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.

Introduction and Aims: Reinfusion drains have been used to decrease the need for blood transfusion following total knee replacement. The aim of this study was to evaluate the degree of activation of platelets and leucocytes in both the blood that has been salvaged after total knee arthroplasty and the patients’ blood following reinfusion.

Method: A prospective series of 24 consecutive patients undergoing a primary total knee replacement in a case-control study were investigated. Post-operatively 12 patients received salvaged blood reinfusion and as a control, 12 patients underwent TKA with a standard drain. The reinfusion was initiated four hours after the operation. Blood samples were taken from all patients at three and five and a half to six hours post-operatively. A third sample was acquired in the treatment group from salvaged blood after reinfusion. Platelet, platelet-leucocyte and leucocyte activation markers were studied in both the drainage blood and the patients’ blood following reinfusion.

Results: Comparison between platelet, platelet-leucocyte and leucocyte activation markers in patients’ circulation prior to reinfusion compared to salvaged blood showed that almost all markers were significantly increased in salvaged blood. For example the platelet activation markers P-selectin (p< 0.01), Factor V (p< 0.01), CD40L (p< 0.01) and platelet derived microparticles (p< 0.01) were all significantly increased in the drainage blood. All studied platelet-leukocyte and leucocyte activation particles were also significantly increased. Following re-infusion of autologous salvaged blood there was no statistically measurable effect on activation markers of patients’ circulating platelets and leucocytes, but there was a slight drop in platelet count in the reinfused group compared to the control group. Levels of prothrombin fragment F 1+2 increased in the reinfused group compared to control indicating either activation of coagulation or simply the effect of addition of the high levels present in the salvage blood.

Conclusion: Blood from reinfusion drains showed a significant increase in activation of platelets and leukocytes indicating activation of coagulation. The reinfused blood did not lead to a difference in platelet and leukocyte activation but a decrease in platelets and an increase in fragment F1+2 suggests the possibility of activation of coagulation.