Steffen Prohaska

A Novel Three-Dimensional Computer-Assisted Method for a Quantitative Study of Microvascular Networks of the Human Cerebral Cortex

Objective: Detailed information on microvascular network anatomy is a requirement for understanding several aspects of microcirculation, including oxygen transport, distributions of pressure, and wall shear stress in microvessels, regulation of blood flow, and interpretation of hemodynamically based functional imaging methods, but very few quantitative data on the human brain microcirculation are available. The main objective of this study is to propose a new method to analyze this microcirculation.

Stereological measures of trabecular bone structure: comparison of 3D micro computed tomography with 2D histological sections in human proximal tibial bone biopsies

Stereology applied on histological sections is the ‘gold standard’ for obtaining quantitative information on cancellous bone structure. Recent advances in micro computed tomography (µCT) have made it possible to acquire three‐dimensional (3D) data non‐destructively. However, before the 3D methods can be used as a substitute for the current ‘gold standard’ they have to be verified against the existing standard. The aim of this study was to compare bone structural measures obtained from 3D µCT data sets with those obtained by stereology performed on conventional histological sections using human tibial bone biopsies. Furthermore, this study forms the first step in introducing the proximal tibia as a potential bone examination location by peripheral quantitative CT and CT. Twenty‐nine trabecular bone biopsies were obtained from autopsy material at the medial side of the proximal tibial metaphysis. The biopsies were embedded in methylmetacrylate before µCT scanning in a Scanco µCT 40 scanner at a resolution of 20 × 20 × 20 µm3, and the 3D data sets were analysed with a computer program. After µCT scanning, 16 sections were cut from the central 2 mm of each biopsy and analysed with a computerized method. Trabecular bone volume (BV/TV) and connectivity density (CD) were estimated in both modalities, whereas trabecular bone pattern factor (TBPf) was estimated on the histological sections only. Trabecular thickness (Tb.Th), number (Tb.N) and separation (Tb.Sp), and structure model index (SMI) were estimated with the µCT method only. Excellent correlations were found between the two techniques for BV/TV (r = 0.95) and CD (r = 0.95). Additionally, an excellent relationship (r = 0.95) was ascertained between TBPf and SMI. The study revealed high correlations between measures of bone structure obtained from conventional 2D sections and 3D µCT data. This indicates that 3D µCT data sets can be used as a substitute for conventional histological sections for bone structural evaluations.

Large-Scale Automated Histology in the Pursuit of Connectomes

How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brains computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivity.

Automated Segmentation of Electron Tomograms for a Quantitative Description of Actin Filament Networks

Cryo-electron tomography allows to visualize individual actin filaments and to describe the three-dimensional organization of actin networks in the context of unperturbed cellular environments. For a quantitative characterization of actin filament networks, the tomograms must be segmented in a reproducible manner. Here, we describe an automated procedure for the segmentation of actin filaments, which combines template matching with a new tracing algorithm. The result is a set of lines, each one representing the central line of a filament. As demonstrated with cryo-tomograms of cellular actin networks, these line sets can be used to characterize filament networks in terms of filament length, orientation, density, stiffness (persistence length), or the occurrence of branching points.

Accelerated visualization of dynamic molecular surfaces

Molecular surfaces play an important role in studying the interactions between molecules. Visualizing the dynamic behavior of molecules is particularly interesting to gain insights into a molecular system. Only recently it has become possible to interactively visualize dynamic molecular surfaces using ray casting techniques.

Opportunities and challenges for digital morphology.

Advances in digital data acquisition, analysis, and storage have revolutionized the work in many biological disciplines such as genomics, molecular phylogenetics, and structural biology, but have not yet found satisfactory acceptance in morphology. Improvements in non-invasive imaging and three-dimensional visualization techniques, however, permit high-throughput analyses also of whole biological specimens, including museum material. These developments pave the way towards a digital era in morphology. Using sea urchins (Echinodermata: Echinoidea), we provide examples illustrating the power of these techniques. However, remote visualization, the creation of a specialized database, and the implementation of standardized, world-wide accepted data deposition practices prior to publication are essential to cope with the foreseeable exponential increase in digital morphological data.ReviewersThis article was reviewed by Marc D. Sutton (nominated by Stephan Beck), Gonzalo Giribet (nominated by Lutz Walter), and Lennart Olsson (nominated by Purificación López-García).

Automated tracing of microtubules in electron tomograms of plastic embedded samples of Caenorhabditis elegans embryos.

The ability to rapidly assess microtubule number in 3D image stacks from electron tomograms is essential for collecting statistically meaningful data sets. Here we implement microtubule tracing using 3D template matching. We evaluate our results by comparing the automatically traced centerlines to manual tracings in a large number of electron tomograms of the centrosome of the early Caenorhabditis elegans embryo. Furthermore, we give a qualitative description of the tracing results for three other types of samples. For dual-axis tomograms, the automatic tracing yields 4% false negatives and 8% false positives on average. For single-axis tomograms, the accuracy of tracing is lower (16% false negatives and 14% false positives) due to the missing wedge in electron tomography. We also implemented an editor specifically designed for correcting the automatic tracing. Besides, this editor can be used for annotating microtubules. The automatic tracing together with a manual correction significantly reduces the amount of manual labor for tracing microtubule centerlines so that large-scale analysis of microtubule network properties becomes feasible.

Blockwise processing applied to brain microvascular network study

The study of cerebral microvascular networks requires high-resolution images. However, to obtain statistically relevant results, a large area of the brain (several square millimeters) must be analyzed. This leads us to consider huge images, too large to be loaded and processed at once in the memory of a standard computer. To consider a large area, a compact representation of the vessels is required. The medial axis is the preferred tool for this application. To extract it, a dedicated skeletonization algorithm is proposed. Numerous approaches already exist which focus on computational efficiency. However, they all implicitly assume that the image can be completely processed in the computer memory, which is not realistic with the large images considered here. We present in this paper a skeletonization algorithm that processes data locally (in subimages) while preserving global properties (i.e., homotopy). We then show some results obtained on a mosaic of three-dimensional images acquired by confocal microscopy

Fast visualization of plane-like structures in voxel data

We present a robust, noise-resistant criterion characterizing plane-like skeletons in binary voxel objects. It is based on a distance map and the geodesic distance along the objects boundary. A parameter allows us to control the noise sensitivity. If needed, homotopy with the original object might be reconstructed in a second step, using an improved distance ordered thinning algorithm. The skeleton is analyzed to create a geometric representation for rendering. Plane-like parts are transformed into an triangulated surface not enclosing a volume by a suitable triangulation scheme. The resulting surfaces have lower triangle count than those created with standard methods and tend to maintain the original geometry, even after simplification with a high decimation rate. Our algorithm allows us to interactively render expressive images of complex 3D structures, emphasizing independently plane-like and rod-like structures. The methods are applied for visualization of the microstructure of bone biopsies.

Interactive Exploration of Large Remote Micro-CT Scans

Datasets of tens of gigabytes are becoming common in computational and experimental science. This development is driven by advances in imaging technology, producing detectors with growing resolutions, as well as availability of cheap processing power and memory capacity in commodity-based computing clusters. We describe the design of a visualization system that allows scientists to interactively explore large remote data sets in an efficient and flexible way. The system is broadly applicable and currently used by medical scientists conducting an osteoporosis research project. Human vertebral bodies are scanned using a high resolution microCT scanner producing scans of roughly 8 GB size each. All participating research groups require access to the centrally stored data. Due to the rich internal bone structure, scientists need to interactively explore the full dataset at coarse levels, as well as visualize subvolumes of interest at the highest resolution. Our solution is based on HDF5 and GridFTP. When accessing data remotely, the HDF5 data processing pipeline is modified to support efficient retrieval of subvolumes. We reduce the overall latency and optimize throughput by executing high-level operations on the remote side. The GridFTP protocol is used to pass the HDF5 requests to a customized server. The approach takes full advantage of local graphics hardware for rendering. Interactive visualization is accomplished using a background thread to access the datasets stored in a multiresolution format. A hierarchical volume tenderer provides seamless integration of high resolution details with low resolution overviews.