Compound Radar Approach for Breast Imaging

Review and Analysis of Tumour Detection and Image Quality Analysis in Experimental Breast Microwave Sensing

This review evaluates the methods used for image quality analysis and tumour detection in experimental breast microwave sensing (BMS), a developing technology being investigated for breast cancer detection. This article examines the methods used for image quality analysis and the estimated diagnostic performance of BMS for image-based and machine-learning tumour detection approaches. The majority of image analysis performed in BMS has been qualitative and existing quantitative image quality metrics aim to describe image contrast-other aspects of image quality have not been addressed. Image-based diagnostic sensitivities between 63 and 100% have been achieved in eleven trials, but only four articles have estimated the specificity of BMS. The estimates range from 20 to 65%, and do not demonstrate the clinical utility of the modality. Despite over two decades of research in BMS, significant challenges remain that limit the development of this modality as a clinical tool. The BMS community should utilize consistent image quality metric definitions and include image resolution, noise, and artifacts in their analyses. Future work should include more robust metrics, estimates of the diagnostic specificity of the modality, and machine-learning applications should be used with more diverse datasets and with robust methodologies to further enhance BMS as a viable clinical technique.

Assessing Patient-Specific Microwave Breast Imaging in Clinical Case Studies

Microwave breast imaging has seen increasing use in clinical investigations in the past decade with over eight systems having being trialled with patients. The majority of systems use radar-based algorithms to reconstruct the image shown to the clinician which requires an estimate of the dielectric properties of the breast to synthetically focus signals to reconstruct the image. Both simulated and experimental studies have shown that, even in simplified scenarios, misestimation of the dielectric properties can impair both the image quality and tumour detection. Many methods have been proposed to address the issue of the estimation of dielectric properties, but few have been tested with patient images. In this work, a leading approach for dielectric properties estimation based on the computation of many candidate images for microwave breast imaging is analysed with patient images for the first time. Using five clinical case studies of both healthy breasts and breasts with abnormalities, the advantages and disadvantages of computational patient-specific microwave breast image reconstruction are highlighted.

Existing and Emerging Breast Cancer Detection Technologies and Its Challenges: A Review

Breast cancer is the most leading cancer occurring in women and is a significant factor in female mortality. Early diagnosis of breast cancer with Artificial Intelligent (AI) developments for breast cancer detection can lead to a proper treatment to affected patients as early as possible that eventually help reduce the women mortality rate. Reliability issues limit the current clinical detection techniques, such as Ultra-Sound, Mammography, and Magnetic Resonance Imaging (MRI) from screening images for precise elucidation. The capability to detect a tumor in early diagnosis, expensive, relatively long waiting time due to pandemic and painful procedure for a patient to perform. This article aims to review breast cancer screening methods and recent technological advancements systematically. In addition, this paper intends to explore the progression and challenges of AI in breast cancer detection. The next state of the art between image and signal processing will be presented, and their performance is compared. This review will facilitate the researcher to insight the view of breast cancer detection technologies advancement and its challenges.

Noninvasive and portable stroke type discrimination and progress monitoring based on a multichannel microwave transmitting-receiving system

The hemorrhagic and the ischemic types of stroke have similar symptoms in the early stage, but their treatments are completely different. The timely and effective discrimination of the two types of stroke can considerable improve the patients' prognosis. In this paper, a 16-channel and noncontact microwave-based stroke detection system was proposed and demonstrated for the potential differentiation of the hemorrhagic and the ischemic stroke. In animal experiments, 10 rabbits were divided into two groups. One group consisted of five cerebral hemorrhage models, and the other group consisted of five cerebral ischemia models. The two groups were monitored by the system to obtain the Euclidean distance transform value of microwave scattering parameters caused by pathological changes in the brain. The support vector machine was used to identify the type and the severity of the stroke. Based on the experiment, a discrimination accuracy of 96% between hemorrhage and ischemia stroke was achieved. Furthermore, the potential of monitoring the progress of intracerebral hemorrhage or ischemia was evaluated. The discrimination of different degrees of intracerebral hemorrhage achieved 86.7% accuracy, and the discrimination of different severities of ischemia achieved 94% accuracy. Compared with that with multiple channels, the discrimination accuracy of the stroke severity with a single channel was only 50% for the intracerebral hemorrhage and ischemia stroke. The study showed that the microwave-based stroke detection system can effectively distinguish between the cerebral hemorrhage and the cerebral ischemia models. This system is very promising for the prehospital identification of the stroke type due to its low cost, noninvasiveness, and ease of operation.

Microwave Breast Imaging Using Rotational Bistatic Impulse Radar for the Detection of Breast Cancer: Protocol for a Prospective Diagnostic Study

Background

Mammography is the standard examination for breast cancer screening; however, it is associated with pain and exposure to ionizing radiation. Microwave breast imaging is a less invasive method for breast cancer surveillance. A bistatic impulse radar–based breast cancer detector has recently been developed.

Objective

This study aims to present a protocol for evaluating the diagnostic accuracy of the novel microwave breast imaging device.

Methods

This is a prospective diagnostic study. A total of 120 participants were recruited before treatment administration and divided into 2 cohorts: 100 patients diagnosed with breast cancer and 20 participants with benign breast tumors. The detector will be directly placed on each breast, while the participant is in supine position, without a coupling medium. Confocal images will be created based on the analyzed data, and the presence of breast tumors will be assessed. The primary endpoint will be the diagnostic accuracy, sensitivity, and specificity of the detector for breast cancer and benign tumors. The secondary endpoint will be the safety and detectability of each molecular subtype of breast cancer. For an exploratory endpoint, the influence of breast density and tumor size on tumor detection will be investigated.

Results

Recruitment began in November 2018 and was completed by March 2020. We anticipate the preliminary results to be available by summer 2021.

Conclusions

This study will provide insights on the diagnostic accuracy of microwave breast imaging using a rotational bistatic impulse radar. The collected data will improve the diagnostic algorithm of microwave imaging and lead to enhanced device performance.

Trial Registration

Japan Registry of Clinical Trials jRCTs062180005; https://jrct.niph.go.jp/en-latest-detail/jRCTs062180005

International Registered Report Identifier (IRRID)

DERR1-10.2196/17524

Use of multi-angle ultra-wide band microwave sounding for high resolution breast imaging

PURPOSE

This report proposes an approach to develop a method of microwave imaging for early, non-invasive diagnosis of breast tumors. Here we describe a data-processing method for obtaining radio images of biological heterogeneities and a new method for filtering static noise in received signals.

METHODS

A specialized radar system was developed in the present study and used to perform sounding of synthetic phantoms with the dielectric properties of breast tissue in the range of 2-8 GHz. Datasets thus contained synthetic structures that imitated the dielectric properties of breast tissues and tumors. The permittivity values of the created artificial materials were verified using a waveguide cell. Tumors were simulated via plastic balls with a diameter of 1 cm that were filled with saline. A special ultra-wide band (UWB) radar system developed at Tomsk State University was used to register radar responses from the phantoms. The radar system included the vector reflectometer, the UWB antenna, and the mechanical scanner that provided sounding in the hemisphere. We also used the time-domain signals processing method to obtain the radio image signals. In this method, all signals received during scanning in the hemisphere are added with calculated delay for the given focus point. Special filtering of the constant components of the signal at each of the angular sounding latitudes was used to eliminate clutter in the received signal. This solution allowed us to account for additive clutter in the received signal from structural elements during scanning in the hemisphere. The influence of the number of angles on the quality of the resulting radio image was evaluated.

RESULTS

The phantoms of a female breast and a malignant tumor from artificial materials with electrophysical characteristics close to those of real tissues have been developed. This facilitated verification of the proposed method for constructing radio images under more clinically relevant conditions. The proposed filtering of the constant components of the signal effectively doubled the signal-to-noise ratio in the resulting radio image compared with the standard algorithm of clutter filtering. The influence of different numbers of scan points on the quality of the final radio image are presented herein. It is concluded that it is sufficient to use not more than 600-800 sounding points for acceptable image quality. A further increase in the number of angles does not significantly improve image quality despite increasing the scan time.

CONCLUSIONS

Scanning in the hemisphere of the breast phantom using the proposed method of clutter filtering show that multi-angle microwave imaging can form accurate three-dimensional (3D) images with double the level of signal-to-clutter compared with the standard filtering approach. The images of artificial tumors were obtained when sounding in the range of 2-8 GHz with the resolution of about 5-7 mm.

Development of an Anthropomorphic Phantom of the Axillary Region for Microwave Imaging Assessment

We produced an anatomically and dielectrically realistic phantom of the axillary region to enable the experimental assessment of Axillary Lymph Node (ALN) imaging using microwave imaging technology. We segmented a thoracic Computed Tomography (CT) scan and created a computer-aided designed file containing the anatomical configuration of the axillary region. The phantom comprises five 3D-printed parts representing the main tissues of interest of the axillary region for the purpose of microwave imaging: fat, muscle, bone, ALNs, and lung. The phantom allows the experimental assessment of multiple anatomical configurations, by including ALNs of different size, shape, and number in several locations. Except for the bone mimicking organ, which is made of solid conductive polymer, we 3D-printed cavities to represent the fat, muscle, ALN, and lung and filled them with appropriate tissue-mimicking liquids. Existing studies about complex permittivity of ALNs have reported limitations. To address these, we measured the complex permittivity of both human and animal lymph nodes using the standard open-ended coaxial-probe technique, over the 0.5 GHz–8.5 GHz frequency band, thus extending current knowledge on dielectric properties of ALNs. Lastly, we numerically evaluated the effect of the polymer which constitutes the cavities of the phantom and compared it to the realistic axillary region. The results showed a maximum difference of 7 dB at 4 GHz in the electric field magnitude coupled to the tissues and a maximum of 10 dB difference in the ALN response. Our results showed that the phantom is a good representation of the axillary region and a viable tool for pre-clinical assessment of microwave imaging technology.

3D printed PLA/copper bowtie antenna for biomedical imaging applications

This study aims to increase the performance of the microwave antenna by using 3D printed conductive substrates, which is mainly used in biomedical imaging applications. Conventional antennas such as Horn and Vivaldi have coarse dimensions to integrate into the microwave imaging systems. Therefore, 3D printed Bowtie antenna structures were developed, which yield low cost and smaller sizes. PLA, PLA/copper, and PLA/carbon substrates were produced with a 3D printer. These materials were tested in terms of their dielectric constants between 1 and 10 GHz. The conductive part of the antenna was copper, with a thickness of 0.8 mm, which was embedded in the substrate parts. The reflection coefficients of the antennas were tested within 0-3 GHz frequency range via miniVNA network analyzer. The results show that the 3D printed PLA/copper and PLA/carbon antenna are highly suitable for the usage in biomedical imaging systems.

Review of Microwaves Techniques for Breast Cancer Detection

Conventional breast cancer detection techniques including X-ray mammography, magnetic resonance imaging, and ultrasound scanning suffer from shortcomings such as excessive cost, harmful radiation, and inconveniences to the patients. These challenges motivated researchers to investigate alternative methods including the use of microwaves. This article focuses on reviewing the background of microwave techniques for breast tumour detection. In particular, this study reviews the recent advancements in active microwave imaging, namely microwave tomography and radar-based techniques. The main objective of this paper is to provide researchers and physicians with an overview of the principles, techniques, and fundamental challenges associated with microwave imaging for breast cancer detection. Furthermore, this study aims to shed light on the fact that until today, there are very few commercially available and cost-effective microwave-based systems for breast cancer imaging or detection. This conclusion is not intended to imply the inefficacy of microwaves for breast cancer detection, but rather to encourage a healthy debate on why a commercially available system has yet to be made available despite almost 30 years of intensive research.

A 4-channel, vector network analyzer microwave imaging prototype based on software defined radio technology

We have implemented a prototype 4-channel transmission-based, microwave measurement system built on innovative software defined radio (SDR) technology. The system utilizes the B210 USRP SDR developed by Ettus Research that operates over a 70 MHz-6 GHz bandwidth. While B210 units are capable of being synchronized with each other via coherent reference signals, they are somewhat unreliable in this configuration and the manufacturer recommends using N200 or N210 models instead. For our system, N-series SDRs were less suitable because they are not amenable to RF shielding required for the cross-channel isolation necessary for an integrated microwave imaging system. Consequently, we have configured an external reference that overcame these limitations in a compact and robust package. Our design exploits the rapidly evolving technology being developed for the telecommunications environment for test and measurement tasks with the higher performance specifications required in medical microwave imaging applications. In a larger channel configuration, the approach is expected to provide performance comparable to commercial vector network analyzers at a fraction of the cost and in a more compact footprint.

Anthropomorphic breast model repository for research and development of microwave breast imaging technologies

A repository of anthropomorphic numerical breast models is made available for the scientific community to support research and development of microwave imaging technologies for diagnostic and therapeutic applications. These models are constructed from magnetic resonance imaging (MRI) scans acquired at our university hospital. Our 3D breast modelling method is used to translate the MRI scans into 3D models representing the geometry and microwave-frequency properties of tissues in the breast. The reconstructed models demonstrate anatomical realism, reconfigurable complexity, and flexibility to adapt to simulations of various microwave imaging techniques and prototype systems. With these models, realistic and rigorous test scenarios can be defined in simulations to support feasibility analysis, performance verification and design improvements of developing microwave imaging techniques, prior to testing on experimental systems. A repository of breast models is created which includes breasts of varying classification - fatty, scattered, heterogeneous, and dense. In addition, the models include brief documentation to facilitate researchers in selecting a model by matching its features with their requirements.

Portable impulse-radar detector for breast cancer: a pilot study

Microwave breast imaging is a painless and nonradiation method. This pilot study aimed to evaluate the detective capability and feasibility of a prototype of a portable breast cancer detector using a radar-based imaging system. Five patients with histologically confirmed breast cancers with a minimum diameter of 1 cm were enrolled in this study. The antenna array dome of the device was placed on the breast of the patient in a supine position for 15 min per single examination. The primary endpoint was a detection rate of breast cancers. The secondary endpoints were positional accuracy and adverse event. All five targeted breast tumors were detected and were visualized at the sites confirmed by other diagnostic modalities. Among five tumors, one was not detected via mammography because of heterogeneously dense breast and another was a microinvasive carcinoma of invasive tumor size 0.5 mm. No study-related adverse events occurred. The prototype of a portable breast cancer detector has sufficient detective capability, is safe for clinical use, and might detect an early stage breast cancer, such as noninvasive carcinoma. Future developments should focus on further decreasing the size of the machine and shortening inspection time.

Parameter Search Algorithms for Microwave Radar-Based Breast Imaging: Focal Quality Metrics as Fitness Functions

Inaccurate estimation of average dielectric properties can have a tangible impact on microwave radar-based breast images. Despite this, recent patient imaging studies have used a fixed estimate although this is known to vary from patient to patient. Parameter search algorithms are a promising technique for estimating the average dielectric properties from the reconstructed microwave images themselves without additional hardware. In this work, qualities of accurately reconstructed images are identified from point spread functions. As the qualities of accurately reconstructed microwave images are similar to the qualities of focused microscopic and photographic images, this work proposes the use of focal quality metrics for average dielectric property estimation. The robustness of the parameter search is evaluated using experimental dielectrically heterogeneous phantoms on the three-dimensional volumetric image. Based on a very broad initial estimate of the average dielectric properties, this paper shows how these metrics can be used as suitable fitness functions in parameter search algorithms to reconstruct clear and focused microwave radar images.