Accelerated Brain Atrophy in Epilepsy: A Prospective Population-Based Study.

Predicting future brain atrophy based on longitudinal MRI

Background Neuron loss is a hallmark of neurodegenerative diseases and leads to brain atrophy detectable with magnetic resonance imaging (MRI). Accurate prediction of future atrophy is valuable for research in Alzheimer's disease (AD) and related dementias. Objective This study aimed to predict annualized percentage changes in hippocampal, ventricular, and total gray matter (TGM) volumes in individuals ranging from cognitively normal to dementia, and to evaluate whether longitudinal MRI-derived change measures improve prediction performance compared with single-time-point MRI information. Methods Using elastic net regression, we compared baseline models based on single-timepoint MRI information with longitudinal models incorporating prior MRI-derived change measures. Both approaches were evaluated as MRI-only and MRI + risk-factor variants, with risk factors including age, sex, APOE4, and diagnostic status. Results In cross-validated analyses using the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, the longitudinal MRI + risk-factor model performed best, yielding Pearson correlations of 0.62 for hippocampal atrophy, 0.51 for ventricular enlargement, and 0.41 for TGM atrophy. Longitudinal models consistently outperformed single time-point models, and adding risk factors improved predictive performance beyond MRI alone. External validation using the Australian Imaging, Biomarkers and Lifestyle cohort confirmed these findings. Predicted atrophy outperformed present-day regional volumes in identifying individuals progressing from normal cognition to MCI/dementia and from MCI to dementia. Conclusions MRI-derived longitudinal features enhance atrophy prediction, and predicted atrophy rates provide sensitive markers of future cognitive decline. These findings support the potential utility of predicted atrophy for cohort enrichment and therapeutic trial design.

Subcortical gray matter atrophy and iron deposition in patients with vascular dementia: a multimodal MRI study

Purpose Vascular dementia (VAD) is the second most common type of dementia worldwide. Therefore, early detection and diagnosis, along with a clear understanding of its pathogenesis are critical for mitigating disease progression. In the present study, we aimed to elucidate the associations of brain volume and iron deposition with VAD based on structural brain and iron content analyses. Methods Fifty-three patients with VAD and 43 control participants were recruited for this study. All participants underwent the Mini-Mental State Examination (MMSE) and brain MRI scans. This study primarily focused on the volume of specific brain regions (assessed using FreeSurfer) and iron deposition (evaluated using quantitative susceptibility mapping [QSM]). Linear regression analysis was also performed. Results Patients with VAD exhibited significant reductions in brain volume in the left putamen (β = −0.342, 95% CI: −0.581 to −0.104), left pallidum (β = −0.099, 95% CI: −0.187 to −0.001), left hippocampus (β = −0.138, 95% CI: −0.271 to −0.004), and right hippocampus (β = −0.235, 95% CI: −0.420 to −0.051). Additionally, significant increases in iron levels were identified in the left (β = 0.006, 95% CI: 0.002 to 0.010) and right (β = 0.005, 95% CI: 0.001 to 0.009) hippocampus. Conclusions These findings indicate that brain volume reduction and increased iron levels in specific regions may be associated with cognitive deficits in patients with VAD.

Macro-structural brainstem volumetry in generalized epilepsy: assessment of subcortical network involvement

Magnetic Resonance Imaging-Based Cortical and Subcortical Volumetric Changes in Alzheimer’s Disease: Association with Clinical Severity

Background/Objectives: This study evaluated automated magnetic resonance imaging (MRI) volumetry for characterizing structural brain changes in Alzheimer’s disease (AD), mild cognitive impairment (MCI), and cognitively healthy controls (HC), and examined its association with cognitive performance. Methods: This retrospective observational study included consecutively enrolled individuals aged ≥65 years. AD dementia and MCI were diagnosed according to the 2011 National Institute on Aging–Alzheimer’s Association (NIA-AA) clinical criteria. Automated volumetric analysis of structural MRI was used to obtain the total intracranial volume-normalized cortical and subcortical volumes, cerebrospinal fluid (CSF) compartments, and hemispheric asymmetry indices. Between-group comparisons were corrected using the Benjamini–Hochberg false discovery rate. Prespecified volumetric markers were evaluated using receiver operating characteristic analysis and internally validated logistic regression models. Results: The study included 102 participants (34 per group). Compared with HC, the AD group showed lower total cerebrum, right hippocampal, and anterior cingulate gyrus (ACgG) volumes and higher CSF volumes. Compared with MCI, the AD group exhibited lower thalamic and caudate volumes. CSF volume showed the highest individual discriminative performance for differentiating AD from HC (AUC = 0.837), whereas the combined hippocampal–ACgG–CSF model showed the best performance for differentiating MCI from HC (AUC = 0.826). After adjustment for diagnostic group, cognitive performance remained positively associated with hippocampal volume and negatively with CSF and lateral ventricular volumes. Conclusions: Automated MRI volumetry may support the quantitative assessment of neurodegeneration in clinically defined AD and MCI. Combined volumetric markers improved discrimination between MCI and HC, although these findings require external validation in larger, longitudinal, biomarker-characterized cohorts.

Cognitive and Biomarker Signatures of Late-Onset Temporal Lobe Epilepsy

Background and Objectives Late-onset unexplained epilepsy (LOUE) represents a substantial proportion of epilepsies with onset after 50 years and often manifests as temporal lobe epilepsy (LO-TLE). Although a link with Alzheimer disease (AD) has been suggested, only a subset of LO-TLE shows AD-related biomarkers, indicating biological heterogeneity. This study aims to characterize the cognitive and CSF phenotype of LO-TLE and compare it with healthy controls (HCs) and patients with mild cognitive impairment due to AD (MCI-AD). Methods This Italian cross-sectional cohort study included LO-TLE patients with normal CSF β-amyloid (Aβ) biomarkers, MCI-AD, and age-matched and sex-matched HC. Participants underwent structural MRI, neuropsychological assessment, and CSF biomarkers assay, including neurofilament light chain (NfL) and the phosphorylated-to-total tau ratio (p/t-tau). Cortical thickness and subcortical volumes were quantified from structural MRI. Cognitive performance was summarized using principal component analyses. Group differences in imaging, cognition, and CSF biomarkers were assessed, and associations between CSF markers and cognition were examined within groups. Results The study included 18 LO-TLE, 24 MCI-AD, and 17 HC. LO-TLE showed preserved cortical thickness and subcortical volumes comparable with HC, whereas MCI-AD exhibited widespread cortical thinning and medial temporal atrophy. Despite normal imaging, LO-TLE showed lower performance compared with HC in episodic memory (t(53) = −7.79, pFDR < 0.001), short-term memory (t(53) = −2.94, pFDR = 0.007), language (t(53) = 4.12, pFDR < 0.001), and executive functions (t(53) = −3.76, pFDR < 0.001), while attention was preserved. Global cognitive performance further distinguished LO-TLE from MCI-AD, with the former group performing better (t(53) = 4.21, pFDR < 0.001). LO-TLE CSF profiles were characterized by low NfL levels and a p/t-tau ratio below the proposed cutoff of 0.17, whereas MCI-AD showed pathologic Aβ and tau alterations, elevated NfL, and p/t-tau ratio above 0.17. In LO-TLE, a higher p/t-tau ratio was associated with better performance on global cognition (rs = 0.585, pFDR = 0.032) and short-term memory (rs = 0.588, pFDR = 0.032), whereas no associations emerged in MCI-AD. Discussion LO-TLE with normal CSF AD biomarkers is characterized by distinct cognitive and biological features compared with MCI-AD, suggesting a disease process independent of AD. The low p/t-tau ratio may reflect alternative pathophysiologic mechanisms and warrants further investigation in larger longitudinal studies to clarify the underlying pathology and clinical trajectories.

Topographic-prognostic gradients of cortical hypometabolism in temporal lobe epilepsy

A hypometabolic gradient is identified in TLE, which covaries with cytoarchitectonic organization, microstructural changes, and hippocampal-neocortical interactions and provides a biologically grounded framework for precise surgical planning, emphasizing that targeting severe hypometabolism may optimize prognosis.