Biomedical Engineering Reference
In-Depth Information
insufficient bone formation during remodeling [6,7]. The pathogenesis has been
associated to dietary aspects [8], immobilization [9], hyper-parathyroidism [10], vi-
tamin D deficiency [11], alteration of biochemical markers like hormone [12,13] and
aging [14]. Regardless etiology, decreased bone mineral density renders the skeletal
system susceptibility to fracture, predominantly occurring at the hip [15], the vertebral
column [16] and wrist [17].
Early diagnosis allows for tertiary prevention, thus reducing the progression and
restricting osteoporosis-related complications. Several methods have been introduced
to act as a screening process, aiming to identify individuals who exhibit early signs of
loss in BMD and thus demonstrate osteopenia or osteoporosis. The dominating tech-
niques however, due to their nonintrusive nature, are DXA, CT and MRI [18,19].
Techniques like peripheral quantitative computed tomography (pQCT) may also be
accurate in measuring BMD at peripheral skeletal sites, exhibit however restrictions
that prohibit measurements at the proximal femur [20,21]. According to the World
Health Organization, osteopenia and osteoporosis are defined by the patient's bone
mass deviation, when compared to that of an average, young and healthy adult [22].
Even though DXA can accurately determine the minerals and lean soft tissue of the
examined area, the overall accuracy of the measurement is impaired by the subtrac-
tion of the indirectly calculated fat mass [23]. Furthermore, DXA results are repre-
sented as mass per area, thus not considering the anisotropy of the bone tissue. This
renders DXA as a quantitative and not qualitative index of the bone structure [24] and
thus associating DXA measurements to the apparent fracture risk, remains a complex
problem requiring heuristic data and FEA supported calculations.
In contrast to these restrictions, CT and MRI measurements can be used to recon-
struct an accurate volumetric data set of the examined bone structure, that can be used
further on as input to FEA software in order to calculate the strength characteristics of
the anatomy. This approach however, requires extensive data processing, thus being
rather time consuming.
In the present paper three noninvasive medical imaging techniques (DXA, CT and
MRI), with potential applications in correlating BMD in the femoral neck to the frac-
ture risk, will be examined. Their concepts strengths and limitations will be intro-
duced, followed by FEA simulations that can be employed, directly (CT and MRI) or
indirectly (DXA), as an indicator of fragility fracture risks.
2
Image Based Reconstruction of Bone Tissue to Determine Its
Strength Characteristics
2.1
CT Based Reconstruction
CT is capable of producing 2D images of various body structures, based on their abili-
ty to withstand the emitted X-radiation. As bone has a unique spectrum of X-ray per-
meability within the human body (ranging from 200 to 2000), it shades white in a CT
slice, thus allowing its relatively unhindered segmentation of the bone from soft tis-
sue, since no other body part exhibits overlapping CT numbers [25]. This results in a
2D outline of the scanned bone and the 3D data set, is generated by overlaying
consecutive measurements. Contemporary CT units facilitate slice spacing in the
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