NDLI: Prediction of Biomechanical Properties of Trabecular Bone in MR Images With Geometric Features and Support Vector Regression

Content Provider	IEEE Xplore Digital Library
Author	Huber, M.B. Lancianese, S.L. Nagarajan, M.B. Ikpot, I.Z. Lerner, A.L. Wismuller, A.
Copyright Year	1964
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.
Sponsorship	IEEE Engineering in Medicine and Biology Society
Page Count	7
File Size	647802
Starting Page	1820
Ending Page	1826
File Format	PDF
ISSN	00189294
Volume Number	58
Issue Number	6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bones Stress Imaging Biomedical measurements Histograms Function approximation Feature extraction trabecular bone Biomechanical properties geometric features MR imaging supervised learning
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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