Inflammatory response toward a Mg-based metallic biomaterial implanted in a rat femur fracture model.

The immune system plays an important role in fracture healing, by modulating the pro-inflammatory and anti-inflammatory responses occurring instantly upon injury. An imbalance in these responses can lead to adverse outcomes, such as non-union of fractures. Implants are used to support and stabilize complex fractures. Biodegradable metallic implants offer the potential to avoid a second surgery for implant removal, unlike non-degradable implants. However, considering our dynamic immune system it is important to conduct in-depth studies on the immune response to these implants in living systems. In this study, we investigated the immune response to Mg and Mg-10Gd in vivo in a rat femur fracture model with external fixation. In vivo imaging using liposomal formulations was used to monitor the fluorescence-related inflammation over time. We combine ex vivo methods with our in vivo study to evaluate and understand the systemic and local effects of the implants on the immune response. We observed no significant local or systemic effects in the Mg-10Gd implanted group compared to the SHAM and Mg implanted groups over time. Our findings suggest that Mg-10Gd is a more compatible implant material than Mg, with no adverse effects observed in the early phase of fracture healing during our 4-week study. STATEMENT OF SIGNIFICANCE: Degradable metallic implants in form of Mg and Mg-10Gd intramedullary pins were assessed in a rat femur fracture model, alongside a non-implanted SHAM group with special respect to the potential to induce an inflammatory response. This pre-clinical study combines innovative non-invasive in vivo imaging techniques associated with multimodal, ex vivo cellular and molecular analytics. The study contributes to the development and evaluation of degradable biometals and their clinical application potential. The study results indicate that Mg-10Gd did not exhibit any significant harmful effects compared to the SHAM and Mg groups.

The potential role for artificial intelligence in fracture risk prediction.

Osteoporotic fractures are a major health challenge in older adults. Despite the availability of safe and effective therapies for osteoporosis, these therapies are underused in individuals at high risk for fracture, calling for better case-finding and fracture risk assessment strategies. Artificial intelligence (AI) and machine learning (ML) hold promise for enhancing identification of individuals at high risk for fracture by distilling useful features from high-dimensional data derived from medical records, imaging, and wearable devices. AI-ML could enable automated opportunistic screening for vertebral fractures and osteoporosis, home-based monitoring and intervention targeting lifestyle factors, and integration of multimodal features to leverage fracture prediction, ultimately aiding improved fracture risk assessment and individualised treatment. Optimism must be balanced with consideration for the explainability of AI-ML models, biases (including information inequity in numerically under-represented populations), model limitations, and net clinical benefit and workload impact. Clinical integration of AI-ML algorithms has the potential to transform osteoporosis management, offering a more personalised approach to reduce the burden of osteoporotic fractures.

AI-based automated detection and stability analysis of traumatic vertebral body fractures on computed tomography.

PURPOSE: We developed and tested a neural network for automated detection and stability analysis of vertebral body fractures on computed tomography (CT). MATERIALS AND METHODS: 257 patients who underwent CT were included in this Institutional Review Board (IRB) approved study. 463 fractured and 1883 non-fractured vertebral bodies were included, with 190 fractures unstable. Two readers identified vertebral body fractures and assessed their stability. A combination of a Hierarchical Convolutional Neural Network (hNet) and a fracture Classification Network (fNet) was used to build a neural network for the automated detection and stability analysis of vertebral body fractures on CT. Two final test settings were chosen: one with vertebral body levels C1/2 included and one where they were excluded. RESULTS: The mean age of the patients was 68 ± 14 years. 140 patients were female. The network showed a slightly higher diagnostic performance when excluding C1/2. Accordingly, the network was able to distinguish fractured and non-fractured vertebral bodies with a sensitivity of 75.8 % and a specificity of 80.3 %. Additionally, the network determined the stability of the vertebral bodies with a sensitivity of 88.4 % and a specificity of 80.3 %. The AUC was 87 % and 91 % for fracture detection and stability analysis, respectively. The sensitivity of our network in indicating the presence of at least one fracture / one unstable fracture within the whole spine achieved values of 78.7 % and 97.2 %, respectively, when excluding C1/2. CONCLUSION: The developed neural network can automatically detect vertebral body fractures and evaluate their stability concurrently with a high diagnostic performance.

A meta-analysis of previous falls and subsequent fracture risk in cohort studies.

The relationship between self-reported falls and fracture risk was estimated in an international meta-analysis of individual-level data from 46 prospective cohorts. Previous falls were associated with an increased fracture risk in women and men and should be considered as an additional risk factor in the FRAX® algorithm. INTRODUCTION: Previous falls are a well-documented risk factor for subsequent fracture but have not yet been incorporated into the FRAX algorithm. The aim of this study was to evaluate, in an international meta-analysis, the association between previous falls and subsequent fracture risk and its relation to sex, age, duration of follow-up, and bone mineral density (BMD). METHODS: The resource comprised 906,359 women and men (66.9% female) from 46 prospective cohorts. Previous falls were uniformly defined as any fall occurring during the previous year in 43 cohorts; the remaining three cohorts had a different question construct. The association between previous falls and fracture risk (any clinical fracture, osteoporotic fracture, major osteoporotic fracture, and hip fracture) was examined using an extension of the Poisson regression model in each cohort and each sex, followed by random-effects meta-analyses of the weighted beta coefficients. RESULTS: Falls in the past year were reported in 21.4% of individuals. During a follow-up of 9,102,207 person-years, 87,352 fractures occurred of which 19,509 were hip fractures. A previous fall was associated with a significantly increased risk of any clinical fracture both in women (hazard ratio (HR) 1.42, 95% confidence interval (CI) 1.33-1.51) and men (HR 1.53, 95% CI 1.41-1.67). The HRs were of similar magnitude for osteoporotic, major osteoporotic fracture, and hip fracture. Sex significantly modified the association between previous fall and fracture risk, with predictive values being higher in men than in women (e.g., for major osteoporotic fracture, HR 1.53 (95% CI 1.27-1.84) in men vs. HR 1.32 (95% CI 1.20-1.45) in women, P for interaction = 0.013). The HRs associated with previous falls decreased with age in women and with duration of follow-up in men and women for most fracture outcomes. There was no evidence of an interaction between falls and BMD for fracture risk. Subsequent risk for a major osteoporotic fracture increased with each additional previous fall in women and men. CONCLUSIONS: A previous self-reported fall confers an increased risk of fracture that is largely independent of BMD. Previous falls should be considered as an additional risk factor in future iterations of FRAX to improve fracture risk prediction.

Human APOE4 Protects High-Fat and High-Sucrose Diet Fed Targeted Replacement Mice against Fatty Liver Disease Compared to APOE3.

Recent genome- and exome-wide association studies suggest that the human APOE ε4 allele protects against non-alcoholic fatty liver disease (NAFLD), while ε3 promotes hepatic steatosis and steatohepatitis. The present study aimed at examining the APOE genotype-dependent development of fatty liver disease and its underlying mechanisms in a targeted replacement mouse model. Male mice expressing the human APOE3 or APOE4 protein isoforms on a C57BL/6J background and unmodified C57BL/6J mice were chronically fed a high-fat and high-sucrose diet to induce obesity. After 7 months, body weight gain was more pronounced in human APOE than endogenous APOE expressing mice with elevated plasma biomarkers suggesting aggravated metabolic dysfunction. APOE3 mice exhibited the highest liver weights and, compared to APOE4, massive hepatic steatosis. An untargeted quantitative proteome analysis of the liver identified a high number of proteins differentially abundant in APOE3 versus APOE4 mice. The majority of the higher abundant proteins in APOE3 mice could be grouped to inflammation and damage-associated response, and lipid storage, amongst others. Results of the targeted qRT-PCR and Western blot analyses contribute to the overall finding that APOE3 as opposed to APOE4 promotes hepatic steatosis, inflammatory- and damage-associated response signaling and fibrosis in the liver of obese mice. Our experimental data substantiate the observation of an increased NAFLD-risk associated with the human APOEε3 allele, while APOEε4 appears protective. The underlying mechanisms of the protection possibly involve a higher capacity of nonectopic lipid deposition in subcutaneous adipose tissue and lower hepatic pathogen recognition in the APOE4 mice.

Exploring the Usability of α-MSH-SM-Liposome as an Imaging Agent to Study Biodegradable Bone Implants In Vivo.

Novel biodegradable metal alloys are increasingly used as implant materials. The implantation can be accompanied by an inflammatory response to a foreign object. For studying inflammation in the implantation area, non-invasive imaging methods are needed. In vivo imaging for the implanted area and its surroundings will provide beneficiary information to understand implant-related inflammation and help to monitor it. Therefore, inflammation-sensitive fluorescent liposomes in rats were tested in the presence of an implant to evaluate their usability in studying inflammation. The sphingomyelin-containing liposomes carrying alpha-melanocyte-stimulating hormone (α-MSH)-peptide were tested in a rat bone implant model. The liposome interaction with implant material (Mg-10Gd) was analyzed with Mg-based implant material (Mg-10Gd) in vitro. The liposome uptake process was studied in the bone-marrow-derived macrophages in vitro. Finally, this liposomal tracer was tested in vivo. It was found that α-MSH coupled sphingomyelin-containing liposomes and the Mg-10Gd implant did not have any disturbing influence on each other. The clearance of liposomes was observed in the presence of an inert and biodegradable implant. The degradable Mg-10Gd was used as an alloy example; however, the presented imaging system offers a new possible use of α-MSH-SM-liposomes as tools for investigating implant responses.

Dual-Layer Spectral-Computed Tomography Enhances the Separability of Calcium-Based Implant Material from Bone: An Ex Vivo Quantitative Imaging Study.

Local treatment of bone loss with an injection of a resorbable, calcium-based implant material to replace bone has a long history of clinical use. The in vivo discrimination of changes in bone versus implant is challenging with standard computed tomography (CT). However, spectral-CT techniques enable the separation between tissues of similar densities but different chemical compositions. Dual-layer spectral-CT imaging and postprocessing analysis methods were applied to investigate the separability of AGN1 (a triphasic calcium-based implant) and bone after AGN1 injection in n = 10 male cadaveric femurs ex vivo. Using the area under the curve (AUC) from receiver-operating characteristic (ROC) analyses, the separability of AGN1 from bone was assessed for AGN1 (postoperatively) versus compact and versus femoral neck cancellous bone (both preoperatively). CT techniques included conventional Hounsfield (HU) and density-equivalent units (BMD, mg hydroxyapatite [HA]/cm3 ) and spectral-CT measures of effective atomic number (Zeff) and electron density (ED). The samples had a wide range of femoral neck BMD (55.66 to 241.71 mg HA/cm3 ). At the injection site average BMD, HU, Zeff, and ED increased from 69.5 mg HA/cm3 , 109 HU, 104.38 EDW, and 8.30 Zeff in the preoperative to 1233 mg HA/cm3 , 1741 HU, 181.27 EDW, and 13.55 Zeff in the postoperative CT scan, respectively. For compact bone at the femoral shaft the preoperative values were 1124.15 mg HA/cm3 , 1648 HU, 177 EDW, and 13.06 Zeff and were maintained postoperatively. Zeff showed substantially sharper distributions and significantly greater separability compared to ED, BMD, and HU (all p < 0.002, for both regions) with average AUCs for BMD, HU, ED, and Zeff of 0.670, 0.640, 0.645, and 0.753 for AGN1 versus compact and 0.996, 0.995, 0.994, and 0.998 for AGN1 versus femoral neck cancellous sites, respectively. Spectral-CT permits better discrimination of calcium-based implants like AGN1 from bone ex vivo. Our results warrant application of spectral-CT in patients undergoing procedures with similar implants. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Human tibial cortical bone with high porosity in type 2 diabetes mellitus is accompanied by distinctive bone material properties.

Diabetes mellitus is a metabolic disease affecting bone tissue at different length-scales. Higher fracture risk in diabetic patients is difficult to detect with common clinical fracture risk assessment due to normal or high bone mineral density in diabetic patients. The observed higher fracture risk despite normal to high areal bone mineral density in diabetic patients points towards impaired bone material quality. Here, we analyze tibial bone from individuals with type 2 diabetes mellitus using a multiscale-approach, which includes clinical and laboratory-based bone quality measures. Tibial cortical bone tissue from individuals with type 2 diabetes mellitus (T2DM) and age-matched healthy controls (n = 15 each) was analyzed with in situ impact indentation, dual energy X-ray absorptiometry (DXA), high resolution peripheral microcomputed tomography (HR-pQCT), micro-computed tomography (microCT), cyclic indentation, quantitative backscattered electron microscopy (qBEI), vibrational spectroscopy (Raman), nanoindentation, and fluorescence spectroscopy. With this approach, a high cortical porosity subgroup of individuals with T2DM was discriminated from two study groups: individuals with T2DM and individuals without T2DM, while both groups were associated with similar cortical porosity quantified by means of microCT. The high porosity T2DM group, but not the T2DM group, showed compromised bone quality expressed by altered cyclic indentation properties (transversal direction) in combination with a higher carbonate-to-amide I ratio in endocortical bone. In addition, in the T2DM group with high cortical porosity group, greater cortical pore diameter was identified with HR-pQCT and lower tissue mineral density using microCT, both compared to T2DM group. Micromechanical analyses of cross-sectioned osteons (longitudinal direction) with cyclic indentation, qBEI, and nanoindentation showed no differences between the three groups. High tibial cortical porosity in T2DM can be linked to locally altered bone material composition. As the tibia is an accessible skeletal site for fracture risk assessment in the clinics (CT, indentation), our findings may contribute to further understanding the site-specific structural and compositional factors forming the basis of bone quality in diabetes mellitus. Refined diagnostic strategies are needed for a comprehensive fracture risk assessment in diabetic bone disease.

Dose-efficient assessment of trabecular microstructure using ultra-high-resolution photon-counting CT.

Photon-counting (PC) detectors for clinical computed tomography (CT) may offer improved imaging capabilities compared to conventional energy-integrating (EI) detectors, e.g. superior spatial resolution and detective efficiency. We here investigate if PCCT can reduce the administered dose in examinations aimed at quantifying trabecular bone microstructure. Five human vertebral bodies were scanned three times in an abdomen phantom (QRM, Germany) using an experimental dual-source CT (Somatom CounT, Siemens Healthineers, Germany) housing an EI detector (0.60 mm pixel size at the iso-center) and a PC detector (0.25 mm pixel size). A tube voltage of 120 kV was used. Tube current-time product for EICT was 355 mAs (23.8 mGy CTDI32 cm). Dose-matched UHR-PCCT (UHRdm, 23.8 mGy) and noise-matched acquisitions (UHRnm, 10.5 mGy) were performed and reconstructed to a voxel size of 0.156 mm using a sharp kernel. Measurements of bone mineral density (BMD) and trabecular separation (Tb.Sp) and Tb.Sp percentiles reflecting the different scales of the trabecular interspacing were performed and compared to a gold-standard measurement using a peripheral CT device (XtremeCT, SCANCO Medical, Switzerland) with an isotropic voxel size of 0.082 mm and 6.6 mGy CTDI10 cm. The image noise was quantified and the relative error with respect to the gold-standard along with the agreement between CT protocols using Lin's concordance correlation coefficient (rCCC) were calculated. The Mean ±â€¯StdDev of the measured image noise levels in EICT was 109.6 ±â€¯3.9 HU. UHRdm acquisitions (same dose as EICT) showed a significantly lower noise level of 78.6 ±â€¯4.6 HU (p = 0.0122). UHRnm (44% dose of EICT) showed a noise level of 115.8 ±â€¯3.7 HU, very similar to EICT at the same spatial resolution. For BMD the overall Mean ±â€¯StdDev for EI, UHRdm and UHRnm were 114.8 ±â€¯28.6 mgHA/cm3, 121.6 ±â€¯28.8 mgHA/cm3 and 121.5 ±â€¯28.6 mgHA/cm3, respectively, compared to 123.1 ±â€¯25.5 mgHA/cm3 for XtremeCT. For Tb.Sp these values were 1.86 ±â€¯0.54 mm, 1.80 ±â€¯0.56 mm and 1.84 ±â€¯0.52 mm, respectively, compared to 1.66 ±â€¯0.48 mm for XtremeCT. The ranking of the vertebrae with regard to Tb.Sp data was maintained throughout all Tb.Sp percentiles and among the CT protocols and the gold-standard. The agreement between protocols was very good for all comparisons: UHRnm vs. EICT (BMD rCCC = 0.97; Tb.Sp rCCC = 0.998), UHRnm vs. UHRdm (BMD rCCC = 0.998; Tb.Sp rCCC = 0.993) and UHRdm vs. EICT (BMD rCCC = 0.97; Tb.Sp rCCC = 0.991). Consequently, the relative RMS-errors from linear regressions against the gold-standard for EICT, UHRdm and UHRnm were very similar for BMD (7.1%, 5.2% and 5.4%) and for Tb.Sp (3.3%, 3.3% and 2.9%), with a much lower radiation dose for UHRnm. Short-term reproducibility for BMD measurements was similar and below 0.2% for all protocols, but for Tb.Sp showed better results for UHR (about 1/3 of the level for EICT). In conclusion, CT with UHR-PC detectors demonstrated lower image noise and better reproducibility for assessments of bone microstructure at similar dose levels. For UHRnm, radiation exposure levels could be reduced by 56% without deterioration of performance levels in the assessment of bone mineral density and bone microstructure.

Dynamic in vivo monitoring of fracture healing process in response to magnesium implant with multimodal imaging: pilot longitudinal study in a rat external fixation model.

Rodent models are commonly used in pre-clinical research of magnesium (Mg)-based and other types of biomaterials for fracture treatment. Most studies selected unstable fixation methods, and there is a lack of multimodal longitudinal in vivo monitoring of bone healing. The purpose of this study is to develop a rat femoral fracture model stabilized by external fixation with intra-medullary Mg implant, and to investigate the dynamic bone union process with several imaging techniques offering complementing insights into the process. Pure Mg pins were prepared, followed by an in vitro degradation test. Male Sprague-Dawley rats in the experimental group underwent femoral osteotomy stabilized by external fixators with intra-medullary implantation of Mg pins, and the control group underwent external fixation without intra-medullary implants. Post-operative radiograph, micro-CT and B-mode ultrasonography were acquired directly after surgery, and re-examined at week 4, 8 and 12. Bone tissue volume, in vivo implant degradation, histological staining and MRI images were analyzed using ex vivo samples. Both groups achieved fracture union at week 12, and the dynamic healing process was illustrated by in vivo radiograph, micro-CT and ultrasonography. Bilateral whole femur ex vivo analysis further demonstrated increased ratio of bone tissue volume in the surgical femur with Mg implants, and in vivo degradation of Mg pins was slower than in vitro results. Titanium screws rather than intra-medullary Mg pins were the source of artifact in MRI. This pilot study showed the rat fracture model with external fixation and intra-medullary Mg implantation to be an effective method for dynamic in vivo monitoring of the bone healing process. Future application of the animal model may facilitate pre-clinical translational research of biodegradable orthopaedic implant materials for fracture treatment.