Borrelli Pasquale, Savini Giovanni, Cavaliere Carlo, Palesi Fulvia, Grazia Bruzzone Maria, Aquino Domenico, Biagi Laura, Bosco Paolo, Carne Irene, Ferraro Stefania, Giulietti Giovanni, Napolitano Antonio, Nigri Anna, Pavone Luigi, Pirastru Alice, Redolfi Alberto, Tagliavini Fabrizio, Tosetti Michela, Salvatore Marco, Gandini Wheeler-Kingshott Claudia A M, Aiello Marco
IRCCS SYNLAB SDN, Naples, Italy.
IRCCS Humanitas Research Hospital, Rozzano, Italy.
Phys Med. 2023 Aug;112:102610. doi: 10.1016/j.ejmp.2023.102610. Epub 2023 Jun 17.
The use of topological metrics to derive quantitative descriptors from structural connectomes is receiving increasing attention but deserves specific studies to investigate their reproducibility and variability in the clinical context. This work exploits the harmonization of diffusion-weighted acquisition for neuroimaging data performed by the Italian Neuroscience and Neurorehabilitation Network initiative to obtain normative values of topological metrics and to investigate their reproducibility and variability across centers.
Different topological metrics, at global and local level, were calculated on multishell diffusion-weighted data acquired at high-field (e.g. 3 T) Magnetic Resonance Imaging scanners in 13 different centers, following the harmonization of the acquisition protocol, on young and healthy adults. A "traveling brains" dataset acquired on a subgroup of subjects at 3 different centers was also analyzed as reference data. All data were processed following a common processing pipeline that includes data pre-processing, tractography, generation of structural connectomes and calculation of graph-based metrics. The results were evaluated both with statistical analysis of variability and consistency among sites with the traveling brains range. In addition, inter-site reproducibility was assessed in terms of intra-class correlation variability.
The results show an inter-center and inter-subject variability of <10%, except for "clustering coefficient" (variability of 30%). Statistical analysis identifies significant differences among sites, as expected given the wide range of scanners' hardware.
The results show low variability of connectivity topological metrics across sites running a harmonised protocol.
使用拓扑度量从结构连接组中导出定量描述符正受到越来越多的关注，但在临床背景下，值得进行专门研究以探究其可重复性和变异性。这项工作利用意大利神经科学与神经康复网络倡议对神经影像数据进行的扩散加权采集的协调，以获得拓扑度量的标准值，并研究其在不同中心之间的可重复性和变异性。
在遵循采集协议协调后，于13个不同中心的高场（如3T）磁共振成像扫描仪上，对年轻健康成年人采集的多壳扩散加权数据计算全局和局部层面的不同拓扑度量。还对在3个不同中心的一组受试者上采集的“移动大脑”数据集作为参考数据进行了分析。所有数据均按照包括数据预处理、纤维束成像、结构连接组生成和基于图形的度量计算在内的通用处理流程进行处理。通过对不同站点之间的变异性和一致性与“移动大脑”范围进行统计分析来评估结果。此外，根据组内相关变异性评估站点间的可重复性。
结果显示，除“聚类系数”（变异性为30%）外，中心间和受试者间的变异性<10%。统计分析确定了不同站点之间存在显著差异，考虑到扫描仪硬件的广泛差异，这是预期的。
结果表明，在运行统一协议的不同站点之间，连接拓扑度量的变异性较低。
