In vivo detection of trabecular bone structural anisotropy using parallel MRI

使用并行 MRI 体内检测小梁骨结构各向异性

• 批准号: 7545488
• 负责人: Michael Wald
• 金额: $ 2.16万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-12-01 至 2009-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7545488
• 关键词: Age; Anisotropy; Bone Density; Data Set; Detection; Development; Diagnosis; Diagnostic Sensitivity; Disease Progression; Elements; Fracture; Health system; Image; Knowledge; Magnetic Resonance Imaging; Measurement; Measures; Metabolic Bone Diseases; Noise; Osteoporosis; Population; Resolution; Risk; Scanning; Signal Transduction; Structure; Techniques; Textiles; Time; Treatment Cost; Treatment Efficacy; United States; Validation; image processing; improved; in vivo; novel; prevent; substantia spongiosa

DESCRIPTION (provided by applicant): Metabolic bone disease, particularly osteoporosis, is a serious challenge to our health system. In the United States, treatment costs for osteoporosis is currently estimated at $10-$18 billion and expected to double over the next decade as the population ages. Currently, fracture risk is diagnosed by bone density measurements. Substantial improvement in the determination of fracture risk can be gained through knowledge of both bone density and trabecular bone (TB) structural integrity. The fabric tensor provides both a measure of bone density (scalar) and the structural orientation of TB (2nd-rank tensor). Magnetic resonance imaging provides a non-invasive means of examining both bone density and trabecular bone microstructure. Yet, technical limitations of in vivo MRI, the achievable signal-to-noise (SNR) and field-of view (FOV) within a reasonable scan time prevent an accurate determination of the fabric tensor. We propose that the TB fabric tensor and its structural anisotropy can be quantified in vivo, thereby improving the diagnostic sensitivity to disease progression and treatment efficacy. Our long-term specific aims include (i) implementation of parallel imaging at higher field strengths for the acquisition of a larger TB volume for improved analysis of the fabric tensor without SNR degradation, (ii) development of novel image processing techniques robust to noise and partial-voluming for the characterization of TB structure, and (iii) validation of the fabric tensor through comparison to finite-element calculations of theTB stiffness tensor from high resolution datasets.

描述(申请人提供)：代谢性骨病，特别是骨质疏松症，对我们的健康系统是一个严重的挑战。在美国，骨质疏松症的治疗费用目前估计为100-180亿美元，预计在未来十年内随着人口老龄化而翻一番。目前，骨折风险是通过骨密度测量来诊断的。通过了解骨密度和骨小梁(TB)结构完整性，可以大大改善骨折风险的确定。结构张量提供了骨密度(标量)和Tb的结构方向(二阶张量)的度量。磁共振成像提供了一种非侵入性检查骨密度和骨小梁微结构的方法。然而，活体磁共振成像的技术限制，在合理的扫描时间内可实现的信噪比(SNR)和视场(FOV)阻碍了对织物张量的准确确定。我们认为，结核组织张量及其结构各向异性可以在体内被量化，从而提高对疾病进展和治疗效果的诊断敏感性。我们的长期具体目标包括(I)在更高的场强下实施并行成像，以获取更大的TB体积，以改进对织物张量的分析，而不会降低信噪比；(Ii)开发新的图像处理技术，对噪声和部分体积进行稳健的图像处理，以表征TB结构；以及(Iii)通过与来自高分辨率数据集的TB硬度张量的有限元计算进行比较，验证织物张量。