DocumentCode
3197121
Title
Investigation of repeatability in hip fracture risk predicted by DXA-based finite element model
Author
Yunhua Luo ; Leslie, William
Author_Institution
Dept. of Mech. Eng., Univ. of Manitoba, Winnipeg, MB, Canada
fYear
2013
fDate
3-7 July 2013
Firstpage
3171
Lastpage
3174
Abstract
DXA (dual energy X-ray absorptiometry) based finite element model is able to integrate all mechanical factors affecting hip fracture in osteoporosis patients and it is thus, in principle, more reliable than areal bone mineral density (BMD) for assessing fracture risk. However, short-term repeatability of DXA-based finite element model in predicting fracture risk has not yet been investigated and satisfactory repeatability is a prerequisite for the procedure to be applied in clinic. Therefore, in the reported research, the repeatability of a previously developed DXA-based patient-specific finite element procedure was investigated. It was found that inconsistence in positioning the patient during DXA scanning and manual segmentation of DXA image in constructing the finite element model are the two dominant factors affecting short-term repeatability of the finite element procedure. The study outcome indicated that to apply the finite element procedure in clinic, a set of more strict guidelines for positioning the patient in DXA scanning must be established and followed.
Keywords
X-ray absorption; biomechanics; bone; diseases; finite element analysis; fracture; image segmentation; medical image processing; BMD; DXA-based finite element model; bone mineral density; dual energy X-ray absorptiometry; hip fracture risk; image segementation; osteoporosis; repeatability; Bones; Finite element analysis; Hip; Image segmentation; Indexes; Minerals; Osteoporosis;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE
Conference_Location
Osaka
ISSN
1557-170X
Type
conf
DOI
10.1109/EMBC.2013.6610214
Filename
6610214
Link To Document