Micro-Anatomical Quantitative Imaging Towards Enabling Automated Diagnosis of Thick Tissues at the Point of Care

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.

Localization of Metal Electrodes in the Intact Rat Brain Using Registration of 3D Microcomputed Tomography Images to a Magnetic Resonance Histology Atlas.

Simultaneous neural recordings taken from multiple areas of the rodent brain are garnering growing interest due to the insight they can provide about spatially distributed neural circuitry. The promise of such recordings has inspired great progress in methods for surgically implanting large numbers of metal electrodes into intact rodent brains. However, methods for localizing the precise location of these electrodes have remained severely lacking. Traditional histological techniques that require slicing and staining of physical brain tissue are cumbersome, and become increasingly impractical as the number of implanted electrodes increases. Here we solve these problems by describing a method that registers 3-D computerized tomography (CT) images of intact rat brains implanted with metal electrode bundles to a Magnetic Resonance Imaging Histology (MRH) Atlas. Our method allows accurate visualization of each electrode bundle's trajectory and location without removing the electrodes from the brain or surgically implanting external markers. In addition, unlike physical brain slices, once the 3D images of the electrode bundles and the MRH atlas are registered, it is possible to verify electrode placements from many angles by "re-slicing" the images along different planes of view. Further, our method can be fully automated and easily scaled to applications with large numbers of specimens. Our digital imaging approach to efficiently localizing metal electrodes offers a substantial addition to currently available methods, which, in turn, may help accelerate the rate at which insights are gleaned from rodent network neuroscience.

On the Origin of Natural Antibody

Natural IgM (nIgM) is constitutively present in the serum, where it aids in the early control of viral and bacterial expansions. nIgM also plays a significant role in the prevention of autoimmune disease by promoting the clearance of cellular debris. However, the cells that maintain high titers of nIgM in the circulation had not yet been identified. Several studies have linked serum nIgM with the presence of fetal-lineage B cells, and others have detected IgM secretion directly by B1a cells in various tissues. Nevertheless, a substantial contribution of undifferentiated B1 cells to nIgM titers is doubtful, as the ability to produce large quantities of antibody (Ab) is a function of the phenotype and morphology of differentiated plasma cells (PCs). No direct evidence exists to support the claim that a B1-cell population directly produces the bulk of circulating nIgM. The source of nIgM thus remained uncertain and unstudied.

In the first part of this study, I identified the primary source of nIgM. Using enzyme-linked immunosorbent spot (ELISPOT) assay, I determined that the majority of IgM Ab-secreting cells (ASCs) in naïve mice reside in the bone marrow (BM). Flow cytometric analysis of BM cells stained for intracellular IgM revealed that nIgM ASCs express IgM and the PC marker CD138 on their surface, but not the B1a cell marker CD5. By spinning these cells onto slides and staining them, following isolation by fluorescence-activated cell sorting (FACS), I found that they exhibit the typical morphological characteristics of terminally differentiated PCs. Transfer experiments demonstrated that BM nIgM PCs arise from a progenitor in the peritoneal cavity (PerC), but not isolated PerC B1a, B1b, or B2 cells. Immunoglobulin (Ig) gene sequence analysis and examination of B1-8i mice, which carry an Ig knockin that prohibits fetal B-cell development, indicated that nIgM PCs differentiate from fetal-lineage B cells. BrdU uptake experiments showed that the nIgM ASC compartment contains a substantial fraction of long-lived plasma cells (LLPCs). Finally, I demonstrated that nIgM PCs occupy a survival niche distinct from that used by IgG PCs.

In the second part of this dissertation, I characterized the unique survival niche of nIgM LLPCs, which maintain constitutive high titers of nIgM in the serum. By using genetically deficient or Ab-depleted mice, I found that neither T cells, type 2 innate lymphoid cells, nor mast cells, the three major hematopoietic producers of IL-5, were required for nIgM PC survival in the BM. However, IgM PCs associate strongly with IL-5-expressing BM stromal cells, which support their survival in vitro when stimulated. In vivo neutralization of IL-5 revealed that, like individual survival factors for IgG PCs, IL-5 is not the sole supporter of IgM PCs, but is likely one of several redundant molecules that together ensure uninterrupted signaling. Thus, the long-lived nIgM PC niche is not composed of hematopoietic sources of IL-5, but a stromal cell microenvironment that provides multiple redundant survival signals.

In the final part of my study, I identified and characterized the precursor of nIgM PCs, which I found in the first project to be resident in the PerC, but not a B1a, B1b, or B2 cell. By transferring PerC cells sorted based on expression of CD19, CD5, and CD11b, I found that only the CD19+CD5+CD11b- population contained cells capable of differentiating into nIgM PCs. Transfer of decreasing numbers of unfractionated PerC cells into Rag1 knockouts revealed an order-of-magnitude drop in the rate of serum IgM reconstitution between stochastically sampled pools of 106 and 3x105 PerC cells, suggesting that the CD19+CD5+CD11b- compartment comprises two cell types, and that interaction between the two necessary for nIgM-PC differentiation. By transferring neonatal liver, I determined that the early hematopoietic environment is required for nIgM PC precursors to develop. Using mice carrying a mutation that disturbs cKit expression, I also found that cKit appears to be required at a critical point near birth for the proper development of nIgM PC precursors.

The collective results of these studies demonstrate that nIgM is the product of BM-resident PCs, which differentiate from a PerC B cell precursor distinct from B1a cells, and survive long-term in a unique survival niche created by stromal cells. My work creates a new paradigm by which to understand nIgM, B1 cell, and PC biology.

Sparse Sample Detection Using Magnetic Bead Manipulation on a Digital Microfluidic Device

This thesis demonstrates a new way to achieve sparse biological sample detection, which uses magnetic bead manipulation on a digital microfluidic device. Sparse sample detection was made possible through two steps: sparse sample capture and fluorescent signal detection. For the first step, the immunological reaction between antibody and antigen enables the binding between target cells and antibody-­‐‑ coated magnetic beads, hence achieving sample capture. For the second step, fluorescent detection is achieved via fluorescent signal measurement and magnetic bead manipulation. In those two steps, a total of three functions need to work together, namely magnetic beads manipulation, fluorescent signal measurement and immunological binding. The first function is magnetic bead manipulation, and it uses the structure of current-­‐‑carrying wires embedded in the actuation electrode of an electrowetting-­‐‑on-­‐‑dielectric (EWD) device. The current wire structure serves as a microelectromagnet, which is capable of segregating and separating magnetic beads. The device can achieve high segregation efficiency when the wire spacing is 50µμm, and it is also capable of separating two kinds of magnetic beads within a 65µμm distance. The device ensures that the magnetic bead manipulation and the EWD function can be operated simultaneously without introducing additional steps in the fabrication process. Half circle shaped current wires were designed in later devices to concentrate magnetic beads in order to increase the SNR of sample detection. The second function is immunological binding. Immunological reaction kits were selected in order to ensure the compatibility of target cells, magnetic bead function and EWD function. The magnetic bead choice ensures the binding efficiency and survivability of target cells. The magnetic bead selection and binding mechanism used in this work can be applied to a wide variety of samples with a simple switch of the type of antibody. The last function is fluorescent measurement. Fluorescent measurement of sparse samples is made possible of using fluorescent stains and a method to increase SNR. The improved SNR is achieved by target cell concentration and reduced sensing area. Theoretical limitations of the entire sparse sample detection system is as low as 1 Colony Forming Unit/mL (CFU/mL).

Molecular characterization of chordoma xenografts generated from a novel primary chordoma cell source and two chordoma cell lines.

OBJECT: Chordoma cells can generate solid-like tumors in xenograft models that express some molecular characteristics of the parent tumor, including positivity for brachyury and cytokeratins. However, there is a dearth of molecular markers that relate to chordoma tumor growth, as well as the cell lines needed to advance treatment. The objective in this study was to isolate a novel primary chordoma cell source and analyze the characteristics of tumor growth in a mouse xenograft model for comparison with the established U-CH1 and U-CH2b cell lines. METHODS: Primary cells from a sacral chordoma, called "DVC-4," were cultured alongside U-CH1 and U-CH2b cells for more than 20 passages and characterized for expression of CD24 and brachyury. While brachyury is believed essential for driving tumor formation, CD24 is associated with healthy nucleus pulposus cells. Each cell type was subcutaneously implanted in NOD/SCID/IL2Rγ(null) mice. The percentage of solid tumors formed, time to maximum tumor size, and immunostaining scores for CD24 and brachyury (intensity scores of 0-3, heterogeneity scores of 0-1) were reported and evaluated to test differences across groups. RESULTS: The DVC-4 cells retained chordoma-like morphology in culture and exhibited CD24 and brachyury expression profiles in vitro that were similar to those for U-CH1 and U-CH2b. Both U-CH1 and DVC-4 cells grew tumors at rates that were faster than those for U-CH2b cells. Gross tumor developed at nearly every site (95%) injected with U-CH1 and at most sites (75%) injected with DVC-4. In contrast, U-CH2b cells produced grossly visible tumors in less than 50% of injected sites. Brachyury staining was similar among tumors derived from all 3 cell types and was intensely positive (scores of 2-3) in a majority of tissue sections. In contrast, differences in the pattern and intensity of staining for CD24 were noted among the 3 types of cell-derived tumors (p < 0.05, chi-square test), with evidence of intense and uniform staining in a majority of U-CH1 tumor sections (score of 3) and more than half of the DVC-4 tumor sections (scores of 2-3). In contrast, a majority of sections from U-CH2b cells stained modestly for CD24 (scores of 1-2) with a predominantly heterogeneous staining pattern. CONCLUSIONS: This is the first report on xenografts generated from U-CH2b cells in which a low tumorigenicity was discovered despite evidence of chordoma-like characteristics in vitro. For tumors derived from a primary chordoma cell and U-CH1 cell line, similarly intense staining for CD24 was observed, which may correspond to their similar potential to grow tumors. In contrast, U-CH2b tumors stained less intensely for CD24. These results emphasize that many markers, including CD24, may be useful in distinguishing among chordoma cell types and their tumorigenicity in vivo.

Stereocomplexes Formed From Select Oligomers of Polymer d-lactic Acid (PDLA) and l-lactate May Inhibit Growth of Cancer Cells and Help Diagnose Aggressive Cancers-Applications of the Warburg Effect.

It is proposed that select oligomers of polymer d-lactic acid (PDLA) will form a stereocomplex with l-lactate in vivo, producing lactate deficiency in tumor cells. Those cancer cells that utilize transport of lactate to maintain electrical neutrality may cease to multiply or die because of lactate trapping, and those cancer cells that benefit from utilization of extracellular lactate may be impaired. Intracellular trapping of lactate produces a different physiology than inhibition of LDH because the cell loses the option of shuttling pyruvate to an alternative pathway to produce an anion. Conjugated with stains or fluorescent probes, PDLA oligomers may be an agent for the diagnosis of tissue lactate and possibly cell differentiation in biopsy specimens. Preliminary experimental evidence is presented confirming that PDLA in high concentrations is cytotoxic and that l-lactate forms a presumed stereocomplex with PDLA. Future work should be directed at isolation of biologically active oligomers of PDLA.

Structured Illumination Microscopy and a Quantitative Image Analysis for the Detection of Positive Margins in a Pre-Clinical Genetically Engineered Mouse Model of Sarcoma.

Intraoperative assessment of surgical margins is critical to ensuring residual tumor does not remain in a patient. Previously, we developed a fluorescence structured illumination microscope (SIM) system with a single-shot field of view (FOV) of 2.1 × 1.6 mm (3.4 mm2) and sub-cellular resolution (4.4 μm). The goal of this study was to test the utility of this technology for the detection of residual disease in a genetically engineered mouse model of sarcoma. Primary soft tissue sarcomas were generated in the hindlimb and after the tumor was surgically removed, the relevant margin was stained with acridine orange (AO), a vital stain that brightly stains cell nuclei and fibrous tissues. The tissues were imaged with the SIM system with the primary goal of visualizing fluorescent features from tumor nuclei. Given the heterogeneity of the background tissue (presence of adipose tissue and muscle), an algorithm known as maximally stable extremal regions (MSER) was optimized and applied to the images to specifically segment nuclear features. A logistic regression model was used to classify a tissue site as positive or negative by calculating area fraction and shape of the segmented features that were present and the resulting receiver operator curve (ROC) was generated by varying the probability threshold. Based on the ROC curves, the model was able to classify tumor and normal tissue with 77% sensitivity and 81% specificity (Youden's index). For an unbiased measure of the model performance, it was applied to a separate validation dataset that resulted in 73% sensitivity and 80% specificity. When this approach was applied to representative whole margins, for a tumor probability threshold of 50%, only 1.2% of all regions from the negative margin exceeded this threshold, while over 14.8% of all regions from the positive margin exceeded this threshold.

Transsynaptic Tracing from Peripheral Targets with Pseudorabies Virus Followed by Cholera Toxin and Biotinylated Dextran Amines Double Labeling.

Transsynaptic tracing has become a powerful tool used to analyze central efferents that regulate peripheral targets through multi-synaptic circuits. This approach has been most extensively used in the brain by utilizing the swine pathogen pseudorabies virus (PRV)(1). PRV does not infect great apes, including humans, so it is most commonly used in studies on small mammals, especially rodents. The pseudorabies strain PRV152 expresses the enhanced green fluorescent protein (eGFP) reporter gene and only crosses functional synapses retrogradely through the hierarchical sequence of synaptic connections away from the infection site(2,3). Other PRV strains have distinct microbiological properties and may be transported in both directions (PRV-Becker and PRV-Kaplan)(4,5). This protocol will deal exclusively with PRV152. By delivering the virus at a peripheral site, such as muscle, it is possible to limit the entry of the virus into the brain through a specific set of neurons. The resulting pattern of eGFP signal throughout the brain then resolves the neurons that are connected to the initially infected cells. As the distributed nature of transsynaptic tracing with pseudorabies virus makes interpreting specific connections within an identified network difficult, we present a sensitive and reliable method employing biotinylated dextran amines (BDA) and cholera toxin subunit b (CTb) for confirming the connections between cells identified using PRV152. Immunochemical detection of BDA and CTb with peroxidase and DAB (3, 3'-diaminobenzidine) was chosen because they are effective at revealing cellular processes including distal dendrites(6-11).