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Song H, Sasada S, Kadoya T, Arihiro K, Okada M, Xiao X, Ishikawa T, O'Loughlin D, Takada JI, Kikkawa T. Cross-Correlation of Confocal Images for Excised Breast Tissues of Total Mastectomy. IEEE Trans Biomed Eng 2024; 71:1705-1716. [PMID: 38163303 DOI: 10.1109/tbme.2023.3348480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
OBJECT The purpose of this study is to develop an image artifact removal method for radar-based microwave breast imaging and demonstrates the detectability on excised breast tissues of total mastectomy. METHODS A cross-correlation method was proposed and measurements were conducted. A hand-held radar-based breast cancer detector was utilized to measure a breast at different orientations. Images were generated by multiplying the confocal image data from two scans after cross-correlation. The optimum reconstruction permittivity values were extracted by the local maxima of the confocal image intensity as a function of reconstruction permittivity. RESULTS With the proposed cross-correlation method, the contrast of the imaging result was enhanced and the clutters were removed. The proposed method was applied to 50 cases of excised breast tissues and the detection sensitivity of 72% was achieved. With the limited number of samples, the dependency of detection sensitivity on the breast size, breast density, and tumor size were examined. CONCLUSION AND SIGNIFICANCE The detection sensitivity was strongly influenced by the breast density. The sensitivity was high for fatty breasts, whereas the sensitivity was low for heterogeneously dense breasts. In addition, it was observed that the sensitivity was high for extremely dense breast. This is the first detailed report on the excised breast tissues.
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Gupta A, Kumar V, Garg D, Alsharif MH, Jahid A. Performance Analysis of an Aperture-Coupled THz Antenna for Diagnosing Breast Cancer. Micromachines (Basel) 2023; 14:1281. [PMID: 37512593 PMCID: PMC10384160 DOI: 10.3390/mi14071281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 06/11/2023] [Accepted: 06/20/2023] [Indexed: 07/30/2023]
Abstract
The most important technique for exposing early-stage breast cancer is terahertz imaging. It aids in lowering the number of breast cancer-related fatalities and enhancing the quality of life. An essential component of developing the THz imaging system for high-quality photos is choosing the right sensor. In this article, a wideband antenna for microwave imaging of breast tissue with an operating frequency of 30 GHz (107 GHz to 137 GHz) is constructed and analyzed. An aperture-coupled antenna with an optimized ground aperture is proposed and analyzed, which made it possible to obtain better and consistent impedance matching in the wideband spectrum. The variation of backscattered signal energy in body tissue is assessed with healthy breast tissue and in the presence of malignant cells. A significant difference in energy scattering is observed for both situations. The suggested antenna's linear and stable time domain characteristics make it an appropriate component for THz imaging technology.
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Affiliation(s)
- Anupma Gupta
- Department of Interdisciplinary Courses in Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, India
| | - Vipan Kumar
- Department of Electronics and Communication Engineering, Sri Sai College of Engineering and Technology, Pathankot 145001, India
| | - Dinesh Garg
- Department of Computer Science Engineering, Sri Sai College of Engineering and Technology, Pathankot 145001, India
| | - Mohammed H Alsharif
- Department of Electrical Engineering, College of Electronics and Information Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Republic of Korea
| | - Abu Jahid
- School of Electrical Engineering and Computer Science, University of Ottawa, 25 Templeton St., Ottawa, ON K1N 6N5, Canada
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Reimer T, Pistorius S. Review and Analysis of Tumour Detection and Image Quality Analysis in Experimental Breast Microwave Sensing. Sensors (Basel) 2023; 23:s23115123. [PMID: 37299852 DOI: 10.3390/s23115123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 05/12/2023] [Accepted: 05/24/2023] [Indexed: 06/12/2023]
Abstract
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.
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Affiliation(s)
- Tyson Reimer
- Department of Physics & Astronomy, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
| | - Stephen Pistorius
- Department of Physics & Astronomy, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
- CancerCare Manitoba Research Institute, Winnipeg, MB R3E 0V9, Canada
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O'Loughlin D, Elahi MA, Lavoie BR, Fear EC, O'Halloran M. Assessing Patient-Specific Microwave Breast Imaging in Clinical Case Studies. Sensors (Basel) 2021; 21:8048. [PMID: 34884050 DOI: 10.3390/s21238048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 11/19/2021] [Accepted: 11/26/2021] [Indexed: 11/25/2022]
Abstract
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.
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Naghibi A, Attari AR. Enhancing image quality of single-frequency microwave imaging with a multistatic full-view array based on sidelobe reduction. Opt Express 2021; 29:22479-22493. [PMID: 34266010 DOI: 10.1364/oe.424508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 04/14/2021] [Indexed: 06/13/2023]
Abstract
Single-frequency microwave imaging can be effectively realized with multistatic full-view arrays, offering great potential in various sensing applications. In this paper, we address the problem of forming high quality images with the focus on multistatic full-view arrays. We aim to enhance its image quality by means of reducing the side-lobe level (SLL) of the imaging array. K-space representation and PSF analysis are presented to get an insight into the effect of low spatial frequency samples collected by the array on the side-lobe response of the array. Based on this understanding, a novel SLL reduction method is proposed based on weakening the effect of low spatial frequency samples. A modified back-projection algorithm is suggested to apply the proposed SLL reduction method in image reconstruction. Numerical simulations confirm a reduction of about 5 dB in side-lobe level. The functionality of the proposed method is verified by using the experimental measurement data of two different targets. Image quality is enhanced by 3.5 and 4.5 dB in terms of signal-to-mean ratio (SMR) for the two studied targets. This considerable improvement has resulted in avoiding appearance of artifacts and wrong interpretations of the target under imaging. The proposed method can be beneficial for existing imaging systems that utilize a full-view multistatic array, from medical to industrial applications.
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Prokhorova A, Ley S, Helbig M. Quantitative Interpretation of UWB Radar Images for Non-Invasive Tissue Temperature Estimation during Hyperthermia. Diagnostics (Basel) 2021; 11:diagnostics11050818. [PMID: 33946581 PMCID: PMC8147219 DOI: 10.3390/diagnostics11050818] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 04/16/2021] [Accepted: 04/28/2021] [Indexed: 12/26/2022] Open
Abstract
The knowledge of temperature distribution inside the tissue to be treated is essential for patient safety, workflow and clinical outcomes of thermal therapies. Microwave imaging represents a promising approach for non-invasive tissue temperature monitoring during hyperthermia treatment. In the present paper, a methodology for quantitative non-invasive tissue temperature estimation based on ultra-wideband (UWB) radar imaging in the microwave frequency range is described. The capabilities of the proposed method are demonstrated by experiments with liquid phantoms and three-dimensional (3D) Delay-and-Sum beamforming algorithms. The results of our investigation show that the methodology can be applied for detection and estimation of the temperature induced dielectric properties change.
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Amin B, Shahzad A, O’Halloran M, Elahi MA. Microwave Bone Imaging: A Preliminary Investigation on Numerical Bone Phantoms for Bone Health Monitoring. Sensors (Basel) 2020; 20:E6320. [PMID: 33167562 PMCID: PMC7664235 DOI: 10.3390/s20216320] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 10/31/2020] [Accepted: 11/03/2020] [Indexed: 11/30/2022]
Abstract
Microwave tomography (MWT) can be used as an alternative modality for monitoring human bone health. Studies have found a significant dielectric contrast between healthy and diseased human trabecular bones. A set of diverse bone phantoms were developed based on single-pole Debye parameters of osteoporotic and osteoarthritis human trabecular bones. The bone phantoms were designed as a two-layered circular structure, where the outer layer mimics the dielectric properties of the cortical bone and the inner layer mimics the dielectric properties of the trabecular bone. The electromagnetic (EM) inverse scattering problem was solved using a distorted Born iterative method (DBIM). A compressed sensing-based linear inversion approach referred to as iterative method with adaptive thresholding for compressed sensing (IMATCS) has been employed for solving the underdetermined set of linear equations at each DBIM iteration. To overcome the challenges posed by the ill-posedness of the EM inverse scattering problem, the L2-based regularization approach was adopted in the amalgamation of the IMATCS approach. The simulation results showed that osteoporotic and osteoarthritis bones can be differentiated based on the reconstructed dielectric properties even for low values of the signal-to-noise ratio. These results show that the adopted approach can be used to monitor bone health based on the reconstructed dielectric properties.
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Affiliation(s)
- Bilal Amin
- Electrical and Electronic Engineering, National University of Ireland Galway, H91 TK33 Galway, Ireland; (M.O.); (M.A.E.)
- Translational Medical Device Lab, National University of Ireland Galway, H91 TK33 Galway, Ireland
| | - Atif Shahzad
- School of Medicine, National University of Ireland Galway, H91 TK33 Galway, Ireland;
| | - Martin O’Halloran
- Electrical and Electronic Engineering, National University of Ireland Galway, H91 TK33 Galway, Ireland; (M.O.); (M.A.E.)
- Translational Medical Device Lab, National University of Ireland Galway, H91 TK33 Galway, Ireland
| | - Muhammad Adnan Elahi
- Electrical and Electronic Engineering, National University of Ireland Galway, H91 TK33 Galway, Ireland; (M.O.); (M.A.E.)
- Translational Medical Device Lab, National University of Ireland Galway, H91 TK33 Galway, Ireland
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O’Loughlin D, Oliveira BL, Glavin M, Jones E, O’Halloran M. Comparing Radar-Based Breast Imaging Algorithm Performance with Realistic Patient-Specific Permittivity Estimation. J Imaging 2019; 5:jimaging5110087. [PMID: 34460510 PMCID: PMC8321188 DOI: 10.3390/jimaging5110087] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 10/25/2019] [Accepted: 11/11/2019] [Indexed: 12/28/2022] Open
Abstract
Radar-based breast imaging has shown promise as an imaging modality for early-stage cancer detection, and clinical investigations of two commercial imaging systems are ongoing. Many imaging algorithms have been proposed, which seek to improve the quality of the reconstructed microwave image to enhance the potential clinical decision. However, in many cases, the radar-based imaging algorithms have only been tested in limited numerical or experimental test cases or with simplifying assumptions such as using one estimate of permittivity for all patient test cases. In this work, the potential impact of patient-specific permittivity estimation on algorithm comparison is highlighted using representative experimental breast phantoms. In particular, the case studies presented help show that the permittivity estimate can impact the conclusions of the algorithm comparison. Overall, this work suggests that it is important that imaging algorithm comparisons use realistic test cases with and without breast abnormalities and with reconstruction permittivity estimation.
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O'Loughlin D, Oliveira BL, Santorelli A, Porter E, Glavin M, Jones E, Popovic M, O'Halloran M. Sensitivity and Specificity Estimation Using Patient-Specific Microwave Imaging in Diverse Experimental Breast Phantoms. IEEE Trans Med Imaging 2019; 38:303-311. [PMID: 30106675 DOI: 10.1109/tmi.2018.2864150] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Many new clinical investigations of microwave breast imaging have been published in recent years. Trials with over one hundred participants have indicated the potential of microwave imaging to detect breast cancer, with particularly encouraging sensitivity results reported from women with dense breasts. The next phase of clinical trials will involve larger and more diverse populations, including women with no breast abnormalities or benign breast diseases. These trials will need to address clinical efficacy in terms of sensitivity and specificity. A number of challenges exist when using microwave imaging with broad populations: 1) addressing the substantial variance in breast composition observed in the population and 2) achieving high specificity given differences between individuals. This paper analyses these challenges using a diverse phantom set which models the variance in breast composition and tumor shape and size seen in the population. The data show that the sensitivity of microwave breast imaging in breasts of differing density can suffer if patient-specific beamforming is not used. Moreover, the results suggest that achieving high specificity in dense breasts may be difficult, but that patient-specific beamforming does not adversely affect the expected specificity. In summary, this paper finds that patient-specific beamforming has a tangible impact on expected sensitivity in experimental cases and that achieving high specificity in dense breasts may be challenging.
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Song H, Sasada S, Masumoto N, Kadoya T, Shiroma N, Orita M, Arihiro K, Okada M, Kikkawa T. Detectability of Breast Tumors in Excised Breast Tissues of Total Mastectomy by IR-UWB-Radar-Based Breast Cancer Detector. IEEE Trans Biomed Eng 2018; 66:2296-2305. [PMID: 30571614 DOI: 10.1109/tbme.2018.2887083] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
The objective of this paper is to investigate the detectability of breast tumors having various histological types in excised breast tissues of total mastectomy. The tumor images measured by a portable impulse-radio-ultra-wideband (IR-UWB)-radar-based breast cancer detector are compared with both pathological images and images of dedicated breast positron emission tomography. It is found that the detector can detect invasive-ductal-carcinomas and extensive intraductal component in the dense breast. The density of the breast has a correlation to the effective permittivity derived from the reconstructed confocal images. The results show that the IR-UWB-radar-based breast cancer detector has a potential as a portable modality for early-stage breast cancer screening.
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O'loughlin D, O'halloran M, Moloney BM, Glavin M, Jones E, Elahi MA. Microwave Breast Imaging: Clinical Advances and Remaining Challenges. IEEE Trans Biomed Eng 2018; 65:2580-90. [DOI: 10.1109/tbme.2018.2809541] [Citation(s) in RCA: 131] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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OrLoughlin D, Barbara Oliveira L, Glavin M, Jones E, OrHalloran M. Effects of Interpatient Variance on Microwave Breast Images: Experimental Evaluation. Annu Int Conf IEEE Eng Med Biol Soc 2018; 2018:5660-5663. [PMID: 30441620 DOI: 10.1109/embc.2018.8513673] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Microwave breast imaging has seen significant developments in recent years, including new clinical trials and formation of a number of spin-out companies. Although many algorithms for microwave breast imaging have been developed, there are significant challenges in translating these algorithms to the clinic. For example, movement due to patient breathing can affect the scan, and both the breast and breast abnormalities vary significantly from patient to patient. As breast density is a known independent risk factor for cancer and cancerous tumours have different shapes and margins to benign tumours, the effect of interpatient variance on the microwave image is important. This work analyses the effect on image quality of tumour shape, size and breast density. Using the diverse and representative BRIGID experimental dataset, images of a variety of tumours are compared to images without tumours present. This work suggests that it is difficult to distinguish images with and without tumours present using existing metrics.
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