Comparison of Different Tissue Clearing Methods for Three-Dimensional Reconstruction of Human Brain Cellular Anatomy Using Advanced Imaging Techniques.
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ABSTRACT:
SUBMITTER: Scardigli M
PROVIDER: S-EPMC8632656 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Tissue clearing methods promise to provide exquisite three-dimensional imaging information; however, there is a need for simplified methods for lower resource settings and for non-fluorescence based phenotyping to enable light microscopic imaging modalities. Here we describe the simplified CLARITY method (SCM) for tissue clearing that preserves epitopes of interest. We imaged the resulting tissues using light sheet microscopy to generate rapid 3D reconstructions of entire tissues and organs. In addition, to enable clearing and 3D tissue imaging with light microscopy methods, we developed a colorimetric, non-fluorescent method for specifically labeling cleared tissues based on horseradish peroxidase conversion of diaminobenzidine to a colored insoluble product. The methods we describe here are portable and can be accomplished at low cost, and can allow light microscopic imaging of cleared tissues, thus enabling tissue clearing and imaging in a wide variety of settings.
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Project description:Optical clearing is a versatile approach to improve imaging quality and depth of optical microscopy by reducing scattered light. However, conventional optical clearing methods are restricted in the efficiency-first applications due to unsatisfied time consumption, irreversible tissue deformation, and fluorescence quenching. Here, we developed an ultrafast optical clearing method (FOCM) with simple protocols and common reagents to overcome these limitations. The results show that FOCM can rapidly clarify 300-µm-thick brain slices within 2 min. Besides, the tissue linear expansion can be well controlled by only a 2.12% increase, meanwhile the fluorescence signals of GFP can be preserved up to 86% even after 11 d. By using FOCM, we successfully built the detailed 3D nerve cells model and showed the connection between neuron, astrocyte, and blood vessel. When applied to 3D imaging analysis, we found that the foot shock and morphine stimulation induced distinct c-fos pattern in the paraventricular nucleus of the hypothalamus (PVH). Therefore, FOCM has the potential to be a widely used sample mounting media for biological optical imaging.
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Project description:An understanding of the anatomy of the Denonvilliers' fascia is essential for successful surgical outcomes for patients with rectal cancer in the mid- to lower regions, especially near the seminal vesicles and prostate in males. Whether the correct surgical plane during a total mesorectal excision should be anterior or posterior to the Denonvilliers' fascia is currently under debate. This study aimed to investigate the Denonvilliers' fascia using micro-computed tomography (micro-CT) to acquire three-dimensional images nondestructively for assessments of the relationship between the Denonvilliers' fascia, the mesorectal fascia, and neurovascular bundles to elucidate the correct anterior total mesorectal excision plane. Eight specimens were obtained bilaterally from four fresh human cadavers. Four specimens were stained with phosphotungstic acid to visualize the soft tissue, and micro-CT images were obtained; the other four specimens were stained with Masson's trichrome to visualize connective tissue. Micro-CT images corroborate that the Denonvilliers' fascia consists of a multilayered structure that separates the rectum from the seminal vesicles and the prostate. Specimens stained with Masson's trichrome showed that the urogenital neurovascular bundle located at the posterolateral corner of the prostate is separated from the mesorectum by the Denonvilliers' fascia. For the preservation of autonomic nerves necessary for urogenital function and optimal oncologic outcomes in patients with rectal cancer, a successful mesorectal excision requires a dissection plane posterior to the Denonvilliers' fascia.
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Project description:PurposeTo develop a machine-learning image processing model for three-dimensional (3D) reconstruction of vitreous anatomy visualized with swept-source optical coherence tomography (SS-OCT).MethodsHealthy subjects were imaged with SS-OCT. Scans of sufficient quality were transferred into the Fiji is just ImageJ image processing toolkit, and proportions of the resulting stacks were adjusted to form cubic voxels. Image-averaging and Trainable Weka Segmentation using Sobel and variance edge detection and directional membrane projections filters were used to enhance and interpret the signals from vitreous gel, liquid spaces within the vitreous, and interfaces between the former. Two classes were defined: "Septa" and "Other." Pixels were selected and added to each class to train the classifier. Results were generated as a probability map. Thresholding was performed to remove pixels that were classified with low confidence. Volume rendering was performed with TomViz.ResultsForty-seven eyes of 34 healthy subjects were imaged with SS-OCT. Thirty-four cube scans from 25 subjects were of sufficient quality for volume rendering. Clinically relevant vitreous features including the premacular bursa, area of Martegiani, and prevascular vitreous fissures and cisterns, as well as varying degrees of vitreous degeneration were visualized in 3D.ConclusionsA machine-learning model for 3D vitreous reconstruction of SS-OCT cube scans was developed. The resultant high-resolution 3D movies illustrated vitreous anatomy in a manner like triamcinolone-assisted vitrectomy or postmortem dye injection.Translational relevanceThis machine learning model now allows for comprehensive examination of the vitreous structure beyond the vitreoretinal interface in 3D with potential applications for common disease states such as the vitreomacular traction and Macular Hole spectrum of diseases or proliferative diabetic retinopathy.
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Project description:BackgroundRecently, we demonstrated the three-dimensional (3D) localization of murine trophoblast giant cells in the pregnant uterus using a modified Clear Unobstructed Brain Imaging Cocktails and Computational analysis (CUBIC) tissue-clearing method and hybrid construct consisting of the cytomegalovirus enhancer fused to the chicken beta-actin promoter (CAG) conjugated enhanced green fluorescent protein (EGFP) transgenic mice. In this study, we applied this method to obtain a transparent whole-image of the ovary and observed the 3D localization of individual oocytes in the developing follicles.MethodsOvarian samples were obtained from EGFP transgenic mice and subjected to nuclear staining with propidium iodide (PI) and CUBIC treatment. The detection of double fluorescence signals (green and red) and subsequent reconstruction of 3D images of the whole ovary were performed by light-sheet microscopy and computer programs, respectively.ResultsThe ovary became transparent using the CUBIC method and each nucleus of the follicle component cells was uniformly fluoro-stained by PI perfusion. In contrast, EGFP signals were strong in oocytes, whereas those of surrounding granulosa cells were faint. These signal differences in EGFP expression among oocytes, granulosa cells, and theca-interstitial cells produce well-contrasted images of the growing follicles, providing clear information of the 3D localization of individual oocytes.ConclusionThese results indicate that this procedure is one of the effective approaches to analyze the 3D structure of follicles in the whole ovary.
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