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: 7407913
• 负责人: Michael Wald
• 金额: $ 4.1万
• 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 2009-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7407913
• 关键词: Age; Anisotropy; Bone Density; Data Set; Detection; Development; Diagnosis; Diagnostic Sensitivity; Disease Progression; Elements; Fracture; Health system; Image; Invasive; 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（由申请人提供）： 代谢性骨病，尤其是骨质疏松症，是对我们卫生系统的严重挑战。在美国，骨质疏松症的治疗费用目前估计为100 - 180亿美元，预计随着人口老龄化，未来十年将翻一番。目前，骨折风险是通过骨密度测量来诊断的。通过了解骨密度和松质骨（TB）结构完整性，可以大大改善骨折风险的确定。织物张量提供了骨密度（标量）和TB结构方向（第二阶张量）的测量。磁共振成像提供了一种检查骨密度和骨小梁微观结构的非侵入性方法。然而，体内MRI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）阻止了对织物张量的准确确定。 我们提出TB结构张量及其结构各向异性可以在体内量化，从而提高对疾病进展和治疗效果的诊断灵敏度。我们的长期具体目标包括：（i）在更高场强下实现并行成像，以获取更大的TB体积，以改善对结构张量的分析，而不会降低SNR;（ii）开发对噪声和部分体积化具有鲁棒性的新型图像处理技术，以表征TB结构;以及（iii）通过与来自高分辨率数据集的TB刚度张量的有限元计算进行比较来验证织物张量。