Restoration of Stiffness During Fracture Healing at the Distal Radius, Using HR-pQCT and Finite Element Methods

Finite Element Modeling of the Human Wrist: A Review

Background  Understanding wrist biomechanics is important to appreciate and treat the wrist joint. Numerical methods, specifically, finite element method (FEM), have been used to overcome experimental methods' limitations. Due to the complexity of the wrist and difficulty in modeling, there is heterogeneity and lack of consistent methodology in the published studies, challenging our ability to incorporate information gleaned from the various studies. Questions/Purposes  This study summarizes the use of FEM to study the wrist in the last decade. Methods  We included studies published from 2012 to 2022 from databases: EBSCO, Research4Life, ScienceDirect, and Scopus. Twenty-two studies were included. Results  FEM used to study wrist in general, pathology, and treatment include diverse topics and are difficult to compare directly. Most studies evaluate normal wrist mechanics, all modeling the bones, with fewer studies including cartilage and ligamentous structures in the model. The dynamic effect of the tendons on wrist mechanics is rarely accounted for. Conclusion  Due to the complexity of wrist mechanics, the current literature remains incomplete. Considering published strategies and modeling techniques may aid in the development of more comprehensive and improved wrist model fidelity.

A multi-stack registration technique to improve measurement accuracy and precision across longitudinal HR-pQCT scans

BACKGROUND

Recent applications of high-resolution peripheral quantitative computed tomography (HR-pQCT) have demonstrated that changes in local bone remodelling can be quantified in vivo using longitudinal three-dimensional image registration. However, certain emerging applications, such as fracture healing and joint analysis, require larger multi-stack scan regions that can result in stack shift image artifacts. These artifacts can be detrimental to the accurate alignment of the bone structure across multiple timepoints. The purpose of this study was to establish a multi-stack registration protocol for evaluating longitudinal HR-pQCT images and to assess the accuracy and precision error in comparison with measures obtained using previously established three-dimensional longitudinal registration.

METHODS

Three same day multi-stack HR-pQCT scans of the radius (2 stacks in length) and tibia (3 stacks in length) were obtained from 39 healthy individuals who participated in a previous reproducibility study. A fully automated multi-stack registration algorithm was developed to re-align stacks within a scan by leveraging slight offsets between longitudinal scans. Stack shift severity before and after registration was quantified using a newly proposed stack-shift severity score. The false discovery rate for bone remodelling events and precision error of bone morphology and micro-finite element analysis parameters were compared between longitudinally registered scans with and without the addition of multi-stack registration.

RESULTS

Most scans (82 %) improved in stack alignment or maintained the lowest stack shift severity score when multi-stack registration was implemented. The false discovery rate of bone remodelling events significantly decreased after multi-stack registration, resulting in median false detection of bone formation and resorption fractions between 3.2 to 7.5 % at the radius and 3.4 to 5.3 % at the tibia. Further, precision error was significantly reduced or remained unchanged in all standard bone morphology and micro-finite element analysis parameters, except for total and trabecular cross-sectional areas.

CONCLUSION

Multi-stack registration is an effective strategy for accurately aligning multi-stack HR-pQCT scans without modification of the image acquisition protocol. The algorithm presented here is a viable approach for performing accurate morphological analysis on multi-stack HR-pQCT scans, particularly for advanced application investigating local bone remodelling in vivo.

The contribution of lower-mineralized tissue to the healing of distal radius fractures assessed using HR-pQCT

High-resolution peripheral quantitative CT (HR-pQCT) enables quantitative assessment of distal radius fracture healing. In previous studies, lower-mineralized tissue formation was observed on HR-pQCT scans, starting early during healing, but the contribution of this tissue to the stiffness of distal radius fractures is unknown. Therefore, the aim of this study was to investigate the contribution of lower-mineralized tissue to the stiffness of fractured distal radii during the first twelve weeks of healing. We did so by combining the results from two series of micro-finite element (μFE-) models obtained using different density thresholds for bone segmentation. Forty-five postmenopausal women with a conservatively-treated distal radius fracture had HR-pQCT scans of their fractured radius at baseline (BL; 1-2 weeks post-fracture), 3-4 weeks, 6-8 weeks, and 12 weeks post-fracture. Compression stiffness (S) was computed using two series of μFE-models from the scans: one series (Msingle) included only higher-mineralized tissue (>320 mg HA/cm3), and one series (Mdual) differentiated between lower-mineralized tissue (200-320 mg HA/cm3) and higher-mineralized tissue. μFE-elements were assigned a Young's Modulus of 10 GPa (higher-mineralized tissue) or 5 GPa (lower-mineralized tissue), and an axial compression test to 1 % strain was simulated. The contribution of the lower-mineralized tissue to S was quantified as the ratio Sdual/Ssingle. Changes during healing were quantified using linear mixed effects models and expressed as estimated marginal means (EMMs) with 95 %-confidence intervals (95 %-CI). Median time to cast removal was 5.0 (IQR: 1.1) weeks. Sdual and Ssingle gradually increased during healing to a significantly higher value than BL at 12 weeks post-fracture (both p < 0.0001). In contrast, Sdual/Ssingle was significantly higher than BL at 3-4 weeks post-fracture (p = 0.0010), remained significantly higher at 6-8 weeks post-fracture (p < 0.0001), and then decreased to BL-values at the 12-week visit. EMMs ranged between 1.05 (95 %-CI: 1.04-1.06) and 1.08 (95 %-CI: 1.07-1.10). To conclude, combining stiffness results from two series of μFE-models obtained using single- and dual-threshold segmentation enables quantification of the contribution of lower-mineralized tissue to the stiffness of distal radius fractures during healing. This contribution is minor but changes significantly around the time of cast removal. Its course and timing during healing may be clinically relevant. Quantification of the contribution of lower-mineralized tissue to stiffness gives a more complete impression of strength recovery post-fracture than the evaluation of stiffness using a single series of μFE-models.

Improvements in radiographic and clinical assessment of distal radius fracture healing by FE-estimated bone stiffness

Bone strength determined from finite element (FE) modelling provides an estimate of fracture healing progression following a distal radius fracture (DRF), but how these measures relate to patient-reported outcomes and functional outcomes remains unknown. We hypothesized that changes in bone stiffness and bone mineral density measured using high-resolution peripheral quantitative computed tomography (HR-pQCT) are associated with clinically available measures of functional and patient-reported outcomes. We also aimed to identify which clinical outcome measures best predict fracture stiffness and could therefore be used to inform cast removal.

Participants (n = 30) with stable distal radius fractures were followed for two week intervals from the time of fracture until two months post-fracture, then at three months and six months post-fracture. At each follow-up, participants underwent clinical, radiographic, and functional assessments, as well as had their fractured wrist scanned using HR-pQCT. Recovery of bone stiffness during fracture healing was determined from micro-FE (μFE) models generated from HR-pQCT image data.

During the DRF healing process, significant longitudinal changes were found in μFE-estimated stiffness, patient-reported outcomes, grip strength, range of motion (ROM), tenderness, number of cortices healed based on radiographs, and fracture line visibility (p < 0.05); however, no significant change was detected in HR-pQCT based total bone mineral density. Patient-reported outcomes, such as the Patient-Rated Wrist Evaluation (PRWE) and the Quick Disability of the Arm, Shoulder and Hand (QuickDASH) questionnaire, correlated strongly with μFE-estimated stiffness (0.61 ≥ r_m ≥ 0.66). Based on μFE-estimated stiffness, PRWE and QuickDASH are the best predictors of stiffness recovery (p < 0.05) and may be used to guide duration of cast immobilization in the clinical setting.

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Recovery of fracture stiffness may inform time required for cast immobilization.

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Patient reported outcomes predict rate of fracture stiffness recovery.

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Radiographic outcomes correlate weakly with fracture stiffness.

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Patient reported outcomes may inform duration of cast immobilization.