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Susan C. Hagness

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Prof. Susan C. Hagness
Department of Electrical and Computer Engineering, University of Wisconsin–Madison
Madison, WI, USA
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Susan C. Hagness is the Philip Dunham Reed Professor in the Department of Electrical and Computer Engineering at the University of Wisconsin–Madison.

Prof. Hagness’s Distinguished Lectures are as follows.

  • “Imaging Tissue and Treating Cancer with Microwaves”
  • “Miniaturized Antennas for New Microwave Therma l Therapy Applications”
  • “Image Guidance for Thermal Ablation of Cancer Using Microwave Imaging”
  • “From Deterministic to Stochastic Computational Electromagnetics Simulation Tools.”

Imaging Tissue and Treating Cancer with Microwaves

The endogenous (and possibly exogenously influenced) dielectric properties of tissue at microwave frequencies vary across different tissue types and physiological states. These properties may be exploited to differentiate tissues via low-power microwave imaging and selectively heat diseased tissue at higher power levels. This presentation will highlight recent theoretical and experimental advances in low-cost microwave theranostics—that is, diagnostic and therapeutic microwave-based technologies—with an emphasis on breast imaging and targeted cancer treatment. On the diagnostic side, three-dimensional quantitative microwave imaging technology has the potential to address several important clinical needs in breast imaging, including evaluating breast density as part of a patient’s individualized risk assessment, screening women who are at higher risk for cancer, and monitoring changes in breast tissue in response to prevention and treatment protocols. On the therapeutic side, minimally invasive microwave ablation (MWA) using miniaturized antennas as interstitial heating probes is emerging as a less-invasive alternative to surgical resection and a more effective and versatile alternative to conventional thermoablative techniques for the treatment of primary tumors.

Miniaturized Antennas for New Microwave Thermal Therapy Applications

MWA is a promising alternative to conventional cancer treatment modalities, offering quicker recoveries and far fewer risks. MWA involves inserting an interstitial antenna into the diseased tissue and delivering the power necessary to induce coagulation necrosis. Promising clinical results to date have motivated further MWA research to expand the range of MWA tumor targets and performance capabilities. Examples include the design of new ultracompact antennas that have the potential to further reduce the intrusiveness of the MWA antenna as well as antennas that permit greater customization of the shape of the ablation zone. This talk will highlight recent advances in minimally invasive antennas for expanding the scope of MWA treatment targets.

Image Guidance for Thermal Ablation of Cancer Using Microwave Imaging

Real-time image guidance is necessary for monitoring the growth of the ablation zone and verifying the completeness of ablation. Ablation monitoring with ultrasound, magnetic resonance imaging, or computed tomography poses challenges in terms of accuracy, safety, portability, and cost. These challenges motivate the development of integrated microwave technology for simultaneously ablating a malignant tumor and monitoring the therapeutic response. The rationale for microwave monitoring of MWA is twofold. First, microwave monitoring can take advantage of not only the temperature dependence of tissue dielectric properties at microwave frequencies but also the large contrast between ablated and nonablated tissue. Second, microwave monitoring can exploit the presence of the interstitial MWA antenna, using it as a local sensor or internal transmitter to obtain information-rich microwave signals sourced right at the site of the ablation. This presentation will focus on recent progress toward the integration of MWA with real-time microwave monitoring.

From Deterministic to Stochastic Computational Electromagnetics Simulation Tools.

Computational electromagnetics (CEM) simulations are an integral part of the engineering design and optimization process and invaluable as a virtual lab bench in scientific inquiry and exploration. Dozens of commercial CEM software packages are currently available to support design, optimization, inquiry, and exploration activities for applications that span the entire electromagnetic spectrum. The predictive power of CEM techniques has improved such that numerical artifacts are arguably no longer the limiting factor in the accuracy of the simulation. Rather, simulation accuracy is limited by the inherent uncertainty in the input parameters. Uncertainty in the structural dimensions and material properties of electromagnetic devices is pervasive, and as a result, device performance is subject to statistical uncertainty that is not accounted for by deterministic CEM modeling techniques. This talk will highlight the emergence of stochastic CEM modeling techniques to accurately and efficiently predict statistics of electromagnetic characteristics due to known uncertainties in the dimensions and/or material properties of the electromagnetic environment.