发表机构
Graz University of Technology; Harvard Medical School; German Centre for Cardiovascular Research (DZHK); BioTechMed-Graz（格拉茨工业大学; 哈佛医学院; 德国心血管研究中心; BioTechMed格拉茨）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究旨在提供满足需求的集成开源框架，通过在BART工具箱添加软件框架及开发驱动序列，实现定量MRI方法，验证在线和离线采集一致性，成功在开源框架内实现先进计算MRI方法的可重复性。
AI 中文摘要
目的：在先进的计算MRI技术中，采集和重建技术需联合设计，为实现可重复性，提供两者的开放实现很重要，同时临床应用需与MRI扫描仪紧密集成，确保长期可重复性和维护面临挑战。方法：在BART工具箱中添加开发脉冲序列的软件框架，开发特定供应商驱动序列以在临床MRI扫描仪上运行序列并在线调整参数，利用Pulseq格式可离线重现相同序列。以T1、关节水/脂肪R2*定量MRI方法等为例进行概念验证，并在体模和体内实验中验证在线和离线采集的一致性。结果：在BART中成功实现了包含采集和重建的定量MRI方法，可在临床MRI系统上在线调整采集参数和视野，基于模型重建的定量参数图在在线和离线Pulseq采集时一致。结论：这项工作在全面的端到端开源框架内实现了先进计算MRI方法的可重复性。
英文摘要
Purpose In advanced computational MRI techniques, acquisition and reconstruction techniques are jointly designed. For reproducibility, it is therefore important to provide an open implementation of both. At the same time, any use in a clinical environment usually requires a close integration with the MRI scanner. Ensuring long-time reproducibility and maintenance then poses additional challenges. In this work, we aim to provide a fully integrated open-source framework that can meet these demands. Methods A software framework to develop pulse sequences is added to BART, an open-source toolbox for computational MRI. In addition, a vendor-specific driver sequence is developed that can be used to run the sequence on a clinical MRI scanner enabling online adjustment of all relevant sequence parameters. Using the Pulseq format, the exact same sequence can also be reproduced offline using a widely used vendor-neutral open-source standard. Using the Pulseq format, the exact same sequence can also be reproduced offline. As proof-of-concept, quantitative MRI methods for T1 and joint water/fat R2*, B0 mapping using radial FLASH and model-based reconstruction are implemented in the proposed framework. Consistency between online and offline acquisition is validated in phantom and in vivo experiments. Results Quantitative MRI methods highlighting specific challenges of acquisition and reconstruction were successfully implemented in BART. Acquisition parameters and FOV can be adapted online on a clinical MRI system. Quantitative parameter maps from model-based reconstruction agree for online and offline regenerated Pulseq acquisitions. Conclusion This work enables reproducibility of advanced computational MRI methods within a comprehensive end-to-end open-source framework.
