Mapping breast tissue types by miniature radio-frequency near-field spectroscopy sensor in ex-vivo freshly excised specimens

Kaufman, Z; Paran, Haim; Haas, Ilana; Malinger, Patricia; Zehavi, Tania; Karni, Tamar; Pappo, Izhak; Sandbank, Judith; Diment, Judith; Allweis, Tanir

doi:10.1186/s12880-016-0160-x

Cited by 14 publications

(10 citation statements)

References 34 publications

(32 reference statements)

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“…showed that contrast in microwave frequency dielectric properties between malignant and normal adipose‐dominated tissues in the breast is considerable, as large as 10:1, but no benign breast lesions were compared . Previous studies have shown differences in the electrical properties of malignant and benign breast epithelial cells, and that both permittivity and conductivity of breast cancer are significantly higher than those of normal tissues . The values of these properties correlate with frequency, and provide a basis for investigating the mechanisms that underlie malignancy, including cellular proliferation, cytoskeleton, and metabolism.…”

Section: Discussionmentioning

confidence: 99%

Dielectric properties for non‐invasive detection of normal, benign, and malignant breast tissues using microwave theories

Cheng

2018

Thoracic Cancer

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BackgroundDespite the high incidence of breast cancer worldwide, methods for early non‐invasive diagnosis and sensitive and specific prognostic evaluation remain difficult. In this study, we investigated microwave parameters as a potential non‐invasive approach to detect breast cancer.MethodsSamples of freshly excised breast tissues (n = 509) from 98 patients were identified as normal, benign tumor, or malignant cancer via histology. Further samples were prepared and the microwave effective dielectric permittivity and effective conductivity were measured every 0.0375 GHz from 0.5 GHz to 8 GHz. These parameters were compared among the breast tissue types.ResultsThe effective relative permittivity and effective conductivity at each frequency was significantly higher in breast cancer tissues compared with benign tumors, which in turn was significantly higher than in normal breast tissue. The standard deviation of each parameter was narrowest at ~2.5 GHz in both normal and malignant breast tissues.ConclusionsThe effective dielectric permittivity and effective conductivity, measured via microwave technology, could differentiate breast cancer from normal and benign tumor tissues.

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Section: Discussionmentioning

confidence: 99%

Dielectric properties for non‐invasive detection of normal, benign, and malignant breast tissues using microwave theories

Cheng

2018

Thoracic Cancer

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“…Our results compare favorably to existing margin assessment methods. RF spectroscopy, which has been shown to reduce the re-excision rate in breast-conserving surgery in two studies [16,17], has shown comparable performance in detection of benign breast tissue and carcinoma with a sensitivity and specificity of 90% and 91%, respectively [30]. RF spectroscopy can cover an area large enough to be practical but can currently only be performed ex vivo, leading to challenges of accurate orientation of the resected tumor.…”

Section: Discussionmentioning

confidence: 99%

Identification of breast tumors from diathermy smoke by differential ion mobility spectrometry

Sutinen

Kontunen

Karjalainen

et al. 2019

European Journal of Surgical Oncology

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Introduction: Breast cancer is the most frequent cancer in women worldwide. The primary treatment is breast-conserving surgery or mastectomy with an adequate clearance margin. Diathermy blade is used extensively in breast-conserving surgery. Surgical smoke produced as a side product has cancerspecific molecular features. Differential mobility spectrometry (DMS) is a rapid and affordable technology for analysis of complex gas mixtures. In our study we examined surgical smoke from malignant and benign breast tissue created with a diathermy blade using DMS. Material and methods: Punch biopsies of 4 mm diameter from breast cancer surgical specimens were taken during gross dissection of fresh surgical specimen and placed in a well plate. The measurement system is a custom-built device called automatic tissue analysis system (ATAS) based on a DMS sensor. Each specimen was incised with a diathermy blade and the surgical smoke was analyzed. Results: We examined 106 carcinoma samples from 21 malignant breast tumors. Benign samples (n = 198) included macroscopically normal mammary gland (n = 82), adipose tissue (n = 88) and vascular tissue (n = 28). The classification accuracy when comparing malignant samples to all benign samples was 87%. The sensitivity was 80% and the specificity was 90%. The classification accuracy of carcinomas to ductal and lobular was 94%, 47%, respectively. Conclusions: Benign and malignant breast tissue can be identified with ATAS. These results lay foundation for intraoperative margin assessment with DMS from surgical smoke.

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“…For these applications, there is usually a significant endogenous contrast that can be exploited for imaging. For breast cancer imaging, there is a substantial property contrast between benign and malignant tissue [ 8 , 9 , 10 ]; for stroke diagnosis, there is a large contrast between blood and normal brain tissue [ 11 ]; for bone, there is a significant correlation between the dielectric properties and bone density [ 7 ]. In addition, the dielectric properties can be exploited to recover functional information such as temperature monitoring during thermal therapy [ 12 , 13 ] due to their temperature dependence [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

Expansion of the Nodal-Adjoint Method for Simple and Efficient Computation of the 2D Tomographic Imaging Jacobian Matrix

Hosseinzadegan

Fhager

Geimer

et al. 2021

Sensors

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This paper focuses on the construction of the Jacobian matrix required in tomographic reconstruction algorithms. In microwave tomography, computing the forward solutions during the iterative reconstruction process impacts the accuracy and computational efficiency. Towards this end, we have applied the discrete dipole approximation for the forward solutions with significant time savings. However, while we have discovered that the imaging problem configuration can dramatically impact the computation time required for the forward solver, it can be equally beneficial in constructing the Jacobian matrix calculated in iterative image reconstruction algorithms. Key to this implementation, we propose to use the same simulation grid for both the forward and imaging domain discretizations for the discrete dipole approximation solutions and report in detail the theoretical aspects for this localization. In this way, the computational cost of the nodal adjoint method decreases by several orders of magnitude. Our investigations show that this expansion is a significant enhancement compared to previous implementations and results in a rapid calculation of the Jacobian matrix with a high level of accuracy. The discrete dipole approximation and the newly efficient Jacobian matrices are effectively implemented to produce quantitative images of the simplified breast phantom from the microwave imaging system.

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Mapping breast tissue types by miniature radio-frequency near-field spectroscopy sensor in ex-vivo freshly excised specimens

Cited by 14 publications

References 34 publications

Dielectric properties for non‐invasive detection of normal, benign, and malignant breast tissues using microwave theories

Dielectric properties for non‐invasive detection of normal, benign, and malignant breast tissues using microwave theories

Identification of breast tumors from diathermy smoke by differential ion mobility spectrometry

Expansion of the Nodal-Adjoint Method for Simple and Efficient Computation of the 2D Tomographic Imaging Jacobian Matrix

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