A (sub)field guide to quality control in hippocampal subfield segmentation on high-resolution T2-weighted MRI

IF 3.5 2区 医学 Q1 NEUROIMAGING
Kelsey L. Canada, Negar Mazloum-Farzaghi, Gustaf Rådman, Jenna N. Adams, Arnold Bakker, Hannah Baumeister, David Berron, Martina Bocchetta, Valerie A. Carr, Marshall A. Dalton, Robin de Flores, Attila Keresztes, Renaud La Joie, Susanne G. Mueller, Naftali Raz, Tales Santini, Thomas Shaw, Craig E. L. Stark, Tammy T. Tran, Lei Wang, Laura E. M. Wisse, Anika Wuestefeld, Paul A. Yushkevich, Rosanna K. Olsen, Ana M. Daugherty, the Hippocampal Subfields Group
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引用次数: 0

Abstract

Inquiries into properties of brain structure and function have progressed due to developments in magnetic resonance imaging (MRI). To sustain progress in investigating and quantifying neuroanatomical details in vivo, the reliability and validity of brain measurements are paramount. Quality control (QC) is a set of procedures for mitigating errors and ensuring the validity and reliability of brain measurements. Despite its importance, there is little guidance on best QC practices and reporting procedures. The study of hippocampal subfields in vivo is a critical case for QC because of their small size, inter-dependent boundary definitions, and common artifacts in the MRI data used for subfield measurements. We addressed this gap by surveying the broader scientific community studying hippocampal subfields on their views and approaches to QC. We received responses from 37 investigators spanning 10 countries, covering different career stages, and studying both healthy and pathological development and aging. In this sample, 81% of researchers considered QC to be very important or important, and 19% viewed it as fairly important. Despite this, only 46% of researchers reported on their QC processes in prior publications. In many instances, lack of reporting appeared due to ambiguous guidance on relevant details and guidance for reporting, rather than absence of QC. Here, we provide recommendations for correcting errors to maximize reliability and minimize bias. We also summarize threats to segmentation accuracy, review common QC methods, and make recommendations for best practices and reporting in publications. Implementing the recommended QC practices will collectively improve inferences to the larger population, as well as have implications for clinical practice and public health.

Abstract Image

高分辨率 T2 加权磁共振成像海马亚区分割质量控制(亚)指南。
磁共振成像(MRI)技术的发展推动了对大脑结构和功能特性的研究。为了在研究和量化体内神经解剖细节方面持续取得进展,脑部测量的可靠性和有效性至关重要。质量控制(QC)是一套减少误差并确保脑部测量有效性和可靠性的程序。尽管质量控制非常重要,但有关最佳质量控制实践和报告程序的指导却很少。体内海马亚区的研究是质量控制的一个关键案例,因为海马亚区体积小,边界定义相互依赖,而且用于亚区测量的磁共振成像数据中常见伪影。为了弥补这一不足,我们对研究海马亚场的广大科学界人士进行了调查,了解他们对 QC 的看法和方法。我们收到了来自 10 个国家的 37 位研究人员的回复,他们处于不同的职业阶段,既研究健康的,也研究病理发育和衰老。在这些样本中,81% 的研究人员认为 QC 非常重要或重要,19% 的研究人员认为 QC 相当重要。尽管如此,只有 46% 的研究人员在以前的出版物中报告了他们的质量控制过程。在很多情况下,缺乏报告似乎是由于相关细节和报告指导方面的指导不明确,而不是缺乏质量控制。在此,我们提出了纠正错误的建议,以最大限度地提高可靠性和减少偏差。我们还总结了对分割准确性的威胁,回顾了常见的质量控制方法,并对出版物中的最佳实践和报告提出了建议。实施推荐的质量控制方法将共同提高对更大人群的推断,并对临床实践和公共卫生产生影响。
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来源期刊
Human Brain Mapping
Human Brain Mapping 医学-核医学
CiteScore
8.30
自引率
6.20%
发文量
401
审稿时长
3-6 weeks
期刊介绍: Human Brain Mapping publishes peer-reviewed basic, clinical, technical, and theoretical research in the interdisciplinary and rapidly expanding field of human brain mapping. The journal features research derived from non-invasive brain imaging modalities used to explore the spatial and temporal organization of the neural systems supporting human behavior. Imaging modalities of interest include positron emission tomography, event-related potentials, electro-and magnetoencephalography, magnetic resonance imaging, and single-photon emission tomography. Brain mapping research in both normal and clinical populations is encouraged. Article formats include Research Articles, Review Articles, Clinical Case Studies, and Technique, as well as Technological Developments, Theoretical Articles, and Synthetic Reviews. Technical advances, such as novel brain imaging methods, analyses for detecting or localizing neural activity, synergistic uses of multiple imaging modalities, and strategies for the design of behavioral paradigms and neural-systems modeling are of particular interest. The journal endorses the propagation of methodological standards and encourages database development in the field of human brain mapping.
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