3D quantification of the lacunocanalicular network on human femoral diaphysis through synchrotron radiation-based nanoCT.

Osteocytes are the major actors in bone mechanobiology. Within bone matrix, they are trapped close together in a submicrometric interconnected network: the lacunocanalicular network (LCN). The interstitial fluid circulating within the LCN transmits the mechanical information to the osteocytes that convert it into a biochemical signal. Understanding the interstitial fluid dynamics is necessary to better understand the bone mechanobiology. Due to the submicrometric dimensions of the LCN, making it difficult to experimentally investigate fluid dynamics, numerical models appear as a relevant tool for such investigation. To develop such models, there is a need for geometrical and morphological data on the human LCN. This study aims at providing morphological data on the human LCN from measurement of 27 human femoral diaphysis bone samples using synchrotron radiation nano-computed tomography with an isotropic voxel size of 100 nm. Except from the canalicular diameter, the canalicular morphological parameters presented a high variability within one sample. Some differences in terms of both lacunar and canalicular morphology were observed between the male and female populations. But it has to be highlighted that all the canaliculi cannot be detected with a voxel size of 100 nm. Hence, in the current study, only a specific population of large canaliculi that could be characterize. Still, to the authors knowledge, this is the first time such a data set was introduced to the community. Further processing will be achieved in order to provide new insight on the LCN permeability.

Single-pixel image reconstruction from experimental data using neural networks.

Single-pixel cameras that measure image coefficients have various promising applications, in particular for hyper-spectral imaging. Here, we investigate deep neural networks that when fed with experimental data can output high-quality images in real time. Assuming that the measurements are corrupted by mixed Poisson-Gaussian noise, we propose to map the raw data from the measurement domain to the image domain based on a Tikhonov regularization. This step can be implemented as the first layer of a deep neural network, followed by any architecture of layers that acts in the image domain. We also describe a framework for training the network in the presence of noise. In particular, our approach includes an estimation of the image intensity and experimental parameters, together with a normalization scheme that allows varying noise levels to be handled during training and testing. Finally, we present results from simulations and experimental acquisitions with varying noise levels. Our approach yields images with improved peak signal-to-noise ratios, even for noise levels that were foreseen during the training of the networks, which makes the approach particularly suitable to deal with experimental data. Furthermore, while this approach focuses on single-pixel imaging, it can be adapted for other computational optics problems.

3D denoised completion network for deep single-pixel reconstruction of hyperspectral images.

Single-pixel imaging acquires an image by measuring its coefficients in a transform domain, thanks to a spatial light modulator. However, as measurements are sequential, only a few coefficients can be measured in the real-time applications. Therefore, single-pixel reconstruction is usually an underdetermined inverse problem that requires regularization to obtain an appropriate solution. Combined with a spectral detector, the concept of single-pixel imaging allows for hyperspectral imaging. While each channel can be reconstructed independently, we propose to exploit the spectral redundancy between channels to regularize the reconstruction problem. In particular, we introduce a denoised completion network that includes 3D convolution filters. Contrary to black-box approaches, our network combines the classical Tikhonov theory with the deep learning methodology, leading to an explainable network. Considering both simulated and experimental data, we demonstrate that the proposed approach yields hyperspectral images with higher quantitative metrics than the approaches developed for grayscale images.

Quantification of the bone lacunocanalicular network from 3D X-ray phase nanotomography images.

There is a growing interest in developing 3D microscopy for the exploration of thick biological tissues. Recently, 3D X-ray nanocomputerised tomography has proven to be a suitable technique for imaging the bone lacunocanalicular network. This interconnected structure is hosting the osteocytes which play a major role in maintaining bone quality through remodelling processes. 3D images have the potential to reveal the architecture of cellular networks, but their quantitative analysis remains a challenge due to the density and complexity of nanometre sized structures and the need to handle and process large datasets, for example, 20483 voxels corresponding to 32 GB per individual image in our case. In this work, we propose an efficient image processing approach for the segmentation of the network and the extraction of characteristic parameters describing the 3D structure. These parameters include the density of lacunae, the porosity of lacunae and canaliculi, and morphological features of lacunae (volume, surface area, lengths, anisotropy etc.). We also introduce additional parameters describing the local environment of each lacuna and its canaliculi. The method is applied to analyse eight human femoral cortical bone samples imaged by magnified X-ray phase nanotomography with a voxel size of 120 nm, which was found to be a good compromise to resolve canaliculi while keeping a sufficiently large field of view of 246 µm in 3D. The analysis was performed on a total of 2077 lacunae showing an average length, width and depth of 17.1 µm × 9.2 µm × 4.4 µm, with an average number of 58.2 canaliculi per lacuna and a total lacuno-canalicular porosity of 1.12%. The reported descriptive parameters provide information on the 3D organisation of the lacuno-canalicular network in human bones.

3D micro structural analysis of human cortical bone in paired femoral diaphysis, femoral neck and radial diaphysis.

Human bone is known to adapt to its mechanical environment in a living body. Both its architecture and microstructure may differ between weight-bearing and non-weight-bearing bones. The aim of the current study was to analyze in three dimensions, the morphology of the multi-scale porosities on human cortical bone at different locations. Eight paired femoral diaphyses, femoral necks, and radial diaphyses were imaged using Synchrotron Radiation µCT with a 0.7 µm isotropic voxel size. The spatial resolution facilitates the investigation of the multiscale porosities of cortical bone, from the osteonal canals system down to the osteocyte lacunar system. Our results showed significant differences in the microstructural properties, regarding both osteonal canals and osteocytes lacunae, between the different anatomical locations. The radius presents significantly lower osteonal canal volume fraction and smaller osteonal canals than the femoral diaphysis or neck. Osteocytes lacunae observed in the radius are significantly different in shape than in the femur, and lacunar density is higher in the femoral neck. These results show that the radius, a non-weight-bearing bone, is significantly different in terms of its microstructure from a weight-bearing bone such as the femur. This implies that the cortical bone properties evaluated on the femoral diaphysis, the main location studied within the literature, cannot be generalized to other anatomical locations.

Time-resolved multispectral imaging based on an adaptive single-pixel camera.

Time-resolved multispectral imaging has many applications in different fields, which range from characterization of biological tissues to environmental monitoring. In particular, optical techniques, such as lidar and fluorescence lifetime imaging, require imaging at the subnanosecond scales over an extended area. In this paper, we demonstrate experimentally a time-resolved multispectral acquisition scheme based on single-pixel imaging. Single-pixel imaging is an emerging paradigm that provides low-cost high-quality images. Here, we use an adaptive strategy that allows acquisition and image reconstruction times to be reduced drastically or full basis scans. Adaptive time-resolved multispectral imaging scheme can have significant applications in biological imaging, at scales from macroscopic to microscopic.

Evaluation of phase retrieval approaches in magnified X-ray phase nano computerized tomography applied to bone tissue.

X-ray phase contrast imaging offers higher sensitivity compared to conventional X-ray attenuation imaging and can be simply implemented by propagation when using a partially coherent synchrotron beam. We address the phase retrieval in in-line phase nano-CT using multiple propagation distances. We derive a method which extends Paganin's single distance method and compare it to the contrast transfer function (CTF) approach in the case of a homogeneous object. The methods are applied to phase nano-CT data acquired at the voxel size of 30 nm (ID16A, ESRF, Grenoble, France). Our results show a gain in image quality in terms of the signal-to-noise ratio and spatial resolution when using four distances instead of one. The extended Paganin's method followed by an iterative refinement step provides the best reconstructions while the homogeneous CTF method delivers quasi comparable results for our data, even without refinement step.

Broadband time-resolved multi-channel functional near-infrared spectroscopy system to monitor in vivo physiological changes of human brain activity.

We have developed a broadband time-resolved multi-channel near-infrared spectroscopy system that can monitor the physiological responses of the adult human brain. This system is composed of a supercontinuum laser for the source part and of an intensified charge-coupled device camera coupled with an imaging spectrometer for the detection part. It allows the detection of the spectral, from 600 to 900 nm, and spatial dimensions as well as the arrival time of photon information simultaneously. We describe the setup and its characterization in terms of temporal instrument response function, wavelength sensitivity, and stability. The ability of the system to detect the hemodynamic response is then demonstrated. First, an in vivo experiment on an adult volunteer was performed to monitor the response in the arm during a cuff occlusion. Second, the response in the brain during a cognitive task was monitored on a group of five healthy volunteers. Moreover, looking at the response at different time windows, we could monitor the hemodynamic response in depth, enhancing the detection of the cortical activation. Those first results demonstrate the ability of our system to discriminate between the responses of superficial and deep tissues, addressing an important issue in functional near-infrared spectroscopy.

Quantification of stiffness measurement errors in resonant ultrasound spectroscopy of human cortical bone.

Resonant ultrasound spectroscopy (RUS) is the state-of-the-art method used to investigate the elastic properties of anisotropic solids. Recently, RUS was applied to measure human cortical bone, an anisotropic material with low Q-factor (20), which is challenging due to the difficulty in retrieving resonant frequencies. Determining the precision of the estimated stiffness constants is not straightforward because RUS is an indirect method involving minimizing the distance between measured and calculated resonant frequencies using a model. This work was motivated by the need to quantify the errors on stiffness constants due to different error sources in RUS, including uncertainties on the resonant frequencies and specimen dimensions and imperfect rectangular parallelepiped (RP) specimen geometry. The errors were first investigated using Monte Carlo simulations with typical uncertainty values of experimentally measured resonant frequencies and dimensions assuming a perfect RP geometry. Second, the exact specimen geometry of a set of bone specimens were recorded by synchrotron radiation micro-computed tomography. Then, a "virtual" RUS experiment is proposed to quantify the errors induced by imperfect geometry. Results show that for a bone specimen of ∼1° perpendicularity and parallelism errors, an accuracy of a few percent ( <6.2%) for all the stiffness constants and engineering moduli is achievable.

How minute sooglossid frogs hear without a middle ear.

Acoustic communication is widespread in animals. According to the sensory drive hypothesis [Endler JA (1993) Philos Trans R Soc Lond B Biol Sci 340(1292):215-225], communication signals and perceptual systems have coevolved. A clear illustration of this is the evolution of the tetrapod middle ear, adapted to life on land. Here we report the discovery of a bone conduction-mediated stimulation of the ear by wave propagation in Sechellophryne gardineri, one of the world's smallest terrestrial tetrapods, which lacks a middle ear yet produces acoustic signals. Based on X-ray synchrotron holotomography, we measured the biomechanical properties of the otic tissues and modeled the acoustic propagation. Our models show how bone conduction enhanced by the resonating role of the mouth allows these seemingly deaf frogs to communicate effectively without a middle ear.

Distribution of mesoscale elastic properties and mass density in the human femoral shaft.

Cortical bone properties are determined by tissue composition and structure at several hierarchical length scales. In this study, the spatial distribution of micro- and mesoscale elastic properties within a human femoral shaft has been investigated. Microscale tissue degree of mineralization (DMB), cortical vascular porosity Ct.Po and the average transverse isotropic stiffness tensor C(Micro) of cylindrical-shaped samples (diameter: 4.4 mm, N = 56) were obtained from cortical regions between 20 and 85% of the total femur length and around the periphery (anterior, medial, posterior and lateral quadrants) by means of synchrotron radiation µCT (SRµCT) and 50-MHz scanning acoustic microscopy (SAM). Within each cylinder, the volumetric bone mineral density (vBMD) and the mesoscale stiffness tensor C(Meso) were derived using a numerical homogenization approach. Moreover, microelastic maps of the axial elastic coefficient c33 measured by SAM at distinct cross-sectional locations along the femur were used to construct a 3-D multiscale elastic model of the femoral shaft. Variations of vBMD (6.1%) were much lower than the variations of mesoscale elastic coefficients (11.1-21.3%). The variation of DMB was only a minor predictor for variations of the mesoscale elastic properties (0.05 ≤ R(2) ≤ 0.34). Instead, variations of the mesoscale elastic properties could be explained by variations of cortical porosity and microscale elastic properties. These data were suitable inputs for numerical evaluations and may help to unravel the relations between structure and composition on the elastic function in cortical bone.

Accessing osteocyte lacunar geometrical properties in human jaw bone on the submicron length scale using synchrotron radiation µCT.

The architectural properties of the osteocyte cell network provide a valuable basis for understanding the mechanisms of bone remodelling, mineral homeostasis, ageing and pathologies. Recent advances in synchrotron microtomography enable unprecedented three-dimensional imaging of both the bone lacunar network and the extracellular matrix. Here, we investigate the three-dimensional morphological properties of osteocyte lacunae in human healthy and bisphosphonate-related osteonecrotic jaw bone based on synchrotron X-ray computed tomography images, with a spatial isotropic voxel size of 300 nm. Bisphosphonate-related osteonecrosis of the jaw is a relatively new disease with increasing incidence, which remains poorly understood. A step forward in elucidating this malady is to assess whether, and how, the morphology of the osteocyte lacunar network is modified in the affected jaw tissue. We evaluate thousands of cell lacunae from five specimens of which three originate from patients diagnosed with bisphosphonate-associated osteonecrosis. In this exploratory study, we report three-dimensional quantitative results on lacunar volumes (296-502 µm(3)), shape (approximated by an ellipsoidal shape with principal axes a > b > c, such that a = 2.2b and a = 4c) and spatial distribution (i.e., 50% of the mineralized matrix volume is located within 12 µm to the closest lacunar boundary) at submicron resolution on such specimens. We observe that the average lacunar volumes of the bisphosphonate-related osteonecrotic jaw specimens were within the range of volumes found in the two specimens originating from healthy donors and conclude that lacunar volumes are not the key element in the course of bisphosphonate-related osteonecrotic jaw. In three out of five specimens we observe lacunar volume sizes in segmented osteons to be significantly different compared to lacunar volumes in the adjacent tissue regions. Furthermore, we quantify the number of lacunae containing small dense objects (on average 9%). In contrast to lacunar morphology we report the lacunar density (16,000-50,000 per mm(3)) to be different in jaw bone tissue compared to what has been reported in femoral sites.

Micro- and nano-CT for the study of bone ultrastructure.

Micro-computed tomography (micro-CT)-a version of X-ray CT operating at high spatial resolution-has had a considerable success for the investigation of trabecular bone micro-architecture. Currently, there is a lot of interest in exploiting CT techniques at even higher spatial resolutions to assess bone tissue at the cellular scale. After recalling the basic principles of micro-CT, we review the different existing system, based on either standard X-ray tubes or synchrotron sources. Then, we present recent applications of micro- and nano-CT for the analysis of osteocyte lacunae and the lacunar-canalicular network. We also address the question of the quantification of bone ultrastructure to go beyond the sole visualization.

Removing streak artifacts from ECG-gated reconstructions using deconvolution.

BACKGROUND: 4D cardiac computed tomography aims at reconstructing the beating heart from a series of 2D projections and the simultaneously acquired electrocardiogram. Each cardiac phase is reconstructed by exploiting the subset of projections acquired during this particular cardiac phase only. In these conditions, the Feldkamp, Davis and Kress method (FDK) generates large streak artifacts in the reconstructed volumes, hampering the medical interpretation. These artifacts can be substantially reduced by deconvolution methods. OBJECTIVE: The aim of this paper is to compare two 4D cardiac CT reconstruction methods based on deconvolution, and to evaluate their practical benefits on two applications: cardiac micro CT and human cardiac C-arm CT. METHODS: The first evaluated method builds upon inverse filtering. It has been proposed recently and demonstrated on 4D cardiac micro CT. The second one is an iterative deconvolution method, and turns out equivalent to an ECG-gated Iterative Filtered Back Projection (ECG-gated IFBP). RESULTS: Results are presented on simulated data in 2D parallel beam, 2D fan beam and 3D cone beam geometries. CONCLUSIONS: Both methods are efficient on the cardiac micro CT simulations, but insufficient to handle 4D human cardiac C-Arm CT simulations. Overall, ECG-gated IFPB largely outperforms the inverse filtering method.

Information-based analysis of X-ray in-line phase tomography with application to the detection of iron oxide nanoparticles in the brain.

The study analyzes noise in X-ray in-line phase tomography in a biomedical context. The impact of noise on detection of iron oxide nanoparticles in mouse brain is assessed. The part of the noise due to the imaging system and the part due to biology are quantitatively expressed in a Neyman Pearson detection strategy with two models of noise. This represents a practical extension of previous work on noise in phase-contrast X-ray imaging which focused on the theoretical expression of the signal-to-noise ratio in mono-dimensional phantoms, taking account of the statistical noise of the imaging system only. We also report the impact of the phase retrieval step on detection performance. Taken together, this constitutes a general methodology of practical interest for quantitative extraction of information from X-ray in-line phase tomography, and is also relevant to assessment of contrast agents with a blob-like signature in high resolution imaging.

Nonlinear approaches for the single-distance phase retrieval problem involving regularizations with sparsity constraints.

The phase retrieval process is a nonlinear ill-posed problem. The Fresnel diffraction patterns obtained with hard x-ray synchrotron beam can be used to retrieve the phase contrast. In this work, we present a convergence comparison of several nonlinear approaches for the phase retrieval problem involving regularizations with sparsity constraints. The phase solution is assumed to have a sparse representation with respect to an orthonormal wavelets basis. One approach uses alternatively a solution of the nonlinear problem based on the Fréchet derivative and a solution of the linear problem in wavelet coordinates with an iterative thresholding. A second method is the one proposed by Ramlau and Teschke which generalizes to a nonlinear problem the classical thresholding algorithm. The algorithms were tested on a 3D Shepp-Logan phantom corrupted by white Gaussian noise. The best simulation results are obtained by the first method for the various noise levels and initializations investigated. The reconstruction errors are significantly decreased with respect to the ones given by the classical linear phase retrieval approaches.

In situ synchrotron radiation µCT indentation of cortical bone: Anisotropic crack propagation, local deformation, and fracture.

The development of treatment strategies for skeletal diseases relies on the understanding of bone mechanical properties in relation to its structure at different length scales. At the microscale, indention techniques can be used to evaluate the elastic, plastic, and fracture behaviour of bone tissue. Here, we combined in situ high-resolution SRµCT indentation testing and digital volume correlation to elucidate the anisotropic crack propagation, deformation, and fracture of ovine cortical bone under Berkovich and spherical tips. Independently of the indenter type we observed significant dependence of the crack development due to the anisotropy ahead of the tip, with lower strains and smaller crack systems developing in samples indented in the transverse material direction, where the fibrillar bone ultrastructure is largely aligned perpendicular to the indentation direction. Such alignment allows to accommodate the strain energy, inhibiting crack propagation. Higher tensile hoop strains generally correlated with regions that display significant cracking radial to the indenter, indicating a predominant Mode I fracture. This was confirmed by the three-dimensional analysis of crack opening displacements and stress intensity factors along the crack front obtained for the first time from full displacement fields in bone tissue. The X-ray beam significantly influenced the relaxation behaviour independent of the tip. Raman analyses did not show significant changes in specimen composition after irradiation compared to non-irradiated tissue, suggesting an embrittlement process that may be linked to damage of the non-fibrillar organic matrix. This study highlights the importance of three-dimensional investigation of bone deformation and fracture behaviour to explore the mechanisms of bone failure in relation to structural changes due to ageing or disease. STATEMENT OF SIGNIFICANCE: Characterising the three-dimensional deformation and fracture behaviour of bone remains essential to decipher the interplay between structure, function, and composition with the aim to improve fracture prevention strategies. The experimental methodology presented here, combining high-resolution imaging, indentation testing and digital volume correlation, allows us to quantify the local deformation, crack propagation, and fracture modes of cortical bone tissue. Our results highlight the anisotropic behaviour of osteonal bone and the complex crack propagation patterns and fracture modes initiating by the intricate stress states beneath the indenter tip. This is of wide interest not only for the understanding of bone fracture but also to understand other architectured (bio)structures providing an effective way to quantify their toughening mechanisms in relation to their main mechanical function.

Quantification of cartilage and subchondral bone cysts on knee specimens based on a spectral photon-counting computed tomography.

Spectral photon-counting computed tomography (SPCCT) is a new technique with the capability to provide mono-energetic (monoE) images with high signal to noise ratio. We demonstrate the feasibility of SPCCT to characterize at the same time cartilage and subchondral bone cysts (SBCs) without contrast agent in osteoarthritis (OA). To achieve this goal, 10 human knee specimens (6 normal and 4 with OA) were imaged with a clinical prototype SPCCT. The monoE images at 60 keV with isotropic voxels of 250 × 250 × 250 µm3 were compared with monoE synchrotron radiation CT (SR micro-CT) images at 55 keV with isotropic voxels of 45 × 45 × 45 µm3 used as benchmark for cartilage segmentation. In the two OA knees with SBCs, the volume and density of SBCs were evaluated in SPCCT images. In 25 compartments (lateral tibial (LT), medial tibial, (MT), lateral femoral (LF), medial femoral and patella), the mean bias between SPCCT and SR micro-CT analyses were 101 ± 272 mm3 for cartilage volume and 0.33 mm ± 0.18 for mean cartilage thickness. Between normal and OA knees, mean cartilage thicknesses were found statistically different (0.005 < p < 0.04) for LT, MT and LF compartments. The 2 OA knees displayed different SBCs profiles in terms of volume, density, and distribution according to size and location. SPCCT with fast acquisitions is able to characterize cartilage morphology and SBCs. SPCCT can be used potentially as a new tool in clinical studies in OA.

X-ray in-line phase tomography of multimaterial objects.

We present a method for phase retrieval from x-ray Fresnel diffraction patterns for multimaterial objects. Previously, homogeneous object assumptions have been used and have been introduced in the Radon domain. Here, we apply prior knowledge in the object domain, which permits the introduction of multiple materials. This is achieved first by a tomographic reconstruction of an attenuation scan and then introduction of the prior followed by a forward projection step to yield the a priori phase maps. The method is applied to the reconstruction of an object of known composition consisting of both soft and hard materials and is shown to perform better than previously proposed algorithms.

Nanoscale imaging of the bone cell network with synchrotron X-ray tomography: optimization of acquisition setup.

PURPOSE: The fundamental role of the osteocyte cell network in regulating the bone remodeling has become evident in the last years. This has raised the necessity to explore this complex three-dimensional interconnected structure, but the existing investigation methods cannot provide an adequate assessment. The authors propose to use parallel beam synchrotron radiation computed tomography at the nanoscale to image in three dimensions the osteocyte lacunocanalicular network. To this aim, the authors study the feasibility of this technique and present an optimized imaging protocol suited for the bone cell network. Moreover, they demonstrate the multifaceted information provided by this method. METHODS: The high brilliance of synchrotron radiation combined with state of art detectors permits reaching nanoscale spatial resolution. With a nominal pixel size of 280 nm, the parallel beam computed tomography setup at the ID19 experimental station of the ESRF is capable of imaging the bone lacunocanalicular network, considering that the reported diameter of canaliculi is in the range 300-600 nm. However, the actual resolution is limited by the detector and by the radiation dose causing sample damage during the scan. The authors sought to overcome these limitations by optimizing the imaging setup and the acquisition parameters in order to minimize the necessary radiation dose to create the images and to improve the spatial resolution of the detector. RESULTS: The authors achieved imaging of the osteocyte cell network in human bone. Due to the optimization of the imaging setup and acquisition parameters, they obtained simultaneously a radiation dose reduction and an increase of the signal to noise ratio in the images. This permitted the authors to generate the first three-dimensional images of the lacunocanalicular network in an area covering several osteons, the fundamental functional units in the bone cortex. The method enables assessment of both architectural parameters of the microporosity and of mineralization degree in the bone matrix. The authors found that the cell network is dense and connected inside osteonal tissue. Conversely, the cell lacunae are sparse, unorganized, and disconnected in interstitial tissue. CONCLUSIONS: The authors show that synchrotron radiation computed tomography is a feasible technique to assess the lacunocanalicular network in three dimensions. This is possible due to an optimal imaging setup in which the detector plays an important role. The authors could establish two valid setups, based on two different insertion devices. These results give access to new information on the bone cell network architecture, covering a number of cells two orders of magnitude greater than existing techniques. This enables biomedical studies on series of samples, paving the way to better understanding of bone fragility and to new treatments for bone diseases.