Rosa Scapaticci

A FEASIBILITY STUDY ON MICROWAVE IMAGING FOR BRAIN STROKE MONITORING

The adoption of microwave imaging as a tool for non- invasive monitoring of brain stroke has recently gained increasing attention. In this respect, the paper aims at providing a twofold contribution. First, we introduce a simple design tool to devise guidelines to properly set the working frequency as well as to choose the optimum matching medium needed to facilitate the penetration of the probing wave into the head. Second, we propose an imaging strategy based on a modifled formulation of the linear sampling method, which allows a quasi real time monitoring of the diseases evolution. The accuracy of the design guidelines and performance of the imaging strategy are assessed through numerical examples dealing with 2D anthropomorphic phantoms.

An Effective Procedure for MNP-Enhanced Breast Cancer Microwave Imaging

Magnetic nanoparticles-enhanced microwave imaging has been recently proposed to overcome the limitations of conventional microwave imaging methods for breast cancer monitoring. In this paper, we discuss how to tackle the linear inverse scattering problem underlying this novel technique in an effective way. In particular, our aim is to minimize the required a priori patient-specific information, avoid occurrence of false positives, and keep the computational burden low. By relying on an extensive numerical analysis in realistic conditions, we show that the method can provide accurate and reliable images without information on the inner structure of the inspected breast and with an only rough knowledge of its shape. Notably, this allows moving to an offline stage the computationally intensive part of the image formation procedure. In addition, we show how to appraise the total amount of magnetic contrast agent targeted in the tumor.

Wavelet-Based Adaptive Multiresolution Inversion for Quantitative Microwave Imaging of Breast Tissues

Microwave imaging is a feasible tool for medical imaging owing to the different electric properties of tissues. To this end, it is important to devise inversion procedures capable of achieving a reliable quantitative estimate of the tissues under test. With respect to breast screening, we propose a full-wave inversion method, which takes advantage of the adaptive multiresolution features of the wavelet basis to accommodate the trade off between spatial resolution and inversion stability. As shown through a preliminary numerical assessment on 2D anthropomorphic breast phantoms, the proposed approach is capable of achieving satisfying results without any a priori knowledge of breast shape, as well as of thickness and electric properties of the skin layer.

Differential Microwave Imaging for Brain Stroke Followup

This paper deals with the possibility of adopting microwave imaging to continuously monitor a patient after the onset of a brain stroke, with the aim to follow the evolution of the disease, promptly counteract its uncontrolled growth, and possibly support decisions in the clinical treatment. In such a framework, the assessed techniques for brain stroke diagnosis are indeed not suitable to pursue this goal. Conversely, microwave imaging can provide a diagnostic tool able to follow up the disease’s evolution, while relying on a relatively low cost and portable apparatus. The proposed imaging procedure is based on a differential approach which requires the processing of scattered field data measured at different time instants. By means of a numerical analysis dealing with synthetic data generated for realistic anthropomorphic phantoms, we address some crucial issues for the method’s effectiveness. In particular, we discuss the role of patient-specific information and the effect of inaccuracies in the measurement procedure, such as an incorrect positioning of the probes between two different examinations. The observed results show that the proposed technique is indeed feasible, even when a simple, nonspecific model of the head is exploited and is robust against the above mentioned inaccuracies.

Wavelet-Based Regularization for Robust Microwave Imaging in Medical Applications

Microwave imaging (MWI) is an emerging tool for medical diagnostics, potentially offering unique advantages such as the capability of providing quantitative images of the inspected tissues. This involves, however, solving a challenging nonlinear and ill-posed electromagnetic inverse scattering problem. This paper presents a robust method for quantitative MWI in medical applications where very little, if any, a priori information on the imaging scenario is available. This is accomplished by employing a distorted Born iterative method and a regularization by projection technique, which reconstructs the tissue parameters using a wavelet basis expansion to represent the unknown contrast. This approach is suited for any microwave medical imaging application where the requirement for increased resolution dictates the use of higher frequency data and, consequently, a robust regularization strategy. To demonstrate the robustness of the proposed approach, this paper presents reconstructions of highly heterogeneous anatomically realistic numerical breast phantoms in a canonical 2-D configuration.

MNP Enhanced Microwave Breast Cancer Imaging: Measurement Constraints and Achievable Performances

Magnetic nanoparticles (MNP) enhanced microwave imaging has been recently proposed as a tool to pursue the diagnostics of breast cancer in an effective and reliable way. By means of a numerical analysis carried out under realistic conditions, this letter aims at assessing the measurement dynamic range (i.e., the measurement resolution), in terms of tumor size, nanoparticles concentration, and working frequency, required for an apparatus based on this diagnostic approach.

A Compressive Sensing Approach for 3D Breast Cancer Microwave Imaging With Magnetic Nanoparticles as Contrast Agent

In microwave breast cancer imaging magnetic nanoparticles have been recently proposed as contrast agent. Due to the non-magnetic nature of human tissues, magnetic nanoparticles make possible the overcoming of some limitations of conventional microwave imaging techniques, thus providing reliable and specific diagnosis of breast cancer. In this paper, a Compressive Sensing inspired inversion technique is introduced for the reconstruction of the magnetic contrast induced within the tumor. The applicability of Compressive Sensing theory is guaranteed by the fact that the underlying inverse scattering problem is linear and the searched magnetic perturbation is sparse. From the numerical analysis, performed in realistic conditions in 3D geometry, it has been pointed out that the adoption of this new tool allows improving resolution and accuracy of the reconstructions, as well as reducing the number of required measurements.

On the Design of Phased Arrays for Medical Applications

This paper deals with the optimal design of phased arrays for medical applications of microwaves, such as hyperthermia treatments and cancer imaging. To address this problem, microwave engineers have to face peculiar and novel challenges, since the region of interest is a 3-D domain in the near field of the array and consists of a highly heterogeneous and lossy medium, whose characteristics change from patient to patient. For this reason, we have to reconsider basic fundamentals about phased array design, in order to devise proper tools and criteria. In particular, we address the design of the system layout, i.e., the choice of the number and locations of the array elements, as this represents the preliminary fundamental problem to face. To this end, we first formulate the two general problems relevant to biomedical applications-the design of an array for therapeutic purposes and of an array for diagnostic/imaging goals. We then address the proper theoretical and analytic tools and methods that enable pursuit of an optimal design with respect to given constraints. Finally, we provide some examples to show how the design procedure can be carried out in practice.

An Effective Method for Borehole Imaging of Buried Tunnels

Detection and imaging of buried tunnels is a challenging problem which is relevant to both geophysical surveys and security monitoring. To comply with the need of exploring large portions of the underground, electromagnetic measurements carried out under a borehole configuration are usually exploited. Since this requires to drill holes in the soil wherein the transmitting and receiving antennas have to be positioned, low complexity of the involved apparatus is important. On the other hand, to effectively image the surveyed area, there is the need for adopting efficient and reliable imaging methods. To address these issues, in this paper we investigate the feasibility of the linear sampling method (LSM), as this inverse scattering method is capable to provide almost real-time results even when 3D images of very large domains are built, while not requiring approximations of the underlying physics. In particular, the results of the reported numerical analysis show that the LSM is capable of performing the required imaging task while using a quite simple measurement configuration consisting of two boreholes and a few number of multiview-multistatic acquisitions.

Exploiting Microwave Imaging Methods for Real-Time Monitoring of Thermal Ablation

Microwave thermal ablation is a cancer treatment that exploits local heating caused by a microwave electromagnetic field to induce coagulative necrosis of tumor cells. Recently, such a technique has significantly progressed in the clinical practice. However, its effectiveness would dramatically improve if paired with a noninvasive system for the real-time monitoring of the evolving dimension and shape of the thermally ablated area. In this respect, microwave imaging can be a potential candidate to monitor the overall treatment evolution in a noninvasive way, as it takes direct advantage from the dependence of the electromagnetic properties of biological tissues from temperature. This paper explores such a possibility by presenting a proof of concept validation based on accurate simulated imaging experiments, run with respect to a scenario that mimics an ex vivo experimental setup. In particular, two model-based inversion algorithms are exploited to tackle the imaging task. These methods provide independent results in real-time and their integration improves the quality of the overall tracking of the variations occurring in the target and surrounding regions.