Demonstration of age-related blood-brain barrier disruption and cerebromicrovascular rarefaction in mice by longitudinal intravital two-photon microscopy and optical coherence tomography.

Age-related blood-brain barrier (BBB) disruption and cerebromicrovascular rarefaction contribute importantly to the pathogenesis of both vascular cognitive impairment and dementia (VCID) and Alzheimer's disease (AD). Recent advances in geroscience research enable development of novel interventions to reverse age-related alterations of the cerebral microcirculation for prevention of VCID and AD. To facilitate this research, there is an urgent need for sensitive and easy-to-adapt imaging methods that enable longitudinal assessment of changes in BBB permeability and brain capillarization in aged mice and that could be used in vivo to evaluate treatment efficiency. To enable longitudinal assessment of changes in BBB permeability in aged mice equipped with a chronic cranial window, we adapted and optimized two different intravital two-photon imaging approaches. By assessing relative fluorescence changes over the baseline within a volume of brain tissue, after qualitative image subtraction of the brain microvasculature, we confirmed that, in 24-mo-old C57BL/6J mice, cumulative permeability of the microvessels to fluorescent tracers of different molecular masses (0.3 to 40 kDa) is significantly increased compared with that of 5-mo-old mice. Real-time recording of vessel cross-sections showed that apparent solute permeability of single microvessels is significantly increased in aged mice vs. young mice. Cortical capillary density, assessed both by intravital two-photon microscopy and optical coherence tomography was also decreased in aged mice vs. young mice. The presented methods have been optimized for longitudinal (over the period of 36 wk) in vivo assessment of cerebromicrovascular health in preclinical geroscience research.NEW & NOTEWORTHY Methods are presented for longitudinal detection of age-related increase in blood-brain barrier permeability and microvascular rarefaction in the mouse cerebral cortex by intravital two-photon microscopy and optical coherence tomography.

Nanoparticle-based fluoroionophore for analysis of potassium ion dynamics in 3D tissue models and in vivo.

The imaging of real-time fluxes of K+ ions in live cell with high dynamic range (5-150 mM) is of paramount importance for neuroscience and physiology of the gastrointestinal tract, kidney and other tissues. In particular, the research on high-performance deep-red fluorescent nanoparticle-based biosensors is highly anticipated. We found that BODIPY-based FI3 K+-sensitive fluoroionophore encapsulated in cationic polymer RL100 nanoparticles displays unusually strong efficiency in staining of broad spectrum of cell models, such as primary neurons and intestinal organoids. Using comparison of brightness, photostability and fluorescence lifetime imaging microscopy (FLIM) we confirmed that FI3 nanoparticles display distinctively superior intracellular staining compared to the free dye. We evaluated FI3 nanoparticles in real-time live cell imaging and found that it is highly useful for monitoring intra- and extracellular K+ dynamics in cultured neurons. Proof-of-concept in vivo brain imaging confirmed applicability of the biosensor for visualization of epileptic seizures. Collectively, this data makes fluoroionophore FI3 a versatile cross-platform fluorescent biosensor, broadly compatible with diverse experimental models and that crown ether-based polymer nanoparticles can provide a new venue for design of efficient fluorescent probes.

Imaging stem cell distribution, growth, migration, and differentiation in 3-D scaffolds for bone tissue engineering using mesoscopic fluorescence tomography.

Regenerative medicine has emerged as an important discipline that aims to repair injury or replace damaged tissues or organs by introducing living cells or functioning tissues. Successful regenerative medicine strategies will likely depend upon a simultaneous optimization strategy for the design of biomaterials, cell-seeding methods, cell-biomaterial interactions, and molecular signaling within the engineered tissues. It remains a challenge to image three-dimensional (3-D) structures and functions of the cell-seeded scaffold in mesoscopic scale (>2 ∼ 3 mm). In this study, we utilized angled fluorescence laminar optical tomography (aFLOT), which allows depth-resolved molecular characterization of engineered tissues in 3-D to investigate cell viability, migration, and bone mineralization within bone tissue engineering scaffolds in situ.

Multi-modality Optical Imaging of Rat Kidney Dysfunction: In Vivo Response to Various Ischemia Times.

We observed in vivo kidney dysfunction with various ischemia times at 30, 75, 90, and 120 min using multi-modality optical imaging: optical coherence tomography (OCT), Doppler OCT (DOCT), and two-photon microscopy (TPM). We imaged the renal tubule lumens and glomerulus at several areas of each kidney before, during, and after ischemia of 5-month-old female Munich-Wistar rats. For animals with 30 and 75 min ischemia times, we observed that all areas were recovered after ischemia, that tubule lumens were re-opened and the blood flow of the glomerulus was re-established. For animals with 90 and 120 min ischemia times, we observed unrecovered areas, and that tubule lumens remained close after ischemia. TPM imaging verified the results of OCT and provided higher resolution images than OCT to visualize renal tubule lumens and glomerulus blood flow at the cellular level.

Large area kidney imaging for pre-transplant evaluation using real-time robotic optical coherence tomography.

Optical coherence tomography (OCT) can be used to image microstructures of human kidneys. However, current OCT probes exhibit inadequate field-of-view, leading to potentially biased kidney assessment. Here we present a robotic OCT system where the probe is integrated to a robot manipulator, enabling wider area (covers an area of 106.39 mm by 37.70 mm) spatially-resolved imaging. Our system comprehensively scans the kidney surface at the optimal altitude with preoperative path planning and OCT image-based feedback control scheme. It further parameterizes and visualizes microstructures of large area. We verified the system positioning accuracy on a phantom as 0.0762 ± 0.0727 mm and showed the clinical feasibility by scanning ex vivo kidneys. The parameterization reveals vasculatures beneath the kidney surface. Quantification on the proximal convoluted tubule of a human kidney yields clinical-relevant information. The system promises to assess kidney viability for transplantation after collecting a vast amount of whole-organ parameterization and patient outcomes data.

A Neoteric Feature Extraction Technique to Predict the Survival of Gastric Cancer Patients.

BACKGROUND: At the time of cancer diagnosis, it is crucial to accurately classify malignant gastric tumors and the possibility that patients will survive. OBJECTIVE: This study aims to investigate the feasibility of identifying and applying a new feature extraction technique to predict the survival of gastric cancer patients. METHODS: A retrospective dataset including the computed tomography (CT) images of 135 patients was assembled. Among them, 68 patients survived longer than three years. Several sets of radiomics features were extracted and were incorporated into a machine learning model, and their classification performance was characterized. To improve the classification performance, we further extracted another 27 texture and roughness parameters with 2484 superficial and spatial features to propose a new feature pool. This new feature set was added into the machine learning model and its performance was analyzed. To determine the best model for our experiment, Random Forest (RF) classifier, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Naïve Bayes (NB) (four of the most popular machine learning models) were utilized. The models were trained and tested using the five-fold cross-validation method. RESULTS: Using the area under ROC curve (AUC) as an evaluation index, the model that was generated using the new feature pool yields AUC = 0.98 ± 0.01, which was significantly higher than the models created using the traditional radiomics feature set (p < 0.04). RF classifier performed better than the other machine learning models. CONCLUSIONS: This study demonstrated that although radiomics features produced good classification performance, creating new feature sets significantly improved the model performance.

Enhancing epidural needle guidance using a polarization-sensitive optical coherence tomography probe with convolutional neural networks.

Epidural anesthesia helps manage pain during different surgeries. Nonetheless, the precise placement of the epidural needle remains a challenge. In this study, we developed a probe based on polarization-sensitive optical coherence tomography (PS-OCT) to enhance the epidural anesthesia needle placement. The probe was tested on six porcine spinal samples. The multimodal imaging guidance used the OCT intensity mode and three distinct PS-OCT modes: (1) phase retardation, (2) optic axis, and (3) degree of polarization uniformity (DOPU). Each mode enabled the classification of different epidural tissues through distinct imaging characteristics. To further streamline the tissue recognition procedure, convolutional neural network (CNN) were used to autonomously identify the tissue types within the probe's field of view. ResNet50 models were developed for all four imaging modes. DOPU imaging was found to provide the highest cross-testing accuracy of 91.53%. These results showed the improved precision by PS-OCT in guiding epidural anesthesia needle placement.

Automatic renal carcinoma biopsy guidance using forward-viewing endoscopic optical coherence tomography and deep learning.

Percutaneous renal biopsy is commonly used for kidney cancer diagnosis. However, the biopsy procedure remains challenging in sampling accuracy. Here we introduce a forward-viewing optical coherence tomography probe for differentiating tumor and normal tissues, aiming at precise biopsy guidance. Totally, ten human kidney samples, nine of which had malignant renal carcinoma and one had benign oncocytoma, were used for system evaluation. Based on their distinct imaging features, carcinoma could be efficiently distinguished from normal renal tissues. Additionally, oncocytoma could be differentiated from carcinoma. We developed convolutional neural networks for tissue recognition. Compared to the conventional attenuation coefficient method, convolutional neural network models provided more accurate carcinoma predictions. These models reached a tissue recognition accuracy of 99.1% on a hold-out set of four kidney samples. Furthermore, they could efficiently distinguish oncocytoma from carcinoma. In conclusion, our convolutional neural network-aided endoscopic imaging platform could enhance carcinoma diagnosis during percutaneous renal biopsy procedures.

Enhancing precision in colorectal cancer surgery: development of an LGR5-targeting RSPO1 peptide mimetic as a contrast agent for intraoperative fluorescence molecular imaging.

Colorectal cancer (CRC) is the third most common cancer worldwide. In the United States alone, CRC was responsible for approximately 52,550 deaths in 2023, with an estimated 153,020 new cases. CRC presents with synchronous peritoneal spread in 5-10% of patients, and up to 20-50% of patients with recurrent disease will develop metachronous colorectal cancer peritoneal metastatic (CRC-PM) disease. Eradication of the tumor, tumor margins and microscopic residual disease is paramount, as microscopic residual disease is associated with local recurrences, with 5-year survival rates of less than 35%. The success of resection and reduction of residual disease depends on the accuracy with which cancer cells and normal tissue can be intra-operatively distinguished. Fluorescence Molecular Imaging (IFMI) and tumor-targeted contrast agents represent a promising approach for intraoperative detection and surgical intervention. Proper target selection, the development of scalable imaging agents and enhanced real-time tumor and tumor microenvironment imaging are critical to enabling enhanced surgical resection. LGR5 (leucine-rich repeat-containing G-protein-coupled receptor 5), a colonic crypt stem cell marker and the receptor for the R-spondins (RSPO) in the Wnt signaling pathway, is also expressed on colorectal cancer stem cells (CSC) and on CRC tumors and metastases, suggesting it could be a useful target for imaging of CRC. However, there are numerous diverging reports on the role of LGR5 in CRC therapy and outcomes. Herein, we report on the synthesis and validation of a 37 amino acid RSPO1-mimetic peptide, termed RC18, that was specifically designed to access the R-spondin binding site of LGR5 to potentially be used for interoperative imaging of CRC-PM. The receptor-binding capabilities of the RC18 indicate that direct interactions with LGR5 neither significantly increased LGR5 signaling nor blocked RSPO1 binding and signal transduction, suggesting that the RSPO1-mimetic is functionally inert, making it an attractive contrast agent for intraoperative CRC-PM imaging.

Dimension-based quantification of aging-associated cerebral microvasculature determined by optical coherence tomography and two-photon microscopy.

Cerebral microvascular health is a key biomarker for the study of natural aging and associated neurological diseases. Our aim is to quantify aging-associated change of microvasculature at diverse dimensions in mice brain. We used optical coherence tomography (OCT) and two-photon microscopy (TPM) to obtain nonaged and aged C57BL/6J mice cerebral microvascular images in vivo. Our results indicated that artery & vein, arteriole & venule, and capillary from nonaged and aged mice showed significant differences in density, diameter, complexity, perimeter, and tortuosity. OCT angiography and TPM provided the comprehensive quantification for arteriole and venule via compensating the limitation of each modality alone. We further demonstrated that arteriole and venule at specific dimensions exhibited negative correlations in most quantification analyses between nonaged and aged mice, which indicated that TPM and OCT were able to offer complementary vascular information to study the change of cerebral blood vessels in aging.

Optical coherence tomography for multicellular tumor spheroid category recognition and drug screening classification via multi-spatial-superficial-parameter and machine learning.

Optical coherence tomography (OCT) is an ideal imaging technique for noninvasive and longitudinal monitoring of multicellular tumor spheroids (MCTS). However, the internal structure features within MCTS from OCT images are still not fully utilized. In this study, we developed cross-statistical, cross-screening, and composite-hyperparameter feature processing methods in conjunction with 12 machine learning models to assess changes within the MCTS internal structure. Our results indicated that the effective features combined with supervised learning models successfully classify OVCAR-8 MCTS culturing with 5,000 and 50,000 cell numbers, MCTS with pancreatic tumor cells (Panc02-H7) culturing with the ratio of 0%, 33%, 50%, and 67% of fibroblasts, and OVCAR-4 MCTS treated by 2-methoxyestradiol, AZD1208, and R-ketorolac with concentrations of 1, 10, and 25 µM. This approach holds promise for obtaining multi-dimensional physiological and functional evaluations for using OCT and MCTS in anticancer studies.

Large Area Kidney Imaging for Pre-transplant Evaluation using Real-Time Robotic Optical Coherence Tomography.

Optical coherence tomography (OCT) is a high-resolution imaging modality that can be used to image microstructures of human kidneys. These images can be analyzed to evaluate the viability of the organ for transplantation. However, current OCT devices suffer from insufficient field-of-view, leading to biased examination outcomes when only small portions of the kidney can be assessed. Here we present a robotic OCT system where an OCT probe is integrated with a robotic manipulator, enabling wider area spatially-resolved imaging. With the proposed system, it becomes possible to comprehensively scan the kidney surface and provide large area parameterization of the microstructures. We verified the probe tracking accuracy with a phantom as 0.0762±0.0727 mm and demonstrated its clinical feasibility by scanning ex vivo kidneys. The parametric map exhibits fine vasculatures beneath the kidney surface. Quantitative analysis on the proximal convoluted tubule from the ex vivo human kidney yields highly clinical-relevant information.

Polarization coherency matrix tomography.

In this paper, a polarization-sensitive optical coherence tomography (PS-OCT) based polarization coherency matrix tomography (PCMT) combining polarization coherency matrix with Mueller matrix is proposed for the determination of complete polarization properties of tissue. PCMT measures the Jones matrix of biological sample based on similar transformation, in which four elements have initial random phase from different polarization states based on traditional PS-OCT. The results indicate that PCMT can eliminate the phase difference of incident lights with different polarization states. In addition, the polarization coherency matrix using three polarization states has complete information of the sample Jones matrix. Finally, the 16 elements of the sample Mueller matrix are applied for deriving fully polarized optical properties of the sample based on the elliptical diattenuator and the elliptical retarder. Thus, the method based on the PCM and Mueller matrix has the advantage over the traditional PS-OCT.

Automatic renal carcinoma biopsy guidance using forward-viewing endoscopic optical coherence tomography and deep learning.

Percutaneous renal biopsy (PRB) is commonly used for kidney cancer diagnosis. However, current PRB remains challenging in sampling accuracy. This study introduces a forward-viewing optical coherence tomography (OCT) probe for differentiating tumor and normal tissues, aiming at precise PRB guidance. Five human kidneys and renal carcinoma samples were used to evaluate the performance of our probe. Based on their distinct OCT imaging features, tumor and normal renal tissues can be accurately distinguished. We examined the attenuation coefficient for tissue classification and achieved 98.19% tumor recognition accuracy, but underperformed for distinguishing normal tissues. We further developed convolutional neural networks (CNN) and evaluated two CNN architectures: ResNet50 and InceptionV3, yielding 99.51% and 99.48% accuracies for tumor recognition, and over 98.90% for normal tissues recognition. In conclusion, combining OCT and CNN significantly enhanced the PRB guidance, offering a promising guidance technology for improved kidney cancer diagnosis.

Optical Coherence Tomography of Tumor Spheroids Identifies Candidates for Drug Repurposing in Ovarian Cancer.

OBJECTIVE: Multicellular tumor spheroids (MCTs) are indispensable models for evaluating drug efficacy for precision cancer therapeutic strategies as well as for repurposing FDA-approved drugs for ovarian cancer. However, current imaging techniques cannot provide effective monitoring of pathological responses due to shallow penetration and experimentally operative destruction. We plan to utilize a noninvasive optical imaging tool to achieve in vivo longitudinal monitoring of the growth of MCTs and therapeutic responses to repurpose three FDA-approved drugs for ovarian cancer therapy. METHODS: A swept-source optical coherence tomography (SS-OCT) system was used to monitor the volume growth of MCTs over 11 days. Three inhibitors of 2-Methoxyestradiol (2-ME), AZD1208, and R-Ketorolac (R-keto) with concentrations of 1, 10, and 25 µM were employed to treat ovarian MCTs on day 5. Three-dimensional (3D), intrinsic optical attenuation contrast, and degree of uniformity were applied to analyze the therapeutic effect of these inhibitors on ovarian MCTs. RESULTS: We found that 2-ME, AZD1208, and R-keto with concentration of 10 and 25 µM significantly inhibited the volume growth of ovarian MCTs. There was no effect to necrotic tissues from all concentrations of 2-ME, AZD1208, and R-keto inhibitors from our OCT results. 2-ME and AZD1208 inhibited the growth of high uniformity tissues within MCTs and higher concentrations provided more significant inhibitory effects. CONCLUSION: Our results indicated that OCT was capable and reliable to monitor the therapeutic effect of inhibitors to ovarian MCTs and it can be used for the rapid characterization of novel therapeutics for ovarian cancers in the future.

Accelerated cerebromicrovascular senescence contributes to cognitive decline in a mouse model of paclitaxel (Taxol)-induced chemobrain.

Chemotherapy-induced cognitive impairment ("chemobrain") is a frequent side-effect in cancer survivors treated with paclitaxel (PTX). The mechanisms responsible for PTX-induced cognitive impairment remain obscure, and there are no effective treatments or prevention strategies. Here, we test the hypothesis that PTX induces endothelial senescence, which impairs microvascular function and contributes to the genesis of cognitive decline. We treated transgenic p16-3MR mice, which allows the detection and selective elimination of senescent cells, with PTX (5 mg/kg/day, 2 cycles; 5 days/cycle). PTX-treated and control mice were tested for spatial memory performance, neurovascular coupling (NVC) responses (whisker-stimulation-induced increases in cerebral blood flow), microvascular density, blood-brain barrier (BBB) permeability and the presence of senescent endothelial cells (by flow cytometry and single-cell transcriptomics) at 6 months post-treatment. PTX induced senescence in endothelial cells, which associated with microvascular rarefaction, NVC dysfunction, BBB disruption, neuroinflammation, and impaired performance on cognitive tasks. To establish a causal relationship between PTX-induced senescence and impaired microvascular functions, senescent cells were depleted from PTX-treated animals (at 3 months post-treatment) by genetic (ganciclovir) or pharmacological (treatment with the senolytic drug ABT263/Navitoclax) means. In PTX treated mice, both treatments effectively eliminated senescent endothelial cells, rescued endothelium-mediated NVC responses and BBB integrity, increased capillarization and improved cognitive performance. Our findings suggest that senolytic treatments can be a promising strategy for preventing chemotherapy-induced cognitive impairment.

Epidural anesthesia needle guidance by forward-view endoscopic optical coherence tomography and deep learning.

Epidural anesthesia requires injection of anesthetic into the epidural space in the spine. Accurate placement of the epidural needle is a major challenge. To address this, we developed a forward-view endoscopic optical coherence tomography (OCT) system for real-time imaging of the tissue in front of the needle tip during the puncture. We tested this OCT system in porcine backbones and developed a set of deep learning models to automatically process the imaging data for needle localization. A series of binary classification models were developed to recognize the five layers of the backbone, including fat, interspinous ligament, ligamentum flavum, epidural space, and spinal cord. The classification models provided an average classification accuracy of 96.65%. During puncture, it is important to maintain a safe distance between the needle tip and the dura mater. Regression models were developed to estimate that distance based on the OCT imaging data. Based on the Inception architecture, our models achieved a mean absolute percentage error of 3.05% ± 0.55%. Overall, our results validated the technical feasibility of using this novel imaging strategy to automatically recognize different tissue structures and measure the distances ahead of the needle tip during the epidural needle placement.

Computer-aided Veress needle guidance using endoscopic optical coherence tomography and convolutional neural networks.

During laparoscopic surgery, the Veress needle is commonly used in pneumoperitoneum establishment. Precise placement of the Veress needle is still a challenge for the surgeon. In this study, a computer-aided endoscopic optical coherence tomography (OCT) system was developed to effectively and safely guide Veress needle insertion. This endoscopic system was tested by imaging subcutaneous fat, muscle, abdominal space, and the small intestine from swine samples to simulate the surgical process, including the situation with small intestine injury. Each tissue layer was visualized in OCT images with unique features and subsequently used to develop a system for automatic localization of the Veress needle tip by identifying tissue layers (or spaces) and estimating the needle-to-tissue distance. We used convolutional neural networks (CNNs) in automatic tissue classification and distance estimation. The average testing accuracy in tissue classification was 98.53 ± 0.39%, and the average testing relative error in distance estimation reached 4.42 ± 0.56% (36.09 ± 4.92 µm).

Quantitative analysis of vascular changes during photoimmunotherapy using speckle variance optical coherence tomography (SV-OCT).

Near-infrared (NIR) photoimmunotherapy (NIR-PIT) is an emerging cancer therapy based on a monoclonal antibody and phthalocyanine dye conjugate. Direct tumor necrosis and immunogenic cell death occur during NIR irradiation. However, the alteration of tumor blood vessels and blood volume inside the blood vessels induced by the NIR-PIT process is still unknown. In our study, a speckle variance (SV) algorithm combined with optical coherence tomography (OCT) technology was applied to monitor the change of blood vessels and the alterations of the blood volume inside the blood vessels during and after NIR-PIT treatment. Vascular density and the measurable diameter of the lumen in the blood vessel (the diameter of the region filled with blood) were extracted for quantitively uncovering the alterations of blood vessels and blood volume induced by NIR-PIT treatment. The results indicate that both the density and the diameter of the lumen in the blood vessels decrease during the NIR-PIT process, while histological results indicated the blood vessels were dilated. The increase of permeability of blood vessels could lead to the increase of the blood pool volume within the tumor (shown in histology) and results in the decrease of free-moving red blood cells inside the blood vessels (shown in SV-OCT).

A pilot study on biaxial mechanical, collagen microstructural, and morphological characterizations of a resected human intracranial aneurysm tissue.

Intracranial aneurysms (ICAs) are focal dilatations that imply a weakening of the brain artery. Incidental rupture of an ICA is increasingly responsible for significant mortality and morbidity in the American's aging population. Previous studies have quantified the pressure-volume characteristics, uniaxial mechanical properties, and morphological features of human aneurysms. In this pilot study, for the first time, we comprehensively quantified the mechanical, collagen fiber microstructural, and morphological properties of one resected human posterior inferior cerebellar artery aneurysm. The tissue from the dome of a right posterior inferior cerebral aneurysm was first mechanically characterized using biaxial tension and stress relaxation tests. Then, the load-dependent collagen fiber architecture of the aneurysm tissue was quantified using an in-house polarized spatial frequency domain imaging system. Finally, optical coherence tomography and histological procedures were used to quantify the tissue's microstructural morphology. Mechanically, the tissue was shown to exhibit hysteresis, a nonlinear stress-strain response, and material anisotropy. Moreover, the unloaded collagen fiber architecture of the tissue was predominantly aligned with the testing Y-direction and rotated towards the X-direction under increasing equibiaxial loading. Furthermore, our histological analysis showed a considerable damage to the morphological integrity of the tissue, including lack of elastin, intimal thickening, and calcium deposition. This new unified characterization framework can be extended to better understand the mechanics-microstructure interrelationship of aneurysm tissues at different time points of the formation or growth. Such specimen-specific information is anticipated to provide valuable insight that may improve our current understanding of aneurysm growth and rupture potential.