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

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.

investigation of cerebral iron deposition in aged patients with ischemic cerebrovascular disease using susceptibility-weighted imaging

Do cerebral white matter lesions influence the rate of progression from mild cognitive impairment to dementia?

White Matter and Perivascular Imaging Changes in Alzheimer's Disease and Cerebral Amyloid Angiopathy

ABSTRACT Objective Peak‐width of skeletonized mean diffusivity (PSMD) and diffusion tensor imaging–analysis along the perivascular space (DTI‐ALPS), reflecting white matter integrity and glymphatic function, are altered in Alzheimer's disease (AD). We evaluated whether these biomarkers differ between AD participants with and without concomitant cerebral amyloid angiopathy (CAA). Methods The study included 50 AD participants with mild cognitive impairment/mild dementia, and intermediate to high AD neuropathologic change at autopsy. AD was categorized as AD with CAA and AD without CAA based on CAA neuropathology. We evaluated global and regional (frontal, parietal, temporal and occipital) PSMD; left, right and mean DTI‐ALPS indices and their association with clinical measures [Clinical dementia rating sum‐of‐boxes (CDR‐SB) from CDR Dementia Staging Instrument, mini mental state examination (MMSE), cognitive composites: memory, processing speed, executive function, and language]. Results AD participants with CAA (n = 17) had higher global [4.02 ± 1.44 (mean ± SD × 10−4 mm2/s) vs. 3.12 ± 0.91, β = −0.80, 95% CI (−1.42, −0.18), p = 0.012] and occipital PSMD [4.02 ± 1.10 vs. 3.00 ± 1.08, β = −0.88, 95% CI (−1.51, −0.26), p = 0.026] than those without CAA. No PSMD metric was associated with any clinical measure. However, imaging‐by‐group interactions showed global PSMD associated with language [β = −0.89, 95% CI (−1.53, −0.26), p = 0.027] and parietal PSMD with language [β = −1.05, 95% CI (−1.74, −0.36), p = 0.014] and memory [β = −0.83, 95% CI (−1.38, −0.28), p = 0.015]. DTI‐ALPS indices did not differ by group. Higher mean and right DTI‐ALPS indices were associated with preserved language function [mean: β = 9.33, 95% CI (2.05, 16.62), p = 0.036; right: β = 7.75, 95% CI (1.54, 13.95), p = 0.043] without imaging‐by‐group interactions. Interpretation Global and occipital PSMD may help identify AD participants with concomitant CAA.

T1 mapping in Alzheimer’s disease: a quantitative MRI study with amyloid-PET correlation

Quantitative T1 mapping (qT1) is a magnetic resonance imaging (MRI) biomarker of brain microstructural changes; however, its application in Alzheimer disease (AD) remains limited. We compared cortico-limbic qT1 values between patients with AD and healthy controls (HCs) and examined their relationship with amyloid burden measured by amyloid-positron emission tomography (PET). We retrospectively identified subjects with mild cognitive impairment due to AD and HCs who underwent 3-T MRI, including a compressed-sensing MP2RAGE sequence, generating three-dimensional T1-weighted images and qT1 maps. Amyloid-PET was available for 16 patients. Hippocampal qT1 and volume were compared between groups, adjusting for age and sex; analyses were repeated after stratifying patients by Mini-Mental State Examination (MMSE). Voxel-wise group comparison was performed using SPM 12. The qT1-standardized uptake value ratio (SUVr) association was assessed with a linear mixed-effects model applied to voxel-level data, accounting for partial volume effects. Thirty-three AD subjects, aged 69.3 ± 8.2 years (mean ± standard deviation), 18 females, and 22 HCs aged 70.5 ± 13.3 years, 15 females, were evaluated. Regional hippocampal qT1 was higher in AD (1,398 ± 53.0 ms versus 1,349 ± 53.4 ms; p = 0.002), without difference across cognitive subgroups stratified by MMSE. AD subjects exhibited increased qT1 in mesial temporal gray matter and temporo-parieto-occipital cortices (1,448 ± 55.7 ms versus 1,344 ± 51.6 ms; p < 0.001). Voxel-level modelling revealed a positive association between qT1 and amyloid-PET SUVr (p < 0.001; d = 0.223). qT1 mapping can be sensitive to changes related to brain amyloidosis, supporting its role as a promising, noninvasive imaging biomarker in AD. Question Can qT1 mapping detect AD-related microstructural changes in the cortico-limbic gray matter? Findings Participants with AD showed increased cortico-limbic qT1 values. A subtle yet consistent positive association was observed between cortical qT1 values and amyloid-PET SUVr. Relevance statement qT1 mapping captures microstructural tissue alterations related to amyloid pathology in Alzheimer’s disease, supporting its role as a potential non-invasive imaging biomarker in this condition.

Advanced neuroimaging of vascular cognitive impairment and dementia: biomarkers, guidelines, and clinical impact.

Vascular cognitive impairment and dementia (VCID) is a leading modifiable contributor to dementia, accounting for an estimated 27-33% of attributable dementia cases. Neuroimaging is central to detection, phenotyping, and longitudinal monitoring. This neuroradiology-focused review integrates the STRIVE-2 imaging lexicon with the VasCog-2 clinical framework and reviews the advanced MRI techniques most pertinent to VCID, spanning clinically established to emerging research approaches: arterial spin labelling, diffusion tensor imaging including peak width of skeletonised mean diffusivity (PSMD), quantitative susceptibility mapping, vessel architecture imaging, and resting-state functional MRI. Unlike previous reviews, we consolidate operational quantitative thresholds already informing decisions (the Staals total small-vessel-disease score, longitudinal white matter hyperintensity progression linked to dementia risk, microbleed and cortical superficial siderosis (cSS) criteria for anti-amyloid therapy eligibility, and validated PSMD reference ranges) and we critically address gaps between research-grade acquisitions and routine clinical workflows. Automated segmentation and structured reporting are transitioning into deployment, expanding the radiologist's role to combine pattern recognition with quantitative characterisation. We outline current limitations of standardisation, reproducibility, and external validation that remain prerequisites before quantitative VCID imaging achieves formal regulatory biomarker qualification.