Simulated lesions representative of metastatic disease predict proximal femur failure strength more accurately than idealized lesions

Finite Element Model-Computed Mechanical Behavior of Femurs with Metastatic Disease Varies Between Physiologic and Idealized Loading Simulations

Background and objectives:

Femurs affected by metastatic bone disease (MBD) frequently undergo surgery to prevent impending pathologic fractures due to clinician-perceived increases in fracture risk. Finite element (FE) models can provide more objective assessments of fracture risk. However, FE models of femurs with MBD have implemented strain- and strength-based estimates of fracture risk under a wide variety of loading configurations, and “physiologic” loading models typically simulate a single abductor force. Due to these variations, it is currently difficult to interpret mechanical fracture risk results across studies of femoral MBD. Our aims were to evaluate (1) differences in mechanical behavior between idealized loading configurations and those incorporating physiologic muscle forces, and (2) differences in the rankings of mechanical behavior between different loading configurations, in FE simulations to predict fracture risk in femurs with MBD.

Methods:

We evaluated 9 different patient-specific FE loading simulations for a cohort of 54 MBD femurs: strain outcome simulations—physiologic (normal walking [NW], stair ascent [SA], stumbling), and joint contact only (NW contact force, excluding muscle forces); strength outcome simulations—physiologic (NW, SA), joint contact only, offset torsion, and sideways fall. Tensile principal strain and femur strength were compared between simulations using statistical analyses.

Results:

Tensile principal strain was 26% higher ( R2 = 0.719, P < .001) and femur strength was 4% lower ( R2 = 0.984, P < .001) in simulations excluding physiologic muscle forces. Rankings of the mechanical predictions were correlated between the strain outcome simulations (ρ = 0.723 to 0.990, P < .001), and between strength outcome simulations (ρ = 0.524 to 0.984, P < .001).

Conclusions:

Overall, simulations incorporating physiologic muscle forces affected local strain outcomes more than global strength outcomes. Absolute values of strain and strength computed using idealized (no muscle forces) and physiologic loading configurations should be used within the appropriate context when interpreting fracture risk in femurs with MBD.

Finite element analysis potentially identifies nonessential prophylactic stabilization in femurs with metastatic disease

Metastatic bone disease (MBD) is often managed by non-specialized orthopedic surgeons who rely on Mirels’ criteria to predict pathologic fracture risk. However, low specificity of Mirels’ criteria implies many lesions are scored at high fracture risk when the actual mechanical fracture risk is minimal. Our goal was to retrospectively compare mechanical fracture risk in MBD patients to Mirels’ score and clinical treatment received. Using a CT-based finite element (FE) model of the proximal femur affected by MBD, femur strength and load-to-strength ratio (LSR) were determined for 52 femurs from 48 patients. Associations of femur strength with pain and Mirels’ scores (Pearson r/Spearman ρ correlations), and the decision to operate (percentile analysis), and associations of LSR with pain and Mirels’ scores (Spearman correlations) were determined. Nineteen of 52 femurs (37%) had a very low computed mechanical fracture risk (LSR < 0.4); 5 of those 19 underwent prophylactic stabilization, suggesting that clinical decision-making in MBD is substantially influenced by non-mechanical factors that likely overestimate pathologic fracture risk. Of the 30 femurs managed non-operatively, 24 had a low computed mechanical fracture risk (LSR ≤ 0.5), none of which (0%) experienced a fracture within 9 months. Patient-reported pain did not correlate with femur strength ( r = −0.05, p = 0.748) nor with LSR (ρ = 0.07, p = 0.632). Mirels’ score correlated weakly with femur strength (ρ = −0.32, p = 0.019) and with LSR (ρ = 0.29, p = 0.034). Computational mechanical tools like this FE model could be used as a clinical decision aid when considering non-surgical management in appropriate patients, potentially alleviating nonessential surgical treatment in some patients with femur MBD.

Fracture Risk Evaluation of Bone Metastases: A Burning Issue

Major progress has been achieved to treat cancer patients and survival has improved considerably, even for stage-IV bone metastatic patients. Locomotive health has become a crucial issue for patient autonomy and quality of life. The centerpiece of the reflection lies in the fracture risk evaluation of bone metastasis to guide physician decision regarding physical activity, antiresorptive agent prescription, and local intervention by radiotherapy, surgery, and interventional radiology. A key mandatory step, since bone metastases may be asymptomatic and disseminated throughout the skeleton, is to identify the bone metastasis location by cartography, especially within weight-bearing bones. For every location, the fracture risk evaluation relies on qualitative approaches using imagery and scores such as Mirels and spinal instability neoplastic score (SINS). This approach, however, has important limitations and there is a need to develop new tools for bone metastatic and myeloma fracture risk evaluation. Personalized numerical simulation qCT-based imaging constitutes one of these emerging tools to assess bone tumoral strength and estimate the femoral and vertebral fracture risk. The next generation of numerical simulation and artificial intelligence will take into account multiple loadings to integrate movement and obtain conditions even closer to real-life, in order to guide patient rehabilitation and activity within a personalized-medicine approach.

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.