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Requist MR, Mills MK, Carroll KL, Lenz AL. Quantitative Skeletal Imaging and Image-Based Modeling in Pediatric Orthopaedics. Curr Osteoporos Rep 2024; 22:44-55. [PMID: 38243151 DOI: 10.1007/s11914-023-00845-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/19/2023] [Indexed: 01/21/2024]
Abstract
PURPOSE OF REVIEW Musculoskeletal imaging serves a critical role in clinical care and orthopaedic research. Image-based modeling is also gaining traction as a useful tool in understanding skeletal morphology and mechanics. However, there are fewer studies on advanced imaging and modeling in pediatric populations. The purpose of this review is to provide an overview of recent literature on skeletal imaging modalities and modeling techniques with a special emphasis on current and future uses in pediatric research and clinical care. RECENT FINDINGS While many principles of imaging and 3D modeling are relevant across the lifespan, there are special considerations for pediatric musculoskeletal imaging and fewer studies of 3D skeletal modeling in pediatric populations. Improved understanding of bone morphology and growth during childhood in healthy and pathologic patients may provide new insight into the pathophysiology of pediatric-onset skeletal diseases and the biomechanics of bone development. Clinical translation of 3D modeling tools developed in orthopaedic research is limited by the requirement for manual image segmentation and the resources needed for segmentation, modeling, and analysis. This paper highlights the current and future uses of common musculoskeletal imaging modalities and 3D modeling techniques in pediatric orthopaedic clinical care and research.
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Affiliation(s)
- Melissa R Requist
- Department of Orthopaedics, University of Utah, 590 Wakara Way, Salt Lake City, UT, 84108, USA
- Department of Biomedical Engineering, University of Utah, 36 S Wasatch Dr., Salt Lake City, UT, 84112, USA
| | - Megan K Mills
- Department of Radiology and Imaging Sciences, University of Utah, 30 N Mario Capecchi Dr. 2 South, Salt Lake City, UT, 84112, USA
| | - Kristen L Carroll
- Department of Orthopaedics, University of Utah, 590 Wakara Way, Salt Lake City, UT, 84108, USA
- Shriners Hospital for Children, 1275 E Fairfax Rd, Salt Lake City, UT, 84103, USA
| | - Amy L Lenz
- Department of Orthopaedics, University of Utah, 590 Wakara Way, Salt Lake City, UT, 84108, USA.
- Department of Biomedical Engineering, University of Utah, 36 S Wasatch Dr., Salt Lake City, UT, 84112, USA.
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Zhang B, Chen Z, Yan R, Lai B, Wu G, You J, Wu X, Duan J, Zhang S. Development and Validation of a Feature-Based Broad-Learning System for Opportunistic Osteoporosis Screening Using Lumbar Spine Radiographs. Acad Radiol 2024; 31:84-92. [PMID: 37495426 DOI: 10.1016/j.acra.2023.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 07/04/2023] [Accepted: 07/05/2023] [Indexed: 07/28/2023]
Abstract
RATIONALE AND OBJECTIVES Osteoporosis is primarily diagnosed using dual-energy X-ray absorptiometry (DXA); yet, DXA is significantly underutilized, causing osteoporosis, an underdiagnosed condition. We aimed to provide an opportunistic approach to screen for osteoporosis using artificial intelligence based on lumbar spine X-ray radiographs. MATERIALS AND METHODS In this institutional review board-approved retrospective study, female patients aged ≥50 years who received both X-ray scans and DXA of the lumbar vertebrae, in three centers, were included. A total of 1180 cases were used for training and 145 cases were used for testing. We proposed a novel broad-learning system (BLS) and then compared the performance of BLS models using radiomic features and deep features as a source of input. The deep features were extracted using ResNet18 and VGG11, respectively. The diagnostic performances of these BLS models were evaluated with the area under the curve (AUC), sensitivity, and specificity. RESULTS The incidence rate of osteoporosis in the training and test sets was 35.9% and 37.9%, respectively. The radiomic feature-based BLS model achieved higher testing AUC (0.802 vs. 0.654 vs. 0.632, both P = .002), sensitivity (78.2% vs. 56.4% vs. 50.9%), and specificity (82.2% vs. 74,4% vs. 75.6%) than the two deep feature-based BLS models. CONCLUSION Our proposed radiomic feature-based BLS model has the potential to expand osteoporosis screening to a broader population by identifying osteoporosis on lumbar spine X-ray radiographs.
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Affiliation(s)
- Bin Zhang
- Department of Radiology, The First Affiliated Hospital of Jinan University, No. 613 Huangpu West Road, Tianhe District, Guangzhou, Guangdong 510627, China (B.Z., R.Y., J.Y., X.W., S.Z.)
| | - Zhangtianyi Chen
- College of Information Science and Technology, Jinan University, Guangzhou, Guangdong, China (Z.C., B.L., G.W., J.D.)
| | - Ruike Yan
- Department of Radiology, The First Affiliated Hospital of Jinan University, No. 613 Huangpu West Road, Tianhe District, Guangzhou, Guangdong 510627, China (B.Z., R.Y., J.Y., X.W., S.Z.)
| | - Bifan Lai
- College of Information Science and Technology, Jinan University, Guangzhou, Guangdong, China (Z.C., B.L., G.W., J.D.)
| | - Guangheng Wu
- College of Information Science and Technology, Jinan University, Guangzhou, Guangdong, China (Z.C., B.L., G.W., J.D.)
| | - Jingjing You
- Department of Radiology, The First Affiliated Hospital of Jinan University, No. 613 Huangpu West Road, Tianhe District, Guangzhou, Guangdong 510627, China (B.Z., R.Y., J.Y., X.W., S.Z.)
| | - Xuewei Wu
- Department of Radiology, The First Affiliated Hospital of Jinan University, No. 613 Huangpu West Road, Tianhe District, Guangzhou, Guangdong 510627, China (B.Z., R.Y., J.Y., X.W., S.Z.)
| | - Junwei Duan
- College of Information Science and Technology, Jinan University, Guangzhou, Guangdong, China (Z.C., B.L., G.W., J.D.); Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization, Jinan University, Guangzhou, Guangdong, China (J.D.)
| | - Shuixing Zhang
- Department of Radiology, The First Affiliated Hospital of Jinan University, No. 613 Huangpu West Road, Tianhe District, Guangzhou, Guangdong 510627, China (B.Z., R.Y., J.Y., X.W., S.Z.).
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Johnson LG, Bortolussi-Courval S, Chehil A, Schaeffer EK, Pawliuk C, Wilson DR, Mulpuri K. Application of statistical shape modeling to the human hip joint: a scoping review. JBI Evid Synth 2023; 21:533-583. [PMID: 36705052 PMCID: PMC9994808 DOI: 10.11124/jbies-22-00175] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
OBJECTIVE The objective of this scoping review was to identify all examples of the application of statistical shape models to the human hip joint, with a focus on applications, population, methodology, and validation. INTRODUCTION Clinical radiographs are the most common imaging tool for management of hip conditions, but it is unclear whether radiographs can adequately diagnose or predict outcomes of 3D deformity. Statistical shape modeling, a method of describing the variation of a population of shapes using a small number of variables, has been identified as a useful tool to associate 2D images with 3D anatomy. This could allow clinicians and researchers to validate clinical radiographic measures of hip deformity, develop new ones, or predict 3D morphology directly from radiographs. In identifying all previous examples of statistical shape modeling applied to the human hip joint, this review determined the prevalence, strengths, and weaknesses, and identified gaps in the literature. INCLUSION CRITERIA Participants included any human population. The concept included development or application of statistical shape models based on discrete landmarks and principal component analysis. The context included sources that exclusively modeled the hip joint. Only peer-reviewed original research journal articles were eligible for inclusion. METHODS We searched MEDLINE, Embase, Cochrane CENTRAL, IEEE Xplore, Web of Science Core Collection, OCLC PapersFirst, OCLC Proceedings, Networked Digital Library of Theses and Dissertations, ProQuest Dissertations and Theses Global, and Google Scholar for sources published in English between 1992 and 2021. Two reviewers screened sources against the inclusion criteria independently and in duplicate. Data were extracted by 2 reviewers using a REDCap form designed to answer the review study questions, and are presented in narrative, tabular, and graphical form. RESULTS A total of 104 sources were considered eligible based on the inclusion criteria. From these, 122 unique statistical shape models of the human hip were identified based on 86 unique training populations. Models were most often applied as one-off research tools to describe shape in certain populations or to predict outcomes. The demographics of training populations were skewed toward older patients in high-income countries. A mean age between 60 and 79 years was reported in 29 training populations (34%), more than reported in all other age groups combined, and 73 training populations (85%) were reported or inferred to be from Europe and the Americas. Only 4 studies created models in a pediatric population, although 15 articles considered shape variation over time in some way. There were approximately equal numbers of 2D and 3D models. A variety of methods for labeling the training set was observed. Most articles presented some form of validation such as reporting a model's compactness (n = 71), but in-depth validation was rare. CONCLUSIONS Despite the high volume of literature concerning statistical shape models of the human hip, there remains a need for further research in key areas. We identified the lack of models in pediatric populations and low- and middle-income countries as a notable limitation to be addressed in future research.
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Affiliation(s)
- Luke G Johnson
- School of Biomedical Engineering, Faculty of Applied Science, University of British Columbia, Vancouver, BC, Canada.,Centre for Hip Health and Mobility, Vancouver, BC, Canada
| | - Sara Bortolussi-Courval
- School of Biomedical Engineering, Faculty of Applied Science, University of British Columbia, Vancouver, BC, Canada.,Department of Mechanical Engineering, Faculty of Applied Science, University of British Columbia, Vancouver, BC, Canada
| | - Anjuli Chehil
- Department of Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Emily K Schaeffer
- Department of Orthopaedics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.,Department of Orthopaedic Surgery, BC Children's Hospital, Vancouver, BC, Canada
| | - Colleen Pawliuk
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - David R Wilson
- Centre for Hip Health and Mobility, Vancouver, BC, Canada.,Department of Orthopaedics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Kishore Mulpuri
- Department of Orthopaedics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.,Department of Orthopaedic Surgery, BC Children's Hospital, Vancouver, BC, Canada.,BC Children's Hospital Research Institute, Vancouver, BC, Canada
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Wang F, Zheng L, Theopold J, Schleifenbaum S, Heyde CE, Osterhoff G. Methods for bone quality assessment in human bone tissue: a systematic review. J Orthop Surg Res 2022; 17:174. [PMID: 35313901 PMCID: PMC8935787 DOI: 10.1186/s13018-022-03041-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 03/02/2022] [Indexed: 02/07/2023] Open
Abstract
Background For biomechanical investigations on bone or bone implants, bone quality represents an important potential bias. Several techniques for assessing bone quality have been described in the literature. This study aims to systematically summarize the methods currently available for assessing bone quality in human bone tissue, and to discuss the advantages and limitations of these techniques. Methods A systematic review of the literature was carried out by searching the PubMed and Web of Science databases from January 2000 to April 2021. References will be screened and evaluated for eligibility by two independent reviewers as per PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Studies must apply to bone quality assessment with imaging techniques, mechanical testing modalities, and compositional characterization. The terms used for the systematic search were: “(bone quality”. Ti,ab.) AND “(human bone specimens)”. Results The systematic review identified 502 relevant articles in total. Sixty-eight articles met the inclusion criteria. Among them, forty-seven articles investigated several imaging modalities, including radiography, dual-energy X-ray absorptiometry (DEXA), CT-based techniques, and MRI-based methods. Nineteen articles dealt with mechanical testing approaches, including traditional testing modalities and novel indentation techniques. Nine articles reported the correlation between bone quality and compositional characterization, such as degree of bone mineralization (DBM) and organic composition. A total of 2898 human cadaveric bone specimens were included. Conclusions Advanced techniques are playing an increasingly important role due to their multiple advantages, focusing on the assessment of bone morphology and microarchitecture. Non-invasive imaging modalities and mechanical testing techniques, as well as the assessment of bone composition, need to complement each other to provide comprehensive and ideal information on the bone quality of human bone specimens. Supplementary Information The online version contains supplementary material available at 10.1186/s13018-022-03041-4.
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Affiliation(s)
- Fangxing Wang
- ZESBO - Center for Research On Musculoskeletal Systems, Department of Orthopedic Surgery, Traumatology and Plastic Surgery, Leipzig University, Semmelweisstraße 14, 04103, Leipzig, Germany. .,Department of Orthopedic Surgery, Traumatology and Plastic Surgery, Leipzig University, Liebigstraße 20 Haus 4, 04103, Leipzig, Germany.
| | - Leyu Zheng
- Department of Orthopedic Surgery, Traumatology and Plastic Surgery, Leipzig University, Liebigstraße 20 Haus 4, 04103, Leipzig, Germany
| | - Jan Theopold
- Department of Orthopedic Surgery, Traumatology and Plastic Surgery, Leipzig University, Liebigstraße 20 Haus 4, 04103, Leipzig, Germany
| | - Stefan Schleifenbaum
- ZESBO - Center for Research On Musculoskeletal Systems, Department of Orthopedic Surgery, Traumatology and Plastic Surgery, Leipzig University, Semmelweisstraße 14, 04103, Leipzig, Germany
| | - Christoph-Eckhard Heyde
- Department of Orthopedic Surgery, Traumatology and Plastic Surgery, Leipzig University, Liebigstraße 20 Haus 4, 04103, Leipzig, Germany
| | - Georg Osterhoff
- Department of Orthopedic Surgery, Traumatology and Plastic Surgery, Leipzig University, Liebigstraße 20 Haus 4, 04103, Leipzig, Germany
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Abstract
Aims Assessment of bone mineral density (BMD) with dual-energy X-ray absorptiometry (DXA) is a well-established clinical technique, but it is not available in the acute trauma setting. Thus, it cannot provide a preoperative estimation of BMD to help guide the technique of fracture fixation. Alternative methods that have been suggested for assessing BMD include: 1) cortical measures, such as cortical ratios and combined cortical scores; and 2) aluminium grading systems from preoperative digital radiographs. However, limited research has been performed in this area to validate the different methods. The aim of this study was to investigate the evaluation of BMD from digital radiographs by comparing various methods against DXA scanning. Methods A total of 54 patients with distal radial fractures were included in the study. Each underwent posteroanterior (PA) and lateral radiographs of the injured wrist with an aluminium step wedge. Overall 27 patients underwent routine DXA scanning of the hip and lumbar spine, with 13 undergoing additional DXA scanning of the uninjured forearm. Analysis of radiographs was performed on ImageJ and Matlab with calculations of cortical measures, cortical indices, combined cortical scores, and aluminium equivalent grading. Results Cortical measures showed varying correlations with the forearm DXA results (range: Pearson correlation coefficient (r) = 0.343 (p = 0.251) to r = 0.521 (p = 0.068)), with none showing statistically significant correlations. Aluminium equivalent grading showed statistically significant correlations with the forearm DXA of the corresponding region of interest (p < 0.017). Conclusion Cortical measures, cortical indices, and combined cortical scores did not show a statistically significant correlation to forearm DXA measures. Aluminium-equivalent is an easily applicable method for estimation of BMD from digital radiographs in the preoperative setting. Cite this article: Bone Joint Res 2021;10(12):830–839.
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Affiliation(s)
- Greg Robertson
- Department of Orthopaedics and Trauma, University of Edinburgh Division of Clinical and Surgical Sciences, Edinburgh, UK.,Department of Orthopaedic Surgery, Queen Elizabeth University Hospital, Glasgow, UK
| | - Robert Wallace
- Department of Orthopaedics and Trauma, University of Edinburgh Division of Clinical and Surgical Sciences, Edinburgh, UK
| | - A Hamish R W Simpson
- Department of Orthopaedics and Trauma, University of Edinburgh Division of Clinical and Surgical Sciences, Edinburgh, UK
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Fujii M, Aoki T, Okada Y, Mori H, Kinoshita S, Hayashida Y, Hajime M, Tanaka K, Tanaka Y, Korogi Y. Prediction of Femoral Neck Strength in Patients with Diabetes Mellitus with Trabecular Bone Analysis and Tomosynthesis Images. Radiology 2016; 281:933-939. [DOI: 10.1148/radiol.2016151657] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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7
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Quantification of differences in bone texture from plain radiographs in knees with and without osteoarthritis. Osteoarthritis Cartilage 2014; 22:1724-31. [PMID: 25278081 PMCID: PMC4587537 DOI: 10.1016/j.joca.2014.06.021] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2013] [Revised: 05/26/2014] [Accepted: 06/22/2014] [Indexed: 02/02/2023]
Abstract
OBJECTIVE To quantify differences in bone texture between subjects with different stages of knee osteoarthritis (OA) and age- and gender-matched controls from plain radiographs using advanced image analysis methods. DESIGN Altogether 203 knees were imaged using constant X-ray parameters and graded according to Kellgren-Lawrence (KL) grading scale (KL0: n = 110, KL1: n = 28, KL2: n = 27, KL3: n = 31, KL4: n = 7). Bone density-related and structure-related parameters were calculated from medial and lateral tibial subchondral bone plate and trabecular bone and from femur. Density-related parameters were derived from grayscale values and structure-related parameters from Laplacian- and local binary patterns (LBP)-based images. RESULTS Reproducibilities of structure-related parameters were better than bone density-related parameters. Bone density-related parameters were significantly (P < 0.05) higher in KL2-4 groups than in control group (KL0) in medial tibial subchondral bone plate and trabecular bone. LBP-based structure parameters differed significantly between KL0 and KL2-4 groups in medial subchondral bone plate, between KL0 and KL1-4 groups in medial and lateral trabecular bone, and between KL0 and KL1-4/KL2-4 in medial and lateral femur. Laplacian-based parameters differed significantly between KL0 and KL2-4 groups in medial side regions-of-interest (ROIs). CONCLUSIONS Our results indicate that the changes in bone texture in knee OA can be quantitatively evaluated from plain radiographs using advanced image analysis. Based on the results, increased bone density can be directly estimated if the X-ray imaging conditions are constant between patients. However, structural analysis of bone was more reproducible than direct evaluation of grayscale values, and is therefore better suited for quantitative analysis when imaging conditions are variable.
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Thevenot J, Hirvasniemi J, Pulkkinen P, Määttä M, Korpelainen R, Saarakkala S, Jämsä T. Assessment of risk of femoral neck fracture with radiographic texture parameters: a retrospective study. Radiology 2014; 272:184-91. [PMID: 24620912 DOI: 10.1148/radiol.14131390] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
PURPOSE To investigate whether femoral neck fracture can be predicted retrospectively on the basis of clinical radiographs by using the combined analysis of bone geometry, textural analysis of trabecular bone, and bone mineral density (BMD). MATERIALS AND METHODS Formal ethics committee approval was obtained for the study, and all participants gave informed written consent. Pelvic radiographs and proximal femur BMD measurements were obtained in 53 women aged 79-82 years in 2006. By 2012, 10 of these patients had experienced a low-impact femoral neck fracture. A Laplacian-based semiautomatic custom algorithm was applied to the radiographs to calculate the texture parameters along the trabecular fibers in the lower neck area for all subjects. Intra- and interobserver reproducibility was calculated by using the root mean square average coefficient of variation to evaluate the robustness of the method. RESULTS The best predictors of hip fracture were entropy (P = .007; reproducibility coefficient of variation < 1%), the neck-shaft angle (NSA) (P = .017), and the BMD (P = .13). For prediction of fracture, the area under the receiver operating characteristic curve was 0.753 for entropy, 0.608 for femoral neck BMD, and 0.698 for NSA. The area increased to 0.816 when entropy and NSA were combined and to 0.902 when entropy, NSA, and BMD were combined. CONCLUSION Textural analysis of pelvic radiographs enables discrimination of patients at risk for femoral neck fracture, and our results show the potential of this conventional imaging method to yield better prediction than that achieved with dual-energy x-ray absorptiometry-based BMD. The combination of the entropy parameter with NSA and BMD can further enhance predictive accuracy.
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Affiliation(s)
- Jérôme Thevenot
- From the Department of Medical Technology (J.T., J.H., P.P., M.M., R.K., S.S., T.J.) and Institute of Health Sciences (R.K.), University of Oulu, PO Box 5000, Oulu 90014, Finland; Department of Sports and Exercise Medicine, Oulu Deaconess Institute, Oulu, Finland (R.K.); Institute of Health Sciences (R.K.) and Department of Diagnostic Radiology (S.S., T.J.), Medical Research Center Oulu, Oulu University Hospital and University of Oulu (J.T., J.H., P.P., M.M., R.K., S.S., T.J.)
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Yang CC, Nagarajan MB, Huber MB, Carballido-Gamio J, Bauer JS, Baum T, Eckstein F, Lochmüller E, Majumdar S, Link TM, Wismüller A. Improving bone strength prediction in human proximal femur specimens through geometrical characterization of trabecular bone microarchitecture and support vector regression. JOURNAL OF ELECTRONIC IMAGING 2014; 23:013013. [PMID: 24860245 PMCID: PMC4030629 DOI: 10.1117/1.jei.23.1.013013] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
We investigate the use of different trabecular bone descriptors and advanced machine learning tech niques to complement standard bone mineral density (BMD) measures derived from dual-energy x-ray absorptiometry (DXA) for improving clinical assessment of osteoporotic fracture risk. For this purpose, volumes of interest were extracted from the head, neck, and trochanter of 146 ex vivo proximal femur specimens on multidetector computer tomography. The trabecular bone captured was characterized with (1) statistical moments of the BMD distribution, (2) geometrical features derived from the scaling index method (SIM), and (3) morphometric parameters, such as bone fraction, trabecular thickness, etc. Feature sets comprising DXA BMD and such supplemental features were used to predict the failure load (FL) of the specimens, previously determined through biomechanical testing, with multiregression and support vector regression. Prediction performance was measured by the root mean square error (RMSE); correlation with measured FL was evaluated using the coefficient of determination R2. The best prediction performance was achieved by a combination of DXA BMD and SIM-derived geometric features derived from the femoral head (RMSE: 0.869 ± 0.121, R2: 0.68 ± 0.079), which was significantly better than DXA BMD alone (RMSE: 0.948 ± 0.119, R2: 0.61 ± 0.101) (p < 10-4). For multivariate feature sets, SVR outperformed multiregression (p < 0.05). These results suggest that supplementing standard DXA BMD measurements with sophisticated femoral trabecular bone characterization and supervised learning techniques can significantly improve biomechanical strength prediction in proximal femur specimens.
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Affiliation(s)
- Chien-Chun Yang
- University of Rochester, Departments of Imaging Sciences and Biomedical Engineering, Rochester, New York 14627
| | - Mahesh B. Nagarajan
- University of Rochester, Departments of Imaging Sciences and Biomedical Engineering, Rochester, New York 14627
| | - Markus B. Huber
- University of Rochester, Departments of Imaging Sciences and Biomedical Engineering, Rochester, New York 14627
| | - Julio Carballido-Gamio
- University of California San Francisco, Musculoskeletal and Quantitative Imaging Research, Department of Radiology and Biomedical Imaging, San Francisco, California 94143
| | - Jan S. Bauer
- Technische Universität München, Institut Für Röntgendiagnostik, Munich, München 85748, Germany
| | - Thomas Baum
- Technische Universität München, Institut Für Röntgendiagnostik, Munich, München 85748, Germany
| | - Felix Eckstein
- Paracelsus Medical University Salzburg, Institute of Anatomy and Musculoskeletal Research, Salzburg 5020, Austria
| | - Eva Lochmüller
- Paracelsus Medical University Salzburg, Institute of Anatomy and Musculoskeletal Research, Salzburg 5020, Austria
| | - Sharmila Majumdar
- University of California San Francisco, Musculoskeletal and Quantitative Imaging Research, Department of Radiology and Biomedical Imaging, San Francisco, California 94143
| | - Thomas M. Link
- University of California San Francisco, Musculoskeletal and Quantitative Imaging Research, Department of Radiology and Biomedical Imaging, San Francisco, California 94143
| | - Axel Wismüller
- University of Rochester, Departments of Imaging Sciences and Biomedical Engineering, Rochester, New York 14627
- University of Munich, Department of Radiology, München 80539, Germany
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Thevenot J, Hirvasniemi J, Finnilä M, Pulkkinen P, Kuhn V, Link T, Eckstein F, Jämsä T, Saarakkala S. Trabecular homogeneity index derived from plain radiograph to evaluate bone quality. J Bone Miner Res 2013; 28:2584-91. [PMID: 23677814 DOI: 10.1002/jbmr.1987] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2013] [Revised: 05/02/2013] [Accepted: 05/06/2013] [Indexed: 11/06/2022]
Abstract
Radiographic texture analysis has been developed lately to improve the assessment of bone architecture as a determinant of bone quality. We validate here an algorithm for the evaluation of trabecular homogeneity index (HI) in the proximal femur from hip radiographs, with a focus on the impact of the principal compressive system of the trabecular bone, and evaluate its correlation with femoral strength, bone mineral density (BMD), and volumetric trabecular structure parameters. A semiautomatic custom-made algorithm was applied to calculate the HI in the femoral neck and trochanteric areas from radiographs of 178 femoral bone specimens (mean age 79.3 ± 10.4 years). Corresponding neck region was selected in CT scans to calculate volumetric parameters of trabecular structure. The site-specific BMDs were assessed from dual-energy X-ray absorptiometry (DXA), and the femoral strength was experimentally tested in side-impact configuration. Regression analysis was performed between the HI and biomechanical femoral strength, BMD, and volumetric parameters. The correlation between HI and failure load was R(2) = 0.50; this result was improved to R(2) = 0.58 for cervical fractures alone. The discrimination of bones with high risk of fractures (load <3000 N) was similar for HI and BMD (AUC = 0.87). Regression analysis between the HIs versus site-specific BMDs yielded R(2) = 0.66 in neck area, R(2) = 0.60 in trochanteric area, and an overall of R(2) = 0.66 for the total hip. Neck HI and BMD correlated significantly with volumetric structure parameters. We present here a method to assess HI that can explain 50% of an experimental failure load and determines bones with high fracture risk with similar accuracy as BMD. The HI also had good correlation with DXA and computed tomography-derived data.
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Affiliation(s)
- Jérôme Thevenot
- Department of Medical Technology, University of Oulu, Oulu, Finland
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11
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Radiographic bone texture analysis is correlated with 3D microarchitecture in the femoral head, and improves the estimation of the femoral neck fracture risk when combined with bone mineral density. Eur J Radiol 2013; 82:1494-8. [DOI: 10.1016/j.ejrad.2013.04.042] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2013] [Revised: 03/28/2013] [Accepted: 04/19/2013] [Indexed: 11/21/2022]
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Le Corroller T, Pithioux M, Chaari F, Rosa B, Parratte S, Maurel B, Argenson JN, Champsaur P, Chabrand P. Bone texture analysis is correlated with three-dimensional microarchitecture and mechanical properties of trabecular bone in osteoporotic femurs. J Bone Miner Metab 2013; 31:82-8. [PMID: 22886379 DOI: 10.1007/s00774-012-0375-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2012] [Accepted: 06/26/2012] [Indexed: 01/23/2023]
Abstract
Fracture of the proximal femur is a major public health problem in elderly persons. It has recently been suggested that combining texture analysis and bone mineral density measurement improves the failure load prediction in human femurs. In this study, we aimed to compare bone texture analysis with three-dimensional (3D) microarchitecture and mechanical properties of trabecular bone in osteoporotic femurs. Eight femoral heads from osteoporotic patients who fractured their femoral neck provided 31 bone cores. Bone samples were studied using a new high-resolution digital X-ray device (BMA™, D3A Medical Systems) allowing for texture analysis with fractal parameter H (mean), and were examined using micro-computed tomography (microCT) for 3D microarchitecture. Finally, uniaxial compression tests to failure were performed to estimate failure load and apparent modulus of bone samples. The fractal parameter H (mean) was strongly correlated with bone volume fraction (BV/TV) (r = 0.84) and trabecular thickness (Tb.Th) (r = 0.91) (p < 0.01). H (mean) was also markedly correlated with failure load (r = 0.84) and apparent modulus (r = 0.71) of core samples (p < 0.01). Bone volume fraction (BV/TV) and trabecular thickness (Tb.Th) demonstrated significant correlations with failure load (r = 0.85 and 0.72, respectively) and apparent modulus (r = 0.72 and 0.64, respectively) (p < 0.01). Overall, the best predictors of failure load were H (mean), bone volume fraction, and trabecular thickness, with r (2) coefficients of 0.83, 0.76, and 0.80 respectively. This study shows that the fractal parameter H (mean) is correlated with 3D microCT parameters and mechanical properties of femoral head bone samples, which suggests that radiographic texture analysis is a suitable approach for trabecular bone microarchitecture assessment in osteoporotic femurs.
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Affiliation(s)
- Thomas Le Corroller
- Radiology Department, Hôpital Sainte-Marguerite, 270 Boulevard de Sainte-Marguerite, 13009, Marseille, France.
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Kolta S, Paratte S, Amphoux T, Persohn S, Campana S, Skalli W, Paternotte S, Argenson JN, Bouler JM, Gagey O, Roux C. Bone texture analysis of human femurs using a new device (BMA™) improves failure load prediction. Osteoporos Int 2012; 23:1311-6. [PMID: 21656265 DOI: 10.1007/s00198-011-1674-2] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2010] [Accepted: 05/09/2011] [Indexed: 10/18/2022]
Abstract
UNLABELLED We measured bone texture parameters of excised human femurs with a new device (BMA™). We also measured bone mineral density by DXA and investigated the performance of these parameters in the prediction of failure load. Our results suggest that bone texture parameters improve failure load prediction when added to bone mineral density. INTRODUCTION Bone mineral density (BMD) is a strong determinant of bone strength. However, nearly half of the fractures occur in patients with BMD which does not reach the osteoporotic threshold. In order to assess fracture risk properly, other factors are important to be taken into account such as clinical risk factors as well as macro- and microarchitecture of bone. Bone microarchitecture is usually assessed by high-resolution QCT, but this cannot be applied in routine clinical settings due to irradiation, cost and availability concerns. Texture analysis of bone has shown to be correlated to bone strength. METHODS We used a new device to get digitized X-rays of 12 excised human femurs in order to measure bone texture parameters in three different regions of interest (ROIs). We investigated the performance of these parameters in the prediction of the failure load using biomechanical tests. Texture parameters measured were the fractal dimension (Hmean), the co-occurrence matrix, and the run length matrix. We also measured bone mineral density by DXA in the same ROIs as well as in standard DXA hip regions. RESULTS The Spearman correlation coefficient between BMD and texture parameters measured in the same ROIs ranged from -0.05 (nonsignificant (NS)) to 0.57 (p = 0.003). There was no correlation between Hmean and co-occurrence matrix nor Hmean and run length matrix in the same ROI (r = -0.04 to 0.52, NS). Co-occurrence matrix and run length matrix in the same ROI were highly correlated (r = 0.90 to 0.99, p < 0.0001). Univariate analysis with the failure load revealed significant correlation only with BMD results, not texture parameters. Multiple regression analysis showed that the best predictors of failure load were BMD, Hmean, and run length matrix at the femoral neck, as well as age and sex, with an adjusted r (2) = 0.88. Added to femoral neck BMD, Hmean and run length matrix at the femoral neck (without the effect of age and sex) improved failure load prediction (compared to femoral neck BMD alone) from adjusted r (2) = 0.67 to adjusted r (2) = 0.84. CONCLUSION Our results suggest that bone texture measurement improves failure load prediction when added to BMD.
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Affiliation(s)
- S Kolta
- Rheumatology Department, Cochin Hospital, Paris Descartes University, Paris, France.
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Mintzopoulos D, Ackerman JL, Song YQ. MRI of trabecular bone using a decay due to diffusion in the internal field contrast imaging sequence. J Magn Reson Imaging 2012; 34:361-71. [PMID: 21780229 DOI: 10.1002/jmri.22612] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
PURPOSE To characterize the DDIF (Decay due to Diffusion in the Internal Field) method using intact animal trabecular bone specimens of varying trabecular structure and porosity, under ex vivo conditions closely resembling in vivo physiological conditions. The DDIF method provides a diffusion contrast which is related to the surface-to-volume ratio of the porous structure of bones. DDIF has previously been used successfully to study marrow-free trabecular bone, but the DDIF contrast hitherto had not been tested in intact specimens containing marrow and surrounded by soft tissue. MATERIALS AND METHODS DDIF imaging was implemented on a 4.7 Tesla (T) small-bore, horizontal, animal scanner. Ex vivo results on fresh bone specimens containing marrow were obtained at body temperature. Control measurements were carried out in surrounding tissue and saline. RESULTS Significant DDIF effect was observed for trabecular bone samples, while it was considerably smaller for soft tissue outside the bone and for lipids. Additionally, significant differences were observed between specimens of different trabecular structure. CONCLUSION The DDIF contrast is feasible despite the reduction of the diffusion constant and of T(1) in such conditions, increasing our confidence that DDIF imaging in vivo may be clinically viable for bone characterization.
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Affiliation(s)
- Dionyssios Mintzopoulos
- Athinoula A Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts 02129, USA.
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Abdominal tumor characterization and recognition using superior-order cooccurrence matrices, based on ultrasound images. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2012; 2012:348135. [PMID: 22312411 PMCID: PMC3270540 DOI: 10.1155/2012/348135] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/02/2011] [Accepted: 09/18/2011] [Indexed: 11/30/2022]
Abstract
The noninvasive diagnosis of the malignant tumors is an important issue in research nowadays. Our purpose is to elaborate computerized, texture-based methods for performing computer-aided characterization and automatic diagnosis of these tumors, using only the information from ultrasound images. In this paper, we considered some of the most frequent abdominal malignant tumors: the hepatocellular carcinoma and the colonic tumors. We compared these structures with the benign tumors and with other visually similar diseases. Besides the textural features that proved in our previous research to be useful in the characterization and recognition of the malignant tumors, we improved our method by using the grey level cooccurrence matrix and the edge orientation cooccurrence matrix of superior order. As resulted from our experiments, the new textural features increased the malignant tumor classification performance, also revealing visual and physical properties of these structures that emphasized the complex, chaotic structure of the corresponding tissue.
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Le Corroller T, Halgrin J, Pithioux M, Guenoun D, Chabrand P, Champsaur P. Combination of texture analysis and bone mineral density improves the prediction of fracture load in human femurs. Osteoporos Int 2012; 23:163-9. [PMID: 21739104 DOI: 10.1007/s00198-011-1703-1] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2011] [Accepted: 06/16/2011] [Indexed: 01/23/2023]
Abstract
UNLABELLED Twenty-one excised femurs were studied using (1) a high-resolution digital X-ray device to estimate three textural parameters, (2) dual-energy X-ray absorptiometry (DXA) to measure bone mineral density (BMD), and (3) mechanical tests to failure. Textural parameters significantly correlated with BMD (p < 0.05) and bone strength (p < 0.05). Combining texture parameters and BMD significantly improved the fracture load prediction from adjusted r(2) = 0.74 to adjusted r(2) =0.82 (p < 0.05). INTRODUCTION The purpose of this study is to determine if the combination of bone texture parameters using a new high-resolution X-ray device and BMD measurement by DXA provided a better prediction of femoral failure load than BMD evaluation alone. METHODS The proximal ends of 21 excised femurs were studied using (1) a high-resolution digital X-ray device (BMA, D3A Medical Systems) to estimate three textural parameters: fractal parameter Hmean, co-occurrence, and run-length matrices, (2) DXA to measure BMD, and (3) mechanical tests to failure in a side-impact configuration. Regions of interest in the femoral neck, intertrochanteric region, and greater trochanter were selected for DXA and bone texture analysis. Every specimen was scanned twice with repositioning before mechanical testing to assess reproducibility using intraclass correlation coefficient (ICC) with 95% confidence interval. The prediction of femoral failure load was evaluated using multiple regression analysis. RESULTS Thirteen femoral neck and 8 intertrochanteric fractures were observed with a mean failure load of 2,612 N (SD, 1,382 N). Fractal parameter Hmean, co-occurrence, and run-length matrices each significantly correlated with site-matched BMD (p < 0.05) and bone strength (p < 0.05). The ICC of the textural parameters varied between 0.65 and 0.90. Combining bone texture parameters and BMD significantly improved the fracture load prediction from adjusted r(2) =0.74 to adjusted r(2) = 0.82 (p < 0.05). CONCLUSION In these excised femurs, the combination of bone texture parameters with BMD demonstrated a better performance in the failure load prediction than that of BMD alone.
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Affiliation(s)
- T Le Corroller
- Department of Radiology, Hôpital Sainte Marguerite, 270 Boulevard de Sainte Marguerite, 13009 Marseille, France.
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Schmah T, Marwan N, Thomsen JS, Saparin P. Long range node-strut analysis of trabecular bone microarchitecture. Med Phys 2011; 38:5003-11. [PMID: 21978044 DOI: 10.1118/1.3622600] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE We present a new morphometric measure of trabecular bone microarchitecture, called mean node strength (NdStr), which is part of a newly developed approach called long range node-strut analysis. Our general aim is to describe and quantify the apparent "latticelike" microarchitecture of the trabecular bone network. METHODS Similar in some ways to the topological node-strut analysis introduced by Garrahan et al. [J. Microsc. 142, 341-349 (1986)], our method is distinguished by an emphasis on long-range trabecular connectivity. Thus, while the topological classification of a pixel (after skeletonization) as a node, strut, or terminus, can be determined from the 3 × 3 neighborhood of that pixel, our method, which does not involve skeletonization, takes into account a much larger neighborhood. In addition, rather than giving a discrete classification of each pixel as a node, strut, or terminus, our method produces a continuous variable, node strength. The node strength is averaged over a region of interest to produce the mean node strength of the region. RESULTS We have applied our long range node-strut analysis to a set of 26 high-resolution peripheral quantitative computed tomography (pQCT) axial images of human proximal tibiae acquired 17 mm below the tibial plateau. We found that NdStr has a strong positive correlation with trabecular volumetric bone mineral density (BMD). After an exponential transformation, we obtain a Pearson's correlation coefficient of r = 0.97. Qualitative comparison of images with similar BMD but with very different NdStr values suggests that the latter measure has successfully quantified the prevalence of the "latticelike" microarchitecture apparent in the image. Moreover, we found a strong correlation (r = 0.62) between NdStr and the conventional node-terminus ratio (Nd∕Tm) of Garrahan et al. The Nd∕Tm ratios were computed using traditional histomorphometry performed on bone biopsies obtained at the same location as the pQCT scans. CONCLUSIONS The newly introduced morphometric measure allows a quantitative assessment of the long-range connectivity of trabecular bone. One advantage of this method is that it is based on pQCT images that can be obtained noninvasively from patients, i.e., without having to obtain a bone biopsy from the patient.
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Affiliation(s)
- Tanya Schmah
- Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada
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Harrison LCV, Nikander R, Sikiö M, Luukkaala T, Helminen MT, Ryymin P, Soimakallio S, Eskola HJ, Dastidar P, Sievänen H. MRI texture analysis of femoral neck: Detection of exercise load-associated differences in trabecular bone. J Magn Reson Imaging 2011; 34:1359-66. [PMID: 21954096 DOI: 10.1002/jmri.22751] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2010] [Accepted: 07/19/2011] [Indexed: 12/23/2022] Open
Abstract
PURPOSE To assess the ability of co-occurrence matrix-based texture parameters to detect exercise load-associated differences in MRI texture at the femoral neck cross-section. MATERIALS AND METHODS A total of 91 top-level female athletes representing five differently loading sports and 20 referents participated in this cross-sectional study. Axial T1-weighted FLASH and T2*-weighted MEDIC sequence images of the proximal femur were obtained with a 1.5T MRI. The femoral neck trabecular bone at the level of the insertion of articular capsule was divided manually into regions of interest representing four anatomical sectors (anterior, posterior, superior, and inferior). Selected co-occurrence matrix-based texture parameters were used to evaluate differences in apparent trabecular structure between the exercise loading groups and anatomical sectors of the femoral neck. RESULTS Significant differences in the trabecular bone texture, particularly at the superior femoral neck, were observed between athletes representing odd-impact (soccer and squash) and high-magnitude exercise loading (power-lifting) groups and the nonathletic reference group. CONCLUSION MRI texture analysis provides a quantitative method for detecting and classifying apparent structural differences in trabecular bone that are associated with specific exercise loading.
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Affiliation(s)
- Lara C V Harrison
- Tampere University Medical School, Tampere, Finland; Department of Biomedical Engineering, Tampere University of Technology, Tampere, Finland; Medical Imaging Centre, Tampere University Hospital, Tampere, Finland.
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Huber MB, Nagarajan MB, Leinsinger G, Eibel R, Ray LA, Wismüller A. Performance of topological texture features to classify fibrotic interstitial lung disease patterns. Med Phys 2011; 38:2035-44. [DOI: 10.1118/1.3566070] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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Huber MB, Lancianese SL, Nagarajan MB, Ikpot IZ, Lerner AL, Wismuller A. Prediction of biomechanical properties of trabecular bone in MR images with geometric features and support vector regression. IEEE Trans Biomed Eng 2011; 58:1820-6. [PMID: 21356612 DOI: 10.1109/tbme.2011.2119484] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Whole knee joint MR image datasets were used to compare the performance of geometric trabecular bone features and advanced machine learning techniques in predicting biomechanical strength properties measured on the corresponding ex vivo specimens. Changes of trabecular bone structure throughout the proximal tibia are indicative of several musculoskeletal disorders involving changes in the bone quality and the surrounding soft tissue. Recent studies have shown that MR imaging also allows non-invasive 3-D characterization of bone microstructure. Sophisticated features like the scaling index method (SIM) can estimate local structural and geometric properties of the trabecular bone and may improve the ability of MR imaging to determine local bone quality in vivo. A set of 67 bone cubes was extracted from knee specimens and their biomechanical strength estimated by the yield stress (YS) [in MPa] was determined through mechanical testing. The regional apparent bone volume fraction (BVF) and SIM derived features were calculated for each bone cube. A linear multiregression analysis (MultiReg) and a optimized support vector regression (SVR) algorithm were used to predict the YS from the image features. The prediction accuracy was measured by the root mean square error (RMSE) for each image feature on independent test sets. The best prediction result with the lowest prediction error of RMSE = 1.021 MPa was obtained with a combination of BVF and SIM features and by using SVR. The prediction accuracy with only SIM features and SVR (RMSE = 1.023 MPa) was still significantly better than BVF alone and MultiReg (RMSE = 1.073 MPa). The current study demonstrates that the combination of sophisticated bone structure features and supervised learning techniques can improve MR-based determination of trabecular bone quality.
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Affiliation(s)
- Markus B Huber
- Department of Imaging Sciences, University of Rochester, NY 14627, USA.
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