DXA parameters, Trabecular Bone Score (TBS) and Bone Mineral Density (BMD), in fracture risk prediction in endocrine-mediated secondary osteoporosis

Osteoporosis is a common disease characterized by low bone mass (i.e. quantity) and altered bone microarchitecture (i.e. quality), resulting in decreased bone strength with an increased risk of fractures [1]. It is associated with an excess of mortality, a decrease in quality of life, and co-morbidities; and has a high social and economic burden, representing a major public health problem. Osteoporosis affects mostly postmenopausal women and fewer men. It is mainly related to the normal aging process— primary osteoporosis. Nevertheless, it can also occur due to secondary causes such as bone-affecting treatments, clinical disorders, or lifestyle habits—secondary osteoporosis [2]. Nine million osteoporotic fractures occur worldwide yearly [3]. The accurate identification of fracture risk, followed by relevant management, would reduce these numbers and the associated costs [4].

Bone mineral density (BMD), measured by dual X-ray absorptiometry (DXA), has been the gold standard for osteoporosis diagnosis in the absence of established fragility fractures [5]. BMD, a bone quantity parameter, is a major determinant of bone strength and fracture risk. Nevertheless, a considerable overlap (up to 45%) exists in BMD values between individuals who develop fractures and those who do not, suggesting that fracture risk prediction based solely on BMD is suboptimal [6]. Thus, the development of bone quality assessments has gained special interest to address this gap. Trabecular bone score (TBS) is one of the most widely used assessments of bone quality [7]. Both BMD and TBS are independent predictors of fragility fractures and are the two pillars of the World Health Organization’s (WHO) clinical definition of osteoporosis [1]. In this article, we review the role of DXA-derived parameters, BMD and TBS, with a special focus on TBS, in fracture risk prediction in endocrine-mediated secondary osteoporosis.

DXA is the most widely used technique and the gold standard for osteoporosis diagnosis and management [8‐10]. It is a simple, quick, painless, and safe examination, which uses very low doses of dual X-rays (considerably lower than those of an X-ray and a CT scan), hence it can be repeated safely over time. DXA acquisition can provide images for total body, hip, posterior–anterior (PA) lumbar spine (LS), and/or forearm. BMD (expressed in g/m²) is measured in well-defined regions of interest in these images. LS, total hip, femoral neck, and/or 1/3 radius BMD values are considered for the osteoporosis diagnosis and/or management. The decision on the use of each of them depends on factors, such as sex and age of the patient. For example, the PA LS is the preferred region for the BMD assessment in women up to 60 years and in men up to 65; the femoral neck and total hip are the chosen sites for BMD assessment in older individuals and/or in the presence of discrepancies or degenerations in the LS. Forearm (1/3 radius) is a backup site taken into consideration when the main sites (PA LS, total hip, and femoral neck) are impacted by certain health conditions such as hyperparathyroidism or obesity (exceeding the weight limit of the DXA device’s table).

The quantitative assessment of BMD is c’ompared with the average BMD value of a population of healthy young adults in the age of peak bone mass (young adult reference population). The number of standard deviations that the BMD differs from the BMD of the young adult reference population is indicated by the term BMD T-score. The WHO classification of osteoporosis is based on the lowest BMD T-score value from PA LS, total hip or femoral neck(or 1/3 radius for the specified scenarios): normal: BMD T-score greater or equal than −1; osteopenia: BMD T-score between −1 and −2.5; osteoporosis: BMD T-score equal or less than −2.5. This classification applies only to the BMD assessed by DXA. Extensive evidence supports the use of DXA BMD for osteoporosis diagnosis, prognosis, and follow-up, for fracture risk stratification and treatment initiation decision-making [11]. The importance of BMD testing, the skeletal sites to measure it, its report and interpretation, and the follow-up intervals between measurements, have been well-defined in several guidelines and taught worldwide by a combined course put together (Osteoporosis Essentials^®) by the International Osteoporosis Foundation (IOF) and the International Society of Clinical Densitometry (ISCD) [12, 13].

BMD is a measurement of high reliability and precision, able to predict osteoporotic fractures well in advance, and useful in osteoporotic patients‘ follow-up. Black et al. demonstrated that BMD and history of nonvertebral fracture could predict fractures in a period as long as 20–25 years in a large cohort of postmenopausal women [14]. The most widely used tool for fracture prediction, FRAX, provides the fracture probability for a period of 10 years [15]. An extended DXA measurement of the hip diaphysis is recommended in patients on long-term treatment with bisphosphonates in order to detect early signs of atypical femur fractures [16]. ISCD recommends the use of BMD as assessed by DXA for antiosteoporotic treatment follow-up [17].

An acknowledged drawback of DXA is its limited capability to assess bone health in type 2 diabetes mellitus (T2DM) patients [18‐20]. Although bone fragility is a known complication of diabetes, T2DM patients have normal or higher BMD levels as compared to non-diabetics. Napoli et al. [21] thoroughly describe the possible mechanisms that could explain this association: in vivo and ex vivo studies have shown the anabolic effect of insulin on osteoblasts, thus hyperinsulinemia in patients with T2DM might explain the high BMD levels; also, sclerostin levels are higher among T2DM and they are positively associated with BMD. Despite the normal or higher BMD values in diabetics as compared to non-diabetics, several studies [22‐24] have shown that low BMD values are associated with a higher risk of fracture in diabetics as compared to non-diabetics. Moreover, BMD is useful at antiosteoporotic treatment follow-up in diabetic patients [22‐25]. Other limitations of DXA are the overestimation of LS BMD as a consequence of degenerative changes in the spine or aortic calcification presence, and the influence of BMD by BMI or regional soft tissue presence [26, 27]. Armameto-Villareal et al. [28] has recently shown that weight loss among obese individuals is associated with bone loss as indicated by BMD values. However, BMD was negatively associated with the presence of fat tissue, indicating that the increase in body fat may increase systemic inflammation leading to frailty and poor bone quality. To address the increase in bone loss and eventual fracture risk in obese undergoing weight loss therapy, Armameto-Villareal et al. suggest a combination of aerobic and resistance exercise and calcium and vitamin D supplements. Other bone health assessments using bone density derived from high-resolution peripheral quantitative computed tomography (HR-pQCT) or other bone strength surrogates (such as bone turnover markers or advanced glycation end-products, etc.) in obese and diabetics have been shown useful at their overall bone health evaluation [29‐31].

Major improvements in DXA technologies over the years have enabled the assessment of bone health parameters other than BMD. For example, the improved spatial resolution (as low as 250 micrometers for some of DXA devices) allows the search for vertebral fractures (vertebral fracture assessment—VFA) and the assessment of trabecular bone texture (TBS) (further elaborated below). Different algorithms can also estimate structural parameters of hip geometry, such as femoral strength index, axis length, cross-sectional area, etc. (hip structural analysis—HSA) [32‐35].

Besides bone, DXA assesses parameters of muscle and fat [36]. Several authors reported the direct and indirect role of DXA in the follow-up of malabsorption conditions [37‐40]. In addition, recently, emerged more and more the key concept of the “modified functional muscle–bone unit”, in which BMD is strongly associated with either mass and quality of muscles, which are further correlated with fracture risk [41]. In this sense, DXA has been demonstrated useful in providing a precise assessment of the skeletal muscle mass, which is crucial in disorders such as sarcopenia or geriatric syndrome [42, 43]. Other parameters of body composition, indicating the presence and distribution of fat mass in different regions of the body are essential in the assessment and follow-up of health disorders associated with fat presence [44‐48].

An interesting recent study demonstrated that during weight-loss programs, BMI can not specify the fat distribution, with limited use of this datum; in contrast with DXA report, which is able to quantify the metabolic re-distribution of total and regional fat mass and visceral adipose tissue [49]. Another study compared the accuracy of six different osteoporosis risk assessment tools in a restricted group of women in Kuala Lumpur, further demosntrating the importance of DXA in such context [50].

TBS is a textural analysis resulting from a computed evaluation of pixel gray-level variations in previously obtained LS DXA images. It is an index of bone microarchitecture correlated with parameters of bone strength [51‐53]. Higher values of TBS indicate a better microarchitecture, whereas lower values indicate a degraded microarchitecture (Fig. 1). Studies have robustly shown that TBS predicts fractures independently of BMD and other clinical risk factors for fracture. The added value of the TBS to BMD in fracture risk assessment has been extensively documented in cross-sectional, prospective, and longitudinal studies [54] and endorsed by medical societies of bone field (IOF, the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis, and the ISCD) [55]. More recently, for regions where intervention guidelines are based solely on BMD T-score, an alternative approach for using TBS in clinical practice based upon a “risk-equivalent” offset adjustment to BMD T-score has been developed [56]. The early validations of this approach illustrate how TBS contributes to vertebral fracture risk assessment by increasing the specificity of the model (by about 20%) without compromising the sensitivity.

Several studies have also demonstrated the ability of TBS to predict fragility fractures in secondary osteoporosis caused by diabetes, PHPT, rheumatoid arthritis, adrenal incidentaloma, chronic kidney disease, long-term glucocorticoid therapy, HIV, or oncological conditions (Fig. 2) [2].