Solving the Pervasive Problem of Protocol Non-Compliance in MRI using an Open-Source tool mrQA.

IF 2.7 4区 医学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Neuroinformatics Pub Date : 2024-07-01 Epub Date: 2024-06-11 DOI:10.1007/s12021-024-09668-4
Harsh Sinha, Pradeep Reddy Raamana
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引用次数: 0

Abstract

Pooling data across diverse sources acquired by multisite consortia requires compliance with a predefined reference protocol i.e., ensuring different sites and scanners for a given project have used identical or compatible MR physics parameter values. Traditionally, this has been an arduous and manual process due to difficulties in working with the complicated DICOM standard and lack of resources allocated towards protocol compliance. Moreover, issues of protocol compliance is often overlooked for lack of realization that parameter values are routinely improvised/modified locally at various sites. The inconsistencies in acquisition protocols can reduce SNR, statistical power, and in the worst case, may invalidate the results altogether. An open-source tool, mrQA was developed to automatically assess protocol compliance on standard dataset formats such as DICOM and BIDS, and to study the patterns of non-compliance in over 20 open neuroimaging datasets, including the large ABCD study. The results demonstrate that the lack of compliance is rather pervasive. The frequent sources of non-compliance include but are not limited to deviations in Repetition Time, Echo Time, Flip Angle, and Phase Encoding Direction. It was also observed that GE and Philips scanners exhibited higher rates of non-compliance relative to the Siemens scanners in the ABCD dataset. Continuous monitoring for protocol compliance is strongly recommended before any pre/post-processing, ideally right after the acquisition, to avoid the silent propagation of severe/subtle issues. Although, this study focuses on neuroimaging datasets, the proposed tool mrQA can work with any DICOM-based datasets.

Abstract Image

使用开源工具 mrQA 解决核磁共振成像中普遍存在的不遵守协议问题。
汇集多站点联盟获取的不同来源的数据需要符合预定义的参考协议,即确保特定项目的不同站点和扫描仪使用相同或兼容的磁共振物理参数值。传统上,由于难以使用复杂的 DICOM 标准和缺乏用于协议合规的资源,这是一个艰巨的手动过程。此外,由于没有意识到参数值在不同地点经常会被临时修改,协议合规性问题经常被忽视。采集协议的不一致会降低信噪比和统计功率,最糟糕的情况是,可能会导致结果完全失效。我们开发了一款开源工具 mrQA,用于自动评估 DICOM 和 BIDS 等标准数据集格式的协议合规性,并研究了包括大型 ABCD 研究在内的 20 多个开放式神经成像数据集的不合规模式。研究结果表明,不遵守协议的现象相当普遍。不合规的常见原因包括但不限于重复时间、回波时间、翻转角度和相位编码方向的偏差。在 ABCD 数据集中还观察到,相对于西门子扫描仪,通用电气和飞利浦扫描仪的违规率更高。强烈建议在进行任何前/后处理之前,最好是在采集后立即对协议合规性进行持续监控,以避免严重/细微问题的无声传播。虽然这项研究的重点是神经成像数据集,但建议使用的 mrQA 工具可以处理任何基于 DICOM 的数据集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Neuroinformatics
Neuroinformatics 医学-计算机:跨学科应用
CiteScore
6.00
自引率
6.70%
发文量
54
审稿时长
3 months
期刊介绍: Neuroinformatics publishes original articles and reviews with an emphasis on data structure and software tools related to analysis, modeling, integration, and sharing in all areas of neuroscience research. The editors particularly invite contributions on: (1) Theory and methodology, including discussions on ontologies, modeling approaches, database design, and meta-analyses; (2) Descriptions of developed databases and software tools, and of the methods for their distribution; (3) Relevant experimental results, such as reports accompanie by the release of massive data sets; (4) Computational simulations of models integrating and organizing complex data; and (5) Neuroengineering approaches, including hardware, robotics, and information theory studies.
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