3D osteocyte lacunar morphometric properties and distributions in human femoral cortical bone using synchrotron radiation micro-CT images

Osteocytes, the most numerous bone cells, are thought to be actively involved in the bone modeling and remodeling processes. The morphology of osteocyte is hypothesized to adapt according to the physiological mechanical loading. Three-dimensional micro-CT has recently been used to study osteocyte lacunae. In this work, we proposed a computationally efficient and validated automated image analysis method to quantify the 3D shape descriptors of osteocyte lacunae and their distribution in human femurs. Thirteen samples were imaged using Synchrotron Radiation (SR) micro-CT at ID19 of the ESRF with 1.4μm isotropic voxel resolution. With a field of view of about 2.9×2.9×1.4mm(3), the 3D images include several tens of thousands of osteocyte lacunae. We designed an automated quantification method to segment and extract 3D cell descriptors from osteocyte lacunae. An image moment-based approach was used to calculate the volume, length, width, height and anisotropy of each osteocyte lacuna. We employed a fast algorithm to further efficiently calculate the surface area, the Euler number and the structure model index (SMI) of each lacuna. We also introduced the 3D lacunar density map to directly visualize the lacunar density variation over a large field of view. We reported the lacunar morphometric properties and distributions as well as cortical bone histomorphometric indices on the 13 bone samples. The mean volume and surface were found to be 409.5±149.7μm(3) and 336.2±94.5μm(2). The average dimensions were of 18.9±4.9μm in length, 9.2±2.1μm in width and 4.8±1.1μm in depth. We found lacunar number density and six osteocyte lacunar descriptors, three axis lengths, two anisotropy ratios and SMI, that are significantly correlated to bone porosity at a same local region. The proposed method allowed an automatic and efficient direct 3D analysis of a large population of bone cells and is expected to provide reliable biological information for better understanding the bone quality and diseases at cellular level.

Topologically associated domains enriched for lineage-specific genes reveal expression-dependent nuclear topologies during myogenesis

The linear distribution of genes across chromosomes and the spatial localization of genes within the nucleus are related to their transcriptional regulation. The mechanistic consequences of linear gene order, and how it may relate to the functional output of genome organization, remain to be fully resolved, however. Here we tested the relationship between linear and 3D organization of gene regulation during myogenesis. Our analysis has identified a subset of topologically associated domains (TADs) that are significantly enriched for muscle-specific genes. These lineage-enriched TADs demonstrate an expression-dependent pattern of nuclear organization that influences the positioning of adjacent nonenriched TADs. Therefore, lineage-enriched TADs inform cell-specific genome organization during myogenesis. The reduction of allelic spatial distance of one of these domains, which contains Myogenin, correlates with reduced transcriptional variability, identifying a potential role for lineage-specific nuclear topology. Using a fusion-based strategy to decouple mitosis and myotube formation, we demonstrate that the cell-specific topology of syncytial nuclei is dependent on cell division. We propose that the effects of linear and spatial organization of gene loci on gene regulation are linked through TAD architecture, and that mitosis is critical for establishing nuclear topologies during cellular differentiation.

Evaluation of Microstructure and Transport Properties of Deteriorated Cementitious Materials from Their X-ray Computed Tomography (CT) Images

Pore structure, tortuosity and permeability are considered key properties of porous materials such as cement pastes to understand their long-term durability performance. Three-dimensional image analysis techniques were used in this study to quantify pore size, effective porosity, tortuosity, and permeability from the X-ray computed tomography (CT) images of deteriorated pastes that were subjected to accelerated leaching test. X-ray microtomography is a noninvasive three-dimensional (3D) imaging technique which has been recently gaining attention for material characterization. Coupled with 3D image analysis, the digitized pore can be extracted and computational simulation can be applied to the pore network to measure relevant microstructure and transport properties. At a spatial resolution of 0.50 μm, the effective porosity (φ_e) was found to be in the range of 0.04 to 0.33. The characteristic pore size (d) using a local thickness algorithm was found to be in the range of 3 to 7 μm. The geometric tortuosity (τ_g) based on a 3D random walk simulation in the percolating pore space was found to be in the range of 2.00 to 7.45. The water permeability values (K) using US NIST Permeability Stokes Solver range from an order of magnitudes of 10⁻¹⁴ to 10⁻¹⁷ m². Indications suggest that as effective porosity increases, the geometric tortuosity increases and the permeability decreases. Correlation among these microstructure and transport parameters is also presented in this study.

Automated Control of Surface Defects on Ceramic Tiles Using 3D Image Analysis

This paper presents a method of acquisition and analysis of three-dimensional images in the task of automatic location and evaluation of defects on the surface of ceramic tiles. It presents a brief description of selected defects appearing on the surface of tiles, along with the analysis of their formation. The paper includes the presentation of the method of constructing a 3D image of the tile surface using the Laser Triangulation Method (LTM), along with the surface imaging parameters employed in the research. The algorithms of three-dimensional surface image analysis of ceramic tiles used in the process of image filtering and defect identification are presented. For selected defects, the method of measuring defect parameters and the method of visualization of defects on the surface are also presented. The developed method was tested on defective products to confirm its effectiveness in the field of quick defect detection in automated control systems installed on production lines.

Retrospective Evaluation of a Technique for Patient-Customized Placement of Precurved Cochlear Implant Electrode Arrays

Objective Precurved electrode arrays (EAs) are commonly used in cochlear implants (CIs). Modiolar placement of such arrays has been shown to lead to better hearing outcomes. In this project, we retrospectively evaluated the modiolar positioning of EAs within a large CI imaging database. We aimed to discover the rate at which perimodiolar placement is successfully achieved and to evaluate a new technique we propose to preoperatively plan patient-customized EA insertion depths to improve perimodiolar placement at the time of surgery. Study Design Retrospective chart review and radiographic analysis. Setting Single tertiary academic referral center. Subjects and Methods Ninety-seven CI ears were evaluated. Perimodiolar positioning of electrodes was quantified using pre- and postimplantation computed tomography scans and automated image analysis techniques. Results Average perimodiolar distance was 0.59 ± 0.18 mm. Disagreement between the actual and our recommended insertion depth was found to be positively correlated with perimodiolar distance ( r = 0.49, P < .0001). Conclusions These results show that the average CI recipient with a precurved EA has a number of electrodes distant to the modiolus where they are not most effective. Our results also indicate the approach we propose for selecting patient-customized EA insertion depth would lead to better perimodiolar placement of precurved EAs.

Enhanced quantification for 3D SEM-EDS: using the full set of available X-ray lines

An enhanced method to quantify energy dispersive spectra recorded in 3D with a scanning electron microscope (3D SEM–EDS) has been previously demonstrated. This paper presents an extension of this method using all the available X-ray lines generated by the beam. The extended method benefits from using high energy lines, that are more accurately quantified, and from using soft X-rays that are highly absorbed and thus more surface sensitive. The data used to assess the method are acquired with a dual beam FIB/SEM investigating a multi-element Ni-based superalloy. A high accelerating voltage, needed to excite the highest energy X-ray line, results in two available X-ray lines for several elements. The method shows an improved compositional quantification as well as an improved spatial resolution.

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3D SEM–EDS mapping of structures smaller than the X-ray generation volume is considered.

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The influence of neighbouring voxels is corrected by a recursive quantification method.

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The method is improved using all available X-ray lines.

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The method is applied to simulated spectra and experimental dual beam FIB/SEM data.

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The method is shown to improve both compositional accuracy and spatial resolution.

CEREBRUM-7T: Fast and Fully Volumetric Brain Segmentation of 7 Tesla MR Volumes

Ultra-high-field magnetic resonance imaging (MRI) enables sub-millimetre resolution imaging of the human brain, allowing the study of functional circuits of cortical layers at the meso-scale. An essential step in many functional and structural neuroimaging studies is segmentation, the operation of partitioning the MR images in anatomical structures. Despite recent efforts in brain imaging analysis, the literature lacks in accurate and fast methods for segmenting 7-tesla (7T) brain MRI. We here present CEREBRUM-7T, an optimised end-to-end convolutional neural network, which allows fully automatic segmentation of a whole 7T T1_w MRI brain volume at once, without partitioning the volume, pre-processing, nor aligning it to an atlas. The trained model is able to produce accurate multi-structure segmentation masks on six different classes plus background in only a few seconds. The experimental part, a combination of objective numerical evaluations and subjective analysis, confirms that the proposed solution outperforms the training labels it was trained on and is suitable for neuroimaging studies, such as layer functional MRI studies. Taking advantage of a fine-tuning operation on a reduced set of volumes, we also show how it is possible to effectively apply CEREBRUM-7T to different sites data. Furthermore, we release the code, 7T data, and other materials, including the training labels and the Turing test.

Effects of cropping systems upon the three-dimensional architecture of soil systems are modulated by texture

Soil delivers fundamental ecosystem functions via interactions between physical and biological processes mediated by soil structure. The structure of soil is also dynamic and modified by natural factors and management intervention. The aim of this study was to investigate the effects of different cropping systems on soil structure at contrasting spatial scales. Three systems were studied in replicated plot field experiments involving varying degrees of plant-derived inputs to the soil, viz. perennial (grassland), annual (arable), and no-plant control (bare fallow), associated with two contrasting soil textures (clayey and sandy). We hypothesized the presence of plants results in a greater range (diversity) of pore sizes and that perennial cropping systems invoke greater structural heterogeneity. Accordingly, the nature of the pore systems was visualised and quantified in 3D by X-ray Computed Tomography at the mm and μm scale. Plants did not affect the porosity of clay soil at the mm scale, but at the μm scale, annual and perennial plant cover resulted in significantly increased porosity, a wider range of pore sizes and greater connectivity compared to bare fallow soil. However, the opposite occurred in the sandy soil, where plants decreased the porosity and pore connectivity at the mm scale but had no significant structural effect at the μm scale. These data reveal profound effects of different agricultural management systems upon soil structural modification, which are strongly modulated by the extent of plant presence and also contingent on the inherent texture of the soil.

Three-dimensional morphological changes of the temporomandibular joint and functional effects after mandibulotomy

BACKGROUND

The midline and paramedian mandibulotomy are surgical procedures that divide the mandibular bone into two halves and disconnects the condylar heads of the TMJ from each other. This study aimed to prospectively evaluate the temporomandibular joint (TMJ) functional and morphological changes after mandibulotomy using a reconstructed 3D models of the TMJ.

METHODS

Sixteen adult patients diagnosed with oral and oropharyngeal tumors with planned surgical mandibulotomy (test group, 9 patients) or transoral (control group, seven patients) treatments were included in the study. MRI and CBCT images were obtained immediately preceeding surgery and 6-8 weeks after surgery. Using the MRI-CBCT registered images, TMJ tissues were segmented at the two occasions by the same operator and 3D models were reconstructed for morphological assessment. Changes across time were measured using the volume overlap and Hausdorff distance of the disc and condyle 3D models. Disc-condyle relationship was measured using point-based and color map analysis. To assess the early functional changes, the Jaw function limitation scale (JFLS) and the maximum mouth opening were measured. Two-sample Hotelling T² t-test was performed to determine the significance of the morphological and clinical outcomes' differences between the two groups.

RESULTS

The two-sample Hotelling T² t-test showed significant differences (T² (df1,df2) = 0.97 (5,26), p <0.01) between the mean values of all outcomes among the 2 groups. The change in disc displacement was significantly different between the two groups (p <0.05). However, the condylar displacement was not significantly different between the two groups (p =0.3). The average of the JFLS score was five times larger after mandibulotomy, and was 2 times larger after transoral surgery (p < 0.01). Patients showed decrease in the average of the maximum interincisal mouth opening by 11 mm after mandibulotomy, and by 5.4 mm after transoral surgery.

CONCLUSION

The quantitative assessment of the TMJ showed minimal changes of the condylar position and variable degrees of articular disc displacement associated with the paramedian split mandibulotomy. As well, limited jaw functions and vertical mouth opening were noticed more in the mandibultomy group compared to the transoral group in 6- weeks after surgery.

Ultrasound-Based Scaffold-Free Core-Shell Multicellular Tumor Spheroid Formation

In cancer research and drug screening, multicellular tumor spheroids (MCTSs) are a popular model to bridge the gap between in vitro and in vivo. However, the current techniques to culture mixed co-culture MCTSs do not mimic the structural architecture and cellular spatial distribution in solid tumors. In this study we present an acoustic trapping-based core-shell MCTSs culture method using sequential seeding of the core and shell cells into microwells coated with a protein repellent coating. Scaffold-free core-shell ovarian cancer OVCAR-8 cell line MCTSs were cultured, stained, cleared and confocally imaged on-chip. Image analysis techniques were used to quantify the shell thickness (23.2 ± 1.8 µm) and shell coverage percentage (91.2 ± 2.8%). We also show that the shell thickness was evenly distributed over the MCTS cores with the exception of being slightly thinner close to the microwell bottom. This scaffold-free core-shell MCTSs formation technique and the analysis tools presented herein could be used as an internal migration assay within the MCTS or to form core-shell MCTS co-cultures to study therapy response or the interaction between tumor and stromal cells.

Association of Plasmodium berghei With the Apical Domain of Hepatocytes Is Necessary for the Parasite's Liver Stage Development

Plasmodium parasites undergo a dramatic transformation during the liver stage of their life cycle, amplifying over 10,000-fold inside infected hepatocytes within a few days. Such a rapid growth requires large-scale interactions with, and manipulations of, host cell functions. Whereas hepatocyte polarity is well-known to be critical for liver function, little is presently known about its involvement during the liver stage of Plasmodium development. Apical domains of hepatocytes are critical components of their polarity machinery and constitute the bile canalicular network, which is central to liver function. Here, we employed high resolution 3-D imaging and advanced image analysis of Plasmodium-infected liver tissues to show that the parasite associates preferentially with the apical domain of hepatocytes and induces alterations in the organization of these regions, resulting in localized changes in the bile canalicular architecture in the liver tissue. Pharmacological perturbation of the bile canalicular network by modulation of AMPK activity reduces the parasite's association with bile canaliculi and arrests the parasite development. Our findings using Plasmodium-infected liver tissues reveal a host-Plasmodium interaction at the level of liver tissue organization. We demonstrate for the first time a role for bile canaliculi, a central component of the hepatocyte polarity machinery, during the liver stage of Plasmodium development.

Identifying the dynamics of actin and tubulin polymerization in iPSCs and in iPSC-derived neurons

The development of the nervous system requires cytoskeleton-mediated processes coordinating self-renewal, migration, and differentiation of neurons. It is not surprising that many neurodevelopmental problems and neurodegenerative disorders are caused by deficiencies in cytoskeleton-related genes. For this reason, we focus on the cytoskeletal dynamics in proliferating iPSCs and in iPSC-derived neurons to better characterize the underpinnings of cytoskeletal organization looking at actin and tubulin repolymerization studies using the cell permeable probes SiR-Actin and SiR-Tubulin. During neurogenesis, each neuron extends an axon in a complex and changing environment to reach its final target. The dynamic behavior of the growth cone and its capacity to respond to multiple spatial information allows it to find its correct target. We decided to characterize various parameters of the actin filaments and microtubules. Our results suggest that a rapid re-organization of the cytoskeleton occurs 45 minutes after treatments with de-polymerizing agents in iPSCs and 60 minutes in iPSC-derived neurons in both actin filaments and microtubules. The quantitative data confirm that the actin filaments have a primary role in the re-organization of the cytoskeleton soon after de-polymerization, while microtubules have a major function following cytoskeletal stabilization. In conclusion, we investigate the possibility that de-polymerization of the actin filaments may have an impact on microtubules organization and that de-polymerization of the microtubules may affect the stability of the actin filaments. Our results suggest that a reciprocal influence of the actin filaments occurs over the microtubules and vice versa in both in iPSCs and iPSC-derived neurons.

NODeJ: an ImageJ plugin for 3D segmentation of nuclear objects

BACKGROUND

The three-dimensional nuclear arrangement of chromatin impacts many cellular processes operating at the DNA level in animal and plant systems. Chromatin organization is a dynamic process that can be affected by biotic and abiotic stresses. Three-dimensional imaging technology allows to follow these dynamic changes, but only a few semi-automated processing methods currently exist for quantitative analysis of the 3D chromatin organization.

RESULTS

We present an automated method, Nuclear Object DetectionJ (NODeJ), developed as an imageJ plugin. This program segments and analyzes high intensity domains in nuclei from 3D images. NODeJ performs a Laplacian convolution on the mask of a nucleus to enhance the contrast of intra-nuclear objects and allow their detection. We reanalyzed public datasets and determined that NODeJ is able to accurately identify heterochromatin domains from a diverse set of Arabidopsis thaliana nuclei stained with DAPI or Hoechst. NODeJ is also able to detect signals in nuclei from DNA FISH experiments, allowing for the analysis of specific targets of interest.

CONCLUSION AND AVAILABILITY

NODeJ allows for efficient automated analysis of subnuclear structures by avoiding the semi-automated steps, resulting in reduced processing time and analytical bias. NODeJ is written in Java and provided as an ImageJ plugin with a command line option to perform more high-throughput analyses. NODeJ can be downloaded from https://gitlab.com/axpoulet/image2danalysis/-/releases with source code, documentation and further information avaliable at https://gitlab.com/axpoulet/image2danalysis . The images used in this study are publicly available at https://www.brookes.ac.uk/indepth/images/ and https://doi.org/10.15454/1HSOIE .

Virtual Mapping of the Frontal Recess: Guiding Safe and Efficient Frontal Sinus Surgery

Objective To define relationships between the frontal sinus opening, ostia of other frontal recess cells, and endoscopic landmarks and to develop a clinically useful framework to guide frontal sinus surgery. Study Design Retrospective review. Setting Tertiary care academic referral center. Methods Adult patients with computed tomography (CT) without sinonasal pathology were included. Virtual endoscopy (using OsiriX) and corresponding CT reconstructions were used to identify all visible ostia in the frontal recess and characterize their positions in spaces between the uncinate/agger nasi (U), bulla ethmoidalis (EB), and middle turbinate (MT). Results Two hundred sides in 100 patients (median age 51 years, 62% female) were analyzed. The "center" of each map was defined as the intersection of spaces between U, EB, and MT. The frontal sinus opening was in the "center" in 53% of frontal recesses, lateral to this position in 29%, and anterior in 11%. When the frontal sinus opening was at the "center," anterior ostia drained frontal Kuhn T cells in 51% and intersinus septal cells in 23%. The skull base attachment of the apical strut of the uncinate process demarcated medial and lateral within the space between U and EB, with the opening to the frontal sinus medial in 68% and lateral in 31%. Left-right asymmetry in frontal sinus openings was noted in 46% of patients. Conclusion Combining preoperative imaging and knowledge of these anatomic relationships may facilitate more efficient frontal outflow tract identification and instrumentation. This represents the first and largest description of ostial configurations relative to endoscopic structural landmarks.

LEVEL OF EVIDENCE

4.

X-ray microtomography analysis of soil pore structure dynamics under wetting and drying cycles

The soil water retention curve is one of the most important properties used to predict the amount of water available to plants, pore size distribution and hydraulic conductivity, as well as knowledge for drainage and irrigation modeling. Depending on the method of measurement adopted, the water retention curve can involve the application of several wetting and drying (W-D) cycles to a soil sample. The method assumes soil pore structure is constant throughout however most of the time soil structure is dynamic and subjected to change when submitted to continuous W-D. Consequently, the pore size distribution, as well as other soil morphological properties can be affected. With this in mind, high resolution X-ray Computed micro-Tomography was utilized to evaluate changes in the soil pore architecture following W-D cycles during the procedure of the water retention curve evaluation. Two different soil sample volumes were analyzed: ROI_W (whole sample) and ROI_HC (the region close to the bottom of the sample). The second region was selected due to its proximity to the hydraulic contact of the soil with the water retention curve measurement apparatus. Samples were submitted to the following W-D treatments: 0, 6 and 12 W-D. Results indicated the soil changed its porous architecture after W-D cycles. The image-derived porosity did not show differences after W-D cycles for ROI_W; while for ROI_HC it increased porosity. The porosity was also lower in ROI_HC in comparison to ROI_W. Pore connectivity improved after W-D cycles for ROI_HC, but not for ROI_W. W-D cycles induced more aligned pores for both ROIs as observed by the tortuosity results. Pore shape showed changes mainly for ROI_W for the equant and triaxial shaped pores; while pore size was significantly influenced by the W-D cycles. Soil water retention curve measurements showed that W-D cycles can affect water retention evaluation and that the changes in the soil morphological properties can play an important role in it.

A scoping review of new technologies for dental plaque quantitation: Benefits and limitations

OBJECTIVES

To determine the validity and reliability of novel digitalized tools for dental plaque detection and explore the benefits and limitations connected to their use.

DATA

Reporting followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Extension for Scoping Reviews. All human clinical studies comparing dental plaque detection using digitalized systems against a standard reference were included.

SOURCES

PubMed and Scopus were screened from 01 January 2013 to 28 September 2023. Bibliographies of primary studies and principal peer-reviewed scientific journals were manually searched.

STUDY SELECTION

The initial search identified 576 articles, with a total of 13 included in the review, published between 2015 and 2023. Most of the studies included (77 %) were cross-sectional with three being prospective. Digital devices captured 2D and 3D images via cameras and intra-oral scanners, respectively. The Turesky's modified plaque index was the most frequent clinical index. Correlation with clinical examination was moderate to strong, with good to excellent intra- and inter-system agreement.

CONCLUSIONS

Within the limitations of this scoping review, image analysis-based plaque detection systems demonstrated good correlations with clinical plaque indices, using both 2D and 3D imaging systems. Whilst digital plaque detection devices offer advantages in terms of procedural standardization and reproducibility, they also have limitations, therefore currently, their application should be underpinned by a comprehensive clinical examination.

CLINICAL SIGNIFICANCE

Digital plaque detection tools, that provide standardized measurements and store acquired images, facilitate more informed feedback to patients. This objective analysis may enhance clinician confidence in their utility for clinical trials and other applications.

DeepProjection: specific and robust projection of curved 2D tissue sheets from 3D microscopy using deep learning

The efficient extraction of image data from curved tissue sheets embedded in volumetric imaging data remains a serious and unsolved problem in quantitative studies of embryogenesis. Here, we present DeepProjection (DP), a trainable projection algorithm based on deep learning. This algorithm is trained on user-generated training data to locally classify 3D stack content, and to rapidly and robustly predict binary masks containing the target content, e.g. tissue boundaries, while masking highly fluorescent out-of-plane artifacts. A projection of the masked 3D stack then yields background-free 2D images with undistorted fluorescence intensity values. The binary masks can further be applied to other fluorescent channels or to extract local tissue curvature. DP is designed as a first processing step than can be followed, for example, by segmentation to track cell fate. We apply DP to follow the dynamic movements of 2D-tissue sheets during dorsal closure in Drosophila embryos and of the periderm layer in the elongating Danio embryo. DeepProjection is available as a fully documented Python package.

Synchrotron radiation-based microcomputed tomography for three-dimensional growth analysis of Aspergillus niger pellets

Filamentous fungi produce a wide range of relevant biotechnological compounds. The close relationship between fungal morphology and productivity has led to a variety of analytical methods to quantify their macromorphology. Nevertheless, only a µ-computed tomography (µ-CT) based method allows a detailed analysis of the 3D micromorphology of fungal pellets. However, the low sample throughput of a laboratory µ-CT limits the tracking of the micromorphological evolution of a statistically representative number of submerged cultivated fungal pellets over time. To meet this challenge, we applied synchrotron radiation-based X-ray microtomography at the Deutsches Elektronen-Synchrotron [German Electron Synchrotron Research Center], resulting in 19,940 3D analyzed individual fungal pellets that were obtained from 26 sampling points during a 48 h Aspergillus niger submerged batch cultivation. For each of the pellets, we were able to determine micromorphological properties such as number and density of spores, tips, branching points, and hyphae. The computed data allowed us to monitor the growth of submerged cultivated fungal pellets in highly resolved 3D for the first time. The generated morphological database from synchrotron measurements can be used to understand, describe, and model the growth of filamentous fungal cultivations.

A robust method for high-precision quantification of the complex three-dimensional vasculatures acquired by X-ray microtomography

The quantification of micro-vasculatures is important for the analysis of angiogenesis on which the detection of tumor growth or hepatic fibrosis depends. Synchrotron-based X-ray computed micro-tomography (SR-µCT) allows rapid acquisition of micro-vasculature images at micrometer-scale spatial resolution. Through skeletonization, the statistical features of the micro-vasculature can be extracted from the skeleton of the micro-vasculatures. Thinning is a widely used algorithm to produce the vascular skeleton in medical research. Existing three-dimensional thinning methods normally emphasize the preservation of topological structure rather than geometrical features in generating the skeleton of a volumetric object. This results in three problems and limits the accuracy of the quantitative results related to the geometrical structure of the vasculature. The problems include the excessively shortened length of elongated objects, eliminated branches of blood vessel tree structure, and numerous noisy spurious branches. The inaccuracy of the skeleton directly introduces errors in the quantitative analysis, especially on the parameters concerning the vascular length and the counts of vessel segments and branching points. In this paper, a robust method using a consolidated end-point constraint for thinning, which generates geometry-preserving skeletons in addition to maintaining the topology of the vasculature, is presented. The improved skeleton can be used to produce more accurate quantitative results. Experimental results from high-resolution SR-µCT images show that the end-point constraint produced by the proposed method can significantly improve the accuracy of the skeleton obtained using the existing ITK three-dimensional thinning filter. The produced skeleton has laid the groundwork for accurate quantification of the angiogenesis. This is critical for the early detection of tumors and assessing anti-angiogenesis treatments.

QuickPIV: Efficient 3D particle image velocimetry software applied to quantifying cellular migration during embryogenesis

BACKGROUND

The technical development of imaging techniques in life sciences has enabled the three-dimensional recording of living samples at increasing temporal resolutions. Dynamic 3D data sets of developing organisms allow for time-resolved quantitative analyses of morphogenetic changes in three dimensions, but require efficient and automatable analysis pipelines to tackle the resulting Terabytes of image data. Particle image velocimetry (PIV) is a robust and segmentation-free technique that is suitable for quantifying collective cellular migration on data sets with different labeling schemes. This paper presents the implementation of an efficient 3D PIV package using the Julia programming language-quickPIV. Our software is focused on optimizing CPU performance and ensuring the robustness of the PIV analyses on biological data.

RESULTS

QuickPIV is three times faster than the Python implementation hosted in openPIV, both in 2D and 3D. Our software is also faster than the fastest 2D PIV package in openPIV, written in C++. The accuracy evaluation of our software on synthetic data agrees with the expected accuracies described in the literature. Additionally, by applying quickPIV to three data sets of the embryogenesis of Tribolium castaneum, we obtained vector fields that recapitulate the migration movements of gastrulation, both in nuclear and actin-labeled embryos. We show normalized squared error cross-correlation to be especially accurate in detecting translations in non-segmentable biological image data.

CONCLUSIONS

The presented software addresses the need for a fast and open-source 3D PIV package in biological research. Currently, quickPIV offers efficient 2D and 3D PIV analyses featuring zero-normalized and normalized squared error cross-correlations, sub-pixel/voxel approximation, and multi-pass. Post-processing options include filtering and averaging of the resulting vector fields, extraction of velocity, divergence and collectiveness maps, simulation of pseudo-trajectories, and unit conversion. In addition, our software includes functions to visualize the 3D vector fields in Paraview.

PREDECT Protocols for Complex 2D/3D Cultures

PREDECT, a European IMI consortium, has assumed the task to generate robust 2D and 3D culture platforms. Protocols established for 2D and 3D monoculture and stromal coculture models of increasing complexity (spheroid, stirred-tank bioreactor, Matrigel- and collagen-embedded cultures) have been established between six laboratories within academia, biotech, and pharma. These models were tested using three tumor cell lines (MCF7, LNCaP, and NCI-H1437), covering three pathologies (breast, prostate, and lung), but should be readily transferable to other model systems. Fluorescent protein tagged cell lines were used for all platforms, allowing for online measurement of growth curves and drug responses to treatments. All methods, from culture setup to phenotypic characterization and gene expression profiling are described in this chapter.The adaptable methodologies and detailed protocols described here should help to include these models more readily to the drug discovery pipeline.

Assessing and Quantifying the Surface Texture of Milk Powder Using Image Processing

Milk powders produced from similar spray dryers have different visual appearances, while the surface appearance of the powder is a key quality attribute because the smoothness of the milk powder also affects flowability and handling properties. Traditionally quantifying this nuanced visual metric was undertaken using sensory panelists, which is both subjective and time consuming. Therefore, it is advantageous to develop an on-line quick and robust appearance assessment tool. The aim of this work is to develop a classification model which can classify the milk powder samples into different surface smoothness groups. This work proposes a strategy for quantifying the relative roughness of commercial milk powder from 3D images. Photogrammetry equipment together with the software RealityCapture were used to build 3D models of milk powder samples, and a surface normal analysis which compares the area of the triangle formed by the 3 adjacent surface normals or compares the angle between the adjacent surface normals was used to quantify the surface smoothness of the milk powder samples. It was found that the area of the triangle of the smooth-surface milk powder cone is smaller than the area of the triangle of the rough-surface milk powder cone, and the angle between the adjacent surface normals of the rough-surface milk powder cone is larger than the angle between the adjacent surface normals of the smooth-surface milk powder cone, which proved that the proposed area metrics and angle metrics can be used as tools to quantify the smoothness of milk powder samples. Finally, the result of the support vector machine (SVM) classifier proved that image processing can be used as a preliminary tool for classifying milk powder into different surface texture groups.

Image-based modeling of vascular organization to evaluate anti-angiogenic therapy

In tumor therapy anti-angiogenic approaches have the potential to increase the efficacy of a wide variety of subsequently or co-administered agents, possibly by improving or normalizing the defective tumor vasculature. Successful implementation of the concept of vascular normalization under anti-angiogenic therapy, however, mandates a detailed understanding of key characteristics and a respective scoring metric that defines an improved vasculature and thus a successful attempt. Here, we show that beyond commonly used parameters such as vessel patency and maturation, anti-angiogenic approaches largely benefit if the complex vascular network with its vessel interconnections is both qualitatively and quantitatively assessed. To gain such deeper insight the organization of vascular networks, we introduce a multi-parametric evaluation of high-resolution angiographic images based on light-sheet fluorescence microscopy images of tumors. We first could pinpoint key correlations between vessel length, straightness and diameter to describe the regular, functional and organized structure observed under physiological conditions. We found that vascular networks from experimental tumors diverted from those in healthy organs, demonstrating the dysfunctionality of the tumor vasculature not only on the level of the individual vessel but also in terms of inadequate organization into larger structures. These parameters proofed effective in scoring the degree of disorganization in different tumor entities, and more importantly in grading a potential reversal under treatment with therapeutic agents. The presented vascular network analysis will support vascular normalization assessment and future optimization of anti-angiogenic therapy.

Role of Hydrogen-Charging on Nucleation and Growth of Ductile Damage in Austenitic Stainless Steels

Hydrogen energy is a possible solution for storage in the future. The resistance of packaging materials such as stainless steels has to be guaranteed for a possible use of these materials as containers for highly pressurized hydrogen. The effect of hydrogen charging on the nucleation and growth of microdamage in two different austenitic stainless steels AISI316 and AISI316L was studied using in situ tensile tests in synchrotron X-ray tomography. Information about damage nucleation, void growth and void shape were obtained. AISI316 was found to be more sensitive to hydrogen compared to AISI316L in terms of ductility loss. It was measured that void nucleation and growth are not affected by hydrogen charging. The effect of hydrogen was however found to change the morphology of nucleated voids from spherical cavities to micro-cracks being oriented perpendicular to the tensile axis.

In Silico Methods for Cell Annotation, Quantification of Gene Expression, and Cell Geometry at Single-Cell Resolution Using 3DCellAtlas

A comprehensive understanding of plant growth and development requires the integration of the spatial and temporal dynamics of gene regulatory networks with changes in cellular geometry during 3D organ growth. 3DCellAtlas is an integrative computational pipeline that semi-automatically identifies cell type and position within radially symmetric plant organs, and simultaneously quantifies 3D cell anisotropy and reporter abundance at single-cell resolution. It is a powerful tool that generates digital single-cell cellular atlases of plant organs and enables 3D cell geometry and reporter abundance (gene/protein/biosensor) from multiple samples to be integrated at single-cell resolution across whole organs. Here we describe how to use 3DCellAtlas to process and analyze radially symmetric organs, and to identify cell types and extract geometric cell data within these 3D cellular datasets. We detail how to use two statistical tools in 3DCellAtlas to compare cellular geometries, and to analyze reporter abundance at single-cell resolution.