channel receive array and a 64-channel research array.

Results: It was possible to construct the 128-channel array with body noise-dominated loops producing an average noise correlation of 5.4%. Measurements showed increased sensitivity compared with the 32-channel and 64-channel array through a combination of higher intrinsic SNR and g-factor improvements. For unaccelerated imaging, the 128-channel array showed SNR gains of 17.6% and 9.3% compared to the 32-channel and 64-channel array, respectively, at the center of the brain and 42% and 18% higher SNR in the peripheral brain regions including the cortex. For R = 5 accelerated imaging, these gains were 44.2% and 24.3% at the brain center and 86.7% and 48.7% in the cortex. The 1/g-factor histograms show both an improved mean and a tighter distribution by increasing the channel count, with both effects becoming more pronounced at higher accelerations.

Conclusion: The experimental results confirm that increasing the channel count to 128 channels is beneficial for 7T brain imaging, both for increasing SNR in peripheral brain regions and for accelerated imaging.

Keywords: cortical imaging; high-field MR phased array coils; neuroimaging; parallel imaging; receive coils; signal to noise ratio.

FIGURE 1 –

The 44 cm diameter head gradient coil (39 cm dia. inside the covers) imposed tight space constraints requiring all Tx and Rx coils to fit on the 37 cm dia. patient table extension. The left column illustrates the development process of the 128-channel coil array system, starting with the basic single loop circuit and several computer-aided design (CAD) renderings of the design with the 1-channel transmit birdcage. The Rx array helmet is designed to fit 75% of the male population and almost 100% of the female population. All preamplifiers are mounted near their Rx loop. The bottom row shows a 3D rendering of the Tx birdcage (its slotted shield not shown), the helmet with Rx coils, patient table, coil plugs, and interface box (brown) on the patient table extension (blue). The right column illustrates the different construction stages of the 3D printed Rx helmet with the 128 wire loops unpopulated (no components) and populated with all wire connections and preamplifiers.

FIGURE 2 –

Measured unloaded to loaded Q-ratio values for single loop coil elements with varying loop diameters at 3T (123.2 MHz) and 7T (297.2 MHz) and dummy wire surrounding elements to simulate losses due to copper. A 2nd order polynomial trendline is fitted to the measurement points. At 7T a head-only array with 128-channels (loop diameter about 40 mm) will still be in body-noise dominance, while the 3T coil is not body-noise dominant.

FIGURE 3 –

Measured noise correlation coefficient matrices for all three arrays obtained from MR data acquired without RF excitation with a human head load. The average noise correlation for the 32-, 64-, and 128-channel arrays were measured to be 6.7, 9.5, and 5.4% respectively.

FIGURE 4 –

Simulated and measured SNR maps using optimal coil-combination (utilizing noise covariance matrix) for the 32-, 64-, and 128-channel array. The top row shows the non-accelerated 1D SNR profiles through the brain-center for a central axial slice for all three arrays. The green bars mark the cortical area of interest. The simulations used a homogeneous numerical head model with 7T electrical properties. Copper losses were estimated from the unloaded Q and added to the simulated body losses determined from the simulation’s E field and conductivity. The measured SNR maps used magnitude images and noise covariance matrices and were normalized by sin(α) where α is the measured local flip angle.

FIGURE 5 –

Simulated and measured retained SNR maps for accelerated imaging (R=5 and R=3x3) for the 32-, 64-, and 128-channel array in a central axial slice of the same subject. Due to the use of a homogeneous numerical phantom for the MARIE simulations and the difficulty of measuring continuous SNR in the skull and scalp, the comparison of SNR values has to start at about 1 to 1.5 cm depth from the surface of the homogeneous head phantom.

FIGURE 6 –

Accelerated SNR as a function of in-plane acceleration factor for a cortical and central ROI for the 64-, and 128-channel array coil relative to the 32-channel array. For each data point, the SNR was normalized so that the 32-channel array yielded SNR = 1 for the unaccelerated central ROI. Note, coil helmets have similar, but no identical, sizes. The SNR was based on 1D accelerated g-factors derived from measured reference GRE images and noise matrix data.

FIGURE 7 –

Simulated and measured inverse g-factor maps (fractional retained SNR) from transverse simulated and measured in-vivo data for the indicated in-plane 1D and 2D acceleration factors for the 32-, 64-, and 128-channel arrays. Low values (blue) are areas with poor parallel imaging performance; high g-factor (low retained SNR). The mean 1/g value is shown for each case.

FIGURE 8 –

Measured 1/g-factor (retained SNR) maps in all three cardinal planes for various in-plane acceleration factors (R_y) together with various SMS factors (R_z). Maps are formed using ESPIRIT coil receive sensitivity estimates and noise covariance data derived from a GRE reference PD-weighted anatomic image acquired using the 32-, 64-, and 128-channel arrays. Mean and max g-values are shown for a brain-masked region-of-interest (ROI) after the application of a smoothing filter. For accelerations below 3x1 all arrays yielded near unity g-factors.

FIGURE 9 –

Density distribution of measured 1/g-factors (retained SNR) over the whole brain volume for the indicated in-plane acceleration factors (R_y) and SMS factors (R_z). Each side of each violin plot represents the 1/g-factor distribution for a given coil array. The 32-, 64-, and 128-channel arrays are color-coded red, light blue, and green, respectively. A more narrow distribution (towards 1 on the y-axis) indicates better parallel imaging performance. The 1/g benefit describes the advantage in % of the array with a higher channel count over the array with a lower number of channels in that plot. The x is the mean value, whereas the short black line is the median value. A detailed explanation on the violin plots can be found in supplementary Figure S5.

FIGURE 10 –

Anatomical T2* -weighted images with 300 μm in-plane resolution and 1 mm slice thickness, acquired using the 128-channel array. The images were acquired using a standard 2D gradient-recalled echo sequence (See sequence parameter in Methods section).