Browsing by Subject "Biophotonics"

The development of non-invasive retinal imaging systems has revolutionized the care and treatment of patients in ophthalmology clinics. Using high-resolution modalities such as scanning laser ophthalmoscopy (SLO) and optical coherence tomography (OCT), physicians and vision scientists are able detect previously unseen features on the subject retina which can 1) provide information for diagnosis, 2) identify disease biomarkers, 3) inform treatment or clinical trial regimens, and 4) improve understanding of underlying disease processes. Traditional SLO and OCT devices are designed as tabletop systems which are unable to accommodate vulnerable populations including intrasurgical patients and young children. Thus, the miniaturization of these systems into compact, handheld form factors is of great interest in both biomedical optics/imaging and medical research fields as they are essential to the proper care of patients. Previous studies have shown that handheld systems are instrumental in assessing overall health of young children and disease progressions in subjects of all ages. However, handheld systems are limited in optical performance as hardware selection is restricted to components of small size and low weight. Additionally, aberrations induced by both the system optics and the human eye degrade the resolution of the images. This work focuses on the integration of adaptive optics (AO) technology into handheld form factors to correct for aberrations and provide in vivo visualization of single cells such as cone photoreceptors and retinal pigment epithelium cells. We present two devices which demonstrate the first ever dual-modality AO-SLO and AO-OCT handheld imaging devices that push the limits of comprehensive, cellular-resolution retinal imaging. Finally, we investigate the use of 3x3 fused fiber couplers as a simple, compact coherent receiver design. Our novel balanced-detection topology achieves shot-noise limited performance in the presence of excess noise and shows improved SNR as compared to previous implementations. We detail its ability to enable instantaneous quadrature projection for applications in LiDAR, phase imaging, and optical communications.

This dissertation research focused on the ways in which clear crustaceans with complex bodies (i.e. with hard cuticles, thick muscles, and other internal organs) maintain transparency across their entire body volume. I used transparent crustacean species that had relatively large (> 25 mm long and > 2 mm thick) bodies and that occupied physically different (pelagic vs. benthic reef) habitats. Studying these transparent crustaceans and making comparisons with closely related opaque crustaceans provided some of the first insights into the puzzling problem of the physical basis of transparency in whole organisms.

First, I examined the ultrastructure of the cuticle of hyperiid amphipods, the first surface to interact with light, to understand what features may minimize reflectance. I investigated the cuticle surfaces of seven species of mostly transparent hyperiids using scanning electron microscopy and found two previously undocumented features that reduced reflectance. I found that the legs of Cystisoma spp. were covered with an ordered array of nanoprotuberances that functioned optically as a gradient refractive index material to reduce reflections. Additionally, I found that Cystisoma and six other species of hyperiids were covered with a monolayer of homogenous nanospheres (approximately 50 nm to 350 nm in diameter) that were most likely bacteria. Optical modeling demonstrated that both the nanoprotuberances and the monolayers reduced reflectance by as much as 250-fold. Even though the models only considered surface reflectance and not internal light scattering, these models showed that the nanoprotuberances and spheres could improve crypsis in a featureless habitat where the smallest reflection could render an animal vulnerable to visual predation.

Second, I took a morphological approach to investigate how light scattering may be minimized internally. Using bright field microscopy, I explored whether there were any gross anatomical differences in the abdominal muscles between a transparent species of shrimp, Ancylomenes pedersoni, and a similarly sized opaque shrimp species, Lysmata wurdemanni. I found no differences in muscle fiber size or any other features. Using transmission electron microscopy (TEM) to visualize muscle ultrastructure, I found that the myofibrils of the transparent species were twice the diameter of the opaque species (mean values of 2.2 μm compared to 1.0 μm). Over a given distance of muscle, light passes through fewer myofibrils due to their larger diameter, with fewer opportunities for light to be scattered at the interfaces between the high-index myofibrillar lattice and the surrounding lower-index fluid-filled sarcoplasmic reticulum (SR). Additionally, because transparency is not always a static trait and can sometimes be disrupted after exercise or physiological stress, I compared the ultrastructure of muscle in transparent A. pedersoni shrimp with the ultrastructure of muscle in A. pedersoni that had temporarily turned opaque after exercise. I found that in this opacified tissue, the fluid-filled space around myofibrils had an increased thickness of 360 nm as compared to a normal thickness of 20 nm. While this could have been a fixation artifact, this result still suggests that opacified tissue had some change in osmolarity or increase in fluid. Models of light scattering across a range of thicknesses and possible refractive indices showed that this observed increase in fluid-filled space dramatically reduced transparency.

Third, I further investigated how exertion or physiological stress may disrupt transparency, what may occur in the tissues to cause this disruption, and what may explain the increased fluid-filled SR interface. I hypothesized that increased perfusion, or an increase in blood volume between muscle fibers, can disrupt the normal organization of tissue, resulting in increased light scattering. I measured pre- and post-exercise perfusion via the injection of a specific fluorescent stain (Alexa Fluor 594-labeled wheat germ agglutinin) that labeled the sarcolemmal areas in contact with hemolymph and the endothelial cells of the blood vessels, and found more open vessels and greater hemolymph perfusion around fibers post-exercise. Changing salinity in the shrimps’ tanks, wounding the shrimp, and injecting proctolin (a vasodilator) were also associated with increased opacity and perfusion. To visualize the shrimps’ overall muscle morphology, I used Diffusible Iodine-based Contrast-Enhanced Computed Tomography (DICECT) to scan one control (transparent) and one experimental (opaque) A. pedersoni. The resulting images added further support to my hypothesis that hemolymph volume in the muscle increases in post-exercise opacified A. pedersoni.

Breast conserving surgery (BCS) is a common treatment option for breast cancer patients. The goal of BCS is to remove the entire tumor from the breast while preserving as much normal tissue as possible for a better cosmetic outcome after surgery. Specifically, the excised specimen must have at least 2 mm of normal tissue surrounding the diseased mass. Unfortunately, a staggering 20-70% of patients undergoing BCS require repeated surgeries due to the incomplete removal of the tumor diagnosed post-operatively. Due to these high re-excision rates as well as limited post-operative histopathological sampling of the tumor specimen, there is an unmet clinical need for margin assessment. Quantitative diffuse reflectance spectral imaging has previously been explored as a promising, method for providing real-time visual maps of tissue composition to help surgeons determine breast tumor margins to ensure the complete removal of the disease during breast conserving surgery. We have leveraged the underlying sources of contrast in breast tissue, specifically total hemoglobin content, beta-carotene content, and tissue scattering, and developed various fiber optics based spectral imaging systems for this clinical application. Combined with a fast inverse Monte Carlo model of reflectance, previous studies have shown that this technology may be able to decrease re-excision rates for BCS. However, these systems, which all consist of a broadband source, fiber optics probes, an imaging spectrograph and a CCD, have severe limitations in system footprint, tumor area coverage, and speed for acquisition and analysis. The fiber based spectral imaging systems are not scalable to smaller designs that cover a large surveillance area at a very fast speed, which ultimately makes them impractical for use in the clinical environment. The objective of this dissertation was to design, develop, test, and show clinical feasibility of a novel wide field spectral imaging system that utilizes the same scientific principles of previously developed fiber optics based imaging systems, but improves upon the technical issues, such as size, complexity, and speed,to meet the demands of the intra-operative setting.

First, our simple re-design of the system completely eliminated the need for an imaging spectrograph and CCD by replacing them with an array of custom annular photodiodes. The geometry of the photodiodes were designed with the goal of minimizing optical crosstalk, maximizing SNR, and achieving the appropriate tissue sensing depth of up to 2 mm for tumor margin assessment. Without the imaging spectrograph and CCD, the system requires discrete wavelengths of light to launch into the tissue sample. A wavelength selection method that combines an inverse Monte Carlo model and a genetic algorithm was developed in order to optimize the wavelength choices specifically for the underlying breast tissue optical contrast. The final system design consisted of a broadband source with an 8-slot filter wheel containing the optimized set of wavelength choices, an optical light guide and quartz light delivery tube to send the 8 wavelengths of light in free space through the back apertures of each annular photodiode in the imaging array, an 8-channel integrating transimpedance amplifier circuit with a switch box and data acquisition card to collect the reflectance signal, and a laptop computer that controls all the components and analyzes the data.

This newly designed wide field spectral imaging system was tested in tissue-mimicking liquid phantoms and achieved comparable performance to previous clinically-validated fiber optics based systems in its ability to extract optical properties with high accuracy. The system was also tested in various biological samples, including a murine tumor model, porcine tissue, and human breast tissue, for the direct comparison with its fiber optics based counterparts. The photodiode based imaging system achieved comparable or better SNR, comparable extractions of optical properties extractions for all tissue types, and feasible improvements in speed and coverage for future iterations. We show proof of concept in performing fast, wide field spectral imaging with a simple, inexpensive design. With a reduction in size, cost, number of wavelengths used, and overall complexity, the system described by this dissertation allows for a more seamless scaling to higher pixel number and density in future iterations of the technology, which will help make this a clinically translatable tool for breast tumor margin assessment.

Alzheimer’s disease (AD) is a neurodegenerative disease currently affecting 5.8 million Americans and more than 50 million people worldwide. It is a progressive disease that destroys cognitive functions, leading to dementia. With increasing life-expectancy, important efforts have been made to clinically diagnose this age-related disease. However, definitive diagnosis of AD has been challenging, especially at an early stage, as there is a lack of quantifiable changes. Recently, many researchers have shown retinal changes as an extension of the brain pathology, leading to a window to study AD using fast and high-resolution retinal imaging tools. This dissertation will be focused on the development of low-cost imaging tools aimed to extract retinal biomarkers for AD. Specifically, the use of optical coherence tomography (OCT) and angle-resolved low-coherence interferometry (a/LCI) will be described, with steps leading to a combined optical system for retinal imaging in humans. OCT has already been established as the gold standard in ophthalmology due to its excellent axial resolution and high sensitivity. Similar to OCT, a/LCI is another interferometric technique that provides depth resolution. Previous work has supported the ability of a/LCI to retrieve depth-resolved light scattering measurements of nuclear morphology in dysplastic tissue. The use of OCT as image guidance for a/LCI can strengthen the technique, providing sample orientation as well as retinal layer segmentation to pinpoint a/LCI measurements. The dissertation starts with the development and clinical application of a low-cost OCT system. Despite the prevalence of OCT, its high-cost nature has limited its access to large eye centers and away from low-resource settings. Clinical feasibility of a complete low-cost OCT system will be evaluated, and its imaging performance compared to a commercial system. System design will be discussed, followed by a comprehensive image processing pipeline to characterize image quality for subsequent low-cost systems. The subsequent portions outline studies using a/LCI and the extraction of light scattering parameters in an AD mouse model. A benchtop co-registered system using a/LCI guided by OCT allowed measurements of depth-resolved light scattering measurements in an AD mouse retina model. Resulting parameters serve as unique quantification of AD tissue structure with potential to be translated to future human studies. A scanning mechanism for 2D a/LCI is also presented, which also allowed for the characterization of a/LCI sensitivity to anisotropic scattering that is often present in the complex retinal tissue. The last portion discusses the development of a second-generation low-cost OCT system which will be integrated in a combined imaging system for eventual AD studies in human patients. Several technical improvements are shown to facilitate clinical retinal imaging at the point-of-care. A characterization of this system in a small clinical study will illustrate the system’s capability to screen AD patients, and to serve as a morphological image guide for a clinical a/LCI system. Finally, a discussion of how the low-cost OCT system can be integrated to a multimodal imaging system for AD human retinal biomarker extraction will be provided.

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.

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.

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′> and % collagen in were determined in benign sites. Age, BMI, and MBD were then correlated to <&mus′> in the adipose and non-adipose sites. Variability in <&mus′> 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′>. Statistics were calculated using Wilcoxon rank-sum tests, Pearson correlation coefficients and linear fits in R.

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′> between malignant (<&mus′>: 8.96cm-1±2.24MAD, [THb]: 42.70&muM±29.31MAD) compared to benign sites (<&mus′>: 7.29cm-1±2.15MAD, [THb]: 32.09&muM±16.73MAD) (p<0.05). Fibroglandular (FG) sites exhibited increased <&mus′> 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′>, but higher [&beta-carotene] than pre-menopausal patients.

Further deconstructing the relationship between optical scattering and tissue morphology resulted in a positive relationship between <&mus′> 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′> 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′> 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′> 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′> compared to the benign sites (r=0.52, p=0.03).

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′> was positively correlated to collagen and negatively correlated to age and BMI. Increased variability of <&mus′> with collagen level was not dependent on the adipose contribution. A stronger correlation between age and <&mus′> was seen in high collagen sites compared to low collagen sites. Contributions from collagen and glands to <&mus′> were independent and equivalent in benign sites; glands showed a stronger correlation to <&mus′> 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.

The success of gene medicine ultimately depends on the efficient intracellular delivery and sustained expression of nucleic acid therapeutics, yet nonviral gene delivery performed with cationic polymer carriers has been chronically hindered by the slow release of nucleic acid payloads at their targets, as well as the transient nature of exogenous transgene expression. Polymer-nucleic acid nanocomplexes made with passive gene carriers using traditional bulk methods have proven inadequate for most translational applications. The objective of this work is to improve nonviral gene delivery through the selection, formulation, and application of improved nanoparticles.

After screening a number of number of cationic polymer delivery systems ranging from natural to synthetic, high molecular weight to low, binary and ternary, we identified a bioreducible linear poly(amido amine) able to give sustained, robust expression of both DNA and RNA through serial dosing. We next turned our attention to the process of nanocomplex assembly. Traditional assembly via bulk mixing is poorly controlled, and the poor quality of these nanocomplexes is a significant impediment to both the establishment of robust structure-function relationships and the advancement of nonviral gene delivery. So, we developed an emulsion-based microfluidic nanomanufacturing platform to better control the self-assembly process, and thus the physical properties of nanocomplexes. Confined mixing within picoliter droplets generates self-assembled nanocomplexes that are more uniform and more effective. This microfluidic nanomanufacturing approach possesses broad utility in the production of polymer-nucleic acid nanocomplexes; we demonstrated that its benefits extend to multiple gene carriers, a range of nucleic acid payloads, and translationally relevant cell types. Then, we applied the improved nanomanufactured particles to begin to address an unmet clinical need, namely the lack of a safe and ethical source of cells to treat neurodegenerative diseases. Nonviral cellular reprogramming strategies eliminate the integration of viral DNA sequences and represent a potentially safer alternative to viral transdifferentiation methods to generate therapeutic cells. Using nanomanufactured polymer-nucleic acid nanocomplexes, we improved the efficiency of the nonviral cellular reprogramming of fibroblasts directly to functional induced neuronal cells.

Nonviral gene therapy will continue to demand more sophisticated delivery systems to continue to progress. Microfluidic nanomanufacturing represents a reproducible and scalable platform to synthesize more uniform and effective nanocomplexes that not only improves their functional performance, but may also help establish clearer structure-function relationships that will inform future gene carrier design. Complementing the innovative chemical and biological approaches to create multifunctional nanoparticles, this study indicates that microfluidic nanomanufacturing can serve as a parallel physical strategy to both optimize the properties of polymer-nucleic acid nanocomplexes and improve their performance in applications with important clinical implications.

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.

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.

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.

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.

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.

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.

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.

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.

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.

\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.