A variable resolution approach for improved acquisition of hyperpolarized 13 C metabolic MRI

Abstract

Purpose: To ameliorate tradeoffs between a fixed spatial resolution and signal-to-noise ratio (SNR) for hyperpolarized ¹³ C MRI.

Methods: In MRI, SNR is proportional to voxel volume but retrospective downsampling or voxel averaging only improves SNR by the square root of voxel size. This can be exploited with a metabolite-selective imaging approach that independently encodes each compound, yielding high-resolution images for the injected substrate and coarser resolution images for downstream metabolites, while maintaining adequate SNR for each. To assess the efficacy of this approach, hyperpolarized [1-¹³ C]pyruvate data were acquired in healthy Sprague-Dawley rats (n = 4) and in two healthy human subjects.

Results: Compared with a constant resolution acquisition, variable-resolution data sets showed improved detectability of metabolites in pre-clinical renal studies with a 3.5-fold, 8.7-fold, and 6.0-fold increase in SNR for lactate, alanine, and bicarbonate data, respectively. Variable-resolution data sets from healthy human subjects showed cardiac structure and neuro-vasculature in the higher resolution pyruvate images (6.0 × 6.0 mm² for cardiac and 7.5 × 7.5 mm² for brain) that would otherwise be missed due to partial-volume effects and illustrates the level of detail that can be achieved with hyperpolarized substrates in a clinical setting.

Conclusion: We developed a variable-resolution strategy for hyperpolarized ¹³ C MRI using metabolite-selective imaging and demonstrated that it mitigates tradeoffs between a fixed spatial resolution and SNR for hyperpolarized substrates, providing both high resolution pyruvate and coarse resolution metabolite data sets in a single exam. This technique shows promise to improve future studies by maximizing metabolite SNR while minimizing partial-volume effects from the injected substrate.

Keywords: EPI; MRI; carbon-13; hyperpolarization; pyruvate.

FIGURE 1

Pulse sequence diagram for variable resolution imaging using an echoplanar readout. In this approach, a single-band SPSP RF pulse is used to independently excite each metabolite. The readout waveform, shown here as an echoplanar trajectory in the encoding module, can then be scaled to yield a voxel size based on the SNR for each metabolite

FIGURE 2

Kinetics of hyperpolarized pyruvate renal metabolism from a single 20 mm slice in a healthy rat. The constant resolution data (A) were acquired at 2.5 × 2.5 mm² in-plane resolution for all metabolites, whereas for the variable resolution study (B) pyruvate was acquired at 2.5 × 2.5 mm², lactate was acquired at 5.0 × 5.0 mm², and bicarbonate and alanine at 7.5 × 7.5 mm². AUC maps (in SNR units) shown below the timecourse highlight the improvement provided by the variable resolution approach, especially for metabolites with low concentration such as bicarbonate. The red arrows indicate the location of the urea phantom, which was used for RF frequency and power calibration

FIGURE 3

The 4D dynamics of hyperpolarized [1-¹³C]pyruvate in the healthy human brain. Eight 1.5-cm slices were acquired with a temporal resolution of 3 s. Data were acquired with an in-plane resolution of 0.75 × 0.75 cm² and are displayed in SNR units. Twenty total timeframes were acquired and the first 10 are shown here

FIGURE 4

AUC images from a healthy brain volunteer. The higher resolution pyruvate data set enabled improved visualization of neuro-vasculature while the lactate and bicarbonate images acquired at a coarser resolution retain sufficient SNR to visualize metabolism throughout the brain. Each metabolite map was zero-filled two-fold for display

FIGURE 5

The 4D dynamics of hyperpolarized [1-¹³C]pyruvate in the healthy human heart. Five 2.1-cm slices were acquired with cardiac gating. Each metabolite volume was acquired within one heartbeat, yielding an effective temporal resolution of ~3.5 s. Data were acquired with an in-plane resolution of 0.6 × 0.6 cm² and are displayed in SNR units. Thirty total timeframes were acquired and the first 15 are shown here

FIGURE 6

AUC images from a healthy cardiac volunteer. The pyruvate data, acquired at finer resolution, provides improved contrast between the left and right ventricles and the myocardium and papillary muscles. The comparatively coarse resolution of lactate and bicarbonate data was better matched to the lower SNR of these metabolites and reveals relevant localization of bicarbonate primarily in the myocardium and lactate in both the myocardium and blood pool. Each metabolite map was zero-filled two-fold for display