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On the feasibility of synthetic sodium MRI based on tissue conductivity

Nazim Lechea¹, Yu Peng Liao², and N. Jon Shah^1,2

¹INM4, JARA-Faculty of Medicine, RWTH Aachen University, Aachen, Germany, Juelich, Germany, ²Institute of Neuroscience and Medicine-4, Forschungszentrum Juelich, Juelich, Germany

Synopsis

The recently proposed magnetic resonance electrical property tomography opens new opportunities for sodium ion characterisation. In this study, a model was built by measuring electrical conductivity and sodium MRI in different saline solutions. We exploit this interdependence with additional temperature correction to build a synthetic sodium brain map based on in vivo electrical conductivity. The results were compared to sodium MRI measurements. A statistically significant Pearson correlation (p<0.001; r=0.43) was observed between the two modalities while Bland-Altman analysis revealed discrepancies between them with a mean difference ~4mMol/L in whole brain. The proposed approach facilitates tissue sodium extraction.

Introduction

Sodium MRI is subject of growing interest as it reflects the inherent property of the tissue function and anatomy, providing crucial biochemical and physiological information. Tissue sodium concentration (TSC) can be used as a direct non-invasive biomarker for pathology investigation due to its vital role in maintaining osmoregulation, nerve impulse transmission, pH regulation and energy production. However, due to its low natural abundance, low gyromagnetic ratio and fast relaxation times compared to hydrogen proton, sodium detection requires high field in addition to advanced MRI sequences with ultra short echo times (1). Recently proposed models have described the interdependence of tissue conductivity and sodium concentration (2). At high frequency (>100MHz), conductivity is directly related to sodium ion concentration, showing the same behaviour in human tissue as observed in saline solutions (3). In this preliminary work, we propose to exploit this biophysical model to build a synthetic TSC brain map.

Material and Methods

For the evaluation of conductivity and sodium mapping accuracy, a multi-compartment cylinder containing 9 tubes filled with different sodium (NaCl) concentration was used. Following MRI data acquisition and post-processing, the mean value and standard deviation of sodium concentration and electrical conductivity (σ) were calculated from the region-of-interests (ROIs) placed within each tube. In addition, the reference conductivity value of the same conductivity component was acquired using an impedance probe (DAK-12, SPEAG, Switzerland). Eight healthy volunteers including three females (25-32 years old), were scanned at two different field strength, i.e., at 3T scanner (Siemens Healthcare, Erlangen) using a 12-channel phased array head coil and a home–assembled 4T scanner (Siemens Syngo, Erlangen) using a double-tuned ¹H/²³Na transmit-receive RF birdcage coil (RAPID Biomedical, Wurzburg). 3D true-FISP scans were acquired at 3T for phase based conductivity reconstruction with the following parameters: TR=4.8ms; TE=2.4ms; matrix=320×320×104; 1.2mm isotropic resolution; FA=45°; 3 averages; TA=11:22min. In the present study, we adopted the transmit and receive (transceive) phase to extract electrical conductivity, σ, using the following equation: σ=Δφ/2ωµ₀, where φ denotes transceive phase, ω Larmor frequency, μ₀ vacuum magnetic permeability, and Δ Laplacian operator (4,5). To reduce artefacts arising from boundary voxels, a 3D local polynomial fitting method was implemented (6). 3D sodium images were acquired using the twisted projection imaging (TPI) sequence (7). Imaging parameters were: TR=160ms; TE=0.4m; matrix=64³; 3.44mm, isotropic nominal resolution; 5120 scanning projections; 2 averages; TA=25min. Additional RF transmit maps (B₁^Tx) were acquired at the sodium frequency to correct B₁^Tx inhomogeneity (8). To facilitate the co-registration to individual brain anatomy, a 1mm isotropic MPRAGE image was acquired. For each subject, TSC and conductivity maps were co-registered and spatially normalized to MNI space using SPM (9). Different ROIs derived from MNI template, were defined within a set of areas including frontal, occipital, parietal and temporal grey matter (GM) and white matter (WM). The brain synthetic TSC (sTSC) was extracted based on saline solution phantom model after temperature correction: sTSC=A∙σ+B, where A and B are constants. To investigate the association between sTSC and sodium MRI, Pearson correlation and Bland–Altman analysis was used.

Results

Conductivity mapping was found to be in good agreement with probe measurement (Figure-1a). Including all tubes, linear regression yields sTSC=72.91×σ−3.40 after body temperature correction (37°C). The conductivity extracted sodium map was largely comparable to sodium MRI measurement (Figure-2). Significantly high resolution and SNR are obtained using synthetic sodium reconstruction (Figure-2, top panel). Across subjects, the sTSC map statistically correlated with sodium MRI. Figure-3a) and -3b) show the brain map in a representative subject using sTSC and direct sodium MRI measurement, respectively. In addition, detailed in vivo sodium concentrations of different brain ROIs were also explored in eight different subjects (r=0.43, p<0.001, Figure-4). Bland-Altman analysis revealed discrepancies with a mean difference between both methods ~4mMol/L with most differences located within the 95% confidence interval (Figure-5).

Discussion and Conclusion

In the present study, we demonstrated the feasibility of extracting a TSC map based on tissue conductivity at 3T using a body temperature saline solution model. Temperature correction is required because a constant bias dramatically influences the model. In contrast with phantom results, in vivo correlations revealed a discrepancy between direct and synthetic MRI mapping, which can be attributed to low resolution of sodium MRI and/or use of saline solutions rather than gels. Additionally, sodium MRI reflects the total combination of intracellular and extracellular sodium in the tissue, while according to previous report (10), due to the membranes capacitance isolation effects, electrical conductivity is highly extracellular sodium weighted which may cause systematic errors. The suitability of the proposed approach for clinical routines facilitating high-quality sodium mapping remains to be explored.

Acknowledgements

This work was supported by the Helmholtz Alliance ICEMED - Imaging and Curing Environmental Metabolic Diseases.

References

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Figures

Figure-1: a) Phantom conductivity values obtained using an impedance probe and MRI measurements. b) Linear regression showing sodium and conductivity interdependence.

Figure-2: Bar histograms showing mean values and standard deviations of conductivity measurements in saline phantom compared to true value. Direct measurements of sodium MRI values are extracted after B₁^Tx correction, calibration to reference values tubes and application of an eroded mask. Equivalent eroded mask was applied to synthetic sodium map before values extraction. Sodium MRI and synthetic sodium map are shown on the top panel.

Figure-3: In vivo TSC in a representative subject using a) conductivity based TSC (sTSC) and b) direct sodium MRI measurement. The displayed regions are WM and GM. To minimise partial volume effects resulting from the low resolution of sodium images, the boundaries of the cerebrospinal fluid were dilated before its exclusion.

Figure-4: Linear regression showing different ROIs located in the GM and WM in eight subjects. Different ROIs derived from MNI template were defined within a set of areas including the frontal, occipital, parietal and temporal GM and WM, hippocampus, thalamus, putamen, medulla, globus pallidus, pons, insula, caudate, arbor vitae.

Figure-5: Bland-Altman analysis of different ROIs in eight subjects using the sTSC and direct sodium MRI measurements. The solid line visualizes the mean difference between the two methods (~4mMol/L).

Proc. Intl. Soc. Mag. Reson. Med. 25 (2017)

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