Ethnic and age differences in right-left breast asymmetry in a large population-based screening population

OBJECTIVE: Exposure to sex hormones is important in the pathogenesis of breast cancer and inability to tolerate such exposure may be reflected in increased asymmetrical growth of the breasts. This study aims to characterize, for the first time, asymmetry in breast volume (BV) and radiodense volume (DV) in a large ethnically diverse population. METHODS: Automated measurements from digital raw mammographic images of 54,591 cancer-free participants (aged 47-73) in a UK breast screening programme were used to calculate absolute (cm3) and relative asymmetry in BV and DV. Logistic regression models were fitted to assess asymmetry associations with age and ethnicity. RESULTS: BV and DV absolute asymmetry were positively correlated with the corresponding volumetric dimension (BV or DV). BV absolute asymmetry increased, whilst DV absolute asymmetry decreased, with increasing age (P-for-linear-trend <0.001 for both). Relative to Whites, Blacks had statistically significantly higher, and Chinese lower, BV and DV absolute asymmetries. However, after adjustment for the corresponding underlying volumetric dimension the age and ethnic differences were greatly attenuated. Median relative (fluctuating) BV and DV asymmetry were 2.34 and 3.28% respectively. CONCLUSION: After adjusting for the relevant volumetric dimension (BV or DV), age and ethnic differences in absolute breast asymmetry were largely resolved. ADVANCES IN KNOWLEDGE: Previous small studies have reported breast asymmetry-breast cancer associations. Automated measurements of asymmetry allow the conduct of large-scale studies to further investigate these associations

BREAST CANCER RISK AND DETECTION USING GENES, MAMMOGRAPHIC DENSITY AND MAMMOGRAMS

Ph.DDOCTOR OF PHILOSOPH

Frequency Domain Ultrasound Waveform Tomography Breast Imaging

Ultrasound tomography is an emerging modality for imaging breast tissue for the detection of disease. Using the principles of full waveform inversion, high-resolution quantitative sound speed and attenuation maps of the breast can be created. In this thesis, we introduce some basic principles of imaging breast disease and the formalism of sound wave propagation. We present numerical methods to model acoustic wave propagation as well methods to solve the corresponding inverse problem. Numerical simulations of sound speed and attenuation reconstructions are used to assess the efficacy of the algorithm. A careful review of the preprocessing techniques needed for the successful inversion of acoustic data is presented. Ex vivo and in vivo sound speed reconstructions highlight the significant improvements that are made upon commonly used travel time sound speed reconstruction methods. Note that we do not present ex vivo or in vivo attenuation reconstructions in this thesis. For the sound speed images, the higher resolution and contrast of the waveform method will hopefully allow a radiologist to make a more informed diagnosis of breast disease. A comparison of full waveform sound speed imaging to MRI shows a great deal of concordant findings. Lastly, we give examples of the use of full waveform inversion sound speed imaging in a clinical setting

Texture Analysis Platform for Imaging Biomarker Research

abstract: The rate of progress in improving survival of patients with solid tumors is slow due to late stage diagnosis and poor tumor characterization processes that fail to effectively reflect the nature of tumor before treatment or the subsequent change in its dynamics because of treatment. Further advancement of targeted therapies relies on advancements in biomarker research. In the context of solid tumors, bio-specimen samples such as biopsies serve as the main source of biomarkers used in the treatment and monitoring of cancer, even though biopsy samples are susceptible to sampling error and more importantly, are local and offer a narrow temporal scope. Because of its established role in cancer care and its non-invasive nature imaging offers the potential to complement the findings of cancer biology. Over the past decade, a compelling body of literature has emerged suggesting a more pivotal role for imaging in the diagnosis, prognosis, and monitoring of diseases. These advances have facilitated the rise of an emerging practice known as Radiomics: the extraction and analysis of large numbers of quantitative features from medical images to improve disease characterization and prediction of outcome. It has been suggested that radiomics can contribute to biomarker discovery by detecting imaging traits that are complementary or interchangeable with other markers. This thesis seeks further advancement of imaging biomarker discovery. This research unfolds over two aims: I) developing a comprehensive methodological pipeline for converting diagnostic imaging data into mineable sources of information, and II) investigating the utility of imaging data in clinical diagnostic applications. Four validation studies were conducted using the radiomics pipeline developed in aim I. These studies had the following goals: (1 distinguishing between benign and malignant head and neck lesions (2) differentiating benign and malignant breast cancers, (3) predicting the status of Human Papillomavirus in head and neck cancers, and (4) predicting neuropsychological performances as they relate to Alzheimer’s disease progression. The long-term objective of this thesis is to improve patient outcome and survival by facilitating incorporation of routine care imaging data into decision making processes.Dissertation/ThesisDoctoral Dissertation Biomedical Informatics 201