Multiphoton Microscopy Imaging Research Articles

A novel variational approach for multiphoton microscopy image restoration: from PSF estimation to 3D deconvolution

In multi-photon microscopy (MPM), a recent in-vivo fluorescence microscopy system, the task of image restoration can be decomposed into two interlinked inverse problems: firstly, the characterization of the point spread function (PSF) and subsequently, the deconvolution (i.e. deblurring) to remove the PSF effect, and reduce noise. The acquired MPM image quality is critically affected by PSF blurring and intense noise. The PSF in MPM is highly spread in 3D and is not well characterized, presenting high variability with respect to the observed objects. This makes the restoration of MPM images challenging. Common PSF estimation methods in fluorescence microscopy, including MPM, involve capturing images of sub-resolution beads, followed by quantifying the resulting ellipsoidal 3D spot. In this work, we revisit this approach, coping with its inherent limitations in terms of accuracy and practicality. We estimate the PSF from the observation of relatively large beads (approximately 1  μm in diameter). This goes through the formulation and resolution of an original non-convex minimization problem, for which we propose a proximal alternating method along with convergence guarantees. Following the PSF estimation step, we then introduce an innovative strategy to deal with the high level multiplicative noise degrading the acquisitions. We rely on a heteroscedastic noise model for which we estimate the parameters. We then solve a constrained optimization problem to restore the image, accounting for the estimated PSF and noise, while allowing a minimal hyper-parameter tuning. Theoretical guarantees are given for the restoration algorithm. These algorithmic contributions lead to an end-to-end pipeline for 3D image restoration in MPM, that we share as a publicly available Python software. We demonstrate its effectiveness through several experiments on both simulated and real data.

Abstract 6444: Assessing cytotoxic T cell responses to immune checkpoint inhibitors in murine and human tumor samples using metabolic imaging

Abstract Background   Immune checkpoint inhibitors (ICI) have revolutionized cancer treatment. Unfortunately, existing FDA approved biomarkers do not accurately predict which patients will respond. The Elephas Cybrid™ platform aims to improve ICI response prediction by imaging a patient’s biopsy treated with ICI ex vivo.   Multiphoton microscopy (MPM) is a powerful imaging technique to interrogate the biological changes in live tumor fragments (LTFs) following ICI treatment. MPM allows rapid visualization of biological processes in 3D living tissues in a non-destructive fashion allowing for longitudinal assessment of a sample. We and others have used label-free metabolic imaging to demonstrate that changes in T cell metabolism and activation status are correlated. Using MPM imaging we successfully demonstrated T cell activation and T cell mediated cytotoxicity in response to ICI in LTFs and tumor biopsies. Methods   Tumors were cut into LTFs, sorted, and cultured using the Cybrid platform. LTF structure and metabolic status were assessed using intrinsically fluorescent NAD(P)H and FAD. Anti-CD8 nanobodies and cleaved caspase 3/7 dye were used to characterize T cell cytotoxicity. Multi-channel fluorescence intensity and lifetime were obtained over 48 hours using MPM. Results   Murine CT26 LTFs generated with the Cybrid platform were treated with ICI and cytotoxicity was assessed in the intact LTFs by monitoring caspase 3/7 activity using MPM over 48 hours. We found that ICI treatment resulted in a significant increase in caspase 3/7 activity compared to control treated LTFs. By blocking the interaction of T cells with tumor cells through antibody blockade, we demonstrated that the cytotoxicity observed was T cell mediated. As additional confirmation, we measured changes in cytotoxicity in the ICI resistant LLC1 tumor model. As expected, we did not observe an increase in cytotoxicity in LLC1 LTFs treated with ICI. MPM allows for the tracking of labeled T cells and characterization of their metabolism as a means of assessing changes in their activation state. We used a CD8 nanobody to label T cells in CT26 LTFs and then characterized the shift in metabolism following ICI treatment. Finally, we applied the Cybrid platform to human biopsies treated with ICI and characterized the cytotoxicity and shifts in T cell metabolism in living tissue. These data show that the Cybrid platform can measure changes in T cell metabolism and T cell cytotoxicity in response to ICI in 3D living tissue. Conclusions  The methods presented herein will advance the field of cancer diagnostics by progressing from fixed tissue imaging and genetic characterization to the assessment of clinically relevant ICI-treated biopsies. Understanding the response of biopsies to immunotherapies will allow clinicians to make more informed treatment decisions and improve the lives of those with cancer.  Citation Format: Jonathan Ouellette, Janey Degnan, Anna Kellner, Evan Flietner, Lindsay Doebert, Zachary Swider, Eric Wait, Victoria Pope, Laura Hrycyniak, Sean Caenepeel, Kevin Eliceiri, T S. Ramasubramanian, Michael J. Korrer. Assessing cytotoxic T cell responses to immune checkpoint inhibitors in murine and human tumor samples using metabolic imaging [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6444.

Abstract 6786: Assessment of immune cell infiltration and cancer metastatic potential in Akura™ Immune Flow Chip - A microfluidic 3D spheroid system

Abstract Evaluation of novel therapeutics often fails to reliably predict severe complications in patients, especially when circulating cells are involved. The reasons may include inter-species differences upon using animal models or the lack of relevant in vitro systems. Moreover, existing in vitro systems mostly rely on static investigations of different cell types leading to overestimation of effects due to non-representative cell-tissue interactions. The incorporation of medium flow may facilitate to mimic physiological conditions more closely. To tackle current limitations of perfused organ-on-chip approaches, we developed a microfluidic chip and operation concept, which prevents undesired sedimentation and accumulation of cells in suspensions. The Akura™ Immune Flow platform was designed to study flow-dependent recruitment of circulating cells to different tissue spheroids via gravity-driven perfusion over several days. The Akura™ Immune Flow platform features standardized formats for co-culturing up to seven spheroids with suspended cells in each microfluidic channel. On-chip staining protocols enabled monitoring of the co-culture. The system allowed for application and extractions of cellular components and liquid for further off-chip analysis. Primary tissue and cell line spheroids (liver and tumor) could be retained in the respective chambers and remained viable over six to 14 days. Circulating cells were kept viable and in suspension for up to six days (PBMCs) and14 days (Prostate Cancer (PCa) cells) respectively. PBMCs were not activated by flow-induced shear forces. Unspecific stimulation of T-cells led to physiological expression of early and late activation markers (CD69 and CD25), which were detected by flow cytometry in periodically collected cells. Multi-photon microscopy imaging confirmed that PBMCs interacted with and infiltrated into 3D tumor spheroids. Application of PCa cells to primary liver spheroids, cultured in Akura™ Immune Flow chips allowed for assessment of their invasive potential. Confocal imaging revealed adhesion of cancer cells to the liver spheroids and offers the potential to study the ability of tissue invasion at later time points. The simple design of the chip facilitates user-friendly operation and high-throughput implementation in cancer research and drug testing. The selected applications support the relevance of using flow solutions for physiologically more complex processes. This work constitutes an important step towards device application as a tool for basic research as well as for efficacy studies of immunotherapeutic drug candidates Citation Format: Tamara Häfeli, Silas Riss, Christian Lohasz, Dzhansu Hasanova, Svenja Lützow, Lisa Hölting, Michal Rudnik, Franziska Linke, Wytske M van Weerden, Laure-Anne Ligeon, Andreas Hierlemann, Mario Modena, Olivier Frey. Assessment of immune cell infiltration and cancer metastatic potential in Akura™ Immune Flow Chip - A microfluidic 3D spheroid system [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6786.

Phenotypic characterization of liver tissue heterogeneity through a next-generation 3D single-cell atlas

Three-dimensional (3D) geometrical models are potent tools for quantifying complex tissue features and exploring structure–function relationships. However, these models are generally incomplete due to experimental limitations in acquiring multiple (> 4) fluorescent channels in thick tissue sections simultaneously. Indeed, predictive geometrical and functional models of the liver have been restricted to few tissue and cellular components, excluding important cellular populations such as hepatic stellate cells (HSCs) and Kupffer cells (KCs). Here, we combined deep-tissue immunostaining, multiphoton microscopy, deep-learning techniques, and 3D image processing to computationally expand the number of simultaneously reconstructed tissue structures. We then generated a spatial single-cell atlas of hepatic architecture (Hep3D), including all main tissue and cellular components at different stages of post-natal development in mice. We used Hep3D to quantitatively study 1) hepatic morphodynamics from early post-natal development to adulthood, and 2) the effect on the liver's overall structure when changing the hepatic environment after removing KCs. In addition to a complete description of bile canaliculi and sinusoidal network remodeling, our analysis uncovered unexpected spatiotemporal patterns of non-parenchymal cells and hepatocytes differing in size, number of nuclei, and DNA content. Surprisingly, we found that the specific depletion of KCs results in morphological changes in hepatocytes and HSCs. These findings reveal novel characteristics of liver heterogeneity and have important implications for both the structural organization of liver tissue and its function. Our next-gen 3D single-cell atlas is a powerful tool to understand liver tissue architecture, opening up avenues for in-depth investigations into tissue structure across both normal and pathological conditions.

Improving the diagnosis of ductal carcinoma in situ with microinvasion without immunohistochemistry: An innovative method with H&E-stained and multiphoton microscopy images.

Ductal carcinoma in situ with microinvasion (DCISM) is a challenging subtype of breast cancer with controversial invasiveness and prognosis. Accurate diagnosis of DCISM from ductal carcinoma in situ (DCIS) is crucial for optimal treatment and improved clinical outcomes. However, there are often some suspicious small cancer nests in DCIS, and it is difficult to diagnose the presence of intact myoepithelium by conventional hematoxylin and eosin (H&E) stained images. Although a variety of biomarkers are available for immunohistochemical (IHC) staining of myoepithelial cells, no single biomarker is consistently sensitive to all tumor lesions. Here, we introduced a new diagnostic method that provides rapid and accurate diagnosis of DCISM using multiphoton microscopy (MPM). Suspicious foci in H&E-stained images were labeled as regions of interest (ROIs), and the nuclei within these ROIs were segmented using a deep learning model. MPM was used to capture images of the ROIs in H&E-stained sections. The intensity of two-photon excitation fluorescence (TPEF) in the myoepithelium was significantly different from that in tumor parenchyma and tumor stroma. Through the use of MPM, the myoepithelium and basement membrane can be easily observed via TPEF and second-harmonic generation (SHG), respectively. By fusing the nuclei in H&E-stained images with MPM images, DCISM can be differentiated from suspicious small cancer clusters in DCIS. The proposed method demonstrated good consistency with the cytokeratin 5/6 (CK5/6) myoepithelial staining method (kappa coefficient = 0.818).

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

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. 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. 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. 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. 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.

Simultaneous Two- and Three-Photon Deep Imaging of Autofluorescence in Bacterial Communities.

The intrinsic fluorescence of bacterial samples has a proven potential for label-free bacterial characterization, monitoring bacterial metabolic functions, and as a mechanism for tracking the transport of relevant components through vesicles. The reduced scattering and axial confinement of the excitation offered by multiphoton imaging can be used to overcome some of the limitations of single-photon excitation (e.g., scattering and out-of-plane photobleaching) to the imaging of bacterial communities. In this work, we demonstrate in vivo multi-photon microscopy imaging of Streptomyces bacterial communities, based on the excitation of blue endogenous fluorophores, using an ultrafast Yb-fiber laser amplifier. Its parameters, such as the pulse energy, duration, wavelength, and repetition rate, enable in vivo multicolor imaging with a single source through the simultaneous two- and three-photon excitation of different fluorophores. Three-photon excitation at 1040 nm allows fluorophores with blue and green emission spectra to be addressed (and their corresponding ultraviolet and blue single-photon excitation wavelengths, respectively), and two-photon excitation at the same wavelength allows fluorophores with yellow, orange, or red emission spectra to be addressed (and their corresponding green, yellow, and orange single-photon excitation wavelengths). We demonstrate that three-photon excitation allows imaging over a depth range of more than 6 effective attenuation lengths to take place, corresponding to an 800 micrometer depth of imaging, in samples with a high density of fluorescent structures.

Label-free assessment of pathological changes in pancreatic intraepithelial neoplasia by biomedical multiphoton microscopy.

Pancreatic intraepithelial neoplasia (PanIN) is the most common precursor lesion that has the potential to progress to invasive pancreatic cancer, and early and rapid detection may offer patients a chance for treatment before the development of invasive carcinoma. Therefore, the identification of PanIN holds significant clinical importance. In this study, we first used multiphoton microscopy (MPM) combining two-photon excitation fluorescence and second-harmonic generation imaging to label-free detect PanIN and attempted to differentiate between normal pancreatic ducts and different grades of PanIN. Then, we also developed an automatic image processing strategy to extract eight morphological features of collagen fibers from MPM images to quantify the changes in collagen fibers surrounding the ducts. Experimental results demonstrate that the combination of MPM and quantitative information can accurately identify normal pancreatic ducts and different grades of PanIN. This study may contribute to the rapid diagnosis of pancreatic diseases and may lay the foundation for further clinical application of MPM.

The Effect of Diabetes Mellitus Type 1 on the Energy Metabolism of Hepatocytes: Multiphoton Microscopy and Fluorescence Lifetime Imaging

A decrease in the regenerative potential of the liver during the development of non-alcoholic fatty liver disease (NAFLD), which is observed in the vast majority of patients with diabetes mellitus type 1, significantly increases the risk of postoperative liver failure. In this regard, it is necessary to develop new approaches for the rapid intraoperative assessment of the condition of liver tissue in the presence of concomitant liver pathology. A modern label-free approach based on multiphoton microscopy, second harmonic generation (SHG), and fluorescence lifetime imaging microscopy (FLIM) allow for the evaluation of the structure of liver tissue as well as the assessment of the metabolic state of hepatocytes, even at the cellular level. We obtained optical criteria and identified specific changes in the metabolic state of hepatocytes for a reduced liver regenerative potential in the presence of induced diabetes mellitus type 1. The obtained criteria will expand the possibilities for the express assessment of the structural and functional state of liver tissue in clinical practice.

A tissue-engineered model of the atherosclerotic plaque cap: Toward understanding the role of microcalcifications in plaque rupture.

Rupture of the cap of an atherosclerotic plaque can lead to thrombotic cardiovascular events. It has been suggested, through computational models, that the presence of microcalcifications in the atherosclerotic cap can increase the risk of cap rupture. However, the experimental confirmation of this hypothesis is still lacking. In this study, we have developed a novel tissue-engineered model to mimic the atherosclerotic fibrous cap with microcalcifications and assess the impact of microcalcifications on cap mechanics. First, human carotid plaque caps were analyzed to determine the distribution, size, and density of microcalcifications in real cap tissue. Hydroxyapatite particles with features similar to real cap microcalcifications were used as microcalcification mimics. Injected clusters of hydroxyapatite particles were embedded in a fibrin gel seeded with human myofibroblasts which deposited a native-like collagenous matrix around the particles, during the 21-day culture period. Second harmonic multiphoton microscopy imaging revealed higher local collagen fiber dispersion in regions of hydroxyapatite clusters. Tissue-engineered caps with hydroxyapatite particles demonstrated lower stiffness and ultimate tensile stress than the control group samples under uniaxial tensile loading, suggesting increased rupture risk in atherosclerotic plaques with microcalcifications. This model supports previous computational findings regarding a detrimental role for microcalcifications in cap rupture risk and can further be deployed to elucidate tissue mechanics in pathologies with calcifying soft tissues.

Rapid label-free detection of early-stage lung adenocarcinoma and tumor boundary via multiphoton microscopy.

Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer-related deaths in China. Rapid and precise evaluation of tumor tissue during lung cancer surgery can reduce operative time and improve negative-margin assessment, thus increasing disease-free and overall survival rates. This study aimed to explore the potential of label-free multiphoton microscopy (MPM) for imaging adenocarcinoma tissues, detecting histopathological features, and distinguishing between normal and cancerous lung tissues. We showed that second harmonic generation (SHG) signals exhibit significant specificity for collagen fibers, enabling the quantification of collagen features in lung adenocarcinomas. In addition, we developed a collagen score that could be used to distinguish between normal and tumor areas at the tumor boundary, showing good classification performance. Our findings demonstrate that MPM imaging technology combined with an image-based collagen feature extraction method can rapidly and accurately detect early-stage lung adenocarcinoma tissues. This article is protected by copyright. All rights reserved.

Assessing pathological features of breast cancer via the multimodal information of multiphoton and Raman imaging

For unveiling the pathological evolution of breast cancer, nonlinear multiphoton microscopic (MPM) and confocal Raman microspectral imaging (CRMI) techniques were both utilized to address the structural and constitutional characteristics of healthy (H), ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (IDC) tissues. MPM-based techniques, including two-photon excited fluorescence (TPEF) and second harmonic generation (SHG), visualized label-free and the fine structure of breast tissue. Meanwhile, CRMI not only presented the chemical images of investigated samples with the K-mean cluster analysis method (KCA), but also pictured the distribution of components in the scanned area through univariate imaging. MPM images illustrated that the cancer cells first arranged around the basement membrane of the duct, then proliferated to fill the lumens of the duct, and finally broke through the basement membrane to infiltrate into the stroma. Although the Raman imaging failed to visualize the cell structure with high resolution, it explained spectroscopically the gradual increase of nucleic acid and protein components inside the ducts as cancer cells proliferated, and displayed the distribution pattern of each biological component during the evolution of breast cancer. Thus, the combination of MPM and CRMI provided new insights into the on-site pathological diagnosis of malignant breast cancer, also ensured technical support for the development of multimodal optical imaging techniques for precise histopathological analysis.

Benign esophageal stricture model construction and mechanism exploration

Esophageal stricture is a debilitating condition that negatively impacts patients' quality of life after undergoing endoscopic mucosal resection (EMR). Despite its significance, this disease remains underexplored due to the lack of a stable animal model. Under direct visualization with choledochoscopy, we retrogradely damaged the esophageal mucosal layer through the gastrostomy to create a rat model of esophageal stricture. The development of histological defects in the mucosal layer was assessed over a 2-week period after model induction. Then the models were evaluated using X-ray barium radiography, Hematoxylin–Eosin, Masson’s trichrome, Sirius red, and Victoria blue staining, multiphoton microscopic imaging. Additionally, the molecular mechanisms of esophageal stricture were explored by conducting RNA transcriptome sequencing, PCR, immunohistochemistry, and immunofluorescence staining. We successfully established fifteen rat models of esophageal stricture by injuring the mucosal layer. In the model group, the mucosal defect initially occurs and subsequently repaired. The epithelium was absent and was plastically remodeled by collagen during the acute inflammatory phase (Day 1), proliferation phase (Day 7), anaphase of proliferation (Day 10), and plastic remodeling phase (Day 14). We observed increased expression of COL1A1, acta2, FGF, IL-1, and TGF-β1 pathway in the model group. We established a highly repeatable rat model of esophageal stricture, and our results suggest that the mucosal defect of the esophagus is a critical factor in esophageal stricture development, rather than damage to the muscularis layer. We identified Atp4b, cyp1a2, and gstk1 as potential targets for treating esophageal stricture, while the TGF-β pathway was found to play an important role in its development.

The impact of UV cross-linking on corneal stromal cell migration, differentiation and patterning

Previous studies have demonstrated that UV cross-linking (CXL) increases stromal stiffness and produces alterations in extracellular matrix (ECM) microstructure. In order to investigate how CXL impacts both keratocyte differentiation and patterning within the stroma, and fibroblast migration and myofibroblast differentiation on top of the stroma, we combined CXL with superficial phototherapeutic keratectomy (PTK) in a rabbit model. Twenty-six rabbits underwent a 6 mm diameter, 70 μm deep phototherapeutic keratectomy (PTK) with an excimer laser to remove the epithelium and anterior basement membrane. In 14 rabbits, standard CXL was performed in the same eye immediately after PTK. Contralateral eyes served as controls. In vivo confocal microscopy through focusing (CMTF) was used to analyze corneal epithelial and stromal thickness, as well as stromal keratocyte activation and corneal haze. CMTF scans were collected pre-operatively, and from 7 to 120 days after the procedure. A subset of rabbits was sacrificed at each time point, and corneas were fixed and labeled in situ for multiphoton fluorescence microscopy and second harmonic generation imaging. In vivo and in situ imaging demonstrated that haze after PTK was primarily derived from a layer of myofibroblasts that formed on top of the native stroma. Over time, this fibrotic layer was remodeled into more transparent stromal lamellae, and quiescent cells replaced myofibroblasts. Migrating cells within the native stroma underneath the photoablated area were elongated, co-aligned with collagen, and lacked stress fibers. In contrast, following PTK + CXL, haze was derived primarily from highly reflective necrotic “ghost cells” in the anterior stroma, and fibrosis on top of the photoablated stroma was not observed at any time point evaluated. Cells formed clusters as they migrated into the cross-linked stromal tissue and expressed stress fibers; some cells at the edge of the CXL area also expressed α-SM actin, suggesting myofibroblast transformation. Stromal thickness increased significantly between 21 and 90 days after PTK + CXL (P < 0.001) and was over 35 μm higher than baseline at Day 90 (P < 0.05). Overall, these data suggest that cross-linking inhibits interlamellar cell movement, and that these changes lead to a disruption of normal keratocyte patterning and increased activation during stromal repopulation. Interestingly, CXL also prevents PTK-induced fibrosis on top of the stroma, and results in long term increases in stromal thickness in the rabbit model.

Differentiating Morphea from Lichen Sclerosus by Using Multiphoton Microscopy Combined with U-Net Model for Elastic Fiber Segmentation.

This paper describes a methodology to differentiate morphea from lichen sclerosus based on examination with multiphoton microscopy (MPM) composed of two-photon excited fluorescence (TPEF) and second harmonic generation (SHG). Subcellular-resolution images were acquired by MPM from unstained lesion tissues then process spectral analysis to quantify the TPEF and SHG signals. Moreover, U-Net was employed to segment elastic fiber in TPEF images to combine with collagen fiber in SHG images for precise fiber quantification. Predictions of segmentation showed excellent performance on several evaluation indicators. The mIoU, mPA, and F1 score reach 0.8516, 0.9281, and 0.941. The quantitative analysis demonstrated the increase of collagen fibers in morphea compared to that in lichen sclerosus cases. Meanwhile, the great diminution of elastic fiber in the dermis of lichen sclerosus was depicted based on MPM imaging. Thus, MPM was comparable to the histopathological examination and our experimental results accurately distinguish between morphea and lichen sclerosus. This article is protected by copyright. All rights reserved.

Temporal focusing multiphoton microscopy with cross-modality multi-stage 3D U-Net for fast and clear bioimaging.

Temporal focusing multiphoton excitation microscopy (TFMPEM) enables fast widefield biotissue imaging with optical sectioning. However, under widefield illumination, the imaging performance is severely degraded by scattering effects, which induce signal crosstalk and a low signal-to-noise ratio in the detection process, particularly when imaging deep layers. Accordingly, the present study proposes a cross-modality learning-based neural network method for performing image registration and restoration. In the proposed method, the point-scanning multiphoton excitation microscopy images are registered to the TFMPEM images by an unsupervised U-Net model based on a global linear affine transformation process and local VoxelMorph registration network. A multi-stage 3D U-Net model with a cross-stage feature fusion mechanism and self-supervised attention module is then used to infer in-vitro fixed TFMPEM volumetric images. The experimental results obtained for in-vitro drosophila mushroom body (MB) images show that the proposed method improves the structure similarity index measures (SSIMs) of the TFMPEM images acquired with a 10-ms exposure time from 0.38 to 0.93 and 0.80 for shallow- and deep-layer images, respectively. A 3D U-Net model, pretrained on in-vitro images, is further trained using a small in-vivo MB image dataset. The transfer learning network improves the SSIMs of in-vivo drosophila MB images captured with a 1-ms exposure time to 0.97 and 0.94 for shallow and deep layers, respectively.

Repeated Measurement of Microglia-Dendritic Spine Interactions Using Multi-Photon Imaging.

In recent decades, mounting evidence has shown that microglia play a vital role in maintaining synapses throughout life. This maintenance is done via numerous microglial processes, which are long, thin, and highly motile protrusions from the cell body that monitor their environment. However, due to the brevity of the contacts and the potentially transient nature of synaptic structures, establishing the underlying dynamics of this relationship has proven difficult. This article describes a method of using rapidly acquired multiphoton microscopy images to track microglial dynamics and microglia:synapse interactions and the fate of the synaptic structures following those interactions. First, we detail a method for capturing multiphoton images at 1-min intervals for approximately 1 hr and how that process can be done at multiple time points. We then discuss how best to prevent and account for any drifting of the region of interest that can occur during the imaging session and how to remove excessive background noise from those images. Finally, we detail the annotation process for dendritic spines and microglial processes using plugins in MATLAB and Fiji, respectively. These semi-automated plugins allow tracking of individual cell structures, even if both microglia and neurons are imaged in the same fluorescent channel. This protocol presents a method of tracking both microglial dynamics and synaptic structures, in the same animal, at multiple time points, giving the user information on process speed, branching, tip size, location, and dwell time, as well as any dendritic spine gains, losses, and size changes. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Rapid multiphoton image capture Basic Protocol 2: Image preparation using MATLAB and Fiji Basic Protocol 3: Dendritic spine and microglial processes annotation using ScanImage and TrackMate.

Elastin is responsible for the rigidity of the ligament under shear and rotational stress: a mathematical simulation study

BackgroundAn accurate understanding of the mechanical response of ligaments is important for preventing their damage and rupture. To date, ligament mechanical responses are being primarily evaluated using simulations. However, many mathematical simulations construct models of uniform fibre bundles or sheets using merely collagen fibres and ignore the mechanical properties of other components such as elastin and crosslinkers. Here, we evaluated the effect of elastin-specific mechanical properties and content on the mechanical response of ligaments to stress using a simple mathematical model.MethodsBased on multiphoton microscopic images of porcine knee collateral ligaments, we constructed a simple mathematical simulation model that individually includes the mechanical properties of collagen fibres and elastin (fibre model) and compared with another model that considers the ligament as a single sheet (sheet model). We also evaluated the mechanical response of the fibre model as a function of the elastin content, from 0 to 33.5%. Both ends of the ligament were fixed to a bone, and tensile, shear, and rotational stresses were applied to one of the bones to evaluate the magnitude and distribution of the stress applied to the collagen and elastin at each load.ResultsUniform stress was applied to the entire ligament in the sheet model, whereas in the fibre model, strong stress was applied at the junction between collagen fibres and elastin. Even in the same fibre model, as the elastin content increased from 0 to 14.4%, the maximum stress and displacement applied to the collagen fibres during shear stress decreased by 65% and 89%, respectively. The slope of the stress–strain relationship at 14.4% elastin was 6.5 times greater under shear stress than that of the model with 0% elastin. A positive correlation was found between the stress required to rotate the bones at both ends of the ligament at the same angle and elastin content.ConclusionsThe fibre model, which includes the mechanical properties of elastin, can provide a more precise evaluation of the stress distribution and mechanical response. Elastin is responsible for ligament rigidity during shear and rotational stress.

Changes in the microstructure of the human aortic adventitia under biaxial loading investigated by multi-photon microscopy.

Among the three layers of the aortic wall, the media is primarily responsible for its mechanical properties, but the adventitia prevents the aorta from overstretching and rupturing. The role of the adventitia is therefore crucial with regard to aortic wall failure, and understanding the load-induced changes in tissue microstructure is of high importance. Specifically, the focus of this study is on the changes in collagen and elastin microstructure in response to macroscopic equibiaxial loading applied to the aortic adventitia. To observe these changes, multi-photon microscopy imaging and biaxial extension tests were performed simultaneously. In particular, microscopy images were recorded at 0.02 stretch intervals. The microstructural changes of collagen fiber bundles and elastin fibers were quantified with the parameters of orientation, dispersion, diameter, and waviness. The results showed that the adventitial collagen was divided from one into two fiber families under equibiaxial loading conditions. The almost diagonal orientation of the adventitial collagen fiber bundles remained unchanged, but the dispersion was substantially reduced. No clear orientation of the adventitial elastin fibers was observed at any stretch level. The waviness of the adventitial collagen fiber bundles decreased under stretch, but the adventitial elastin fibers showed no change. These original findings highlight differences between the medial and adventitial layers and provide insight into the stretching process of the aortic wall. STATEMENT OF SIGNIFICANCE: To provide accurate and reliable material models, it is essential to understand the mechanical behavior of the material and its microstructure. Such understanding can be enhanced with tracking of the microstructural changes caused by mechanical loading of the tissue. This study provides therefore a unique dataset of structural parameters of the human aortic adventitia obtained under equibiaxial loading. The structural parameters describe orientation, dispersion, diameter, and waviness of collagen fiber bundles and elastin fibers. Eventually, the microstructural changes in the human aortic adventitia are compared with the microstructural changes in the human aortic media from a previous study. This comparison reveals the cutting-edge findings on the differences in the response to the loading between these two human aortic layers.

A dataset of rodent cerebrovasculature from in vivo multiphoton fluorescence microscopy imaging

We present MiniVess, the first annotated dataset of rodent cerebrovasculature, acquired using two-photon fluorescence microscopy. MiniVess consists of 70 3D image volumes with segmented ground truths. Segmentations were created using traditional image processing operations, a U-Net, and manual proofreading. Code for image preprocessing steps and the U-Net are provided. Supervised machine learning methods have been widely used for automated image processing of biomedical images. While much emphasis has been placed on the development of new network architectures and loss functions, there has been an increased emphasis on the need for publicly available annotated, or segmented, datasets. Annotated datasets are necessary during model training and validation. In particular, datasets that are collected from different labs are necessary to test the generalizability of models. We hope this dataset will be helpful in testing the reliability of machine learning tools for analyzing biomedical images.