Vallini Giulia, Silvestri Erica, Volpi Tommaso, Lee John J, Vlassenko Andrei G, Goyal Manu S, Cecchin Diego, Corbetta Maurizio, Bertoldo Alessandra
Department of Information Engineering, University of Padova, Padova, Italy.
Padova Neuroscience Center, University of Padova, Padova, Italy.
Eur J Nucl Med Mol Imaging. 2025 Feb;52(3):836-850. doi: 10.1007/s00259-024-06956-8. Epub 2024 Oct 30.
This study evaluates the potential of within-individual Metabolic Connectivity (wi-MC), from dynamic [F]FDG PET data, based on the Euclidean Similarity method. This approach leverages the biological information of the tracer's full temporal dynamics, enabling the direct extraction of individual metabolic connectomes. Specifically, the proposed framework, applied to glioma pathology, seeks to assess sensitivity to metabolic dysfunctions in the whole brain, while simultaneously providing further insights into the pathophysiological mechanisms regulating glioma progression.
We designed an index (Distance from Healthy Group, DfHG) based on the alteration of wi-MC in each patient (n = 44) compared to a healthy reference (from 57 healthy controls), to individually quantify metabolic connectivity abnormalities, resulting in an Impairment Map highlighting significantly compromised areas. We then assessed whether our measure of metabolic network alteration is associated with well-established markers of disease severity (tumor grade and volume, with and without edema). Subsequently, we investigated disruptions in wi-MC homotopic connectivity, assessing both affected and seemingly healthy tissue to deepen the pathology's impact on neural communication. Finally, we compared network impairments with local metabolic alterations determined from SUVR, a validated diagnostic tool in clinical practice.
Our framework revealed how gliomas cause extensive alterations in the topography of brain networks, even in structurally unaffected regions outside the lesion area, with a significant reduction in connectivity between contralateral homologous regions. High-grade gliomas have a stronger impact on brain networks, and edema plays a mediating role in global metabolic alterations. As compared to the conventional SUVR-based analysis, our approach offers a more holistic view of the disease burden in individual patients, providing interesting additional insights into glioma-related alterations.
Considering our results, individual PET connectivity estimates could hold significant clinical value, potentially allowing the identification of new prognostic factors and personalized treatment in gliomas or other focal pathologies.
本研究基于欧几里得相似性方法，评估来自动态[F]FDG PET数据的个体内代谢连通性（wi-MC）的潜力。这种方法利用了示踪剂完整时间动态的生物学信息，能够直接提取个体代谢连接组。具体而言，应用于胶质瘤病理学的所提出框架旨在评估对全脑代谢功能障碍的敏感性，同时进一步深入了解调节胶质瘤进展的病理生理机制。
我们设计了一个指数（与健康组的距离，DfHG），基于每位患者（n = 44）与健康对照（来自57名健康对照）相比wi-MC的改变，以个体量化代谢连通性异常，从而生成一个突出显示明显受损区域的损伤图谱。然后，我们评估我们的代谢网络改变测量是否与疾病严重程度的既定标志物（肿瘤分级和体积，有无水肿）相关。随后，我们研究wi-MC同位连通性的破坏，评估受影响和看似健康的组织，以加深病理学对神经通信的影响。最后，我们将网络损伤与通过标准化摄取值比（SUVR）确定的局部代谢改变进行比较，SUVR是临床实践中一种经过验证的诊断工具。
我们的框架揭示了胶质瘤如何在脑网络拓扑结构中引起广泛改变，即使在病变区域外结构未受影响的区域，对侧同源区域之间的连通性也显著降低。高级别胶质瘤对脑网络的影响更强，水肿在整体代谢改变中起中介作用。与基于传统SUVR的分析相比，我们的方法提供了对个体患者疾病负担更全面的看法，为胶质瘤相关改变提供了有趣的额外见解。
考虑到我们的结果，个体PET连通性估计可能具有重大临床价值，有可能在胶质瘤或其他局灶性病变中识别新的预后因素并实现个性化治疗。
