The applications of multiphoton microscopy for deep tissue imaging in basic and clinical research are ever increasing, supplementing confocal imaging of the surface layers of cells in tissue. However, imaging living tissue is made difficult by the light scattering properties of the tissue, and this is extraordinarily apparent in the mouse mammary gland which contains a stroma filled with fat cells surrounding the ductal epithelium. Whole mount mammary glands stained with Carmine Alum are easily archived for later reference and readily viewed using bright field microscopy to observe branching architecture of the ductal network. Here, we report on the advantages of multiphoton imaging of whole mount mammary glands. Chief among them is that optical sectioning of the terminal end bud (TEB) and ductal epithelium allows the appreciation of abnormalities in structure that are very difficult to ascertain using either bright field imaging of the stained gland or the conventional approach of hematoxylin and eosin staining of fixed and paraffin-embedded sections. A second advantage is the detail afforded by second harmonic generation (SHG) in which collagen fiber orientation and abundance can be observed.
GFP-mouse mammary glands were imaged live or after whole mount preparation using a Zeiss LSM510/META/NLO multiphoton microscope with the purpose of obtaining high resolution images with 3D content, and evaluating any structural alterations induced by whole mount preparation. We describe a simple means for using a commercial confocal/ multiphoton microscope equipped with a Ti-Sapphire laser to simultaneously image Carmine Alum fluorescence and collagen fiber networks by SHG with laser excitation set to 860 nm. Identical terminal end buds (TEBs) were compared before and after fixation, staining, and whole mount preparation and structure of collagen networks and TEB morphologies were determined. Flexibility in excitation and emission filters was explored using the META detector for spectral emission scanning. Backward scattered or reflected SHG (SHG-B) was detected using a conventional confocal detector with maximum aperture and forward scattered or transmitted SHG (SHG-F) detected using a non-descanned detector.
We show here that the developing mammary gland is encased in a thin but dense layer of collagen fibers. Sparse collagen layers are also interspersed between stromal layers of fat cells surrounding TEBs. At the margins, TEBs approach the outer collagen layer but do not penetrate it. Abnormal mammary glands from an HAI-1 transgenic FVB mouse model were found to contain TEBs with abnormal pockets of cells forming extra lumens and zones of continuous lateral bud formation interspersed with sparse collagen fibers.
Parameters influencing live imaging and imaging of fixed unstained and Carmine Alum stained whole mounts were evaluated. Artifacts induced by light scattering of GFP and Carmine Alum signals from epithelial cells were identified in live tissue as primarily due to fat cells and in whole mount tissue as due to dense Carmine Alum staining of epithelium. Carmine Alum autofluorescence was detected at excitation wavelengths from 750 to 950 nm with a peak of emission at 623 nm (~602-656 nm). Images of Carmine Alum fluorescence differed dramatically at emission wavelengths of 565–615 nm versus 650–710 nm. In the latter, a mostly epithelial (nuclear) visualization of Carmine Alum predominates. Autofluorescence with a peak emission of 495 nm was derived from the fixed and processed tissue itself as it was present in the unstained whole mount. Contribution of autofluorescence to the image decreases with increasing laser excitation wavelengths. SHG-B versus SHG-F signals revealed collagen fibers and could be found within single fibers, or in different fibers within the same layer. These differences presumably reflected different states of collagen fiber maturation. Loss of SHG signals from layer to layer could be ascribed to artifacts rendered by light scattering from the dense TEB structures, and unless bandpass emissions were selected, contained unfiltered non-SHG fluorescence and autofluorescent emissions. Flexibility in imaging can be increased using spectral emission imaging to optimize emission bandwidths and to separate SHG-B, GFP, and Carmine Alum signals, although conventional filters were also useful.
Collagen fibril arrangement and TEB structure is well preserved during the whole mount procedure and light scattering is reduced dramatically by extracting fat resulting in improved 3D structure, particularly for SHG signals originating from collagen. In addition to providing a bright signal, Carmine Alum stained whole mount slides can be imaged retrospectively such as performed for the HAI-1 mouse gland revealing new aspects of abnormal TEB morphology. These studies demonstrated the intimate contact, but relatively sparse abundance of collagen fibrils adjacent to normal and abnormal TEBS in the developing mammary gland and the ability to obtain these high resolution details subject to the discussed limitations. Our studies demonstrated that the TEB architecture is essentially unchanged after processing.
We present a very simple procedure yielding high-contrast images of adherent, confluent cells such as human neuroblastoma (SH-EP) cells by ordinary bright-field microscopy. Cells are illuminated through a color filter and a pinhole aperture placed between the condenser and the cell culture surface. Refraction by each cell body generates a sharp, bright spot when the image is defocused. The technique allows robust, automatic cell counting from a single bright-field image in a wide range of focal positions; it does this via free, readily available image-analysis tools. Contrast may be enhanced by swelling cell bodies by brief incubation in PBS. The procedure was benchmarked against manual counting and automated counting of fluorescently labeled cell nuclei.. Counts from day-old and freshly seeded plates were compared in a range of densities, from sparse to densely overgrown. On average bright-field images produced the same counts as fluorescent images, with less than 5% error. This method will allow routine cell counting using a plain bright-field microscope, absent cell-line modification or cell staining.
Brightfield; microscopy; fluorescence; cell culture; counting; pinhole; monochomatic; PBS; defocusing
In recent years, high-throughput microscopy has emerged as a powerful tool to analyze cellular dynamics in an unprecedentedly high resolved manner. The amount of data that is generated, for example in long-term time-lapse microscopy experiments, requires automated methods for processing and analysis. Available software frameworks are well suited for high-throughput processing of fluorescence images, but they often do not perform well on bright field image data that varies considerably between laboratories, setups, and even single experiments.
In this contribution, we present a fully automated image processing pipeline that is able to robustly segment and analyze cells with ellipsoid morphology from bright field microscopy in a high-throughput, yet time efficient manner. The pipeline comprises two steps: (i) Image acquisition is adjusted to obtain optimal bright field image quality for automatic processing. (ii) A concatenation of fast performing image processing algorithms robustly identifies single cells in each image. We applied the method to a time-lapse movie consisting of ∼315,000 images of differentiating hematopoietic stem cells over 6 days. We evaluated the accuracy of our method by comparing the number of identified cells with manual counts. Our method is able to segment images with varying cell density and different cell types without parameter adjustment and clearly outperforms a standard approach. By computing population doubling times, we were able to identify three growth phases in the stem cell population throughout the whole movie, and validated our result with cell cycle times from single cell tracking.
Our method allows fully automated processing and analysis of high-throughput bright field microscopy data. The robustness of cell detection and fast computation time will support the analysis of high-content screening experiments, on-line analysis of time-lapse experiments as well as development of methods to automatically track single-cell genealogies.
Giemsa staining of thick blood smears remains the "gold standard" for detecting malaria. However, this method is not very good for diagnosing low-level infections. A method for the simultaneous staining of Plasmodium-parasitized culture and blood smears for both bright field and fluorescence was developed and its ability to improve detection efficiency tested.
A total of 22 nucleic acid-specific fluorescent dyes were tested for their ability to provide easily observable staining of Plasmodium falciparum-parasitized red blood cells following Giemsa staining.
Of the 14 dyes that demonstrated intense fluorescence staining, only SYBR Green 1, YOYO-1 and ethidum homodimer-2 could be detected using fluorescent microscopy, when cells were first stained with Giemsa. Giemsa staining was not effective when applied after the fluorescent dyes. SYBR Green 1 provided the best staining in the presence of Giemsa, as a very high percentage of the parasitized cells were simultaneously stained. When blood films were screened using fluorescence microscopy the parasites were more readily detectable due to the sharp contrast between the dark background and the specific, bright fluorescence produced by the parasites.
The dual staining method reported here allows fluorescence staining, which enhances the reader's ability to detect parasites under low parasitaemia conditions, coupled with the ability to examine the same cell under bright field conditions to detect the characteristic morphology of Plasmodium species that is observed with Giemsa staining.
Patients with cerebral metastasis of carcinomas have a poor prognosis. However, the process at the metastatic site has barely been investigated, in particular the role of the resident (stromal) cells. Studies in primary carcinomas demonstrate the influence of the microenvironment on metastasis, even on prognosis1,2. Especially the tumor associated macrophages (TAM) support migration, invasion and proliferation3. Interestingly, the major target sites of metastasis possess tissue-specific macrophages, such as Kupffer cells in the liver or microglia in the CNS. Moreover, the metastatic sites also possess other tissue-specific cells, like astrocytes. Recently, astrocytes were demonstrated to foster proliferation and persistence of cancer cells4,5. Therefore, functions of these tissue-specific cell types seem to be very important in the process of brain metastasis6,7.
Despite these observations, however, up to now there is no suitable in vivo/in vitro model available to directly visualize glial reactions during cerebral metastasis formation, in particular by bright field microscopy. Recent in vivo live imaging of carcinoma cells demonstrated their cerebral colonization behavior8. However, this method is very laborious, costly and technically complex. In addition, these kinds of animal experiments are restricted to small series and come with a substantial stress for the animals (by implantation of the glass plate, injection of tumor cells, repetitive anaesthesia and long-term fixation). Furthermore, in vivo imaging is thus far limited to the visualization of the carcinoma cells, whereas interactions with resident cells have not yet been illustrated. Finally, investigations of human carcinoma cells within immunocompetent animals are impossible8.
For these reasons, we established a coculture system consisting of an organotypic mouse brain slice and epithelial cells embedded in matrigel (3D cell sphere). The 3D carcinoma cell spheres were placed directly next to the brain slice edge in order to investigate the invasion of the neighboring brain tissue. This enables us to visualize morphological changes and interactions between the glial cells and carcinoma cells by fluorescence and even by bright field microscopy. After the coculture experiment, the brain tissue or the 3D cell spheroids can be collected and used for further molecular analyses (e.g. qRT-PCR, IHC, or immunoblot) as well as for investigations by confocal microscopy. This method can be applied to monitor the events within a living brain tissue for days without deleterious effects to the brain slices. The model also allows selective suppression and replacement of resident cells by cells from a donor tissue to determine the distinct impact of a given genotype. Finally, the coculture model is a practicable alternative to in vivo approaches when testing targeted pharmacological manipulations.
Medicine; Issue 80; Brain Tissue; Cancer Cells; Nervous System; Neoplasms; Therapeutics; Organotypic brain slice; coculture; tumor invasion; cerebral colonization; brain metastasis; microglia; astrocyte; live-imaging
Undiluted blood samples are difficult to image in large volumes since blood constitutes a highly absorbing and scattering medium. As a result of this limitation, optical imaging of rare cells (e.g., circulating tumour cells) within unprocessed whole blood remains a challenge, demanding the use of special micro-fluidic technologies. Here we demonstrate a new fluorescent on-chip imaging modality that can rapidly screen large volumes of absorbing and scattering media such as undiluted whole blood samples for detection of fluorescent micro-objects at low concentrations (for example ≤ 50–100 particles/mL). In this high-throughput imaging modality, a large area micro-fluidic device (e.g., 7–18 cm2), which contains for example ~0.3–0.7 mL of undiluted whole blood sample, is directly positioned onto a wide-field opto-electronic sensor-array such that the fluorescent emission within the micro-channel can be detected without the use of any imaging lenses. This micro-fluidic device is then illuminated and laterally scanned with an array of Gaussian excitation spots, which is generated through a spatial light modulator. For each scanning position of this excitation array, a lensfree fluorescent image of the blood sample is captured using the opto-electronic sensor-array, resulting in a sequence of images (e.g., 144 lensfree frames captured in ~36 seconds) for the same sample chip. Digitally merging these lensfree fluorescent images based on a Maximum Intensity Projection (MIP) algorithm enabled us to significantly boost the signal-to-noise ratio (SNR) and contrast of the fluorescent micro-objects within whole blood, which normally remain undetected (i.e., hidden) using conventional uniform excitation schemes, involving plane wave illumination. This high-throughput on-chip imaging platform based on structured excitation could be useful for rare cell research by enabling rapid screening of large volume micro-fluidic devices that process whole blood and other optically dense media.
Automated image analysis, measurements of virtual slides, and open access electronic measurement user systems require standardized image quality assessment in tissue-based diagnosis.
To describe the theoretical background and the practical experiences in automated image quality estimation of colour images acquired from histological slides.
Theory, material and measurements
Digital images acquired from histological slides should present with textures and objects that permit automated image information analysis. The quality of digitized images can be estimated by spatial independent and local filter operations that investigate in homogenous brightness, low peak to noise ratio (full range of available grey values), maximum gradients, equalized grey value distribution, and existence of grey value thresholds. Transformation of the red-green-blue (RGB) space into the hue-saturation-intensity (HSI) space permits the detection of colour and intensity maxima/minima. The feature distance of the original image to its standardized counterpart is an appropriate measure to quantify the actual image quality. These measures have been applied to a series of H&E stained, fluorescent (DAPI, Texas Red, FITC), and immunohistochemically stained (PAP, DAB) slides. More than 5,000 slides have been measured and partly analyzed in a time series.
Analysis of H&E stained slides revealed low shading corrections (10%) and moderate grey value standardization (10 – 20%) in the majority of cases. Immunohistochemically stained slides displayed greater shading and grey value correction. Fluorescent stained slides are often revealed to high brightness. Images requiring only low standardization corrections possess at least 5 different statistically significant thresholds, which are useful for object segmentation. Fluorescent images of good quality only posses one singular intensity maximum in contrast to good images obtained from H&E stained slides that present with 2 – 3 intensity maxima.
Evaluation of image quality and creation of formally standardized images should be performed prior to automatic analysis of digital images acquired from histological slides. Spatial dependent and local filter operations as well as analysis of the RGB and HSI spaces are appropriate methods to reproduce evaluated formal image quality.
We developed a cryo-imaging system to provide single-cell detection of fluorescently labeled cells in mouse, with particular applicability to stem cells and metastatic cancer. The Case cryo-imaging system consists of a fluorescence microscope, robotic imaging positioner, customized cryostat, PC-based control system, and visualization/analysis software. The system alternates between sectioning (10−40 μm) and imaging, collecting color brightfield and fluorescent block-face image volumes >60GB. In mouse experiments, we imaged quantum-dot labeled stem cells, GFP-labeled cancer and stem cells, and cell-size fluorescent microspheres. To remove subsurface fluorescence, we used a simplified model of light-tissue interaction whereby the next image was scaled, blurred, and subtracted from the current image. We estimated scaling and blurring parameters by minimizing entropy of subtracted images. Tissue specific attenuation parameters were found [uT : heart (267 ± 47.6 μm), liver (218 ± 27.1 μm), brain (161 ± 27.4 μm)] to be within the range of estimates in the literature. “Next image” processing removed subsurface fluorescence equally well across multiple tissues (brain, kidney, liver, adipose tissue, etc.), and analysis of 200 microsphere images in the brain gave 97±2% reduction of subsurface fluorescence. Fluorescent signals were determined to arise from single cells based upon geometric and integrated intensity measurements. Next image processing greatly improved axial resolution, enabled high quality 3D volume renderings, and improved enumeration of single cells with connected component analysis by up to 24%. Analysis of image volumes identified metastatic cancer sites, found homing of stem cells to injury sites, and showed microsphere distribution correlated with blood flow patterns.
We developed and evaluated cryo-imaging to provide single-cell detection of fluorescently labeled cells in mouse. Our cryo-imaging system provides extreme (>60GB), micron-scale, fluorescence, and bright field image data. Here we describe our image pre-processing, analysis, and visualization techniques. Processing improves axial resolution, reduces subsurface fluorescence by 97%, and enables single cell detection and counting. High quality 3D volume renderings enable us to evaluate cell distribution patterns. Applications include the myriad of biomedical experiments using fluorescent reporter gene and exogenous fluorophore labeling of cells in applications such as stem cell regenerative medicine, cancer, tissue engineering, etc.
image processing; block face imaging; fluorescence imaging; in vivo cellular imaging; stem cell imaging; cryo-imaging
Many cell lines currently used in medical research, such as cancer cells or stem cells, grow in confluent sheets or colonies. The biology of individual cells provide valuable information, thus the separation of touching cells in these microscopy images is critical for counting, identification and measurement of individual cells. Over-segmentation of single cells continues to be a major problem for methods based on morphological watershed due to the high level of noise in microscopy cell images. There is a need for a new segmentation method that is robust over a wide variety of biological images and can accurately separate individual cells even in challenging datasets such as confluent sheets or colonies.
We present a new automated segmentation method called FogBank that accurately separates cells when confluent and touching each other. This technique is successfully applied to phase contrast, bright field, fluorescence microscopy and binary images. The method is based on morphological watershed principles with two new features to improve accuracy and minimize over-segmentation.
First, FogBank uses histogram binning to quantize pixel intensities which minimizes the image noise that causes over-segmentation. Second, FogBank uses a geodesic distance mask derived from raw images to detect the shapes of individual cells, in contrast to the more linear cell edges that other watershed-like algorithms produce.
We evaluated the segmentation accuracy against manually segmented datasets using two metrics. FogBank achieved segmentation accuracy on the order of 0.75 (1 being a perfect match). We compared our method with other available segmentation techniques in term of achieved performance over the reference data sets. FogBank outperformed all related algorithms. The accuracy has also been visually verified on data sets with 14 cell lines across 3 imaging modalities leading to 876 segmentation evaluation images.
FogBank produces single cell segmentation from confluent cell sheets with high accuracy. It can be applied to microscopy images of multiple cell lines and a variety of imaging modalities. The code for the segmentation method is available as open-source and includes a Graphical User Interface for user friendly execution.
Electronic supplementary material
The online version of this article (doi:10.1186/s12859-014-0431-x) contains supplementary material, which is available to authorized users.
FogBank; Single cell segmentation; Robustness; Open-source
Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs) is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF) on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC) images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional fluorescence single-cell processing to perform objective, accurate quantitative analyses for various biological applications.
Carbon-based nanomaterials, like carbon nanotubes (CNTs), belong to this type of nanoparticles which are very difficult to discriminate from carbon-rich cell structures and de facto there is still no quantitative method to assess their distribution at cell and tissue levels. What we propose here is an innovative method allowing the detection and quantification of CNTs in cells using a multispectral imaging flow cytometer (ImageStream, Amnis). This newly developed device integrates both a high-throughput of cells and high resolution imaging, providing thus images for each cell directly in flow and therefore statistically relevant image analysis. Each cell image is acquired on bright-field (BF), dark-field (DF), and fluorescent channels, giving access respectively to the level and the distribution of light absorption, light scattered and fluorescence for each cell. The analysis consists then in a pixel-by-pixel comparison of each image, of the 7,000-10,000 cells acquired for each condition of the experiment. Localization and quantification of CNTs is made possible thanks to some particular intrinsic properties of CNTs: strong light absorbance and scattering; indeed CNTs appear as strongly absorbed dark spots on BF and bright spots on DF with a precise colocalization.
This methodology could have a considerable impact on studies about interactions between nanomaterials and cells given that this protocol is applicable for a large range of nanomaterials, insofar as they are capable of absorbing (and/or scattering) strongly enough the light.
Bioengineering; Issue 82; bioengineering; imaging flow cytometry; Carbon Nanotubes; bio-nano-interactions; cellular uptake; cell trafficking
Analysis of cellular processes with microscopic bright field defocused imaging has the advantage of low phototoxicity and minimal sample preparation. However bright field images lack the contrast and nuclei reporting available with florescent approaches and therefore present a challenge to methods that segment and track the live cells. Moreover, such methods must be robust to systemic and random noise, variability in experimental configuration, and the multiple unknowns in the biological system under study.
A new method called maximal-information is introduced that applies a non-parametric information theoretic approach to segment bright field defocused images. The method utilizes a combinatorial optimization strategy to select specific defocused images from each image stack such that set complexity, a Kolmogorov complexity measure, is maximized. Differences among these selected images are then applied to initialize and guide a level set based segmentation algorithm. The performance of the method is compared with a recent approach that uses a fixed defocused image selection strategy over an image data set of embryonic kidney cells (HEK 293T) from multiple experiments. Results demonstrate that the adaptive maximal-information approach significantly improves precision and recall of segmentation over the diversity of data sets.
Integrating combinatorial optimization with non-parametric Kolmogorov complexity has been shown to be effective in extracting information from microscopic bright field defocused images. The approach is application independent and has the potential to be effective in processing a diversity of noisy and redundant high throughput biological data.
Nosema locustae, a protozoan parasite of grasshoppers, is used as a bioinsecticide. In the present study, the persistence of N. locustae spores in soil and the interaction of these spores with the indigenous soil microflora were examined with various forms of microscopy and staining. Fluorescence microscopy was found to be better than phase-contrast or bright-field microscopy for detecting and viewing spores in soil. Fluorescein isothiocyanate was a better fluorescent stain than acridine orange or fluorescein diacetate; water-soluble aniline blue did not stain spores. The eight bright-field microscopy stains tested (phenolic erythrosin, phenolic rose bengal, malachite green, crystal violet, safranin, Congo red, methyl red, and eosin B) were not satisfactory, as spore staining characteristics were either poor or masked by overstained soil debris. A procedure was developed which allowed spores to be extracted from soil with a peptone-phosphate buffer, recovered on a membrane filter, and stained with fluorescein isothiocyanate for microscopic counting. This procedure was used to assess the persistence of N. locustae spores in field and laboratory soils. The number of N. locustae spores in a laboratory model soil system persisted at a high level for over 8 weeks when the soil was incubated at 5°C but exhibited a 1,000-fold decrease after 1 week of incubation at 27°C. Persistence was related to the temperature-dependent activity of the indigenous soil microflora, which, on the basis of microscopic observations, appeared to prey on N. locustae spores. N. locustae spores were detected in an N. locustae-treated field soil at a low level consistent with the level for laboratory soil incubated at 27°C, and they persisted at this level for over 2 months. No spores were detected on vegetation from this field or in the soil from an adjacent, nontreated control field. N. locustae-like spores were also detected in soil from nontreated fields supporting large grasshopper populations.
We describe a technique based on moment-analysis for the measurement of the average number of molecules and brightness in each pixel in fluorescence microscopy images. The average brightness of the particle is obtained from the ratio of the variance to the average intensity at each pixel. To obtain the average number of fluctuating particles, we divide the average intensity at one pixel by the brightness. This analysis can be used in a wide range of concentrations. In cells, the intensity at any given pixel may be due to bright immobile structures, dim fast diffusing particles, and to autofluorescence or scattering. The total variance is given by the variance of each of the above components in addition to the variance due to detector noise. Assuming that all sources of variance are independent, the total variance is the sum of the variances of the individual components. The variance due to the particles fluctuating in the observation volume is proportional to the square of the particle brightness while the variance of the immobile fraction, the autofluorescence, scattering, and that of the detector is proportional to the intensity of these components. Only the fluctuations that depend on the square of the brightness (the mobile particles) will have a ratio of the variance to the intensity >1. Furthermore, changing the fluorescence intensity by increasing the illumination power, distinguishes between these possible contributions. We show maps of molecular brightness and number of cell migration proteins obtained using a two-photon scanning microscope operating with a photon-counting detector. These brightness maps reveal binding dynamics at the focal adhesions with pixel resolution and provide a picture of the binding and unbinding process in which dim molecules attach to the adhesions or large molecular aggregates dissociate from adhesion.
Study objectives: To detect invisible lung cancer and to determine field of laser radiation
during PDT we developed a full-color fluorescence fiberscopic system. We tested the efficacy
of this system in patients with various bronchial malignancies.
System design: A fiber-optic endoscope was attached to a camera box containing a color
ICCD camera which can detect from 400 to 700nm fluorescence in full-color. Light of
average wavelength 405 nm was selected and radiated through the light channel of the
fiberscope from a 300W Xenon lamp.
Patients and methods: We examined nine consecutive patients with bronchial malignancy
admitted in our hospital to receive PDT. Sixteen lesions in these nine patients were observed
with white light and excitation light and the results were compared. Histological examinations
were done by taking biopsy specimens and samples for pathological and cytological
examination. After the diagnosis was confirmed, 2.0 mg/kg Photofrin was injected. Forty eight
hours after the administration of Photofrin, observation of the bronchial wall was made using
a full-color endoscopic fluorescence imaging system just before PDT.
Results: Bright red fluorescence from Photofrin was Observed in 14/14 bronchial
malignancies: 3 squamous cell carcinoma, 9 squamous cell carcinoma in situ, 1 metastatic
breast cancer and 1 metastatic islet cell tumor. Bright red fluorescence was also detected in 2/2
squamous dysplasia. Green autofluorescence was observed in the normal part of the bronchus.
Conclusions: Results of the present study suggest that the full-color endoscopic
fluorescence imaging system can be used to detect malignant and premalignant lesions as red
fluorescence against green autofluorescence with Photofrin administration, and this system has the potential to detect absence of autofluorescence in cancerous lesions.
Microscopy imaging of mouse growth plates is extensively used in biology to understand the effect of specific molecules on various stages of normal bone development and on bone disease. Until now, such image analysis has been conducted by manual detection. In fact, when existing automated detection techniques were applied, morphological variations across the growth plate and heterogeneity of image background color, including the faint presence of cells (chondrocytes) located deeper in tissue away from the image’s plane of focus, and lack of cell-specific features, interfered with identification of cell. We propose the first method of automated detection and morphometry applicable to images of cells in the growth plate of long bone. Through ad hoc sequential application of the Retinex method, anisotropic diffusion and thresholding, our new cell detection algorithm (CDA) addresses these challenges on bright-field microscopy images of mouse growth plates. Five parameters, chosen by the user in respect of image characteristics, regulate our CDA. Our results demonstrate effectiveness of the proposed numerical method relative to manual methods. Our CDA confirms previously established results regarding chondrocytes’ number, area, orientation, height and shape of normal growth plates. Our CDA also confirms differences previously found between the genetic mutated mouse Smad1/5CKO and its control mouse on fluorescence images. The CDA aims to aid biomedical research by increasing efficiency and consistency of data collection regarding arrangement and characteristics of chondrocytes. Our results suggest that automated extraction of data from microscopy imaging of growth plates can assist in unlocking information on normal and pathological development, key to the underlying biological mechanisms of bone growth.
Anisotropic diffusion; cell detection; growth plate; mouse; Retinex
Our goal was to optimize procedures for assessing shapes, sizes, and other quantitative metrics of retinal pigment epithelium (RPE) cells and contact- and noncontact-mediated cell-to-cell interactions across a large series of flatmount RPE images.
The two principal methodological advances of this study were optimization of a mouse RPE flatmount preparation and refinement of open-access software to rapidly analyze large numbers of flatmount images. Mouse eyes were harvested, and extra-orbital fat and muscles were removed. Eyes were fixed for 10 min, and dissected by puncturing the cornea with a sharp needle or a stab knife. Four radial cuts were made with iridectomy scissors from the puncture to near the optic nerve head. The lens, iris, and the neural retina were removed, leaving the RPE sheet exposed. The dissection and outcomes were monitored and evaluated by video recording. The RPE sheet was imaged under fluorescence confocal microscopy after staining for ZO-1 to identify RPE cell boundaries. Photoshop, Java, Perl, and Matlab scripts, as well as CellProfiler, were used to quantify selected parameters. Data were exported into Excel spreadsheets for further analysis.
A simplified dissection procedure afforded a consistent source of images that could be processed by computer. The dissection and flatmounting techniques were illustrated in a video recording. Almost all of the sheet could be routinely imaged, and substantial fractions of the RPE sheet (usually 20–50% of the sheet) could be analyzed. Several common technical problems were noted and workarounds developed. The software-based analysis merged 25 to 36 images into one and adjusted settings to record an image suitable for large-scale identification of cell-to-cell boundaries, and then obtained quantitative descriptors of the shape of each cell, its neighbors, and interactions beyond direct cell–cell contact in the sheet. To validate the software, human- and computer-analyzed results were compared. Whether tallied manually or automatically with software, the resulting cell measurements were in close agreement. We compared normal with diseased RPE cells during aging with quantitative cell size and shape metrics. Subtle differences between the RPE sheet characteristics of young and old mice were identified. The IRBP−/− mouse RPE sheet did not differ from C57BL/6J (wild type, WT), suggesting that IRBP does not play a direct role in maintaining the health of the RPE cell, while the slow loss of photoreceptor (PhR) cells previously established in this knockout does support a role in the maintenance of PhR cells. Rd8 mice exhibited several measurable changes in patterns of RPE cells compared to WT, suggesting a slow degeneration of the RPE sheet that had not been previously noticed in rd8.
An optimized dissection method and a series of programs were used to establish a rapid and hands-off analysis. The software-aided, high-sampling-size approach performed as well as trained human scorers, but was considerably faster and easier. This method allows tens to hundreds of thousands of cells to be analyzed, each with 23 metrics. With this combination of dissection and image analysis of the RPE sheet, we can now analyze cell-to-cell interactions of immediate neighbors. In the future, we may be able to observe interactions of second, third, or higher ring neighbors and analyze tension in sheets, which might be expected to deviate from normal near large bumps in the RPE sheet caused by druse or when large frank holes in the RPE sheet are observed in geographic atrophy. This method and software can be readily applied to other aspects of vision science, neuroscience, and epithelial biology where patterns may exist in a sheet or surface of cells.
We introduce the first open resource for mouse olfactory connectivity data produced as part of the Mouse Connectome Project (MCP) at UCLA. The MCP aims to assemble a whole-brain connectivity atlas for the C57Bl/6J mouse using a double coinjection tracing method. Each coinjection consists of one anterograde and one retrograde tracer, which affords the advantage of simultaneously identifying efferent and afferent pathways and directly identifying reciprocal connectivity of injection sites. The systematic application of double coinjections potentially reveals interaction stations between injections and allows for the study of connectivity at the network level. To facilitate use of the data, raw images are made publicly accessible through our online interactive visualization tool, the iConnectome, where users can view and annotate the high-resolution, multi-fluorescent connectivity data (www.MouseConnectome.org). Systematic double coinjections were made into different regions of the main olfactory bulb (MOB) and data from 18 MOB cases (~72 pathways; 36 efferent/36 afferent) currently are available to view in iConnectome within their corresponding atlas level and their own bright-field cytoarchitectural background. Additional MOB injections and injections of the accessory olfactory bulb (AOB), anterior olfactory nucleus (AON), and other olfactory cortical areas gradually will be made available. Analysis of connections from different regions of the MOB revealed a novel, topographically arranged MOB projection roadmap, demonstrated disparate MOB connectivity with anterior versus posterior piriform cortical area (PIR), and exposed some novel aspects of well-established cortical olfactory projections.
main olfactory bulb; piriform cortical area; lateral olfactory tract; online digital atlas; connectome; neural tract tracing
Inertial microfluidics has demonstrated the potential to provide a rich range of capabilities to manipulate biological fluids and particles to address various challenges in biomedical science and clinical medicine. Various microchannel geometries have been used to study the inertial focusing behavior of particles suspended in simple buffer solutions or in highly diluted blood. One aspect of inertial focusing that has not been studied is how particles suspended in whole or minimally diluted blood respond to inertial forces in microchannels. The utility of imaging techniques (i.e., high-speed bright-field imaging and long exposure fluorescence (streak) imaging) primarily used to observe particle focusing in microchannels is limited in complex fluids such as whole blood due to interference from the large numbers of red blood cells (RBCs). In this study, we used particle trajectory analysis (PTA) to observe the inertial focusing behavior of polystyrene beads, white blood cells, and PC-3 prostate cancer cells in physiological saline and blood. Identification of in-focus (fluorescently labeled) particles was achieved at mean particle velocities of up to 1.85 m s−1. Quantitative measurements of in-focus particles were used to construct intensity maps of particle frequency in the channel cross-section and scatter plots of particle centroid coordinates vs. particle diameter. PC-3 cells spiked into whole blood (HCT = 45%) demonstrated a novel focusing mode not observed in physiological saline or diluted blood. PTA can be used as an experimental frame of reference for understanding the physical basis of inertial lift forces in whole blood and discover inertial focusing modes that can be used to enable particle separation in whole blood.
Visualisation of neurons labeled with fluorescent proteins or compounds generally require exposure to intense light for a relatively long period of time, often leading to bleaching of the fluorescent probe and photodamage of the tissue. Here we created a technique to drastically shorten light exposure and improve the targeting of fluorescent labeled cells that is specially useful for patch-clamp recordings. We applied image tracking and mask overlay to reduce the time of fluorescence exposure and minimise mistakes when identifying neurons.
Neurons are first identified according to visual criteria (e.g. fluorescence protein expression, shape, viability etc.) and a transmission microscopy image Differential Interference Contrast (DIC) or Dodt contrast containing the cell used as a reference for the tracking algorithm. A fluorescence image can also be acquired later to be used as a mask (that can be overlaid on the target during live transmission video). As patch-clamp experiments require translating the microscope stage, we used pattern matching to track reference neurons in order to move the fluorescence mask to match the new position of the objective in relation to the sample. For the image processing we used the Open Source Computer Vision (OpenCV) library, including the Speeded-Up Robust Features (SURF) for tracking cells. The dataset of images (n = 720) was analyzed under normal conditions of acquisition and with influence of noise (defocusing and brightness).
We validated the method in dissociated neuronal cultures and fresh brain slices expressing Enhanced Yellow Fluorescent Protein (eYFP) or Tandem Dimer Tomato (tdTomato) proteins, which considerably decreased the exposure to fluorescence excitation, thereby minimising photodamage. We also show that the neuron tracking can be used in differential interference contrast or Dodt contrast microscopy.
The techniques of digital image processing used in this work are an important addition to the set of microscopy tools used in modern electrophysiology, specially in experiments with neuron cultures and brain slices.
Neurons; Fluorescent proteins; Photodamage; Patch-clamp; Image tracking; Mask overlay
Fluorescent in situ hybridization (FISH) allows the quantification of single mRNAs in budding yeast using fluorescently labeled single-stranded DNA probes, a wide-field epifluorescence microscope and a spot-detection algorithm. Fixed yeast cells are attached to coverslips and hybridized with a mixture of FISH probes, each conjugated to several fluorescent dyes. Images of cells are acquired in 3D and maximally projected for single-molecule analysis. Diffraction-limited labeled mRNAs are observed as bright fluorescent spots and can be quantified using a spot-detection algorithm. FISH preserves the spatial distribution of cellular RNA distribution within the cell and the stochastic fluctuations in individual cells that can lead to phenotypic differences within a clonal population. This information, however, is lost if the RNA content is measured on a population of cells by using reverse transcriptase PCR, microarrays or high-throughput sequencing. The FISH procedure and image acquisition described here can be completed in 3 d.
Light emitting diodes (LED), which are available as small monochromatic light sources with characteristic features such as maximum illumination power combined with minimum energy consumption and extremely long lifespan have already proved as a highly potential low-cost alternative for specific diagnostic applications in clinical medicine such as tuberculosis fluorescence microscopy. Likewise, the most reliable evaluation of Her-2/neu (c-erbB2) gene amplification, which has been established in the last few years for routine diagnosis in clinical pathology as determinant towards Herceptin-based treatment of patients with breast cancer, is based on fluorescence in situ hybridization (FISH) and corresponding high priced fluorescence equipment. In order to test the possibility to utilize the advantages of low-cost LED technology on FISH analysis of c-erbB2 gene expression for routine diagnostic purposes, the applicability of a standard bright field Carl Zeiss Axiostar Plus microscope equipped with a Fraen AFTER* LED Fluorescence Microscope Kit for the detection of Her-2/neu gene signals was compared to an advanced Nikon Eclipse 80i fluorescence microscope in combination with a conventional 100W mercury vapor lamp. Both microscopes were fitted with the same Quicam FAST CCD digital camera to unequivocally compare the quality of the captured images. C-erbB2 gene expression was analyzed in 30 different human tissue samples of primary invasive breast cancer, following formalin fixation and subsequent paraffin-embedding. The Her2/neu gene signals (green) were identifiable in the tumor cells in all cases and images of equal quality were captured under almost identical conditions by 480 nm (blue) LED module equipped standard Axiostar microscope as compared to conventional fluorescence microscopy. In this first attempt, these monochromatic LED elements proved in principle to be suitable for the detection of Her-2/neu gene expression by FISH. Thus, our own experiences emphasize the high potential of this technology to provide a serious alternative to conventional fluorescence microscopy in routine pathology; representing a sustainable technological progress, this low-cost technology will clearly give direction also to the growing field of molecular pathology.
* AFTER = Amplified Fluorescence by transmitted Excitation of Radiation
In recent years, new microscopic imaging techniques have evolved to allow us to visualize several different proteins (or other biomolecules) in a visual field. Analysis of protein co-localization becomes viable because molecules can interact only when they are located close to each other. We present a novel approach to align images in a multi-tag fluorescence image stack. The proposed approach is applicable to multi-tag bioimaging systems which (a) acquire fluorescence images by sequential staining and (b) simultaneously capture a phase contrast image corresponding to each of the fluorescence images. To the best of our knowledge, there is no existing method in the literature, which addresses simultaneous registration of multi-tag bioimages and selection of the reference image in order to maximize the overall overlap between the images.
We employ a block-based method for registration, which yields a confidence measure to indicate the accuracy of our registration results. We derive a shift metric in order to select the Reference Image with Maximal Overlap (RIMO), in turn minimizing the total amount of non-overlapping signal for a given number of tags. Experimental results show that the Robust Alignment of Multi-Tag Bioimages (RAMTaB) framework is robust to variations in contrast and illumination, yields sub-pixel accuracy, and successfully selects the reference image resulting in maximum overlap. The registration results are also shown to significantly improve any follow-up protein co-localization studies.
For the discovery of protein complexes and of functional protein networks within a cell, alignment of the tag images in a multi-tag fluorescence image stack is a key pre-processing step. The proposed framework is shown to produce accurate alignment results on both real and synthetic data. Our future work will use the aligned multi-channel fluorescence image data for normal and diseased tissue specimens to analyze molecular co-expression patterns and functional protein networks.
The use of genetically-encoded fluorescent proteins has revolutionized the fields of cell and developmental biology and in doing so redefined our understanding of the dynamic morphogenetic processes that shape the embryo. With the advent of more accessible and sophisticated imaging technologies as well as an abundance of fluorescent proteins with different spectral characteristics, the dynamic processes taking place in situ in living cells and tissues can now be probed. Photomodulatable fluorescent proteins are one of the emerging classes of genetically-encoded fluorescent proteins.
We have compared PA-GFP, PS-CFP2, Kaede and KikGR four readily available and commonly used photomodulatable fluorescent proteins for use in ES cells and mice. Our results suggest that the green-to-red photoconvertible fluorescent protein, Kikume Green-Red (KikGR), is most suitable for cell labeling and lineage studies in ES cells and mice because it is developmentally neutral, bright and undergoes rapid and complete photoconversion. We have generated transgenic ES cell lines and strains of mice exhibiting robust widespread expression of KikGR. By efficient photoconversion of KikGR we labeled subpopulations of ES cells in culture, and groups of cells within ex utero cultured mouse embryos. Red fluorescent photoconverted cells and their progeny could be followed for extended periods of time.
Transgenic ES cells and mice exhibiting widespread readily detectable expression of KikGR are indistinguishable from their wild type counterparts and are amenable to efficient photoconversion. They represent novel tools for non-invasive selective labeling specific cell populations and live imaging cell dynamics and cell fate. Genetically-encoded photomodulatable proteins such as KikGR represent emergent attractive alternatives to commonly used vital dyes, tissue grafts and genetic methods for investigating dynamic behaviors of individual cells, collective cell dynamics and fate mapping applications.
An on-chip multi-imaging flow cytometry system has been developed to obtain morphometric parameters of cell clusters such as cell number, perimeter, total cross-sectional area, number of nuclei and size of clusters as “imaging biomarkers”, with simultaneous acquisition and analysis of both bright-field (BF) and fluorescent (FL) images at 200 frames per second (fps); by using this system, we examined the effectiveness of using imaging biomarkers for the identification of clustered circulating tumor cells (CTCs). Sample blood of rats in which a prostate cancer cell line (MAT-LyLu) had been pre-implanted was applied to a microchannel on a disposable microchip after staining the nuclei using fluorescent dye for their visualization, and the acquired images were measured and compared with those of healthy rats. In terms of the results, clustered cells having (1) cell area larger than 200 µm2 and (2) nucleus area larger than 90 µm2 were specifically observed in cancer cell-implanted blood, but were not observed in healthy rats. In addition, (3) clusters having more than 3 nuclei were specific for cancer-implanted blood and (4) a ratio between the actual perimeter and the perimeter calculated from the obtained area, which reflects a shape distorted from ideal roundness, of less than 0.90 was specific for all clusters having more than 3 nuclei and was also specific for cancer-implanted blood. The collected clusters larger than 300 µm2 were examined by quantitative gene copy number assay, and were identified as being CTCs. These results indicate the usefulness of the imaging biomarkers for characterizing clusters, and all of the four examined imaging biomarkers—cluster area, nuclei area, nuclei number, and ratio of perimeter—can identify clustered CTCs in blood with the same level of preciseness using multi-imaging cytometry.