With ageing and various diseases, the vascular pore volume fraction (porosity) in cortical bone increases, and the morphology of the pore network is altered. Cortical bone elasticity is known to decrease with increasing porosity, but the effect of the microstructure is largely unknown, while it has been thoroughly studied for trabecular bone. Also, popular micromechanical models have disregarded several micro-architectural features, idealizing pores as cylinders aligned with the axis of the diaphysis. The aim of this paper is to quantify the relative effects on cortical bone anisotropic elasticity of porosity and other descriptors of the pore network micro-architecture associated with pore number, size and shape. The five stiffness constants of bone assumed to be a transversely isotropic material were measured with resonant ultrasound spectroscopy in 55 specimens from the femoral diaphysis of 29 donors. The pore network, imaged with synchrotron radiation X-ray micro-computed tomography, was used to derive the pore descriptors and to build a homogenization model using the fast Fourier transform (FFT) method. The model was calibrated using experimental elasticity. A detailed analysis of the computed effective elasticity revealed in particular that porosity explains most of the variations of the five stiffness constants and that the effects of other micro-architectural features are small compared to usual experimental errors. We also have evidence that modelling the pore network as an ensemble of cylinders yields biased elasticity values compared to predictions based on the real micro-architecture. The FFT homogenization method is shown to be particularly efficient to model cortical bone.

Volumetric ultrasound imaging has the potential for operator-independent acquisition and enhanced field of view. Panoramic acquisition has many applications across ultrasound; spanning musculoskeletal, liver, breast, and pediatric imaging; and image-guided therapy. Challenges in high-resolution human imaging, such as subtle motion and the presence of bone or gas, have limited such acquisition. These issues can be addressed with a large transducer aperture and fast acquisition and processing. Programmable, ultrafast ultrasound scanners with a high channel count provide an unprecedented opportunity to optimize volumetric acquisition. In this work, we implement nonlinear processing and develop distributed beamformation to achieve fast acquisition over a 47-centimeter aperture. As a result, we achieve a 50-micrometer −6-decibel point spread function at 5 megahertz and resolve in-plane targets. A large volume scan of a human limb is completed in a few seconds, and in a 2-millimeter dorsal vein, the image intensity difference between the vessel center and surrounding tissue was ~50 decibels, facilitating three-dimensional reconstruction of the vasculature.

The cortex of the femoral neck is a key structural element of the human body, yet there is not a reliable metric for predicting the mechanical properties of the bone in this critical region. This study explored the use of a range of non-destructive metrics to measure femoral neck cortical bone stiffness at the millimetre length scale. A range of testing methods and imaging techniques were assessed for their ability to measure or predict the mechanical properties of cortical bone samples obtained from the femoral neck of hip replacement patients. Techniques that can potentially be applied in vivo to measure bone stiffness, including computed tomography (CT), bulk wave ultrasound (BWUS) and indentation, were compared against in vitro techniques, including compression testing, density measurements and resonant ultrasound spectroscopy. Porosity, as measured by micro-CT, correlated with femoral neck cortical bone’s elastic modulus and ultimate compressive strength at the millimetre length scale. Large-tip spherical indentation also correlated with bone mechanical properties at this length scale but to a lesser extent. As the elastic mechanical properties of cortical bone correlated with porosity, we would recommend further development of technologies that can safely measure cortical porosity in vivo.

Objective: Hemorrhagic stroke is a leading threat to human's health. The fast-developing microwave-induced thermoacoustic tomography (MITAT) technique holds potential to do brain imaging. However, transcranial brain imaging based on MITAT is still challenging due to the involved huge heterogeneity in speed of sound and acoustic attenuation of human skull. This work aims to address the adverse effect of the acoustic heterogeneity using a deep-learning-based MITAT (DL-MITAT) approach for transcranial brain hemorrhage detection. Methods: We establish a new network structure, a residual attention U-Net (ResAttU-Net), for the proposed DL-MITAT technique, which exhibits improved performance as compared to some traditionally used networks. We use simulation method to build training sets and take images obtained by traditional imaging algorithms as the input of the network. Results: We present ex-vivo transcranial brain hemorrhage detection as a proof-of-concept validation. By using an 8.1-mm thick bovine skull and porcine brain tissues to perform ex-vivo experiments, we demonstrate that the trained ResAttU-Net is capable of efficiently eliminating image artifacts and accurately restoring the hemorrhage spot. It is proved that the DL-MITAT method can reliably suppress false positive rate and detect a hemorrhage spot as small as 3 mm. We also study effects of several factors of the DL-MITAT technique to further reveal its robustness and limitations. Conclusion: The proposed ResAttU-Net-based DL-MITAT method is promising for mitigating the acoustic inhomogeneity issue and performing transcranial brain hemorrhage detection. Significance: This work provides a novel ResAttU-Net-based DL-MITAT paradigm and paves a compelling route for transcranial brain hemorrhage detection as well as other transcranial brain imaging applications.