Dual Component Analysis for In Vivo T₂* Decay of Hyperpolarized ¹³C Metabolites

PURPOSE: To investigate the exchange and redistribution of hyperpolarized ¹³C metabolites between different pools by temporally analyzing the relative fraction of dual T₂* components of hyperpolarized ¹³C metabolites. MATERIALS AND METHODS: A dual exponential decay analysis of T₂* is performed for [1-¹³C] pyruvate and [1-¹³C] lactate using nonspatially resolved dynamic ¹³C MR spectroscopy from mice brains with tumors (n = 3) and without (n = 4) tumors. The values of shorter and longer T₂* components are explored when fitted from averaged spectrum and temporal variations of their fractions. RESULTS: The T₂* values were not significantly different between the tumor and control groups, but the fraction of longer T₂* [1-¹³C] lactate components was more than 10% in the tumor group over that of the controls (P < 0.1). The fraction of shorter T₂* components of [1-¹³C] pyruvate showed an increasing tendency while that of the [1-¹³C] lactate was decreasing over time. The slopes of the changing fraction were steeper for the tumor group than the controls, especially for lactate (P < 0.01). In both pyruvate and lactate, the fraction of the shorter T₂* component was always greater than the longer T₂* component over time. CONCLUSIONS: The exchange and redistribution of pyruvate and lactate between different pools was investigated by dual component analysis of the free induction decay signal from hyperpolarized ¹³C experiments. Tumor and control groups showed differences in their fractions rather than the values of longer and shorter T₂* components. Fraction changing dynamics may provide an aspect for extravasation and membrane transport of pyruvate and lactate, and will be useful to determine the appropriate time window for acquisition of hyperpolarized ¹³C images.

Non-Invasive in vivo Loss Tangent Imaging: Thermal Sensitivity Estimation at the Larmor Frequency

Visualization of the tissue loss tangent property can provide distinct contrast and offer new information related to tissue electrical properties. A method for non-invasive imaging of the electrical loss tangent of tissue using magnetic resonance imaging (MRI) was demonstrated, and the effect of loss tangent was observed through simulations assuming a hyperthermia procedure. For measurement of tissue loss tangent, radiofrequency field maps (B1+ complex map) were acquired using a double-angle actual flip angle imaging MRI sequence. The conductivity and permittivity were estimated from the complex valued B1+ map using Helmholtz equations. Phantom and ex-vivo experiments were then performed. Electromagnetic simulations of hyperthermia were carried out for observation of temperature elevation with respect to loss tangent. Non-invasive imaging of tissue loss tangent via complex valued B1+ mapping using MRI was successfully conducted. Simulation results indicated that loss tangent is a dominant factor in temperature elevation in the high frequency range during hyperthermia. Knowledge of the tissue loss tangent value can be a useful marker for thermotherapy applications.

Alternating Acquisition Technique for Quantification of in vitro Hyperpolarized 1-13C Pyruvate Metabolism

PURPOSE: To develop a technique for quantifying the 13C-metabolites by performing frequency-selective hyperpolarized 13C magnetic resonance spectroscopy (MRS) in vitro which combines simple spectrally-selective excitation with spectrally interleaved acquisition. METHODS: Numerical simulations were performed with varying noise level and K(p) values to compare the quantification accuracies of the proposed and the conventional methods. For in vitro experiments, a spectrally-selective excitation scheme was enabled by narrow-band radiofrequency (RF) excitation pulse implemented into a free-induction decay chemical shift imaging (FIDCSI) sequence. Experiments with LDH / NADH enzyme mixture were performed to validate the effectiveness of the proposed acquisition method. Also, a modified two-site exchange model was formulated for metabolism kinetics quantification with the proposed method. RESULTS: From the simulation results, significant increase of the lactate peak signal to noise ratio (PSNR) was observed. Also, the quantified K(p) value from the dynamic curves were more accurate in the case of the proposed acquisition method compared to the conventional non-selective excitation scheme. In vitro experiment results were in good agreement with the simulation results, also displaying increased PSNR for lactate. Fitting results using the modified two-site exchange model also showed expected results in agreement with the simulations. CONCLUSION: A method for accurate quantification of hyperpolarized pyruvate and the downstream product focused on in vitro experiment was described. By using a narrow-band RF excitation pulse with alternating acquisition, different resonances were selectively excited with a different flip angle for increased PSNR while the hyperpolarized magnetization of the substrate can be minimally perturbed with a low flip angle. Baseline signals from neighboring resonances can be effectively suppressed to accurately quantify the metabolism kinetics.

Determination of Optimal Scan Time for the Measurement of Downstream Metabolites in Hyperpolarized 13C MRSI

PURPOSE: For a single time-point hyperpolarized 13C magnetic resonance spectroscopy imaging (MRSI) of animal models, scan-time window after injecting substrates is critical in terms of signal-to-noise ratio (SNR) of downstream metabolites. Prescans of time-resolved magnetic resonance spectroscopy (MRS) can be performed to determine the scan-time window. In this study, based on two-site exchange model, protocol-specific simulation approaches were developed for 13C MRSI and the optimal scan-time window was determined to maximize the SNR of downstream metabolites. MATERIALS AND METHODS: The arterial input function and conversion rate constant from injected substrates (pyruvate) to downstream metabolite (lactate) were precalibrated, based on pre-scans of time-resolved MRS. MRSI was simulated using twosite exchange model with considerations of scan parameters of MRSI. Optimal scantime window for mapping lactate was chosen from simulated lactate intensity maps. The performance was validated by multiple in vivo experiments of BALB/C nude mice with MDA-MB-231 breast tumor cells. As a comparison, MRSI were performed with other scan-time windows simply chosen from the lactate signal intensities of prescan time-resolved MRS. RESULTS: The optimal scan timing for our animal models was determined by simulation, and was found to be 15 s after injection of the pyruvate. Compared to the simple approach, we observed that the lactate peak signal to noise ratio (PSNR) was increased by 230%. CONCLUSIONS: Optimal scan timing to measure downstream metabolites using hyperpolarized 13C MRSI can be determined by the proposed protocol-specific simulation approaches.

Quantitative Conductivity Estimation Error due to Statistical Noise in Complex B1+ Map

PURPOSE: In-vivo conductivity reconstruction using transmit field (B1+) information of MRI was proposed. We assessed the accuracy of conductivity reconstruction in the presence of statistical noise in complex B1 + map and provided a parametric model of the conductivity-to-noise ratio value. MATERIALS AND METHODS: The B1+ distribution was simulated for a cylindrical phantom model. By adding complex Gaussian noise to the simulated B1+ map, quantitative conductivity estimation error was evaluated. The quantitative evaluation process was repeated over several different parameters such as Larmor frequency, object radius and SNR of B1+ map. A parametric model for the conductivity-to-noise ratio was developed according to these various parameters. RESULTS: According to the simulation results, conductivity estimation is more sensitive to statistical noise in B1+ phase than to noise in B1+ magnitude. The conductivity estimate of the object of interest does not depend on the external object surrounding it. The conductivity-to-noise ratio is proportional to the signal-to-noise ratio of the B1+ map, Larmor frequency, the conductivity value itself and the number of averaged pixels. To estimate accurate conductivity value of the targeted tissue, SNR of B1+ map and adequate filtering size have to be taken into account for conductivity reconstruction process. In addition, the simulation result was verified at 3T conventional MRI scanner. CONCLUSION: Through all these relationships, quantitative conductivity estimation error due to statistical noise in B1+ map is modeled. By using this model, further issues regarding filtering and reconstruction algorithms can be investigated for MREPT.