Patients with cancer and bone metastases can have an increased risk of fracturing their femur. Treatment is based on the impending fracture risk: patients with a high fracture risk are considered for prophylactic surgery, whereas low fracture risk patients are treated conservatively with radiotherapy to decrease pain. Current clinical guidelines suggest to determine fracture risk based on axial cortical involvement of the lesion on conventional radiographs, but that appears to be difficult. Therefore, we developed a patient-specific finite element (FE) computer model that has shown to be able to predict fracture risk in an experimental setting and in patients. The goal of this study was to determine whether patient-specific finite element (FE) computer models are better at predicting fracture risk for femoral bone metastases compared to clinical assessments based on axial cortical involvement on conventional radiographs, as described in current clinical guidelines.

45 patients (50 affected femurs) affected with predominantly lytic bone metastases who were treated with palliative radiotherapy for pain were included. CT scans were made and patients were followed for six months to determine whether or not they fractured their femur. Non-linear isotropic FE models were created with the patient-specific geometry and bone density obtained from the CT scans. Subsequently, an axial load was simulated on the models mimicking stance. Failure loads normalized for bodyweight (BW) were calculated for each femur. High and low fracture risks were determined using a failure load of 7.5 × BW as a threshold. Experienced assessors measured axial cortical involvement on conventional radiographs. Following clinical guidelines, patients with lesions larger than 30 mm were identified as having a high fracture risk. FE predictions were compared to clinical assessments by means of diagnostic accuracy values (sensitivity, specificity and positive (PPV) and negative predictive values (NPV)).

Seven femurs (14%) fractured during follow-up. Median time to fracture was 8 weeks. FE models were better at predicting fracture risk in comparison to clinical assessments based on axial cortical involvement (sensitivity 100% vs. 86%, specificity 74% vs. 42%, PPV 39% vs. 19%, and NPV 100% vs. 95%, for the FE computer model vs. axial cortical involvement, respectively). We concluded that patient-specific FE computer models improve fracture risk predictions of femoral bone metastases in advanced cancer patients compared to clinical assessments based on axial cortical involvement, which is currently used in clinical guidelines. Therefore, we are initiating a pilot for clinical implementation of the FE model.

Objectives

In this prospective cohort study, we investigated whether patient-specific finite element (FE) models can identify patients at risk of a pathological femoral fracture resulting from metastatic bone disease, and compared these FE predictions with clinical assessments by experienced clinicians.

Aims

This study aims to assess first, whether mutations in the epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma (kRAS) genes are associated with overall survival (OS) in patients who present with symptomatic bone metastases from non-small cell lung cancer (NSCLC) and secondly, whether mutation status should be incorporated into prognostic models that are used when deciding on the appropriate palliative treatment for symptomatic bone metastases.

Previously, we showed that case-specific non-linear finite element (FE) models are better at predicting the load to failure of metastatic femora than experienced clinicians. In this study we improved our FE modelling and increased the number of femora and characteristics of the lesions. We retested the robustness of the FE predictions and assessed why clinicians have difficulty in estimating the load to failure of metastatic femora. A total of 20 femora with and without artificial metastases were mechanically loaded until failure. These experiments were simulated using case-specific FE models. Six clinicians ranked the femora on load to failure and reported their ranking strategies. The experimental load to failure for intact and metastatic femora was well predicted by the FE models (R² = 0.90 and R² = 0.93, respectively). Ranking metastatic femora on load to failure was well performed by the FE models (τ = 0.87), but not by the clinicians (0.11 < τ < 0.42). Both the FE models and the clinicians allowed for the characteristics of the lesions, but only the FE models incorporated the initial bone strength, which is essential for accurately predicting the risk of fracture. Accurate prediction of the risk of fracture should be made possible for clinicians by further developing FE models.

A number of risk factors based upon mostly retrospective surgical data, have been formulated in order to identify impending pathological fractures of the femur from low-risk metastases. We have followed up patients taking part in a randomised trial of radiotherapy, prospectively, in order to determine if these factors were effective in predicting fractures. In 102 patients with 110 femoral lesions, 14 fractures occurred during follow-up. The risk factors studied were increasing pain, the size of the lesion, radiographic appearance, localisation, transverse/axial/circumferential involvement of the cortex and the scoring system of Mirels. Only axial cortical involvement > 30 mm (p = 0.01), and circumferential cortical involvement > 50% (p = 0.03) were predictive of fracture. Mirels’ scoring system was insufficiently specific to predict a fracture (p = 0.36). Our results indicate that most conventional risk factors overestimate the actual occurrence of pathological fractures of the femur. The risk factor of axial cortical involvement provides a simple, objective tool in order to decide which treatment is appropriate.