This study investigated regional and whole-brain microstructural alterations following stroke using diffusion tensor imaging (DTI) and Mean Apparent Propagator MRI (MAP-MRI). Multi-shell diffusion and T1-weighted MRI data were analyzed from participants with chronic stroke and healthy controls. DTI-derived fractional anisotropy (FA) and mean diffusivity (MD), and MAP-MRI-derived return-to-origin (RTOP), return-to-axis (RTAP), and return-to-plane (RTPP) probabilities were quantified across 13 predefined regions in native diffusion space. Regional group differences were assessed using participant-level median values with Benjamini–Hochberg false discovery rate (BH-FDR) correction across all 65 ROI × diffusion-metric comparisons and age- and sex-adjusted sensitivity analyses. Complementary lesion-relative whole-brain analyses used nonparametric permutation testing with threshold-free cluster enhancement and family-wise error correction.MAP-MRI demonstrated widespread regional abnormalities, with significant group differences in 11 of 13 regions for RTOP, 12 of 13 for RTAP, and 10 of 13 for RTPP, compared with 8 of 13 for FA and all 13 regions for MD. After adjustment for age and sex, significant differences remained in 11, 10, and 9 regions for RTOP, RTAP, and RTPP, respectively, compared with 6 for FA and all 13 for MD. Whole-brain analyses demonstrated significant corrected abnormalities across all five diffusion metrics, with RTOP and RTAP showing the most spatially extensive Control > Stroke effects, followed by RTPP and FA, whereas MD showed extensive effects in the opposite, Stroke > Control direction. Regional discrimination varied by anatomical region and metric, without a uniform advantage of MAP-MRI over DTI. Exploratory diffusion–function analyses identified several nominal associations, but none survived correction across all comparisons.These findings demonstrate complementary, region- and metric-specific sensitivity of MAP-MRI and DTI to chronic stroke-related microstructural abnormalities. MAP-MRI identified distributed abnormalities across regional and whole-brain analyses, while MD remained highly sensitive to widespread tissue differences. The differing spatial distributions and regional discriminative performance of MAP-MRI and DTI suggest that these approaches capture partially distinct features of the post-stroke diffusion environment. Together, these findings support their complementary use for characterizing distributed microstructural abnormalities following chronic stroke.
Background Parkinson's disease (PD) diagnosis remains primarily clinical and is often delayed until substantial neurodegeneration has occurred. Neuromelanin-sensitive MRI (NM-MRI) assesses the integrity of neuromelanin-rich nuclei affected in PD, the substantia nigra pars compacta (SNpc) and locus coeruleus (LC), but its diagnostic performance, technical determinants, and translational applicability remain unclear amid heterogeneity. We aimed to quantify diagnostic accuracy, determine whether performance varies across methodological approaches, and contextualise evidence from clinically relevant settings. Methods We systematically reviewed NM-MRI diagnostic studies through December 2025. QUADAS-2 assessed risk of bias. Sensitivity and specificity were jointly pooled using a bivariate model, and AUC using random-effects meta-analysis. Subgroup analyses and exploratory meta-regressions assessed methodological heterogeneity; broader clinical evidence was synthesised qualitatively. Results Thirty-nine studies were included. Across 20 PD-versus-healthy-control (HC) studies (878 PD; 690 HCs), pooled sensitivity was 89.03% (95% CI 86.01–91.45%), specificity 87.02% (95% CI 82.76–90.34%), PLR 6.86, NLR 0.126, and DOR 54.37. Across 32 studies (1411 PD; 1086 HCs), pooled AUC was 0.909 (95% CI 0.884–0.929; I2 = 64.6%). No significant unadjusted differences emerged by sequence, dimensionality, segmentation, or measurement type. NM-MRI abnormalities were detectable across prodromal, early- and advanced-stage PD, although global measures showed limited discrimination between disease stages. Subregional measures captured phenotypic variation, genotype discrimination was limited, and PD-versus-ET/APS performance was promising but variable, within small, heterogeneous evidence bases. Conclusion NM-MRI is a promising non-invasive imaging biomarker for PD, with strong discrimination across diverse methodological approaches. Harmonised acquisition and analysis, externally validated diagnostic thresholds, and prospective multicentre studies in clinically representative populations are needed to support future clinical implementation.
Background Electroconvulsive therapy (ECT) induces hippocampal volume alterations, but the clinical significance of the volumetric change remains unclear. Greater electric field (EF) strength has been associated with increases in hippocampal volume and decline in cognitive performance following ECT, and this association might be moderated by individual-level variables, such as sex. Methods In this study, 29 patients with severe or treatment-resistant depression underwent right unilateral ECT. EF strength was simulated using ROAST, and hippocampal volumes were segmented with FreeSurfer. Cognitive performance was assessed pre- and post-ECT using a multidomain neuropsychological battery. Associations between EF strength, hippocampal volume change, and cognitive outcomes were analyzed, with sex as a moderator. Results At the group level, ECT reduced depressive symptom severity, without cognitive decline. Female patients exhibited higher EF strength in bilateral hippocampi, associated with smaller intracranial volumes and greater changes in the left hippocampal volume following ECT. Exploratory analyses indicated that higher EF strength and greater left hippocampal volume increase were linked to smaller improvement in verbal memory performance; moreover, a sex×volume interaction suggested opposite trends by sex, with volume increase correlating with greater improvement in males but smaller in females. Greater hippocampal volume change was also linked to lower consistency in autobiographical memory; however, post-hoc sensitivity analysis indicated that this association was outlier-driven and should be interpreted with caution. Conclusions Our findings suggest that individual anatomical variability influences the EF and may contribute to cognitive side effects following ECT. Awareness of anatomy-related EF differences may inform future research strategies for individualized treatment planning and cognitive monitoring.
Background Post-stroke fatigue is common and disabling, yet rarely distinguished from co-occurring depression, limiting understanding of its neural substrates. We examined resting-state fMRI correlates of post-stroke fatigue while accounting for depressive symptoms. Methods We studied 103 stroke patients and 29 age-matched controls from a longitudinal neuroimaging cohort. Fatigue was assessed via the SF-36 Vitality subscale and depression via the Geriatric Depression Scale - Short (GDS-15). Linear mixed-effects models evaluated associations between vitality and resting-state functional connectivity, adjusting for depression and covariates. Residualized vitality models served as sensitivity analyses to isolate fatigue variance independent of depressive symptoms, with FDR correction applied within feature families. Results In depression-adjusted models, higher vitality (lower fatigue) was associated with increased frontoparietal-limbic connectivity (β = 0.0013, FDR q = 0.048), though this did not survive depression residualization. In a residualized sensitivity analysis, higher vitality (lower fatigue) was associated with reduced thalamus-insula and thalamus-ventral attention network connectivity (thalamus-insula: β = −0.0071, FDR q = 0.011; thalamus-VAN: β = −0.0043, FDR q = 0.012); these associations were attenuated and did not survive correction in the primary depression-adjusted model (q ≈ 0.075). Conclusions Fatigue was associated with both frontoparietal-limbic and thalamocortical connectivity, although the thalamic associations were attenuated after adjustment for depressive symptoms in the primary analysis and were most evident in residualized sensitivity analyses. These findings suggest that fatigue and depressive symptoms may involve both shared and potentially distinct neural correlates. Point estimates were smaller in stroke participants than controls, providing no evidence that the observed associations were stroke-specific. Future work should determine whether these relationships are unique to stroke or reflect broader neural correlates of fatigue across clinical populations.
