CT required to perform robotic-assisted total hip arthroplasty can identify previously undiagnosed osteoporosis and guide femoral fixation strategy

Employing single-cell RNA sequencing coupled with an array of bioinformatics approaches to ascertain the shared genetic characteristics between osteoporosis and obesity

Aims

This study examined the relationship between obesity (OB) and osteoporosis (OP), aiming to identify shared genetic markers and molecular mechanisms to facilitate the development of therapies that target both conditions simultaneously.

Methods

Using weighted gene co-expression network analysis (WGCNA), we analyzed datasets from the Gene Expression Omnibus (GEO) database to identify co-expressed gene modules in OB and OP. These modules underwent Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and protein-protein interaction analysis to discover Hub genes. Machine learning refined the gene selection, with further validation using additional datasets. Single-cell analysis emphasized specific cell subpopulations, and enzyme-linked immunosorbent assay (ELISA), protein blotting, and cellular staining were used to investigate key genes.

Results

WGCNA revealed critical gene modules for OB and OP, identifying the Toll-like receptor (TLR) signalling pathway as a common factor. TLR2 was the most significant gene, with a pronounced expression in macrophages. Elevated TLR2 expression correlated with increased adipose accumulation, inflammation, and osteoclast differentiation, linking it to OP development.

Conclusion

Our study underscores the pivotal role of TLR2 in connecting OP and OB. It highlights the influence of TLR2 in macrophages, driving both diseases through a pro-inflammatory mechanism. These insights propose TLR2 as a potential dual therapeutic target for treating OP and OB.

A comprehensive predictive model for postoperative joint function in robot-assisted total hip arthroplasty patients: combining radiomics and clinical indicators

Total hip arthroplasty (THA) effectively treats various end-stage hip conditions, offering pain relief and improved joint function. However, surgical outcomes are influenced by multifaceted factors. This research aims to create a predictive model, incorporating radiomic and clinical information, to forecast post-surgery joint function in robot-assisted THA (RA-THA) patients. The study set comprised 136 patients who underwent unilateral RA-THA, which were subsequently partitioned into a training set (n = 95) and a test set (n = 41) for analysis. Preoperative CT imaging was employed to derive 851 radiomic characteristics, selecting those with an intra-class correlation coefficient > 0.75 for analysis. Least absolute shrinkage and selection operator regression reduced redundancy to six significant radiomic features. Clinical data including preoperative Visual Analog Scale (VAS), Harris Hip Score (HHS), and Western Ontario and McMaster University Osteoarthritis Index (WOMAC) score were collected. Logistic regression identified significant predictors, and three models were developed. Receiver operating characteristic and decision curves evaluated the models. Preoperative VAS, HHS, WOMAC score, and radiomics feature scores were significant predictors. In the training set, the AUCs were 0.835 (clinical model), 0.757 (radiomic model), and 0.891 (combined model). In the test set, the AUCs were 0.777 (clinical model), 0.824 (radiomic model), and 0.881 (combined model). The constructed nomogram prediction model combines radiological features with relevant clinical data to accurately predict functional outcomes 3 years after RA-THA. This model has significant prediction accuracy and broad clinical application prospects and can provide a valuable reference for formulating personalized treatment plans and optimizing patient management strategies.

The current role of CT in total knee arthroplasty

Advanced 3D imaging and CT-based navigation have emerged as valuable tools to use in total knee arthroplasty (TKA), for both preoperative planning and the intraoperative execution of different philosophies of alignment. Preoperative planning using CT-based 3D imaging enables more accurate prediction of the size of components, enhancing surgical workflow and optimizing the precision of the positioning of components. Surgeons can assess alignment, osteophytes, and arthritic changes better. These scans provide improved insights into the patellofemoral joint and facilitate tibial sizing and the evaluation of implant-bone contact area in cementless TKA. Preoperative CT imaging is also required for the development of patient-specific instrumentation cutting guides, aiming to reduce intraoperative blood loss and improve the surgical technique in complex cases. Intraoperative CT-based navigation and haptic guidance facilitates precise execution of the preoperative plan, aiming for optimal positioning of the components and accurate alignment, as determined by the surgeon's philosophy. It also helps reduce iatrogenic injury to the periarticular soft-tissue structures with subsequent reduction in the local and systemic inflammatory response, enhancing early outcomes. Despite the increased costs and radiation exposure associated with CT-based navigation, these many benefits have facilitated the adoption of imaged based robotic surgery into routine practice. Further research on ultra-low-dose CT scans and exploration of the possible translation of the use of 3D imaging into improved clinical outcomes are required to justify its broader implementation.

Guanylate cyclase promotes osseointegration by inhibiting oxidative stress and inflammation in aged rats with iron overload

Aims

This study intended to investigate the effect of vericiguat (VIT) on titanium rod osseointegration in aged rats with iron overload, and also explore the role of VIT in osteoblast and osteoclast differentiation.

Methods

In this study, 60 rats were included in a titanium rod implantation model and underwent subsequent guanylate cyclase treatment. Imaging, histology, and biomechanics were used to evaluate the osseointegration of rats in each group. First, the impact of VIT on bone integration in aged rats with iron overload was investigated. Subsequently, VIT was employed to modulate the differentiation of MC3T3-E1 cells and RAW264.7 cells under conditions of iron overload.

Results

Utilizing an OVX rat model, we observed significant alterations in bone mass and osseointegration due to VIT administration in aged rats with iron overload. The observed effects were concomitant with reductions in bone metabolism, oxidative stress, and inflammation. To elucidate whether these effects are associated with osteoclast and osteoblast activity, we conducted in vitro experiments using MC3T3-E1 cells and RAW264.7 cells. Our findings indicate that iron accumulation suppressed the activity of MC3T3-E1 while enhancing RAW264.7 function. Furthermore, iron overload significantly decreased oxidative stress levels; however, these detrimental effects can be mitigated by VIT treatment.

Conclusion

Collectively, our data provide compelling evidence that VIT has the potential to reverse the deleterious consequences of iron overload on osseointegration and bone mass during ageing.

Osteoporotic Patients Undergoing Total Hip Arthroplasty Have a Similar 5-Year Cumulative Incidence Rate of Periprosthetic Fracture Regardless of Cemented Versus Cementless Femoral Stem Fixation

BACKGROUND

In osteoporotic patients, surgeons may utilize cemented femoral fixation to minimize risk of fracture. The purpose of this study was to compare 5-year implant survivability in patients who have osteoporosis who underwent elective total hip arthroplasty (THA) with cementless versus cemented fixation.

METHODS

A retrospective analysis of patients who have osteoporosis undergoing THA with either cemented or cementless femoral fixation was conducted using a national administrative claims database. Of the 18,431 identified THA patients who have osteoporosis, 15,867 (86.1%) underwent cementless fixation. The primary outcome was a comparison of the 5-year cumulative incidences of aseptic revision, mechanical loosening, and periprosthetic fracture (PPF). Kaplan-Meier and Multivariable Cox Proportional Hazard Ratio analyses were used, controlling for femoral fixation method, age, sex, a comorbidity scale, use of osteoporosis medication, and important comorbidity.

RESULTS

There was no difference in aseptic revision (Hazard's Ratio (HR): 1.13; 95% Confidence Interval (CI): 0.79 to 1.62; P value: .500) and PPF (HR: 0.96; 95% CI: 0.64 to 1.44; P value: .858) within 5 years of THA between fixation cohorts. However, patients who had cemented fixation were more likely to suffer mechanical loosening with 5 years post-THA (HR: 1.79; 95% CI: 1.17 to 2.71; P-value: .007).

CONCLUSIONS

We found a similar 5-year rate of PPF when comparing patients who underwent cementless versus cemented femoral fixation for elective THA regardless of preoperative diagnosis of osteoporosis. While existing registry data support the use of cemented fixation in elderly patients, a more thorough understanding of the interplay between age, osteoporosis, and implant design is needed to delineate in whom cemented fixation is most warranted for PPF prevention.

Accuracy of femoral component anteversion in robotic total hip arthroplasty

Aims

Femoral component anteversion is an important factor in the success of total hip arthroplasty (THA). This retrospective study aimed to investigate the accuracy of femoral component anteversion with the Mako THA system and software using the Exeter cemented femoral component, compared to the Accolade II cementless femoral component.

Methods

We reviewed the data of 30 hips from 24 patients who underwent THA using the posterior approach with Exeter femoral components, and 30 hips from 24 patients with Accolade II components. Both groups did not differ significantly in age, sex, BMI, bone quality, or disease. Two weeks postoperatively, CT images were obtained to measure acetabular and femoral component anteversion.

Results

The mean difference in femoral component anteversion between intraoperative and postoperative CT measurements (system accuracy of component anteversion) was 0.8° (SD 1.8°) in the Exeter group and 2.1° (SD 2.3°) in the Accolade II group, respectively (p = 0.020). The mean difference in anteversion between the plan and the postoperative CT measurements (clinical accuracy of femoral component anteversion) was 1.2° (SD 3.6°) in the Exeter group, and 4.2° (SD 3.9°) in the Accolade II group (p = 0.003). No significant differences were found in acetabular component inclination and anteversion; however, the clinical accuracy of combined anteversion was significantly better in the Exeter group (0.6° (SD 3.9°)) than the Accolade II group (3.6° (SD 4.1°)).

Conclusion

The Mako THA system and software helps surgeons control the femoral component anteversion to achieve the target angle of insertion. The Exeter femoral component, inserted using Mako THA system, showed greater precision for femoral component and combined component anteversion than the Accolade II component.

The Value of Computed Tomography Scan in Three-dimensional Planning and Intraoperative Navigation in Primary Total Hip Arthroplasty

Total hip arthroplasty (THA) is a frequently performed procedure; the objective is restoration of native hip biomechanics and achieving functional range of motion (ROM) through precise positioning of the prosthetic components. Advanced three-dimensional (3D) imaging and computed tomography (CT)-based navigation are valuable tools in both the preoperative planning and intraoperative execution. The aim of this study is to provide a thorough overview on the applications of CT scans in both the preoperative and intraoperative settings of primary THA. Preoperative planning using CT-based 3D imaging enables greater accuracy in prediction of implant sizes, leading to enhancement of surgical workflow with optimization of implant inventory. Surgeons can perform a more thorough assessment of posterior and anterior acetabular wall coverage, acetabular osteophytes, anatomical landmarks, and thus achieve more functional implant positioning. Intraoperative CT-based navigation can facilitate precise execution of the preoperative plan, to attain optimal positioning of the prosthetic components to avoid impingement. Medial reaming can be minimized preserving native bone stock, which can enable restoration of femoral, acetabular, and combined offsets. In addition, it is associated with greater accuracy in leg length adjustment, a critical factor in patients' postoperative satisfaction. Despite the higher costs and radiation exposure, which currently limits its widespread adoption, it offers many benefits, and the increasing interest in robotic surgery has facilitated its integration into routine practice. Conducting additional research on ultra-low-dose CT scans and examining the potential for translation of 3D imaging into improved clinical outcomes will be necessary to warrant its expanded application.

Accuracy of Preoperative 3D vs 2D Digital Templating for Cementless Total Hip Arthroplasty Using a Direct Anterior Approach

Background

An important aspect of preoperative planning for total hip arthroplasty is templating. Although two-dimensional (2D) templating remains the gold standard, computerized tomography (CT)-based three-dimensional (3D) templating is a novel preoperative planning technique. This study aims to compare the accuracy of a 2D and 3D plan using an anterior approach for the placement of the same uncemented prosthesis.

Methods

Two consecutive cohorts of 100 patients each were retrospectively analyzed. We analyzed the accuracy of the size of the implant (stem, cup, head), the length of head, and offset. As a secondary criterion, we analyzed the rates of stems with more than 3° of varus, fracture, and/or subsidence at 3 months postoperatively.

Results

Within the exact size, the accuracy of the stem and cup size with the 2D plan was 69% and 56%, respectively. With the 3D plan accuracy being 88% (P = .0046) and 96% (P < .0001), respectively. Regarding size and length of the implant head, accuracy was 86% and 82% with the 2D plan and 100% (P < .0001) and 94% (P = .016), respectively, with the 3D plan. The offset of the implants increased beyond 3 mm in 23% of patients in the 2D group and in 5% of patients in the 3D group (P = .0003). The rate of varus stems was 10% in the 2D group and 2% in the 3D group (P = .03). Two fractures and one case of subsidence occurred in the 2D group. None were identified in the 3D cohort.

Conclusions

A CT-based 3D plan is more accurate for implant size selection, allows better prosthetic offset, and reduces the rate of varus stems.

Interleukin-19 promotes bone resorption by suppressing osteoprotegerin expression in BMSCs in a lipopolysaccharide-induced bone loss mouse model

Aims

Osteoporosis is characterized by decreased trabecular bone volume, and microarchitectural deterioration in the medullary cavity. Interleukin-19 (IL-19), a member of the IL-10 family, is an anti-inflammatory cytokine produced primarily by macrophages. The aim of our study was to investigate the effect of IL-19 on osteoporosis.

Methods

Blood and femoral bone marrow suspension IL-19 levels were first measured in the lipopolysaccharide (LPS)-induced bone loss model. Small interfering RNA (siRNA) was applied to knock down IL-19 for further validation. Thereafter, osteoclast production was stimulated with IL-19 in combination with mouse macrophage colony-stimulating factor (M-CSF) and receptor activator of nuclear factor-κB ligand (RANKL). The effect of IL-19 was subsequently evaluated using tartrate-resistant acid phosphatase (TRAP) staining and quantitative real-time polymerase chain reaction (RT-qPCR). The effect of IL-19 on osteoprotegerin (OPG) was then assessed using in vitro recombinant IL-19 treatment of primary osteoblasts and MLO-Y4 osteoblast cell line. Finally, transient transfection experiments and chromatin immunoprecipitation (ChIP) experiments were used to examine the exact mechanism of action.

Results

In the LPS-induced bone loss mouse model, the levels of IL-19 in peripheral blood serum and femoral bone marrow suspension were significantly increased. The in vivo results indicated that global IL-19 deletion had no significant effect on RANKL content in the serum and bone marrow, but could increase the content of OPG in serum and femoral bone marrow, suggesting that IL-19 inhibits OPG expression in bone marrow mesenchymal stem cells (BMSCs) and thus increases bone resorption.

Conclusion

IL-19 promotes bone resorption by suppressing OPG expression in BMSCs in a LPS-induced bone loss mouse model, which highlights the potential benefits and side effects of IL-19 for future clinical applications.

Unveiling Osteoporosis Through Radiomics Analysis of Hip CT Imaging

RATIONALE AND OBJECTIVES

This study aims to investigate the use of radiomics analysis of hip CT imaging to unveil osteoporosis.

MATERIALS AND METHODS

The researchers analyzed hip CT scans from a cohort of patients, including both osteoporotic and healthy individuals. Radiomics technique are employed to extract a comprehensive array of features from these images, encompassing texture, shape, and intensity alterations. Radiomics analysis using the 10 most commonly used machine learning models was employed to identify screened radiomics features for the detection of osteoporosis in patients. In addition to radiomics features, the basic information of patients is also utilized as training data for these machine learning models to accurately identify the presence of osteoporosis. A comparison would be made between the efficiency of recognizing radiomics features and the efficiency of recognizing patient basic information. The machine learning model that achieves the highest performance would be chosen to integrate patient basic information and radiomics features for the development of clinical nomograms.

RESULT

After a thorough screening process, 16 radiomics features were selected as input parameters for the machine learning model. In the test group, the highest accuracy achieved using radiomics features was 0.849, with an area under the curve (AUC) of 0.919. Evaluation of clinical features identified age and gender as closely associated with osteoporosis. Among these features, the KNN model exhibited the highest accuracy of 0.731 and an AUC of 0.658 in the test group. Comparing the performance of radiomics and clinical features, radiomics features demonstrated superior AUC values in the machine learning models. Ultimately, the XGBoost model, utilizing both radiomics and clinical features, was selected as the final Nomogram prediction model. In the test group, this model achieved an accuracy of 0.882 and an AUC of 0.886 in screening for osteoporosis.

CONCLUSION

Radiomics features derived from hip CT scans exhibit strong screening capabilities for osteoporosis. Furthermore, when combined with easily obtainable clinical features like patient age and gender, an effective screening efficacy for osteoporosis can be achieved.

Development and validation of an open-source tool for opportunistic screening of osteoporosis from hip CT images

Aims

This study aimed to develop and validate a fully automated system that quantifies proximal femoral bone mineral density (BMD) from CT images.

Methods

The study analyzed 978 pairs of hip CT and dual-energy X-ray absorptiometry (DXA) measurements of the proximal femur (DXA-BMD) collected from three institutions. From the CT images, the femur and a calibration phantom were automatically segmented using previously trained deep-learning models. The Hounsfield units of each voxel were converted into density (mg/cm3). Then, a deep-learning model trained by manual landmark selection of 315 cases was developed to select the landmarks at the proximal femur to rotate the CT volume to the neutral position. Finally, the CT volume of the femur was projected onto the coronal plane, and the areal BMD of the proximal femur (CT-aBMD) was quantified. CT-aBMD correlated to DXA-BMD, and a receiver operating characteristic (ROC) analysis quantified the accuracy in diagnosing osteoporosis.

Results

CT-aBMD was successfully measured in 976/978 hips (99.8%). A significant correlation was found between CT-aBMD and DXA-BMD (r = 0.941; p < 0.001). In the ROC analysis, the area under the curve to diagnose osteoporosis was 0.976. The diagnostic sensitivity and specificity were 88.9% and 96%, respectively, with the cutoff set at 0.625 g/cm2.

Conclusion

Accurate DXA-BMD measurements and diagnosis of osteoporosis were performed from CT images using the system developed herein. As the models are open-source, clinicians can use the proposed system to screen osteoporosis and determine the surgical strategy for hip surgery.