Abstract:Effective coil combination methods for human hyperpolarized 13 C spectroscopy multi-channel data had been relatively unexplored. This study implemented and tested several coil combination methods, including 1) the sum-of-squares (SOS), 2) singular value decomposition (SVD), 3) Roemer method by using reference peak area as a sensitivity map (RefPeak), and 4) Roemer method by using ESPIRiT-derived sensitivity map (ESPIRiT). These methods were evaluated by numerical simulation, thermal phantom experiments, and hu… Show more
“…This will still result in increased image quality, however, without intensity correction. 39,40 The phantom results share a trend with the simulations, in the sense that theoretic pre-calibrated reconstructions resulted in the highest image quality, and auto-calibrated A single oblique slice (close to the coronal plane) is shown, cropped to focus on the kidneys and interpolated to an isotropic voxel size of 2.5 mm. Pyruvate and lactate images are shown interleaved, as acquired, with the first image being of lactate for the fully sampled acquisitions (FS), and the first being of pyruvate for the undersampled acquisitions (US).…”
Section: Discussionsupporting
confidence: 59%
“…For phantoms with signal non‐uniformity and for in vivo imaging, auto‐calibrated coil sensitivities need to be based on the sum‐of‐squares normalized image to divide out object contrast. This will still result in increased image quality, however, without intensity correction …”
Purpose
To investigate auto‐ and pre‐calibration coil profile estimation for parallel imaging reconstruction of hyperpolarized 13C MRI volumetric data.
Methods
Parallel imaging reconstruction was studied with 3 different approaches for coil profile estimation: auto‐calibration, phantom calibration, and theoretic calibration. Acquisition was performed with a 3D stack‐of‐spirals sequence with spectral–spatial excitation and Cartesian undersampling. Parallel imaging reconstructions were done with conjugate gradient SENSE and 3D gridding with inhomogeneity correction. The approaches were compared in simulations with different SNR, through phantom experiments, and in an in vivo pig study focused on the kidneys. All imaging was done with a rigid home‐built 12‐channel 13C receive coil at 3T.
Results
The phantom calibrated and theoretic approaches resulted in the best structural similarities in simulations and demonstrated higher image quality in the phantom experiments compared to the auto‐calibrated approach. In vivo mapping of pyruvate uptake and lactate conversion improved for accelerated acquisitions because of a better temporal resolution. From a practical and image quality point of view, use of theoretic coil profiles led to improved results compared to the other approaches.
Conclusion
The success of the theoretic coil profile estimation demonstrates a negligible effect of load on sensitivity profiles at the carbon frequency at 3T. Through theoretic or phantom calibrated parallel imaging, accelerated 3D volumes could be reconstructed with sufficient sensitivity, temporal, and spatial resolution to map the metabolism of kidneys exemplifying abdominal organs. This approach overcomes a critical step in the clinical translation of parallel imaging in hyperpolarized 13C MR.
“…This will still result in increased image quality, however, without intensity correction. 39,40 The phantom results share a trend with the simulations, in the sense that theoretic pre-calibrated reconstructions resulted in the highest image quality, and auto-calibrated A single oblique slice (close to the coronal plane) is shown, cropped to focus on the kidneys and interpolated to an isotropic voxel size of 2.5 mm. Pyruvate and lactate images are shown interleaved, as acquired, with the first image being of lactate for the fully sampled acquisitions (FS), and the first being of pyruvate for the undersampled acquisitions (US).…”
Section: Discussionsupporting
confidence: 59%
“…For phantoms with signal non‐uniformity and for in vivo imaging, auto‐calibrated coil sensitivities need to be based on the sum‐of‐squares normalized image to divide out object contrast. This will still result in increased image quality, however, without intensity correction …”
Purpose
To investigate auto‐ and pre‐calibration coil profile estimation for parallel imaging reconstruction of hyperpolarized 13C MRI volumetric data.
Methods
Parallel imaging reconstruction was studied with 3 different approaches for coil profile estimation: auto‐calibration, phantom calibration, and theoretic calibration. Acquisition was performed with a 3D stack‐of‐spirals sequence with spectral–spatial excitation and Cartesian undersampling. Parallel imaging reconstructions were done with conjugate gradient SENSE and 3D gridding with inhomogeneity correction. The approaches were compared in simulations with different SNR, through phantom experiments, and in an in vivo pig study focused on the kidneys. All imaging was done with a rigid home‐built 12‐channel 13C receive coil at 3T.
Results
The phantom calibrated and theoretic approaches resulted in the best structural similarities in simulations and demonstrated higher image quality in the phantom experiments compared to the auto‐calibrated approach. In vivo mapping of pyruvate uptake and lactate conversion improved for accelerated acquisitions because of a better temporal resolution. From a practical and image quality point of view, use of theoretic coil profiles led to improved results compared to the other approaches.
Conclusion
The success of the theoretic coil profile estimation demonstrates a negligible effect of load on sensitivity profiles at the carbon frequency at 3T. Through theoretic or phantom calibrated parallel imaging, accelerated 3D volumes could be reconstructed with sufficient sensitivity, temporal, and spatial resolution to map the metabolism of kidneys exemplifying abdominal organs. This approach overcomes a critical step in the clinical translation of parallel imaging in hyperpolarized 13C MR.
“…In the setting of advanced prostate cancer, early (6 weeks) after effective androgen deprivation therapy, there was a significant early reduction in k PL that receded changes in mp- 1 H MRI and predicted clinical response ( Figure 3 ). 107 Comparison with current state-of-the-art imaging modalities such as 1 H MRI is key to determining the added value of HP 13 C MRI, and with current HP 13 C MRI studies expanding to metastatic sites within the body, [108] , [109] the synergy of HP MRI with currently used PET probes will also need to be investigated. Figure 3 Representative axial T 2 -weighted anatomic image and corresponding water apparent diffusion coefficient (ADC) image and T 2 W image with an overlaid pyruvate-to-lactate metabolic flux ( k PL ) image and corresponding HP 13 C spectral array for a 52-year-old prostate cancer patient with extensive high-grade prostate cancer (A) before therapy and (B) 6 weeks after initiation of androgen ablation and chemotherapy.…”
Section: Translation To Patients With Cancermentioning
This white paper discusses prospects for advancing hyperpolarization technology to better understand cancer metabolism, identify current obstacles to HP (hyperpolarized) 13C magnetic resonance imaging’s (MRI’s) widespread clinical use, and provide recommendations for overcoming them. Since the publication of the first NIH white paper on hyperpolarized 13C MRI in 2011, preclinical studies involving [1-13C]pyruvate as well a number of other 13C labeled metabolic substrates have demonstrated this technology's capacity to provide unique metabolic information. A dose-ranging study of HP [1-13C]pyruvate in patients with prostate cancer established safety and feasibility of this technique. Additional studies are ongoing in prostate, brain, breast, liver, cervical, and ovarian cancer. Technology for generating and delivering hyperpolarized agents has evolved, and new MR data acquisition sequences and improved MRI hardware have been developed. It will be important to continue investigation and development of existing and new probes in animal models. Improved polarization technology, efficient radiofrequency coils, and reliable pulse sequences are all important objectives to enable exploration of the technology in healthy control subjects and patient populations. It will be critical to determine how HP 13C MRI might fill existing needs in current clinical research and practice, and complement existing metabolic imaging modalities. Financial sponsorship and integration of academia, industry, and government efforts will be important factors in translating the technology for clinical research in oncology. This white paper is intended to provide recommendations with this goal in mind.
“…For both healthy volunteer data sets, multichannel data were pre-whitened 31 and then coil combined using pyruvate to estimate the coil weights. 32 For analysis, the peak dynamic SNR and area under the curve (AUC) ratio were determined for each metabolite. Peak dynamic SNR was calculated as the maximum voxel signal from each metabolite timecourse divided by the standard deviation of the noise, which was obtained from a timeframe and slice where no signal was present.…”
Purpose
To ameliorate tradeoffs between a fixed spatial resolution and signal‐to‐noise ratio (SNR) for hyperpolarized 13C 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 [1‐13C]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 13C 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.
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