ArticleEuropean radiology experimental2021
Bone Strain Index predicts fragility fracture in osteoporotic women: an artificial intelligence-based study.
Article in European radiology experimental, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Artificial Intelligence in Rheumatology: From Algorithms to Clinical Impact in Osteoporosis and Chronic Inflammatory Rheumatic Diseases.Journal of clinical medicine · 2026Article
- Artificial intelligence for predicting the risk of bone fragility fractures in osteoporosis.European radiology experimental · 2025Review
- Application of artificial intelligence in osteoporosis: a review.Frontiers in medicine · 2025Review
- Hypopituitarism and bone disease: pathophysiology, diagnosis and treatment outcomes.Pituitary · 2024Review
- Development and reporting of artificial intelligence in osteoporosis management.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2024Review
- DXA-derived lumbar bone strain index corrected for kyphosis is associated with vertebral fractures and trabecular bone score in acromegaly.Endocrine · 2024Article
- Long non-coding RNA MIAT serves as a biomarker of fragility fracture and promotes fracture healing.Journal of orthopaedic surgery and research · 2024Article
- New Horizons: Artificial Intelligence Tools for Managing Osteoporosis.The Journal of clinical endocrinology and metabolism · 2023Article
- Use of artificial neural networks in the prognosis of musculoskeletal diseases-a scoping review.BMC musculoskeletal disorders · 2023Article
- Predicting the risk of osteoporosis in older Vietnamese women using machine learning approaches.Scientific reports · 2022Article
- Bone Strain Index: preliminary distributional characteristics in a population of women with normal bone mass, osteopenia and osteoporosis.La Radiologia medica · 2022Article
- The Bone Strain Index: An Innovative Dual X-ray Absorptiometry Bone Strength Index and Its Helpfulness in Clinical Medicine.Journal of clinical medicine · 2022Review
- An Evolution Gaining Momentum-The Growing Role of Artificial Intelligence in the Diagnosis and Treatment of Spinal Diseases.Diagnostics (Basel, Switzerland) · 2022Review
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11 authors.
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Abstract
backgroundWe applied an artificial intelligence-based model to predict fragility fractures in postmenopausal women, using different dual-energy x-ray absorptiometry (DXA) parameters.
methodsOne hundred seventy-four postmenopausal women without vertebral fractures (VFs) at baseline (mean age 66.3 ± 9.8) were retrospectively evaluated. Data has been collected from September 2010 to August 2018. All subjects performed a spine x-ray to assess VFs, together with lumbar and femoral DXA for bone mineral density (BMD) and the bone strain index (BSI) evaluation. Follow-up exams were performed after 3.34 ± 1.91 years. Considering the occurrence of new VFs at follow-up, two groups were created: fractured versus not-fractured. We applied an artificial neural network (ANN) analysis with a predictive tool (TWIST system) to select relevant input data from a list of 13 variables including BMD and BSI. A semantic connectivity map was built to analyse the connections among variables within the groups. For group comparisons, an independent-samples t-test was used; variables were expressed as mean ± standard deviation.
resultsFor each patient, we evaluated a total of n = 6 exams. At follow-up, n = 69 (39.6%) women developed a VF. ANNs reached a predictive accuracy of 79.56% within the training testing procedure, with a sensitivity of 80.93% and a specificity of 78.18%. The semantic connectivity map showed that a low BSI at the total femur is connected to the absence of VFs.
conclusionWe found a high performance of ANN analysis in predicting the occurrence of VFs. Femoral BSI appears as a useful DXA index to identify patients at lower risk for lumbar VFs.
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