Real-time feedback MRI for improved reproducibility in imaging biomarkers

描述（由申请人提供）：该项目的总体目标是将先进的实时反馈技术纳入MRI协议，以增加MRI衍生参数的可重复性，并提高宾夕法尼亚大学各种临床程序的准确性和效率。虽然该提案侧重于小梁骨结构微mri、实时心脏成像和功能神经成像等领域的一些具体应用，但候选人预计，该项目期间开发的实时反馈编程框架将对宾夕法尼亚大学和其他地方的其他NIH资助的研究项目产生重大影响。

DESCRIPTION (provided by applicant): The overall goal of this project is to incorporate advanced real-time feedback techniques into MRI protocols in order to increase reproducibility of MR-derived parameters and improve the accuracy and efficiency of a variety of clinical procedures at the University of Pennsylvania. While this proposal focuses on a few specific applications in the areas of structural micro-MRI of trabecular bone, real-time cardiac imaging, and functional neuroimaging, the candidate anticipates that the real-time feedback programming framework developed during the project will have a significant impact on other NIH funded research projects at Penn and elsewhere. The candidate, a mathematician with a background in computer science, has developed a graphical pulse sequence programming environment which has been fully interfaced to the Siemens whole-body scanners. This software, which has been used by students and researchers to develop dozens of research pulse sequences, will be the starting point for the proposed real-time feedback programming framework. Through collaborations with clinical and biomedical researchers at Penn, the candidate expects this technology to fill gaps in research techniques and ultimately have a significant positive impact on health care. Medical imaging is becoming increasingly important for the development and validation of new drugs, medical devices and procedures. Magnetic resonance imaging (MRI) is particularly suitable for these purposes because it is non-invasive and sensitive to a wide range of physiological processes. However, the modality also has a number of inherent challenges that often reduce the accuracy or reproducibility of quantitative MRI-derived parameters (imaging biomarkers). Subject motion during a scan, inconsistent patient positioning, and other MRI-related problems can hinder the ability to detect small changes in biomarkers in response to treatment or disease progression. Real-time feedback techniques (including prospective motion compensation and automatic section prescription) can significantly improve the accuracy and precision of such measurements. However, due to the technical difficulty of implementing these advanced scanning techniques, real-time feedback capabilities are not available for many of the clinical procedures that could most benefit.