Theoretical Premises and Contemporary Optimizations of Microwave Tomography

Abstract

Microwave imaging has long been proposed as an effective means for biomedical applications—breast cancer detection and therapy monitoring being the most prominent because of the endogenous dielectric property contrast between malignant and normal breast tissue. While numerous numerical simulations have been presented demonstrating feasibility, translation to actual physical and clinical implementations have been lacking. In contrast, the Dartmouth team has taken somewhat counterintuitive but fundamentals-based approaches to the problem—primarily addressing the confounding multipath signal corruption problem and exploiting core concepts from the parameter estimation community. In so doing, we have configured a unique system design that is a synergism of both the hardware and software worlds. In this paper, we describe our approaches in the context of competing strategies and suggest rationales for why these techniques work—especially in 2D. Finally, we present data from actual neoadjuvant chemotherapy exams that confirm that our technique is capable of imaging the tumor and also visualizing its progression during treatment.