ArticleBone & joint research2018
Can patient-specific finite element models better predict fractures in metastatic bone disease than experienced clinicians?: Towards computational modelling in daily clinical practice.
Article in Bone & joint research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 52 citations in OpenAlex.
- The epidemiology of cancer patients with proximal femoral lesions and evaluation of surgical decision tools: A prospective cohort study.Bone reports · 2026Article
- Diagnostic accuracy of Mirels score, CT-based Structural Rigidity Analysis, and Finite Element Analysis for predicting impending femoral pathologic fractures in metastatic bone disease: a systematic review.Journal of bone oncology · 2026Review
- Importance of Metastatic Lesion Location and Subject-Specificity in the Determination of Femoral Fracture Risk.International journal for numerical methods in biomedical engineering · 2026Article
- Predicting the Risk for Pathological Fracture in Bone Metastases.Current oncology (Toronto, Ont.) · 2025Review
- Internal validation of modified Mirels' scoring system for pathologic femur fractures.BMC musculoskeletal disorders · 2024Article
- Finite Element Model-Computed Mechanical Behavior of Femurs with Metastatic Disease Varies Between Physiologic and Idealized Loading Simulations.Biomedical engineering and computational biology · 2023Article
- The application of an isotropic crushable foam model to predict the femoral fracture risk.PloS one · 2023Article
- Article
- Osteolytic vs. Osteoblastic Metastatic Lesion: Computational Modeling of the Mechanical Behavior in the Human Vertebra after Screws Fixation Procedure.Journal of clinical medicine · 2022Article
- The effect of variations in CT scan protocol on femoral finite element failure load assessment using phantomless calibration.PloS one · 2022Article
- Breast Cancer Induced Bone Osteolysis Prediction Using Temporal Variational Autoencoders.BME frontiers · 2022Article
- Finite Element Assessment of Bone Fragility from Clinical Images.Current osteoporosis reports · 2021Review
- Review
- Evaluation of inter- and intra-operator reliability of manual segmentation of femoral metastatic lesions.International journal of computer assisted radiology and surgery · 2021Article
- Fracture Risk of Long Bone Metastases: A Review of Current and New Decision-Making Tools for Prophylactic Surgery.Cancers · 2021Review
- Biomechanics of subtrochanteric fracture fixation using short cephalomedullary nails: A finite element analysis.PloS one · 2021Article
- Prospective cohort study of surgical outcome for spinal metastases in patients aged 70 years or older.The bone & joint journal · 2020Article
- Article
- Review
- Nonlinear voxel-based finite element model for strength assessment of healthy and metastatic proximal femurs.Bone reports · 2020Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesIn 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.
methodsA 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.
resultsIn 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%
conclusionFE 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.
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