Most recent paper

Psychoradiology. 2025 Sep 23;5:kkaf026. doi: 10.1093/psyrad/kkaf026. eCollection 2025.

ABSTRACT

BACKGROUND: Molecular imaging plays a key role in advancing understanding of neuropsychiatric disorders. However, the conceptual structure of this interdisciplinary field remains poorly mapped from a bibliometric perspective. The objective of this study was to explore the intellectual structure and thematic development of research on molecular imaging applied to neuropsychiatric disorders using co-citation network analysis.

METHODS: A bibliometric co-citation analysis was conducted using data retrieved from Scopus. A targeted search strategy identified articles from 2014 to 2023 focused on MRS, fMRI, PET, and SPECT in the context of neuropsychiatric disorders. Bibliographic data were exported, and cited references were analyzed using VOSviewer. A manually curated thesaurus was applied to unify variant citations and reduce duplication. Co-citation networks were generated, and thematic clusters were identified and interpreted based on total link strength and citation density.

RESULTS: The co-citation network included 51 documents and revealed six major thematic clusters encompassing automated anatomical labeling and brain segmentation, functional and structural connectivity, affective neuroscience, clinical biomarkers, and methodological standardization. Notable references included foundational works on resting-state functional connectivity, motion correction, and diagnostic criteria for neuropsychiatric disorders. The clustering structure highlighted the convergence of radiology, neuroscience, and psychiatry around shared methodological tools and conceptual frameworks.

CONCLUSION: Co-citation analysis revealed a well-defined and maturing intellectual landscape in molecular imaging applied to neuropsychiatry. The identified clusters represent distinct yet interconnected research lines, reflecting methodological innovation and translational potential. These findings offer a roadmap for future research, emphasizing methodological rigor, interdisciplinary collaboration, and clinical applicability.

PMID:41200096 | PMC:PMC12586992 | DOI:10.1093/psyrad/kkaf026

Psychoradiology. 2025 Oct 13;5:kkaf027. doi: 10.1093/psyrad/kkaf027. eCollection 2025.

ABSTRACT

BACKGROUND: The thalamo-prefrontal white matter (WM) pathway, a core structural element of the frontal-limbic system disrupted in premenstrual syndrome (PMS), remains poorly understood.

METHODS: Diffusion tensor imaging (DTI), functional MRI (fMRI), and serum cytokine levels were collected from 41 PMS participants and 51 healthy controls (HCs), all diagnosed using the Daily Record of Severity of Problems (DRSP) scale. Bilateral thalamic-frontal WM pathways-the anterior thalamic radiations (ATRs)-were reconstructed using probabilistic fiber tracking. Two-sample tests examined group differences in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), and amplitude of low-frequency fluctuation (ALFF) within bilateral ATRs. Spearman correlations assessed associations among these MRI metrics, inflammatory cytokines, and DRSP scores. Machine learning models further evaluated the diagnostic and predictive utility of left ATR features combined with inflammatory cytokines.

RESULTS: Compared to HCs, PMS patients exhibited increased MD, AD, RD, and ALFF values in the left ATR, as well as elevated tumor necrosis factor (TNF)-α levels. Correlation analysis revealed that these MRI alterations in the left ATR and TNF-α levels were linked to DRSP scores. Additionally, the machine learning models constructed using the optimal feature subset, involved in MD, AD and ALFF of left ATR as well as TNF-α, demonstrated robust performance in diagnosing PMS and predicting DRSP scores.

CONCLUSION: These findings suggest altered thalamo-frontal WM connectivity and elevated TNF-α in PMS. The left ATR may serve as a biomarker of PMS neuro-mechanisms when combined with multi-MRI and inflammation metrics.

PMID:41200094 | PMC:PMC12586991 | DOI:10.1093/psyrad/kkaf027