Elemental and phase composition of breast calcifications

Despite the importance of calcifications in early detection of breast cancer, and their proposed association with tumour growth, remarkably little detail is known about their chemical composition, or how this relates to pathology. One reason for this gap is the difficulty of systematically and precisely locating calcifications for analysis, particularly in sections taken from diagnostic archives. Two simple methods were developed which can achieve this in sections cut from wax embedded breast tissue. These are based on micro-CT and x-ray fluoroscopy mapping, and were used to locate calcifications for further study. The elemental composition of calcifications in histological sections was measured using energy-dispersive x-ray spectroscopy in an environmental scanning electron microscope. Variations in Ca:P ratio could in principle be detected non-invasively by dual energy absorptiometry, as demonstrated in a proof of principle experiment. However, the Ca:P ratio was found to lie in a narrow range similar to bone, with no significant difference between benign and malignant. In contrast, a substantial and significant difference in Na:Ca ratio was found between benign and malignant specimens. This has potential for revealing malignant changes in the vicinity of a core needle biopsy. The phase composition and crystallographic parameters within calcifications was measured using synchrotron x-ray diffraction. This is the first time crystallite size and lattice parameters have been measured in breast calcifications, and it was found that these both parallel closely the changes in these parameters with age observed in foetal bone. It was also discovered that these calcifications contain a small proportion of magnesium whitlockite, and that this proportion increases from benign, to carcinoma in-situ, to invasive cancer. When combined with other recent evidence on the effect of magnesium on hydroxyapatite precipitation, this suggests a mechanism explaining observations that carbonate levels within breast calcifications are lower in malignant specimens

Tissue mimicking materials for imaging and therapy phantoms: a review

Tissue mimicking materials (TMMs), typically contained within phantoms, have been used for many decades in both imaging and therapeutic applications. This review investigates the specifications that are typically being used in development of the latest TMMs. The imaging modalities that have been investigated focus around CT, mammography, SPECT, PET, MRI and ultrasound. Therapeutic applications discussed within the review include radiotherapy, thermal therapy and surgical applications. A number of modalities were not reviewed including optical spectroscopy, optical imaging and planar x-rays. The emergence of image guided interventions and multimodality imaging have placed an increasing demand on the number of specifications on the latest TMMs. Material specification standards are available in some imaging areas such as ultrasound. It is recommended that this should be replicated for other imaging and therapeutic modalities. Materials used within phantoms have been reviewed for a series of imaging and therapeutic applications with the potential to become a testbed for cross-fertilization of materials across modalities. Deformation, texture, multimodality imaging and perfusion are common themes that are currently under development

A dual modality, DCE-MRI and x-ray, physical phantom for quantitative evaluation of breast imaging protocols

The current clinical standard for breast cancer screening is mammography. However, this technique has a low sensitivity which results in missed cancers. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has recently emerged as a promising technique for breast cancer diagnosis and has been reported as being superior to mammography for screening of high-risk women and evaluation of extent of disease. At the same time, low and variable specificity has been documented in the literature as well as a rising number of mastectomies possibly due to the increasing use of DCE-MRI. In this study, we developed and characterized a dual-modality, x-ray and DCE-MRI, anthropomorphic breast phantom for the quantitative assessment of breast imaging protocols. X-ray properties of the phantom were quantitatively compared with patient data, including attenuation coefficients, which matched human values to within the measurement error, and tissue structure using spatial covariance matrices of image data, which were found to be similar in size to patient data. Simulations of the phantom scatter-to-primary ratio (SPR) were produced and experimentally validated then compared with published SPR predictions for homogeneous phantoms. SPR values were as high as 85% in some areas and were heavily influenced by the heterogeneous tissue structure. MRI properties of the phantom, T1 and T2 relaxation values and tissue structure, were also quantitatively compared with patient data and found to match within two error bars. Finally, a dynamic lesion that mimics lesion border shape and washout curve shape was included in the phantom. High spatial and temporal resolution x-ray measurements of the washout curve shape were performed to determine the true contrast agent concentration as a function of time. DCE-MRI phantom measurements using a clinical imaging protocol were compared against the x-ray truth measurements. MRI signal intensity curves were shown to be less specific to lesion type than the x-ray derived contrast agent concentration curves. This phantom allows, for the first time, for quantitative evaluation of and direct comparisons between x-ray and MRI breast imaging modalities in the context of lesion detection and characterization

Enhanced algorithms for lesion detection and recognition in ultrasound breast images

Mammography is the gold standard for breast cancer detection. However, it has very high false positive rates and is based on ionizing radiation. This has led to interest in using multi-modal approaches. One modality is diagnostic ultrasound, which is based on non-ionizing radiation and picks up many of the cancers that are generally missed by mammography. However, the presence of speckle noise in ultrasound images has a negative effect on image interpretation. Noise reduction, inconsistencies in capture and segmentation of lesions still remain challenging open research problems in ultrasound images. The target of the proposed research is to enhance the state-of-art computer vision algorithms used in ultrasound imaging and to investigate the role of computer processed images in human diagnostic performance. [Continues.

Histopathological image analysis : a review

Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe

Digital Image Processing Applications

Digital image processing can refer to a wide variety of techniques, concepts, and applications of different types of processing for different purposes. This book provides examples of digital image processing applications and presents recent research on processing concepts and techniques. Chapters cover such topics as image processing in medical physics, binarization, video processing, and more