{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,26]],"date-time":"2026-10-26T19:30:41Z","timestamp":1793043041055,"version":"4.5.0"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,10,19]],"date-time":"2021-10-19T00:00:00Z","timestamp":1634601600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,10,19]],"date-time":"2021-10-19T00:00:00Z","timestamp":1634601600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur Radiol Exp"],"published-print":{"date-parts":[[2021,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>We applied an artificial intelligence-based model to predict fragility fractures in postmenopausal women, using different dual-energy x-ray absorptiometry (DXA) parameters.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>One hundred seventy-four postmenopausal women without vertebral fractures (VFs) at baseline (mean age 66.3 \u00b1 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 \u00b1 1.91\u2009years. Considering the occurrence of new VFs at follow-up, two groups were created: fractured <jats:italic>versus<\/jats:italic> 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 <jats:italic>t<\/jats:italic>-test was used; variables were expressed as mean \u00b1 standard deviation.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>For each patient, we evaluated a total of <jats:italic>n<\/jats:italic> = 6 exams. At follow-up, <jats:italic>n<\/jats:italic> = 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.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>We 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.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s41747-021-00242-0","type":"journal-article","created":{"date-parts":[[2021,10,19]],"date-time":"2021-10-19T01:11:36Z","timestamp":1634605896000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Bone Strain Index predicts fragility fracture in osteoporotic women: an artificial intelligence-based study"],"prefix":"10.1186","volume":"5","author":[{"given":"Fabio Massimo","family":"Ulivieri","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luca","family":"Rinaudo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carmelo","family":"Messina","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luca Petruccio","family":"Piodi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Davide","family":"Capra","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Barbara","family":"Lupi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Camilla","family":"Meneguzzo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luca Maria","family":"Sconfienza","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesco","family":"Sardanelli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrea","family":"Giustina","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Enzo","family":"Grossi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,10,19]]},"reference":[{"key":"242_CR1","doi-asserted-by":"publisher","first-page":"785","DOI":"10.1001\/jama.285.6.785","volume":"285","author":"NIH Consensus Development Panel on Osteoporosis Prevention, Diagnosis, and Therapy","year":"2001","unstructured":"NIH Consensus Development Panel on Osteoporosis Prevention, Diagnosis, and Therapy (2001) Osteoporosis prevention, diagnosis, and therapy. 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Local Ethical Committees approval was obtained: Comitato Etico Milano Area 2. Protocol N 2.0 BQ. 265_2017, 13 June 2017 for IRCCS Fondazione Ca\u2019 Granda Ospedale Maggiore Policlinico, Milan, Italy. Comitato Etico San Raffaele; Studio clinico 2.0 BQ, version 4.0, 8 August 2019, for IRCCS Istituto Ortopedico Galeazzi, Milan; and IRCCS Policlinico San Donato, San Donato Milanese (MI).","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"\u2022 Francesco Sardanelli has received research grants from and is a member of the speakers\u2019 bureau and of the advisory group for General Electric. In addition, Francesco Sardanelli is the Editor-in-Chief of <i>European Radiology Experimental<\/i>; for this reason, he was not involved in any way in the revision\/decision process, which was completely managed by the Deputy Editor, Dr. Akos Varga-Szemes (Medical University of South Carolina, Charleston, SC, USA).\u2022 Luca Rinaudo, former working in Academic University Politecnico of Turin and now employed at the commercial company \u201cTECHNOLOGIC S.r.l\u201d, has extracted and tabulated the densitometric data and has applied the mathematical algorithms based on the finite element analysis to calculate the Bone Strain Index. TECHNOLOGIC S.r.l. provided support in the form of salary for author LR but did not have any role in the study design, data collection and analysis, decision to publish or preparation of the manuscript.\u2022 Luca Maria Sconfienza is a member of the <i>European Radiology Experimental<\/i> Editorial Board. He has not taken part in the review or selection process of this article.\u2022 All remaining authors declare that they have no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"47"}}