Automated Quantitative Bone Analysis in In Vivo X-ray Micro-Computed Tomography.

Measurement and analysis of bone morphometry in 3D micro-computed tomography volumes using automated image processing and analysis improve the accuracy, consistency, reproducibility, and speed of preclinical osteological research studies. Automating segmentation and separation of individual bones in 3D micro-computed tomography volumes of murine models presents significant challenges considering partial volume effects and joints with thin spacing, i.e., 50 to [Formula: see text]. In this paper, novel hybrid splitting filters are presented to overcome the challenge of automated bone separation. This is achieved by enhancing joint contrast using rotationally invariant second-derivative operators. These filters generate split components that seed marker-controlled watershed segmentation. In addition, these filters can be used to separate metaphysis and epiphysis in long bones, e.g., femur, and remove the metaphyseal growth plate from the detected bone mask in morphometric measurements. Moreover, for slice-by-slice stereological measurements of long bones, particularly curved bones, such as tibia, the accuracy of the analysis can be improved if the planar measurements are guided to follow the longitudinal direction of the bone. In this paper, an approach is presented for characterizing the bone medial axis using morphological thinning and centerline operations. Building upon the medial axis, a novel framework is presented to automatically guide stereological measurements of long bones and enhance measurement accuracy and consistency. These image processing and analysis approaches are combined in an automated streamlined software workflow and applied to a range of in vivo micro-computed tomography studies for validation.

Flat field correction for high-throughput imaging of fluorescent samples.

Vignetting of microscopic images impacts both the visual impression of the images and any image analysis applied to it. Especially in high-throughput screening high demands are made on an automated image analysis. In our work we focused on fluorescent samples and found that two profiles (background and foreground) for each imaging channel need to be estimated to achieve a sufficiently flat image after correction. We have developed a method which runs completely unsupervised on a wide range of assays. By adding a reliable internal quality control we mitigate the risk of introducing artefacts into sample images through correction. The method requires hundreds of images for the foreground profile, thus limiting its application to high-throughput screening where this requirement is fulfilled in routine operation.

Calculation of photon-count number distributions via master equations.

Fitting of photon-count number histograms is a way of analysis of fluorescence intensity fluctuations, a successor to fluorescence correlation spectroscopy. First versions of the theory for calculating photon-count number distributions have assumed constant emission intensity by a molecule during a counting time interval. For a long time a question has remained unanswered: to what extent is this assumption violated in experiments? Here we present a theory of photon-count number distributions that takes account of intensity fluctuations during a counting time interval. Theoretical count-number distributions are calculated via a numerical solution of Master equations (ME), which is a set of differential equations describing diffusion, singlet-triplet transitions, and photon emission. Detector afterpulsing and dead-time corrections are also included. The ME-theory is tested by fitting a series of photon-count number histograms corresponding to different lengths of the counting time interval. Compared to the first version of fluorescence intensity multiple distribution analysis theory introduced in 2000, the fit quality is significantly improved. It is discussed how a theory of photon-count number distributions, which assumes constant emission intensity during a counting time interval, may also yield a good fit quality. We argue that the spatial brightness distribution used in calculations of the fit curve is not the true spatial brightness distribution. Instead, a number of dynamic processes, which cause fluorescence intensity fluctuations, are indirectly taken into account via the profile adjustment parameters.

Comparison of different fluorescence fluctuation methods for their use in FRET assays: monitoring a protease reaction.

We compare the accuracy of a variety of Fluorescence Fluctuation Spectroscopy (FFS) methods for the study of Förster Resonance Energy Transfer (FRET) assays. As an example, the cleavage of a doubly labeled, FRET-active peptide substrate by the protease Trypsin is monitored and analyzed using methods based on fluorescence intensity, Fluorescence Correlation Spectroscopy (FCS) and Fluorescence Intensity Distribution Analysis (FIDA). The presented fluorescence data are compared to High-Pressure Liquid Chromatography (HPLC) data obtained from the same assay. The HPLC analysis discloses general disadvantages of the FRET approach, such as incomplete labeling and the need for aliquots. However, the simultaneous use of two photon detectors monitoring the fluorescence signal of both labels significantly improves the analysis. In particular, the two global analysis tools Two-Dimensional Fluorescence Intensity Distribution Analysis (2D-FIDA) and Two-Color Global Fluorescence Correlation Spectroscopy (2CG-FCS) highlight the potential of a combination of FFS and FRET. While conventional FIDA and FCS auto- or cross-correlation analysis leaves the user with drawbacks inherent in two-color and FRET applications, these effects are overcome by the global analysis on the molecular level. Furthermore, it is advantageous to analyze the unnormalized as opposed to the normalized correlation data when combining any fluorescence correlation method with FRET, since the analysis of the unnormalized data introduces more accuracy and is less sensitive to the experimental drawbacks.

Rapid analysis of Forster resonance energy transfer by two-color global fluorescence correlation spectroscopy: trypsin proteinase reaction.

In this study we introduce the combination of two-color global fluorescence correlation spectroscopy (2CG-FCS) and Förster resonance energy transfer (FRET) as a very powerful combination for monitoring biochemical reactions on the basis of single molecule events. 2CG-FCS, which is a new variation emerging from the family of fluorescence correlation spectroscopy, globally analyzes the simultaneously recorded auto- and cross-correlation data from two photon detectors monitoring the fluorescence emission of different colors. Overcoming the limitations inherent in mere auto- and cross-correlation analysis, 2CG-FCS is sensitive in resolving and quantifying fluorescent species that differ in their diffusion characteristics and/or their molecular brightness either in one or both detection channels. It is able to account for effects that have often been considered as sources of severe artifacts in two-color and FRET measurements, the most prominent artifacts comprising photobleaching, cross talk, or concentration variations in sample preparation. Because of its very high statistical accuracy, the combination of FRET and 2CG-FCS is suited for high-throughput applications such as drug screening. Employing beam scanning during data acquisition even further enhances this capability and allows measurement times of <2 s. The improved performance in monitoring a FRET sample was verified by following the protease cleavage reaction of a FRET-active peptide. The FRET-inactive subpopulation of uncleaved substrate could be correctly assigned, revealing a substantial portion of inactive or missing acceptor label. The results were compared to those obtained by two-dimensional fluorescence intensity distribution analysis.

Fluorescence intensity and lifetime distribution analysis: toward higher accuracy in fluorescence fluctuation spectroscopy.

Fluorescence fluctuation methods such as fluorescence correlation spectroscopy and fluorescence intensity distribution analysis (FIDA) have proven to be versatile tools for studying molecular interactions with single molecule sensitivity. Another well-known fluorescence technique is the measurement of the fluorescence lifetime. Here, we introduce a method that combines the benefits of both FIDA and fluorescence lifetime analysis. It is based on fitting the two-dimensional histogram of the number of photons detected in counting time intervals of given width and the sum of excitation to detection delay times of these photons. Referred to as fluorescence intensity and lifetime distribution analysis (FILDA), the technique distinguishes fluorescence species on the basis of both their specific molecular brightness and the lifetime of the excited state and is also able to determine absolute fluorophore concentrations. The combined information yielded by FILDA results in significantly increased accuracy compared to that of FIDA or fluorescence lifetime analysis alone. In this paper, the theory of FILDA is elaborated and applied to both simulated and experimental data. The outstanding power of this technique in resolving different species is shown by quantifying the binding of calmodulin to a peptide ligand, thus indicating the potential for application of FILDA to similar problems in the life sciences.