Targeted multispectral filter array design for the optimization of endoscopic cancer detection in the gastrointestinal tract.

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.

Spatial profiling reveals tissue-specific neuro-immune interactions in gastroenteropancreatic neuroendocrine tumors.

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.

Combined flat-field and frequency filter approach to correcting artifacts of multichannel two-photon microscopy.

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.

Evaluating backscattering polarized light imaging microstructural mapping capabilities through neural tissue and analogous phantom imaging.

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.

Design, fabrication, and preclinical testing of a miniaturized, multispectral, chip-on-tip, imaging probe for intraluminal fluorescence imaging of the gastrointestinal tract.

Gastrointestinal cancers continue to account for a disproportionately large percentage of annual cancer deaths in the US. 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 to port through 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 multiple fluorochromes, and devised for deployment via the accessory channel of a standard gastroscope.

Wide field-of-view fluorescence imaging for organ-level lineage tracing of rare intestinal stem cell populations.

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.

Clinically Defined Mutations in MEN1 Alter Its Tumor-suppressive Function Through Increased Menin Turnover.

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.

Combined multiphoton microscopy and somatostatin receptor type 2 imaging of pancreatic neuroendocrine tumors.

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.

Quantitative characterization of duodenal gastrinoma autofluorescence using multiphoton microscopy.

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.

Multispectral imaging of nailfold capillaries using light-emitting diode illumination.

Significance: 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. Aim: To design, construct, and test a low-cost multispectral imaging (MSI) system using light-emitting diode (LED) illumination to assess relative hemoglobin oxygenation in the nailfold capillaries. Approach: An LED ring light was first designed and modeled. The ring light was fabricated using four commercially available LED colors and a custom-designed printed circuit board. The experimental system was characterized and results compared with the illumination model. A blood phantom with variable oxygenation was used to determine the feasibility of using the illumination-based MSI system for oximetry. Nailfold capillaries were then imaged in a healthy subject. Results: The illumination modeling results were in close agreement with the constructed system. Imaging of the blood phantom demonstrated sensitivity to changing hemoglobin oxygenation, which was in line with the spectral modeling of reflection. The morphological properties of the volunteer capillaries were comparable to those measured in current gold standard systems. Conclusions: LED-based illumination could be used as a low-cost approach to enable MSI of the nailfold capillaries to provide insight into the oxygenation of the blood contained within the capillary network.

GFAP-directed Inactivation of Men1 Exploits Glial Cell Plasticity in Favor of Neuroendocrine Reprogramming.

BACKGROUND & AIMS: 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. METHODS: Transgenic GFAPΔMen1 mice were generated by conditional GFAP-directed Men1 deletion in GFAP-expressing cells. Cre specificity was confirmed using a tdTomato reporter. GFAPΔMen1 mice were evaluated for GEP-NEN development and neuroendocrine cell hyperplasia. Small interfering RNA-mediated Men1 silencing in a rat enteric glial cell line was performed in parallel. RESULTS: GFAPΔMen1 mice developed pancreatic NENs, in addition to pituitary prolactinomas that phenocopied the human MEN1 syndrome. GFAPΔMen1 mice exhibited gastric neuroendocrine hyperplasia that coincided with a significant loss of GFAP expression. Men1 deletion induced loss of glial-restricted progenitor lineage markers and an increase in neuroendocrine genes, suggesting a reprogramming of GFAP+ cells. Deleting Kif3a, a mediator of Hedgehog signaling, in GFAP-expressing cells attenuated neuroendocrine hyperplasia by restricting the neuroendocrine cell fate. Similar results in the pancreas were observed when Sox10 was used to delete Men1. CONCLUSIONS: GFAP-directed Men1 inactivation exploits glial cell plasticity in favor of neuroendocrine differentiation.

Opti-MSFA: a toolbox for generalized design and optimization of multispectral filter arrays.

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.

Ovarian cancer detection using optical coherence tomography and convolutional neural networks.

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.

Effect of an Added Mass on the Vibration Characteristics for Raster Scanning of a Cantilevered Optical Fiber.

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.

Pilot Study: Texture Analysis of PET Imaging Demonstrates Changes in 18F-FDG Uptake of the Brain After Prophylactic Cranial Irradiation.

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. Methods: 18F-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. Results: 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. Conclusion: 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.

Use of embedded and patterned dichroic surfaces with reflective optical power to enable multiple optical paths in a micro-objective.

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.

Fluorescence and Multiphoton Imaging for Tissue Characterization of a Model of Postmenopausal Ovarian Cancer.

BACKGROUND AND OBJECTIVES: To determine the efficacy of targeted fluorescent biomarkers and multiphoton imaging to characterize early changes in ovarian tissue with the onset of cancer. STUDY DESIGN/MATERIALS AND METHODS: A transgenic TgMISIIR-TAg mouse was used as an animal model for ovarian cancer. Mice were injected with fluorescent dyes to bind to the folate receptor α, matrix metalloproteinases, and integrins. Half of the mice were treated with 4-vinylcyclohexene diepoxide (VCD) to simulate menopause. Widefield fluorescence imaging (WFI) and multiphoton imaging of the ovaries and oviducts were conducted at 4 and 8 weeks of age. The fluorescence signal magnitude was quantified, and texture features were derived from multiphoton imaging. Linear discriminant analysis was then used to classify mouse groups. RESULTS: Imaging features from both fluorescence imaging and multiphoton imaging show significant changes (P < 0.01) with age, VCD treatment, and genotype. The classification model is able to classify different groups to accuracies of 75.53%, 69.53%, and 86.76%, for age, VCD treatment, and genotype, respectively. Building a classification model using features from multiple modalities shows marked improvement over individual modalities. CONCLUSIONS: This study demonstrates that using WFI with targeted biomarkers, and multiphoton imaging with endogenous contrast shows promise for detecting early changes in ovarian tissue with the onset of cancer. The results indicate that multimodal imaging can provide higher sensitivity for classifying tissue types than using single modalities alone. Lasers Surg. Med. © 2020 Wiley Periodicals, Inc.

Robustness to misalignment of low-cost, compact quantitative phase imaging architectures.

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.

Quantification of multiphoton and fluorescence images of reproductive tissues from a mouse ovarian cancer model shows promise for early disease detection.

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 < 0.001). The wide-field fluorescence signal also changes significantly between genotypes (p < 0.01). We use the features to classify multiple tissue groups to over 80% accuracy. These results suggest that MPM and WFI are promising techniques for the early detection of ovarian cancer.

Evaluation of segmentation algorithms for optical coherence tomography images of ovarian tissue.

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 32 % ± 1.2 % . Of the segmentation algorithms, active contours performs best, segmenting with an accuracy of 94.8 % ± 1.2 % compared with manual segmentation. Even so, further optimization could lead to maximizing the performance for segmenting OCT images of the ovaries.