Tunable and Anisotropic Dual-Band Metamaterial Absorber Using Elliptical Graphene-Black Phosphorus Pairs.

We numerically propose a dual-band absorber in the infrared region based on periodic elliptical graphene-black phosphorus (BP) pairs. The proposed absorber exhibits near-unity anisotropic absorption for both resonances due to the combination of graphene and BP. Each of the resonances is independently tunable via adjusting the geometric parameters. Besides, doping levels of graphene and BP can also tune resonant properties effectively. By analyzing the electric field distributions, surface plasmon resonances are observed in the graphene-BP ellipses, contributing to the strong and anisotropic plasmonic response. Moreover, the robustness for incident angles and polarization sensitivity are also illustrated.

The performance of a reduced-order adaptive controller when used in multi-antenna hyperthermia treatments with nonlinear temperature-dependent perfusion.

In large multi-antenna systems, adaptive controllers can aid in steering the heat focus toward the tumor. However, the large number of sources can greatly increase the steering time. Additionally, controller performance can be degraded due to changes in tissue perfusion which vary non-linearly with temperature, as well as with time and spatial position. The current work investigates whether a reduced-order controller with the assumption of piecewise constant perfusion is robust to temperature-dependent perfusion and achieves steering in a shorter time than required by a full-order controller. The reduced-order controller assumes that the optimal heating setting lies in a subspace spanned by the best heating vectors (virtual sources) of an initial, approximate, patient model. An initial, approximate, reduced-order model is iteratively updated by the controller, using feedback thermal images, until convergence of the heat focus to the tumor. Numerical tests were conducted in a patient model with a right lower leg sarcoma, heated in a 10-antenna cylindrical mini-annual phased array applicator operating at 150 MHz. A half-Gaussian model was used to simulate temperature-dependent perfusion. Simulated magnetic resonance temperature images were used as feedback at each iteration step. Robustness was validated for the controller, starting from four approximate initial models: (1) a 'standard' constant perfusion lower leg model ('standard' implies a model that exactly models the patient with the exception that perfusion is considered constant, i.e., not temperature dependent), (2) a model with electrical and thermal tissue properties varied from 50% higher to 50% lower than the standard model, (3) a simplified constant perfusion pure-muscle lower leg model with +/-50% deviated properties and (4) a standard model with the tumor position in the leg shifted by 1.5 cm. Convergence to the desired focus of heating in the tumor was achieved for all four simulated models. The controller accomplished satisfactory therapeutic outcomes: approximately 80% of the tumor was heated to temperatures 43 degrees C and approximately 93% was maintained at temperatures <41 degrees C. Compared to the controller without model reduction, a approximately 9-25 fold reduction in convergence time was accomplished using approximately 2-3 orthonormal virtual sources. In the situations tested, the controller was robust to the presence of temperature-dependent perfusion. The results of this work can help to lay the foundation for real-time thermal control of multi-antenna hyperthermia systems in clinical situations where perfusion can change rapidly with temperature.

Control time reduction using virtual source projection for treating a leg sarcoma with nonlinear perfusion.

PURPOSE: Blood perfusion is a well-known factor that complicates accurate control of heating during hyperthermia treatments of cancer. Since blood perfusion varies as a function of time, temperature and location, determination of appropriate power deposition pattern from multiple antenna array Hyperthermia systems and heterogeneous tissues is a difficult control problem. Therefore, we investigate the applicability of a real-time eigenvalue model reduction (virtual source - VS) reduced-order controller for hyperthermic treatments of tissue with nonlinearly varying perfusion. METHODS: We impose a piecewise linear approximation to a set of heat pulses, each consisting of a 1-min heat-up, followed by a 2-min cool-down. The controller is designed for feedback from magnetic resonance temperature images (MRTI) obtained after each iteration of heat pulses to adjust the projected optimal setting of antenna phase and magnitude for selective tumor heating. Simulated temperature patterns with additive Gaussian noise with a standard deviation of 1.0°C and zero mean were used as a surrogate for MRTI. Robustness tests were conducted numerically for a patient's right leg placed at the middle of a water bolus surrounded by a 10-antenna applicator driven at 150 MHz. Robustness tests included added discrepancies in perfusion, electrical and thermal properties, and patient model simplifications. RESULTS: The controller improved selective tumor heating after an average of 4-9 iterative adjustments of power and phase, and fulfilled satisfactory therapeutic outcomes with approximately 75% of tumor volumes heated to temperatures >43°C while maintaining about 93% of healthy tissue volume < 41°C. Adequate sarcoma heating was realized by using only 2 to 3 VSs rather than a much larger number of control signals for all 10 antennas, which reduced the convergence time to only 4 to 9% of the original value. CONCLUSIONS: Using a piecewise linear approximation to a set of heat pulses in a VS reduced-order controller, the proposed algorithm greatly improves the efficiency of hyperthermic treatment of leg sarcomas while accommodating practical nonlinear variation of tissue properties such as perfusion.

Microwave breast imaging: 3-D forward scattering simulation.

Active microwave imaging (MWI) is emerging as a promising technique for the detection of biomedical anomalies such as breast cancer because of the high electrical contrasts between malignant tumors and normal tissue. Previously, we have developed fast two-dimensional forward and inverse scattering algorithms for MWI systems. In this paper, we report the full three-dimensional (3-D) forward scattering simulation in order to account for 3-D effects and to provide a fast solver in future 3-D nonlinear inverse scattering methods. The 3-D fast forward method is based on the stabilized biconjugate-gradient fast Fourier transform (BCGS-FFT) algorithm. The method has been validated for various MWI measurement scenarios. Using this fast simulation method, we demonstrate the importance of accounting for 3-D effects in MWI, and we compare numerical results with the measurements from an experimental prototype.