Toloknieiev Artur, Voitsekhivskyi Dmytro, Kholodkov Hlib, Lvovich Roman, Matiushko Petro, Rekretiuk Daria, Dikhtiar Andrii, Viter Antonii, Pokras Volodymyr, Wunderlich Stephan, Stoecklein Sophia
Department of Radiology, University Hospital, LMU Munich, Munich, Germany.
Department of Radiology, University Hospital, LMU Munich, Munich, Germany; Munich School of Management, LMU Munich, Munich, Germany.
Neuroimage Clin. 2025 Aug 13;48:103856. doi: 10.1016/j.nicl.2025.103856.
Functional connectivity magnetic resonance imaging (fcMRI) is a well-established technique for studying brain networks in both healthy and diseased individuals. However, no fcMRI-based biomarker has yet achieved clinical relevance. To establish better understanding of the state of the art in quantifying abnormal connectivity in comparison to a reference distribution, for potential use in individual patients, we have conducted a scoping review over 5672 entries from the last 10 years. We have located five publications proposing metrics of abnormal connectivity quantification, reported these metrics, formalized their computing methods, assessed their technology readiness and estimated their computational efficiency. Building upon our findings, we have discussed the metrics' lesion data handling, region of interest level of detail and potential clinical use cases. We also proposed methodical and computational strategies for improvement of current and emerging abnormality quantification metrics in fcMRI research.
功能连接磁共振成像（fcMRI）是一种成熟的技术，用于研究健康个体和患病个体的脑网络。然而，尚未有基于fcMRI的生物标志物具有临床相关性。为了更好地了解与参考分布相比量化异常连接的技术现状，以便潜在地应用于个体患者，我们对过去10年的5672篇文献进行了范围综述。我们找到了五篇提出异常连接量化指标的出版物，报告了这些指标，规范了它们的计算方法，评估了它们的技术成熟度，并估计了它们的计算效率。基于我们的研究结果，我们讨论了这些指标的病变数据处理、感兴趣区域的细节程度以及潜在的临床应用案例。我们还提出了方法和计算策略，以改进fcMRI研究中当前和新兴的异常量化指标。
