Osteoporosis is a degenerative bone disease that affects millions of people worldwide. The goal of this study was to test a new ultrasonic technique developed for clinical bone assessment called the backscatter amplitude decay constant (BADC). Ultrasonic backscatter measurements were performed on 97 volunteers at the left and right femoral necks using an ultrasonic imaging system (Terason T3000) equipped with a 3.5 MHz convex array transducer. The backscatter signals were analyzed to determine the backscatter amplitude decay constant (BADC), a parameter that measures the exponential decay in the amplitude of the backscatter signal. For comparison, additional ultrasonic measurements were performed at the left and right heels using an ultrasonometer (GE Achilles EXPII) to measure the stiffness index of the calcaneus. BADC demonstrated weak but statistically significant correlations with stiffness index (R < 0.25, p < 0.05). With further refinement of the measurement technique, BADC may be a useful parameter for ultrasonic bone assessment.
Introduction: Ultrasonic backscatter techniques are being developed to detect changes in bone caused by osteoporosis. The goal of this study was to evaluate the clinical utility of backscatter difference measurements at the femoral neck. Methods: Backscatter signals were acquired from the left and right femoral necks of 97 human volunteers using an ultrasonic imaging system (Terason T3000). The signals were analyzed to measure the normalized mean of the backscatter difference (nMBD), a quantity that represents the power difference between two portions of the same backscatter signal. Also, a bone sonometer (GE Achilles EXPII) was used to measure the stiffness index (SI) of the left and right heel bones. Results: Linear regression analysis was used to compare nMBD measurement at the femoral neck to SI measurements at the heel. A statistically significant (R ≥ 0.2) correlation was observed between nMBD and SI. Conclusion: These results suggest that nMBD is sensitive to naturally occurring variations in bone tissue, and thus may be able to detect larger changes in bone caused by osteoporosis.
The global impact of osteoporosis as a major public health problem has generated interest in developing ultrasonic techniques that can be used to screen populations for this bone disease. The goal of this study was to assess the relative performance of three ultrasonic backscatter parameters: apparent integrated backscatter (AIB), frequency slope of apparent backscatter (FSAB) and frequency intercept of apparent backscatter (FIAB). Measurements were performed at the left and right femoral necks of 88 healthy volunteers using an ultrasonic imaging system equipped with a 3 MHz convex multi-element transducer. Backscatter signals from the femoral neck were captured for analysis. AIB was determined from the frequency averaged power in the backscatter signal compensated for the frequency dependent response of the measurement system. FSAB and FIAB were determined from the slope and intercept, respectively, of a line fitted to the compensated spectrum. Linear regression analysis was used to compare measurements performed at the left and right femur. All three parameters demonstrated similar and highly significant (p < 0.000001) correlations between left and right side measurements (RAIB = 0.62, RFSAB = 0.56, RFIAB = 0.51) indicating that they are equally sensitive to naturally occurring variations in the ultrasonic properties of the femoral neck.
Ultrasonic backscatter may be able to detect changes in bone caused by osteoporosis. This study assesses the relative in vivo performance of three ultrasonic backscatter parameters: cortical-cancellous mean (CCM), cortical-cancellous slope (CCS), and cortical-cancellous intercept (CCI). Measurements were performed at the left and right femoral necks of 88 healthy volunteers. CCM was determined by frequency averaging the spectral power difference in decibels between echoes from the outer cortical surface and backscatter from underlying cancellous bone. CCS and CCI were determined from the slope and intercept, respectively, of a line fitted to the spectral power difference. Linear regression analysis was used to compare measurements performed at the left and right femur. CCM demonstrated highly significant ( p < 0.0001) correlations between left and right side measurements across nine choices of gate delay and width for analysis of both ten and thirty adjacent signals centered on the bone (0.41 < R < 0.53). CCS and CCI showed significant correlations only for five and three gate choices, respectively, for the ten signal analysis (0.001 < p < 0.05). These results indicate that CCM is sensitive to naturally occurring variations in bone tissue and may be sensitive to changes in bone tissue caused by osteoporosis.
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