Targeting cortical bone state by quantitative in-vivo ultrasound imaging

通过定量体内超声成像瞄准皮质骨状态

• 批准号: 506408593
• 负责人: Professor Dr. Kay Raum
• 金额: --
• 依托单位: CharitéCentrum für Biomedizin (CC4)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/506408593?language=en
• 关键词: Targeting; cortical; bone; state; quantitative

Osteoporosis (OP) is one of the most important global health problems of our aging population. The majority of individuals who have sustained an osteoporosis-related fracture or who are at high risk of fracture are not diagnosed as osteoporotic according to the current gold standard to predict bone status (bone mineral density BMD measured with dual energy x-ray absorptiometry DXA). The mechanical integrity of cortical bone (~80% of the human skeleton mass) is a key factor of bone strength at several anatomical sites. As a consequence of an unbalanced intracortical remodeling some large pores appear, leading to a characteristic change of the pore size distribution, increased cortical porosity (Ct.Po) and reduced thickness (Ct.Th). These structural alterations together with compromised viscoelastic tissue matrix properties dramatically reduce bone strength. In a previous bi-national DFG-ANR project “TaCoSound” (2015-2018) a systematic ex-vivo survey of bone properties in human tibia and proximal femur and their associations with proximal femur stiffness and ultimate strength has been conducted. During the past 2 years, the applicant and international collaboration partners proposed original quantitative in-vivo ultrasound US imaging modalities to i) assess sound velocity (resembling Ct.Po and viscoelastic tissue properties) and Ct.Th from refraction-corrected ultrasound images of the cortical bone shell, and ii) to assess from the "spectral fingerprint" of acoustic waves backscattered from cortical pores the respective pore size distribution. The present project builds on TaCoSound and recent findings suggesting that the majority (82%) of variations of proximal femur strength can be predicted by Ct.Th (69%) and the prevalence of large pores (18%) in the tibia midshaft. Promising ex-vivo and preliminary in-vivo results demonstrate that - for the first time in humans – cortical pore size distribution can be assessed noninvasively and together with attenuation provides superior fracture discrimination performance compared to DXA. However, improved image reconstruction algorithms and a more comprehensive backscatter model need to be developed prior a broad clinical application.TaCoSoundInVivo aims at the development of an US imaging modality that combines robust and spatially resolved estimations of macro- and microstructural as well as viscoelastic properties of cortical bone and will apply it on a representative cohort of healthy, osteopenic and osteoporotic people. The fracture discrimination performance of US parameters will be benchmarked i) ex-vivo on well characterized bone phantoms and ii) in-vivo by means of site-matched high-resolution peripheral quantitative computed tomography (HRpQCT). We anticipate to observe age-, gender and disease associated alterations, and that multiple US parameters can identify people at increased fracture risk, particularly in people with normal or reduced BMD.

骨质疏松症（OP）是我们老龄化人口中最重要的全球健康问题之一。根据目前的金标准，大多数患有与骨质疏松相关的骨折或处于高骨折风险的个体没有被诊断为骨质疏松性，以预测骨骼状态（骨矿物质密度BMD（用双能X射线X射线X射线绝对能力测定DXA）测量）。皮质骨（约80％的人骨骼质量）的机械完整性是几个解剖部位的骨强度的关键因素。由于心脏内重塑不平衡的结果，某些大毛孔出现，导致孔径分布的特征变化，皮质孔隙率增加（CT.PO）和厚度减小（CT.TH）。这些结构改变以及受损的粘弹性组织基质特性大大降低了骨强度。在先前的双民族DFG-ANR项目“ Tacosound”（2015-2018）中，对人胫骨和股骨近端的骨骼特性进行了系统的体外调查，并且已经进行了与股骨近端僵硬和最终强度的关联。在过去的两年中，应用和国际合作伙伴提出了原始定量体内超声超声波化对i）评估声音速度（类似于ct.po和粘弹性组织属性）和ct。各自的孔径分布。本项目建立在TACOSOUND和最新发现的基础上，表明股骨近端强度变化的大多数（82％）可以通过CT.TH（69％）和胫骨中层中的大毛孔（18％）的流行率预测。有希望的前体和初步体内结果表明，在人类中，可以非侵入性地评估皮质孔径分布，并与衰减一起评估与DXA相比提供出色的断裂歧视性能。然而，需要在广泛的临床应用之前开发改进的图像重建算法和更全面的反向散射模型。TacoSoundInvivo旨在开发美国成像模态，该形象结合了宏观和微观结构的宏观和微观结构以及在皮质骨骼上的宏观结构和粘弹性的估计，并在皮质骨骼的粘弹性上进行了健康，并将其应用于健康的固定性。 人们。美国参数的断裂歧视性能将以基准为基准的i）在表征良好的骨幻象上的ex-Vivo和ii）ii）通过位点匹配的高分辨率外围周围定量计算机断层扫描（HRPQCT）的体内。我们预计会观察到年龄，性别和疾病相关的改变，并且多个美国参数可以识别出骨折风险增加的人，尤其是在BMD正常或降低的人中。