The aim of this work was to develop multimodal anthropomorphic breast phantoms suitable for evaluating the imaging performance of a recently-introduced Microwave Imaging (MWI) technique in comparison to the established diagnostic imaging modalities of Magnetic Resonance Imaging (MRI), Ultrasound (US), mammography and Computed Tomography (CT). MWI is an emerging technique with significant potential to supplement established imaging techniques to improve diagnostic confidence for breast cancer detection. To date, numerical simulations have been used to assess the different MWI scanning and image reconstruction algorithms in current use, while only a few clinical trials have been conducted. To bridge the gap between the numerical simulation environment and a more realistic diagnostic scenario, anthropomorphic phantoms which mimic breast tissues in terms of their heterogeneity, anatomy, morphology, and mechanical and dielectric characteristics, may be used. Key in this regard is achieving realism in the imaging appearance of the different healthy and pathologic tissue types for each of the modalities, taking into consideration the differing imaging and contrast mechanisms for each modality. Suitable phantoms can thus be used by radiologists to correlate image findings between the emerging MWI technique and the more familiar images generated by the conventional modalities. Two phantoms were developed in this study, representing difficult-to-image and easy-to-image patients: the former contained a complex boundary between the mammary fat and fibroglandular tissues, extracted from real patient MRI datasets, while the latter contained a simpler and less morphologically accurate interface. Both phantoms were otherwise identical, with tissue-mimicking materials (TMMs) developed to mimic skin, subcutaneous fat, fibroglandular tissue, tumor and pectoral muscle. The phantoms’ construction used non-toxic materials, and they were inexpensive and relatively easy to manufacture. Both phantoms were scanned using conventional modalities (MRI, US, mammography and CT) and a recently introduced MWI radar detection procedure called in-coherent Multiple Signal Classification (I-MUSIC). Clinically realistic artifact-free images of the anthropomorphic breast phantoms were obtained using the conventional imaging techniques as well as the emerging technique of MWI.

In this paper we consider radar approaches for breast cancer detection. The aim is to give a brief review of the main features of incoherent methods, based on beam-forming and Multiple SIgnal Classification (MUSIC) algorithms, that we have recently developed, and to compare them with classical coherent beam-forming. Those methods have the remarkable advantage of not requiring antenna characterization/compensation, which can be problematic in view of the close (to the breast) proximity set-up usually employed in breast imaging. Moreover, we proceed to an experimental validation of one of the incoherent methods, i.e., the I-MUSIC, using the multimodal breast phantom we have previously developed. While in a previous paper we focused on the phantom manufacture and characterization, here we are mainly concerned with providing the detail of the reconstruction algorithm, in particular for a new multi-step clutter rejection method that was employed and only barely described. In this regard, this contribution can be considered as a completion of our previous study. The experiments against the phantom show promising results and highlight the crucial role played by the clutter rejection procedure.

The objective of the study was to investigate whether clinically used ultrasonic contrast agents improved the accuracy of spectral Doppler ultrasound in the detection of low grade (<50%) renal artery stenosis. Low grade stenoses in the renal artery are notoriously difficult to reliably detect using Doppler ultrasound due to difficulties such as overlying fat and bowel gas. A range of anatomically-realistic renal artery phantoms with varying low degrees of stenosis (0, 30 and 50%) were constructed and peak velocity data was measured from within the pre-stenotic and mid-stenotic regions in each phantom, for both unenhanced and contrast-enhanced spectral Doppler data acquisitions. The effect of a 20 mm overlying fat layer on the ultrasound beam distortion and phase aberration, and hence on the measured peak velocity data, was also investigated. The overlying fat layer produced a statistically significant underestimation (p < 0.01) in both the peak velocity and peak velocity ratio [Stenotic Region(Vmax)/Pre-stenotic Region(Vmax)] for the 0% and 30% stenosis models, but not the 50% model. A statistically significant increase (p < 0.01) in the peak velocity was found in the contrast-enhanced Doppler spectra; however, no significant difference was found between the unenhanced and contrast enhanced peak velocity ratio data, which suggests that the ratio metric has better diagnostic accuracy. The peak velocity ratios determined for each of the contrast-enhanced phantoms correctly predicted if the phantom had a stenosis and furthermore correctly classified the degree of stenosis. Contrast-enhanced Doppler ultrasound could significantly assist in the early detection of renal artery disease.

In this contribution we briefly present the experimental verification of incoherent radar imaging approaches recently developed in the framework of medical imaging. In particular, a prototype radar system is described and breast and head phantoms are developed and employed to collect the measurements.