Reed Murray B, Cocchi Luca, Sander Christin Y, Chen Jingyuan, Matheson Granville J, Fisher Patrick, Volpi Tommaso, Khattar Nikkita, DeLorenzo Christine, Gryglewski Gregor, Silberbauer Leo R, Murgaš Matej, Godbersen Godber M, Nics Lukas, Walter Martin, Hacker Marcus, Bertoldo Alessandra, Lubberink Mark, Silfstein Mark, Ogden R Todd, Mann J John, Suhara Tetsuya, Varrone Andrea, Boellaard Ronald, Gunn Roger N, Hammers Alexander, Biswal Bharat, Rosen Bruce, Knudsen Gitte M, Carson Richard, Price Julie, Lanzenberger Rupert, Hahn Andreas
Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
Comprehensive Center for Clinical Neurosciences and Mental Health (C3 NMH), Medical University of Vienna, Vienna, Austria.
Eur J Nucl Med Mol Imaging. 2025 Jun 2. doi: 10.1007/s00259-025-07357-1.
Positron emission tomography (PET)-based connectivity analysis provides a molecular perspective that complements fMRI-derived functional connectivity. However, lack of standardized terminology and diverse methodologies in PET connectivity studies has resulted in inconsistencies, complicating the interpretation and comparison of results across studies. A standardized nomenclature is thus needed to reduce ambiguity, enhance reproducibility, and facilitate interpretability across radiotracers, imaging modalities and studies. Here, we define and differentiate the terms "molecular connectivity" and "molecular covariance". Drawing parallels from other imaging modalities, we propose "molecular connectivity" as an umbrella term to characterize statistical dependencies between the measured PET signal across brain regions at a within-subject level. Like fMRI resting-state functional connectivity, "molecular connectivity" leverages spatio-temporal associations in the PET signal to derive brain network associations. Conversely, "molecular covariance" denotes group-level computations of covariance matrices between-subjects. Further specification of the terminology can be achieved by including the target of the employed radioligand, such as "metabolic connectivity/covariance" for [F]FDG or "amyloid covariance" for [F]flutemetamol and "tau covariance" for [F]flortaucipir. While this approach to standardization aims to clarify terminology, open questions remain about the neurobiological underpinnings of these connectivity metrics. Future research should focus on elucidating these mechanisms and developing advanced computational methodologies that evaluate diverse feature relationships and improve the robustness of PET-based connectivity metrics.
基于正电子发射断层扫描（PET）的连接性分析提供了一种分子层面的视角，对源自功能磁共振成像（fMRI）的功能连接性起到补充作用。然而，PET连接性研究中缺乏标准化术语以及多样的方法，导致了研究结果的不一致，使得跨研究结果的解释和比较变得复杂。因此，需要一种标准化的命名法来减少歧义、提高可重复性，并促进不同放射性示踪剂、成像模态和研究之间的可解释性。在此，我们定义并区分“分子连接性”和“分子协方差”这两个术语。借鉴其他成像模态，我们提出“分子连接性”作为一个总括性术语，用于描述个体水平上跨脑区测量的PET信号之间的统计依赖性。与fMRI静息态功能连接性类似，“分子连接性”利用PET信号中的时空关联来推导脑网络关联。相反，“分子协方差”表示受试者间协方差矩阵的组水平计算。通过纳入所使用放射性配体的靶点，可以进一步明确术语，例如针对[F]FDG的“代谢连接性/协方差”、针对[F]氟替美坦的“淀粉样蛋白协方差”以及针对[F]氟 tau 西匹的“tau 协方差”。虽然这种标准化方法旨在澄清术语，但这些连接性指标的神经生物学基础仍存在一些未解决的问题。未来的研究应专注于阐明这些机制，并开发先进的计算方法，以评估多样的特征关系并提高基于PET的连接性指标的稳健性。
