Travis William Sawyer

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• Carlson, R., Comrie, C., Bonaventura, J., Morara, K., Daigle, N., Hutchinson, E., & Sawyer, T. W. (2025). Backscattering Mueller matrix polarimetry estimates microscale anisotropy and orientation in complex brain tissue structure. Journal of Medical Imaging, 12(Issue 1). doi:10.1117/1.jmi.12.1.016001
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  Purpose: Diffusion magnetic resonance imaging (dMRI) quantitatively estimates brain microstructure, diffusion tractography being one clinically utilized framework. To advance such dMRI approaches, direct quantitative comparisons between microscale anisotropy and orientation are imperative. Complete backscattering Mueller matrix polarized light imaging (PLI) enables the imaging of thin and thick tissue specimens to acquire numerous optical metrics not possible through conventional transmission PLI methods. By comparing complete PLI to dMRI within the ferret optic chiasm (OC), we may investigate the potential of this PLI technique as a dMRI validation tool and gain insight into the microstructural and orientational sensitivity of this imaging method in different tissue thicknesses. Approach: Post-mortem ferret brain tissue samples (whole brain, n ¼ 1 and OC, n ¼ 3) were imaged with both dMRI and complete backscattering Mueller matrix PLI. The specimens were sectioned and then reimaged with PLI. Region of interest and correlation analyses were performed on scalar metrics and orientation vectors of both dMRI and PLI in the coherent optic nerve and crossing chiasm. Results: Optical retardance and dMRI fractional anisotropy showed similar trends between metric values and were strongly correlated, indicating a bias to macroscale architecture in retardance. Thick tissue displays comparable orientation between the diattenuation angle and dMRI fiber orientation distribution glyphs that are not evident in the retardance angle. Conclusions: We demonstrate that backscattering Mueller matrix PLI shows potential as a tool for microstructural dMRI validation in thick tissue specimens. Performing complete polarimetry can provide directional characterization and potentially microscale anisotropy information not available by conventional PLI alone.
• Guan, S., Knapp, T., Alfonso-Garcia, A., Duan, S., & Sawyer, T. W. (2025). Optical phenotyping using label-free microscopy and deep learning. Annals of the Entomological Society of America, 2(Issue 3). doi:10.1117/1.bios.2.3.035001
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  Significance Tissue phenotyping plays a critical role in biomedical research and clinical applications by providing insight into the structural and functional characteristics of tissues that can characterize clinical behavior and identify therapeutic targets. However, conventional phenotyping techniques are destructive, time-intensive, and expensive, posing challenges for both efficiency and widespread use. Aim We aim to develop an optical phenotyping approach in pancreatic cancer specimens using label-free multiphoton microscopy combined with spatial transcriptomics and deep learning. Approach We measure and co-register a dataset comprised of spatial transcriptomics, autofluorescence, and second harmonic generation microscopy. We then cluster tissue subregions into meaningful phenotypes using transcriptomic signatures. We evaluate three different classification models to predict phenotype based on label-free imaging data, and we assess generalizability and prediction accuracy. Result Our deep-learning classification model achieves over 89% accuracy in classifying six tissue types using label-free microscopy images. The one-versus-rest area under the curve (AUC) values for all classes approach 1, confirming the robustness of our model. Conclusion We demonstrate the feasibility of optical phenotyping in distinguishing the structural and functional characteristics of pancreatic cancer specimens. Integrating additional gene-expression data or complementary label-free imaging modalities, such as fluorescence lifetime imaging microscopy, holds the potential to further enhance its accuracy and expand its applications in clinical research and diagnostics.
• Lima, N., Deleon, C. M., & Sawyer, T. W. (2025). Polarimetry through a flexible imaging fiber bundle with a pixelated polarizer. Biomedical Optics Express, 16(Issue 4). doi:10.1364/boe.554860
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  Polarization measurements of tissue in ex vivo and in vivo rigid laparoscopy studies have shown promise for enhancing diagnosis, guiding biopsies, and improving biological contrast compared to conventional imaging. However, a technological gap exists in performing polarization measurements through flexible endoscopes. The depolarization inherent in the coherent fiber bundles commonly used in these endoscopes to relay images from within the body hinders polarization information retrieval. To address this, we propose a simple, compact, and low-cost architecture: a pixelated polarizer placed directly on the tip of the flexible, coherent imaging fiber bundle. We demonstrate this architecture’s ability to retrieve the linear polarization properties of a scene.
• Magnus, J. H., Nguyen, L. T., Alevy, E. G., Sawyer, T. W., Crossley, S. D., & Kieu, K. (2025). Fifth-harmonic and five-photon excitation fluorescence multiphoton microscopy. Optics Letters, 50(Issue 12). doi:10.1364/ol.566910
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  We report the application of fifth-harmonic and five-photon excitation fluorescence multiphoton microscopy. This novel, to our knowledge, label-free imaging modality has been characterized with spectral and power dependence measurements. The advantages of fifth-harmonic and five-photon excitation fluorescence imaging are higher resolution and use of longer wavelength excitation sources, which may allow deeper penetration depth while still exciting near-UV to blue fluorophores. This imaging modality may find interesting applications in biological research, materials characterization, geologic studies, and semiconductor manufacturing.
• Montague, J. E., Hutchens, G. V., Howard, C. C., Rice, P. F., Besselsen, D. G., Slayton, M., Utzinger, U., Barton, J. K., & Sawyer, T. W. (2025). Multiphoton Microscopy Assessment of Healing From Tendon Laceration and Microthermal Coagula in a Rat Model. Lasers in Surgery and Medicine, 57(Issue 2). doi:10.1002/lsm.23871
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  Objectives: To study the healing response of rat Achilles tendon when lacerated or treated with intense therapeutic ultrasound (ITU) via utilization of multiphoton microscopy (MPM) imaging and histology. Materials and Methods: The right Achilles tendon of each Sprague Dawley rat within a cohort was partially lacerated. 1 to 2 days post-surgery, each rat received ITU treatment of the Achilles tendon on either the right or left leg. Rats were euthanized in groups at 1, 3, 7, 14, or 28 days posttreatment and their tendons were explanted, formalin fixed, paraffin embedded, sectioned, and placed on slides for imaging. Slides from each time point were imaged using a laboratory built MPM with a 780 nm Ti:Sapphire laser. The resulting second harmonic generation (SHG) and two-photon excited fluorescence (2PEF) signals were captured, assessed, and compared to brightfield microscopy images of the same section subsequently stained with hematoxylin and eosin. Results: At early timepoints, 2PEF images show the presence of red blood cells, infiltration of inflammatory cells and formation of a fibrin clot at laceration sites, and attraction of fibroblasts to ITU coagula. SHG images indicate an absence of organized collagen in both types of lesions. At later timepoints, new organized collagen can be seen at the laceration sites, and the concentration of inflammatory cells has noticeably decreased. Automated detection of red blood cells and infiltrative cells, as well as analysis of SHG signal intensity and homogeneity was performed at laceration locations. Results show that all quantities except SHG signal intensity approach normal values by day 28. Thus, combined analysis of 2PEF and SHG images elucidates tendon healing processes that align with and complement histological findings. Conclusion: These results indicate that multiphoton imaging can effectively visualize the healing response to mechanical (laceration) and thermal (ITU) injury, including the organization of new collagen which is more difficult to visualize with histology.
• Wende, M., Rothermel, F., Stilson, E., Kübler, F., Sawyer, T., Herkommer, A. M., & Toulouse, A. (2025). 3D-printed endo-microscope with a fast magnetic actuator for axial image plane scanning. Optics Letters, 50(Issue 7). doi:10.1364/ol.546292
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  Miniaturized endo-microscopes enable imaging with cellular resolution in hard-to-access, confined spaces. Femtosecond 3D-printing provides ultra-compact imaging optics (∅
• Barton, J. K., Nfonsam, V., Routh, J., Sawyer, T. W., Shir, H., Young, L., & Montague, J. (2024). Feasibility of non-imaging, random-sampling second harmonic generation measurements to distinguish colon cancer. Biophotonics Discovery, 1(3), 035001. doi:https://doi.org/10.1117/1.BIOS.1.3.035001
• Bonaventura, J., Morara, K., Carlson, R., Comrie, C., Twer, A., Hutchinson, E., & Sawyer, T. (2024). Evaluating backscattering polarized light imaging microstructural mapping capabilities through neural tissue and analogous phantom imaging. Journal of biomedical optics, 29(5). doi:10.1117/1.jbo.29.5.052914
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  Significance: Knowledge of fiber microstructure and orientation in the brain is critical for many applications. Polarized light imaging (PLI) has been shown to have potential for better understanding neural fiber microstructure and directionality due to the anisotropy in myelin sheaths surrounding nerve fibers of the brain. Continuing to advance backscattering based PLI systems could provide a valuable avenue for in vivo neural imaging. Aim: To assess the potential of backscattering PLI systems, the ability to resolve crossing fibers, and the sensitivity to fiber inclination and curvature are considered across different imaging wavelengths. Approach: Investigation of these areas of relative uncertainty is undergone through imaging potential phantoms alongside analogous regions of interest in fixed ferret brain samples with a five-wavelength backscattering Mueller matrix polarimeter. Results: Promising phantoms are discovered for which the retardance, diattenuation and depolarization mappings are derived from the Mueller matrix and studied to assess the sensitivity of this polarimeter configuration to fiber orientations and tissue structures. Conclusions: Rich avenues for future study include further classifying this polarimeter's sensitivity to fiber inclination and fiber direction to accurately produce microstructural maps of neural tissue.
• Comrie, C. J., Carlson, R., Ahsan, Z., Moshkriz, A., Sawyer, T. W., Intorcia, A. J., Serrano, G. E., Beach, T. G., & Hutchinson, E. B. (2024). Identification of diffusion, kurtosis, and propagator MRI markers of Alzheimer’s disease pathology in post-mortem human tissue. Imaging Neuroscience, 2. doi:10.1162/imag_a_00164
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  Alzheimer’s disease (AD) is an irreversible degenerative brain disease affecting 6.7 million Americans and while the hallmark AD pathologies of plaques and tangles follow a stereotyped progression during the course of the disease, clinical markers for early diagnosis are lacking and approximately 20% of all AD cases are ultimately misdiagnosed. Conventional clinical MRI is capable of reporting severe brain atrophy, but fails to recognize earlier biomarkers associated with more subtle cellular and molecular changes. Microstructural Magnetic Resonance Imaging (MRI) techniques are promising to address this challenge and may sensitively detect and distinguish tissue degeneration, tauopathies, and beta amyloid plaques to improve accuracy of diagnosis and enable early detection. The objective of this study was to identify and compare the most promising microstructural markers of AD pathology over a range of diffusion and relaxometry-based MRI techniques from conventional to advanced. To accomplish this, we performed MRI microscopy of post-mortem human temporal lobe specimens (n = 14) at high resolution and image quality and evaluated the relative influence of metrics across multiple microstructural MRI frameworks using principal component analysis (PCA). We performed additional correlation analysis between metrics identified by PCA and clinical neuropathology scores of Braak stage and plaque and tangle load. Hippocampal diffusion and restriction metrics contributed most to the first principal component, and the correlation with Braak score was positive for diffusivity and negative for restriction metrics. Additionally, the MAP-MRI propagator anisotropy (PA) metric of microscale anisotropy was strongly and negatively correlated with AD pathology while the conventional fractional anisotropy (FA) metric showed little or no correspondence and there was not a strong association between FA and PA by PCA. Entorhinal cortex findings were minimal except for reported increases in restriction due to plaque content. Taken together, our findings suggest that microstructural MRI metrics of restriction and diffusion are most prominent and may reflect degenerative processes in AD brain tissue and that microscale anisotropy may be more advantageous than conventional FA for the detection of subtle and earlier cellular changes in AD.
• Daigle, N., Guan, S., & Sawyer, T. (2024). Two-Photon Microscopy Yields a Clear Guide for Tumor Resection. Biophotonics International, 31(3).
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  Pancreatic cancer is one of the deadliest malignancies, with an average five-year survival rate of only 12[%]1. Surgical resection of the tumor is often the only realistic approach to saving a pancreatic cancer patient, but only if the malignant tissue can be completely removed.
• Duan, S., Sawyer, T. W., Witten, B. L., Song, H., Else, T., & Merchant, J. L. (2024). Spatial profiling reveals tissue‐specific neuro‐immune interactions in gastroenteropancreatic neuroendocrine tumors. The Journal of Pathology, 262(3), 362-376. doi:10.1002/path.6241
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  Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are heterogeneous malignancies that arise from complex cellular interactions within the tissue microenvironment. Here, we sought to decipher tumor-derived signals from the surrounding microenvironment by applying digital spatial profiling (DSP) to hormone-secreting and non-functional GEP-NETs. By combining this approach with in vitro studies of human-derived organoids, we demonstrated the convergence of cell autonomous immune and pro-inflammatory proteins that suggests their role in neuroendocrine differentiation and tumorigenesis. DSP was used to evaluate the expression of 40 neural- and immune-related proteins in surgically resected duodenal and pancreatic NETs (n = 20) primarily consisting of gastrinomas (18/20). A total of 279 regions of interest were examined between tumors, adjacent normal and abnormal-appearing epithelium, and the surrounding stroma. The results were stratified by tissue type and multiple endocrine neoplasia I (MEN1) status, whereas protein expression was validated by immunohistochemistry (IHC). A tumor immune cell autonomous inflammatory signature was further evaluated by IHC and RNAscope, while functional pro-inflammatory signaling was confirmed using patient-derived duodenal organoids. Gastrin-secreting and non-functional pancreatic NETs showed a higher abundance of immune cell markers and immune infiltrate compared with duodenal gastrinomas. Compared with non-MEN1 tumors, MEN1 gastrinomas and preneoplastic lesions showed strong immune exclusion and upregulated expression of neuropathological proteins. Despite a paucity of immune cells, duodenal gastrinomas expressed the pro-inflammatory and pro-neural factor IL-17B. Treatment of human duodenal organoids with IL-17B activated NF-κB and STAT3 signaling and induced the expression of neuroendocrine markers. In conclusion, multiplexed spatial protein analysis identified tissue-specific neuro-immune signatures in GEP-NETs. Duodenal gastrinomas are characterized by an immunologically cold microenvironment that permits cellular reprogramming and neoplastic transformation of the preneoplastic epithelium. Moreover, duodenal gastrinomas cell autonomously express immune and pro-inflammatory factors, including tumor-derived IL-17B, that stimulate the neuroendocrine phenotype. © 2024 The Pathological Society of Great Britain and Ireland.
• Knapp, T., Lima, N., Daigle, N., Duan, S., Merchant, J. L., & Sawyer, T. W. (2024). Combined flat-field and frequency filter approach to correcting artifacts of multichannel two-photon microscopy. Journal of Biomedical Optics, 29(Issue 1). doi:10.1117/1.jbo.29.1.016007
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  Significance: Multiphoton microscopy (MPM) is a useful biomedical imaging tool for its ability to probe labeled and unlabeled depth-resolved tissue biomarkers at high resolution. Automated MPM tile scanning allows for whole-slide image acquisition but can suffer from tile-stitching artifacts that prevent accurate quantitative data analysis. Aim: We have investigated postprocessing artifact correction methods using ImageJ macros and custom Python code. Quantitative and qualitative comparisons of these methods were made using whole-slide MPM autofluorescence and second-harmonic generation images of human duodenal tissue. Approach: Image quality after artifact removal is assessed by evaluating the processed image and its unprocessed counterpart using the root mean square error, structural similarity index, and image histogram measurements. Results: Consideration of both quantitative and qualitative results suggest that a combination of a custom flat-field-based correction and frequency filtering processing step provide improved artifact correction when compared with each method used independently to correct for tiling artifacts of tile-scan MPM images. Conclusions: While some image artifacts remain with these methods, further optimization of these processing steps may result in computational-efficient methods for removing these artifacts that are ubiquitous in large-scale MPM imaging. Removal of these artifacts with retention of the original image information would facilitate the use of this imaging modality in both research and clinical settings, where it is highly useful in collecting detailed morphologic and optical properties of tissue.
• Lima, N., & Sawyer, T. (2024). Roadmap to a large area multispectral fluorescence imaging system. Optical Engineering, 63(5). doi:10.1117/1.oe.63.5.055105
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  Significance: Multispectral fluorescence imaging (MSFI) is a technique that measures endogenous and exogenous tissue fluorescence to reveal crucial insights into underlying biological mechanisms. Developing well-characterized high-performance fluorescence imaging equipment is crucial to any clinical or research application. Considering the diverse range of clinical scenarios and ongoing research areas in biomedicine leveraging MSFI instrumentation, there is an evident and pressing need for comprehensive resources that detail the development of such tools. Aim: This study provides a template for developing an MSFI instrument by highlighting the development and verification of our instrumentation. We present the design roadmap alongside the development of a large-area MSFI instrument to measure tissue fluorescence and diffuse reflectance properties. Approach: We divide our design approach into four subsections, highlighting the important physical milestones: illumination, imaging, detection, and computation. Each subsection includes design considerations, the methods used to validate the performance, and finally, the results and discussion of the validation process. Results: We present the validation of the instrument across the illumination, imaging, detection, and computation subsystems. Two fluorophores are used to validate the instrument through serial dilution to establish a detection threshold and spectral capabilities limit. A mouse model expressing multi-colored fluorescent proteins is used to verify the multispectral performance. Conclusions: Our study lays out the groundwork for researchers to design and validate their own MSFI instrument. We present this alongside our instrument design to study fluorescence and diffuse reflectance properties of large-area tissues, such as murine or resected surgical specimens. Findings from the application of MSFI instrumentation can be translated to motivate and guide the design of fluorescence-based medical tools for the clinic or research environment.
• Taylor-Williams, M., Tao, R., Sawyer, T. W., Waterhouse, D. J., Yoon, J., & Bohndiek, S. E. (2024). Targeted multispectral filter array design for the optimization of endoscopic cancer detection in the gastrointestinal tract. Journal of Biomedical Optics, 29(03). doi:10.1117/1.jbo.29.3.036005
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  Significance: Color differences between healthy and diseased tissue in the gastrointestinal (GI) tract are detected visually by clinicians during white light endoscopy; however, the earliest signs of cancer are often just a slightly different shade of pink compared to healthy tissue making it hard to detect. Improving contrast in endoscopy is important for early detection of disease in the GI tract during routine screening and surveillance. Aim: We aim to target alternative colors for imaging to improve contrast using custom multispectral filter arrays (MSFAs) that could be deployed in an endoscopic “chip-on-tip” configuration. Approach: Using an open-source toolbox, Opti-MSFA, we examined the optimal design of MSFAs for early cancer detection in the GI tract. The toolbox was first extended to use additional classification models (k-nearest neighbor, support vector machine, and spectral angle mapper). Using input spectral data from published clinical trials examining the esophagus and colon, we optimized the design of MSFAs with three to nine different bands. Results: We examined the variation of the spectral and spatial classification accuracies as a function of the number of bands. The MSFA configurations tested showed good classification accuracies when compared to the full hyperspectral data available from the clinical spectra used in these studies. Conclusion: The ability to retain good classification accuracies with a reduced number of spectral bands could enable the future deployment of multispectral imaging in an endoscopic chip-on-tip configuration using simplified MSFA hardware. Further studies using an expanded clinical dataset are needed to confirm these findings.
• Daigle, N., Duan, S., Song, H., Lima, N., Sontz, R., Merchant, J. L., & Sawyer, T. W. (2023). Wide field-of-view fluorescence imaging for organ-level lineage tracing of rare intestinal stem cell populations. Journal of Biomedical Optics, 28(09). doi:10.1117/1.jbo.28.9.096004
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  Significance: Lineage tracing using fluorescent reporters is a common tool for monitoring the expression of genes and transcription factors in stem cell populations and their progeny. The zinc-binding protein 89 (ZBP-89/Zfp148 mouse gene) is a transcription factor that plays a role in gastrointestinal (GI) stem cell maintenance and cellular differentiation and has been linked to the progression of colon cancer. While lineage tracing is a useful tool, it is commonly performed with high-magnification microscopy on a small field of view within tissue sections, thereby limiting the ability to resolve reporter expression at the organ level. Furthermore, this technique requires extensive tissue processing, which is time consuming and requires euthanizing the animal. Further knowledge could be elucidated by measuring the expression of fluorescent reporters across entire organs with minimal tissue processing. Aim: We present the application of wide-field fluorescence imaging for whole-organ lineage tracing of an inducible Zfp148-tdTomato-expressing transgenic mouse line to assess the expression of ZBP-89/Zfp148 in the GI tract. Approach: We measured tdTomato fluorescence in ex vivo organs at time points between 24 h and 6 months post-induction. Fluctuations in tdTomato expression were validated by fluorescence microscopy of tissue sections. Results: Quantification of the wide field-of-view images showed a statistically significant increase in fluorescent signal across the GI tract between transgenic mice and littermate controls. The results also showed a gradient of decreasing reporter expression from proximal to distal intestine, suggesting a higher abundance of ZBP- 89 expressing stem cells, or higher expression of ZBP-89 within the stem cells, in the proximal intestine. Conclusions: We demonstrate that wide-field fluorescence imaging is a valuable tool for monitoring whole-organ expression of fluorescent reporters. This technique could potentially be applied in vivo for longitudinal assessment of a single animal, further enhancing our ability to resolve rare stem cell lineages spatially and temporally.
• Duan, S., Sheriff, S., Elvis-Offiah, U. B., Witten, B. L., Sawyer, T. W., Sundaresan, S., Cierpicki, T., Grembecka, J., & Merchant, J. L. (2023). Clinically Defined Mutations in MEN1 Alter Its Tumor-suppressive Function Through Increased Menin Turnover. Cancer Research Communications, 3(7), 1318-1334. doi:10.1158/2767-9764.crc-22-0522
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  Loss of the tumor suppressor protein menin is a critical event underlying the formation of neuroendocrine tumors (NET) in hormone-expressing tissues including gastrinomas. While aberrant expression of menin impairs its tumor suppression, few studies explore the structure–function relationship of clinical multiple endocrine neoplasia, type 1 (MEN1) mutations in the absence of a complete LOH at both loci. Here, we determined whether clinical MEN1 mutations render nuclear menin unstable and lead to its functional inactivation. We studied the structural and functional implications of two clinical MEN1 mutations (R516fs, E235K) and a third variant (A541T) recently identified in 10 patients with gastroenteropancreatic (GEP)-NETs. We evaluated the subcellular localization and half-lives of the mutants and variant in Men1-null mouse embryo fibroblast cells and in hormone-expressing human gastric adenocarcinoma and NET cell lines. Loss of menin function was assessed by cell proliferation and gastrin gene expression assays. Finally, we evaluated the effect of the small-molecule compound MI-503 on stabilizing nuclear menin expression and function in vitro and in a previously reported mouse model of gastric NET development. Both the R516fs and E235K mutants exhibited severe defects in total and subcellular expression of menin, and this was consistent with reduced half-lives of these mutants. Mutated menin proteins exhibited loss of function in suppressing tumor cell proliferation and gastrin expression. Treatment with MI-503 rescued nuclear menin expression and attenuated hypergastrinemia and gastric hyperplasia in NET-bearing mice. Clinically defined MEN1 mutations and a germline variant confer pathogenicity by destabilizing nuclear menin expression. Significance: We examined the function of somatic and germline mutations and a variant of MEN1 sequenced from gastroenteropancreatic NETs. We report that these mutations and variant promote tumor cell growth and gastrin expression by rendering menin protein unstable and prone to increased degradation. We demonstrate that the menin-MLL (mixed lineage leukemia) inhibitor MI-503 restores menin protein expression and function in vitro and in vivo, suggesting a potential novel therapeutic approach to target MEN1 GEP-NETs.
• Knapp, T. G., Duan, S., Merchant, J. L., & Sawyer, T. W. (2023). Quantitative characterization of duodenal gastrinoma autofluorescence using multiphoton microscopy. Lasers in Surgery and Medicine, 55(Issue 2). doi:10.1002/lsm.23619
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  Background: Duodenal gastrinomas (DGASTs) are neuroendocrine tumors that develop in the submucosa of the duodenum and produce the hormone gastrin. Surgical resection of DGASTs is complicated by the small size of these tumors and the tendency for them to develop diffusely in the duodenum. Endoscopic mucosal resection of DGASTs is an increasingly popular method for treating this disease due to its low complication rate but suffers from poor rates of pathologically negative margins. Multiphoton microscopy can capture high-resolution images of biological tissue with contrast generated from endogenous fluorescence (autofluorescence [AF]) through two-photon excited fluorescence (2PEF). Second harmonic generation is another popular method of generating image contrast with multiphoton microscopy (MPM) and is a light-scattering phenomenon that occurs predominantly from structures such as collagen in biological samples. Some molecules that contribute to AF change in abundance from processes related to the cancer disease process (e.g., metabolic changes, oxidative stress, and angiogenesis). Study Design/Materials and Methods: MPM was used to image 12 separate patient samples of formalin-fixed and paraffin-embedded duodenal gastrinoma slides with a second-harmonic generation (SHG) channel and four 2PEF channels. The excitation and emission profiles of each 2PEF channel were tuned to capture signal dominated by distinct fluorophores with well-characterized fluorescent spectra and known connections to the physiologic changes that arise in cancerous tissue. Results: We found that there was a significant difference in the relative abundance of signal generated in the 2PEF channels for regions of DGASTs in comparison to the neighboring tissues of the duodenum. Data generated from texture feature extraction of the MPM images were used in linear discriminant analysis models to create classifiers for tumor versus all other tissue types before and after principal component analysis (PCA). PCA improved the classifier accuracy and reduced the number of features required to achieve maximum accuracy. The linear discriminant classifier after PCA distinguished between tumor and other tissue types with an accuracy of 90.6%−93.8%. Conclusions: These results suggest that multiphoton microscopy 2PEF and SHG imaging is a promising label-free method for discriminating between DGASTs and normal duodenal tissue which has implications for future applications of in vivo assessment of resection margins with endoscopic MPM.
• Bonaventura, J., Morara, K., Carlson, R., Comrie, C., Daigle, N., Hutchinson, E., & Sawyer, T. (2022). Backscattering Mueller Matrix polarimetry on whole brain specimens shows promise for minimally invasive mapping of microstructural orientation features. Frontiers in Photonics, 3. doi:10.3389/fphot.2022.1034739
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  Understanding microscale physiology and microstructural cellular features of the brain is key to understanding mechanisms of neurodegenerative diseases and injury, as well as prominent changes undergone in development and aging. Non-invasive imaging modalities sensitive to the microscale, especially diffusion magnetic resonance imaging (dMRI), are promising for mapping of cellular microstructure of brain tissues; however, there is a need for robust validation techniques to verify and improve the biological accuracy of information derived. Recent advances in dMRI have moved toward probing of the more complex grey matter architecture, challenging current validation techniques, which are largely based on ex vivo staining and microscopy focusing on white matter. Polarized light imaging (PLI) has been shown to be successful for high resolution, direct, microstructural imaging and has been applied to dMRI validation with clear advantages over staining and microscopy techniques. Conventionally, PLI is applied to thin, sectioned samples in transmission mode, but PLI has also been extended to operate in reflectance mode to bridge the gap toward in vivo measurements of the brain. In this report we investigate the use of backscattering Mueller Matrix polarimetry to characterize the microstructural content of intact ferret brain specimens. The results show that backscattering polarimetry can probe white matter fiber coherence and fiber orientation, and show promise for probing grey matter microstructure. Ultimately, this motivates further study to fully understand how best to implement backscattering polarimetry for in vivo microstructural imaging of the brain.
• Duan, S., Sawyer, T. W., Sontz, R. A., Wieland, B. A., Diaz, A. F., & Merchant, J. L. (2022). GFAP-directed Inactivation of Men1 Exploits Glial Cell Plasticity in Favor of Neuroendocrine Reprogramming. Cellular and molecular gastroenterology and hepatology, 14(5), 1025-1051.
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  Efforts to characterize the signaling mechanisms that underlie gastroenteropancreatic neoplasms (GEP-NENs) are precluded by a lack of comprehensive models that recapitulate pathogenesis. Investigation into a potential cell-of-origin for gastrin-secreting NENs revealed a non-cell autonomous role for loss of menin in neuroendocrine cell specification, resulting in an induction of gastrin in enteric glia. Here, we investigated the hypothesis that cell autonomous Men1 inactivation in glial fibrillary acidic protein (GFAP)-expressing cells induced neuroendocrine differentiation and tumorigenesis.
• Knapp, T. G., Duan, S., Merchant, J. L., & Sawyer, T. W. (2022). Quantitative characterization of duodenal gastrinoma autofluorescence using multiphoton microscopy. Lasers in surgery and medicine.
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  Duodenal gastrinomas (DGASTs) are neuroendocrine tumors that develop in the submucosa of the duodenum and produce the hormone gastrin. Surgical resection of DGASTs is complicated by the small size of these tumors and the tendency for them to develop diffusely in the duodenum. Endoscopic mucosal resection of DGASTs is an increasingly popular method for treating this disease due to its low complication rate but suffers from poor rates of pathologically negative margins. Multiphoton microscopy can capture high-resolution images of biological tissue with contrast generated from endogenous fluorescence (autofluorescence [AF]) through two-photon excited fluorescence (2PEF). Second harmonic generation is another popular method of generating image contrast with multiphoton microscopy (MPM) and is a light-scattering phenomenon that occurs predominantly from structures such as collagen in biological samples. Some molecules that contribute to AF change in abundance from processes related to the cancer disease process (e.g., metabolic changes, oxidative stress, and angiogenesis).
• Sawyer, T. W., Taylor-Williams, M., Tao, R., Xia, R., Williams, C., & Bohndiek, S. E. (2022). Opti-MSFA: a toolbox for generalized design and optimization of multispectral filter arrays. Optics express, 30(5), 7591-7611.
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  Multispectral imaging captures spatial information across a set of discrete spectral channels and is widely utilized across diverse applications such as remote sensing, industrial inspection, and biomedical imaging. Multispectral filter arrays (MSFAs) are filter mosaics integrated atop image sensors that facilitate cost-effective, compact, snapshot multispectral imaging. MSFAs are pre-configured based on application-where filter channels are selected corresponding to targeted absorption spectra-making the design of optimal MSFAs vital for a given application. Despite the availability of many design and optimization approaches for spectral channel selection and spatial arrangement, major limitations remain. There are few robust approaches for joint spectral-spatial optimization, techniques are typically only applicable to limited datasets and most critically, are not available for general use and improvement by the wider community. Here, we reconcile current MSFA design techniques and present Opti-MSFA: a Python-based open-access toolbox for the centralized design and optimization of MSFAs. Opti-MSFA incorporates established spectral-spatial optimization algorithms, such as gradient descent and simulated annealing, multispectral-RGB image reconstruction, and is applicable to user-defined input of spatial-spectral datasets or imagery. We demonstrate the utility of the toolbox by comparing against other published MSFAs using the standard hyperspectral datasets Samson and Jasper Ridge, and further show application on experimentally acquired fluorescence imaging data. In conjunction with end-user input and collaboration, we foresee the continued development of Opti-MSFA for the benefit of the wider research community.
• Schwartz, D., Sawyer, T. W., Thurston, N., Barton, J., & Ditzler, G. (2022). Ovarian cancer detection using optical coherence tomography and convolutional neural networks. Neural computing & applications, 34(11), 8977-8987.
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  Ovarian cancer has the sixth-largest fatality rate in the United States among all cancers. A non-surgical assay capable of detecting ovarian cancer with acceptable sensitivity and specificity has yet to be developed. However, such a discovery would profoundly impact the pace of the treatment and improvement to patients' quality of life. Achieving such a solution requires high-quality imaging, image processing, and machine learning to support an acceptably robust automated diagnosis. In this work, we propose an automated framework that learns to identify ovarian cancer in transgenic mice from optical coherence tomography (OCT) recordings. Classification is accomplished using a neural network that perceives spatially ordered sequences of tomograms. We present three neural network-based approaches, namely a VGG-supported feed-forward network, a 3D convolutional neural network, and a convolutional LSTM (Long Short-Term Memory) network. Our experimental results show that our models achieve a favorable performance with no manual tuning or feature crafting, despite the challenging noise inherent in OCT images. Specifically, our best performing model, the convolutional LSTM-based neural network, achieves a mean AUC (± standard error) of 0.81 ± 0.037. To the best of the authors' knowledge, no application of machine learning to analyze depth-resolved OCT images of whole ovaries has been documented in the literature. A significant broader impact of this research is the potential transferability of the proposed diagnostic system from transgenic mice to human organs, which would enable medical intervention from early detection of an extremely deadly affliction.
• Slomka, B., Duan, S., Knapp, T. G., Lima, N., Sontz, R., Merchant, J. L., & Sawyer, T. W. (2022). Design, fabrication, and preclinical testing of a miniaturized, multispectral, chip-on-tip, imaging probe for intraluminal fluorescence imaging of the gastrointestinal tract. Frontiers in Photonics, 3. doi:10.3389/fphot.2022.1067651
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  Gastrointestinal cancers continue to account for a disproportionately large percentage of annual cancer deaths in the United States. Advancements in miniature imaging technology combined with a need for precise and thorough tumor detection in gastrointestinal cancer screenings fuel the demand for new, small-scale, and low-cost methods of localization and margin identification with improved accuracy. Here, we report the development of a miniaturized, chip-on-tip, multispectral, fluorescence imaging probe designed for compatibility with a gastroscope working channel with the aim of detecting cancerous lesions in point-of-care endoscopy of the gastrointestinal lumen. Preclinical testing has confirmed fluorescence sensitivity and supports that this miniature probe can locate structures of interest via detection of fluorescence emission from exogenous contrast agents. This work demonstrates the design and preliminary performance evaluation of a miniaturized, single-use, chip-on-tip fluorescence imaging system, capable of detecting multiplexed fluorophores, and devised for deployment via the accessory channel of a standard gastroscope.
• Taylor-Williams, M., Mead, S., Sawyer, T. W., Hacker, L., Williams, C., Berks, M., Murray, A., & Bohndiek, S. E. (2022). Multispectral imaging of nailfold capillaries using light-emitting diode illumination. Journal of biomedical optics, 27(12), 126002.
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  The capillaries are the smallest blood vessels in the body, typically imaged using video capillaroscopy to aid diagnosis of connective tissue diseases, such as systemic sclerosis. Video capillaroscopy allows visualization of morphological changes in the nailfold capillaries but does not provide any physiological information about the blood contained within the capillary network. Extracting parameters such as hemoglobin oxygenation could increase sensitivity for diagnosis and measurement of microvascular disease progression.
• Kiekens, K. C., Vega, D., Thurgood, H. T., Galvez, D., McGregor, D. J., Sawyer, T. W., & Barton, J. K. (2021). Effect of an Added Mass on the Vibration Characteristics for Raster Scanning of a Cantilevered Optical Fiber. Journal of engineering and science in medical diagnostics and therapy, 4(2), 021007.
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  Piezoelectric tube actuators with cantilevered optical fibers have enabled the miniaturization of scanning image acquisition techniques for endoscopic implementation. To achieve raster scanning for such a miniaturized system, the first resonant frequency should be of the order of 10 s of Hz. We explore adding a mass at an intermediate location along the length of the fiber to alter the resonant frequencies of the system. We provide a mathematical model to predict resonant frequencies for a cantilevered beam with an intermediate mass. The theoretical and measured data match well for various fiber lengths, mass sizes, and mass attachment locations along the fiber.
• Sawyer, D. M., Sawyer, T. W., Eshghi, N., Hsu, C., Hamilton, R. J., Garland, L. L., & Kuo, P. H. (2021). Pilot Study: Texture Analysis of PET Imaging Demonstrates Changes in F-FDG Uptake of the Brain After Prophylactic Cranial Irradiation. Journal of nuclear medicine technology, 49(1), 34-38.
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  Prophylactic cranial irradiation (PCI) is used to decrease the probability of developing brain metastases in patients with small cell lung cancer and has been linked to deleterious cognitive effects. Although no well-established imaging markers for these effects exist, previous studies have shown that structural and metabolic changes in the brain can be detected with MRI and PET. This study used an image processing technique called texture analysis to explore whether global changes in brain glucose metabolism could be characterized in PET images. F-FDG PET images of the brain from patients with small cell lung cancer, obtained before and after the administration of PCI, were processed using texture analysis. Texture features were compared between the pre- and post-PCI images. Multiple texture features demonstrated statistically significant differences before and after PCI when texture analysis was applied to the brain parenchyma as a whole. Regional differences were also seen but were not statistically significant. Global changes in brain glucose metabolism occur after PCI and are detectable using advanced image processing techniques. These changes may reflect radiation-induced damage and thus may provide a novel method for studying radiation-induced cognitive impairment.
• Fitzpatrick, C. R., Wilson, A., Sawyer, T. W., Christopher, P. J., Wilkinson, T. D., Bohndiek, S. E., & Gordon, G. S. (2020). Robustness to misalignment of low-cost, compact quantitative phase imaging architectures. OSA continuum, 3(10), 2660-2679.
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  Non-interferometric approaches to quantitative phase imaging could enable its application in low-cost, miniaturised settings such as capsule endoscopy. We present two possible architectures and both analyse and mitigate the effect of sensor misalignment on phase imaging performance. This is a crucial step towards determining the feasibility of implementing phase imaging in a capsule device. First, we investigate a design based on a folded 4f correlator, both in simulation and experimentally. We demonstrate a novel technique for identifying and compensating for axial misalignment and explore the limits of the approach. Next, we explore the implications of axial and transverse misalignment, and of manufacturing variations on the performance of a phase plate-based architecture, identifying a clear trade-off between phase plate resolution and algorithm convergence time. We conclude that while the phase plate architecture is more robust to misalignment, both architectures merit further development with the goal of realising a low-cost, compact system for applying phase imaging in capsule endoscopy.
• Sawyer, T. W., Koevary, J. W., Howard, C. C., Austin, O. J., Rice, P. F., Hutchens, G. V., Chambers, S. K., Connolly, D. C., & Barton, J. K. (2020). Fluorescence and Multiphoton Imaging for Tissue Characterization of a Model of Postmenopausal Ovarian Cancer. Lasers in surgery and medicine, 52(10), 993-1009.
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  To determine the efficacy of targeted fluorescent biomarkers and multiphoton imaging to characterize early changes in ovarian tissue with the onset of cancer.
• Vega, D., Sawyer, T. W., Pham, N. Y., & Barton, J. K. (2020). Use of embedded and patterned dichroic surfaces with reflective optical power to enable multiple optical paths in a micro-objective. Applied optics, 59(22), G71-G78.
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  We demonstrate the use of patterned dichroic surfaces with reflective optical power to create multiple optical paths in a single lens system. The application of these surfaces enables a micro-endoscope to accommodate multiple imaging technologies with only one optical system, making the packaging more compact and reliable. The optical paths are spectrally separated using different wavelengths for each path. The dichroic surfaces are designed such that the visible wavelengths transmit through the surfaces optically unaffected, but the near-infrared wavelengths are reflected in a telescope-like configuration with the curved dichroic surfaces providing reflective optical power. We demonstrate wide-field visible monochromatic imaging and microscopic near-infrared imaging using the same set of lenses. The on-axis measured resolution of the wide-field imaging configuration is approximately 14 µm, and the measured resolution of the microscopic imaging configuration is approximately 2 µm. Wide-field white-light imaging of an object is also demonstrated for a qualitative perspective on the imaging capabilities. Other configurations and applications in fields such as optical metrology are discussed to expand on the versatility of the demonstrated optical system.
• Zhao, L. L., Tronsgaard, R., Trahan, R., Szymkowiak, A. E., Shao, M., Sawyer, T. W., Sawyer, D. M., Riva, M., Petersburg, R. R., Pawluczyk, R., Pariani, G., Ong, J. M., Nemati, B., Mccracken, T. M., Llama, J., Leet, C., Jurgenson, C. A., Genoni, M., Fournier, P., , Fischer, D. A., et al. (2020). Performance Verification of the EXtreme PREcision Spectrograph. The Astronomical Journal, 159(5), 238. doi:10.3847/1538-3881/ab811d
• Gordon, G. S., Joseph, J., Alcolea, M. P., Sawyer, T., Williams, C., Fitzpatrick, C. R., Jones, P. H., di Pietro, M., Fitzgerald, R. C., Wilkinson, T. D., & Bohndiek, S. E. (2019). Quantitative phase and polarization imaging through an optical fiber applied to detection of early esophageal tumorigenesis. Journal of biomedical optics, 24(12), 1-13.
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  Phase and polarization of coherent light are highly perturbed by interaction with microstructural changes in premalignant tissue, holding promise for label-free detection of early tumors in endoscopically accessible tissues such as the gastrointestinal tract. Flexible optical multicore fiber (MCF) bundles used in conventional diagnostic endoscopy and endomicroscopy scramble phase and polarization, restricting clinicians instead to low-contrast amplitude-only imaging. We apply a transmission matrix characterization approach to produce full-field images of amplitude, quantitative phase, and resolved polarimetric properties through an MCF. We first demonstrate imaging and quantification of biologically relevant amounts of optical scattering and birefringence in tissue-mimicking phantoms. We present an entropy metric that enables imaging of phase heterogeneity, indicative of disordered tissue microstructure associated with early tumors. Finally, we demonstrate that the spatial distribution of phase and polarization information enables label-free visualization of early tumors in esophageal mouse tissues, which are not identifiable using conventional amplitude-only information.
• Gordon, G. S., Joseph, J., Sawyer, T., Macfaden, A. J., Williams, C., Wilkinson, T. D., & Bohndiek, S. E. (2019). Full-field quantitative phase and polarisation-resolved imaging through an optical fibre bundle. Optics express, 27(17), 23929-23947.
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  Flexible optical fibres, used in conventional medical endoscopy and industrial inspection, scramble phase and polarisation information, restricting users to amplitude-only imaging. Here, we exploit the near-diagonality of the multi-core fibre (MCF) transmission matrix in a parallelised fibre characterisation architecture, enabling accurate imaging of quantitative phase (error
• Sawyer, T. W., Koevary, J. W., Rice, F. P., Howard, C. C., Austin, O. J., Connolly, D. C., Cai, K. Q., & Barton, J. K. (2019). Quantification of multiphoton and fluorescence images of reproductive tissues from a mouse ovarian cancer model shows promise for early disease detection. Journal of biomedical optics, 24(9), 1-16.
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  Ovarian cancer is the deadliest gynecologic cancer due predominantly to late diagnosis. Early detection of ovarian cancer can increase 5-year survival rates from 40% up to 92%, yet no reliable early detection techniques exist. Multiphoton microscopy (MPM) is a relatively new imaging technique sensitive to endogenous fluorophores, which has tremendous potential for clinical diagnosis, though it is limited in its application to the ovaries. Wide-field fluorescence imaging (WFI) has been proposed as a complementary technique to MPM, as it offers high-resolution imagery of the entire organ and can be tailored to target specific biomarkers that are not captured by MPM imaging. We applied texture analysis to MPM images of a mouse model of ovarian cancer. We also conducted WFI targeting the folate receptor and matrix metalloproteinases. We find that texture analysis of MPM images of the ovary can differentiate between genotypes, which is a proxy for disease, with high statistical significance (p 
• Sawyer, T. W., Rice, P. F., Sawyer, D. M., Koevary, J. W., & Barton, J. K. (2019). Evaluation of segmentation algorithms for optical coherence tomography images of ovarian tissue. Journal of medical imaging (Bellingham, Wash.), 6(1), 014002.
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  Ovarian cancer has the lowest survival rate among all gynecologic cancers predominantly due to late diagnosis. Early detection of ovarian cancer can increase 5-year survival rates from 40% up to 92%, yet no reliable early detection techniques exist. Optical coherence tomography (OCT) is an emerging technique that provides depth-resolved, high-resolution images of biological tissue in real-time and demonstrates great potential for imaging of ovarian tissue. Mouse models are crucial to quantitatively assess the diagnostic potential of OCT for ovarian cancer imaging; however, due to small organ size, the ovaries must first be separated from the image background using the process of segmentation. Manual segmentation is time-intensive, as OCT yields three-dimensional data. Furthermore, speckle noise complicates OCT images, frustrating many processing techniques. While much work has investigated noise-reduction and automated segmentation for retinal OCT imaging, little has considered the application to the ovaries, which exhibit higher variance and inhomogeneity than the retina. To address these challenges, we evaluate a set of algorithms to segment OCT images of mouse ovaries. We examine five preprocessing techniques and seven segmentation algorithms. While all preprocessing methods improve segmentation, Gaussian filtering is most effective, showing an improvement of . Of the segmentation algorithms, active contours performs best, segmenting with an accuracy of compared with manual segmentation. Even so, further optimization could lead to maximizing the performance for segmenting OCT images of the ovaries.
• Sawyer, T. W. (2018). Alignment of sensor arrays in optical instruments using a geometric approach. Applied optics, 57(4), 794-801.
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  Alignment of sensor arrays in optical instruments is critical to maximize the instrument's performance. While many commercial systems use standardized mounting threads for alignment, custom systems require specialized equipment and alignment procedures. These alignment procedures can be time-consuming, dependent on operator experience, and have low repeatability. Furthermore, each alignment solution must be considered on a case-by-case basis, leading to additional time and resource cost. Here I present a method to align a sensor array using geometric analysis. By imaging a grid pattern of dots, I show that it is possible to calculate the misalignment for a sensor in five degrees of freedom simultaneously. I first test the approach by simulating different cases of misalignment using Zemax before applying the method to experimentally acquired data of sensor misalignment for an echelle spectrograph. The results show that the algorithm effectively quantifies misalignment in five degrees of freedom for an F/5 imaging system, accurate to within ±0.87  deg in rotation and ±0.86  μm in translation. Furthermore, the results suggest that the method can also be applied to non-imaging systems with a small penalty to precision. This general approach can potentially improve the alignment of sensor arrays in custom instruments by offering an accurate, quantitative approach to calculating misalignment in five degrees of freedom simultaneously.
• Sawyer, T. W., Chandra, S., Rice, P. F., Koevary, J. W., & Barton, J. K. (2018). Three-dimensional texture analysis of optical coherence tomography images of ovarian tissue. Physics in medicine and biology, 63(23), 235020.
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  Ovarian cancer has the lowest survival rate among all gynecologic cancers due to predominantly late diagnosis. Optical coherence tomography (OCT) has been applied successfully to experimentally image the ovaries in vivo; however, a robust method for analysis is still required to provide quantitative diagnostic information. Recently, texture analysis has proved to be a useful tool for tissue characterization; unfortunately, existing work in the scope of OCT ovarian imaging is limited to only analyzing 2D sub-regions of the image data, discarding information encoded in the full image area, as well as in the depth dimension. Here we address these challenges by testing three implementations of texture analysis for the ability to classify tissue type. First, we test the traditional case of extracted 2D regions of interest; then we extend this to include the entire image area by segmenting the organ from the background. Finally, we conduct a full volumetric analysis of the image volume using 3D segmented data. For each case, we compute features based on the Grey-Level Co-occurence Matrix and also by introducing a new approach that evaluates the frequency distribution in the image by computing the energy density. We test these methods on a mouse model of ovarian cancer to differentiate between age, genotype, and treatment. The results show that the 3D application of texture analysis is most effective for differentiating tissue types, yielding an average classification accuracy of 78.6%. This is followed by the analysis in 2D with the segmented image volume, yielding an average accuracy of 71.5%. Both of these improve on the traditional approach of extracting square regions of interest, which yield an average classification accuracy of 67.7%. Thus, applying texture analysis in 3D with a fully segmented image volume is the most robust approach to quantitatively characterizing ovarian tissue.
• Sawyer, T. W., Hawkins, K. S., & Damento, M. (2017). Using confidence intervals to evaluate the focus alignment of spectrograph detector arrays. Applied optics, 56(18), 5295-5300.
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  High-resolution spectrographs extract detailed spectral information of a sample and are frequently used in astronomy, laser-induced breakdown spectroscopy, and Raman spectroscopy. These instruments employ dispersive elements such as prisms and diffraction gratings to spatially separate different wavelengths of light, which are then detected by a charge-coupled device (CCD) or complementary metal-oxide-semiconductor (CMOS) detector array. Precise alignment along the optical axis (focus position) of the detector array is critical to maximize the instrumental resolution; however, traditional approaches of scanning the detector through focus lack a quantitative measure of precision, limiting the repeatability and relying on one's experience. Here we propose a method to evaluate the focus alignment of spectrograph detector arrays by establishing confidence intervals to measure the alignment precision. We show that propagation of uncertainty can be used to estimate the variance in an alignment, thus providing a quantitative and repeatable means to evaluate the precision and confidence of an alignment. We test the approach by aligning the detector array of a prototype miniature echelle spectrograph. The results indicate that the procedure effectively quantifies alignment precision, enabling one to objectively determine when an alignment has reached an acceptable level. This quantitative approach also provides a foundation for further optimization, including automated alignment. Furthermore, the procedure introduced here can be extended to other alignment techniques that rely on numerically fitting data to a model, providing a general framework for evaluating the precision of alignment methods.
• Sawyer, T. W., Luthman, A. S., & Bohndiek, S. E. (2017). Evaluation of illumination system uniformity for wide-field biomedical hyperspectral imaging. Journal of Optics, 19(4), 045301. doi:10.1088/2040-8986/aa6176
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  Hyperspectral imaging (HSI) systems collect both spatial (morphological) and spectral (chemical) information from a sample. HSI can provide sensitive analysis for biological and medical applications, for example, simultaneously measuring reflectance and fluorescence properties of a tissue, which together with structural information could improve early cancer detection and tumour characterisation. Illumination uniformity is a critical pre-condition for quantitative data extraction from an HSI system. Non-uniformity can cause glare, specular reflection and unwanted shading, which negatively impact statistical analysis procedures used to extract abundance of different chemical species. Here, we model and evaluate several illumination systems frequently used in wide-field biomedical imaging to test their potential for HSI. We use the software LightTools and FRED. The analysed systems include: a fibre ring light; a light emitting diode (LED) ring; and a diffuse scattering dome. Each system is characterised for spectral, spatial, and angular uniformity, as well as transfer efficiency. Furthermore, an approach to measure uniformity using the Kullback–Leibler divergence (KLD) is introduced. The KLD is generalisable to arbitrary illumination shapes, making it an attractive approach for characterising illumination distributions. Although the systems are quite comparable in their spatial and spectral uniformity, the most uniform angular distribution is achieved using a diffuse scattering dome, yielding a contrast of 0.503 and average deviation of 0.303 over a ±60° field of view with a 3.9% model error in the angular domain. Our results suggest that conventional illumination sources can be applied in HSI, but in the case of low light levels, bespoke illumination sources may offer improved performance.
• Sawyer, T. W., Luthman, A. S., & Bohndiek, S. E. (2017). Evaluation of illumination systems for wide-field hyperspectral imaging in biomedical applications. Proceedings of SPIE, 10068. doi:10.1117/12.2250633
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  Hyperspectral imaging (HSI) systems collect both morphological and chemical characteristics from a sample by simultaneously acquiring spatial and spectral information. HSI has potential to advance cancer diagnostics by characterizing reflectance and fluorescence properties of a tissue, as well as extracting microstructural in- formation, all of which are altered through the development of a tumor. Illumination uniformity is a critical pre-condition for extracting quantitative data from an HSI system. Spatial, angular, or spectral non-uniformity can cause glare, specular reflection and unwanted shading, which negatively impact statistical analysis techniques used to extract abundance of different chemical species. This is further exacerbated when imaging three-dimensional structures, such as tumors, whose appearance can cast shadows and form other occlusions. Furthermore, as HSI can be used simultaneously for white light and fluorescence imaging, a flexible system, which multiplexes narrowband and broadband illumination is necessary to fully utilize the capabilities of a biomedical HSI system. To address these challenges, we modeled illumination systems frequently used in wide-field biological imaging with the software LightTools and FRED. Each system is characterized for spectral, spatial, and angular uniformity, as well as total efficiency. While all three systems provide high spatial and spectral uniformity, the highest angular uniformity is achieved using a diffuse scattering dome, yielding a contrast of 0.503 and average deviation of 0.303 with a 3.91% model error. Nonetheless, results suggest that conventional systems may not be suitable for low-light-level applications, where tailoring illumination to match spatial and spectral requirements may be the best approach to maximize the performance.
• Sawyer, T. W., Petersburg, R., & Bohndiek, S. E. (2017). Tolerancing the alignment of large-core optical fibers, fiber bundles and light guides using a Fourier approach. Applied optics, 56(12), 3303-3310.
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  Optical fiber technology is found in a wide variety of applications to flexibly relay light between two points, enabling information transfer across long distances and allowing access to hard-to-reach areas. Large-core optical fibers and light guides find frequent use in illumination and spectroscopic applications, for example, endoscopy and high-resolution astronomical spectroscopy. Proper alignment is critical for maximizing throughput in optical fiber coupling systems; however, there currently are no formal approaches to tolerancing the alignment of a light-guide coupling system. Here, we propose a Fourier alignment sensitivity (FAS) algorithm to determine the optimal tolerances on the alignment of a light guide by computing the alignment sensitivity. The algorithm shows excellent agreement with both simulated and experimentally measured values and improves on the computation time of equivalent ray-tracing simulations by two orders of magnitude. We then apply FAS to tolerance and fabricate a coupling system, which is shown to meet specifications, thus validating FAS as a tolerancing technique. These results indicate that FAS is a flexible and rapid means to quantify the alignment sensitivity of a light guide, widely informing the design and tolerancing of coupling systems.

Proceedings Publications

• Gonzales, A., Dong, R., Walton Mitstifer, R., Ruhland, C., Sawyer, T., Mouneimne, G., & Barton, J. K. (2025). Optical coherence tomography and elastography for the visualization of architecture and stiffness differences in soft- and stiff-conditioned murine mammary tumors. In Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XXIII 2025, 13306.
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  Cancer is commonly characterized by changes in tissue architecture and increased tissue stiffness. Visualization of these alterations is challenging for current white light endoscopy methods. We utilized two modes of optical coherence tomography (OCT), a non-destructive imaging modality that uses reflected near-infrared light to generate cross-sectional images of tissue, to visualize microstructure and relative stiffness of explanted tissue from an intra-ductal mouse model of breast cancer. Tumors were generated from MCF7 breast cancer cells conditioned in either soft (0.5 kPa) or stiff (8 kPa) hydrogels. Images were collected with a benchtop OCT system (Thorlabs Telesto TEL221). Structural OCT was used to visualize changes in tissue architecture including proliferative intraductal tumor. Optical coherence elastography (OCE) was used to extract relative measures of tissue stiffness. A phantom of known mechanical properties was placed on the tissue and an axial force was applied. The resulting deformation (strain) of the phantom provided relative measurements of tissue stiffness. Classification of normal and cancerous tissue was confirmed by histology using Masson's Trichrome staining. Cancerous tissue had visible tumor nodules which were absent in the normal mammary glands and higher tissue stiffness than normal tissue. These tissue features are classic characteristics of cancer, making this technique potentially useful for the detection of several cancer types. Future work aims to implement endoscopic OCT and OCE to detect cancer at early stages in vivo.
• Aguilera-Cuenca, I., Hutchinson, E., & Sawyer, T. (2024). Estimation and Comparison of Brainstem Fiber Orientation Via Diffusion MRI Tractography and Polarization Sensitive OCT. In 2024 Latin America Optics and Photonics Conference, LAOP 2024.
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  dMRI-based tractography methods reconstruct neural pathways but often lack detailed microstructural information. This study compares fiber orientation distributions in the human brainstem obtained through Constrained Spherical Deconvolution Tractography and polarization-sensitive OCT.
• Guan, S., Daigle, N., & Sawyer, T. (2024). Automated classification of pancreatic neuroendocrine tumors using label-free multiphoton microscopy and deep learning. In 2024 Label-free Biomedical Imaging and Sensing, LBIS 2024, 12854.
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  Pancreatic neuroendocrine tumors (PNETs) present significant diagnostic and therapeutic challenges due to their heterogeneity and complex nature as a subtype of pancreatic cancer. The treatment approach varies considerably based on the tumor's location, grading, and focality. Accurate prognosis and management typically necessitate the expertise of a pathologist to evaluate histological slides of the tissue, a process that is often time-consuming and labor-intensive. Developing point-of-care techniques for automatic classification of PNETs would greatly improve the ability to treat and manage this disease by providing real-time decision-making information. In response to these challenges, our study introduces a highly efficient and versatile diagnostic strategy. This innovative approach synergistically integrates label-free multiphoton microscopy with finely adjusted, pre-trained deep learning models, optimized for performance even with limited data availability. We have meticulously optimized four pre-trained convolutional neural networks, utilizing a dataset comprising only 49 images, which includes both two-photon excitation fluorescence and second-harmonic generation imaging. This refined approach has resulted in an impressive average classification accuracy of over 95% for the development dataset and more than 90% for the test dataset. These results are significantly superior when compared to the preoperative misdiagnosis rates of conventional diagnostic modalities such as ultrasound (US) and computed tomography (CT), which stand at 81.8% and 61.5%, respectively. This methodology represents a significant advancement in the diagnostic process for PNETs, promising a more streamlined, rapid, and accurate approach to treatment. Furthermore, it opens substantial potential for the automated classification of various tumor types using multiphoton microscopic imaging, even in scenarios characterized by limited data availability.
• Knapp, T., Duan, S., Alfonso-Garcia, A., Merchant, J. L., & Sawyer, T. W. (2024). Validation of label-free optical imaging markers of pancreatic cancer using spatial transcriptomics. In 2024 Label-free Biomedical Imaging and Sensing, LBIS 2024, 12854.
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  Label-free biomedical imaging represents a range of powerful technologies used to visualize natural sources of biological contrast. Label-free techniques such as autofluorescence and fluorescence lifetime imaging measure contrast produced by various cellular products and provide high sensitivity for detecting tissue changes that occur with disease onset. However, a major limitation of these modalities, and many label-free modalities broadly, is the lack of robust validation methods that confirm signal specificity. Moreover, existing approaches are limited to assessing correlations and fail to provide mechanistic information into pathological events. Spatially resolved gene sequencing methods (e.g., spatial transcriptomics) are a powerful tool to gain detailed biological insight into tissue properties by creating 2-D maps of variations in gene expression that influence tissue properties. Thus, these techniques represent an avenue for validation of label-free imaging markers through the examination of how label-free image features correspond to gene expression. Toward this aim, we performed autofluorescence and fluorescence lifetime imaging on tissue specimens from four patients presenting with pancreatic neuroendocrine tumors. We then performed spatial transcriptome sequencing on serial tissue sections to measure transcriptome-wide signatures. We assessed imaging biomarkers related to cellular metabolism, vasculature, and extracellular matrix properties. After registering the label-free images to the transcriptomic signatures, we performed k-means clustering, and assessed the correlation between imaging markers and differentially expressed genes associated with tissue properties of interest. Specifically, we aimed to examine correlations between gene expression and established optical biomarkers (e.g., optical redox ratio), along with identifying other potential connections between label-free optics and cellular genetics. The results show that spatial transcriptomics can be used as an effective validation tool for label-free imaging markers, while simultaneously providing additional biological insight to improve the specificity of imaging studies.
• Kropatsch, M., Daigle, N., Duan, S., Sontz, R., Merchant, J. L., & Sawyer, T. W. (2024). Evaluating the impact of freeze-thaw protocols on tissue microstructural imaging features measured using optical coherence tomography. In 2024 Label-free Biomedical Imaging and Sensing, LBIS 2024, 12854.
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  Cryopreservation is routine in biomedical research and clinical practice for various purposes, including sample transportation, RNA preservation, and long-term storage. However, freezing poses risks of tissue damage due to ice crystal formation and cell lysis. The effects of tissue freezing and thawing on microstructural image features are not fully understood, and determining a freezing protocol that best preserves tissue integrity is essential for maximizing the transferability of imaging studies using previously frozen tissues. This study investigates the impact of freeze-thaw protocols on tissue microstructure using optical coherence tomography (OCT), an imaging technique that provides detailed 3D images of biological structures. Tissue specimens from three organs - lung, liver, and duodenum - were collected from six mice and imaged before and after freeze-thawing using different protocols. We tested protocols including slow freezing to -20 °C, slow freezing to -80 °C, and liquid nitrogen submersion. We examined immersion in both phosphate buffered saline and routine cryopreservation compounds for all methods. Using images from each specimen before and after freeze-thawing, differences in structural features were analyzed qualitatively and by using texture analysis. Texture features were extracted from OCT images using Haralick's method, and statistical analysis was performed to compare the different protocols and tissue types. Results show that flash freezing methods and the use of cryopreservation compounds cause fewer alterations in tissue microstructure compared to slow freezing. This study provides insight into the effects of common freezing protocols on tissue integrity, which may inform the optimization of tissue preservation techniques across many disciplines.
• Stilson, E. H., Lima, N., Setiadi, J., Sontz, R., Duan, S., Merchant, J., & Sawyer, T. (2024). Fixative Induced Effects in Labeled and Unlabeled Fluorescence: Implications for Biomedical Imaging Studies. In Multiscale Imaging and Spectroscopy V 2024, 12827.
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  Paraformaldehyde (PFA) is one of the most common fixatives in biological and biomedical research. It is used to preserve tissue or cell morphology while preventing contamination by crosslinking proteins and other biological molecules. Although fixation is required for histology, it has been documented that chemical fixation can cause alterations in the fluorescence properties of exogenous and endogenous fluorophores, which are valuable markers for understanding biological processes, ultimately reducing the accuracy and reliability of quantitative fluorescence measurements. Therefore, there is a need for understanding the behavior of tissue fluorescence during PFA fixation. Multispectral fluorescence imaging (MFSI) is an imaging technique used in biological and biomedical research to visualize and quantify the fluorescence properties of tissue over several wavelength bands, enabling measurement of several fluorophores simultaneously. To evaluate the effects of PFA on tissue fluorescence, we imaged brain tissue samples using MSFI from two cohorts of mice: the SOX10 Cre; R26R-Brainbow 2.1/Confetti mice (expressing four exogenous fluorophores), and wild type Cre-negative controls. Specimens from each were immersed in 10 ml of PFA or phosphate buffer saline (PBS) as a control. The fluorescence intensity was captured using MFSI every 15 minutes over three hours. Analysis was performed on the resulting images to produce quantitative metrics of the resulting fluorescence signal. The results show that exogenous fluorophores are dramatically quenched within the first half hour when fixed in PFA, whereas endogenous fluorescence increased slightly in the same time period. These results are valuable to understand how fixation can influence fluorescence properties and can inform optimal fixation protocols.
• Bonaventura, J., Morara, K., Carlson, R., Comrie, C., Hutchinson, E., & Sawyer, T. (2023). Reflectance full Mueller matrix polarimetry for microstructural validation of diffusion magnetic resonance imaging. In Polarized Light and Optical Angular Momentum for Biomedical Diagnostics 2023, 12382.
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  Knowledge of fiber microstructure and orientation in the brain is critical for understanding the pathogenesis and progression of neurodegenerative diseases such as Alzheimer's Disease. Diffusion magnetic resonance imaging (dMRI) is a noninvasive imaging modality that can generate mappings of nerve fiber orientation. Due to rigorous levels of mathematical modeling involved in reconstructing dMRI data; and limited spatial resolution, there arises a need to validate the biological accuracy of collected dMRI data. Polarized light imaging (PLI) has been shown to have potential for microstructural validation due to the anisotropy in many biological tissues, particularly in myelin sheaths surrounding nerve fibers in the brain. Using PLI for this purpose is appealing because it is directly sensitive to tissue structure and can be done at high resolution. While several studies have had success using PLI for fiber mapping, continuing to advance this modality, particularly reflectance based PLI systems, could provide a valuable avenue for in vivo neural imaging. In order to reach the full potential of reflectance PLI systems, some key questions remain such as the ability of PLI to resolve crossing fibers, and the sensitivity of reflectance PLI to fiber inclination. Tissue phantoms are one potential method to isolate these issues in order to investigate them. In this proceeding, a five-wavelength reflectance Mueller Matrix polarimeter is used for imaging of promising PLI tissue phantoms as well as regions of interest in fixed ferret brain samples. The retardance, diattenuation and depolarization mappings are derived from the Mueller matrix and studied in order to assess the sensitivity of this polarimeter configuration to different fiber orientations.
• Daigle, N., Knapp, T., Duan, S., Jones, D. W., Azhdarinia, A., Ghosh, S. C., AghaAmiri, S., Ikoma, N., Estrella, J., Schnermann, M. J., Merchant, J. L., & Sawyer, T. W. (2023). Combined multiphoton microscopy and somatostatin receptor type 2 imaging of pancreatic neuroendocrine tumors. In Multimodal Biomedical Imaging XVIII 2023, 12371.
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  Pancreatic neuroendocrine tumors (PNETs) are a rare but increasingly more prevalent cancer with heterogeneous clinical and pathological presentation. Surgery is the preferred treatment for all hormone-expressing PNETs and any PNET greater than 2 cm, but difficulties arise when tumors are multifocal, metastatic, or small in size due to lack of effective surgical localization. Existing techniques such as intraoperative ultrasound provide poor contrast and resolution, resulting in low sensitivity for such tumors. Somatostatin receptor type 2 (SSTR2) is commonly overexpressed in PNETs and presents an avenue for targeted tumor localization. SSTR2 is often used for pre-operative imaging and therapeutic treatment, with recent studies demonstrating that somatostatin receptor imaging (SRI) can be applied in radioguided surgery to aid in removal of metastatic lymph nodes and achieving negative surgical margins. However not all PNETs express SSTR2, indicating labeled SRI could benefit from using a supplemental label-free technique such as multiphoton microscopy (MPM), which has proven useful in improving the accuracy of diagnosing more common exocrine pancreatic cancers. Our work tests the suitability of combined SRI and MPM for localizing PNETs by imaging and comparing samples of PNETs and normal pancreatic tissue. Specimens were labeled with a novel SSTR2-targeted contrast agent and imaged using fluorescence microscopy, and subsequently imaged using MPM to collect four autofluorescent channels and second harmonic generation. Our results show that a combination of both SRI and MPM provides enhanced contrast and sensitivity for localizing diseased tissue, suggesting that this approach could be a valuable clinical tool for surgical localization and treatment of PNETs.
• Setiadi, J. C., Bonaventura, J., Knapp, T. G., Duan, S., Merchant, J. L., & Sawyer, T. W. (2023). Mueller Matrix polarization imaging of gastrinoma shows promise for tumor localization. In Label-free Biomedical Imaging and Sensing (LBIS) 2023, 12391.
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  Gastrinomas are gastrin-producing neuroendocrine tumors (NETs) located in the gastroenteropancreatic system. Gastrinomas are often small, multifocal, and found at late stages. Their unpredictable behavior and metastatic potential make it extremely challenging to develop therapeutic strategies. Surgery is the only potentially curative treatment for gastrinoma, but current tumor localization techniques such as intraoperative ultrasound and manual palpitation have poor sensitivity for small tumors, resulting in higher rates of recurrence and metastasis. Therefore, there is a strong clinical need for developing advanced intraoperative imaging technologies for tumor localization in treating gastrinoma. Polarized light imaging (PLI) is a promising method for label-free tissue characterization due to its sensitivity to micro and nanoscale structures, which are often influenced with the onset of cancer, but no works have yet investigated the application of PLI for gastrinoma localization. To assess the suitability of PLI for gastrinoma localization, we imaged 11 formalin-fixed paraffin embedded (FFPE) specimens of gastrinoma using a five-wavelength Mueller Matrix Polarization Microscope. The Lu-Chipman decomposition was applied to spatial maps of the sixteen Mueller matrix parameters. Values for depolarization, diattenuation, and retardance were compared for regions of interest corresponding to tumor and adjacent tissues. There was significant difference between the average depolarization of the Brunner’s gland and tumors when imaged with light at 442, 543, and 632nm (p
• Bonaventura, J., Knapp, T., Koshel, J., & Sawyer, T. (2022). Smartphone spectroscopy for melanoma detection. In Optics and Biophotonics in Low-Resource Settings VIII 2022, 11950.
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  Rates of melanoma mortality are greater in remote areas than in cities. In the United States early-stage melanoma incidence was slightly higher in cities while later stage incidence with metastatic spread was higher in rural areas, suggesting a diagnosis gap between the two. Early detection is key as the 5-year survival rate with early discovery can reach 99%, but as the cancer spreads this survival rate is reduced to 27%. This problem is exacerbated by the inaccessibility of state-of-the-art medical care in remote areas. Thus, an affordable, easily operated, tool can help close the diagnostic gap. Previous studies show melanoma’s reflective and fluorescent spectral signature to be distinct from that of healthy skin, which can be utilized for in-vivo skin cancer detection. Here we present a smartphone spectroscopy system as a tool for melanoma screening with the aim of bringing point-of-care testing to remote areas. The spectrometer consists of a fiber optic cable, collimator, and diffraction grating which couple directly to the smartphone camera, detecting a spectrum in the range of 380-650nm. The spectral data is analyzed and displayed by a custom developed phone application, which uses the smartphone’s integrated computing to extract and calibrate the spectrum. Key spectral features tied to melanoma can then be input into a classification model, with the aim of providing a noninvasive rapid optical biopsy. The results are promising; preliminary validation of the system is conducted; next steps include collection of a robust training data set of skin samples.
• Montague, J., Shir, H., Sawyer, T., Galvez, D., Nfonsam, V. N., & Barton, J. K. (2022). Feasibility of non-imaging, random-sampling second harmonic generation measurements to distinguish colon cancer. In Label-free Biomedical Imaging and Sensing (LBIS) 2022, 11972.
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  Globally, colorectal cancer was the second leading cause of cancer death in 2020. Research suggests that collagen, a major structural protein, plays a pivotal role in cancer development and metastasis, and by extension, subject prognosis. Collagen surrounding tumor cells undergoes structural changes that can be quantitatively studied with second harmonic generation (SHG), a subset of multiphoton microscopy (MPM). MPM as an imaging modality is difficult to implement in an endoscope because of the complex and expensive miniaturized scanning components required. Endoscope complexity can be greatly reduced by implementing a simpler, non-synchronized scanning mechanism. This study investigates whether non-imaging, randomly sampled SHG intensity measurements are sufficient to distinguish normal tissue from tumor/tumor-adjacent tissue. Unstained tumor, normal, and adjacent formalin-fixed, paraffin-embedded thin sections from 12 colorectal cancer subjects were imaged using a multiphoton microscope with 850nm excitation and 400-430nm emission band, constant power, and consisting of 1024x1024 pixels over 425x425μm. SHG signal from collagen fibers was isolated by grayscale thresholding, and the grayscale mean of the thresholded image was calculated. Then, random supra-threshold pixels in the image were selected. The mean SHG signal from normal samples was significantly greater than adjacent samples (p = 0.014) and cancer samples (p = 0.007). For both tumor and adjacent comparisons to normal tissue, p value becomes reliable after randomly sampling only 1000 pixels. This study suggests that reliable diagnostic information may be obtained through simple non-imaging, random-sampling SHG intensity measurements. A simple endoscope with this capability could help identify suspicious masses or optimum surgical margins.
• Sawyer, T. W., Hutchinson, E. B., Bonventura, J., Comrie, C. J., & Carlson, R. (2022, May). Backscattering Mueller Matrix polarimetry shows promise for validation of diffusion MRI microstructural features in thick tissue specimens. In International Society for Magnetic Resonance in Medicine.
• Barton, J. K., & Sawyer, T. W. (2021). Enabling high-throughput spectroscopy with liquid crystal polarization gratings. In Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XIX, 11647.
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  Autofluorescence (AF) spectroscopy and imaging are used widely in the field of biomedicine for disease diagnosis and screening. Concentrations of many intrinsic fluorophores share a strict relationship with morphological and functional characteristics of tissue, making AF spectroscopy a powerful tool to directly monitor tissue health. One major challenge with AF imaging is maintaining high signal-to-noise ratios, as emission levels are low due to poor fluorophore quantum efficiencies and low illumination power levels. As a result, maximizing the throughput of the measurement system is critical to mitigate losses. Diffraction gratings are commonly used for spectroscopy for dispersion, but rarely exhibit efficiencies above 80%, limiting the system performance. Liquid crystal polarization gratings (LCPGs) are a relatively new technology that possess extremely high efficiency, typically over 90% for the design wavelength, and in some cases up to 99%, making it an attractive option for AF spectroscopy. However, with unpolarized autofluorescent light, the grating would split the light equally into two orders, only one of which could be collected with a standard detector array. Here, we present the first design and demonstration of a visible light spectrometer using a LCPG. To overcome the loss of 50% of incoming unpolarized light being split into separate orders, we report a novel prism system used to merge the two orders into a single spectrum with minimal degradation of spectral resolution. Our results indicate that that using LCPGs could increase signal levels by up to 20%, significantly improving the performance of spectrometers used for biomedical AF imaging.
• Barton, J. K., Gorman, T., Rice, P. F., Santaniello, S. P., & Sawyer, T. W. (2021). Multispectral fluorescence imaging of ovarian tissue for the characterization and classification of early-stage ovarian cancer. In Label-free Biomedical Imaging and Sensing (LBIS) 2021, 11655.
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  Ovarian cancer is challenging due to poor detection rates and high mortality. Multispectral fluorescence imaging (MFI) has recently become a favorable method for cancer characterization. By utilizing MFI along with a characterized ovarian cancer mouse model and human fallopian tube histology sections, we were able to study cancer in its earliest stages with a promising modality for early disease detection. Fluorescence images with various emission combinations from 280nm to 550nm excitation and reflectance images from 320nm to 550nm were taken of 8-week-old mouse ovarian tissues. Human fallopian tube histology slides were also imaged with the same fluorescence images. Disease characterization was studied using Quadratic Discriminant Analysis (QDA) on image grayscale intensities for both tissues as well as the greylevel co-occurrence matrix (GLCM) in human tissue slides in order to determine a classification group with the highest predictive merit. Both tissues were able to be classified with greater than 80% accuracy, suggesting promise for MFI as a potential diagnostic candidate.
• Sawyer, T. W., Salcin, E., Friedman, J. S., & Diaz, A. (2021). Extraction of precise object orientation and position from LIDAR data using maximum-likelihood methods. In Laser Radar Technology and Applications XXVI.
• Sawyer, T. W., Salcin, E., Friedman, J. S., & Diaz, A. (2021). Using principle component analysis to estimate geometric parameters from point cloud LIDAR data. In Laser Radar Technology and Applications XXVI, 11744.
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  Light Detection and Ranging (LIDAR) is a popular sensing technique to measure static and dynamic objects with applications in many areas of defense technology including robotics, aircraft navigation and guidance systems, autonomous vehicles and aircraft landing systems, as well as tracking and measuring attitude of hypersonic objects. Despite widespread use of LIDAR to map out objects and environments, there remains a need for advanced analytic techniques to recover quantitative information about objects from LIDAR data, for example, the position and trajectory of a foreign object. One major class of LIDAR systems are those that produce so-called point-cloud data, which is a threedimensional sampling of a scene. Technical demands for extraction of geometric parameters from point-cloud spatial models are increasing as 3D LIDAR sensors and their application technology is continuously developed and popularized. While classical techniques for feature extraction and estimation exist, these existing techniques are currently inadequate to recover geometric parameters with desired accuracy for precision applications. To address this challenge, we developed an algorithm based on principal component analysis (PCA) to extract precise geometric parameters from LIDAR point-cloud data of objects including pitch, yaw, roll and xyz-position, as well as the rates of change of these parameters. We present the basis of this algorithm, as well as initial results using point cloud data of a rotating cylindrical object. The results suggest that PCA-based analysis could provide a robust and high precision approach for recovering object position and orientation, particularly when combined with other analytical approaches such as machine learning.
• Williams, C., Taylor-williams, M., Sawyer, T. W., Murray, A. K., Mead, S., Hacker, L., Bohndiek, S. E., & Berks, M. (2021). A low-cost LED-based multispectral capillaroscopy system for oximetry of the nailfold. In Optical Diagnostics and Sensing XXI: Toward Point-of-Care Diagnostics, 11651.
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  Nailfold capillaroscopy is a technique for imaging the capillary bed in the finger nailfold, that is used in the diagnosis of scleroderma. Knowledge of the capillary oxygenation profile would be a substantial advantage in disease evaluation. A compact, low-cost LED-illuminated capillaroscopy system was conceived based on inexpensive parts and optical hardware. The system uses a compact Raspberry Pi to control a custom-designed LED ring light, with white-light LEDs interleaved with three narrowband LEDs, and a Raspberry Pi camera. Capillary visualisation and distinction of haemoglobin contrast is demonstrated, suggesting future promise for application of multispectral nailfold capillaroscopy in low-resource settings.
• Yoon, J., Wilson, A., Waterhouse, D. J., Sawyer, T. W., Fitzgerald, R. C., Bohndiek, S. E., & Pietro, M. D. (2020). Development of a compact multimodal imaging system for rapid characterisation of intrinsic optical properties of freshly excised tissue (Conference Presentation). In Multimodal Biomedical Imaging XV, 11232.
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  Advanced optical endoscopic imaging techniques, including hyperspectral and holographic endoscopy, have shown promise in the improved diagnosis of the early stage of cancer. However, clinical applications of these imaging systems are still limited due to unclear diagnostic optical properties. Here, we developed a compact multimodal imaging system that enables hyperspectral imaging, spatial-frequency domain imaging, and 3D profilometric imaging to characterise the optimal optical features for the early detection of lesions. Optical properties of fresh specimens obtained from patients were measured within 30 minutes, and then histopathological assessment of specimens was performed to link extracted optical features to gold-standard diagnosis. With further sample collection and system refinements, this system can be used for high-throughput optical characterisation of fresh tissue specimens, allowing us to determine the optical signatures of early-stage disease.
• Sawyer, T. W., Barton, J. K., Cai, K. Q., Connolly, D. C., Koevary, J. W., Rice, P. F., & Rice, F. F. (2019). In vivo multiphoton imaging of an ovarian cancer mouse model. In Diseases in the Breast and Reproductive System V, 10856.
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  Ovarian cancer is the deadliest gynecologic cancer due to predominantly late diagnosis. Early detection of ovarian cancer can increase 5-year survival rates from 40% up to 92%, yet no reliable early detection techniques exist. Multiphoton microscopy (MPM) is a relatively new imaging technique with tremendous potential for clinical diagnosis. A sub-modality of MPM is second harmonic generation (SHG) imaging, which generates contrast from anisotropic structures like collagen molecules, enabling the acquisition of detailed molecular structure maps. As collagen is known to change throughout the progression of cancer, MPM is a promising candidate for ovarian cancer screening. While MPM has shown favorable results in a research environment, it has not yet found broad success in a clinical setting. One major obstacle is the quantitative analysis of the image content. Recently, the application of texture analysis to MPM images has shown success for characterizing the collagen content of the tissue, making it a prime candidate for disease screening. Unfortunately, existing work is limited in its application to ovarian tissue and few texture analysis approaches have been evaluated in this context. To address these challenges, we applied texture analysis to second harmonic generation (SHG) and two-photon excited fluorescence (TPEF) images of a mouse model (TgMISIIR-TAg) of ovarian cancer. Using features from the grey-level co-occurrence matrix, we find that texture analysis of TPEF images of the ovary can differentiate between genotype with high statistical significance (p
• Sawyer, T. W., Barton, J. K., Koevary, J. W., & Rice, P. F. (2019). Endogenous and exogenous contrast mechanisms for detection of ovarian cancer. In Biophotonics Congress: Optics in the Life Sciences Congress 2019 (BODA,BRAIN,NTM,OMA,OMP), 2019.
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  We show that multispectral fluorescence imaging, optical coherence tomography, and multispectral microscopy differentiates normal, cancer, and benign ovary and fallopian tube tissue in a mouse model and human tissue samples.
• Sawyer, T. W., Barton, J. K., Koevary, J. W., & Rice, P. F. (2019). Fluorescence and multiphoton imaging of a mouse model of spontaneous ovarian cancer. In Biophotonics Congress: Optics in the Life Sciences Congress 2019 (BODA,BRAIN,NTM,OMA,OMP), 2019.
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  Ovarian cancer is the deadliest gynecologic cancer, but can be addressed with early detection. We investigate fluorescence and multiphoton imaging for imaging ovarian cancer, finding that tissue changes can be detected through quantitative analysis.
• Sawyer, T. W., Barton, J. K., Koevary, J. W., Rice, P. F., & Watson-koevary, J. (2019). In vivo optical coherence tomography of a mouse model of spontaneous ovarian cancer. In Clinical and Preclinical Optical Diagnostics II, 11073.
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  Ovarian cancer is the deadliest gynecologic cancer, but can be addressed with early detection. We investigate optical coherence tomography for imaging ovarian cancer, finding that tissue changes can be detected through quantitative analysis.
• Sawyer, T. W., Williams, C., & Bohndiek, S. E. (2019). Spectral Band Selection and Tolerancing for Multispectral Filter Arrays. In Frontiers in Optics + Laser Science APS/DLS.
• Gordon, G. S., Sawyer, T. W., Bohndiek, S. E., Wilkinson, T. D., & Fitzpatrick, C. R. (2018). Wide-field phase imaging for the endoscopic detection of dysplasia and early-stage esophageal cancer. In Endoscopic Microscopy XIII, 10470.
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  © 2018 SPIE. Esophageal cancer has a 5-year survival rate below 20%, but can be curatively resected if it is detected early. At present, poor contrast for early lesions in white light imaging leads to a high miss rate in standard-of-care endoscopic surveillance. Early lesions in the esophagus, referred to as dysplasia, are characterized by an abundance of abnormal cells with enlarged nuclei. This tissue has a different refractive index profile to healthy tissue, which results in different light scattering properties and provides a source of endogenous contrast that can be exploited for advanced endoscopic imaging. For example, point measurements of such contrast can be made with scattering spectroscopy, while optical coherence tomography generates volumetric data. However, both require specialist interpretation for diagnostic decision making. We propose combining wide-field phase imaging with existing white light endoscopy in order to provide enhanced contrast for dysplasia and early-stage cancer in an image format that is familiar to endoscopists. Wide-field phase imaging in endoscopy can be achieved using coherent illumination combined with phase retrieval algorithms. Here, we present the design and simulation of a benchtop phase imaging system that is compatible with capsule endoscopy. We have undertaken preliminary optical modelling of the phase imaging setup, including aberration correction simulations and an investigation into distinguishing between different tissue phantom scattering coefficients. As our approach is based on phase retrieval rather than interferometry, it is feasible to realize a device with low-cost components for future clinical implementation.
• Sawyer, T. W., Barton, J. K., Koevary, J. W., Rice, P. F., & Sawyer, D. M. (2018). Evaluation of segmentation algorithms for optical coherence tomography images of ovarian tissue. In Diagnosis and Treatment of Diseases in the Breast and Reproductive System IV, 10472.
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  Ovarian cancer has the lowest survival rate among all gynecologic cancers due to predominantly late diagnosis. Early detection of ovarian cancer can increase 5-year survival rates from 40% up to 92%, yet no reliable early detection techniques exist. Optical coherence tomography (OCT) is an emerging technique that provides depthresolved, high-resolution images of biological tissue in real time and demonstrates great potential for imaging of ovarian tissue. Mouse models are crucial to quantitatively assess the diagnostic potential of OCT for ovarian cancer imaging; however, due to small organ size, the ovaries must rst be separated from the image background using the process of segmentation. Manual segmentation is time-intensive, as OCT yields three-dimensional data. Furthermore, speckle noise complicates OCT images, frustrating many processing techniques. While much work has investigated noise-reduction and automated segmentation for retinal OCT imaging, little has considered the application to the ovaries, which exhibit higher variance and inhomogeneity than the retina. To address these challenges, we evaluated a set of algorithms to segment OCT images of mouse ovaries. We examined ve preprocessing techniques and six segmentation algorithms. While all pre-processing methods improve segmentation, Gaussian filtering is most effective, showing an improvement of 32% +/- 1.2%. Of the segmentation algorithms, active contours performs best, segmenting with an accuracy of 0.948 +/- 0.012 compared with manual segmentation (1.0 being identical). Nonetheless, further optimization could lead to maximizing the performance for segmenting OCT images of the ovaries.
• Sawyer, T. W., & Bohndiek, S. E. (2017). Towards a simulation framework to maximize the resolution of biomedical hyperspectral imaging. In Diffuse Optical Spectroscopy and Imaging VI, 10412.
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  When light is incident upon tissue, imaging contrast can be obtained from a range of interactions including absorption, scattering and fluorescence. Clinical optical imaging systems are typically optimized to report on a single contrast source, for example, using standard RGB cameras to produce white light reflectance images or filter-based approaches to extract fluorescence emissions. Hyperspectral imaging has the potential to over-come the need for specialized instrumentation, by sampling spatial and spectral information simultaneously. In particular, spectrally resolved detector arrays (SRDAs) now monolithically integrate spectral filters with CMOS image sensors to provide a robust, compact and low cost solution to video rate hyperspectral imaging. However, SRDAs suffer from a significant limitation, which is the inherent tradeoff between spatial and spectral resolution. Therefore, the properties of the SRDA including the number of filters, their wavelength and bandwidth, needs be optimized for tissue imaging. To achieve this, we have developed a software framework to optimize spectral band selection, simulating the hyperspectral sample illumination, data acquisition and spectral unmixing processes. Our approach shows early promise for selecting appropriate spectral filters, which allows us to maintain high spatial resolution for imaging.