ReviewCurrent osteoporosis reports2022
A Review of CT-Based Fracture Risk Assessment with Finite Element Modeling and Machine Learning.
Review in Current osteoporosis reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- CT image-based biomarkers for opportunistic screening of osteoporotic fractures: a systematic review and meta-analysis.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2024Pooled it
- A clinically applicable energy-based approach for evaluating bone strength.Bone & joint research · 2026Article
- Artificial Intelligence in Rheumatology: From Algorithms to Clinical Impact in Osteoporosis and Chronic Inflammatory Rheumatic Diseases.Journal of clinical medicine · 2026Article
- Integration of Multi-Scale Predictive Tools of Bone Fragility: A Structural and Material Property Perspective.Materials (Basel, Switzerland) · 2025Review
- Variations over time in proximal femoral strength in young adult men are not explained by areal bone mineral density alone.JBMR plus · 2025Article
- Revolutionizing spine surgery with emerging AI-FEA integration.Journal of robotic surgery · 2025Review
- Faster R-CNN model for target recognition and diagnosis of scapular fractures.Journal of bone oncology · 2025Article
- Gender differences in L1 vertebral strength in adults 50+ using automated CT-based finite element analysis.Scientific reports · 2025Article
- Article
- Inelastic mechanical descriptors for osteoporotic hip fracture discrimination with 3D-DXA-based nonlinear finite element models.Frontiers in bioengineering and biotechnology · 2025Article
- Fully automated CT imaging biomarkers for opportunistic prediction of future hip fractures.The British journal of radiology · 2024Article
- Development and validation of a semi-automated and unsupervised method for femur segmentation from CT.Scientific reports · 2024Article
- From MRI to FEM: an automated pipeline for biomechanical simulations of vertebrae and intervertebral discs.Frontiers in bioengineering and biotechnology · 2024Article
- Characterizing Bone Phenotypes Related to Skeletal Fragility Using Advanced Medical Imaging.Current osteoporosis reports · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
purpose of reviewWe reviewed advances over the past 3 years in assessment of fracture risk based on CT scans, considering methods that use finite element models, machine learning, or a combination of both. RECENT
findingsSeveral studies have demonstrated that CT-based assessment of fracture risk, using finite element modeling or biomarkers derived from machine learning, is equivalent to currently used clinical tools. Phantomless calibration of CT scans for bone mineral density enables accurate measurements from routinely taken scans. This opportunistic use of CT scans for fracture risk assessment is facilitated by high-quality automated segmentation with deep learning, enabling workflows that do not require user intervention. Modeling of more realistic and diverse loading conditions, as well as improved modeling of fracture mechanisms, has shown promise to enhance our understanding of fracture processes and improve the assessment of fracture risk beyond the performance of current clinical tools. CT-based screening for fracture risk is effective and, by analyzing scans that were taken for other indications, could be used to expand the pool of people screened, therefore improving fracture prevention. Finite element modeling and machine learning both provide valuable tools for fracture risk assessment. Future approaches should focus on including more loading-related aspects of fracture risk.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.