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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. METHODS: A total of 39 patients with non-fractured femoral metastatic lesions who were irradiated for pain were included from three radiotherapy institutes. During follow-up, nine pathological fractures occurred in seven patients. Quantitative CT-based FE models were generated for all patients. Femoral failure load was calculated and compared between the fractured and non-fractured femurs. Due to inter-scanner differences, patients were analyzed separately for the three institutes. In addition, the FE-based predictions were compared with fracture risk assessments by experienced clinicians. RESULTS: In institute 1, median failure load was significantly lower for patients who sustained a fracture than for patients with no fractures. In institutes 2 and 3, the number of patients with a fracture was too low to make a clear distinction. Fracture locations were well predicted by the FE model when compared with post-fracture radiographs. The FE model was more accurate in identifying patients with a high fracture risk compared with experienced clinicians, with a sensitivity of 89% versus 0% to 33% for clinical assessments. Specificity was 79% for the FE models versus 84% to 95% for clinical assessments. CONCLUSION: FE models can be a valuable tool to improve clinical fracture risk predictions in metastatic bone disease. Future work in a larger patient population should confirm the higher predictive power of FE models compared with current clinical guidelines.Cite this article: F. Eggermont, L. C. Derikx, N. Verdonschot, I. C. M. van der Geest, M. A. A. de Jong, A. Snyers, Y. M. van der Linden, E. Tanck. Can patient-specific finite element models better predict fractures in metastatic bone disease than experienced clinicians? Towards computational modelling in daily clinical practice. Bone Joint Res 2018;7:430-439. DOI: 10.1302/2046-3758.76.BJR-2017-0325.R2.
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BACKGROUND: Radiation-associated angiosarcoma (RAAS) of the breast is a rare, aggressive disease. The incidence is increasing with the prolonged survival of women irradiated for primary breast cancer. Surgery is the current treatment of choice. Prognosis is poor. This review aims to evaluate all publications on primary treatment of RAAS to identify prognostic factors and evaluate treatment modalities. METHODS: Databases were searched for articles with published individual patient data on prognostic factors, treatment and follow-up of patients with RAAS. A regression analysis was performed to test the prognostic values of age, interval between primary treatment and RAAS, tumour size and grade on the local recurrence-free interval (LRFI) and overall survival (OS). The effects of treatment modalities surgery, radiation (with or without hyperthermia) and chemotherapy or combinations were evaluated. RESULTS: 74 articles were included, representing data on 222 patients. In these patients, the 5-year OS was 43% and 5-year LRFI was 32%. Tumour size and age were significant prognostic factors on LRFI and OS. Of all patients, 68% received surgery alone, 17% surgery and reirradiation and 6% surgery with chemotherapy. The remaining 9% received primary treatments without surgery. Surgery with radiotherapy had a better 5-year LRFI of 57% compared to 34% for surgery alone (p=0.008). The value of other treatment modalities could not be assessed. CONCLUSIONS: This systematic review confirms the poor prognosis of RAAS. Tumour size and age were of prognostic value. The addition of reirradiation to surgery in the treatment of RAAS appears to enhance local control.