Microwave Imaging System Based on Signal Analysis in a Planar Environment for Detection of Abdominal Aortic Aneurysms.

A proof-of-concept of a microwave imaging system for the fast detection of abdominal aortic aneurysms is shown. This experimental technology seeks to overcome the factors hampering the fast screening for these aneurysms with the usual equipment, such as high cost, long-time operation or hazardous exposure to chemical substances. The hardware system is composed of 16 twin antennas mastered by a microcontroller through a switching network, which connects the antennas to the measurement instrument for sequential measurement. The software system is run by a computer, mastering the whole system, automatizing the measurement process and running the signal processing and medical image generation algorithms. Two image generation algorithms are tested: Delay-and-Sum (DAS) and Improved Delay-and-Sum (IDAS). Own-modified versions of these algorithms adapted to the requirements of our system are proposed. The system is carefully calibrated and fine-tuned with known objects placed at known distances. An experimental proof-of-concept is shown with a human torso phantom, including an aorta phantom and an aneurysm phantom placed in different positions. The results show good imaging capabilities with the potential for detecting and locating possible abdominal aortic aneurysms and reporting acceptable errors.

UWB Antenna with Enhanced Directivity for Applications in Microwave Medical Imaging.

Microwave medical imaging (MMI) is experiencing a surge in research interest, with antenna performance emerging as a key area for improvement. This work addresses this need by enhancing the directivity of a compact UWB antenna using a Yagi-Uda-inspired reflector antenna. The proposed reflector-loaded antenna (RLA) exhibited significant gain and directivity improvements compared to a non-directional reference antenna. When analyzed for MMI applications, the RLA showed a maximum increase of 4 dBi in the realized gain and of 14.26 dB in the transmitted field strength within a human breast model. Moreover, it preserved the shape of time-domain input signals with a high correlation factor of 94.86%. To further validate our approach, another non-directional antenna with proven head imaging capabilities was modified with a reflector, achieving similar directivity enhancements. The combined results demonstrate the feasibility of RLAs for improved performance in MMI systems.

Microwave Imaging Based on a Subspace-based Two-step Iterative Shrinkage/Thresholding Method.

This paper presents a subspace-based two-step iterative shrinkage/thresholding method(S-TwIST) based on the Distorted Born iterative method (DBIM) to improve the performance of the original TwIST inverse algorithm. This method retrieves the deterministic part of the induced current from inhomogeneous Green's function operator leading to more accurate total field calculation at each iteration step than that of the original TwIST. Both inverse algorithms have been evaluated with a set of synthetic geometries with fine structures. Compared with TwIST, the results show that S-TwIST has superior accuracy in multiple objects profile (εerr=0.1454%) and 1/16λ resolution at 2GHz. Also, S-TwIST is more robust to initial guess, which means it is less likely to become unstable when the inversion procedure starts without initial guess.

Microwave imaging for monitoring breast cancer treatment: A pilot study.

BACKGROUND: Microwave imaging has been proposed for medical applications, creating maps related to water content of tissues. Breast imaging has emerged as a key application because the signals can be coupled directly into the breast and experience limited attenuation in fatty tissues. While the literature contains reports of tumor detection with microwave approaches, there is limited exploration of treatment monitoring. PURPOSE: This study aims to detect treatment-related changes in breast tissue with a low-resolution microwave scanner. METHODS: Microwave scans of 15 patients undergoing treatment for early-stage breast cancer are collected at up to 4 time points: after surgery (baseline), 6 weeks after accelerated partial breast radiation, as well as 1 and 2 years post-treatment. Both the treated and untreated breast are scanned at each time point. The microwave scanner consists of planar transmit and receive arrays and uses signals from 0.1 to 10 GHz. The average microwave frequency properties (permittivity) are calculated for each scan to enable quantitative comparison. Baseline and 6-week results are analyzed with a two-way ANOVA with blocking. RESULTS: Consistent properties are observed for the untreated breast over time, similar to a previous study. Comparison of the scans of the treated and untreated breast suggests increased properties related to treatment, particularly at baseline and 6-weeks following radiotherapy. Analysis of the average properties of the scans with ANOVA indicates statistically significant differences ( p < 0.05 $p < 0.05$ ) in the treated and untreated breast at these time points. CONCLUSIONS: Microwave imaging has the potential to track treatment-related changes in breast tissues.

Semi-automatic artifact quantification in thermal ablation probe and algorithms for the evaluation of metal artifact reduction.

OBJECTIVES: To compare metal artifacts and evaluation of metal artifact reduction algorithms during probe positioning in computed tomography (CT)-guided microwave ablation (MWA), cryoablation (CRYO), and radiofrequency ablation (RFA). MATERIALS AND METHODS: Using CT guidance, individual MWA, CRYO, and RFA ablation probes were placed into the livers of 15 pigs. CT imaging was then performed to determine the probe's position within the test subject's liver. Filtered back projection (B30f) and iterative reconstructions (I30-1) were both used with and without dedicated iterative metal artifact reduction (iMAR) to generate images from the initial data sets. Semi-automatic segmentation-based quantitative evaluation was conducted to estimate artifact percentage within the liver, while qualitative evaluation of metal artifact extent and overall image quality was performed by two observers using a 5-point Likert scale: 1-none, 2-mild, 3-moderate, 4-severe, 5-non-diagnostic. RESULTS: Among MWA, RFA, and CRYO, compared with non-iMAR in B30f reconstruction, the largest extent of artifact volume percentages were observed for CRYO (11.5-17.9%), followed by MWA (4.7-6.6%) and lastly in RFA (5.5-6.2%). iMAR significantly reduces metal artifacts for CRYO and MWA quantitatively (p = 0.0020; p = 0.0036, respectively) and qualitatively (p = 0.0001, p = 0.0005), but not for RFA. No significant reduction in metal artifact percentage was seen after applying iterative reconstructions (p > 0.05). Noise, contrast-to-noise-ratio, or overall image quality did not differ between probe types, irrespective of the application of iterative reconstruction and iMAR. CONCLUSION: A dedicated metal artifact algorithm may decrease metal artifacts and improves image quality significantly for MWA and CRYO probes. Their application alongside with dedicated metal artifact algorithm should be considered during CT-guided positioning.

UWB-Modulated Microwave Imaging for Human Brain Functional Monitoring.

Morphological microwave imaging has shown interesting results on reconstructing biological objects inside the human body, and these parameters represent their actual biological condition, but not their biological activity. In this paper, we propose a novel microwave technique to locate the low-frequency (f≃1 kHz) -modulated signals produced by a microtag mimicking an action potential and proved it in a cylindrical phantom of the brain region. A set of two combined UWB microwave applicators, operating in the 0.5 to 2.5 GHz frequency band and producing a nsec interrogation pulse, is able to focus its radiated field into a small region of the brain containing the microtag with a modulated photodiode. The illuminating UWB microwave field was first modulated by the low-frequency (f≃1 kHz) electrical signal produced by the photodiode, inducing modulated microwave currents into the microtag that reradiating back towards the focusing applicators. At the receiving end, the low-frequency (f≃1 kHz) -modulated signal was first extracted from the full set of the backscattered signals, then focused into the region of interest and spatially represented in the corresponding region of the brain, resulting in a spatial resolution of the images in the order of 10 mm.

Review of microwave imaging algorithms for stroke detection.

Microwave imaging is one of the rapidly developing frontier disciplines in the field of modern medical imaging. The development of microwave imaging algorithms for reconstructing stroke images is discussed in this paper. Compared with traditional stroke detection and diagnosis techniques, microwave imaging has the advantages of low price and no ionizing radiation hazards. The research hotspots of microwave imaging algorithms in the field of stroke are mainly reflected in the design and improvement of microwave tomography, radar imaging, and deep learning imaging. However, the current research lacks the analysis and combing of microwave imaging algorithms. In this paper, the development of common microwave imaging algorithms is reviewed. The concept, research status, current research hotspots and difficulties, and future development trends of microwave imaging algorithms are systematically expounded. The microwave antenna is used to collect scattered signals, and a series of microwave imaging algorithms are used to reconstruct the stroke image. The classification diagram and flow chart of the algorithms are shown in this Figure. (The classification diagram and flow chart are based on the microwave imaging algorithms.).

Split Ring Resonator Topology Based Microwave Induced Thermoacoustic Imaging (SRR-MTAI).

Microwave-induced thermoacoustic imaging (MTAI) using low-energy and long-wavelength microwave photons has great potential in detecting deep-seated diseases due to its unique ability of visualizing intrinsic electric properties of tissue in high resolution. However, the low contrast in conductivity between a target (e.g., a tumor) and the surroundings sets a fundamental limit for achieving a high imaging sensitivity, which significantly hinders its biomedical applications. To overcome this limit, we develop a split ring resonator (SRR) topology based MTAI (SRR-MTAI) approach to achieve highly sensitive detection by precise manipulation and efficient delivery of microwave energy. The in vitro experiments show that SRR-MTAI demonstrates an ultrahigh sensitivity of distinguishing a 0.4% difference in saline concentrations and a 2.5-fold enhancement of detecting a tissue target which mimicks a tumor embedded at a depth of 2 cm. The in vivo animal experiments conducted indicate that the imaging sensitivity between a tumor and the surrounding tissue is increased by 3.3-fold using SRR-MTAI. The dramatic enhancement in imaging sensitivity suggests that SRR-MTAI has the potential to open new avenues for MTAI to tackle a variety of biomedical problems that were impossible previously.

Evaluating the Performance of Algorithms in Axillary Microwave Imaging towards Improved Breast Cancer Staging.

Breast cancer is the most common and the fifth deadliest cancer worldwide. In more advanced stages of cancer, cancer cells metastasize through lymphatic and blood vessels. Currently there is no satisfactory neoadjuvant (i.e., preoperative) diagnosis to assess whether cancer has spread to neighboring Axillary Lymph Nodes (ALN). This paper addresses the use of radar Microwave Imaging (MWI) to detect and determine whether ALNs have been metastasized, presenting an analysis of the performance of different artifact removal and beamformer algorithms in distinct anatomical scenarios. We assess distinct axillary region models and the effect of varying the shape of the skin, muscle and subcutaneous adipose tissue layers on single ALN detection. We also study multiple ALN detection and contrast between healthy and metastasized ALNs. We propose a new beamformer algorithm denominated Channel-Ranked Delay-Multiply-And-Sum (CR-DMAS), which allows the successful detection of ALNs in order to achieve better Signal-to-Clutter Ratio, e.g., with the muscle layer up to 3.07 dB, a Signal-to-Mean Ratio of up to 20.78 dB and a Location Error of 1.58 mm. In multiple target detection, CR-DMAS outperformed other well established beamformers used in the context of breast MWI. Overall, this work provides new insights into the performance of algorithms in axillary MWI.

An Effective Framework for Deep-Learning-Enhanced Quantitative Microwave Imaging and Its Potential for Medical Applications.

Microwave imaging is emerging as an alternative modality to conventional medical diagnostics technologies. However, its adoption is hindered by the intrinsic difficulties faced in the solution of the underlying inverse scattering problem, namely non-linearity and ill-posedness. In this paper, an innovative approach for a reliable and automated solution of the inverse scattering problem is presented, which combines a qualitative imaging technique and deep learning in a two-step framework. In the first step, the orthogonality sampling method is employed to process measurements of the scattered field into an image, which explicitly provides an estimate of the targets shapes and implicitly encodes information in their contrast values. In the second step, the images obtained in the previous step are fed into a neural network (U-Net), whose duty is retrieving the exact shape of the target and its contrast value. This task is cast as an image segmentation one, where each pixel is classified into a discrete set of permittivity values within a given range. The use of a reduced number of possible permittivities facilitates the training stage by limiting its scope. The approach was tested with synthetic data and validated with experimental data taken from the Fresnel database to allow a fair comparison with the literature. Finally, its potential for biomedical imaging is demonstrated with a numerical example related to microwave brain stroke diagnosis.

A Simple Differential Microwave Imaging Approach for In-Line Inspection of Food Products.

Microwave imaging has been recently proposed as alternative technology for in-line inspection of packaged products in the food industry, thanks to its non-invasiveness and the low-cost of the equipment. In this framework, simple and effective detection/imaging strategies, able to reveal the presence of foreign bodies that may have contaminated the product during the packaging stage, are needed to allow real-time and reliable detection, thus avoiding delays along the production line and limiting occurrence of false detections (either negative or positive). In this work, a novel detection/imaging approach meeting these requirements is presented. The approach performs the detection/imaging of the contaminant by exploiting the symmetries usually characterizing the food items. Such symmetries are broken by the presence of foreign bodies, thereby determining a differential signal that can be processed to reveal their presence. In so doing, the approach does not require the prior measurement of a reference, defect-free, item. With respect to the quite common case of homogeneous food packaged in circular plastic/glass jars, numerical analyses are provided to show the effectiveness of the proposed approach.

Location of Early Stage Tumor Detection using Microwave Imaging in the Breast Phantom.

BACKGROUND: Universally, the most predominant cause of female mortality is mainly due to breast cancer. Owing to numerous constraints in the existing imaging technique, researchers are trying out an alternative tool to detect the tumor before going to the miserable stage. METHODS: This article presents a novel method to detect the mean value system for detecting the location of the tumor in different depths by shifting the antenna anywhere in the breast tissue. In addition, an algorithm to reconstruct the breast image, namely Delay-Multiply-and-Sum (DMAS) is followed to identify the tumor implanted in the breast tissue. RESULTS: The analysis shows that the maximum mean value occurs while the antenna moves very near to the tumor while the mean value reduces while the antenna shifts apart from the tumor location. The mean value in different locations is converted into a microwave image. The high intensity in the image exhibits the precise position of the tumor. This technique can identify the location of early-stage tumor of size 3mm. Multiple tumors of sizes 6mm and 7mm can identify at a depth of 12mm and 18mm in the homogeneous breast phantom. DMAS can provide better imaging results in the early stage tumor of size 3mm embedded in the breast phantom. CONCLUSION: Microwave imaging is an efficient technique to differentiate healthy and malignant tissue in the breast. Antenna plays a major role in identifying tumors in the breast in the early stage. Hence a high-performance Ultra Wideband Dielectric Resonator Antenna (DRA-UWB) is used to identify the tumor in the breast. An antenna is sketched in different locations of the breast phantom. On account of the hemispherical structure, the mean value of the reflected signal is high at the center than at the edge. Hence, the difference in mean value is calculated with and without breast phantom for identifying the tumor location. The overall efficiency of this technique can be improved by using a high-performance UWB antenna. The image of the breast is reformed by the DMAS beamforming algorithm.

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.

Real-Time 3D Microwave Medical Imaging With Enhanced Variational Born Iterative Method.

In this paper, we present a new variational Born iterative method (VBIM) for real-time microwave imaging (MWI) applications. The S-parameter volume integral equation and waveport vector Green's function are implemented to utilize the measured signal of the MWI system. Meanwhile, the real and imaginary separation (RIS) approach is used at each iterative step to simultaneously reconstruct the dielectric permittivity and conductivity of unknown objects. Compared with the Born iterative method and distorted Born iterative method, VBIM requires less computational time to reach the convergence threshold. The graphics processing unit based acceleration technique is implemented for real-time imaging. To demonstrate the efficiency and accuracy of this VBIM-RIS method, synthetic analysis of a complex multi-layer spherical phantom is first conducted. Then, the algorithm is tested with measured data using our new MWI system prototype. Finally, a synthetic brain-tumor phantom model under a thermal therapy procedure is monitored to exemplify the real-time imaging with about 5 seconds per reconstruction frame.

A Simple Microwave Imaging System for Food Product Inspection through a Symmetry-Based Microwave Imaging Approach.

In the food industry, there is a growing demand for cost-effective methods for the inline inspection of food items able to non-invasively detect small foreign bodies that may have contaminated the product during the production process. Microwave imaging may be a valid alternative to the existing technologies, thanks to its inherently low-cost and its capability of sensing low-density contaminants. In this paper, a simple microwave imaging system specifically designed to enable the inspection of a large variety of food products is presented. The system consists of two circularly loaded antipodal Vivaldi antennas with a very large operative band, from 1 to 15 GHz, thus allowing a suitable spatial resolution for different food products, from mostly fatty to high water-content foods. The antennas are arranged in such a way as to collect a signal that can be used to exploit a recently proposed real-time microwave imaging strategy, leveraging the inherent symmetries that usually characterize food items. The system is experimentally characterized, and the achieved results compare favorably with the design specifications and numerical simulations. Relying on these positive results, the first experimental proof of the effectiveness of the entire system is presented confirming its efficacy.

Modelling level I Axillary Lymph Nodes depth for Microwave Imaging.

PURPOSE: Patient-specific information on the depth of Axillary Lymph Nodes (ALNs) is important for the development of new diagnostic imaging technologies, e.g. Microwave Imaging (MWI), aiming to assess the diagnosis of ALNs during breast cancer staging. Studies about ALNs depth have been presented for treatment planning, but they lack information on sample size and usability of the data to infer the depth of ALNs. The aim of this study was to create a mathematical model that can be used to predict a depth interval where level I ALNs are likely to be located. METHODS: We extracted biometric features of 98 patients who underwent breast Magnetic Resonance Imaging (MRI) to train two types of regression models. We then tested different combination of features to predict ALNs depth and found the best predictor. The final prediction models were then implemented in an algorithm used for MWI and tested with anthropomorphic phantoms of the axillary region. RESULTS: Body Mass Index (BMI) was the feature with best performance to predict ALNs depth with coefficient of determination (R2) ranging from 0.49 to 0.55 and Root Mean Squared Error (RMSE) ranging from 0.68 to 0.91 cm. The proposed model showed satisfactory results in microwave images of patients with different BMIs. CONCLUSIONS: The presented results contribute to the development of reconstruction algorithms for new imaging technologies and to the assessment of ALNs in other medical applications.

Gradient Index Metasurface Lens for Microwave Imaging.

This paper presents the design, simulation and experimental validation of a gradient-index (GRIN) metasurface lens operating at 8 GHz for microwave imaging applications. The unit cell of the metasurface consists of an electric-LC (ELC) resonator. The effective refractive index of the metasurface is controlled by varying the capacitive gap at the center of the unit cell. This allows the design of a gradient index surface. A one-dimensional gradient index lens is designed and tested at first to describe the operational principle of such lenses. The design methodology is extended to a 2D gradient index lens for its potential application as a microwave imaging device. The metasurface lenses are designed and analyzed using full-wave finite element (FEM) solver. The proposed 2D lens has an aperture of size 119 mm (3.17λ) × 119 mm (3.17λ) and thickness of only 0.6 mm (0.016λ). Horn antenna is used as source of plane waves incident on the lens to evaluate the focusing performance. Field distributions of the theoretical designs and fabricated lenses are analyzed and are shown to be in good agreement. A microwave nondestructive evaluation (NDE) experiment is performed with the 2D prototype lens to image a machined groove in a Teflon sample placed at the focal plane of the lens.

Real-Time Detection and 3D Localization of Coronary Atherosclerosis Using a Microwave Imaging Technique: A Simulation Study.

Obtaining the exact position of accumulated calcium on the inner walls of coronary arteries is critical for successful angioplasty procedures. For the first time to our knowledge, in this work, we present a high accuracy imaging of the inner coronary artery using microwaves for precise calcium identification. Specifically, a cylindrical catheter radiating microwave signals is designed. The catheter has multiple dipole-like antennas placed around it to enable a 360° field-of-view around the catheter. In addition, to resolve image ambiguity, a metallic rod is inserted along the axis of the plastic catheter. The reconstructed images using data obtained from simulations show successful detection and 3D localization of the accumulated calcium on the inner walls of the coronary artery in the presence of blood flow. Considering the space and shape limitations, and the highly lossy biological tissue environment, the presented imaging approach is promising and offers a potential solution for accurate localization of coronary atherosclerosis during angioplasty or other related procedures.

Slotted Monopole Patch Antenna for Microwave-Based Head Imaging Applications.

A modified monopole patch antenna for microwave-based hemorrhagic or ischemic stroke recognition is presented in this article. The designed antenna is fabricated on a cost-effective FR-4 lossy material with a 0.02 loss tangent and 4.4 dielectric constant. Its overall dimensions are 0.32 λ × 0.28 λ × 0.007 λ, where λ is the lower bandwidth 1.3 GHz frequency wavelength. An inset feeding approach is utilized to feed the antenna to reduce the input impedance (z = voltage/current). A total bandwidth (below -10 dB) of 2.4 GHz (1.3-3.7 GHz) is achieved with an effective peak gain of over 6 dBi and an efficiency of over 90%. A time-domain analysis confirms that the antenna produces minimal signal distortion. Simulated and experimental findings share a lot of similarities. Brain tissue is penetrated by the antenna to a satisfactory degree, while still exhibiting a safe specific absorption rate (SAR). The maximum SAR value measured for the head model is constrained to be equal to or below 0.1409 W/kg over the entire usable frequency band. Evaluation of theoretical and experimental evidence indicates the intended antenna is appropriate for Microwave Imaging (MWI) applications.

Impact of Skin on Microwave Tomography in the Lossy Coupling Medium.

In microwave imaging, the effects of skin on recovering property distributions of tissue underneath the surface may be significant because it has high dielectric contrast with subcutaneous fat, which inevitably causes significant signal reflections. While the thickness of skin, especially relative to the wavelengths in use, would presumably have minor effects, it can introduce practical difficulties, for instance, in reflection-based imaging techniques, where the impact of the skin is large-often as high as two orders of magnitude greater than that of signals from underlying tumors in the breast imaging setting. However, in tomography cases utilizing transmission-based measurement data and lossy coupling materials, the situation is considerably different. Accurately implementing a skin layer for numerical modeling purposes is challenging because of the need to discretize the size and shape of the skin without increasing computational overhead substantially. In this paper, we assess the effects of the skin on field solutions in a realistic 3D model of a human breast. We demonstrate that the small changes in transmission field values introduced by including the skin cause minor differences in reconstructed images.