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Objective <p>To investigate cross-sectional differences in individualized metabolic brain network topology between patients with diffuse large B-cell lymphoma (DLBCL) and healthy controls, and to explore the associations between network topology and cognitive performance.</p> Methods <p>A total of 104 patients with DLBCL and 33 healthy controls were prospectively enrolled. All participants underwent whole-body <sup>18</sup>F-FDG PET/CT between January 2024 and January 2026. Patients were categorized into baseline and post-chemotherapy groups according to treatment status. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Functional Assessment of Cancer Therapy-Cognitive Function Scale (FACT-Cog). Individual metabolic brain networks were constructed using the Kullback-Leibler Divergence Similarity Estimation (KLSE) method. Graph theory was applied to analyze global and nodal topological properties. Group comparisons and correlation analyses were conducted to evaluate associations between network metrics and cognitive scores (<i>P</i> &lt; 0.05).</p> Results <p>We included 137 participants: 104 patients (mean age, 55.6 ± 11.7 years; 57 males) and 33 healthy controls (mean age, 50.3 ± 11.8 years; 17 males). Compared with controls, both baseline and post-chemotherapy patients showed significantly lower MMSE and MoCA scores (<i>P</i> &lt; 0.001). There were no significant differences in cognitive scale scores between the two patient groups. Meanwhile, all groups exhibited small-world properties (γ &gt; 1, λ ≈ 1, σ &gt; 1), with no significant differences in global network metrics (<i>P</i> &gt; 0.05). At the nodal level, baseline patients showed increased nodal degree and efficiency specifically in frontal regions, and decreased betweenness centrality in bilateral parietal regions. In cross-sectional comparisons, post-chemotherapy patients exhibited decreased degree centrality and nodal efficiency in prefrontal regions compared with baseline. In contrast, temporal, occipital, and selected subcortical regions showed increased nodal degree or efficiency. Furthermore, nodal degree, efficiency, and betweenness centrality in these regions were significantly correlated with cognitive scores.</p> Conclusion <p>DLBCL patients maintained global network organization but demonstrated specific regional topological changes compared to healthy controls. The observed nodal differences between baseline and post-chemotherapy patients were correlated with cognitive performance. Individualized <sup>18</sup>F-FDG PET/CT assessment of metabolic brain networks offers valuable insight into cognitive impairment in DLBCL.</p>

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Individualized metabolic brain network alterations in diffuse large B-cell lymphoma: an 18F-FDG PET study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月11日

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  • Yelu Gu,
  • Fan Yang,
  • Hailun Zhang,
  • Jingke Xiao,
  • Jiangyan Liu

摘要

Objective

To investigate cross-sectional differences in individualized metabolic brain network topology between patients with diffuse large B-cell lymphoma (DLBCL) and healthy controls, and to explore the associations between network topology and cognitive performance.

Methods

A total of 104 patients with DLBCL and 33 healthy controls were prospectively enrolled. All participants underwent whole-body 18F-FDG PET/CT between January 2024 and January 2026. Patients were categorized into baseline and post-chemotherapy groups according to treatment status. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Functional Assessment of Cancer Therapy-Cognitive Function Scale (FACT-Cog). Individual metabolic brain networks were constructed using the Kullback-Leibler Divergence Similarity Estimation (KLSE) method. Graph theory was applied to analyze global and nodal topological properties. Group comparisons and correlation analyses were conducted to evaluate associations between network metrics and cognitive scores (P < 0.05).

Results

We included 137 participants: 104 patients (mean age, 55.6 ± 11.7 years; 57 males) and 33 healthy controls (mean age, 50.3 ± 11.8 years; 17 males). Compared with controls, both baseline and post-chemotherapy patients showed significantly lower MMSE and MoCA scores (P < 0.001). There were no significant differences in cognitive scale scores between the two patient groups. Meanwhile, all groups exhibited small-world properties (γ > 1, λ ≈ 1, σ > 1), with no significant differences in global network metrics (P > 0.05). At the nodal level, baseline patients showed increased nodal degree and efficiency specifically in frontal regions, and decreased betweenness centrality in bilateral parietal regions. In cross-sectional comparisons, post-chemotherapy patients exhibited decreased degree centrality and nodal efficiency in prefrontal regions compared with baseline. In contrast, temporal, occipital, and selected subcortical regions showed increased nodal degree or efficiency. Furthermore, nodal degree, efficiency, and betweenness centrality in these regions were significantly correlated with cognitive scores.

Conclusion

DLBCL patients maintained global network organization but demonstrated specific regional topological changes compared to healthy controls. The observed nodal differences between baseline and post-chemotherapy patients were correlated with cognitive performance. Individualized 18F-FDG PET/CT assessment of metabolic brain networks offers valuable insight into cognitive impairment in DLBCL.