In vivo electrical conductivity measurement of muscle, cartilage, and peripheral nerve around knee joint using MR-electrical properties tomography.

This study aimed to investigate whether in vivo MR-electrical properties tomography (MR-EPT) is feasible in musculoskeletal tissues by evaluating the conductivity of muscle, cartilage, and peripheral nerve around the knee joint, and to explore whether these measurements change after exercise. This prospective study was approved by the institutional review board. On February 2020, ten healthy volunteers provided written informed consent and underwent MRI of the right knee using a three-dimensional balanced steady-state free precession (bSSFP) sequence. To test the effect of loading, the subjects performed 60 squatting exercises after baseline MRI, immediately followed by post-exercise MRI with the same sequences. After reconstruction of conductivity map based on the bSSFP sequence, conductivity of muscles, cartilages, and nerves were measured. Measurements between the baseline and post-exercise MRI were compared using the paired t-test. Test-retest reliability for baseline conductivity was evaluated using the intraclass correlation coefficient. The baseline and post-exercise conductivity values (mean ± standard deviation) [S/m] of muscles, cartilages, and nerves were 1.73 ± 0.40 and 1.82 ± 0.50 (p = 0.048), 2.29 ± 0.47 and 2.51 ± 0.37 (p = 0.006), and 2.35 ± 0.57 and 2.36 ± 0.57 (p = 0.927), respectively. Intraclass correlation coefficient for the baseline conductivity of muscles, cartilages, and nerves were 0.89, 0.67, and 0.89, respectively. In conclusion, in vivo conductivity measurement of musculoskeletal tissues is feasible using MR-EPT. Conductivity of muscles and cartilages significantly changed with an overall increase after exercise.

Dictionary-based electric properties tomography.

PURPOSE: To develop and validate a new algorithm called "dictionary-based electric properties tomography" (dbEPT) for deriving tissue electric properties from measured B1 maps. METHODS: Inspired by Magnetic Resonance fingerprinting, dbEPT uses a dictionary of local patterns ("atoms") of B1 maps and corresponding electric properties distributions, derived from electromagnetic field simulations. For reconstruction, a pattern from a measured B1 map is compared with the B1 atoms of the dictionary. The B1 atom showing the best match with the measured B1 pattern yields the optimum electric properties pattern that is chosen for reconstruction. Matching was performed through machine learning algorithms. Two dictionaries, using transmit and transceive phases, were evaluated. The spatial distribution of local matching distance between optimal atom and measured pattern yielded a reconstruction reliability map. The method was applied to reconstruct conductivity of 4 volunteers' brains. A conventional, Helmholtz-based Electric properties tomography (EPT) reconstruction was performed for reference. Noise performance was studied through phantom simulations. RESULTS: Quantitative values of conductivity agree with literature values. Results of the 2 dictionaries exhibit only minor differences. Somewhat larger differences are visible between dbEPT and Helmholtz-based EPT. Quantified by the correlation between conductivity and anatomic images, dbEPT depicts brain details more clearly than Helmholtz-based EPT. Matching distance is minimal in homogeneous brain ventricles and increases with tissue heterogeneity. Central processing unit time was approximately 2 minutes per dictionary training and 3 minutes per brain conductivity reconstruction using standard hardware equipment. CONCLUSION: A new, dictionary-based approach for reconstructing electric properties is presented. Its conductivity reconstruction is able to overcome the EPT transceive-phase problem.

B1-based specific energy absorption rate determination for nonquadrature radiofrequency excitation.

The current gold standard to estimate local and global specific energy absorption rate for MRI involves numerically modeling the patient and the transmit radiofrequency coil. Recently, a patient-individual method was presented, which estimated specific energy absorption rate from individually measured B(1) maps. This method, however, was restricted to quadrature volume coils due to difficulties distinguishing phase contributions from radiofrequency transmission and reception. In this study, a method separating these two phase contributions by comparing the electric conductivity reconstructed from different transmit channels of a parallel radiofrequency transmission system is presented. This enables specific energy absorption rate estimation not only for quadrature excitation but also for the nonquadrature excitation of the single elements of the transmit array. Though the contributions of the different phases are known, unknown magnetic field components and tissue boundary artifacts limit the technique. Nevertheless, the high agreement between simulated and experimental results found in this study is promising. B(1)-based specific energy absorption rate determination might become possible for arbitrary radiofrequency excitation on a patient-individual basis.

Specific absorption rate reduction in parallel transmission by k-space adaptive radiofrequency pulse design.

The specific absorption rate (SAR) is an important safety criterion, limiting many MR protocols with respect to the achievable contrast and scan duration. Parallel transmission enables control of the radiofrequency field in space and time and hence allows for SAR management. However, a trade-off exists between radiofrequency pulse performance and SAR reduction. To overcome this problem, in this work, parallel transmit radiofrequency pulses are adapted to the position in sampling k-space. In the central k-space, highly homogeneous but SAR-intensive radiofrequency shim settings are used to achieve optimal performance and contrast. In the outer k-space, the homogeneity requirement is relaxed to reduce the average SAR of the scan. The approach was experimentally verified on phantoms and volunteers using field echo and spin echo sequences. A reduction of the SAR by 25-50% was achieved without compromising image quality.

Electrical conductivity imaging using magnetic resonance tomography.

The electrical conductivity of human tissue could be used as an additional diagnostic parameter or might be helpful for the prediction of the local SAR during MR measurements. In this study, the approach "Electric Properties Tomography" (EPT) is applied, which derives the patient's electric conductivity using a standard MR system. To this goal, the spatial transmit sensitivity distribution of the applied RF coil is measured. This sensitivity distribution represents the positive circularly polarized component of the magnetic field. It can be post-processed utilizing Faraday's and Ampere's law, yielding an estimation of the spatial distribution of the patient's electric conductivity. Thus, EPT does not apply externally mounted electrodes, currents, or RF probes. In this study, phantom experiments underline the principle feasibility of EPT. Furthermore, initial conductivity measurements in the brain allow distinguishing cerebro-spinal fluid from the surrounding grey and white matter.

Determination of electric conductivity and local SAR via B1 mapping.

The electric conductivity can potentially be used as an additional diagnostic parameter, e.g., in tumor diagnosis. Moreover, the electric conductivity, in connection with the electric field, can be used to estimate the local SAR distribution during MR measurements. In this study, a new approach, called electric properties tomography (EPT) is presented. It derives the patient's electric conductivity, along with the corresponding electric fields, from the spatial sensitivity distributions of the applied RF coils, which are measured via MRI. Corresponding numerical simulations and initial experiments on a standard clinical MRI system underline the principal feasibility of EPT to determine the electric conductivity and the local SAR. In contrast to previous methods to measure the patient's electric properties, EPT does not apply externally mounted electrodes, currents, or RF probes, thus enhancing the practicality of the approach. Furthermore, in contrast to previous methods, EPT circumvents the solution of an inverse problem, which might lead to significantly higher spatial image resolution.