Structure tensor based analysis of cells and nuclei organization in tissues

International audienceMotivation: Extracting geometrical information from large 2D or 3D biomedical images is important to better understand fundamental phenomena such as morphogenesis. We address the problem of automatically analyzing spatial organization of cells or nuclei in 2D or 3D images of tissues. This problem is challenging due to the usually low quality of microscopy images as well as their typically large sizes. Results: The structure tensor is a simple and robust descriptor that was developed to analyze textures orientation. Contrarily to segmentation methods which rely on an object based modelling of images, the structure tensor views the sample at a macroscopic scale, like a continuum. We propose an original theoretical analysis of this tool and show that it allows quantifying two important features of nuclei in tissues: their privileged orientation as well as the ratio between the length of their main axes. A quantitative evaluation of the method is provided for synthetic and real 2D and 3D images. As an application, we analyze the nuclei orientation and anisotropy on multicellular tumor spheroids cryosections. This analysis reveals that cells are elongated in a privileged direction that is parallel to the boundary of the spheroid. Availability: Source codes are available at http://www.math.univ-toulouse.fr/~weiss

Voxel-wise comparisons of cellular microstructure and diffusion-MRI in mouse hippocampus using 3D Bridging of Optically-clear histology with Neuroimaging Data (3D-BOND)

A key challenge in medical imaging is determining a precise correspondence between image properties and tissue microstructure. This comparison is hindered by disparate scales and resolutions between medical imaging and histology. We present a new technique, 3D Bridging of Optically-clear histology with Neuroimaging Data (3D-BOND), for registering medical images with 3D histology to overcome these limitations. Ex vivo 120 × 120 × 200 μm resolution diffusion-MRI (dMRI) data was acquired at 7 T from adult C57Bl/6 mouse hippocampus. Tissue was then optically cleared using CLARITY and stained with cellular markers and confocal microscopy used to produce high-resolution images of the 3D-tissue microstructure. For each sample, a dense array of hippocampal landmarks was used to drive registration between upsampled dMRI data and the corresponding confocal images. The cell population in each MRI voxel was determined within hippocampal subregions and compared to MRI-derived metrics. 3D-BOND provided robust voxel-wise, cellular correlates of dMRI data. CA1 pyramidal and dentate gyrus granular layers had significantly different mean diffusivity (p > 0.001), which was related to microstructural features. Overall, mean and radial diffusivity correlated with cell and axon density and fractional anisotropy with astrocyte density, while apparent fibre density correlated negatively with axon density. Astrocytes, axons and blood vessels correlated to tensor orientation

Multiscale Anisotropy Analysis of Second-Harmonic Generation Imaging of Pancreatic Cancer

Despite recent advancements in biomedicine, cancer is still the second leading cause of death in the United States. Early detection of cancer is critical to improving patient care, but there are risks of over screening caused by the need for surgical biopsies in many cancers for final diagnostics. Recent advancements in computer aided diagnostics for breast cancer screening has reduced the need for biopsies and resulted in earlier diagnoses which has lowered the mortality rate from breast cancer within the past two decades. Developing new computer aided diagnostic tools that can be applied to a vast majority of cancers would serve to improve quality of life worldwide. These tools could also help researchers target and understand biological markers that lead to more malignant cancers improving both our treatment and understanding of cancer progression. The novel combination of the label-free, collagen-specific microscopy technique known as second harmonic generation (SHG) and the 2D Wavelet Transform Modulus Maxima (2D WTMM) Anisotropy Method is a prime candidate to serve this role. The 2D WTMM Anisotropy Method, originally developed for galactic astronomy and then used in multiple biological studies, was further adapted for SHG imaging of cancer in this work by improving both the binning and normalization techniques. This improved method was then applied to forty slides from pancreatic ductal adenocarcinoma (PDAC) patients and eight images were captured per each tissue category on each slide. Cancer and fibrosis had greater anisotropy factors (Fa) at small wavelet scales than normal and normal adjacent tissue. At scales larger than 21 μm this relationship changed with normal tissue having a higher Fa than all other tissue groups. This demonstrated that our developed method is sensitive to changes induced by PDAC. Our method was also compared to other open source SHG image analysis tools currently used by researchers in the field by generating 100 simulated fiber images at four different angle distributions of 0-180°, 30-150°, 60-120°, and 85-95°. The 2D WTMM Anisotropy method could differentiate the 0-180° and 30-150° groups at multiple scales whereas off-the-shelf tools could not. Four different levels of white noise were also added to the 60-120° angle distributions images to test each methods sensitivity to noise by comparing each noise convolved fiber image to pure white noise. The 2D WTMM Anisotropy Method was the only method capable of differentiating all added noise levels from white noise demonstrating its superior resistance to noise. This method will soon be applied to a larger breast cancer study and a breast cancer spheroid study. In both cases further developments to the method are planned, such as developing a version capable of analyzing 3D images and coupling the method with a machine learning technique

Quantitative characterization of pore structure of several biochars with 3D imaging

Pore space characteristics of biochars may vary depending on the used raw material and processing technology. Pore structure has significant effects on the water retention properties of biochar amended soils. In this work, several biochars were characterized with three-dimensional imaging and image analysis. X-ray computed microtomography was used to image biochars at resolution of 1.14 $\mu$m and the obtained images were analysed for porosity, pore-size distribution, specific surface area and structural anisotropy. In addition, random walk simulations were used to relate structural anisotropy to diffusive transport. Image analysis showed that considerable part of the biochar volume consist of pores in size range relevant to hydrological processes and storage of plant available water. Porosity and pore-size distribution were found to depend on the biochar type and the structural anisotopy analysis showed that used raw material considerably affects the pore characteristics at micrometre scale. Therefore attention should be paid to raw material selection and quality in applications requiring optimized pore structure.Comment: 16 pages, 4 figures. The final publication is available at Springer via http://dx.doi.org/10.1007/s11356-017-8823-

An orbitally derived single-atom magnetic memory

A single magnetic atom on a surface epitomizes the scaling limit for magnetic information storage. Indeed, recent work has shown that individual atomic spins can exhibit magnetic remanence and be read out with spin-based methods, demonstrating the fundamental requirements for magnetic memory. However, atomic spin memory has been only realized on thin insulating surfaces to date, removing potential tunability via electronic gating or distance-dependent exchange-driven magnetic coupling. Here, we show a novel mechanism for single-atom magnetic information storage based on bistability in the orbital population, or so-called valency, of an individual Co atom on semiconducting black phosphorus (BP). Distance-dependent screening from the BP surface stabilizes the two distinct valencies and enables us to electronically manipulate the relative orbital population, total magnetic moment and spatial charge density of an individual magnetic atom without a spin-dependent readout mechanism. Furthermore, we show that the strongly anisotropic wavefunction can be used to locally tailor the switching dynamics between the two valencies. This orbital memory derives stability from the energetic barrier to atomic relaxation and demonstrates the potential for high-temperature single-atom information storage

Probing white-matter microstructure with higher-order diffusion tensors and susceptibility tensor MRI.

Diffusion MRI has become an invaluable tool for studying white matter microstructure and brain connectivity. The emergence of quantitative susceptibility mapping and susceptibility tensor imaging (STI) has provided another unique tool for assessing the structure of white matter. In the highly ordered white matter structure, diffusion MRI measures hindered water mobility induced by various tissue and cell membranes, while susceptibility sensitizes to the molecular composition and axonal arrangement. Integrating these two methods may produce new insights into the complex physiology of white matter. In this study, we investigated the relationship between diffusion and magnetic susceptibility in the white matter. Experiments were conducted on phantoms and human brains in vivo. Diffusion properties were quantified with the diffusion tensor model and also with the higher order tensor model based on the cumulant expansion. Frequency shift and susceptibility tensor were measured with quantitative susceptibility mapping and susceptibility tensor imaging. These diffusion and susceptibility quantities were compared and correlated in regions of single fiber bundles and regions of multiple fiber orientations. Relationships were established with similarities and differences identified. It is believed that diffusion MRI and susceptibility MRI provide complementary information of the microstructure of white matter. Together, they allow a more complete assessment of healthy and diseased brains