Multi-Vendor Multi-Site Novel Accelerated MRI Relaxometry

项目总结/摘要 磁共振弛豫测量已被应用于改善早期诊断和预后的广泛疾病。 然而，将定量MRI集成到临床方案中的一个典型障碍是长的采集时间。 此外，调查各研究中心的定量变异性是一个必要但有时被忽视的步骤 和MR系统，以便验证MR成像生物标志物，并在大规模多- 供应商多中心试验。具体而言，缺乏对供应商之间、地点之间的差异的系统评价， 尽管T1ρ成像已广泛应用于神经、肝脏、心脏、肿瘤和肌肉骨骼， (MSK)显像两种市售T1ρ造影剂均不可用。拟议的研究正在解决这些问题 显著的差距，旨在开发和交叉验证新的快速MR T1ρ和T2成像方法， 系统从多个供应商，然后在患者的风险骨关节炎的可行性评估。关节炎 (OA)影响了美国超过2700万人没有疾病修饰OA药物（DMOAD）可用，尽管 广泛的努力。开发DMOAD的一个障碍是缺乏敏感和可靠的非侵入性生物标志物 可以在短时间内检测治疗效果。这些生物标志物也将有益于临床实践 通过识别有发生OA风险的患者或处于疾病早期阶段的患者， 这些策略显示出在减缓疾病进展方面最有效。有一个紧迫的，未满足的 临床上需要对早期退行性变进行可靠的评估，这对于支持OA的范式转变至关重要 从缓解晚期疾病到通过早期诊断和早期治疗进行预防 治疗/干预。已证明Carnival MR T1ρ和T2测量是有前途的成像 早期软骨退化的生物标志物。然而，在临床上应用这些方法仍然存在许多挑战。 技术，包括缺乏标准化的采集和分析方法，采集时间长， 不同MR系统之间变化的不确定性。在这项研究中，我们将开发新的加速T1ρ， T2成像方法，在三家主要供应商（Siemens、GE和 Philips），使用专用T1ρ和T2系统评价这些测量的供应商间和研究中心间差异 校准体模（将在本研究中开发）和旅行受试者，调查来源， 差异的大小，探索减轻差异的方法，并证明 新开发的加速技术，用于在多供应商中纵向量化软骨退化 设置.拟议研究的成功实施将提供一整套T1ρ和T2成像， 将准备好传播，并将有助于为大规模多供应商，多地点试验铺平道路 使用T1ρ和T2成像，促进这些定量MR技术的临床转化， 使用定量成像生物标志物改变OA和其他疾病的患者管理。

PROJECT SUMMARY/ABSTRACT MRI relaxometry has been applied to improve early diagnosis and prognosis for a wide range of diseases. However, one typical obstacle of integrating quantitative MRI into clinical protocols is the long acquisition time. Furthermore, it is an essential but sometimes overlooked step to investigate quantification variability across sites and MR systems in order to validate MR imaging biomarkers and to apply the measures in large scale multi- vendor multi-site trials. Specifically, there is a lack of systematic evaluation of inter-vendor inter-site variability of T1ρ imaging, even though it has been widely applied in neural-, liver-, cardiac-, oncology-, and musculoskeletal- (MSK) imaging. Neither commercial T1ρ phantoms are available. The proposed study is addressing these significant gaps and aims to develop and cross-validate novel fast MR T1ρ and T2 imaging methods on MR systems from multiple vendors, followed by feasibility evaluation in patients at risk for osteoarthritis. Osteoarthritis (OA) affects over 27 million people in the US. No disease modifying OA drugs (DMOADs) are available, despite extensive effort. One hurdle for developing DMOADs is the lack of sensitive and reliable non-invasive biomarkers that can detect treatment effects over a short time window. Such biomarkers would also benefit clinical practice by identifying patients at risk for developing OA or at an early disease stage, when behavior modification strategies are shown to be most effective in slowing down the disease progression. There is a pressing, unmet clinical need for robust assessment of early degeneration, which is critical to support a paradigm shift of OA management from palliation of late disease towards prevention through early diagnosis and early treatment/interventions. Cartilage MR T1ρ and T2 measures have been shown to be promising imaging biomarkers for early cartilage degeneration. However, many challenges remain to clinically applying these techniques, including lack of standardized acquisition and analysis methods, long acquisition time, and uncertainty of variations between different MR systems. In this study, we will develop novel accelerated T1ρ and T2 imaging methods, implement these techniques on MR systems of three major vendors (Siemens, GE and Philips), systematically evaluate inter-vendor inter-site variation of these measures using dedicated T1ρ and T2 calibration phantoms (to be developed in this study) and traveling subjects, investigate the source(s) and magnitude of the differences, explore methods to mitigate the variability, and demonstrate the feasibility of the newly developed acceleration techniques to quantify cartilage degeneration longitudinally in a multi-vendor setting. Successful implementation of the proposed study will provide a full package of T1ρ and T2 imaging that will be ready for dissemination and will help to pave the way towards large-scale multi-vendor, multi-site trials using T1ρ and T2 imaging, facilitate clinical translation of these quantitative MR techniques, and ultimately transform patient management of OA and other disorders using quantitative imaging biomarkers.