Bone mineral density measurement in children and adolescents: Quantitative Ultrasound measurement (QUS)
The first generation of QUS systems characterized the bone tissue with the use of two relevant parameters: the speed of sound (SOS) and the attenuation of the signal [broadband ultrasound attenuation (BUA)]. The amount of attenuation depends on the structure, the specific acoustic properties of the medium, and the wavelength the ultrasound signal used. In performed in vivo ultrasound measurements, it is not possible to separate absorption from scattering what is resulting measurement of total attenuation. Generally, QUS devices provide a combined measurement nominated “stiffness” or “quantitative ultrasound index”. These parameters are calculated from both SOS and BUA values indirectly reflected information of strength as bone quality. Amplitude of the ultrasound signal decreases with the increase in bone porosity and lead to the identification of an amplitude-related measurement of SOS (AD-SOS).
Expressed in meters per seconds parameter is able to magnify the differences in SOS as measured in diverse bone status. SOS measured along cortical bone with little interference of soft tissue could also provide some relevant information about the biomechanical behavior of that kind of tissue as a whole, regarding all the matrix mineralization and the mi- crostructural factors of bone material quality together. Even when this approach is used it still needs to be validated. In sum up, QUS can be regarded as promising technique for improving noninvasively the resources of bone strength.
Limitations of bone mass measurements
Bone mass measurements obtained with DXA in children have the advantages of low cost, accuracy, and low radiation exposure. However, DXA is a projection technique, and its measurements are based on the two dimensional assessment of a three dimensional structure without taking to consideration potential changes in three skeletal functions: the size of the bone, the volume of the bone examined and its mineral density. In trial of solving these issues mathematical models were developed that account for the dimensions of the bone; as examples cross-sectional area of the vertebrae is shaped in them like a cube and long bones – like cylinder with a circular base. Similar formulas were proposed for the femur and the midradius. The potential inaccuracies of DXA measurements are related to lack of homogeneous distribution of soft tissues. Inhomogeneous fat distribution may influence DXA measurements by as much as 10%. The next source of error for DXA bone mineral analysis can be the use of inappropriate software for both the acquisition and the subsequent analysis of the data. It became obvious that only appropriate use of reference data necessitates comparison of the results of DXA examinations with different normative data sets. Another considerable error of DXA measurements is head density involvement in total body program .
Some resolution of DXA limitations are over passed by the use of CT but the cost and inaccessibility of CT scanners have markedly limited its use in bone measurements. It should be noted that when assessing the metaphyseal regions of the long bones by QCT trabecular bone measurements are influenced by cortical bone thickness due to beam-hardening effects or photon scattering. This error is especially prominent in pQCT evaluations of the radius. Medication you can afford cialis professional 20 mg
On the last, coming to QUS, despite extensive research, the question what it really measure when using this technique, still remains unanswered. SOS signals are greatly influenced by the material density of bone whereas BUA depends on many structural parameters that contribute to scattering and attenuation of sound waves. Also QUS measurements are limited to skeletal locations where the interference of soft tissue is minimal such as the calcis, the patella, and the phalanxes. In addition, no matter which techniques are used for measurement of bone mass, the development of proper reference data for its evaluation is crucial matter. Chronological age- and sex- matched normal values are not sufficient to correctly interpret the data. Important for evaluation are anthropometrical variables like: weight and height, but also skeletal age, and pubertal stage. Moreover, the functional association between muscle and bone through a regulatory mechanism (mechanostat) should be considered. Mechanostat theory suggests that the statistical association between LBM and BMC reflects a direct cause-and-ef- fect relationship. If muscle forces drive bone development, then analyses of muscle function should also be added to the armamentarium of clinicians diagnosing bone disorders. Many bone disorders may at least partly be due to muscle disuse or dysfunction, opening a new field of potential targets for therapeutic interventions.