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Cao X, Keyak JH, Sigurdsson S, Zhao C, Zhou W, Liu A, Lang TF, Deng HW, Gudnason V, Sha Q. A new hip fracture risk index derived from FEA-computed proximal femur fracture loads and energies-to-failure. Osteoporos Int 2024; 35:785-794. [PMID: 38246971 PMCID: PMC11069422 DOI: 10.1007/s00198-024-07015-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 01/02/2024] [Indexed: 01/23/2024]
Abstract
Hip fracture risk assessment is an important but challenging task. Quantitative CT-based patient-specific finite element (FE) analysis (FEA) incorporates bone geometry and bone density in the proximal femur. We developed a global FEA-computed fracture risk index to increase the prediction accuracy of hip fracture incidence. PURPOSE Quantitative CT-based patient-specific finite element (FE) analysis (FEA) incorporates bone geometry and bone density in the proximal femur to compute the force (fracture load) and energy necessary to break the proximal femur in a particular loading condition. The fracture loads and energies-to-failure are individually associated with incident hip fracture, and provide different structural information about the proximal femur. METHODS We used principal component analysis (PCA) to develop a global FEA-computed fracture risk index that incorporates the FEA-computed yield and ultimate failure loads and energies-to-failure in four loading conditions of 110 hip fracture subjects and 235 age- and sex-matched control subjects from the AGES-Reykjavik study. Using a logistic regression model, we compared the prediction performance for hip fracture based on the stratified resampling. RESULTS We referred the first principal component (PC1) of the FE parameters as the global FEA-computed fracture risk index, which was the significant predictor of hip fracture (p-value < 0.001). The area under the receiver operating characteristic curve (AUC) using PC1 (0.776) was higher than that using all FE parameters combined (0.737) in the males (p-value < 0.001). CONCLUSIONS The global FEA-computed fracture risk index increased hip fracture risk prediction accuracy in males.
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Affiliation(s)
- Xuewei Cao
- Department of Mathematical Sciences, Michigan Technological University, Houghton, MI, 49931, USA
| | - Joyce H Keyak
- Department of Radiological Sciences, Department of Biomedical Engineering, and Department of Mechanical and Aerospace Engineering, University of California, Irvine, CA, USA
| | | | - Chen Zhao
- Department of Applied Computing, Michigan Technological University, Houghton, MI, USA
| | - Weihua Zhou
- Department of Applied Computing, Michigan Technological University, Houghton, MI, USA
| | - Anqi Liu
- Center for Bioinformatics and Genomics, School of Medicine, Tulane University, New Orleans, LA, USA
| | - Thomas F Lang
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Hong-Wen Deng
- Center for Bioinformatics and Genomics, School of Medicine, Tulane University, New Orleans, LA, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association Research Institute, Kopavogur, Iceland.
- University of Iceland, Reykjavik, Iceland.
| | - Qiuying Sha
- Department of Mathematical Sciences, Michigan Technological University, Houghton, MI, 49931, USA.
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2
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Grassi L, Väänänen SP, Jehpsson L, Ljunggren Ö, Rosengren BE, Karlsson MK, Isaksson H. 3D Finite Element Models Reconstructed From 2D Dual-Energy X-Ray Absorptiometry (DXA) Images Improve Hip Fracture Prediction Compared to Areal BMD in Osteoporotic Fractures in Men (MrOS) Sweden Cohort. J Bone Miner Res 2023; 38:1258-1267. [PMID: 37417707 DOI: 10.1002/jbmr.4878] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 06/15/2023] [Accepted: 07/04/2023] [Indexed: 07/08/2023]
Abstract
Bone strength is an important contributor to fracture risk. Areal bone mineral density (aBMD) derived from dual-energy X-ray absorptiometry (DXA) is used as a surrogate for bone strength in fracture risk prediction tools. 3D finite element (FE) models predict bone strength better than aBMD, but their clinical use is limited by the need for 3D computed tomography and lack of automation. We have earlier developed a method to reconstruct the 3D hip anatomy from a 2D DXA image, followed by subject-specific FE-based prediction of proximal femoral strength. In the current study, we aim to evaluate the method's ability to predict incident hip fractures in a population-based cohort (Osteoporotic Fractures in Men [MrOS] Sweden). We defined two subcohorts: (i) hip fracture cases and controls cohort: 120 men with a hip fracture (<10 years from baseline) and two controls to each hip fracture case, matched by age, height, and body mass index; and (ii) fallers cohort: 86 men who had fallen the year before their hip DXA scan was acquired, 15 of which sustained a hip fracture during the following 10 years. For each participant, we reconstructed the 3D hip anatomy and predicted proximal femoral strength in 10 sideways fall configurations using FE analysis. The FE-predicted proximal femoral strength was a better predictor of incident hip fractures than aBMD for both hip fracture cases and controls (difference in area under the receiver operating characteristics curve, ΔAUROC = 0.06) and fallers (ΔAUROC = 0.22) cohorts. This is the first time that FE models outperformed aBMD in predicting incident hip fractures in a population-based prospectively followed cohort based on 3D FE models obtained from a 2D DXA scan. Our approach has potential to notably improve the accuracy of fracture risk predictions in a clinically feasible manner (only one single DXA image is needed) and without additional costs compared to the current clinical approach. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
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Affiliation(s)
- Lorenzo Grassi
- Department of Biomedical Engineering, Lund University, Lund, Sweden
| | - Sami P Väänänen
- Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
- Department of Applied Physics, University of Eastern Finland, Eastern Finland, Finland
| | - Lars Jehpsson
- Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Östen Ljunggren
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Björn E Rosengren
- Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Magnus K Karlsson
- Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Hanna Isaksson
- Department of Biomedical Engineering, Lund University, Lund, Sweden
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3
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Abstract
PURPOSE OF REVIEW We re-evaluated clinical applications of image-to-FE models to understand if clinical advantages are already evident, which proposals are promising, and which questions are still open. RECENT FINDINGS CT-to-FE is useful in longitudinal treatment evaluation and groups discrimination. In metastatic lesions, CT-to-FE strength alone accurately predicts impending femoral fractures. In osteoporosis, strength from CT-to-FE or DXA-to-FE predicts incident fractures similarly to DXA-aBMD. Coupling loads and strength (possibly in dynamic models) may improve prediction. One promising MRI-to-FE workflow may now be tested on clinical data. Evidence of artificial intelligence usefulness is appearing. CT-to-FE is already clinical in opportunistic CT screening for osteoporosis, and risk of metastasis-related impending fractures. Short-term keys to improve image-to-FE in osteoporosis may be coupling FE with fall risk estimates, pool FE results with other parameters through robust artificial intelligence approaches, and increase reproducibility and cross-validation of models. Modeling bone modifications over time and bone fracture mechanics are still open issues.
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Affiliation(s)
- Enrico Schileo
- Bioengineering and Computing Laboratory, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy.
| | - Fulvia Taddei
- Bioengineering and Computing Laboratory, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
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Foessl I, Bassett JHD, Bjørnerem Å, Busse B, Calado Â, Chavassieux P, Christou M, Douni E, Fiedler IAK, Fonseca JE, Hassler E, Högler W, Kague E, Karasik D, Khashayar P, Langdahl BL, Leitch VD, Lopes P, Markozannes G, McGuigan FEA, Medina-Gomez C, Ntzani E, Oei L, Ohlsson C, Szulc P, Tobias JH, Trajanoska K, Tuzun Ş, Valjevac A, van Rietbergen B, Williams GR, Zekic T, Rivadeneira F, Obermayer-Pietsch B. Bone Phenotyping Approaches in Human, Mice and Zebrafish - Expert Overview of the EU Cost Action GEMSTONE ("GEnomics of MusculoSkeletal traits TranslatiOnal NEtwork"). Front Endocrinol (Lausanne) 2021; 12:720728. [PMID: 34925226 PMCID: PMC8672201 DOI: 10.3389/fendo.2021.720728] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 10/21/2021] [Indexed: 12/16/2022] Open
Abstract
A synoptic overview of scientific methods applied in bone and associated research fields across species has yet to be published. Experts from the EU Cost Action GEMSTONE ("GEnomics of MusculoSkeletal Traits translational Network") Working Group 2 present an overview of the routine techniques as well as clinical and research approaches employed to characterize bone phenotypes in humans and selected animal models (mice and zebrafish) of health and disease. The goal is consolidation of knowledge and a map for future research. This expert paper provides a comprehensive overview of state-of-the-art technologies to investigate bone properties in humans and animals - including their strengths and weaknesses. New research methodologies are outlined and future strategies are discussed to combine phenotypic with rapidly developing -omics data in order to advance musculoskeletal research and move towards "personalised medicine".
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Affiliation(s)
- Ines Foessl
- Department of Internal Medicine, Division of Endocrinology and Diabetology, Endocrine Lab Platform, Medical University of Graz, Graz, Austria
| | - J. H. Duncan Bassett
- Molecular Endocrinology Laboratory, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom
| | - Åshild Bjørnerem
- Department of Clinical Medicine, UiT The Arctic University of Norway, Tromsø, Norway
- Norwegian Research Centre for Women’s Health, Oslo University Hospital, Oslo, Norway
| | - Björn Busse
- Department of Osteology and Biomechanics, University Medical Center, Hamburg-Eppendorf, Hamburg, Germany
| | - Ângelo Calado
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Centro Académico de Medicina de Lisboa, Lisboa, Portugal
| | | | - Maria Christou
- Department of Hygiene and Epidemiology, Medical School, University of Ioannina, Ioannina, Greece
| | - Eleni Douni
- Institute for Bioinnovation, Biomedical Sciences Research Center “Alexander Fleming”, Vari, Greece
- Department of Biotechnology, Agricultural University of Athens, Athens, Greece
| | - Imke A. K. Fiedler
- Department of Osteology and Biomechanics, University Medical Center, Hamburg-Eppendorf, Hamburg, Germany
| | - João Eurico Fonseca
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Centro Académico de Medicina de Lisboa, Lisboa, Portugal
- Rheumatology Department, Hospital de Santa Maria, Centro Hospitalar Universitário Lisboa Norte (CHULN), Lisbon Academic Medical Centre, Lisbon, Portugal
| | - Eva Hassler
- Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Medical University Graz, Graz, Austria
| | - Wolfgang Högler
- Department of Paediatrics and Adolescent Medicine, Johannes Kepler University Linz, Linz, Austria
| | - Erika Kague
- The School of Physiology, Pharmacology and Neuroscience, Biomedical Sciences, University of Bristol, Bristol, United Kingdom
| | - David Karasik
- Azrieli Faculty of Medicine, Bar-Ilan University, Ramat Gan, Israel
| | - Patricia Khashayar
- Center for Microsystems Technology, Imec and Ghent University, Ghent, Belgium
| | - Bente L. Langdahl
- Department of Endocrinology and Internal Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Victoria D. Leitch
- Innovative Manufacturing Cooperative Research Centre, Royal Melbourne Institute of Technology, School of Engineering, Carlton, VIC, Australia
| | - Philippe Lopes
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Georgios Markozannes
- Department of Hygiene and Epidemiology, Medical School, University of Ioannina, Ioannina, Greece
| | | | | | - Evangelia Ntzani
- Department of Hygiene and Epidemiology, Medical School, University of Ioannina, Ioannina, Greece
- Department of Health Services, Policy and Practice, Center for Research Synthesis in Health, School of Public Health, Brown University, Providence, RI, United States
| | - Ling Oei
- Centre for Bone and Arthritis Research, Institute of Medicine, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | - Claes Ohlsson
- Centre for Bone and Arthritis Research, Institute of Medicine, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
- Department of Drug Treatment, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Pawel Szulc
- INSERM UMR 1033, University of Lyon, Lyon, France
| | - Jonathan H. Tobias
- Musculoskeletal Research Unit, Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- MRC Integrative Epidemiology Unit, Bristol Medical School, Bristol, University of Bristol, Bristol, United Kingdom
| | - Katerina Trajanoska
- Department of Internal Medicine, Erasmus MC Rotterdam, Rotterdam, Netherlands
| | - Şansın Tuzun
- Physical Medicine & Rehabilitation Department, Cerrahpasa Medical Faculty, Istanbul University-Cerrahpaşa, Istanbul, Turkey
| | - Amina Valjevac
- Department of Human Physiology, School of Medicine, University of Sarajevo, Sarajevo, Bosnia and Herzegovina
| | - Bert van Rietbergen
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
| | - Graham R. Williams
- Molecular Endocrinology Laboratory, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom
| | - Tatjana Zekic
- Department of Rheumatology and Clinical Immunology, Faculty of Medicine, Clinical Hospital Center Rijeka, Rijeka, Croatia
| | | | - Barbara Obermayer-Pietsch
- Department of Internal Medicine, Division of Endocrinology and Diabetology, Endocrine Lab Platform, Medical University of Graz, Graz, Austria
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Luo Y. On challenges in clinical assessment of hip fracture risk using image-based biomechanical modelling: a critical review. J Bone Miner Metab 2021; 39:523-533. [PMID: 33423096 DOI: 10.1007/s00774-020-01198-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 12/11/2020] [Indexed: 10/22/2022]
Abstract
INTRODUCTION Hip fracture is a common health risk among elderly people, due to the prevalence of osteoporosis and accidental fall in the population. Accurate assessment of fracture risk is a crucial step for clinicians to consider patient-by-patient optimal treatments for effective prevention of fractures. Image-based biomechanical modeling has shown promising progress in assessment of fracture risk, and there is still a great possibility for improvement. The purpose of this paper is to identify key issues that need be addressed to improve image-based biomechanical modeling. MATERIALS AND METHODS We critically examined issues in consideration and determination of the four biomechanical variables, i.e., risk of fall, fall-induced impact force, bone geometry and bone material quality, which are essential for prediction of hip fracture risk. We closely inspected: limitations introduced by assumptions that are adopted in existing models; deficiencies in methods for construction of biomechanical models, especially for determination of bone material properties from bone images; problems caused by separate use of the variables in clinical study of hip fracture risk; availability of clinical information that are required for validation of biomechanical models. RESULTS AND CONCLUSIONS A number of critical issues and gaps were identified. Strategies for effectively addressing the issues were discussed.
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Affiliation(s)
- Yunhua Luo
- Department of Mechanical Engineering, University of Manitoba, 75A Chancellor's Circle, Winnipeg, MB, R3T 2N2, Canada.
- Department of Biomedical Engineering, University of Manitoba, 75A Chancellor's Circle, Winnipeg, MB, R3T 2N2, Canada.
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6
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Abstract
A bone fractures when a force applied to it exceeds its strength. Assessment of bone strength is an important component in determining the risk of fracture and guiding treatment decisions. Dual-energy X-ray absorptiometry is used to diagnosis osteoporosis, estimate fracture risk, and monitor changes in bone density. Fracture risk algorithms provide enhanced fracture risk predictability. Advanced technologies with computed tomography (CT) and MRI can measure parameters of bone microarchitecture. Mathematical modeling using CT data can evaluate the behavior of bone structures in response to external loading. Microindentation techniques directly measure the strength of outer bone cortex.
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Affiliation(s)
- E Michael Lewiecki
- New Mexico Clinical Research & Osteoporosis Center, 300 Oak Street Northeast, Albuquerque, NM 87106, USA.
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Cha YH, Yoo JI. Comparison of hip structure analysis and grip strength between femoral neck and basicervical fractures. BMC Musculoskelet Disord 2021; 22:461. [PMID: 34011356 PMCID: PMC8135173 DOI: 10.1186/s12891-021-04363-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 05/10/2021] [Indexed: 11/10/2022] Open
Abstract
Background The purpose of this study was to analyze differences in geometrical properties of the proximal femur and predict the occurrence of basicervical fractures through a comparative study of femoral neck and basicervical fractures in patients undergoing hip structural analysis (HSA). Methods All patients with hip fractures who were at least 65 years old and admitted to our hospital between March 2017 and December 2019 were eligible for this study. During the study period, 149 femur neck fractures (FNF) and basicervical fractures (intertrochanteric fractures of A31.2) were included in this study. Fifty-nine patients were included in the final analysis. Factors considered to be important confounders affecting the occurrence of basicervical hip fractures were chosen for propensity-score analysis. A logistic model with basicervical hip fracture as the outcome and age, sex, weight, spinal T-score, hip T-score, and vitamin D levels as confounders was used to estimate the propensity score. Results The cross-sectional moment of inertia (CSMI) of the intertrochanter was significantly lower in patients with basicervical hip fracture (HF) than in patients with FNF (p = 0.045). However, there was no significant differences in any other HSA variable between the two groups. Receiver operating characteristic (ROC) analysis showed that cutoff point for HSA was 100 for hip axis length (HAL) (AUC = 0.659, p < 0.001) and 5.712 for CSMI of the intertrochanter (AUC = 0.676, p < 0.001). ROC analysis showed that cutoff points of HAL, CSMI of intertrochanter, and handgrip strength were 104.8, 8.75, and 16.9, respectively (AUC = 0.726, p < 0.001). Conclusions Proximal femoral geometric analysis using HSA is a useful method for predicting the type of hip fracture. Additionally, a lower CSMI, a shorter HAL, and a lower grip strength are major predictors of basicervical fractures.
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Affiliation(s)
- Yong-Han Cha
- Department of Orthopaedic Surgery, Eulji University hospital, Daejeon, South Korea
| | - Jun-Il Yoo
- Department of Orthopaedic Surgery, Gyeongsang national university hospital, Jinju, Gyeongnamdo, South Korea.
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Abstract
PURPOSE OF REVIEW To critically assess recent evidence concerning osteoporosis fracture risk. RECENT FINDINGS Robust instruments exist for predicting factures incorporating well-documented risk factors especially prior fracture whose magnitude varies with site, occurrence time, and age. Stratifying time-since-prior fracture has resulted in the concept of imminent fracture risk and increased focus on secondary fracture prevention. Secondary fracture prevention recommendations include fracture liaison service, pharmacologic and non-pharmacologic multidisciplinary intervention, and communicating that fractures in older adults are the predictable consequence of underlying osteoporosis rather than unfortunate accidents. Quality improvement in osteoporosis care includes diagnosing osteoporosis on the basis of clinical fractures rather than exclusively relying on bone density testing; applying diagnostic rather than screening approaches to patients with prior fractures; regularly updating fall and fracture histories; performing a physical exam focused on spinal curvature, posture, and musculoskeletal function; reviewing images to identify prevalent fractures that may have been missed; and general use of fracture risk algorithms at all stages of osteoporosis management. Communicating effectively with patients about osteoporosis and fractures, their consequences, and pharmacological and non-pharmacological management is the cornerstone of high-value care.
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Affiliation(s)
- Sanford Baim
- Division of Endocrinology and Metabolism, Rush University Medical Center and Cook County Health and Hospital System, Professional Building, 1725 W. Harrison St., Suite 250, Chicago, IL, 606012, USA.
| | - Robert Blank
- Bone Biology and Healthy Aging Group, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
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Ulivieri FM, Rinaudo L. Beyond Bone Mineral Density: A New Dual X-Ray Absorptiometry Index of Bone Strength to Predict Fragility Fractures, the Bone Strain Index. Front Med (Lausanne) 2021; 7:590139. [PMID: 33521014 PMCID: PMC7843921 DOI: 10.3389/fmed.2020.590139] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Accepted: 12/17/2020] [Indexed: 12/12/2022] Open
Abstract
For a proper assessment of osteoporotic fragility fracture prediction, all aspects regarding bone mineral density, bone texture, geometry and information about strength are necessary, particularly in endocrinological and rheumatological diseases, where bone quality impairment is relevant. Data regarding bone quantity (density) and, partially, bone quality (structure and geometry) are obtained by the gold standard method of dual X-ray absorptiometry (DXA). Data about bone strength are not yet readily available. To evaluate bone resistance to strain, a new DXA-derived index based on the Finite Element Analysis (FEA) of a greyscale of density distribution measured on spine and femoral scan, namely Bone Strain Index (BSI), has recently been developed. Bone Strain Index includes local information on density distribution, bone geometry and loadings and it differs from bone mineral density (BMD) and other variables of bone quality like trabecular bone score (TBS), which are all based on the quantification of bone mass and distribution averaged over the scanned region. This state of the art review illustrates the methodology of BSI calculation, the findings of its in reproducibility and the preliminary data about its capability to predict fragility fracture and to monitor the follow up of the pharmacological treatment for osteoporosis.
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Affiliation(s)
- Fabio Massimo Ulivieri
- Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Ca' Granda Ospedale Maggiore Policlinico, Unità Operativa (UO) Medicina Nucleare, Milan, Italy
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10
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Abstract
PURPOSE OF REVIEW Identifying individuals at high fracture risk can be used to target those likely to derive the greatest benefit from treatment. This narrative review examines recent developments in using specific risk factors used to assess fracture risk, with a focus on publications in the last 3 years. RECENT FINDINGS There is expanding evidence for the recognition of individual clinical risk factors and clinical use of composite scores in the general population. Unfortunately, enthusiasm is dampened by three pragmatic randomized trials that raise questions about the effectiveness of widespread population screening using clinical fracture prediction tools given suboptimal participation and adherence. There have been refinements in risk assessment in special populations: men, patients with diabetes, and secondary causes of osteoporosis. New evidence supports the value of vertebral fracture assessment (VFA), high resolution peripheral quantitative CT (HR-pQCT), opportunistic screening using CT, skeletal strength assessment with finite element analysis (FEA), and trabecular bone score (TBS). The last 3 years have seen important developments in the area of fracture risk assessment, both in the research setting and translation to clinical practice. The next challenge will be incorporating these advances into routine work flows that can improve the identification of high risk individuals at the population level and meaningfully impact the ongoing crisis in osteoporosis management.
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Affiliation(s)
- William D Leslie
- Departments of Medicine and Radiology, University of Manitoba, 409 Tache Avenue, Winnipeg, Manitoba, R2H 2A6, Canada.
| | - Suzanne N Morin
- Department of Medicine, McGill University- McGill University Health Center, Montreal, Quebec, Canada
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11
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Prediction and diagnosis of vertebral tumors on the Internet of Medical Things Platform using geometric rough propagation neural network. Neural Comput Appl 2020. [DOI: 10.1007/s00521-020-04935-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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12
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Bouxsein ML, Zysset P, Glüer CC, McClung M, Biver E, Pierroz DD, Ferrari SL. Perspectives on the non-invasive evaluation of femoral strength in the assessment of hip fracture risk. Osteoporos Int 2020; 31:393-408. [PMID: 31900541 DOI: 10.1007/s00198-019-05195-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Accepted: 10/04/2019] [Indexed: 10/25/2022]
Abstract
UNLABELLED We reviewed the experimental and clinical evidence that hip bone strength estimated by BMD and/or finite element analysis (FEA) reflects the actual strength of the proximal femur and is associated with hip fracture risk and its changes upon treatment. INTRODUCTION The risk of hip fractures increases exponentially with age due to a progressive loss of bone mass, deterioration of bone structure, and increased incidence of falls. Areal bone mineral density (aBMD), measured by dual-energy X-ray absorptiometry (DXA), is the most used surrogate marker of bone strength. However, age-related declines in bone strength exceed those of aBMD, and the majority of fractures occur in those who are not identified as osteoporotic by BMD testing. With hip fracture incidence increasing worldwide, the development of accurate methods to estimate bone strength in vivo would be very useful to predict the risk of hip fracture and to monitor the effects of osteoporosis therapies. METHODS We reviewed experimental and clinical evidence regarding the association between aBMD and/orCT-finite element analysis (FEA) estimated femoral strength and hip fracture risk as well as their changes with treatment. RESULTS Femoral aBMD and bone strength estimates by CT-FEA explain a large proportion of femoral strength ex vivo and predict hip fracture risk in vivo. Changes in femoral aBMD are strongly associated with anti-fracture efficacy of osteoporosis treatments, though comparable data for FEA are currently not available. CONCLUSIONS Hip aBMD and estimated femoral strength are good predictors of fracture risk and could potentially be used as surrogate endpoints for fracture in clinical trials. Further improvements of FEA may be achieved by incorporating trabecular orientations, enhanced cortical modeling, effects of aging on bone tissue ductility, and multiple sideway fall loading conditions.
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Affiliation(s)
- M L Bouxsein
- Center for Advanced Orthopedic Studies, Beth Israel Deaconess Medical Center, and Department of Orthopedic Surgery, Harvard Medical School, Boston, MA, USA
| | - P Zysset
- ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
| | - C C Glüer
- Section of Biomedical Imaging, Department of Radiology and Neuroradiology, University Medical Center of Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - M McClung
- Oregon Osteoporosis Center, Portland, OR, USA
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, Australia
| | - E Biver
- Division of Bone Disease, Department of Internal Medicine Specialties, Faculty of Medicine, Geneva University Hospital, Geneva, Switzerland
| | - D D Pierroz
- International Osteoporosis Foundation (IOF), Nyon, Switzerland
| | - S L Ferrari
- Division of Bone Disease, Department of Internal Medicine Specialties, Faculty of Medicine, Geneva University Hospital, Geneva, Switzerland.
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13
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Luo Y. Age-related periosteal expansion at femoral neck among elderly women may maintain bending stiffness, but not femoral strength. Osteoporos Int 2020; 31:371-377. [PMID: 31696273 DOI: 10.1007/s00198-019-05165-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Accepted: 09/09/2019] [Indexed: 10/25/2022]
Abstract
UNLABELLED Periosteal expansion and bone loss have opposite effects on femur strength. Their combined effect has not been fully understood. Our investigation using a recently developed beam model suggested that periosteal expansion may maintain femur bending stiffness among elderly women, but not help preserve femoral strength and reduce hip fracture risk. INTRODUCTION Periosteal expansion and bone loss are two accompanying biological phenomena in old population. Their combined effect on bone stiffness, strength, and fracture risk is still not clear, because previous studies have reported contradictory results. METHODS A recently developed DXA (dual-energy X-ray absorptiometry)-based beam model was applied to study the effect at the femoral neck. We first made a theoretical analysis. Then, a clinical cohort consisting of 961 women (316 hip fractures and 645 controls, age of 75.9 ± 7.1) was used to investigate the associations quantitatively. We investigated (1) correlations of femoral-neck width and bone mineral density with femoral stiffness and strength; (2) correlations of femoral stiffness, strength, and hip fracture risk index with age; (3) associations of femoral stiffness, strength and fracture risk index with actual fracture status, measured by the area under the curve (AUC) and odds ratio (OR). RESULTS The investigation results showed that (i) femoral-neck width had stronger correlation with femoral bending stiffness (r = 0.61-0.82, p < 0.001) than with the other stiffness components, while bone mineral density had stronger correlation with axial/shearing stiffness (r = 0.84-0.97, p < 0.001), strength (r = 0.85-0.92, p < 0.001), and fracture risk index (r = -0.61-0.62, p < 0.001) than with bending stiffness. (ii) The association between femoral bending stiffness and age was insignificant (r = - 0.06-0.05, r > 0.05); The associations of axial/shearing stiffness (r = - 0.27--0.20, p < 0.001), strength (r = - 0.28, p < 0.001), and fracture risk index (r = 0.38, p < 0.001) with age were significant. (iii) Fracture risk index had the strongest association with actual fracture status (AUC = 0.75, OR = 3.19), followed by strength (AUC = 0.74, OR = 2.84) and axial/shearing stiffness (AUC = 0.56-0.65, OR = 2.39-2.49). Femoral bending stiffness had the weakest association (AUC = 0.48-0.69, OR = 1.42-2.09). CONCLUSION We concluded that periosteal expansion may be adequate to maintain femoral bending stiffness among elderly women, but it may not help preserve strength and reduce hip fracture risk.
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Affiliation(s)
- Y Luo
- Department of Mechanical Engineering, University of Manitoba, 75A Chancellor's Circle, Winnipeg, MB, R3T 2N2, Canada.
- Department of Biomedical Engineering, University of Manitoba, 75A Chancellor's Circle, Winnipeg, MB, R3T 2N2, Canada.
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14
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Diez-Perez A, Brandi ML, Al-Daghri N, Branco JC, Bruyère O, Cavalli L, Cooper C, Cortet B, Dawson-Hughes B, Dimai HP, Gonnelli S, Hadji P, Halbout P, Kaufman JM, Kurth A, Locquet M, Maggi S, Matijevic R, Reginster JY, Rizzoli R, Thierry T. Radiofrequency echographic multi-spectrometry for the in-vivo assessment of bone strength: state of the art-outcomes of an expert consensus meeting organized by the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO). Aging Clin Exp Res 2019; 31:1375-1389. [PMID: 31422565 PMCID: PMC6763416 DOI: 10.1007/s40520-019-01294-4] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Accepted: 07/24/2019] [Indexed: 01/19/2023]
Abstract
PURPOSE The purpose of this paper was to review the available approaches for bone strength assessment, osteoporosis diagnosis and fracture risk prediction, and to provide insights into radiofrequency echographic multi spectrometry (REMS), a non-ionizing axial skeleton technique. METHODS A working group convened by the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis met to review the current image-based methods for bone strength assessment and fracture risk estimation, and to discuss the clinical perspectives of REMS. RESULTS Areal bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DXA) is the consolidated indicator for osteoporosis diagnosis and fracture risk assessment. A more reliable fracture risk estimation would actually require an improved assessment of bone strength, integrating also bone quality information. Several different approaches have been proposed, including additional DXA-based parameters, quantitative computed tomography, and quantitative ultrasound. Although each of them showed a somewhat improved clinical performance, none satisfied all the requirements for a widespread routine employment, which was typically hindered by unclear clinical usefulness, radiation doses, limited accessibility, or inapplicability to spine and hip, therefore leaving several clinical needs still unmet. REMS is a clinically available technology for osteoporosis diagnosis and fracture risk assessment through the estimation of BMD on the axial skeleton reference sites. Its automatic processing of unfiltered ultrasound signals provides accurate BMD values in view of fracture risk assessment. CONCLUSIONS New approaches for improved bone strength and fracture risk estimations are needed for a better management of osteoporotic patients. In this context, REMS represents a valuable approach for osteoporosis diagnosis and fracture risk prediction.
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Affiliation(s)
- Adolfo Diez-Perez
- Department of Internal Medicine, Hospital del Mar/IMIM and CIBERFES, Autonomous University of Barcelona, Passeig Maritim 25-29, 08003, Barcelona, Spain.
| | - Maria Luisa Brandi
- FirmoLab Fondazione F.I.R.M.O., Florence, Italy
- Department of Biological, Experimental and Clinical Science, University of Florence, Florence, Italy
| | - Nasser Al-Daghri
- Chair for Biomarkers of Chronic Diseases, Biochemistry Department, College of Science, King Saud University, Riyadh, Kingdom of Saudi Arabia
| | - Jaime C Branco
- NOVA Medical School, Universidade Nova de Lisboa, Lisbon, Portugal
| | - Olivier Bruyère
- WHO Collaborating Centre for Public Health Aspects of Musculoskeletal Health and Aging, University of Liège, Liège, Belgium
| | - Loredana Cavalli
- FirmoLab Fondazione F.I.R.M.O., Florence, Italy
- Department of Biological, Experimental and Clinical Science, University of Florence, Florence, Italy
| | - Cyrus Cooper
- MRC Lifecourse Epidemiology Unit, Southampton General Hospital, University of Southampton, Southampton, UK
| | - Bernard Cortet
- Department of Rheumatology and EA 4490, University-Hospital of Lille, Lille, France
| | - Bess Dawson-Hughes
- Bone Metabolism Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA
| | - Hans Peter Dimai
- Department of Internal Medicine, Division of Endocrinology and Diabetology, Medical University of Graz, Graz, Austria
| | - Stefano Gonnelli
- Department of Medicine, Surgery and Neurosciences, University of Siena, Siena, Italy
| | - Peyman Hadji
- Frankfurter Hormon und Osteoporose Zentrum, Frankfurt, Germany
| | | | - Jean-Marc Kaufman
- Department of Endocrinology, Ghent University Hospital, Ghent, Belgium
| | - Andreas Kurth
- Department of Orthopaedic Surgery and Osteology, Klinikum Frankfurt, Frankfurt, Germany
- Mayor Teaching Hospital, Charite Medical School, Berlin, Germany
| | - Medea Locquet
- Department of Public Health, Epidemiology and Health Economics, University of Liège, Liège, Belgium
| | - Stefania Maggi
- National Research Council, Aging Program, Institute of Neuroscience, Padua, Italy
| | - Radmila Matijevic
- Faculty of Medicine, University of Novi Sad, Novi Sad, Serbia
- Clinical Center of Vojvodina, Clinic for Orthopedic Surgery, Novi Sad, Serbia
| | - Jean-Yves Reginster
- Chair for Biomarkers of Chronic Diseases, Biochemistry Department, College of Science, King Saud University, Riyadh, Kingdom of Saudi Arabia
- WHO Collaborating Centre for Public Health Aspects of Musculoskeletal Health and Aging, University of Liège, Liège, Belgium
| | - René Rizzoli
- Service of Bone Diseases, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland
| | - Thomas Thierry
- Department of Rheumatology, Hospital Nord, CHU St Etienne, St Etienne, France
- INSERM 1059, University of Lyon, St Etienne, France
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15
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Ha YC, Yoo JI, Yoo J, Park KS. Effects of Hip Structure Analysis Variables on Hip Fracture: A Propensity Score Matching Study. J Clin Med 2019; 8:E1507. [PMID: 31547057 PMCID: PMC6833009 DOI: 10.3390/jcm8101507] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 09/15/2019] [Accepted: 09/17/2019] [Indexed: 12/13/2022] Open
Abstract
The purpose of this retrospective study was to compare the hip structural analysis (HSA) levels of patients with those of a hip fracture group. All patients with an initial hip fracture who were older than or equal to 65 years old and admitted to our hospital between March 2018 and January 2019 were eligible for this study. During the study period, 134 hip fracture patients aged 65 years and older were admitted to the study institution, and a total of 51 hip fracture patients were ultimately assigned to the patient group. Age, sex, body mass index (BMI), skeletal muscle index (SMI), and vitamin D were matched in the two groups (hip fracture (HF) group vs. non-hip fracture group) using propensity score matching (PSM) without any statistical differences. Following propensity score matching, 51 patients in the HF group and 51 patients in the non-HF group were included in the study, respectively. Hip axis length (p = 0.031), neck-shaft angle (p = 0.043), width of intertrochanter (p = 0.005), and femur shaft (p = 0.01) were found to be significantly higher in the HF group (107.31 (mean) ± 9.55 (standard deviation, SD), 131.11 ± 5.29, 5.57 ± 0.58, and 3.05 ± 0.23, respectively) than in the non-HF group (102.07 ± 14.15, 128.85 ± 5.81, 5.29 ± 0.38, and 2.92 ± 0.23, respectively). However, cross-sectional area (CSA) of femur neck (p = 0.005) and femur shaft (p = 0.01) as well as cortical thickness (CT) of femur neck (p = 0.031) and femur shaft (p = 0.031) were found to be significantly lower in the HF group (1.93 ± 0.44, 3.18 ± 0.83, 0.11 ± 0.02, and 0.38 ± 0.09, respectively) than in the non-HF group (2.12 ± 0.46, 3.57 ± 0.78, 0.13 ± 0.03, and 0.47 ± 0.11, respectively). The HSA showed excellent sensitivity (82.4% to 90.2%). HSA is an important factor in predicting the occurrence of hip fracture. Therefore, not only should bone mineral density (BMD) be considered clinically, but it is also important to look closely at HSA for risk of hip fracture.
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Affiliation(s)
- Yong-Chan Ha
- Department of Orthopaedic Surgery, Chung-Ang University College of Medicine, Seoul 06974, Korea.
| | - Jun-Il Yoo
- Department of Orthopaedic Surgery, Gyeongsang National University Hospital, Jinju 52727, Korea.
| | - Jeongkyun Yoo
- Department of Orthopaedic Surgery, Gyeongsang National University College of Medicine, Jinju 52727, Korea.
| | - Ki Soo Park
- Institute of Health Sciences, Gyeongsang National University, Jinju 52727, Korea.
- Department of Preventive medicine, Gyeongsang National University School of Medicine, Jinju 52727, Korea.
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