Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyüan, Taiwan.
Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyüan, Taiwan.
Sci Rep. 2022 Jan 10;12(1):414. doi: 10.1038/s41598-021-04425-y.
Osteoporosis is a critical problem during aging. Ultrasound signals backscattered from bone contain information associated with microstructures. This study proposed using entropy imaging to collect the information in bone microstructures as a possible solution for ultrasound bone tissue characterization. Bone phantoms with different pounds per cubic foot (PCF) were used for ultrasound scanning by using single-element transducers of 1 (nonfocused) and 3.5 MHz (nonfocused and focused). Clinical measurements were also performed on lumbar vertebrae (L3 spinal segment) in participants with different ages (n = 34) and postmenopausal women with low or moderate-to-high risk of osteoporosis (n = 50; identified using the Osteoporosis Self-Assessment Tool for Taiwan). The signals backscattered from the bone phantoms and subjects were acquired for ultrasound entropy imaging by using sliding window processing. The independent t-test, one-way analysis of variance, Spearman correlation coefficient r, and the receiver operating characteristic (ROC) curve were used for statistical analysis. The results indicated that ultrasound entropy imaging revealed changes in bone microstructures. Using the 3.5-MHz focused ultrasound, small-window entropy imaging (side length: one pulse length of the transducer) was found to have high performance and sensitivity in detecting variation among the PCFs (r = - 0.83; p < 0.05). Small-window entropy imaging also performed well in discriminating young and old participants (p < 0.05) and postmenopausal women with low versus moderate-to-high osteoporosis risk (the area under the ROC curve = 0.80; cut-off value = 2.65; accuracy = 86.00%; sensitivity = 71.43%; specificity = 88.37%). Ultrasound small-window entropy imaging has great potential in bone tissue characterization and osteoporosis assessment.
骨质疏松症是衰老过程中的一个严重问题。从骨骼反向散射的超声信号包含与微观结构相关的信息。本研究提出使用熵成像来收集骨骼微观结构中的信息，作为超声骨组织特征描述的一种可能解决方案。使用 1MHz（非聚焦）和 3.5MHz（非聚焦和聚焦）的单元素换能器对具有不同每立方英尺磅数（PCF）的骨标本进行超声扫描。还对不同年龄（n=34）的参与者的腰椎（L3 脊柱段）和低危或中高危骨质疏松症的绝经后妇女（使用台湾骨质疏松症自我评估工具确定，n=50）进行了临床测量。通过使用滑动窗口处理，从骨标本和受试者中获取反向散射信号，用于超声熵成像。使用独立 t 检验、单因素方差分析、Spearman 相关系数 r 和接收者操作特征（ROC）曲线进行统计分析。结果表明，超声熵成像揭示了骨骼微观结构的变化。使用 3.5MHz 聚焦超声，小窗口熵成像（边长：换能器的一个脉冲长度）在检测 PCF 之间的变化方面表现出高性能和高灵敏度（r=-0.83；p<0.05）。小窗口熵成像在区分年轻和年老参与者以及低危与中高危骨质疏松症绝经后妇女方面也表现良好（p<0.05）（ROC 曲线下面积=0.80；截断值=2.65；准确率=86.00%；敏感度=71.43%；特异性=88.37%）。超声小窗口熵成像在骨组织特征描述和骨质疏松症评估方面具有很大的潜力。
