Imaging considerations for in vivo 13C metabolic mapping using hyperpolarized 13C-pyruvate

Abstract

One of the challenges of optimizing signal-to-noise ratio (SNR) and image quality in (13)C metabolic imaging using hyperpolarized (13)C-pyruvate is associated with the different MR signal time-courses for pyruvate and its metabolic products, lactate and alanine. The impact of the acquisition time window, variation of flip angles, and order of phase encoding on SNR and image quality were evaluated in mathematical simulations and rat experiments, based on multishot fast chemical shift imaging (CSI) and three-dimensional echo-planar spectroscopic imaging (3DEPSI) sequences. The image timing was set to coincide with the peak production of lactate. The strategy of combining variable flip angles and centric phase encoding (cPE) improved image quality while retaining good SNR. In addition, two aspects of EPSI sampling strategies were explored: waveform design (flyback vs. symmetric EPSI) and spectral bandwidth (BW = 500 Hz vs. 267 Hz). Both symmetric EPSI and reduced BW trended toward increased SNR. The imaging strategies reported here can serve as guidance to other multishot spectroscopic imaging protocols for (13)C metabolic imaging applications.

FIG. 1

Signal-time courses derived from dynamic ¹³C MR spectra acquired on a rat following an injection of hyperpolarized ¹³C-1-pyruvate (4). The acquisition parameters were 5 kHz, 2048 points, 5° flip angle, and 3-s temporal resolution. The insert plot shows the changes of spectra over time for lactate, pyruvate-hydrate, alanine, pyruvate, and bicarbonate peaks (from left to right). The three boxes illustrate the time window of a typical 17-s fast CSI acquisition at three different time delays: 15 s, 25 s, and 35 s.

FIG. 2

Schematic diagram to illustrate the k-space simulation of fast CSI acquisition using Bessel functions of the first order, smoothed by a Gaussian filter, and then sampled by a 16 × 16 matrix, with 20% reduction in k-space corner coverage. The corresponding images at each step of the k-space simulation are shown here under “Object domain.” The intensity of pyruvate circles is scaled down by a factor of three in all simulation images presented in this work so that lactate and alanine circles can be easily seen in the images.

FIG. 3

Gradient waveforms evaluated in this work: flyback EPSI at 500 Hz (top), symmetric EPSI at 500 Hz (middle), and flyback EPSI at 267 Hz (bottom). The flyback EPSI waveform consists of cycles of encoding and rewind gradients (as labeled). The symmetric EPSI waveform consists of odd and even echoes (as numbered). The dashed lines indicate the period at which data were collected for reconstruction.

FIG. 4

Simulated data for a constant 10° flip angle and VFAs in sequential vs. centric phase encoding orders based on the fast CSI acquisition of a 16 × 16 matrix. The signal intensity in k-space (ky vs. kz; top row) was extracted from the pyruvate dynamic curve (Fig. 1; red) at a 25-s time delay. The corresponding PSFs (center row) and their profiles (bottom row) plotted horizontally across the center of the matrix are shown to predict the severity of image blurring. The PSF profiles of the constant flip angle schemes are both broader than those of the VFA schemes, indicating that image blurring is expected to be more severe with a constant flip angle. The profile of the VFA/sPE strategy is very similar to but perhaps slightly sharper than the profile of the VFA/cPE strategy.

FIG. 5

a: SNR enhancement factor of VFA/cPE compared to sPE with a constant flip angle ranging from 3° to 10°. b: PSF of 10°/sPE (dashed line), 6°/sPE (dotted line), and VFA/cPE (solid line).

FIG. 6

Reconstructed simulated images using constant 10° flip angles at three time delays (15 s, 25 s, and 35 s) are shown here with the estimated SNR for pyruvate (P), alanine (A), and lactate (L). Note that the quoted pyruvate SNR has been scaled down by a factor of 3. The highest lactate SNR is expected with 25-s delay and cPE, but the image is blurry in both dimensions. Images of sPE are sharper but the SNRs are low for all metabolites.

FIG. 7

Using VFA, the best lactate SNR is expected at a 25-s delay. Because the plateaus of lactate and alanine are fairly broad (~12 s), when sampling on the plateaus, similar SNRs are obtained no matter which PE order is applied. The pyruvate SNR, however, is the best with cPE. Although the image of VFA/sPE may be slightly better than the image of VFA/cPE, considering the SNR of all metabolites, the best strategy is the combination of VFA and cPE.

FIG. 8

Axial in vivo ¹³C lactate images (color) acquired by using 3DEPSI on the same rat to compare the image quality and SNR of (a) flyback EPSI, 500 Hz, VFA, cPE; (b) flyback EPSI, 500 Hz, 10° flip angles, sPE; (c) flyback EPSI, 267 Hz, VFA, cPE; and (d) symmetric EPSI, 500 Hz, VFA, cPE. The order of imaging acquisition was (a)-(d)-(c)-(b) and the same order applied for all four rats. For each data set, the spectrum obtained from a 5 mm × 5 mm area on the left kidney (white box) is shown at the bottom. The reference is a syringe filled with 1.77 M 1-¹³C-lactate solution placed on the top of rat. The scan time was 13 s for each acquisition. The acquired spatial resolution was 5-mm isotropic and zero-fills were applied to generate the color metabolite maps. See Materials and Methods section for the acquisition parameters and reconstruction method. The brightest lactate signal appears in the left kidney. Strong lactate signal is also found posterior (on the top) of the left kidney on a structure that is possibly the spleen or pancreas.