Systems and Methods for Quantitative Functional Imaging of Breast Tumor Margin Morphology
dc.contributor.advisor | Ramanujam, Nirmala | |
dc.contributor.author | Nichols, Brandon Scott | |
dc.date.accessioned | 2017-05-16T17:27:07Z | |
dc.date.available | 2018-04-25T08:17:12Z | |
dc.date.issued | 2016 | |
dc.department | Biomedical Engineering | |
dc.description.abstract | \abstract Among women, breast cancer has the highest incidence rate worldwide and remains the leading cause of cancer-related deaths in developed countries. Women with stage I or II breast cancer are eligible for a surgical procedure known as breast conserving surgery (BCS) which seeks to optimize the amount of tissue removed.BCS involves removing the tumor and a minimally thin peripheral layer, or margin of disease-free tissue surrounding the tumor. While the procedure dramatically minimizes the amount of tissue removed, an unfortunate concomitant reality is that a significant percentage (around 25$\%$) of patients will be advised to return for a second surgery due to the discovery of malignant cells at the tissue margin edge, suggesting that it is likely not all of the malignant cells were removed in the initial procedure. The fact that margins are analyzed in histopathology post-operatively (in most cases) presents a substantial clinical burden that could be reduced if the surgeon was able to reliably assess suspicious areas intra-operatively. The primary challenge in addressing this need stems from the need to resolve microscopic cellular morphology within a relatively tremendous amount of benign breast tissue. Many investigative optical tools seek to address this challenge, as the wavelength-dependent nature of light propagation within tissue can be used to assign optical signatures to tissue types derived from the relative tissue constituents. Among the numerous techniques, quantitative diffuse reflectance spectroscopy (QDRS) is a well-established, comparatively simple technique that has been extensively validated in simulation, tissue-simulating phantoms, and various clinical contexts to robustly provide feature-specific optical signatures related to tissue morphology. We have leveraged QDRS in an evolution of several system formats to describe the morphological state of excised breast tissue based on the endogenous optical chromophores and scatterers within the breast, specifically, the amount of hemoglobin from blood, \betac~ in fat, as well as the size distribution and number density of scatterers. We have employed multiple hardware embodiments of this technique related to the context of use. Each device leverages the same physical principles: The diffuse reflectance spectrum is measured using an imaging probe with multiple optical channels and is analyzed with a feature extraction algorithm based on a fast, scalable \mc~ model to quantitatively determine the absorption spectrum (\mualam) and reduced scattering spectrum (\musplam). The technology detects varying amounts of malignancy in the presence of benign tissue by quantifying the margin “landscape” as a cumulative distribution function (CDF) of the ratio of \betac~ concentration (absorber) and the wavelength averaged tissue scattering (\bscat), derived from \oprop, respectively. We have established through histopathological validation that the \bscat~ reports on the relative amount of adipose to collagen, glands, and fibrous content; decreased ratios are strongly associated with the presence of residual disease. Local recurrence in BCS has a compelling association with residual disease, suggesting that QDRS could be used to reduce re-excision rates. The work presented here demonstrates a systematic approach in the development of a pragmatic and clinically viable QDRS imaging system. Two approaches are employed: a robust, research-grade 49-channel system is used to validate previous clinical findings and determine the optimal sampling resolution, and secondly, a low-cost, portable, miniature system based on annular photodiodes is developed and shown to be diagnostically comparable. These systems are accompanied by the development of a unique imaging platform that provides robust quality control and improved resolution, further improving the diagnostic capability. The diagnostic utility of the \bscat parameter is explored in a 100-patient clinical study. The potential for commercialization of the miniature system is informed through deployment of a replica system at a remote institution. Accessibility is improved through the design of a generic, object oriented software package that abstracts the individual hardware components. The portability, accuracy, and manufacturability provide a realistically translatable path for integration into the clinical standard of care. | |
dc.identifier.uri | ||
dc.subject | Engineering | |
dc.subject | Physics | |
dc.subject | Electrical engineering | |
dc.subject | Biophotonics | |
dc.subject | Clinical Imaging | |
dc.subject | Diffuse reflectance | |
dc.subject | Light-Tissue Interactions | |
dc.subject | Spectral imaging | |
dc.subject | Spectroscopy | |
dc.title | Systems and Methods for Quantitative Functional Imaging of Breast Tumor Margin Morphology | |
dc.type | Dissertation | |
duke.embargo.months | 11 |
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