Properties Of Normal Breast Tissues Research Articles

Nanoindentation study of the viscoelastic properties of human triple negative breast cancer tissues: Implications for mechanical biomarkers.

This paper presents the results of a combined experimental and theoretical study of the structure and viscoelastic properties of human non-tumorigenic mammary breast tissues and triple negative breast cancer (TNBC) tissues of different histological grades. A combination of immunofluorescence and confocal microscopy, and atomic force microscopy is used to study the actin cytoskeletal structures of non-tumorigenic and tumorigenic breast tissues (grade I to grade III). A combination of nanoindentation and statistical techniques is then used to measure viscoelastic properties of non-tumorigenic and human TNBC of different histological grades. A Standard Fluid Model/Anti-Zener Model II is also used to characterize the viscoelastic properties of the non-tumorigenic and tumorigenic TNBC tissues of different grades. The implications of the results are discussed for the potential application of nanoindentation and statistical deconvolution techniques to the development of mechanical biomarkers for TNBC detection/cancer diagnosis. STATEMENT OF SIGNIFICANCE: There is increasing interest in the development of mechanical biomarkers for cancer diagnosis. Here, we show that nanoindentation techniques can be used to characterize the viscoelastic properties of normal breast tissue and TNBC tissues of different histological grades. The Standard Fluid Model (Anti-Zener Model II) is used to classify the viscoelastic properties of breast tissues of different TNBC histological grades. Our results suggest that breast tissue and TNBC tissue viscoelastic properties can be used as mechanical biomarkers for the detection of TNBC at different stages.

Factors influencing breast elasticity measured by the ultrasound Shear Wave elastography - preliminary results.

IntroductionMany physiological changes of breast elasticity depend on the age, hormonal status, menstrual cycle and many others. The aim of this study was to evaluate viscoelastic properties of normal breast tissues in a large group of women and to search for factors which play a role in its mechanical properties.Material and methods101 women aged 18-74 years who underwent B-mode sonography and additionally sonoelastography. We measured viscoelasticity in 8 quadrants by a share wave ultrasonic device estimating Young modules in regions of interest.ResultsMean elasticity measured in all 8 scans in glandular and fatty tissue were 11.28 ±5.79 kPa (0.1-46.26 kPa) and 9.24 ±4.48 kPa (0.1-29.78 kPa), respectively. The correlation between age and mean elasticity of glandular tissue was Rs = 0.27 (p = 0.007). The correlation between glandular tissue elasticity heterogeneity and breast mastalgia measured by VAS was Rs = –0.23 (p = 0.241). Fat tissue elasticity correlated with duration of lactation was Rs = 0.21 (p = 0.01).ConclusionsThere are several parameters influencing breast viscoelasticity measured by share wave sonoelastography. Glandular tissue elasticity correlates positively with age, fatty tissue elasticity correlates positively with duration of lactation and heterogeneity of the elasticity map of glandular tissue correlates with breast pain and fat tissue with BMI.

SPIKING NEURAL NETWORKS FOR BREAST CANCER CLASSIFICATION USING RADAR TARGET SIGNATURES

Recent studies have shown that the dielectric properties of normal breast tissue vary considerably. This dielectric heterogeneity may mean that the identiflcation of tumours using Ultra Wideband Radar imaging alone may be quite di-cult. Signiflcantly, since the dielectric properties of benign tissue were shown to overlap with those of malignant, breast tumour classiflcation using traditional UWB Radar imaging algorithms could be very problematic. Rather than simply examining the dielectric properties of scatterers within the breast, other features of scatterers must be used for classiflcation. Radar Target Signatures have been previously used to classify tumours due to the signiflcant difierence in size, shape and surface texture between benign and malignant tumours. This paper investigates Spiking Neural Networks (SNNs) applied as a novel tumour classiflcation method. This paper will describe the creation of 3D tumour models, the generation of representative backscatter, the application of a feature extraction method and the use of SNNs to classify tumours as either benign or malignant. The performance of the SNN classifler is shown to outperform existing UWB Radar classiflcation algorithms.

The Effects of Breast Tissue Heterogeneity on Data-adaptive Beamforming

Ultrawideband (UWB) Microwave Imaging is an emerging technology for breast cancer detection which is based on the dielectric contrast between normal and cancerous tis- sues at microwave frequencies. The breast is illuminated by a UWB pulse and re∞ected signals are used to determine the presence and location of signiflcant dielectric scatterers, which may be representative of cancerous tissue within the breast. Beamformers are used to spatially fo- cus the re∞ected signals and to compensate for path dependent attenuation and phase efiects. These beamformers can be divided into two distinct categories: Data-Independent and Data- Adaptive beamformers. Data-Independent beamformers typically use an assumed channel model to compensate for path-dependent propagation efiects. Conversely, Data-Adaptive beamformers attempt to directly estimate the actual channel based on signals re∞ected from the breast. Recent studies by Lazebnik etal. indicate that the range of dielectric properties of normal breast tissue is much greater than reported previously. This presents a much more di-cult imaging prob- lem due to dielectric heterogeneity. Di-culties encountered by data-independent beamformers in locating tumors within dielectrically heterogeneous breasts have been documented previously. In this paper, the efiects of heterogeneity on data-adaptive beamformers is investigated. 2D MRI-derived breast models with varying levels of dielectric heterogeneity are used to evaluate the data-adaptive beamformers.

Development of Anatomically Realistic Numerical Breast Phantoms With Accurate Dielectric Properties for Modeling Microwave Interactions With the Human Breast

Computational electromagnetics models of microwave interactions with the human breast serve as an invaluable tool for exploring the feasibility of new technologies and improving design concepts related to microwave breast cancer detection and treatment. In this paper, we report the development of a collection of anatomically realistic 3-D numerical breast phantoms of varying shape, size, and radiographic density which can readily be used in finite-difference time-domain computational electromagnetics models. The phantoms are derived from T1-weighted MRIs of prone patients. Each MRI is transformed into a uniform grid of dielectric properties using several steps. First, the structure of each phantom is identified by applying image processing techniques to the MRI. Next, the voxel intensities of the MRI are converted to frequency-dependent and tissue-dependent dielectric properties of normal breast tissues via a piecewise-linear map. The dielectric properties of normal breast tissue are taken from the recently completed large-scale experimental study of normal breast tissue dielectric properties conducted by the Universities of Wisconsin and Calgary. The comprehensive collection of numerical phantoms is made available to the scientific community through an online repository.

A large-scale study of the ultrawideband microwave dielectric properties of normal, benign and malignant breast tissues obtained from cancer surgeries

The development of microwave breast cancer detection and treatment techniques has been driven by reports of substantial contrast in the dielectric properties of malignant and normal breast tissues. However, definitive knowledge of the dielectric properties of normal and diseased breast tissues at microwave frequencies has been limited by gaps and discrepancies across previously published studies. To address these issues, we conducted a large-scale study to experimentally determine the ultrawideband microwave dielectric properties of a variety of normal, malignant and benign breast tissues, measured from 0.5 to 20 GHz using a precision open-ended coaxial probe. Previously, we reported the dielectric properties of normal breast tissue samples obtained from reduction surgeries. Here, we report the dielectric properties of normal (adipose, glandular and fibroconnective), malignant (invasive and non-invasive ductal and lobular carcinomas) and benign (fibroadenomas and cysts) breast tissue samples obtained from cancer surgeries. We fit a one-pole Cole–Cole model to the complex permittivity data set of each characterized sample. Our analyses show that the contrast in the microwave-frequency dielectric properties between malignant and normal adipose-dominated tissues in the breast is considerable, as large as 10:1, while the contrast in the microwave-frequency dielectric properties between malignant and normal glandular/fibroconnective tissues in the breast is no more than about 10%.For more information on this article, see medicalphysicsweb.org

A large-scale study of the ultrawideband microwave dielectric properties of normal breast tissue obtained from reduction surgeries

The efficacy of emerging microwave breast cancer detection and treatment techniques will depend, in part, on the dielectric properties of normal breast tissue. However, knowledge of these properties at microwave frequencies has been limited due to gaps and discrepancies in previously reported small-scale studies. To address these issues, we experimentally characterized the wideband microwave-frequency dielectric properties of a large number of normal breast tissue samples obtained from breast reduction surgeries at the University of Wisconsin and University of Calgary hospitals. The dielectric spectroscopy measurements were conducted from 0.5 to 20 GHz using a precision open-ended coaxial probe. The tissue composition within the probe's sensing region was quantified in terms of percentages of adipose, fibroconnective and glandular tissues. We fit a one-pole Cole–Cole model to the complex permittivity data set obtained for each sample and determined median Cole–Cole parameters for three groups of normal breast tissues, categorized by adipose tissue content (0–30%, 31–84% and 85–100%). Our analysis of the dielectric properties data for 354 tissue samples reveals that there is a large variation in the dielectric properties of normal breast tissue due to substantial tissue heterogeneity. We observed no statistically significant difference between the within-patient and between-patient variability in the dielectric properties.

Two-dimensional FDTD analysis of a pulsed microwave confocal system for breast cancer detection: fixed-focus and antenna-array sensors.

A novel focused active microwave system is investigated for detecting tumors in the breast. In contrast to X-ray and ultrasound modalities, the method reviewed here exploits the breast-tissue physical properties unique to the microwave spectrum, namely, the translucent nature of normal breast tissues and the high dielectric contrast between malignant tumors and surrounding lesion-free normal breast tissues. The system uses a pulsed confocal technique and time-gating to enhance the detection of tumors while suppressing the effects of tissue heterogeneity and absorption. Using published data for the dielectric properties of normal breast tissues and malignant tumors, we have conducted a two-dimensional (2-D) finite-difference time-domain (FDTD) computational electromagnetics analysis of the system. The FDTD simulations showed that tumors as small as 2 mm in diameter could be robustly detected in the presence of the background clutter generated by the heterogeneity of the surrounding normal tissue. Lateral spatial resolution of the tumor location was found to be about 0.5 cm.