Factor of Risk for Fracture - Skeletal Aging and Osteoporosis: Biomechanics and Mechanobiology - page 142

The determination of muscle forces in vivo could improve the estimation of
bone loading in factor of risk studies. A common approach for estimating muscle
forces is the use of a biomechanical model that represents the musculoskeletal
anatomy and determines muscle forces using an optimization algorithm. Only one
study to date has used this approach in estimating loading for factor of risk [ 49 ].
Such models have been used to estimate forces on the proximal femur during gait
[ 30 ] and vertebral bodies during lifting tasks [ 1 ]. However, it is unknown if muscle
forces can be accurately determined during an event such as a fall using such
models. Nonetheless, future examinations of factor of risk may benefit from
improved estimation of muscle forces, and therefore skeletal loading, using more
complex biomechanical models.
Studies of factor of risk have not examined all relevant loading conditions,
particularly in the case of the spine. Vertebral factor of risk during a fall has not been
examined even though up to half of acute vertebral fractures occur during a fall
[ 11 , 22 , 51 ]. Moreover, in a finite element study, Matsumoto et al. [ 42 ] showed that
fracture force for L2 was significantly lower in a forward bending configuration than
in uniaxial compression of the vertebral body. Thus, while uniaxial loading has been
used in factor of risk studies of vertebral bodies, it may not be the most relevant
loading configuration for vertebral fracture. Finally, studies of factor of risk have
primarily focused on the L3 vertebral level, while clinically most vertebral fractures
occur at mid-thoracic (T7-T8) and thoraco-lumbar (T11-L1) locations [ 20 , 22 , 31 ,
40 , 43 ]. Studies examining the variation in vertebral strength, loading and factor of
risk at different spinal locations may provide additional insights.
Even in the distal forearm, where fractures are almost invariably caused by a
fall onto the hand and muscle forces may not play a significant role, there are other
possible loading conditions. All studies of factor of risk for forearm fracture have
used the data of Chiu and Robinovitch [ 9 ], based on a forward fall, to estimate
loading. However, only about 40-45% of falls that cause a distal forearm fracture
are in the forward direction, with about 40-45% backward, and about 15% to the
side [ 46 , 58 ]. Falls in these other directions could possibly produce different
loading conditions on the distal forearm than a forward fall.
Similar to the current limitations for estimates of skeletal loading, estimation of
bone strength for factor of risk in some studies has been based on relatively simple
approaches. Specifically, many studies have based strength on regression equations
relating strength to aBMD, which may not reflect all the aspects contributing to
whole bone strength. In comparison, a number of studies of factor of risk have
determined strength using state-of-the art QCT- or HR-pQCT-based finite element
models, including in the proximal femur [ 34 , 56 ], vertebral body [ 44 , 47 ] and
distal forearm [ 32 , 45 , 46 ]. This may be the best approach for determining in vivo
bone strength. Finite element models also have the advantage that strength can be
determined for multiple and complex loading conditions. However, strength
estimates from finite element analyses are greatly dependent on the imposed
boundary conditions, and future work could examine the effect of different
boundary conditions on the FEA-based strength estimates. As already noted ver-
tebral strength estimates are different when applying axial compression versus a