<p>The rate of occurrence and number of deaths associated with cancer continues to climb each year despite the continual efforts to battle the disease. When given a cancer diagnosis, it is particularly demoralizing and devastating news to a patient. Generally, cancer is defined as the uncontrolled rapid growth of abnormal cells with metastatic potential. In the cancer types originating from solid tissue or organ sites, a tumor will grow as a result of this rapid proliferation of cells. Surgical resection is a commonly used as part of the treatment regimen prescribed for these types of cancer.</p><p>Specifically in breast cancer, which impacts over 200,000 women a year, surgical intervention is used in almost 92% of treated cases. A specific surgical procedure is known as breast conserving surgery (BCS), where the physician removes only the tumor, while retaining as much normal tissue as possible. BCS is used in 59% of cases and is generally more preferable than the more radically mastectomy procedure where the entire breast is removed.</p><p>To minimize the chance of local recurrence, it is vital that the tumor is completely removed and residual cancer cells are not still present in the patient. This diagnosis is made by inspecting the edge of the resected tumor mass, typically known as the surgical margin. If tumor cells are still present at the margin, then a positive diagnosis is given and tumor cells likely remain inside the patient. Unfortunately, since margins are typically diagnosed using post-operative pathology a patient with a positive margin must undergo a second re-excision operation to remove additional tissue.</p><p>For breast cancer patients undergoing BCS, a staggering 20-70% of patients must undergo additional operations due to incomplete tumor removal during the first procedure. </p><p>Currently, there are two intra-operative techniques that are used, frozen section analysis and touch prep cytology. Although both have been proven to be effective in reducing re-excision rates, both techniques require</p><p>There remains a clinical unmet need for an intra-operative technology capable of quickly diagnosis tumor margins during the initial surgical operation</p><p>Optical technologies provide an attractive method of quickly and non-destructively assessing tissue. These techniques rely the interactions of light with tissue, which include absorption, scattering, and fluorescence. Utilizing proper measurement systems, these interactions can be measured and exploited to yield specific sources of contrast in tissue. In this dissertation, I have focused on developing two specific optical techniques for the purpose of surgical margin assessment. </p><p>The first is diffuse reflectance spectroscopy (DRS) which is a specific method to extract quantitative biological composition of tissues has been used to discern tissue types in both pre-clinical and clinical cancer studies. Typically, diffuse reflectance spectroscopy systems are designed for single-point measurements. Clinically, an imaging system would provide valuable spatial information on tissue composition. While it is feasible to build a multiplexed fiber-optic probe based spectral imaging system, these systems suffer from drawbacks with respect to cost and size. To address these I developed a compact and low cost system using a broadband light source with an 8-slot filter wheel for illumination and silicon photodiodes for detection. The spectral imaging system was tested on a set of tissue mimicking liquid phantoms which yielded an optical property extraction accuracy of 6.40 ± 7.78% for the absorption coefficient (µa) and 11.37 ± 19.62% for the wavelength-averaged reduced scattering coefficient (µs').</p><p>While DRS provided one potential approach to margin diagnosis, the technique was inherently limited in terms of lateral resolution. The second optical technique I chose to focus on was fluorescence microscopy, which had the ability to achieve lateral resolution on the order of microns. Cancer is associated with specific cellular morphological changes, such as increased nuclear size and crowding from rapidly proliferating cells. In situ tissue imaging using fluorescent stains may be useful for intraoperative detection of residual cancer in surgical tumor margins. I developed a widefield fluorescence structured illumination microscope (SIM) system with a single-shot FOV of 2.1×1.6 mm (3.4 mm2) and sub-cellular resolution (4.4 µm). The objectives of this work were to measure the relationship between illumination pattern frequency and optical sectioning strength and signal-to-noise ratio in turbid (i.e. thick) samples for selection of the optimum frequency, and to determine feasibility for detecting residual cancer on tumor resection margins, using a genetically engineered primary mouse model of sarcoma. The SIM system was tested in tissue mimicking solid phantoms with various scattering levels to determine impact of both turbidity and illumination frequency on two SIM metrics, optical section thickness and modulation depth. To demonstrate preclinical feasibility, ex vivo 50 µm frozen sections and fresh intact thick tissue samples excised from a primary mouse model of sarcoma were stained with acridine orange, which stains cell nuclei, skeletal muscle, and collagenous stroma. The cell nuclei were segmented using a high-pass filter algorithm, which allowed quantification of nuclear density. The results showed that the optimal illumination frequency was 31.7 µm&#8722;1 used in conjunction with a 4x 0.1 NA objective. This yielded an optical section thickness of 128 µm and an 8.9x contrast enhancement over uniform illumination. I successfully demonstrated the ability to resolve cell nuclei in situ achieved via SIM, which allowed segmentation of nuclei from heterogeneous tissues in the presence of considerable background fluorescence. Specifically, I demonstrated that optical sectioning of fresh intact thick tissues performed equivalently in regards to nuclear density quantification, to physical frozen sectioning and standard microscopy.</p><p>However the development of the SIM system was only the first step in showing potential application to surgical margin assessment. The nest study presented in this dissertation was to demonstrate clinical viability on a sample size of 23 animals. The biological samples used in this study were a genetically engineered mouse model of sarcoma, where a spontaneous solid tumor was grown in the hind leg. After the tumor was surgically removed from the animal and the relevant margin was stained with acridine orange (AO), a simple and widely available contrast agent that brightly stains cell nuclei and fibrous tissues. The margin was imaged with the SIM system with the primary goal of visualizing specific morphological changes in cell nuclei. To automatically segment AO-stained regions, an algorithm known as maximally stable extremal regions (MSER) was optimized and applied to the images. </p><p>As an intermediate step prior to diagnosing whole margins, a tissue-type classification model was developed to differentiate localized regions (75x75 µm) of tumor from skeletal muscle and adipose tissue based on the MSER nuclei segmentation output. A logistic regression model was used which yielded a final output in terms of probability (0-100%) the tumor within the localized region. The model performance was tested using an ROC curve analysis that revealed a 77% sensitivity and 81% specificity. For margin classification, the whole margin image was divided into localized regions and this tissue-type classification model was applied. In a subset of 6 margins (3 negative, 3 positive), it was shown that at a tumor probability threshold of 50% only 8% of all regions from a negative margins exceeded this threshold, while over 25% of all regions exceeded the threshold in the positive margins.</p> / Dissertation

<p>Histopathology is the clinical standard for tissue diagnosis. However, histopathology has several limitations including that it requires tissue processing, which can take 30 minutes or more, and requires a highly trained pathologist to diagnose the tissue. Additionally, the diagnosis is qualitative, and the lack of quantitation leads to possible observer-specific diagnosis. Taken together, it is difficult to diagnose tissue at the point of care using histopathology.</p><p>Several clinical situations could benefit from more rapid and automated histological processing, which could reduce the time and the number of steps required between obtaining a fresh tissue specimen and rendering a diagnosis. For example, there is need for rapid detection of residual cancer on the surface of tumor resection specimens during excisional surgeries, which is known as intraoperative tumor margin assessment. Additionally, rapid assessment of biopsy specimens at the point-of-care could enable clinicians to confirm that a suspicious lesion is successfully sampled, thus preventing an unnecessary repeat biopsy procedure. Rapid and low cost histological processing could also be potentially useful in settings lacking the human resources and equipment necessary to perform standard histologic assessment. Lastly, automated interpretation of tissue samples could potentially reduce inter-observer error, particularly in the diagnosis of borderline lesions. </p><p>To address these needs, high quality microscopic images of the tissue must be obtained in rapid timeframes, in order for a pathologic assessment to be useful for guiding the intervention. Optical microscopy is a powerful technique to obtain high-resolution images of tissue morphology in real-time at the point of care, without the need for tissue processing. In particular, a number of groups have combined fluorescence microscopy with vital fluorescent stains to visualize micro-anatomical features of thick (i.e. unsectioned or unprocessed) tissue. However, robust methods for segmentation and quantitative analysis of heterogeneous images are essential to enable automated diagnosis. Thus, the goal of this work was to obtain high resolution imaging of tissue morphology through employing fluorescence microscopy and vital fluorescent stains and to develop a quantitative strategy to segment and quantify tissue features in heterogeneous images, such as nuclei and the surrounding stroma, which will enable automated diagnosis of thick tissues.</p><p>To achieve these goals, three specific aims were proposed. The first aim was to develop an image processing method that can differentiate nuclei from background tissue heterogeneity and enable automated diagnosis of thick tissue at the point of care. A computational technique called sparse component analysis (SCA) was adapted to isolate features of interest, such as nuclei, from the background. SCA has been used previously in the image processing community for image compression, enhancement, and restoration, but has never been applied to separate distinct tissue types in a heterogeneous image. In combination with a high resolution fluorescence microendoscope (HRME) and a contrast agent acriflavine, the utility of this technique was demonstrated through imaging preclinical sarcoma tumor margins. Acriflavine localizes to the nuclei of cells where it reversibly associates with RNA and DNA. Additionally, acriflavine shows some affinity for collagen and muscle. SCA was adapted to isolate acriflavine positive features or APFs (which correspond to RNA and DNA) from background tissue heterogeneity. The circle transform (CT) was applied to the SCA output to quantify the size and density of overlapping APFs. The sensitivity of the SCA+CT approach to variations in APF size, density and background heterogeneity was demonstrated through simulations. Specifically, SCA+CT achieved the lowest errors for higher contrast ratios and larger APF sizes. When applied to tissue images of excised sarcoma margins, SCA+CT correctly isolated APFs and showed consistently increased density in tumor and tumor + muscle images compared to images containing muscle. Next, variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82% and 75%. The utility of this approach was further tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78% and 82%. The results indicate that SCA+CT can accurately delineate APFs in heterogeneous tissue, which is essential to enable automated and rapid surveillance of tissue pathology. </p><p>Two primary challenges were identified in the work in aim 1. First, while SCA can be used to isolate features, such as APFs, from heterogeneous images, its performance is limited by the contrast between APFs and the background. Second, while it is feasible to create mosaics by scanning a sarcoma tumor bed in a mouse, which is on the order of 3-7 mm in any one dimension, it is not feasible to evaluate an entire human surgical margin. Thus, improvements to the microscopic imaging system were made to (1) improve image contrast through rejecting out-of-focus background fluorescence and to (2) increase the field of view (FOV) while maintaining the sub-cellular resolution needed for delineation of nuclei. To address these challenges, a technique called structured illumination microscopy (SIM) was employed in which the entire FOV is illuminated with a defined spatial pattern rather than scanning a focal spot, such as in confocal microscopy. </p><p>Thus, the second aim was to improve image contrast and increase the FOV through employing wide-field, non-contact structured illumination microscopy and optimize the segmentation algorithm for new imaging modality. Both image contrast and FOV were increased through the development of a wide-field fluorescence SIM system. Clear improvement in image contrast was seen in structured illumination images compared to uniform illumination images. Additionally, the FOV is over 13X larger than the fluorescence microendoscope used in aim 1. Initial segmentation results of SIM images revealed that SCA is unable to segment large numbers of APFs in the tumor images. Because the FOV of the SIM system is over 13X larger than the FOV of the fluorescence microendoscope, dense collections of APFs commonly seen in tumor images could no longer be sparsely represented, and the fundamental sparsity assumption associated with SCA was no longer met. Thus, an algorithm called maximally stable extremal regions (MSER) was investigated as an alternative approach for APF segmentation in SIM images. MSER was able to accurately segment large numbers of APFs in SIM images of tumor tissue. In addition to optimizing MSER for SIM image segmentation, an optimal frequency of the illumination pattern used in SIM was carefully selected because the image signal to noise ratio (SNR) is dependent on the grid frequency. A grid frequency of 31.7 mm-1 led to the highest SNR and lowest percent error associated with MSER segmentation. </p><p>Once MSER was optimized for SIM image segmentation and the optimal grid frequency was selected, a quantitative model was developed to diagnose mouse sarcoma tumor margins that were imaged ex vivo with SIM. Tumor margins were stained with acridine orange (AO) in aim 2 because AO was found to stain the sarcoma tissue more brightly than acriflavine. Both acriflavine and AO are intravital dyes, which have been shown to stain nuclei, skeletal muscle, and collagenous stroma. A tissue-type classification model was developed to differentiate localized regions (75x75 µm) of tumor from skeletal muscle and adipose tissue based on the MSER segmentation output. Specifically, a logistic regression model was used to classify each localized region. The logistic regression model yielded an output in terms of probability (0-100%) that tumor was located within each 75x75 µm region. The model performance was tested using a receiver operator characteristic (ROC) curve analysis that revealed 77% sensitivity and 81% specificity. For margin classification, the whole margin image was divided into localized regions and this tissue-type classification model was applied. In a subset of 6 margins (3 negative, 3 positive), it was shown that with a tumor probability threshold of 50%, 8% of all regions from negative margins exceeded this threshold, while over 17% of all regions exceeded the threshold in the positive margins. Thus, 8% of regions in negative margins were considered false positives. These false positive regions are likely due to the high density of APFs present in normal tissues, which clearly demonstrates a challenge in implementing this automatic algorithm based on AO staining alone. </p><p>Thus, the third aim was to improve the specificity of the diagnostic model through leveraging other sources of contrast. Modifications were made to the SIM system to enable fluorescence imaging at a variety of wavelengths. Specifically, the SIM system was modified to enabling imaging of red fluorescent protein (RFP) expressing sarcomas, which were used to delineate the location of tumor cells within each image. Initial analysis of AO stained panels confirmed that there was room for improvement in tumor detection, particularly in regards to false positive regions that were negative for RFP. One approach for improving the specificity of the diagnostic model was to investigate using a fluorophore that was more specific to staining tumor. Specifically, tetracycline was selected because it appeared to specifically stain freshly excised tumor tissue in a matter of minutes, and was non-toxic and stable in solution. Results indicated that tetracycline staining has promise for increasing the specificity of tumor detection in SIM images of a preclinical sarcoma model and further investigation is warranted. </p><p>In conclusion, this work presents the development of a combination of tools that is capable of automated segmentation and quantification of micro-anatomical images of thick tissue. When compared to the fluorescence microendoscope, wide-field multispectral fluorescence SIM imaging provided improved image contrast, a larger FOV with comparable resolution, and the ability to image a variety of fluorophores. MSER was an appropriate and rapid approach to segment dense collections of APFs from wide-field SIM images. Variables that reflect the morphology of the tissue, such as the density, size, and shape of nuclei and nucleoli, can be used to automatically diagnose SIM images. The clinical utility of SIM imaging and MSER segmentation to detect microscopic residual disease has been demonstrated by imaging excised preclinical sarcoma margins. Ultimately, this work demonstrates that fluorescence imaging of tissue micro-anatomy combined with a specialized algorithm for delineation and quantification of features is a means for rapid, non-destructive and automated detection of microscopic disease, which could improve cancer management in a variety of clinical scenarios.</p> / Dissertation

OBJECTIVE: Breast cancer represents a significant risk in women's health, affecting many women worldwide. Current treatment options in the U.S involve a multidisciplinary approach, most often beginning with surgery to remove cancerous tissue. Evaluation of margins for cancer on excised tissue is an important part of surgery, an important predictor of survival. As a result, there has been a great deal of research interest in intraoperative margin assessment, with a focus on fast and accurate results. Micro-computed Tomography (micro-CT) has emerged as a promising avenue to this end. We hypothesize that micro-CT scans will show a statistically significant difference in radiodensity between cancerous and non-cancerous tissue at intraoperative scan times. METHODS: 15 breast lumpectomy specimens were collected from patients undergoing surgery at Massachusetts General Hospital (MGH). Lumpectomies were scanned with a Nikon XTH225 Micro-CT scanner. Corresponding histology slides were scanned with a whole slide scanner, and matched with micro-CT scans. Representative areas of cancerous and non-cancerous tissues were segmented from micro-CT scans, and their respective radiodensity differences were tested for statistical significance. RESULTS: 9 of 15 lumpectomy cases were successfully matched with histology sections. Of the 9 cases matched, 8 showed a statistically significant difference in mean radiodensity. CONCLUSION: Due to potential confounds in the study, the results are difficult to deem conclusive. However, micro-CT remains a promising tool in margin assessment, and could be fit for clinical use with further study.

Light delivery and sample handling systems are essential for any high performance imaging application. The custom design for two such devices with medical imaging applications are presented. The first device, a galvanometer-stage combination, is for general use optical coherence tomography and can be configured to scan over a large range of sample sizes and types. The second device, constructed in parallel, a rotation-linear stage combination, has been carefully designed for a specific imaging task: assessing tumour margins. The design of the two devices is driven by operational requirements and although requirements vary greatly from application to application, there are several common parameters that must be considered for every system. In this thesis, parameters like total scan time, scan resolution, sampling rate, and sample type flexibility are analysed and are some of the primary factors that influence the viability of a system for further development. This work's contribution to medical imaging research is the design of two light delivery systems and an analysis process that can be applied to future iterations of scan systems. The devices are shown to be flexible enough for use in test-bed systems, while providing the necessary functionality to meet the needs of medical histology and pathology. Controlling the light delivery and sample positioning of an imaging device adds important functionality to a scan system and is not a trivial task when high spatial-resolution scan spacing is required. The careful design of an imaging system to meet the unique requirements of the application enables better information and better resulting decision making. Advanced imagery provides new insights and perspectives to everyday scenes. It is these new perspectives that allow for re-evaluation and examination of problems with a fresh eye.

Light delivery and sample handling systems are essential for any high performance imaging application. The custom design for two such devices with medical imaging applications are presented. The first device, a galvanometer-stage combination, is for general use optical coherence tomography and can be configured to scan over a large range of sample sizes and types. The second device, constructed in parallel, a rotation-linear stage combination, has been carefully designed for a specific imaging task: assessing tumour margins. The design of the two devices is driven by operational requirements and although requirements vary greatly from application to application, there are several common parameters that must be considered for every system. In this thesis, parameters like total scan time, scan resolution, sampling rate, and sample type flexibility are analysed and are some of the primary factors that influence the viability of a system for further development. This work's contribution to medical imaging research is the design of two light delivery systems and an analysis process that can be applied to future iterations of scan systems. The devices are shown to be flexible enough for use in test-bed systems, while providing the necessary functionality to meet the needs of medical histology and pathology. Controlling the light delivery and sample positioning of an imaging device adds important functionality to a scan system and is not a trivial task when high spatial-resolution scan spacing is required. The careful design of an imaging system to meet the unique requirements of the application enables better information and better resulting decision making. Advanced imagery provides new insights and perspectives to everyday scenes. It is these new perspectives that allow for re-evaluation and examination of problems with a fresh eye.

<p>In 2011, an estimated 230,480 new cases of invasive breast cancer were diagnosed among women, as well as an estimated 57,650 additional cases of in situ breast cancer [1]. Breast conserving surgery (BCS) is a recommended surgical choice for women with early stage breast cancer (stages 0, I, II) and for those with Stage II-III disease who undergo successful neo-adjuvant treatment to reduce their tumor burden [2, 3]. Cancer within 2mm of a margin following BCS increases the risk of local recurrence and mortality [4-6]. Margin assessment presents an unmet clinical need. Breast tissue is markedly heterogeneous which makes identifying cancer foci within benign tissue challenging. Optical spectroscopy can provide surgeons with intra-operative diagnostic tools. Here, ex-vivo breast tissue is evaluated to determine which sources of optical contrast have the potential to detect malignancy at the margins in women of differing breast composition. Then, H&E images of ex-vivo breast tissue sites are quantified to further deconstruct the relationship between optical scattering and the underlying tissue morphology. </p><p>Diffuse reflectance spectra were measured from benign and malignant sites from the margins of lumpectomy specimens. Benign and malignant sites were compared and then stratified by tissue type and depth. The median and median absolute deviance (MAD) was calculated for each category. The frequencies of the benign tissue types were separated by menopausal status and compared to the corresponding optical properties. </p><p>H&E images were then taken of the malignant and benign sites and quantified to describe the % adipose, % collagen and % glands. Adipose sites, images at 10x, were predominantly fatty and quantified according to adipocyte morphology. H&E-stained adipose tissue sections were analyzed with an automated image processing algorithm to extract average cell area and cell density. Non-adipose sites were imaged with a 2.5x objective. Grids of 200µm boxes corresponding to the 3mm x 2mm area were overlaid on each non-adipose image. The non-adipose images were classified as the following: adipose and collagen (fibroadipose); collagen and glands (fibroglandular); adipose, collagen and glands (mixed); and malignant sites. Correlations between <&mus&#8242;> and % collagen in were determined in benign sites. Age, BMI, and MBD were then correlated to <&mus&#8242;> in the adipose and non-adipose sites. Variability in <&mus&#8242;> was determined to be related to collagen and not adipose content. In order to further investigate this relationship, the importance of age, BMI and MBD was analyzed after adjusting for the % collagen. Lastly, the relationship between % collagen and % glands was analyzed to determine the relative contributions of % collagen and % glands <&mus&#8242;>. Statistics were calculated using Wilcoxon rank-sum tests, Pearson correlation coefficients and linear fits in R. </p><p> The diagnostic ability of the optical parameters was linked to the distance of tumor from the margin as well as menopausal status. [THb] showed statistical differences from <&mus&#8242;> between malignant (<&mus&#8242;>: 8.96cm-1±2.24MAD, [THb]: 42.70&muM±29.31MAD) compared to benign sites (<&mus&#8242;>: 7.29cm-1±2.15MAD, [THb]: 32.09&muM±16.73MAD) (p<0.05). Fibroglandular (FG) sites exhibited increased <&mus&#8242;> while adipose sites showed increased [&beta-carotene] within benign tissues. Scattering differentiated between ductal carcinoma in situ (DCIS) (9.46cm-1±1.06MAD) and invasive ductal carcinoma (IDC) (8.00cm-1±1.81MAD), versus adipose sites (6.50cm-1±1.95MAD). [&beta-carotene] showed marginal differences between DCIS (19.00&muM±6.93MAD, and FG (15.30&muM±5.64MAD). [THb] exhibited statistical differences between positive sites (92.57&muM±18.46MAD) and FG (34.12&muM±22.77MAD), FA (28.63&muM±14.19MAD), and A (30.36&muM±14.86MAD). Due to decreased fibrous content and increased adipose content, benign sites in post-menopausal patients exhibited lower <&mus&#8242;>, but higher [&beta-carotene] than pre-menopausal patients.</p><p>Further deconstructing the relationship between optical scattering and tissue morphology resulted in a positive relationship between <&mus&#8242;> and % collagen (r=0.28, p=0.00034). Increased variability was observed in sites with a higher percentage of collagen. In adipose tissues MBD was negatively correlated with age (r=-0.19, p=0.006), BMI (r=-0.33, p=2.3e-6) and average cell area (r=-0.15, p=0.032) but positively related to the log of the average cell density (r=0.17, p=0.12). In addition, BMI was positively correlated to average cell area (r=0.31, p=1.2e-5) and negatively related to log of the cell density (r=-0.28, p=7.6e-5). In non-adipose sites, age was negatively correlated to <&mus&#8242;> in benign (r=-0.32, p=4.7e-5) and malignant (r=-0.32, p=1.4e-5) sites and this correlation varied significantly by the collagen level (r=-0.40 vs. -0.13). BMI was negatively correlated to <&mus&#8242;> in benign (r=-0.32, p=4e-5) and malignant (r=-0.31, p=2.8e-5) sites but this relationship did not vary by collagen level. MBD was positively correlated to <&mus&#8242;> in benign (r=0.22, p=0.01) and malignant (r=0.21, p=4.6e-3) sites. Optical scattering was shown to be tied to patient demographics. Lastly, the analysis of collagen vs. glands was narrowed to investigate sites with glands between 0-40% (the dynamic range of the data), the linear model reflected an equivalent relationship to scattering from % glands and the % collagen in benign sites (r=0.18 vs. r=0.17). In addition, the malignant sites showed a stronger positive relationship (r=0.64, p=0.005) to <&mus&#8242;> compared to the benign sites (r=0.52, p=0.03).</p><p>The data indicate that the ability of an optical parameter to differentiate benign from malignant breast tissues is dictated by patient demographics. Scattering differentiated between malignant and adipose sites and would be most effective in post-menopausal women. [&beta-carotene] or [THb] may be more applicable in pre-menopausal women to differentiate malignant from fibrous sites. Patient demographics are therefore an important component to incorporate into optical characterization of breast specimens. Through the subsequent stepwise analysis of tissue morphology, <&mus&#8242;> was positively correlated to collagen and negatively correlated to age and BMI. Increased variability of <&mus&#8242;> with collagen level was not dependent on the adipose contribution. A stronger correlation between age and <&mus&#8242;> was seen in high collagen sites compared to low collagen sites. Contributions from collagen and glands to <&mus&#8242;> were independent and equivalent in benign sites; glands showed a stronger correlation to <&mus&#8242;> in malignant sites than collagen. This information will help develop improved scattering models and additional technologies from separating fibroglandular sites from malignant sites and ultimately improve margin assessment.</p> / Dissertation

This study investigates the possibility of using a time-resolved Fluorescence and Diffuse Reflectance Spectroscopy (tr-FRS) system to define tumour surgical margins of invasive ducal carcinoma of breast. UV excitation light was used for the fluorescence component and data was collected from the 370-550 nm range. A broadband source was used for diffuse reflectance collection and the emitted response was in the 400-800 nm range. 40 matched pair cases were collected from patients undergoing breast conservation surgeries. Histological analysis was performed on each sample to determine the fat and tumour content within each normal and tumour sample respectively. Statistical analysis was performed on the optical data to reveal biochemical changes in the endogenous fluorophores collagen, reduced nicotinamide adenine dinucleotide (NADH), and flavin adenine dinucleotide (FAD) as well as changes in absorption and scattering properties attributed to variances in absorber concentrations and cell density respectively. Statistical significant differences in collagen, NADH, and FAD lifetimes, collagen, NADH, FAD and NADH/FAD intensity, diffuse reflectance and reduced scatter coefficient were observed between tumour and normal breast samples. These significant factors were used in Principle Component Analysis model construction and a binary classification scheme using Soft Independent Modeling of Class Analogy (SIMCA) was used as a classification tool to predict unknown breast samples as either normal or tumour with specificity of 60% and sensitivity slightly over 50%. / Thesis / Master of Science (MSc)

No description available.

<div> Advancements in cancer treatments have increased rapidly in recent years, but cures remain elusive. Surgical tumor resection is a central treatment for many solid malignancies. Residual tumor at surgical margins leads to tumor recurrence. Novel tools for assessing residual tumor at surgical margins could improve surgical outcomes by helping to maximize the extent of resection. Ambient ionization-mass spectrometry (MS) methods generate and analyze ions from minimally prepared samples in near-real-time (e.g. seconds to minutes). These methods leverage the high sensitivity and specificity of mass spectrometry for analyzing gas phase ions and generating those ions quickly and with minimal sample preparation. Recent work has shown that differential profiles of ions, corresponding to phospholipids and small metabolites, are detected from cancerous and their respective normal tissue with ambient ionization-MS methods. When properly implemented, ambient ionization-MS could be used to assess for tumor at surgical margins and provide a molecular diagnosis during surgery. </div><div><br></div><div>The research herein reports efforts in developing rapid intraoperative ambient ionization-MS methods for the molecular assessment of cancerous tissues. Touch spray (TS) ionization and desorption electrospray ionization (DESI) were utilized to analyze kidney cancer and brain cancer.</div><div><br></div><div> As a demonstration of the applicability of TS-MS to provide diagnostic information from fresh surgical tissues, TS-MS was used to rapidly analyze renal cell carcinoma and healthy renal tissue biopsies obtained from human subjects undergoing nephrectomy surgery. Differential phospholipid profiles were identified using principal component analysis (PCA), and the significant ions were characterized using multiple stages of mass spectrometry and high resolution/exact mass MS. The same TS-MS analyzed renal tissues were subsequently analyzed with DESI-MS imaging to corroborate the TS-MS results, and the significant DESI-MS ions were also characterized with MS.</div><div><br></div><div>Significant efforts were made in developing and evaluating a standalone intraoperative DESI-MS system for analyzing brain tissue biopsies during brain tumor surgery. The intraoperative DESI-MS system consists of a linear trap quadrupole mass spectrometer placed on a custom-machined cart that contains all hardware for operating the mass spectrometer. This instrument was operated in the neurosurgical suites at Indiana University School of Medicine to rapidly analyze brain tissue biopsies obtained from glioma resection surgeries. A DESI-MS library of normal brain tissue and glioma was used to statistically classify the brain tissue biopsies collected in the operating room. Multivariate statistical methodologies were employed to predict the disease state and tumor cell percentage of the samples. A DESI-MS assay for detecting 2-hydroxyglutarate (2HG), the oncometabolic product of the isocitrate dehydrogenase (IDH) mutation (a key glioma prognostic marker), was developed and applied to determine the IDH mutation status during the surgical resection. The strengths, weaknesses, and areas of future work in this field are discussed. </div><div><br></div>