Rationale, design and clinical performance of the mechanical response tissue analyser: a non-invasive technology for measurement of long bone bending stiffness

Fracture discrimination capability of ulnar flexural rigidity measured via Cortical Bone Mechanics Technology: study protocol for The STRONGER Study

Osteoporosis is characterized by low bone mass and structural deterioration of bone tissue, which leads to bone fragility (ie, weakness) and an increased risk for fracture. The current standard for assessing bone health and diagnosing osteoporosis is DXA, which quantifies areal BMD, typically at the hip and spine. However, DXA-derived BMD assesses only one component of bone health and is notably limited in evaluating the bone strength, a critical factor in fracture resistance. Although multifrequency vibration analysis can quickly and painlessly assay bone strength, there has been limited success in advancing a device of this nature. Recent progress has resulted in the development of Cortical Bone Mechanics Technology (CBMT), which conducts a dynamic 3-point bending test to assess the flexural rigidity (EI) of ulnar cortical bone. Data indicate that ulnar EI accurately estimates ulnar whole bone strength and provides unique and independent information about cortical bone compared to DXA-derived BMD. Consequently, CBMT has the potential to address a critical unmet need: Better identification of patients with diminished bone strength who are at high risk of experiencing a fragility fracture. However, the clinical utility of CBMT-derived EI has not yet been demonstrated. We have designed a clinical study to assess the accuracy of CBMT-derived ulnar EI in discriminating post-menopausal women who have suffered a fragility fracture from those who have not. These data will be compared to DXA-derived peripheral and central measures of BMD obtained from the same subjects. In this article, we describe the study protocol for this multi-center fracture discrimination study (The STRONGER Study).

Association between body mass index, bone bending strength, and BMD in young sedentary women

The rationale was to determine whether body mass index (BMI) is a predictor of bone bending strength and bone mineral density (BMD) in young sedentary women. Results show that BMI is not a predictor of bone bending strength and that young women with low BMI also have low BMD.

INTRODUCTION

The purpose of this study was to determine whether body mass index (BMI) is a predictor of tibial or ulnar bending strength and bone mineral density (BMD) in sedentary women.

METHODS

Sedentary women (n = 34), age 19-27 years, with low BMI (LBMI < 18.5 kg/m², n = 16), and normal or high BMI (NHBMI between 18.5 and 29.9 kg/m², n = 18) participated as study subjects. Study outcomes included tibial and ulnar bending strength (EI in Nm²) using a non-invasive mechanical response tissue analyzer (MRTA); BMD and bone mineral content (BMC) of the whole body (WB), femoral neck (FN), total hip (TH), lumbar spine 1-4 (LS1-4), and ulna; and bone turnover biomarkers.

RESULTS

The LBMI group have lower (p < 0.01) body weight [group difference (Δ) = 32.0%], lean mass (LM) (Δ = 23.1%), fat mass (FM) (Δ = 77.2%), and tibial bending strength (Δ = 22.0%), compared to the NHBMI. The LBMI group also have lower (all p < 0.025) BMC in WB (Δ = 19.9%), FN (Δ = 20.1%) and TH (Δ = 19.0%), compared to the NHMBI, not in BMD results. Multivariate regression analysis shows that significant predictors of tibial bending strength are tibia length (adjusted R² = .341), age (adjusted R² = .489), ulna BMD (adjusted R² = .536), and LM (adjusted R² = .580). BMI was positively correlated with tibial EI (p < 0.05), height, weight, FM, LM, body fat% (all p < 0.01), and BMD of WB, FN, TH, and LS 1-4 (p < 0.05 or < 0.01).

CONCLUSIONS

Our results show that BMI is not a significant predictor of tibial or ulnar bending strength in young sedentary women.

Improvements to mechanical response tissue analysis

Cortical Bone Mechanics Technology™ (CBMT) comprises certain improvements over a previous method known as Mechanical Response Tissue Analysis (MRTA). Both methods are dynamic 3-point bending tests intended for measuring the mechanical properties of cortical bone in living people. MRTA presented a theoretical potential for direct measurement of skeletal fragility, but it had acquired a reputation for error and fallen into disuse. We found sources of error in both MRTA data collection and data analysis. We describe here the fundamentals of MRTA, the major sources of error we found in MRTA, and our innovations for avoiding them. •Data collection at many sites across the mid-shaft of the ulna bone in the forearm.•Parameter estimation by fitting analytical complex compliance and stiffness transfer functions to empirical complex compliance and stiffness frequency response functions.•Optimization by selecting results from frequency response functions with the smallest deviations between fits to compliance and stiffness frequency response functions.

A new noninvasive mechanical bending test accurately predicts ulna bending strength in cadaveric human arms

BACKGROUND

High error rates in the prediction of fragility fractures by bone mineral density have motivated searches for better clinical indicators of bone strength, and the high incidence of non-hip, non-spine fractures has raised interest in cortical bone. The aim of this study was to assess the accuracy of Cortical Bone Mechanics Technology™. CBMT is a new non-invasive 3-point bending technique for measuring the mechanical properties of cortical bone in the ulnas of living humans.

METHODS

35 cadaveric human arms were obtained from small women and large men ranging widely in age (17 < Age < 99 years) and body size (14 < BMI < 40 kg/m²). Noninvasive CBMT measurements of the flexural rigidity of the ulna bones within these arms (EI_CBMT) were compared to measurements of EI by Quasistatic Mechanical Testing in the ulnas excised from those arms (EI_QMT). Ulna bending strength was also measured by QMT as the peak moment before fracture (M_peak). The open source BoneJ plugin to ImageJ image processing software was used to calculate cortical porosity (CP) in micro-computed tomography images of a 2 mm length of the mid-shaft of each fractured ulna, and the interosseous diameter (IOD) of each ulna was also measured in those images.

RESULTS

EI_CBMT measurements (13 < EI_CBMT < 97 Nm²) explained 99% of the variance in QMT measurements of ulna bending strength (11 < M_peak < 90 Nm), but EI_CBMT was biased high by 30% (p < 0.0001) relative to EI_QMT (11 < EI_QMT < 69 Nm²). After correcting this bias, EI_CBMT and EI_QMT measurements lay along the identity line (y = 1.00x, R² = 0.99, SEE = 3.1 Nm²). Predictions of M_peak by EI_CBMT were less accurate than predictions by EI_QMT (both R² = 0.99; SEE_CBMT = 5.9 Nm vs SEE_QMT = 4.5 Nm, F = 2.92, p = 0.001), but EI_CBMT predictions were substantially more accurate than those by IOD (R² = 0.79; SEE_IOD = 10.6 Nm, F = 3.30, p < 0.001) and CP (R² = 0.35; SEE_CP = 18.9 Nm, F = 10.45, p < 10^-9). Predictions by EI_CBMT were also more accurate than predictions by arm donor height (R² = 0.63; SEE = 14.3 Nm, F = 5.87, p < 10^-6), body weight (R² = 0.77; SEE = 11.1 Nm, F = 3.54, p < 0.001) and BMI (R² = 0.64; SEE = 14.1 Nm, F = 2.39, p < 0.01). In forward stepwise multiple regression beginning with EI_CBMT, only age explained any additional variance in ulna bending strength (ΔR² = 0.3%, F = 8.03, p = 0.008).

CONCLUSION

Noninvasive CBMT measurements of ulna EI explain 99% of individual differences in QMT measurements of ulna bending strength in cadaveric human arms.

Response to "Clinical Evaluation of Bone Strength and Fracture Risk"

We read with great interest the recent review by de Bakker et al that summarized the state of several existing and emerging technologies for estimating bone strength and fracture risk in vivo. Much of their review focused on how well the measurements of selected technologies predicted experimental measurements of bone strength by ex vivo quasistatic mechanical testing (QMT) and on how well they tracked changes in mechanical properties of bone. The authors noted that the association of many common skeletal health measurements (e.g., DXA measures of trabecular bone score and areal and volumetric BMD) are only moderately associated with bone strength. The authors did not include mechanical response tissue analysis (MRTA) in their review. MRTA is a dynamic mechanical bending test that uses a vibration analysis technique to make immediate, direct, functional measurements of the mechanical properties (mass, stiffness, and damping) of long bones in humans in vivo. In this article we note our interest in the ability of MRTA to detect large changes in bone stiffness that go undetected by DXA. We also highlight results of our proprietary improvements to MRTA technology that have resulted in unmatched accuracy in QMT-validated measurements of the bending stiffness and estimates of the bending strength (both R2 = 0.99) of human ulna bones. To distinguish our improved technique from the legacy MRTA technology, we refer to it as Cortical Bone Mechanics Technology (CBMT). Further research will determine whether such CBMT measurements are clinically useful.

Accuracy and reproducibility of bending stiffness measurements by mechanical response tissue analysis in artificial human ulnas

Osteoporosis is characterized by reduced bone strength, but no FDA-approved medical device measures bone strength. Bone strength is strongly associated with bone stiffness, but no FDA-approved medical device measures bone stiffness either. Mechanical Response Tissue Analysis (MRTA) is a non-significant risk, non-invasive, radiation-free, vibration analysis technique for making immediate, direct functional measurements of the bending stiffness of long bones in humans in vivo. MRTA has been used for research purposes for more than 20 years, but little has been published about its accuracy. To begin to investigate its accuracy, we compared MRTA measurements of bending stiffness in 39 artificial human ulna bones to measurements made by Quasistatic Mechanical Testing (QMT). In the process, we also quantified the reproducibility (i.e., precision and repeatability) of both methods. MRTA precision (1.0±1.0%) and repeatability (3.1 ± 3.1%) were not as high as those of QMT (0.2 ± 0.2% and 1.3+1.7%, respectively; both p<10(-4)). The relationship between MRTA and QMT measurements of ulna bending stiffness was indistinguishable from the identity line (p=0.44) and paired measurements by the two methods agreed within a 95% confidence interval of ± 5%. If such accuracy can be achieved on real human ulnas in situ, and if the ulna is representative of the appendicular skeleton, MRTA may prove clinically useful.