Zierhut Matthew L, Gardner Jill C, Spilker Mary E, Sharp John T, Vicini Paolo
Resource Facility for Population Kinetics, Department of Bioengineering, University of Washington, Box 355061, Seattle, WA 98195-5061, USA.
Ann Biomed Eng. 2007 May;35(5):781-95. doi: 10.1007/s10439-006-9249-7. Epub 2007 Mar 6.
In recent years, development of rheumatoid arthritis (RA) drug therapy has been more directly targeted to counteract specific mechanisms of inflammation, and it is now believed that early aggressive treatment with disease modifying drugs is important to inhibit future structural joint damage. The development of these new treatments has increased the need for methodologies to assess disease activity in RA and monitor the effectiveness of drug therapy. Unlike X-ray, which shows only structural bone damage, magnetic resonance imaging (MRI) can depict soft tissue damage and synovitis, the primary pathology of RA. Recent studies have also indicated that MRI is sensitive to pathophysiologic changes that may predate radiographic erosions and may predict future joint damage. In this study, we have developed a computer automated analysis technique for MR wrist images that provides an objective measure of RA synovitis. This method applies a two-compartment pharmacokinetic model to every voxel of a dynamic contrast-enhanced MRI (DCE-MRI) dataset and outputs resulting parametric images. The aim of this technique is to not only objectively quantify the severity of rheumatoid synovitis, but to also locally determine where areas of serious disease activity are situated through kinetic modeling of blood-tissue exchange. Preliminary results show good correlation to early enhancement rate, which has previously been shown to be a useful clinical marker of RA activity. However, the use of tracer kinetic modeling methods potentially provides more specific information regarding underlying RA physiology. This approach could provide a useful new tool in RA patient management and could substantially improve RA therapeutic studies by calculating objective biomarkers of the disease state.
近年来，类风湿关节炎（RA）药物治疗的发展更直接地针对对抗特定的炎症机制，现在人们认为使用改善病情的药物进行早期积极治疗对于抑制未来关节结构损伤很重要。这些新治疗方法的出现增加了评估RA疾病活动度和监测药物治疗效果的方法的需求。与仅显示骨骼结构损伤的X射线不同，磁共振成像（MRI）能够描绘软组织损伤和滑膜炎，而滑膜炎是RA的主要病理表现。最近的研究还表明，MRI对可能早于放射学侵蚀的病理生理变化敏感，并且可以预测未来的关节损伤。在本研究中，我们开发了一种用于MR腕部图像的计算机自动分析技术，该技术可提供RA滑膜炎的客观测量。该方法将双室药代动力学模型应用于动态对比增强MRI（DCE-MRI）数据集的每个体素，并输出所得的参数图像。该技术的目的不仅是客观地量化类风湿滑膜炎的严重程度，还通过血液-组织交换的动力学建模来局部确定严重疾病活动区域的位置。初步结果显示与早期增强率有良好的相关性，早期增强率先前已被证明是RA活动的有用临床标志物。然而，示踪剂动力学建模方法的使用可能会提供有关潜在RA生理学的更具体信息。这种方法可以为RA患者管理提供一种有用的新工具，并且通过计算疾病状态的客观生物标志物可以显著改善RA治疗研究。
