Patient-specific computer (finite element (FE)) models are a potential tool to improve clinical fracture risk predictions in patients with metastatic bone disease. That was concluded in a study by Eggermont et al., recently published in Bone and Joint Research.Patients with cancer and bone metastases have an increased risk of pathological fractures, which severely affect the quality of life. Treatment of patients with bone metastases is based on the fracture risk: patients with a low fracture risk will be treated conservatively with local radiotherapy, while patient with a high fracture risk are considered for preventive stabilizing surgery. However, current clinical practice lacks an accurate tool to guide clinicians to the correct treatment decision. Therefore, researchers from the Orthopaedic Research Lab have been developing an FE model for fracture risk prediction, which was previously validated using cadaveric femurs. The next step was to evaluate the FE models in a multi-center prospective cohort study. A total of 39 patients with non-fractured femoral metastatic lesions who were treated with radiotherapy were included. All patients underwent CT scans, from which the patient-specific geometry and bone density were obtained, that functioned as input to the FE models. An axial load was simulated on the FE models and femoral failure load was calculated. Patients were followed for six months, during which nine pathological fractures occurred. FE-predicted failure loads were compared between fractured and non-fractured femurs. In addition, the FE-predictions were compared with fracture risk assessments by experienced clinicians.The FE model was more accurate at 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. It was concluded that FE models can be a valuable tool to improve clinical fracture risk predictions in metastatic bone disease, mainly to prevent unnecessary surgeries.
Can patient-specific finite element models better predict fractures in metastatic bone disease than experienced clinicians? Towards computational modeling in daily clinical practice.
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.
Florieke Eggermont is member of research theme Reconstructive and regenerative medicine.
Related news items
The Postdoctoral Networking Tour in artificial intelligence2 July 2020
You are a postdoctoral researcher in the field of artificial intelligence? The Postdoc-NeT-AI offers you the opportunity to participate in one week of on-site visits to leading German universities, research institutes and companies. Apply now to this year's tour until 16 August 2020.read more
Register for Phd courses via gROW What does this mean for you?2 July 2020
From now on you can arrange everything related to the general RU PhD courses via gROW. Because of this there will be some changes in the registration! What does this mean for you?read more
Experts on metabolic diseases still an unknown major problem...1 July 2020
Six Dutch UMCs and a patient association contribute to treating and solving this major, often unknown, problem. Timely detection of metabolic diseases is vital. Therefore, Radboudumc is also part of the consortium “United for Metabolic Diseases”.read more
Stefan Listl member Lancet Commission on Oral Health29 June 2020
In recognition of the global public health importance, woeful neglect of oral diseases, and the need for a broader understanding and commitment to global oral health within medicine and global health agendas, The Lancet recently established a Commission on Oral Health.read more
Trained immunity: a tool for reducing susceptibility to and the severity of SARS-CoV-2 infection29 June 2020
In a review in Cell Mihai Netea, Frank van de Veerdonk, Reinout van Crevel and Jorge Dominguez Andres propose that induction of trained immunity by whole-microorganism vaccines may represent an important tool for reducing susceptibility to and severity of SARS-CoV-2.read more
Master Prizes 2018-2019 awarded for best internship reports24 June 2020
Which students have made the best reports of their scientific internship? On 18 June the Radboudumc Master Prizes were awarded, an annual tradition to reward 'remarkably good scientific work by students'. This year's presentation was virtual, given the corona conditions.read more