Quantitative imaging methods in osteoporosis
Review Article

Quantitative imaging methods in osteoporosis

Ling Oei1,2, Fjorda Koromani1,2, Fernando Rivadeneira1,2, M. Carola Zillikens1, Edwin H. G. Oei3

1Department of Internal Medicine, 2Department of Radiology & Nuclear Medicine, 3Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center, Rotterdam, The Netherlands

Correspondence to: Edwin H. G. Oei, MD, PhD. Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center, ’s-Gravendijkwal 230, 3015 CE Rotterdam, The Netherlands. Email: e.oei@erasmusmc.nl.

Abstract: Osteoporosis is characterized by a decreased bone mass and quality resulting in an increased fracture risk. Quantitative imaging methods are critical in the diagnosis and follow-up of treatment effects in osteoporosis. Prior radiographic vertebral fractures and bone mineral density (BMD) as a quantitative parameter derived from dual-energy X-ray absorptiometry (DXA) are among the strongest known predictors of future osteoporotic fractures. Therefore, current clinical decision making relies heavily on accurate assessment of these imaging features. Further, novel quantitative techniques are being developed to appraise additional characteristics of osteoporosis including three-dimensional bone architecture with quantitative computed tomography (QCT). Dedicated high-resolution (HR) CT equipment is available to enhance image quality. At the other end of the spectrum, by utilizing post-processing techniques such as the trabecular bone score (TBS) information on three-dimensional architecture can be derived from DXA images. Further developments in magnetic resonance imaging (MRI) seem promising to not only capture bone micro-architecture but also characterize processes at the molecular level. This review provides an overview of various quantitative imaging techniques based on different radiological modalities utilized in clinical osteoporosis care and research.

Keywords: Quantitative imaging; osteoporosis; radiography; dual-energy X-ray absorptiometry (DXA); computed tomography (CT); magnetic resonance imaging (MRI); positron emission tomography (PET)


Submitted Nov 26, 2016. Accepted for publication Dec 14, 2016.

doi: 10.21037/qims.2016.12.13


Introduction

Osteoporosis is characterized by a decreased bone mass and quality resulting in an increased fracture risk. Quantitative imaging methods are of utmost importance in the diagnosis and follow-up of treatment effects in osteoporosis. The World Health Organization’s (WHO) fracture risk assessment tool (FRAX®) is one of the well-established clinical risk score estimators enabling physicians to calculate the future risk of osteoporotic fractures in patients (1). Prior fracture (2-4) and bone mineral density (BMD) as quantitative parameters (5) are particularly strong predictors of future osteoporotic fractures. Therefore, when this information is available, these data can be entered into FRAX® along with epidemiological and clinical parameters to guide individualized therapeutic decision-making for patients. A high predicted risk justifies preventative treatment with anti-osteoporotic drugs. Although algorithms such as FRAX® represent major advances in clinical practice, clinicians should be aware that these calculations do not accommodate all known risk factors and there are more fracture determinants remaining to be discovered (6-8). Although FRAX® and the Garvan Fracture Risk Calculator provide estimates of which patients will sustain a fracture, these algorithms still underestimate observed fracture risk in at least half of patients (9). Also, there may be value in examining longitudinal follow-up assessments within a cohort over time, which is more feasible with objective quantitative measures. Ideally, we would like to expand our current diagnostic panels by more advanced imaging to facilitate precision medicine and, subsequently, further improve the customization of healthcare tailored to the individual patient. Experimental assessments for osteoporosis are being developed in the research setting by either post-processing of radiographic or DXA data or involving more advanced imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI) to appraise bone microarchitecture or bone geometry (i.e., biomechanical characteristics of a bone’s size and shape) (10-16). This review discusses quantitative imaging methods for osteoporosis as applied in clinical care and scientific research.


Radiography

Unlike qualitative assessments of radiographs mostly applied for the diagnosis and follow-up of fractures, the application of quantitative radiographic methods in osteoporosis is declining, because these techniques have largely been replaced by DXA, as will be discussed below. Nevertheless, this paragraph will provide a brief summary of several techniques available. It is well-known that osteoporosis in appendicular long bones such as the proximal femur can be evident by cortical thinning and alterations of the trabecular pattern, which can be classified semi-quantitatively using for example the Singh index (17). Early X-ray based techniques for quantification of bone loss include radiogrammetry and radiographic absorptiometry. Radiogrammetry is a measurement of the cortical thickness of long bones, which has been used particularly in peripheral sites such as in the metacarpals (18). In radiographic absorptiometry, an aluminium phantom is placed next to the region of interest during X-ray acquisition. Subsequently, BMD is calibrated relative to the density of the phantom (19). Pulkkinen et al. extracted several geometrical and trabecular parameters from plain pelvic radiographs and related these to hip fracture risk (20). It has also been shown that bone density- and structure-related parameters can be calculated from radiographs of the proximal tibia in cadavers (21) and in subjects with osteoarthritis (22).


BMD by dual-energy X-ray absorptiometry (DXA)

Clinical measurement of BMD by DXA is currently the most widespread method to diagnose osteoporosis and evaluate the risk of fracture. DXA at the lumbar spine and femoral neck (Figure 1A,B) to measure BMD is nowadays a routine investigation in osteoporosis. DXA-measured BMD accounts for 60–70% of the variation in bone strength (23) and each standard deviation (SD) decrease of BMD is associated with a two-fold increase in fracture risk (1,24). Other skeletal sites or modes of measurement which are used more frequently in research settings are for example: total body (Figure 1C), (distal) radius, and skull. The BMD measured is measured in g/cm2 but most commonly is expressed as the T-score, the number of SDs above or below the mean for a healthy 30-year-old adult of the same sex and ethnicity as the patient. Subsequently, osteoporosis is defined as a T-score ≤−2.5 and osteopenia as a T-score ≤−1.0 at any skeletal site. No upper reference value has been proposed, as the adverse health effects of having an increased BMD have been poorly studied. Intriguingly, the far majority of fractures occur in individuals without an abnormal clinically assessed BMD (24). Sensitivity and specificity for incident osteoporotic fractures are limited with an area under the ROC curve of 0.63 (25,26), as most fractures in the population distribution occur in mildly to moderately decreased BMD, i.e., osteopenia, or even at normal BMD values (24).

Figure 1 Example DXA images of the lumbar spine (A), femoral neck (B) and total body (C) with corresponding regions of interest in which BMD is measured. DXA, dual-energy X-ray absorptiometry; BMD, bone mineral density.

Moreover, several diseases are paradoxically known to be associated with a higher fracture risk despite a higher BMD, such as diabetes-related bone disease and degenerative disease (27,28). Theoretically, an individual with 5% higher femoral neck BMD would have a 10% decrease in fracture risk. Nonetheless, it has been shown that individuals with type 2 diabetes have 69% higher fracture risk than those without diabetes despite having higher BMD at the femoral neck and lumbar spine. Schwartz and colleagues established that the World Health Organization’s fracture risk assessment tool (FRAX®) underestimates osteoporotic fracture risk in individuals with diabetes (29); this is why diabetes as a risk factor should be considered for inclusion in future iterations of FRAX® (30). Intriguingly, subjects with lumbar disc degeneration (LDD) have systematically higher BMD at the lumbar spine, femoral neck, skull, and consequently, at the total body measurement. In spite of this systematically higher BMD, persons with LDD are at higher risk of osteoporotic fractures, particularly males in whom LDD seems more severe (31). These observations suggest that more parameters are needed to define osteoporosis and obtain a better fracture risk assessment.


DXA—additional parameters

In recent years, several additional quantitative parameters have been described that can be extracted from existing DXA imaging data. For example, hip structural analysis can be performed on DXA images (32-34). Parameters that can be derived include cross-sectional area (CSA), cross-sectional moment of inertia (CSMI), and the section modulus, and using appropriate assumptions, one can estimate endocortical width and the cortical thickness (35). CSMI, as an estimation of the resistance of bone to bending, is calculated according to the formula: ([periosteal diameter/2]4 − [medullary diameter/2]4) × π/4 (36). Section modulus is calculated as CSMI divided by the greater of the measured distances from the center of mass to the medial or lateral surface, and is a measure of bending and torsional strength (35).

The trabecular bone score (TBS) seems a promising quantitative imaging parameter in osteoporosis, to some extent independent of DXA-BMD (37). Whereas DXA-BMD is a measure of bone quantity, TBS provides information on the biomechanics and microarchitecture which reflects trabecular structure (Figure 2). It is a grey-level texture measurement that utilizes an experimental variogram of two-dimensional (2D) projection images by measuring the rate of local variation in grey levels within 2D projection images to approximate three-dimensional (3D) bone microarchitecture (38). TBS is less expensive and more easily accessible than CT or MRI for wide-spread clinical implementation or as an outcome in large research studies. The very first TBS reports showed applications for the prediction of fracture risk in osteoporosis (39-41), have added value in those individuals with bone density outside of the osteoporosis range (42) and monitoring of treatment effects (43,44), and similarly, TBS may find an application in other conditions such as primary hyperparathyroidism (45), hypercortisolism (46), rheumatoid arthritis (47), and diabetes-related bone disease (48). A major advantage is that it can be derived from DXA scans using dedicated post-processing software. A recent meta-analysis demonstrated that the hazard ratio per 1 SD decrease in TBS increases by 1.44 for major osteoporotic fractures and seems of additional predictive value independent of the current FRAX model (49). TBS may be recognized as an independent endophenotype of osteoporosis and may have potential to guide clinical decision making similar to DXA-BMD in the future, which again would justify investigations into the determinants of TBS.

Figure 2 iDXA images of the spine, L1–L4 level of two individuals (top and bottom row); while LS-BMD values are the same for both, LS-TBS in the second subject is clearly lower compared to the first subject, corresponding to deteriorated microarchitecture of the vertebral body. LS-TBS value is derived by an algorithm that analyzes the spatial organization of pixel intensity, which in turn corresponds to the differences in the X-ray absorption power of an osteoporotic bone versus a normal trabecular pattern. (Images partly adapted from http://www.medimapsgroup.com/product/technology/).

Quantitative ultrasound (QUS)

Over the past 30 years, ultrasonographic analysis, termed QUS, has been developed as a method of determining material properties of a variety of structures including the in vivo assessment of bone structure and fragility (50). In general, low-frequency ultrasonic velocity measurements are applied to the calcaneus without the use of ionizing radiation. Alternative peripheral sites to which QUS has been applied are the radius, tibiae and phalanges (51). Depending on the site of measurement, either of the two types of QUS is applied, i.e., horizontal transmission on the cortical layer of the bone, or longitudinal transmission measuring the speed of sound (52). The two main parameters are velocity of sound (VOS) and broadband ultrasound attenuation (BUA), and additional parameters obtained are stiffness index (SI), quantitative ultrasound index (QUI), amplitude-dependent speed of sound (AD-SOS), and estimated BMD (eBMD) (18,52). The speed of sound refers to the division of transmission time of the sound waves by the length of the body part studied in meter per second (m/s) (52). Broadband attenuation of sound refers to the energy which is absorbed by the tissues through which the sound waves are transmitted relative to the signal’s frequency expressed in dB/MHz (52).

A meta-analysis by Moayyeri et al. showed that QUS parameters of the heel are associated with risk of hip fracture with relative risks per 1 SD decrease of 1.69 (95% CI: 1.43–2.00) for BUA, 1.96 (95% CI: 1.64–2.34) for SOS, 2.26 (95% CI: 1.71–2.99) for SI and 1.99 (95% CI: 1.49–2.67) for QUI (53). Analyses in the Canadian Multicentre Osteoporosis Study have been described for three alternative skeletal sites (distal radius, tibia, and phalanx) with a follow-up duration of 5 years (54).


Computed tomography (CT)

There is still a need for additional and more refined radiological imaging investigations for osteoporosis such as assessments based on CT. CT is more costly and requires more ionizing radiation than DXA and conventional radiography, but has numerous advantages as reviewed below. It is believed that there are skeletal-site specific effects for fracture risk including different roles for cortical versus trabecular bone, justifying efforts to separately analyze these entities (55). Quantitative computed tomography (QCT) yields volumetric 3D measurements by utilizing low dose scan protocols on a standard CT scanner or by performing high resolution-peripheral quantitative computed tomography (HR-)pQCT with the use of a dedicated extremity scanner (56). This allows more sophisticated analysis of cortical and trabecular bone, the imaging of trabecular structure and the application of finite element analysis (FEA) to model bone strength biomechanically (57-59). pQCT is also used in exploratory analyses for muscle, measuring for instance muscle CSA, muscle density, and intramuscular adipose tissue, which may be related to sarcopenia (60). In addition to the disadvantage of ionizing radiation, the analysis of CT imaging data can be complex and requires specialized software.

QCT is most commonly applied to the spine, and typically lumbar vertebral elements are evaluated (Figure 3A,B); Other skeletal sites include the hip (Figure 3C,D,E) and the forearm (61). Simply measuring X-ray attenuation expressed as Hounsfield units (HU) to derive BMD has been evaluated (62,63), but ideally the tissue density of the analyzed volume is calibrated to units of equivalent concentration of a hydroxyapatite phantom in g/cm3 yielding the BMD values (64). Volumes of interest are defined and a distinction is made between cortical, trabecular and integral volumes (65). QCT-based vertebral bone measurements are associated with vertebral fractures (66,67), and may outperform DXA-based measurements (68). Several studies have been performed in the proximal femur showing a difference of FEA parameters between hip fracture and vertebral fracture cases versus controls (69-71).

Figure 3 Quantitative computed tomography (QCT) of the lumbar spine and the hip. Source image obtained in the lumbar spine of a 65-year-old female (A), with definition of region of interest in vertebra L3 yielding a BMD (68.4 mg/cc) in the osteoporotic range according to the guidelines of the American Board of radiologists (B). Source image obtained in the hip of a 76-year-old female (C), with definition of regions of interest in the left femoral neck (D) and subsequent bone mineral density (BMD) analysis showing normal bone densities (E). (Images courtesy of Thomas Link, MD PhD, University of California at San Francisco, Dept. of Radiology and Biomedical imaging).

HR-pQCT is applied to the tibia or (distal) radius with simultaneous scanning of a hydroxyapatite calibration phantom, obtaining measurements within trabecular and cortical compartments (12). In cortical bone, standard analysis comprises cortical thickness (Ct.Th) in mm, cortical porosity (Ct.Po) as a percentage relative to the cortical pore volume (Ct.Po.V), and cortical bone volume (Ct.BV) in mm3 (72,73). It has been shown that with increasing age most bone loss is cortical due to predominantly intracortical remodelling (74). This results in increased spatial distribution, number and size of pores (75). In trabecular bone, standard analysis includes quantifying structural properties of trabecular bone, such as bone volume fraction (BV/TV), which is derived from trabecular BMD (Tb.BMD), average number of trabeculae (Tb.N), average trabecular thickness (Tb.Th), and average trabecular separation (Tb.Sp) (76). Associations have been demonstrated for different HR-pQCT measurements at the tibia and radius for vertebral and any-type of fractures (77-81).

Volumetric assessments with HR-pQCT also have added value in complex phenotypes such as diabetic bone disease. DXA-based studies showed that type 2 diabetes patients with worse glycemic control have paradoxically higher BMD and thicker femoral cortices in narrower bones in spite of a higher fracture risk (82). A study using HR-pQCT reported that the cortical porosity in type 2 diabetic patients was up to twice that of controls at the radius (73). This supports the hypothesis that an inefficient redistribution of bone mass, accumulation of microcracks and cortical porosity reflecting impaired bone repair give rise to fragility in apparently “strong” bones on 2D assessments in inadequately controlled diabetes. Subsequently, Patsch et al. showed in a four-group comparison of type 2 diabetes patients with and without fragility fractures to controls with and without fractures that cortical porosity is specific to those type 2 diabetes patients that fracture (83). Moreover, an innovative investigation utilizing in vivo microindentation testing of the tibia showed that patients with type 2 diabetes have reduced serum markers of bone turnover and lower bone material strength than controls (84). In this same study the average glycemic level over the previous ten years was negatively correlated with bone material strength (84). It would be desirable to investigate these phenomena with (pQ)CT on a larger population scale. Medical evidence is still too limited to warrant large-scale implementation of CT in clinical practice at this point (85,86). In the future, diagnostics and therapeutics may separately target cortical versus trabecular bone compartments.


MRI

High-resolution (HR) MRI may help in directly or indirectly assessing the structure of bone (87). MRI is relatively more costly and time-consuming, and produces a lower spatial resolution than CT. However, a major advantage is that it does not require ionizing radiation. Furthermore, MRI has great potential for detailed characterization of bone at the micro-architectural and molecular level, as reviewed below.

Histomorphometry is the gold standard for assessing bone, because it is the only method for the direct analysis of bone cells and their activities (88). Yet, even in the clinical setting bone biopsies are rarely used to diagnose and manage patients with osteoporosis, because of their invasiveness (89). Molecular imaging, the in vivo characterization and measurement of biological processes at the cellular and molecular level, is being hailed as the next great advance for imaging (90). Technical improvements in MRI are necessary for human application, particularly with regard to maximizing signal-to-noise ratio and spatial resolution within clinically acceptable scan times. This is a prerequisite for the introduction into large-scale population imaging studies and clinical practice in the future to aid the analysis of a large variety of musculoskeletal disorders including osteoporosis.

Inferences can be made about trabecular bone structure from HR MRI. Osteoporosis patients with and without fractures compared to individuals without osteoporosis have been evaluated for different MRI-derived texture parameters of bone, and differences between these groups were demonstrated at the distal radius and calcaneus (91-93).

One of the few MRI-based studies in diabetic bone disease reported greater trabecular heterogeneity in subjects with type 2 diabetes mellitus than in healthy controls (94). More MRI studies in diabetic bone disease are necessary given the recent insights regarding the impact of diabetes on bone quality.

Indirect MRI methods used for evaluation of the bone structure include MRI spectroscopy aiming to visualize the osseous structure or the changes in the structure at a molecular level without the need of contrast agents. Proton-magnetic resonance spectroscopy (1H-MRS) is considered the MRI gold standard for bone marrow fat quantification, and point-resolved spectroscopy (PRESS) and stimulated echo acquisition mode (STEAM) single-voxel 1H-MRS pulse sequences have been commonly used for the characterization of the fat spectrum in the bone marrow at the pelvis, spine, and hip (95). Images are acquired using dedicated coils to detect and quantify frequency signals of water, lipids, and other metabolites, expressed as universal ppm (parts per million) units with evaluation of areas under the peaks. In addition to qualitative interpretation, (semi-)quantitative analysis is in use such as scaling of ratios to unsuppressed water or to noise (96,97). Increased emphasis on quantitative assessment instead of qualitative dichotomization of metabolite content by MRS has been advocated (98). Measurement quality and awareness of possible artifacts are important in MRS (99), and adequate distinction of the molecular peaks and regions of interest can be technically challenging (95); corrections can be applied to minimize confounding effects (100).

Direct methods include chemical shift imaging, diffusion-weighted imaging, and perfusion MRI. Chemical shift imaging aims to separately detect protons that process with similar yet slightly different frequencies, namely, those of water and fat (101). A study evaluating the reproducibility of signal intensity index (SII) measurements in healthy volunteers with MRI systems from different vendors and with different field strengths found intra- and inter-observer correlation coefficients ranging from 0.82 to 0.98 (102). In osteoporosis, the few studies performed until now have primarily assessed the bone marrow (103-105). Diffusion-weighted imaging measures the Brownian motion of water at a microscopic level and provides information on cellularity and cellular integrity expressed in the apparent diffusion coefficient (ADC) (101). A review article discussing diffusion-weighted imaging in musculoskeletal radiology has been published in this journal before (106). Also for diffusion-weighted imaging, most studies in osteoporosis have focused on the bone marrow (107-109). A few studies reported diffusion-weighted MR imaging parameters to be associated with BMD (110,111). One study has examined ADC values before and after vertebroplasty and found that high preoperative ADC was predictive of the occurrence of new compression fractures (112); replication studies are necessary. Different methods are used for perfusion imaging, of which the dynamic contrast-enhanced MRI (DCE-MRI) technique is the most commonly implemented (101). Possible analytical approaches to DCE-MRI data include time-intensity curves, enhancement patterns over time and pharmacokinetic modeling approaches to quantify blood flow. Quantitative outcomes of diffusion-weighted imaging and dynamic contrast-enhanced MRI have been reported to be different between acute osteoporotic vertebral fractures from normal appearing vertebrae (113). Furthermore, maximum enhancement [E(max)] and enhancement slope [E(slope)] are significantly decreased in osteoporosis in at least the femurs and vertebrae (114-118). Quantitative parameters of blood flow were studied with DCE-MRI in osteoporotic patients with acute vertebral fracture compared to a control group (119). Plasma flow (mL/100 mL/min) quantifies the volume of plasma flowing through the region of interest per unit time; plasma volume (mL/100 mL) corresponds to the volume of the plasma per tissue volume in the region of interest and extraction flow (mL/100 mL/min) characterizes the net flow between the plasma and the interstitial space (extracellular and extravascular space). These perfusion parameters were decreased in normal-appearing vertebral bone marrow of osteoporosis patients compared to controls, but they were found to increase in acute vertebral fractures.

A shortcoming of MRI is that, due to its short T2 relaxation time, no signal from cortical bone is acquired with conventional MRI pulse sequences (120). Hence, sequences with ultrashort echo time are needed to capture signals of those tissues which exhibit short T2 (e.g., cortical bones, tendons, ligaments, menisci and myelin) (121). This may be overcome with novel ultrashort or zero time to echo (UTE/ZTE) MRI techniques (Figure 4). 1H, being the most abundant isotope of hydrogen, is present in bone water and these signals can be acquired by aforementioned techniques. The 1H signal arises from different pools, distinguishable by their relaxation times. Relatively free water within large pores has the longest T2 relaxation times; water in small pores has greater surface to volume ratios, experiences greater surface relaxation and thus has a shorter T2 relaxation time (122). Protons bound to bone matrix are more tightly restricted in movement and have shorter T2 relaxation times. A variety of UTE pulse sequences have been developed capable of depicting signal from different water pools in bone (Figure 5) and quantitating the amount of water by means of T2* relaxometry. The field is making steps in translating experience from animal and cadaveric experiments to in vivo human studies (123-126). As bone water is present mainly in the pore system of bone, this parameter provides a surrogate measure for porosity, and it has been demonstrated that cortical bone water concentration is greater in postmenopausal women than in premenopausal women (127).

Figure 4 MRI of a cadaveric forearm. Cortical bone produces a signal void on a conventional fast-spin echo (FSE) sequence (A), while signal is detected from cortical bone with the use of an inversion recovery ultrashort echo time (IR UTE, TR/TI 300/120 ms) pulse sequence. MRI, magnetic resonance imaging. (Images courtesy of Jiang Du, PhD, University of California at San Diego, Dept. of Radiology).
Figure 5 Axial (1st row) and sagittal (2nd row) imaging of a cortical bone sample with 2D FSE (A,G), 2D GRE (B,H), 2D UTE (C,I), 2D IR-UTE (D,J), 3D UTE (E,K) and 3D IR-UTE (F,L) sequences. Free water in the Haversian canals is detected by both FSE, 2D and 3D UTE sequences. Both 2D and 3D IR-UTE show a relatively uniform bright signal, consistent with only bound water being detected. GRE shows little signal for both bound and free water in cortical bone. The bright signal in (B) corresponds to marrow fat (arrow). (Images courtesy of Jiang Du, PhD, University of California at San Diego, Dept. of Radiology).

Bone marrow fat imaging

Bone marrow fat may be affected by diseases such as osteoporosis and diabetic bone disease (128). The bone marrow fat volume can be measured (129). Further, bone marrow fat composition can be examined, regarding presence and types of hydrogen bonds, where unsaturated fats contain at least one double bond and saturated fats have the maximum number of hydrogens bonded to carbons. This can be evaluated with MRS, dual energy QCT (130,131), T1-weighted and occasionally T2-weighted MRI (132). The average coefficient of variation for vertebral bone marrow fat fraction on spectroscopy has been reported at 1.7% (97). The correlation between the marrow fat fraction obtained with MRS and that obtained with dual-energy CT has been reported as high as r=0.91 (133). Vertebral marrow fat content is significantly increased in osteoporosis compared to osteopenia or normal bone density as evaluated by higher fat fractions on MRS and lower ADC by diffusion weighted MR (134). An ancillary study in the population-based Age Gene/Environment Susceptibility (AGES) cohort found that higher marrow fat assessed by MRS correlated with lower trabecular BMD in women and higher marrow fat was associated with prevalent vertebral fracture in men (135). Validation of these results should be pursued.

Dixon quantitative chemical shift MRI (QCSI) relies on phase shifts created by fat-water resonance frequency differences to separate water from fat (136). Studies have reported good reproducibility for Dixon QCSI for measuring the bone marrow fat fraction in the L1–L4 vertebral bodies and this measurement seems independent of DXA-BMD (137).

A small study in subjects with disuse osteoporosis has demonstrated morphological changes in the bone marrow at the lower limb such as reinforcement of trabecular lines, subchondral fat content, signal intensity and vasculature (138). Further quantitative texture analysis on this subject in larger samples may be worthwhile.

Combined QCT and MRS studies have demonstrated that the prevalence of fragility fractures is associated with lower unsaturation levels and higher saturation levels of bone marrow fat, in which the participants with diabetes with fractures have the lowest marrow unsaturation and highest saturation (139). In contrast to controls without diabetes, higher mean vertebral bone marrow fat content is significantly correlated with visceral adipose tissue and HbA1C in persons with type 2 diabetes, representing worse metabolic profiles (140). The concept of high-saturated fat-associated adipose inflammation and insulin resistance has been proposed; however, underlying molecular mechanisms remain to be elucidated.


Positron emission tomography (PET)

Application of PET/CT in the field of osteoporosis is still limited. In certain clinical fracture cases where CT and MRI images are inconclusive in differentiating benign from malignant etiologies, PET/CT can be acquired, which can also discover additional skeletal or extra-skeletal metastases (141). The standardized uptake value (SUV), a dimensionless parameter, is commonly used as a relative measure of FDG tissue uptake with correction for the amount of injected FDG and the patient size (142). Further, bone fracture healing can be visualized by PET/CT, but this has predominantly been studied in animal models (143-146). Zooming in further, in 18F-Fluoride PET scanning it is believed that PET intensity reflects the activities of osteoblasts and osteoclasts, and at least in animal experiments, microdamage can be detected (147). Regional bone perfusion and turnover studies with bone turnover markers as a reference have been performed comparing different skeletal sites in treatment-naïve and patients with osteoporosis on treatment with various anti-osteoporotic agents (148-154). The long term precision reflected by the coefficients of variation (12.2–26.6%) and intraclass correlation (0.44–0.85) for 18F-Fluoride PET parameters has been reported to be equivalent to that observed for biochemical bone turnover markers (155). It has been hypothesized that PET/CT may be useful in atypical femoral fracture patients, but supportive research data is needed (156).

No reports on the utilization of PET/MRI in osteoporosis have been published to date. Neither has diabetic bone disease been studied with PET/MRI in humans; a small study comparing diabetic and healthy pigs found a significant inverse correlation between vertebral bone marrow glucose uptake and fat content (157). Nonetheless, the first PET/MRI studies to detect and characterize osseous metabolic abnormalities in osteoarthritis are being done where PET/MRI may detect metabolic abnormalities in subchondral bone, which appear normal on MRI (158). Development of MRI quantitative imaging techniques is an exciting area of research deserving further explorations.


Vertebral fractures

The occurrence of fracture is without doubt the most important clinical outcome in osteoporosis. Vertebral fractures may go misdiagnosed as the clinical presentation can be aspecific. Moreover, as two thirds of vertebral fractures do not give clinical symptoms, these may be only detected on radiological imaging (159). Nevertheless, vertebral fractures increase the risk of new vertebral fracture up to five-fold and the risk of other fragility fractures two- to four-fold (160). Drugs available for the treatment of osteoporosis are highly effective, with the most potent bisphosphonate zoledronic acid reducing the risk of vertebral fractures by 76% and of non-vertebral fractures by 24% (161). Therefore, another valuable evaluation in osteoporosis is vertebral fracture assessment (VFA) on mostly lateral DXA or radiography (Figure 6). Vertebral fractures can be detected on other modalities such as CT or MRI as well. The differentiation between vertebral fractures of benign and malignant etiologies has been reviewed elsewhere (162).

Figure 6 Vertebral fracture assessment (VFA) on lateral DXA demonstrates multiple wedge-shaped vertebral fractures in a patient with osteoporosis. DXA, dual-energy X-ray absorptiometry.

Fractures can be classified according to skeletal site and shape, and quantified according to the amount of height loss and the number of fractures. However, there is currently no gold standard for osteoporotic vertebral fracture diagnosis (163). Several radiological scoring methods exist, each using different criteria for diagnosing and grading fractures. These assessment methods for osteoporotic vertebral fractures including quantitative morphometry (QM) analyses have been reviewed extensively elsewhere (164,165). Frequently used are methods based on (semi) QM evaluating vertebral height (166) or the algorithm-based qualitative (ABQ) method (167) mainly judging endplate integrity regardless of vertebral height reduction. Further work is needed to reveal which of the discordant cases are actually clinically relevant; evaluating the predictive ability of the different definitions with different relevant outcomes like future non-vertebral and vertebral fractures, and mortality are desirable. All vertebral fractures are deformities, but not all vertebral deformities are fractures. There are a number of differential diagnoses that have to be considered in individuals with vertebral deformities (168), such as Scheuermann’s disease and degenerative changes (167). Scheuermann’s disease is a form of osteochondrosis of the spine of unknown etiology characterized by increased posterior rounding of the thoracic spine in association with structural deformity of the vertebral elements (169,170).

Phenotype definition is a cornerstone of epidemiological research into vertebral fracture risk to prevent bias hampering discoveries (171-173). Moreover, merely measuring vertebral heights in clinical practice frequently leads to misdiagnosis of fracture in non-osteoporotic conditions including Scheuermann’s disease (174-176). Simultaneous assessment of vertebral heights together with endplate integrity may correctly differentiate these cases. One of the major advantages of software-assisted QM is the level of detail of the data recording (165). If more evidence supporting the ABQ method will be put forward, it will be worthwhile to explore if endplate integrity can be captured in software-assisted assessments based on computer-based morphometric recognition. In addition to improvement of the radiological vertebral fracture definition by itself, clearer criteria for non-fracture deformities differential diagnosis are necessary. A clear and correct fracture definition is crucial, because vertebral fractures form an integral part of clinical decision making to initiate anti-osteoporotic drugs or to switch to more potent and expensive agents in case of fractures under current therapy.


Conclusions

This review has summarized quantitative imaging methods in osteoporosis, where current clinical practice most frequently utilizes assessments from DXA and conventional radiography. Correct interpretation is crucial as treatment decisions are taken based on these outcomes. Further technical developments are ongoing to expand the richness of data obtained from these modalities. Finally, potentially novel application of quantitative parameters from ultrasound, CT, MRI and PET are underway in clinical and research settings.


Acknowledgements

None.


Footnote

Conflicts of Interest: The authors have no conflicts of interest to declare.


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Cite this article as: Oei L, Koromani F, Rivadeneira F, Zillikens MC, Oei EH. Quantitative imaging methods in osteoporosis. Quant Imaging Med Surg 2016;6(6):680-698. doi: 10.21037/qims.2016.12.13

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