Microwave Breast Lesion Classification - Results from Clinical Investigation of the SAFE Microwave Breast Cancer System.

RATIONALE AND OBJECTIVES: Microwave breast cancer imaging (MWI) is an emerging non-invasive technology used to clinically assess the internal breast tissue inhomogeneity. MWI utilizes the variance in dielectric properties of healthy and cancerous tissue to identify anomalies inside the breast and make further clinical predictions. In this study, we evaluate our SAFE MWI system in a clinical setting. Capability of SAFE to provide breast pathology is assessed. MATERIALS AND METHODS: Patients with BI-RADS category 4 or 5 who were scheduled for biopsy were included in the study. Machine learning approach, more specifically the Adaptive Boosting (AdaBoost) model, was implemented to determine if the level of difference between backscattered signals of breasts with the benign and malignant pathological outcome is significant enough for quantitative breast health classification via SAFE. RESULTS: A dataset of 113 (70 benign and 43 malignant) breast samples was used in the study. The proposed classification model achieved the sensitivity, specificity, and accuracy of 79%, 77%, and 78%, respectively. CONCLUSION: The non-ionizing and non-invasive nature gives SAFE an opportunity to impact breast cancer screening and early detection positively. Device classified both benign and malignant lesions at a similar rate. Further clinical studies are planned to validate the findings of this study.

Monitoring of intracerebral hemorrhage with a linear microwave imaging algorithm.

Intracerebral hemorrhage is a life-threatening condition where conventional imaging modalities such as CT and MRI are indispensable in diagnosing. Nevertheless, monitoring the evolution of intracerebral hemorrhage still poses a technological challenge. We consider continuous monitoring of intracerebral hemorrhage in this context and present a differential microwave imaging scheme based on a linearized inverse scattering. Our aim is to reconstruct non-anatomical maps that reveal the volumetric evolution of hemorrhage by using the differences between consecutive electric field measurements. This approach can potentially allow the monitoring of intracerebral hemorrhage in a real-time and cost-effective manner. Here, we devise an indicator function, which reveals the position, volumetric growth, and shrinkage of hemorrhage. Later, the method is numerically tested via a 3D anthropomorphic dielectric head model. Through several simulations performed for different locations of intracerebral hemorrhage, the indicator function-based technique is demonstrated to be capable of detecting the changes accurately. Finally, the robustness under noisy conditions is analyzed to assess the feasibility of the method. This analysis suggests that the method can be used to monitor the evolution of intracerebral hemorrhage in real-world scenarios.

Gradient-Boosting Algorithm for Microwave Breast Lesion Classification-SAFE Clinical Investigation.

(1) Background: Microwave breast imaging (MBI) is a promising breast-imaging technology that uses harmless electromagnetic waves to radiate the breast and assess its internal structure. It utilizes the difference in dielectric properties of healthy and cancerous tissue, as well as the dielectric difference between different cancerous tissue types to identify anomalies inside the breast and make further clinical predictions. In this study, we evaluate the capability of our upgraded MBI device to provide breast tissue pathology. (2) Methods: Only patients who were due to undergo biopsy were included in the study. A machine learning (ML) approach, namely Gradient Boosting, was used to understand information from the frequency spectrum, collected via SAFE, and provide breast tissue pathology. (3) Results: A total of 54 patients were involved in the study: 29 of them had benign and 25 had malignant findings. SAFE acquired 20 true-positive, 24 true-negative, 4 false-positive and 4 false-negative findings, achieving the sensitivity, specificity and accuracy of 80%, 83% and 81%, respectively. (4) Conclusions: The use of harmless tissue radiation indicates that SAFE can be used to provide the breast pathology of women of any age without safety restrictions. Results indicate that SAFE is capable of providing breast pathology at a high rate, encouraging further clinical investigations.

Single-slice microwave imaging of breast cancer by reverse time migration.

PURPOSE: Microwave imaging of breast cancer is considered and a new microwave imaging prototype including the imaging algorithm, the antenna array, and the measurement configuration is presented. The prototype aims to project the geometrical features of the anomalies inside the breast to a single-slice image at the coronal plane depending on the complex dielectric permittivity variation among the tissues to aid the diagnosis. METHODS: The imaging prototype uses a solid cylindrical dielectric platform, where a total of 24 optimized Vivaldi antennas are embedded inside to form a uniform circular antenna array. The center of the platform is carved to create a hollow part for placement of the breast and the multistatic, microwave scattering parameters are collected with the antenna array around the hollow center. The dielectric platform further enhances the microwave impedance matching against the breast fat tissue and preserves the vertical polarization during the measurements. In the imaging phase, a computationally efficient inverse electromagnetic scattering method-reverse time migration (RTM)-is considered and adapted in terms of scattering parameters to comply with the actual measurements. RESULTS: The prototype system is experimentally tested against tissue-mimicking breast phantoms with realistic dielectric permittivity profiles. The reconstructed single-slice images accurately determined the locations and the geometrical extents of the tumor phantoms. These experiments not only verified the microwave imaging prototype but also provided the first experimental results of the imaging algorithm. CONCLUSIONS: The presented prototype system implementing the RTM method is capable of reconstructing single-slice, nonanatomical images, where the hotspots correspond to the geometrical projections of the anomalies inside the breast.

SAFE: A Novel Microwave Imaging System Design for Breast Cancer Screening and Early Detection-Clinical Evaluation.

SAFE (Scan and Find Early) is a novel microwave imaging device intended for breast cancer screening and early detection. SAFE is based on the use of harmless electromagnetic waves and can provide relevant initial diagnostic information without resorting to X-rays. Because of SAFE's harmless effect on organic tissue, imaging can be performed repeatedly. In addition, the scanning process itself is not painful since breast compression is not required. Because of the absence of physical compression, SAFE can also detect tumors that are close to the thoracic wall. A total number of 115 patients underwent the SAFE scanning procedure, and the resultant images were compared with available magnetic resonance (MR), ultrasound, and mammography images in order to determine the correct detection rate. A sensitivity of 63% was achieved. Breast size influenced overall sensitivity, as sensitivity was lower in smaller breasts (51%) compared to larger ones (74%). Even though this is only a preliminary study, the results show promising concordance with clinical reports, thus encouraging further SAFE clinical studies.

Microwave imaging of breast cancer with factorization method: SPIONs as contrast agent.

Female breast at macroscopic scale is a nonmagnetic medium, which eliminates the possibility of realizing microwave imaging of the breast cancer based on magnetic permeability variations. However, by administering functionalized, superparamagnetic iron oxide nanoparticles (SPIONs) as a contrast material to modulate magnetic permeability of cancer cells, a small variation on the scattered electric field from the breast is achievable under an external, polarizing magnetic field. PURPOSE: We demonstrate an imaging technique that can locate cancerous tumors inside the breast due to electric field variations caused by SPION tracers under different magnetic field intensities. Furthermore, we assess the feasibility of SPION-enhanced microwave imaging for breast cancer with simulations performed on a multi-static imaging configuration. METHODS: The imaging procedure is realized as the factorization method of qualitative inverse scattering theory, which is essentially a shape retrieval algorithm for inaccessible objects. The formulation is heuristically modified to accommodate the scattering parameters instead of the electric field to comply with the requirements of experimental microwave imaging systems. RESULTS: With full-wave electromagnetic simulations performed on an anthropomorphically realistic breast phantom, which is excited with a cylindrical imaging prototype of 18 dipole antenna arranged as a single row, the technique is able to locate cancerous tumors for a experimentally achievable doses. CONCLUSIONS: The technique generates nonanatomic microwave images, which map the cancerous tumors depending on the concentration of SPION tracers, to aid the diagnosis of the breast cancer.

Microwave dielectric property based classification of renal calculi: Application of a kNN algorithm.

The proper management of renal lithiasis presents a challenge, with the recurrence rate of the disease being as high as 46%. To prevent recurrence, the first step is the accurate categorization of the discarded renal calculi. Currently, the discarded renal calculi type is determined with the X-ray powder diffraction method which requires a cumbersome sample preparation. This work presents a new approach that can enable fast and accurate classification of discarded renal calculi with minimal sample preparation requirements. To do so, first, the measurements of the dielectric properties of naturally formed renal calculi are collected with the open-ended contact probe technique between 500 MHz and 6 GHz with 100 MHz intervals. Cole-Cole parameters are fitted to the measured dielectric properties with the generalized Newton-Raphson method. The renal calculi types are classified based on their Cole-Cole parameters as calcium oxalate, cystine, or struvite. The classification is performed using k-nearest neighbors (kNN) machine learning algorithm with the 10 nearest neighbors, where accuracy as high as 98.17% is achieved.

Qualitative microwave imaging of breast cancer with contrast agents.

A microwave imaging (MWI) methodology for early diagnosis of breast cancer is presented. Instead of generating a tomographic image of the breast, the proposed technique aims to reconstruct a map of malignant tumours inside the breast by adopting an extended form of factorization method. The implementation of factorization method requires (i) two multi-static scattered field measurements around the breast, which correspond to two different states of the breast, and (ii) the inhomogeneous Green's function associated to the breast. For this purpose, the paper proposes the use of contrast agents, which selectively increase the dielectric properties of the malign tissues. Two multi-static field measurements are collected before and after the administration of contrast agents. Later, the inhomogeneous Green's function of the breast is estimated by back-propagating the scattered field measurements, which are taken before the contrast agent usage. The feasibility and efficiency of the proposed technique are demonstrated with numerical examples that are performed on a slice of the realistic breast phantoms, which are derived from real three dimensional magnetic resonance imaging (3D-MRI) measurements.

Hand-Held Volatilome Analyzer Based on Elastically Deformable Nanofibers.

This study reports on a hand-held volatilome analyzer for selective determination of clinically relevant biomarkers in exhaled breath. The sensing platform is based on electrospun polymer nanofiber-multiwalled carbon nanotube (MWCNT) sensing microchannels. Polymer nanofibers of poly(vinylidene fluoride) (PVDF), polystyrene (PS), and poly(methyl methacrylate) (PMMA) incorporated with MWCNT exhibits a stable response to interferences of humidity and CO2 and provides selective deformations upon exposure of exhaled breath target volatilomes acetone and toluene, exhibiting correlation to diabetes and lung cancer, respectively. The sensing microchannels "P1" (PVDF-MWCNT), "P2" (PS-MWCNT), and "P3" (PMMA-MWCNT) are integrated with a microfluidic cartridge (µ-card) that facilitates collection and concentration of exhaled breath. The volatilome analyzer consists of a conductivity monitoring unit, signal conditioning circuitries and a low energy display module. A combinatorial operation algorithm was developed for analyzing normalized resistivity changes of the sensing microchannels upon exposure to breath in the concentration ranges between 35 ppb and 3.0 ppm for acetone and 1 ppb and 10 ppm for toluene. Subsequently, responses of volatilomes from individuals in the different risk groups of diabetes were evaluated for validation of the proposed methodology. We foresee that proposed methodology provides an avenue for rapid detection of volatilomes thereby enabling point of care diagnosis in high-risk group individuals.

Machine learning aided diagnosis of hepatic malignancies through in vivo dielectric measurements with microwaves.

In the past decade, extensive research on dielectric properties of biological tissues led to characterization of dielectric property discrepancy between the malignant and healthy tissues. Such discrepancy enabled the development of microwave therapeutic and diagnostic technologies. Traditionally, dielectric property measurements of biological tissues is performed with the well-known contact probe (open-ended coaxial probe) technique. However, the technique suffers from limited accuracy and low loss resolution for permittivity and conductivity measurements, respectively. Therefore, despite the inherent dielectric property discrepancy, a rigorous measurement routine with open-ended coaxial probes is required for accurate differentiation of malignant and healthy tissues. In this paper, we propose to eliminate the need for multiple measurements with open-ended coaxial probe for malignant and healthy tissue differentiation by applying support vector machine (SVM) classification algorithm to the dielectric measurement data. To do so, first, in vivo malignant and healthy rat liver tissue dielectric property measurements are collected with open-ended coaxial probe technique between 500 MHz to 6 GHz. Cole-Cole functions are fitted to the measured dielectric properties and measurement data is verified with the literature. Malign tissue classification is realized by applying SVM to the open-ended coaxial probe measurements where as high as 99.2% accuracy (F1 Score) is obtained.

Surface impedance based microwave imaging method for breast cancer screening: contrast-enhanced scenario.

A new microwave imaging method that uses microwave contrast agents is presented for the detection and localization of breast tumours. The method is based on the reconstruction of breast surface impedance through a measured scattered field. The surface impedance modelling allows for representing the electrical properties of the breasts in terms of impedance boundary conditions, which enable us to map the inner structure of the breasts into surface impedance functions. Later a simple quantitative method is proposed to screen breasts against malignant tumours where the detection procedure is based on weighted cross correlations among impedance functions. Numerical results demonstrate that the method is capable of detecting small malignancies and provides reasonable localization.