An optoacoustic imaging feature set to characterise blood vessels surrounding benign and malignant breast lesions.

Combining optoacoustic (OA) imaging with ultrasound (US) enables visualisation of functional blood vasculature in breast lesions by OA to be overlaid with the morphological information of US. Here, we develop a simple OA feature set to differentiate benign and malignant breast lesions. 94 female patients with benign, indeterminate or suspicious lesions were recruited and underwent OA-US. An OA-US imaging feature set was developed using images from the first 38 patients, which contained 14 malignant and 8 benign solid lesions. Two independent radiologists blindly scored the OA-US images of a further 56 patients, which included 31 malignant and 13 benign solid lesions, with a sensitivity of 96.8% and specificity of 84.6%. Our findings indicate that OA-US can reveal vascular patterns of breast lesions that indicate malignancy using a simple feature set based on single wavelength OA data, which is therefore amenable to application in low resource settings for breast cancer management.

Detecting treatment response in a model of human breast adenocarcinoma using hyperpolarised [1-13C]pyruvate and [1,4-13C2]fumarate.

BACKGROUND: The recent introduction of a dynamic nuclear polarisation technique has permitted noninvasive imaging of tumour cell metabolism in vivo following intravenous administration of (13)C-labelled cell substrates. METHODS: Changes in hyperpolarised [1-(13)C]pyruvate and [1,4-(13)C(2)]fumarate metabolism were evaluated in both MDA-MB-231 cells and in implanted MDA-MB-231 tumours following doxorubicin treatment. RESULTS: Treatment of MDA-MB-231 cells resulted in the induction of apoptosis, which was accompanied by a decrease in hyperpolarised (13)C label flux between [1-(13)C]pyruvate and lactate, which was correlated with a decrease in the cellular NAD(H) coenzyme pool. There was also an increase in the rate of fumarate conversion to malate, which accompanied the onset of cellular necrosis. In vivo, the decrease in (13)C label exchange between pyruvate and lactate and the increased flux between fumarate and malate, following drug treatment, were shown to occur in the absence of any detectable change in tumour size. CONCLUSION: We show here that the early responses of a human breast adenocarcinoma tumour model to drug treatment can be followed by administration of both hyperpolarised [1-(13)C]pyruvate and [1,4-(13)C(2)]fumarate. These techniques could be used, therefore, in the clinic to detect the early responses of breast tumours to treatment.

Signal and noise transfer properties of CMOS based active pixel flat panel imager coupled to structured CsI:Tl.

Complementary metal-oxide-semiconductors (CMOS) active pixel sensors can be optically coupled to CsI:Tl phosphors forming a indirect active pixel flat panel imager (APFPI) for high performance medical imaging. The aim of this work is to determine the x-ray imaging capabilities of CMOS-based APFPI and study the signal and noise transfer properties of CsI:Tl phosphors. Three different CsI:Tl phosphors from two different vendors have been used to produce three system configurations. The performance of each system configuration has been studied in terms of the modulation transfer function (MTF), noise power spectra, and detective quantum efficiency (DQE) in the mammographic energy range. A simple method to determine quantum limited systems in this energy range is also presented. In addition, with aid of monochromatic synchrotron radiation, the effect of iodine characteristic x-rays of the CsI:Tl on the MTF has been determined. A Monte Carlo simulation of the signal transfer properties of the imager is also presented in order to study the stages that degrade the spatial resolution of our current system. The effect of using substrate patterning during the growth of CsI:Tl columnar structure was also studied, along with the effect of CsI:Tl fixed pattern noise due to local variations in the scintillation light. CsI:Tl fixed pattern noise appears to limit the performance of our current system configurations. All the system configurations are quantum limited at 0.23 microC/kg with two of them having DQE (0) equal to 0.57. Active pixel flat panel imagers are shown to be digital x-ray imagers with almost constant DQE throughout a significant part of their dynamic range and in particular at very low exposures.

Empirical electro-optical and x-ray performance evaluation of CMOS active pixels sensor for low dose, high resolution x-ray medical imaging.

Monolithic complementary metal oxide semiconductor (CMOS) active pixel sensors with high performance have gained attention in the last few years in many scientific and space applications. In order to evaluate the increasing capabilities of this technology, in particular where low dose high resolution x-ray medical imaging is required, critical electro-optical and physical x-ray performance evaluation was determined. The electro-optical performance includes read noise, full well capacity, interacting quantum efficiency, and pixels cross talk. The x-ray performance, including x-ray sensitivity, modulation transfer function, noise power spectrum, and detection quantum efficiency, has been evaluated in the mammographic energy range. The sensor is a 525 x 525 standard three transistor CMOS active pixel sensor array with more than 75% fill factor and 25 x 25 microm pixel pitch. Reading at 10 f/s, it is found that the sensor has 114 electrons total additive noise, 10(5) electrons full well capacity with shot noise limited operation, and 34% interacting quantum efficiency at 530 nm. Two different structured CsI:Tl phosphors with thickness 95 and 115 microm, respectively, have been optically coupled via a fiber optic plate to the array resulting in two different system configurations. The sensitivity of the two different system configurations was 43 and 47 electrons per x-ray incident on the sensor. The MTF at 10% of the two different system configurations was 9.5 and 9 cycles/mm with detective quantum efficiency of 0.45 and 0.48, respectively, close to zero frequency at approximately 0.44 microC/kg (1.72 mR) detector entrance exposure. The detector was quantum limited at low spatial frequencies and its performance was comparable with high resolution a: Si and charge coupled device based x-ray imagers. The detector also demonstrates almost an order of magnitude lower noise than active matrix flat panel imagers. The results suggest that CMOS active pixel sensors when coupled to structured CsI:Tl can be used for conventional and advanced digital mammography due to their low noise, high resolution performance.

Correlation of energy dispersive diffraction signatures and microCT of small breast tissue samples with pathological analysis.

Identification of specific tissue types in conventional mammographic examinations is extremely limited. However, the use of x-ray diffraction effects during imaging has the potential to characterize the tissue types present due to the fact that each tissue type produces its own unique diffraction signature. Nevertheless, the analysis and categorization of these diffraction signatures by tissue type can be hampered by the inhomogeneous nature of breast tissue, leading to categorization errors where several types are present. This work aims to reduce sample categorization errors by combining spectral diffraction signature collection with sample imaging, giving more detailed data on the composition of each sample. Diffraction microCT was carried out on 19 unfixed breast tissue samples using an energy resolving translate-rotate CT system. High-resolution transmission microCT images were also recorded for comparison and sample composition analysis. Following imaging, the samples were subjected to histopathological analysis. Reconstructing on various momentum transfer regions allows different tissue types to be identified in the diffraction images. Results show a correlation between measured x-ray diffraction images and stained histopathological tissue sections. X-ray diffraction signatures generated from the measured data were categorized and analysed, with a t-test indicating that they have the potential for use in tissue type identification.