ArticleQuantitative imaging in medicine and surgery2026
Associations between altered morphometric inverse divergence networks, choroid plexus volume, and perivascular space network in patients with Parkinson disease: a cross-sectional study.
Article in Quantitative imaging in medicine and surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Recent evidence suggests that Parkinson disease (PD) involves structural alterations in gray-matter volume, cortical surface area, and cortical thickness. Clinical symptoms of PD have also been associated with the choroid plexus (CP) volume and perivascular space (PVS) network parameters. However, the relationship between morphometric inverse divergence (MIND) network alterations and CP volume or PVS network parameters in PD remains unclear. This study aimed to clarify these associations via multimodal imaging analyses. Methods: This retrospective study included healthy controls (HCs; n=82) and patients with PD (n=99) who underwent 3.0-T magnetic resonance imaging (MRI). MIND network analysis quantified interregional structural similarity through use of multiple anatomical MRI measures across brain regions. CP volume and PVS network parameters, including extracellular free water (FW) fraction, diffusion tensor imaging-analysis along the PVS (DTI-ALPS) index, and PVS volume fraction (PVSVF), were calculated. Pearson correlation coefficients were used to assess statistical associations. Results: MIND values were predominantly lower in the frontal and occipital cortical regions and higher in the cingulate and insular cortical regions in patients with PD (P<0.05). In patients with PD, regional MIND values were positively associated with CP volume (R=0.29; P<0.05) and FW fraction (R=0.28 to 0.60; P<0.05), negatively associated with the DTI-ALPS index (R=-0.36 to -0.37: P<0.05), and not significantly correlated with PVSVF (P>0.05). Conclusions: These findings enhance the understanding of macrostructural alterations in PD and provide insight into the associations among brain structure, CP volume, and the PVS network.
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