C = capacitance; ε = permittivity; EIS = electrical impedance scanning; R = resistance; σ = conductance; SMM = 99m Tc-sestamibi scintimammography; Z = magnitude.Available online http://breast-cancer-research.com/content/6/2/69 IntroductionElectrical impedance scanning (EIS) maps are a measure of the electrical properties of an object made through surface measurements. The information is obtained quickly and comfortably, and the method shows promise for detecting cancers that may have previously gone undetected. The technology of electrical impedance measurements in the detection of disease has become a topic of great interest for engineering and physiological scientists. Electrical properties of biological tissues Electrical properties of living tissueInterest and experimentation in the electrical properties of tissues began in the late 1800s. This interest has evolved into a branch of physiology and the research has lead to insight into various mechanisms. This section provides an overview of some electrical terminology that is used in tissue impedance studies.First are basic explanations of resistance (R), conductance (σ), permittivity (ε) and capacitance (C). Resistance is a property that opposes current flow, and conductance is the inverse of resistance. Capacitance is a property that opposes a change in voltage or electric potential across an object and acts to store energy. A capacitor consists of two conductors, each oppositely charged and separated by a dielectric material. Permittivity is a property of the dielectric material and reflects the ability of charges in the material to move in response to an electric field. Capacitance is a function of the permittivity and the physical geometry of the object. For example, the capacitance formula for a two-plate capacitor is C = εA / d, where A is the area of each plate and d is the distance between them. The complex impedance (Z) of an RC series circuit can be described as Z = R + jX c , where X c = 1 / ωC (ω = 2πf, where f is frequency). The representation of the impedance can also be in the form of polar coordinates with Z = Z / θ, where Z is the magnitude and θ is the phase angle of the impedance. Z is the square root of R 2 + X c 2 and θ = arctan(X c / R). Permittivity and thus capacitance are usually considered to be constant values, independent of frequency. AbstractThe present paper focuses on electrical impedance scanning. The basic science behind the new modality, measurements of breast tissue impedance in vivo and in vitro, and the studies performed with a newly available commercial machine are discussed. Electrical impedance scanning has been generating interest for several reasons, including comfort to the patient, the relatively low cost, and studies suggest that it may be effective in detecting disease in mammographically dense breasts.

Cerebral palsy (CP) develops as a consequence of white matter damage (WMD) in approximately one out of every 10 very preterm infants. Ultrasound (US) is widely used to screen for a variety of brain injuries in this patient population, but early US often fails to detect WMD. We hypothesized that quantitative texture measures on US images obtained within one week of birth are associated with the subsequent development of CP. In this retrospective study, using images from a variety of US machines, we extracted unique texture measures by means of adaptive processing and high resolution feature enhancement. We did not standardize the images, but used patients as their own controls. We did not remove speckle, as it may contain information. To test our hypothesis, we used the "random forest" algorithm to create a model. The random forest classifier achieved a 72% match to the health outcome of the patients (CP versus no CP), whereas designating all patients as having CP would have resulted in 53% error. This suggests that quantitative early texture measures contain diagnostic information relevant to the development of CP.

Background The extent of cellular heterogeneity in breast cancer could have potential impact on diagnosis and long-term outcome. However, pathology evaluation is limited to biomarker immunohistochemical staining and morphology of the bulk cancer. Inter-cellular heterogeneity of biomarkers is not usually assessed. As an initial evaluation of the extent of breast cancer cellular heterogeneity, we conducted quantitative and spatial imaging of Estrogen Receptor (ER), Progesterone Receptor (PR), Epidermal Growth Factor Receptor-2 (HER2), Ki67, TP53, CDKN1A (P21/WAF1), CDKN2A (P16INK4A), CD8 and CD20 of a tissue microarray (TMA) representing subtypes defined by St. Gallen surrogate classification. Methods Quantitative, single cell-based imaging was conducted using an Immunofluorescence protein multiplexing platform (MxIF) to study protein co-expression signatures and their spatial localization patterns. The range of MxIF intensity values of each protein marker was compared to the respective IHC score for the TMA core. Extent of heterogeneity in spatial neighborhoods was analyzed using co-occurrence matrix and Diversity Index measures. Results On the 101 cores from 59 cases studied, diverse expression levels and distributions were observed in MxIF measures of ER and PR among the hormonal receptor-positive tumor cores. As expected, Luminal A-like cancers exhibit higher proportions of cell groups that co-express ER and PR, while Luminal B-like (HER2-negative) cancers were composed of ER+, PR- groups. Proliferating cells defined by Ki67 positivity were mainly found in groups with PR-negative cells. Triple-Negative Breast Cancer (TNBC) exhibited the highest proliferative fraction and incidence of abnormal P53 and P16 expression. Among the tumors exhibiting P53 overexpression by immunohistochemistry, a group of TNBC was found with much higher MxIF-measured P53 signal intensity compared to HER2+, Luminal B-like and other TNBC cases. Densities of CD8 and CD20 cells were highest in HER2+ cancers. Spatial analysis demonstrated variability in heterogeneity in cellular neighborhoods in the cancer and the tumor microenvironment. Conclusions Protein marker multiplexing and quantitative image analysis demonstrated marked heterogeneity in protein co-expression signatures and cellular arrangement within each breast cancer subtype. These refined descriptors of biomarker expressions and spatial patterns could be valuable in the development of more informative tools to guide diagnosis and treatment.

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Premature infants are prone to white matter damage (WMD), which is associated with cerebral palsy (CP) and cognitive impairment. Ultrasound (US) is the preferred imaging modality to detect WMD. To improve on existing diagnostic rates, quantitative measures incorporating new information are needed. We are investigating US texture measures as new indicators of white matter health.We have developed algorithms to enhance texture features and then obtain a measure of the tissue texture. Using our texture measures, data from 18 patients (12 with normal outcome, 6 who developed CP) form separate populations based on patient outcome. Our algorithms are applied to B-mode cranial US images without compensating for operator-dependent machine settings and without suppressing speckle. The results of the preliminary study will form the basis for the design of a computer aided diagnosis system for the early detection of white matter damage.