Although advanced 3-dimensional imaging, multi-plane x-rays, and combinations of studies, including PET scanning (Ulaner, 2017) can demonstrate radiographic depictions of the damage caused by metastatic lesions to the proximal femur, the available literature fails to define specific parameters that can accurately predict fracture risk. Low-quality evidence (Oh, 2017; Ulaner, 2017) supports the intuitive presumption that increased bone damage in the proximal femur is associated with an increased fracture risk. Furthermore, although MRI evaluation can accurately demonstrate the intra and extraosseous extent of lesions, there is no reliable evidence that this modality can be used as a predictor for fracture. Combining clinical factors, particularly tumor pain and pain with weight bearing, may aid clinicians in deciding when to intervene surgically in order to prevent a frank pathological fracture and the associated morbidities which may then occur.
- Oh, E., Seo, S. W., Yoon, Y. C., Kim, D. W., Kwon, S., Yoon, S. Prediction of pathologic femoral fractures in patients with lung cancer using machine learning algorithms: Comparison of computed tomography-based radiological features with clinical features versus without clinical features. Journal of Orthopaedic Surgery 2017; 2:
- Ulaner, G. A., Zindman, A. M., Zheng, J., Kim, T. W. B., Healey, J. H. FDG PET/CT Assesses the Risk of Femoral Pathological Fractures in Patients with Metastatic Breast Cancer. Clinical Nuclear Medicine 2017; 4: 264-270