The Application of Digital Volume Correlation (DVC) to Evaluate Strain Predictions Generated by Finite Element Models of the Osteoarthritic Humeral Head

Measurement of bone damage caused by quasi-static compressive loading-unloading to explore dental implants stability: Simultaneous use of in-vitro tests, μ-CT images, and digital volume correlation

Primary stability of dental implants is the initial mechanical engagement of the implant with its adjacent bone. Implantation and the subsequent loading may cause mechanical damage in the peripheral bone, which ultimately reduces the stability of the implant. This study aimed at evaluating primary stability of dental implants through applying stepwise compressive displacement-controlled, loading-unloading cycles to obtain overall stiffness and dissipated energy of the bone-implant structure; and quantifying induced plastic strains in surrounding bone using digital volume correlation (DVC) method, through comparing μCT images in different loading steps. To this end, dental implants were inserted into the cylindrical trabecular bones, then the bone-implant structure was undergone step-wise loading-unloading cycles, and μCT images were taken in some particular steps, then comparison was made between undeformed and deformed configurations using DVC to quantify plastic strain within the trabecular bone. Comparing stiffness reduction and dissipated energy values in different loading steps, obtained from the force-displacement curve in each loading step, revealed that the maximum displacement of 0.16 mm can be deemed as a safe threshold above which damages in peri-implant bone started to increase considerably (p < 0.05). In addition, it was found here that peri-implant bone strain linearly increased with decreasing bone-implant stiffness (p < 0.05). Moreover, strain concentration in peri-implant bone region showed that the plastic strain in trabecular bone spread up to a distance of about 2.5 mm away from the implant surface. Research of this kind can be used to optimize the design of dental implants, with the ultimate goal of improving their stability, also to validate in-silico models, e.g., micro-finite element models, which can help gain a deeper understanding of bone-implant construct behavior.

Comparison of clinical-CT segmentation techniques for measuring subchondral bone cyst volume in glenohumeral osteoarthritis

PURPOSE

This study aimed to assess the accuracy and reproducibility of four common segmentation techniques measuring subchondral bone cyst volume in clinical-CT scans of glenohumeral OA patients.

METHODS

Ten humeral head osteotomies collected from cystic OA patients, having undergone total shoulder arthroplasty, were scanned within a micro-CT scanner, and corresponding preoperative clinical-CT scans were gathered. Cyst volumes were measured manually in micro-CT and served as a reference standard (n = 13). Respective cyst volumes were measured on the clinical-CT scans by two independent graders using four segmentation techniques: Qualitative, Edge Detection, Region Growing, and Thresholding. Cyst volume measured in micro-CT was compared to the different clinical-CT techniques using linear regression and Bland-Altman analysis. Reproducibility of each technique was assessed using intraclass correlation coefficient (ICC).

RESULTS

Each technique outputted lower volumes on average than the reference standard (-0.24 to -3.99 mm³). All linear regression slopes and intercepts were not significantly different than 1 and 0, respectively (p < 0.05). Cyst volumes measured using Qualitative and Edge Detection techniques had the highest overall agreement with reference micro-CT volumes (mean discrepancy: 0.24, 0.92 mm³). These techniques showed good to excellent reproducibility between graders.

CONCLUSIONS

Qualitative and Edge Detection techniques were found to accurately and reproducibly measure subchondral cyst volume in clinical-CT. These findings provide evidence that clinical-CT may accurately gauge glenohumeral cystic presence, which may be useful for disease monitoring and preoperative planning.

LEVEL OF EVIDENCE

Retrospective cohort Level 3 study.

Osteoarthritis year in review 2021: mechanics

Osteoarthritis (OA) has a complex, heterogeneous and only partly understood etiology. There is a definite role of joint cartilage pathomechanics in originating and progressing of the disease. Although it is still not identified precisely enough to design or select targeted treatments, the progress of this year's research demonstrates that this goal became much closer. On multiple scales - tissue, joint and whole body - an increasing number of studies were done, with impressive results. (1) Technology based instrument innovations, especially when combined with machine learning models, have broadened the applicability of biomechanics. (2) Combinations with imaging make biomechanics much more precise & personalized. (3) The combination of Musculoskeletal & Finite Element Models yield valid personalized cartilage loads. (4) Mechanical outcomes are becoming increasingly meaningful to inform and evaluate treatments, including predictive power from biomechanical models. Since most recent advancements in the field of biomechanics in OA are at the level of a proof op principle, future research should not only continue on this successful path of innovation, but also aim to develop clinical workflows that would facilitate including precision biomechanics in large scale studies. Eventually this will yield clinical tools for decision making and a rationale for new therapies in OA.

Digital volume correlation for the characterization of musculoskeletal tissues: Current challenges and future developments

Biological tissues are complex hierarchical materials, difficult to characterise due to the challenges associated to the separation of scale and heterogeneity of the mechanical properties at different dimensional levels. The Digital Volume Correlation approach is the only image-based experimental approach that can accurately measure internal strain field within biological tissues under complex loading scenarios. In this minireview examples of DVC applications to study the deformation of musculoskeletal tissues at different dimensional scales are reported, highlighting the potential and challenges of this relatively new technique. The manuscript aims at reporting the wide breath of DVC applications in the past 2 decades and discuss future perspective for this unique technique, including fast analysis, applications on soft tissues, high precision approaches, and clinical applications.

3D strain analysis of trabecular bone within the osteoarthritic humeral head subjected to stepwise compressive loads

Understanding the local mechanical properties of trabecular bone at the humeral head-neck junction is essential for the safe design of stemless humeral head implants. Recent advancements in mechanical testing coupled with volumetric imaging have allowed for the ability to quantify full-field strain distributions throughout trabecular bone. Within this study, digital volume correlation (DVC) was applied to micro-computed tomography images to investigate the local load carrying characteristics of trabecular bone within osteoarthritic (OA) humeral heads subjected to stepwise loading. A multi-pegged indenter was used to transfer loads from a custom-fabricated loading apparatus to trabecular bone on the resection surface of OA humeral head osteotomies retrieved from patients undergoing total shoulder arthroplasty (TSA). In regions of trabecular bone that eventually fractured, third principal strains were significantly higher (95^th percentile third principal strain = -12,558 μstrain, p < 0.001) compared to regions that did not fracture (95^th percentile third principal strain = -7,806 μstrain). As well, bone volume fraction (p = 0.012), trabecular separation (p = 0.014), and trabecular number (p = 0.007) were found to influence the likelihood of trabecular bone fracture. Collectively, this work has led to a deeper understanding of the local load carrying characteristics of trabecular bone specific to patients receiving TSA for osteoarthritis.

A novel approach to evaluate the effects of artificial bone focal lesion on the three-dimensional strain distributions within the vertebral body

The spine is the first site for incidence of bone metastasis. Thus, the vertebrae have a high potential risk of being weakened by metastatic tissues. The evaluation of strength of the bone affected by the presence of metastases is fundamental to assess the fracture risk. This work proposes a robust method to evaluate the variations of strain distributions due to artificial lesions within the vertebral body, based on in situ mechanical testing and digital volume correlation. Five porcine vertebrae were tested in compression up to 6500N inside a micro computed tomography scanner. For each specimen, images were acquired before and after the application of the load, before and after the introduction of the artificial lesions. Principal strains were computed within the bone by means of digital volume correlation (DVC). All intact specimens showed a consistent strain distribution, with peak minimum principal strain in the range -1.8% to -0.7% in the middle of the vertebra, demonstrating the robustness of the method. Similar distributions of strains were found for the intact vertebrae in the different regions. The artificial lesion generally doubled the strain in the middle portion of the specimen, probably due to stress concentrations close to the defect. In conclusion, a robust method to evaluate the redistribution of the strain due to artificial lesions within the vertebral body was developed and will be used in the future to improve current clinical assessment of fracture risk in metastatic spines.

Full-field comparisons between strains predicted by QCT-derived finite element models of the scapula and experimental strains measured by digital volume correlation

Subject-specific finite element models (FEMs) of the shoulder can be used to evaluate joint replacement designs preclinically. However, to ensure accurate conclusions are drawn, experimental validation is critical. The objective of the current study was to evaluate the accuracy of strain predictions generated by subject-specific scapula FEMs through comparisons against full-field experimental strains measured using digital volume correlation (DVC). Three cadaveric scapulae were mechanically loaded using a custom-hexapod robot within a micro-CT scanner. BoneDVC was used to quantify resultant experimental full-field strains. Scapula FEMs were generated using three different density-modulus relationships to assign material properties. Two types of boundary conditions (BCs) were simulated: DVC-displacement-driven or applied-force-driven. Third principal strains were compared between the DVC measurements and FEM predictions. With applied-force BCs, poor agreement was observed between the predicted and measured strains (slope range: 0.16-0.19, r² range: 0.04-0.30). Agreement was improved with the use of DVC-displacement BCs (slope range: 0.54-0.59, r² range: 0.73-0.75). Strain predictions were independent of the density-modulus relationship used for DVC-displacement BCs, but differences were observed in the correlation coefficient and intercept for applied-force BCs. Overall, this study utilized full-field DVC-derived experimental strains for comparison with FEM predicted strains in models with varying material properties and BCs. It was found that fair agreement can be achieved in localized strain measurements between DVC measurements and FEM predictions when DVC-displacement BCs are used. However, performance suffered with use of applied-force BCs.