The bone strength is primarily dependent on Bone Mineral Density (BMD). Bone densitometry refers to the process of testing bone density at the reference axial sites: lumbar vertebrae and the femoral neck. A low BMD is an indication of potential fracture risk and, according to the guidelines of World Health Organization, the results of BMD testing are used to determine osteoporosis: based on a standard scale (T-Score) patients are classified into normal, osteopenic, and osteoporotic categories.
However, DXA is focused only on the average quantity of bone minerals and not on the bone micro-architecture quality, therefore DXA is not designed to predict the risk of fracture.
The gold standard technique is called dual-energy x-ray absorptiometry (DXA). During a DXA test, a x-ray tube is passed over spine and hip and the information is evaluated by a computer program that determines how much bone mass the patient has expressed in g/cm2.
Nevertheless, physicians are unable to assess the risk of bone loss due to the limitations of DXA, that is focused only on the average quantity of bone minerals and not on the bone micro-architecture quality and the potential impact of widespread testing of BMD on the burden of fractures is less than optimal also for the limited availability of bone densitometers due to the high cost of the devices and ionizing radiation exposure.
The actual effectiveness of DXA systems has been critically assessed taking into account the factors that can restrict its employment and/or affect its accuracy and precision levels.
First of all, because DXA scanners use two X-ray energies in the presence of three types of tissue (mineralized bone, lean tissue and adipose tissue), measurement errors due to non-uniform distribution of adipose tissues have been reported in literature. The typical uncertainty level associated to both hip and spine BMD measurements is around 0.060 g/cm2, which roughly corresponds to a relative error in the range 5-10% and this should be considered in evaluating the accuracy of DXA scanning.
Secondly, DXA outcome is strongly influenced by patient positioning, which should be carefully assessed by the technologist and double-checked by the clinician that interprets the test.
A further source of inaccuracy in DXA scans is represented by possible post-acquisition analysis errors. Actually, DXA software typically provides an automatic identification of the regions of interest (ROIs) within the target bone district, but the technologist should make manual adjustments in order to obtain a reliable outcome.
Quantitative ultrasound (QUS) is an alternative method introduced to evaluate skeletal integrity at easily accessible peripheral sites performed on the calcaneus (heel), wrist, phalanx and tibia. QUS techniques involve the generation of US pulses which are transmitted through or along the bone under investigation.
Ultrasound has a number of intrinsic advantages over established DXA method, namely low cost, lack of ionizing radiation exposure, minimal regulatory requirements, portability and bone micro-architecture properties provided alongside bone density.
Nevertheless, despite the huge amount of published data, the ISCD restricted the actual clinical diagnostic usefulness of QUS devices due to the low accuracy and the impossibility to perform scans at the spine and hip, the reference sites for the diagnosis of osteoporosis.
Innovative method overcomes all main DXA and QUS limitations in the diagnosis of osteoporosis.
R.E.M.S. (Radiofrequency Echographic Multi Spectrometry) technique overcomes all main QUS and DXA mentioned limitations related to tissue modeling approximation, patient positioning and image manual segmentation by providing highly accurate measurements.
In fact, patient positioning does not affect the BMD measurements, since inclination between incident US beam and target bone depends only on probe placement, and this operation is supported, firstly, by on-screen markers to facilitate the proper alignment between US beam and bone surface and, secondly, by the fully automatic selection of the frames with a suitable signal-to-noise (SNR) ratio.
Furthermore, the numbers of frames needed for a correct diagnosis is 1/25 of the actually acquired data: excess acquired data improve diagnostic reliability. This assures that diagnostic calculations are performed only on correctly acquired data, while the “noisy” frames are discarded: in case, the system could ask the operator to repeat the acquisition, but “noisy” frames and artefacts will be never used to provide an unreliable diagnostic output.
Finally, once data acquisition is complete, the whole process is fully automatic and there are no further sources of error that can affect measurement reproducibility. The proprietary technology has been developed to take into account only Region of Interest belonging to the targeted skeletal site and then tissues and processing models do not affect the diagnostic performances.