Bulk Wave Velocities in Cortical Bone Reflect Porosity and Compression Strength

Conventional Manufacturing by Pouring Versus Additive Manufacturing Technology of β-Tricalcium Phosphate Bone Substitute Implants

The aim of the study was to compare conventional sintering with additive manufacturing techniques for β-TCP bioceramics, focusing on mechanical properties and biocompatibility. A "critical" bone defect requires surgical intervention beyond simple stabilization. Autologous bone grafting is the gold standard treatment for such defects, but it has its limitations. Alloplastic bone grafting with synthetic materials is becoming increasingly popular. The use of bone graft substitutes has increased significantly, and current research has focused on optimizing these substitutes, whereas this study compares two existing manufacturing techniques and the resulting β-TCP implants. The 3D printed β-TCP hybrid structure implant was fabricated from two components, a column structure and a freeze foam, which were sintered together. The conventionally fabricated ceramics were fabricated by casting. Both scaffolds were characterized for porosity, mechanical properties, and biocompatibility. The hybrid structure had an overall porosity of 74.4 ± 0.5%. The microporous β-TCP implants had a porosity of 43.5 ± 2.4%, while the macroporous β-TCP implants had a porosity of 61.81%. Mechanical testing revealed that the hybrid structure had a compressive strength of 10.4 ± 6 MPa, which was significantly lower than the microporous β-TCP implants with 32.9 ± 8.7 MPa. Biocompatibility evaluations showed a steady increase in cell proliferation over time for all the β-TCP implants, with minimal cytotoxicity. This study provides a valuable insight into the potential of additive manufacturing for β-TCP bioceramics in the treatment of bone defects.

In Vivo Assessment of Bone Quality Without X-rays

PURPOSE OF REVIEW

This review summarizes recent advances in the assessment of bone quality using non-X-ray techniques.

RECENT FINDINGS

Quantitative ultrasound (QUS) provides multiple measurements of bone characteristics based on the propagation of sound through bone, the attenuation of that sound, and different processing techniques. QUS parameters and model predictions based on backscattered signals can discriminate non-fracture from fracture cases with accuracy comparable to standard bone mineral density (BMD). With advances in magnetic resonance imaging (MRI), bound water and pore water, or a porosity index, can be quantified in several long bones in vivo. Since such imaging-derived measurements correlate with the fracture resistance of bone, they potentially provide new BMD-independent predictors of fracture risk. While numerous measurements of mineral, organic matrix, and bound water by Raman spectroscopy correlate with the strength and toughness of cortical bone, the clinical assessment of person's bone quality using spatially offset Raman spectroscopy (SORS) requires advanced spectral processing techniques that minimize contaminating signals from fat, skin, and blood. Limiting exposure of patients to ionizing radiation, QUS, MRI, and SORS has the potential to improve the assessment of fracture risk and track changes of new therapies that target bone matrix and micro-structure.

The influence of intra-cortical microstructure on the contrast in ultrasound images of the cortex of long bones: A 2D simulation study

Decreased thickness of the bone cortex due to bone loss in the course of ageing and osteoporosis is associated with reduced bone strength. Cortical thickness measurement from ultrasound images was recently demonstrated in young adults. This requires the identification of both the outer (periosteum) and inner (endosteum) surfaces of the bone cortex. However, with bone loss, the cortical porosity and the size of the vascular pores increase resulting in enhanced ultrasound scattering which may prevent the detection of the endosteum. The aim of this work was to study the influence of cortical bone microstructure variables, such as porosity and pore size, on the contrast of the endosteum in ultrasound images. We wanted to estimate the range of these variables for which ultrasound imaging of the endosteum is feasible. We generated synthetic data using a two-dimensional time-domain code to simulate the propagation of elastodynamic waves. A synthetic aperture imaging sequence with an array transducer operating at a center frequency of 2.5 MHz was used. The numerical simulations were conducted for 105 cortical microstructures obtained from high resolution X-ray computed tomography images of ex vivo bone samples with a porosity ranging from 2% to 24 %. Images were reconstructed using a delay-and-sum (DAS) algorithm with optimized f-number, correction of refraction at the periosteum, and sample-specific wave-speed. We observed a range variation of 18 dB of endosteum contrast in our data set depending on the bone microstructure. We found that as porosity increases, speckle intensity inside the bone cortex increases whereas the intensity of the signal from the endosteum decreases. Also, a microstructure with large pores (diameter >250 μm) was associated with poor endosteum visibility, compared with a microstructure with equal porosity but a more narrow distribution of pore sizes. These findings suggest that ultrasound imaging of the bone cortex with a probe operating at a central frequency of 2.5 MHz using refraction-corrected DAS is capable of detecting the endosteum of a cortex with moderate porosity (less than about 10%) if the largest pores remain smaller than about 200 μm.

Improving Transcranial Acoustic Targeting: The Limits of CT-Based Velocity Estimates and the Role of MR

Transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) enables the noninvasive treatment of the deep brain. This capacity relies on the ability to focus acoustic energy through the in-tact skull, a feat that requires accurate estimates of the acoustic velocity in individual patient skulls. In current practice, these estimates are generated using a pretreatment computed tomography (CT) scan and then registered to a magnetic resonance (MR) dataset on the day of the treatment. Treatment safety and efficacy can be improved by eliminating the need to register the CT data to the MR images and by improving the accuracy of acoustic velocity measurements. In this study, we examine the capacity of MR to supplement or replace CT as a means of estimating velocity in the skull. We find that MR can predict velocity with less but comparable accuracy to CT. We then use micro-CT imaging to better understand the limitations of Hounsfield unit (HU)-based estimates of velocity, demonstrating that the macrostructure of pores in the skull contributes to the acoustic velocity of the bone. We find evidence that detailed T2 measurements provide information about pore macrostructure similar to the information obtained with micro-CT, offering a potential clinical mechanism for improving patient-specific estimates of acoustic velocity in the human skull.

Personalised pose estimation from single-plane moving fluoroscope images using deep convolutional neural networks

Measuring joint kinematics is a key requirement for a plethora of biomechanical research and applications. While x-ray based systems avoid the soft-tissue artefacts arising in skin-based measurement systems, extracting the object’s pose (translation and rotation) from the x-ray images is a time-consuming and expensive task. Based on about 106’000 annotated images of knee implants, collected over the last decade with our moving fluoroscope during activities of daily living, we trained a deep-learning model to automatically estimate the 6D poses for the femoral and tibial implant components. By pretraining a single stage of our architecture using renderings of the implant geometries, our approach offers personalised predictions of the implant poses, even for unseen subjects. Our approach predicted the pose of both implant components better than about 0.75 mm (in-plane translation), 25 mm (out-of-plane translation), and 2° (all Euler-angle rotations) over 50% of the test samples. When evaluating over 90% of test samples, which included heavy occlusions and low contrast images, translation performance was better than 1.5 mm (in-plane) and 30 mm (out-of-plane), while rotations were predicted better than 3−4°. Importantly, this approach now allows for pose estimation in a fully automated manner.

Ultrasound Scattering in Cortical Bone

Recent advances in imaging of bone microstructure have led to a growing recognition of the role of cortical microstructure in osteoporosis. It is now accepted that the assessment of the microstructure of cortical porosity is essential to assess bone mechanical competence and predict fracture risk. Cortical porosity affects the propagation of ultrasound waves because pores act as ultrasound scatterers. Scattering by the porosity is an opportunity that should be leveraged to extract quantitative information about cortical microstructure. Scattering by the pores affects a number of ultrasound parameters that should be quantified, including attenuation, backscatter coefficient, ultrasound diffusivity, and their frequency dependence. Measuring these ultrasound parameters and developing models that describe their dependence upon parameters of cortical microstructure is the key to solve inverse problems that will allow the quantitative assessment of cortical porosity and ultimately will improve the non-invasive ultrasound-based evaluation of bone mechanical competence and fracture risk. In this chapter, we present recent advances in measuring and modeling those parameters in cortical bone.

An investigation on osteoporosis based on guided wave propagation in multi-layered bone plates

In this study, the multi-layer structure of bones has been used to simulate bone loss, and the guided waves were transmitted to the double-layer structured simulated bone plates, which are cortical bone and spongy bone. The soft tissue layer was simulated by water and the theoretical solution of the multilayer structure has been established. The guided waves were excited by the laser ultrasound technique and the Recursive Asymptotic Stiffness Matrix (RASM) was used to build a multilayer structure. Results show that, as the cortical bone is thinned, the dispersion relationship curve mode shifts toward high frequency and low phase velocity. Also, as the spongy bone density decreases, the dispersion relationship curve mode moves toward high frequency and high phase velocity. Further, it is found that, as the porosity rises, the mode of the dispersion relationship curve shifts to the direction of low frequency and low phase velocity. Through the addition of soft tissues and introduction of simultaneous changes in parameters, osteoporosis can be distinguished with high accuracy and hence this method can be applied to the detection of osteoporosis in the future.

Finite Element Assessment of Bone Fragility from Clinical Images

PURPOSE OF REVIEW

We re-evaluated clinical applications of image-to-FE models to understand if clinical advantages are already evident, which proposals are promising, and which questions are still open.

RECENT FINDINGS

CT-to-FE is useful in longitudinal treatment evaluation and groups discrimination. In metastatic lesions, CT-to-FE strength alone accurately predicts impending femoral fractures. In osteoporosis, strength from CT-to-FE or DXA-to-FE predicts incident fractures similarly to DXA-aBMD. Coupling loads and strength (possibly in dynamic models) may improve prediction. One promising MRI-to-FE workflow may now be tested on clinical data. Evidence of artificial intelligence usefulness is appearing. CT-to-FE is already clinical in opportunistic CT screening for osteoporosis, and risk of metastasis-related impending fractures. Short-term keys to improve image-to-FE in osteoporosis may be coupling FE with fall risk estimates, pool FE results with other parameters through robust artificial intelligence approaches, and increase reproducibility and cross-validation of models. Modeling bone modifications over time and bone fracture mechanics are still open issues.

Pore-Size Distribution and Frequency-Dependent Attenuation in Human Cortical Tibia Bone Discriminate Fragility Fractures in Postmenopausal Women With Low Bone Mineral Density

Osteoporosis is a disorder of bone remodeling leading to reduced bone mass, structural deterioration, and increased bone fragility. The established diagnosis is based on the measurement of areal bone mineral density by dual‐energy X‐ray absorptiometry (DXA), which poorly captures individual bone loss and structural decay. Enlarged cortical pores in the tibia have been proposed to indicate structural deterioration and reduced bone strength in the hip. Here, we report for the first time the in vivo assessment of the cortical pore‐size distribution together with frequency‐dependent attenuation at the anteromedial tibia midshaft by means of a novel ultrasonic cortical backscatter (CortBS) technology. We hypothesized that the CortBS parameters are associated with the occurrence of fragility fractures in postmenopausal women (n = 55). The discrimination performance was compared with those of DXA and high‐resolution peripheral computed tomography (HR‐pQCT). The results suggest a superior discrimination performance of CortBS (area under the receiver operating characteristic curve [AUC]: 0.69 ≤ AUC ≤ 0.75) compared with DXA (0.54 ≤ AUC ≤ 0.55) and a similar performance compared with HR‐pQCT (0.66 ≤ AUC ≤ 0.73). CortBS is the first quantitative bone imaging modality that can quantify microstructural tissue deteriorations in cortical bone, which occur during normal aging and the development of osteoporosis. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.