Gradient-Induced Mechanical Vibration of Neural Interfaces During MRI

Gradient-induced vibrations and motion-induced Lenz effects on conductive nonmagnetic orthopedic implants in MRI

PURPOSE

To quantify the extent of gradient-induced vibrations, and the magnitude of motion-induced displacement forces ("Lenz effect"), in conductive nonmagnetic orthopedic prostheses.

METHODS

The investigation is carried out through numerical simulations, for a 3 T scanner. For gradient-induced torques and vibrations, a knee and a shoulder implant are considered, at dB/dt equal to 42 T/s (rms). For motion-induced forces associated with the Lenz effect, a knee and a hip implant are studied, considering a patient who translates on the examination couch, or walks next to it.

RESULTS

Gradient-induced torques may be within the same order of magnitude as the worst case gravitational torque defined in the ASTM standards. However, for all investigated cases, they result to be lower. In vacuum, the extent of the corresponding vibration reduces with frequency. At the lowest investigated frequency (270 Hz), it keeps below 25 μm. For an implant partially embedded in bone, the extent of the vibration increases with frequency. Nevertheless, the displacement is far lower than the worst case observed in vacuum (negligible in contact with the bone; ˜1 μm or less where the implant emerges from the bone). The Lenz effect induced by the motion of the patient through the stationary magnetic field produces forces on the order of a few millinewtons (i.e., at least two orders of magnitude lower than the implant weight).

CONCLUSION

Comparing the results with mechanical loads caused by ordinary activities of daily living, and with the levels of tolerable micromotions, a good safety margin is confirmed.

Advances in Injectable Hydrogels Based on Diverse Gelation Methods for Biomedical Imaging

The injectable hydrogels can deliver the loads directly to the predetermined sites and form reservoirs to increase the enrichment and retention of the loads in the target areas. The preparation and injection of injectable hydrogels involve the sol-gel transformation of hydrogels, which is affected by factors such as temperature, ions, enzymes, light, mechanics (self-healing property), and pH. However, tracing the injection, degradation, and drug release from hydrogels based on different ways of gelation is a major concern. To solve this problem, contrast agents are introduced into injectable hydrogels, enabling the hydrogels to be imaged under techniques such as fluorescence imaging, photoacoustic imaging, magnetic resonance imaging, and radionuclide imaging. This review details methods for causing the gelation of imageable hydrogels; discusses the application of injectable hydrogels containing contrast agents in various imaging techniques, and finally explores the potential and challenges of imageable hydrogels based on different modes of gelation.

Vibration and Trajectory Tracking Control of Engineering Mechanical Arm Based on Neural Network

We offer a neural network-based control method to control the vibration of the engineering mechanical arm and the trajectory in order to solve the problem of large errors in tracking the path when the engineering mechanical arm is unstable and under the influence of the outside world. A mechanical arm network is used to perform tasks related to learning the unknown dynamic properties of a engineering mechanical arms keyboard without the need for prior learning. Given the dynamic equations of the engineering mechanical arm, the dynamic properties of the mechanical arm were studied using a positive feedback network. The adaptive neural network management system was developed, and the stability and integrity of the closed-loop system were proved by Lyapunov’s function. Engineering mechanical arm motion trajectory control errors were modeled and validated in the Matlab/Simulink environment. The simulation results show that the management of the adaptive neural network is able to better control the desired path of the engineering mechanical arm in the presence of external interference, and the fluctuation range of input torque is small. The PID control has a large error in the expected trajectory tracking of the engineering mechanical arm, the fluctuation range of the input torque is as high as 20, and the jitter phenomenon is more serious. The use of detailed comparisons and adaptive neural network monitoring can perform well in manipulating the trajectory of the engineering mechanical arm. The engineering mechanical arm uses an adaptive neural network control method, in which the control precision of engineering mechanical arm motion trajectory can be improved and the out-of-control phenomenon of mechanical arm motion can be reduced.

Glassy carbon microelectrodes minimize induced voltages, mechanical vibrations, and artifacts in magnetic resonance imaging

The recent introduction of glassy carbon (GC) microstructures supported on flexible polymeric substrates has motivated the adoption of GC in a variety of implantable and wearable devices. Neural probes such as electrocorticography and penetrating shanks with GC microelectrode arrays used for neural signal recording and electrical stimulation are among the first beneficiaries of this technology. With the expected proliferation of these neural probes and potential clinical adoption, the magnetic resonance imaging (MRI) compatibility of GC microstructures needs to be established to help validate this potential in clinical settings. Here, we present GC microelectrodes and microstructures-fabricated through the carbon micro-electro-mechanical systems process and supported on flexible polymeric substrates-and carry out experimental measurements of induced vibrations, eddy currents, and artifacts. Through induced vibration, induced voltage, and MRI experiments and finite element modeling, we compared the performances of these GC microelectrodes against those of conventional thin-film platinum (Pt) microelectrodes and established that GC microelectrodes demonstrate superior magnetic resonance compatibility over standard metal thin-film microelectrodes. Specifically, we demonstrated that GC microelectrodes experienced no considerable vibration deflection amplitudes and minimal induced currents, while Pt microelectrodes had significantly larger currents. We also showed that because of their low magnetic susceptibility and lower conductivity, the GC microelectrodes caused almost no susceptibility shift artifacts and no eddy-current-induced artifacts compared to Pt microelectrodes. Taken together, the experimental, theoretical, and finite element modeling establish that GC microelectrodes exhibit significant MRI compatibility, hence demonstrating clear clinical advantages over current conventional thin-film materials, further opening avenues for wider adoption of GC microelectrodes in chronic clinical applications.