Medial Temporal Atrophy Research Articles (Page 1)

The association of diabetes with Alzheimer's disease biomarkers and vascular burden across European aging and memory clinic cohorts

Medial Temporal Atrophy (MTA) is a key biomarker in the early diagnosis of dementia. However, its assessment through manual inspection of MRI scans is subjective, time-consuming, and prone to inter-observer variability. This creates the need for automated systems that can provide accurate, consistent, and clinically interpretable evaluations. This study aims to develop a hybrid deep learning framework that integrates U-Net with a ResNet-50 backbone for simultaneous hippocampal segmentation and MTA grading, thereby reducing diagnostic subjectivity and bridging the gap between image processing and clinical interpretation. The main contribution of this work lies in the dual functionality of the proposed architecture: not only producing precise segmentation masks of the hippocampal region but also classifying the degree of atrophy into MTA scores (0–4), which previous studies on hippocampal segmentation have not addressed. The proposed method employs a U-Net for pixel-level segmentation, enhanced with a ResNet-50 backbone to stabilize gradient propagation and enrich feature representation during encoding. Results demonstrated excellent performance, achieving a training accuracy of 99.9% with strong convergence between training and validation curves. On a test set of 32 coronal MRI slices, the model correctly classified 26 samples, misclassifying only 6. Overall, the proposed U-Net with ResNet-50 backbone provides an accurate and reliable end-to-end solution for hippocampal segmentation and MTA grading. Its clinical performance demonstrates parity with expert radiologists, underscoring its potential as a decision-support tool in dementia diagnosis. Future work will focus on extending this framework to 3D U-Net architectures, enabling the integration of volumetric MRI features to enhance robustness and generalizability across diverse datasets further

Aims: This study aimed to evaluate the impact of atrial fibrillation (AF) on cognitive function and neuroradiological markers in patients with Alzheimer’s disease (AD). Methods: A total of 800 patients were screened at the Dementia Outpatient Clinic of Sancaktepe Şehit Prof. Dr. İlhan Varank Training and Research Hospital. Thirty-three AD patients with confirmed AF were included, alongside 31 age-, sex, and education-matched AD patients without AF as controls. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), while mood symptoms were evaluated with the Geriatric Anxiety Scale and the Geriatric Depression Scale. Brain MRI scans were analyzed using Fazekas, Medial Temporal Atrophy (MTA), and Koedam scores. Due to the modest sample size, this study is best interpreted as exploratory in nature. Results: After six months, the AF-positive group exhibited a significant decline in MMSE scores, whereas the AF-negative group showed no significant change. Koedam scores were significantly higher in the AF-positive group, indicating more advanced cortical atrophy. Regression analysis revealed that AF had a borderline significant negative impact on cognitive performance after adjusting for baseline MMSE scores. Conclusion: AF may accelerate cognitive decline and is associated with greater cortical atrophy in patients with AD. These findings suggest that close cognitive monitoring and individualized care strategies may be beneficial in this population, though further research is needed to confirm this.

To identify clinical and radiological features of cerebral amyloid angiopathy-related inflammation (CAA-ri), and compare these features with those of sporadic CAA, to improve the understanding, diagnosis, and clinical care of CAA-ri. We retrospectively reviewed routine clinical data from 37 patients with CAA-ri and 158 patients with sporadic CAA, including conventional vascular risk factors and comorbidities. We assessed brain magnetic resonance imaging for: radiological markers of CAA; features of amyloid-related imaging abnormalities with edema/effusion (ARIA-E) including parenchymal white matter hyperintensities, sulcal hyperintensities, and gyral swelling; and evidence of neurodegeneration (medial temporal atrophy and global cortical atrophy). Compared with patients with sporadic CAA, patients with CAA-ri had more numerous lobar cerebral microbleeds (median 207[IQR 33-811] vs 19[IQR 7-58], p < 0.001), and higher rates of medial temporal and global cortical atrophy. In comparison with sporadic CAA, all ARIA-E features were much more common in patients with CAA-ri (parenchymal hyperintensities 89% vs 3%, sulcal hyperintensities 78% vs 9%, and gyral swelling 86% vs 0.6%), as were conventional vascular risk factors (hypertension, dyslipidemia) and long-term comorbidities (inflammatory and infectious disorders, autoimmune or connective tissue disorders, or malignancies). Features of ARIA-E (parenchymal white matter hyperintensities, sulcal hyperintensities, and gyral swelling) are more common in CAA-ri in comparison with "non-inflammatory" sporadic CAA, suggesting shared mechanisms with Alzheimer's disease immunotherapy and a potential role in improving diagnostic accuracy for CAA-ri. The high prevalence of atrophy and lobar cerebral microbleeds suggests a potential mechanistic role for capillary CAA, Alzheimer's disease, or both, in CAA-ri. Cardiovascular risk factors and other long-term comorbidities may also be relevant to the underlying mechanisms of CAA-ri. ANN NEUROL 2025 ANN NEUROL 2025.

Cognitive function, psychobehavioral symptoms, and MRI features in patients with non-demented Parkinson's disease, Parkinson's disease with dementia, and dementia with Lewy bodies.

BackgroundPatients with Alzheimer's disease (AD) displayed abnormal retinal morphology; however, its potential associations with clinical symptoms, damage of the blood-brain barrier (BBB), and brain structure are unclear.ObjectiveTo investigate the correlations of retinal morphology with clinical symptoms, BBB damage, and brain structure in AD patients.MethodsIn 97 patients with mild cognitive impairment due to AD (AD-MCI) and dementia due to AD (AD-D), retinal morphology, clinical symptoms, BBB variables in cerebrospinal fluid, and brain structure variables, including medial temporal atrophy (MTA), global cortical atrophy (GCA), and white matter hyperintensities scores were evaluated.ResultsIn AD patients, peripapillary superotemporal retinal nerve fiber layer thickness (NFLT) was positively correlated with memory score; the NFLTs of average, inferior, and inferotemporal quadrants were negatively correlated with the level of matrix metalloproteinase 3 level in cerebrospinal fluid; the NFLTs of average, superior, and inferior quadrants were negatively correlated with MTA and GCA scores; superotemporal NFLT was negatively correlated with GCA score. In AD-MCI group, superotemporal NFLT maintained a positive correlation with memory score; the NFLTs in superior and nasoupper quadrants were negatively associated with GCA score. In AD-D group, superonasal NFLT was negatively correlated with matrix metalloproteinase 9 level in cerebrospinal fluid.ConclusionsIn AD patients, thinner peripapillary NFLT mirrors worse memory, significant BBB damage, the atrophy of medial temporal lobe and cortex. In AD-MCI patients, thinner NFLT mirrors worse memory and cortical atrophy. In AD-D patients, thinner NFLT mirrors significant BBB damage.

ABSTRACTThe hippocampal‐to‐ventricle ratio (HVR) is a biomarker of medial temporal atrophy, particularly useful in the assessment of neurodegeneration in diseases such as Alzheimer's disease (AD). To minimize subjectivity and inter‐rater variability, an automated, accurate, precise, and reliable segmentation technique for the hippocampus (HC) and surrounding cerebro‐spinal fluid (CSF) filled spaces—such as the temporal horns of the lateral ventricles—is essential. We trained and evaluated three automated methods for the segmentation of both HC and CSF (Multi‐Atlas Label Fusion (MALF), Nonlinear Patch‐Based Segmentation (NLPB), and a Convolutional Neural Network (CNN)). We then evaluated these methods, including the widely used FreeSurfer technique, using baseline T1w MRIs of 1641 participants from the AD Neuroimaging Initiative study with various degree of atrophy associated with their cognitive status on the spectrum from cognitively healthy to clinically probable AD. Our gold standard consisted in manual segmentation of HC and CSF from 80 cognitively healthy individuals. We calculated HC volumes and HVR and compared all methods in terms of segmentation reliability, similarity across methods, sensitivity in detecting between‐group differences and associations with age, scores of the learning subtest of the Rey Auditory Verbal Learning Test (RAVLT) and the Alzheimer's Disease Assessment Scale 13 (ADAS13) scores. Cross validation demonstrated that the CNN method yielded more accurate HC and CSF segmentations when compared to MALF and NLPB, demonstrating higher volumetric overlap (Dice Kappa = 0.94) and correlation (rho = 0.99) with the manual labels. It was also the most reliable method in clinical data application, showing minimal failures. Our comparisons yielded high correlations between FreeSurfer, CNN and NLPB volumetric values. HVR yielded higher control:AD effect sizes than HC volumes among all segmentation methods, reinforcing the significance of HVR in clinical distinction. The positive association with age was significantly stronger for HVR compared to HC volumes on all methods except FreeSurfer. Memory associations with HC volumes or HVR were only significant for individuals with mild cognitive impairment. Finally, the HC volumes and HVR showed comparable negative associations with ADAS13, particularly in the mild cognitive impairment cohort. This study provides an evaluation of automated segmentation methods centered to estimate HVR, emphasizing the superior performance of a CNN‐based algorithm. The findings underscore the pivotal role of accurate segmentation in HVR calculations for precise clinical applications, contributing valuable insights into medial temporal lobe atrophy in neurodegenerative disorders, especially AD.

BackgroundWhite matter hyperintensities (WMH) are commonly observed in Alzheimer's disease (AD), but their underlying pathophysiology remains poorly understood.ObjectiveThis cross-sectional study aims to explore the multifactorial etiologies and cognitive correlates of global and regional WMH in a cohort of biologically diagnosed AD patients.MethodsWe included 170 AD patients who underwent brain MRI, neuropsychological testing, and cerebrospinal fluid (CSF) biomarker evaluation within three months. Linear and logostic regressions were used to assess associations between global/regional WMH and age, cerebral microbleeds (CMB), AD biomarkers, cortical atrophy, and vascular risk scores. Sensitivity analyses included replacing vascular score with hypertension, p-tau181 with t-tau, and inclusion of APOE ε4 status. Associations between Mini-Mental State Exam scores and WMH and atrophy burden were also evaluated, adjusting for age, sex, and education.ResultsGreater global WMH burden was significantly associated with older age (β = 0.03, p < 0.001), lower CSF Aβ42 levels (β = -0.0014, p = 0.01), and more severe CMB grade (β = 0.48, p = 0.003), but not with vascular risk scores. Regionally, WMH in the paraventricular, frontal, and parietal lobes were linked to CSF Aβ42 and CMB. Cognitive impairment was independently associated with increased paraventricular WMH burden (β = -0.22, p < 0.001) and medial temporal atrophy (β = -0.82, p < 0.001).ConclusionsOur findings suggest that WMH in AD-particularly in the paraventricular, frontal, and parietal areas-are driven more by AD-specific pathology, including amyloid deposition and cerebral amyloid angiopathy, than by conventional vascular risk. Paraventricular WMH contribute to cognitive decline independent of cortical atrophy, underscoring their relevance as potential imaging biomarkers in AD.

Introduction: The usefulness of neuroimaging in patients with first-episode psychosis (FEP) remains controversial. The aim of this study was to assess the prevalence and types of structural abnormalities on neuroimaging in patients with FEP and identify the most frequently used imaging modalities in a real-world setting. Methodology: A retrospective observational study based on a consecutive series of patients admitted to our institution with FEP was conducted. We analyzed the imaging tests performed, the presence of specific lesions, the degree of cortical atrophy (Global Cortical Atrophy, GCA scale), medial temporal atrophy (Medial Temporal lobe Atrophy, MTA scale) and non-specific white matter lesions (Fazekas scale). Descriptive and bivariate analyses were performed according to previously established age cut-offs. Results: A total of 105 patients were included (median age: 36 years; 52.4% men). The most frequently used neuroimaging test was computed tomography (CT) (92.4%). GCA scores that were out of the age range were found in 32.4% of patients, being more frequent in those older than 65 years (p < 0.001). Out-of-range MTA scores were found in 36.2% of patients, especially in patients older than 75 years (p < 0.001). Out-of-range Fazekas scores were found in 4.3% of patients, especially in patients older than 70 years (p = 0.157). Finally, only one specific structural lesion (right frontal cavernoma) was identified in one patient (1%). Overall, at least one non-age-matched abnormality was found in 46.7% of patients. Conclusions: Although non-specific alterations not in accordance with age exist in a significant percentage of patients with FEP, the prevalence of specific lesions is very low. This suggests that neuroimaging tests could be restricted in patients with FEP, especially CT, due to the risks associated with ionizing radiation. However, further prospective and controlled studies are needed to validate our results.

Background:In mild cognitive impairment and dementia due to Alzheimer’s disease (AD), postmortem and in vivo neuroimaging studies have demonstrated significant neuronal loss in the basal forebrain cholinergic system (BFCS), which provides the primary cholinergic input to the cerebral cortex. Within this region, atrophy is most prominent in the nucleus basalis of Meynert (nbM), a group of posteriorly clustered magnocellular neurons in the BFCS. However, less is known surrounding the relationship between amyloid deposition, BFCS atrophy, and medial temporal lobe (MTL) volume loss in the preclinical stages of AD. The current study investigates the relationship between sub-structural BFCS volume and cortical Aβ burden in cognitively unimpaired middle-aged individuals at varying genetic risk for AD.Methods:Cognitively unimpaired participants aged 50–65 with a first-degree family history for AD were genetically screened to select three groups: APOE genotype ε4ε4 (n=15), ε3ε4 (n=15), and ε3ε3 (n=15), matched for age and sex. Participants underwent imaging with [11C]PiB PET and structural 3T MRI. Distribution volumes ratios (DVR) with a whole cerebellum reference region were calculated for [11C]PiB PET analyses. BFCS sub-structural volumes were obtained from the SPM8 Anatomy Toolbox (Cholinergic nuclei [Ch] 1–3, Ch4). MTL subregional volumes (entorhinal cortex, hippocampus, amygdala, parahippocampal gyrus) were extracted using Freesurfer.Results:BFCS amyloid burden was highest among APOE ε4 homozygotes (Ch1-3, F(2, 42)=3.26, P=0.048; Ch4, F(2, 42)=3.82, P= 0.03). Ch4 (nbM), but not Ch1-3 volume, was found to be inversely associated with global Aβ burden (Pearson r=−0.40, P=0.007). MTL subregional volumes were not associated with global Aβ burden in the pooled sample. Exploratory analyses in groups stratified by amyloid positivity demonstrated reduced Ch4 volume (P=0.032) and significant inverse associations between Ch4 volume and amyloid burden (Pearson r = −0.70, P=0.02) in Aβ+ participants.Conclusions:We observed nbM (Ch4), but not MTL volume, to be significantly inversely associated with cortical amyloid burden in cognitively unimpaired, Aβ+, middle-aged adults at varying genetic risk for AD. These findings provide further in vivo evidence suggesting that nbM atrophy is an early structural correlate of AD pathogenesis, potentially preceding MTL atrophy.

BackgroundTwo of the most common complaints seen in neurology clinics are Alzheimer's disease (AD) and mild cognitive impairment (MCI), characterized by similar symptoms. The aim of this study was to develop and internally validate the diagnostic value of combined neurological and radiological predictors in differentiating mild AD from MCI as the outcome variable, which helps in preventing AD development.MethodsA cross‐sectional study of 161 participants was conducted in a general healthcare setting, including 30 controls, 71 mild AD, and 60 MCI. Binary logistic regression was used to identify predictors of interest, with collinearity assessment conducted prior to model development. Model performance was assessed through calibration, shrinkage, and decision‐curve analyses. Finally, the combined clinical and radiological model was compared to models utilizing only clinical or radiological predictors.ResultsThe final model included age, sex, education status, Montreal cognitive assessment, Global Cerebral Atrophy Index, Medial Temporal Atrophy Scale, mean hippocampal volume, and Posterior Parietal Atrophy Index, with the area under the curve of 0.978 (0.934–0.996). Internal validation methods did not show substantial reduction in diagnostic performance. Combined model showed higher diagnostic performance compared to clinical and radiological models alone. Decision curve analysis highlighted the usefulness of this model for differentiation across all probability levels.ConclusionA combined clinical‐radiological model has excellent diagnostic performance in differentiating mild AD from MCI. Notably, the model leveraged straightforward neuroimaging markers, which are relatively simple to measure and interpret, suggesting that they could be integrated into practical, formula‐driven diagnostic workflows without requiring computationally intensive deep learning models.

Cerebral microbleeds are a common neuroradiological feature among the elderly population. Their contribution to the development of cognitive decline is an ongoing point of discussion. We investigated cognitive deficits and comorbidities of patients with mixed and strictly lobar microbleeds, as well as the presence of other neuroradiological features. The goal was to identify risk factors for cognitive decline. In this exploratory study, imaging markers and clinical data of 37 participants were retrospectively analyzed. Magnetic resonance images were assessed for cerebral microbleeds, lacunar infarctions, white matter hyperintensities, medial temporal lobe atrophy, global brain atrophy, and for “macro” hemorrhage (cortical superficial siderosis and intracerebral hemorrhage). Cognitive functions were assessed by neuropsychological screening examinations (n = 30) or relative’s questionnaire (n = 7). Memory was the cognitive domain most severely affected (mean ± SD, 2.34 ± 1.85) on the cognitive semiquantitative score (ranging from 0 to 6 points), while the other domains attained mean values of at least 4.75 points. Advanced age, intracerebral hemorrhage, male sex, coronary heart disease, and atrial fibrillation were more prevalent in patients with cognitive decline than without. “Macro” hemorrhage was associated with lower scores in executive functions (p-value = 0.001). Brain atrophy and medial temporal atrophy seemed to be associated with cognitive decline. Memory impairment is common in patients with cerebral microbleeds. Patients with “macro” hemorrhage show a greater cognitive decline in executive functions than subjects without. Atrial fibrillation, intracerebral hemorrhage, and coronary heart disease might be comorbidities associated with cognitive decline. Atrophy might be more relevant for cognitive decline than cerebral microbleeds.

The left piriform cortex and amygdala (PC&A) tend to be slightly hyperintense relative to the right PC&A on T2-weighted fluid-attenuated inversion recovery (T2W-FLAIR) images in patients with probable Alzheimer's disease (pAD). This likely represents the antecedent and thus advanced degeneration of the left PC&A. To investigate the relationship between left PC&A hyperintensities and cerebral cortical atrophy on magnetic resonance (MR) voxel-based morphometry in patients with pAD and discuss how this finding could relate to AD progression. Patients with pAD (n = 47; age range = 68-93years, mean = 80.8 ± 6.7years; 14 men and 33 women) who underwent T2W-FLAIR imaging and MR morphometric study using a voxel-based specific regional analysis system for AD (VSRAD) were retrospectively examined. To measure signal intensity ratios of the left to right PC&A (L-PC&A/R-PC&A), regions of interest (ROIs) were set on the transaxial images in which both PC&As were most broadly depicted; the ROIs were defined as large as possible. Correlations between the L-PC&A/R-PC&A and medial temporal lobe cortical atrophy (MTLCA) as well as whole cerebral cortical atrophy (WCCA) on VSRAD were determined. Correlation between the L-PC&A/R-PC&A and age was also determined. The L-PC&A/R-PC&A correlated with both MTLCA (r = 0.375, p = .010, 95% confidence interval [CI] = 0.095-0.600) and WCCA (r = 0.576, p < .001, 95% CI = 0.343-0.742). The L-PC&A/R-PC&A did not correlate with age (r = 0.013, p = .932, 95% CI = -0.282-0.305). Left-sided dominance of PC&A degeneration appeared to accelerate with the progression of AD stages.

BackgroundData regarding long-term recovery from autoimmune encephalitis (AE) remain limited.MethodsThis retrospective observational study investigated outcomes in 182 patients who met the 2016 criteria for definite AE. Recovery data were available...

The medial temporal lobe atrophy (MTA) score is used for visual assessment of MTA on radiological images in suspected neurodegenerative dementia. Although volumetric tools are available, many radiologists still use visual scoring and compare to reference images. Numerous such example images are found online on educational websites and in scientific articles. The aim of this study was to compare congruencies between MTA scores of publicly available sample images with normalized heights and areas of relevant brain structures, measured in the same images.MethodSystematic online searches yielded 148 individual sample images. The height and area of relevant brain structures were manually delineated, normalized, and compared with regard to the displayed MTA score.ResultsThe normalized heights and areas showed correlation with MTA but with considerable overlap between adjacent scores, especially when comparing heights. Also, displays of the MTA score were more consistent with the area of the temporal horn than with the hippocampal area.ConclusionThere is considerable overlap between adjacent scores in publicly available pictorial displays of the MTA grading system. Insufficient congruency leads to confusion and reduces inter-rater reliability. We also found that publicly available images are more consistent with temporal horn area than the hippocampus, which means that ventricular size may bias the grading. This can impede relevant differential diagnostics, especially regarding normal pressure hydrocephalus. Here, we present lectotype images selected specifically with regard to the hippocampal area.Key PointsQuestionOverlap between publicly available example images of medial temporal atrophy causes confusion and limits reliability.FindingsAvailable images are more consistent with ventricular dilatation than hippocampal atrophy; this article provides lectotype images selected specifically regarding the hippocampal area.Clinical relevanceVisual assessment of medial temporal atrophy is used daily and worldwide in radiological examinations regarding suspected dementia. In clinical routine, many radiologists experience uncertainty, and hydrocephalus is often overlooked. This may be caused by insufficient congruency between educational sample images.Graphical

Cerebral blood flow alterations measured by ASL-MRI as a predictor of vascular dementia in small vessel ischemic disease.

Neuroimaging correlates of domain-specific cognitive deficits in amyotrophic lateral sclerosis.

AimAlzheimer’s disease (AD) is a major cause of dementia, marked by cognitive decline and behavioral and psychological symptoms of dementia (BPSD). Early differentiation between AD, mild cognitive impairment (MCI), and healthy controls (HC) is essential for improving diagnostic accuracy and guiding effective treatment strategies.MethodsThis retrospective study included 120 participants divided into AD (n = 40), MCI (n = 40), and HC (n = 40) groups. Brain MRI data were analyzed using the AccuBrain system to quantify AD Resemblance Atrophy Index (AD-RAI), Quantitative Medial Temporal Atrophy (QMTA), hippocampal volume, and white matter hyperintensities. Correlation analyses were conducted between imaging biomarkers and cognitive function scores (Mini-Mental State Examination, MMSE; Neuropsychiatric Inventory, NPI). Receiver operating characteristic (ROC) curve analysis was used to evaluated the diagnostic performance of the biomarkers.ResultsAD patients had significantly higher AD-RAI (0.91 ± 0.25) and more pronounced hippocampal atrophy (0.36 ± 0.09) compared to MCI and HC (P < 0.001). Correlation analyses showed that AD-RAI and QMTA were negatively correlated with MMSE scores (r = -0.718, P < 0.001; r = -0.463, P < 0.001), while hippocampal volume was positively correlated with MMSE (r = 0.408, P < 0.001). ROC analysis revealed that AD-RAI had an AUC of 0.777 for distinguishing AD from MCI, while QMTA had an AUC of 0.938 for distinguishing AD from HC. BPSD patients exhibited higher AD-RAI (1.09 ± 0.18) and greater hippocampal atrophy, with ROC AUC > 0.9 for distinguishing BPSD from non-BPSD patients.ConclusionThe AccuBrain MRI system demonstrated high sensitivity and diagnostic value in distinguishing AD from MCI and HC, as well as in identifying patients with BPSD. Correlation and ROC analyses support the use of these imaging biomarkers for early diagnosis and personalized treatment strategies in AD.

Brain serotonin dysregulation is associated with dementia and neuropsychiatric symptomology. However, the prognostic utility of circulating serotonin levels in detecting features of prodromal dementia including functional decline, cognitive impairment, mild behavioural impairment and brain atrophy remains unclear. In this prospective study of memory clinic subjects followed-up for ≤5 years, dementia-free subjects, classified as having no cognitive impairment or cognitive impairment, no dementia at baseline, underwent annual neuropsychological assessments including Montreal Cognitive Assessment, Global Cognition Z-scores and Clinical Dementia Rating Scale Global Scores (where a ≥ 0.5 increment from baseline denotes functional decline). Mild behavioural impairment was measured using baseline and annual Neuropsychiatric Inventory assessments, while brain atrophy was evaluated using cortical and medial temporal atrophy scores from baseline MRI scans. Baseline serum serotonin was then associated with the neuropsychological and neuroimaging measures cross-sectionally and longitudinally. Furthermore, associations of serum serotonin with cross-sectional brain atrophy scores were studied. Of the 191 elderly subjects included in the study, 63 (33.0%) had no cognitive impairment while 128 (67.0%) had cognitive impairment, no dementia. Fourteen subjects (9.0%) showed baseline mild behavioural impairment. Compared with the highest tertile, subjects within the lowest tertile of serotonin had greater Cortical Atrophy scores (adjusted odds ratio = 2.54, 95% confidence interval=1.22-5.30, P = 0.013). Serotonin levels were not significantly associated with cross-sectional neuropsychological or mild behavioural impairment scores (all P > 0.05). Of the 181 subjects with longitudinal cognitive follow-up (median duration 60.0 months), 56 (30.9%) developed functional decline, while incident mild behavioural impairment occurred in 26/119 (21.8%) subjects. Compared with the highest tertile, lower serotonin levels were associated with higher hazards of functional decline (lowest tertile: adjusted hazards ratio = 2.15, 95% confidence interval = 1.04-4.44, P = 0.039), and incident mild behavioural impairment (lowest tertile: adjusted hazards ratio = 3.82, 95% confidence interval = 1.13-12.87, P = 0.031, middle tertile: adjusted hazards ratio = 3.56, 95% confidence interval =1.05-12.15, P = 0.042). The association between the lowest serotonin tertile and functional decline was mediated via its effect on incident mild behavioural impairment (adjusted odds ratio = 3.96, 95% confidence interval = 1.15-13.61, P = 0.029). In conclusion, low circulating serotonin may be associated with cortical atrophy at baseline, as well as act as an early prognostic marker for functional decline and mild behavioural impairment in elderly, dementia-free subjects.

BackgroundVisual rating scales are routinely used in clinical radiology to assess brain atrophy on scans of patients with suspected neurodegenerative conditions. Limbic predominant age-related TDP-43 encephalopathy (LATE) has recently been described, featuring early and severe atrophy of the amygdala. However, there is currently no scoring system specifically designed to assess amygdalar atrophy on MRI.Objectivesto develop and validate a visual rating scale for amygdalar atrophy.Materials and methodsStringent criteria were developed for no, mild/moderate, and severe amygdalar atrophy based on axial and coronal volumetric T1-weighted MRI scans. Inter- and intra-rater reliabilities were estimated by three independent expert neuroradiologists in 100 randomly selected scans from the Geneva Memory Center cohort selected to be representative of the variability of medial temporal atrophy. Convergent validity was evaluated versus amygdalar volumes extracted by FreeSurfer on 1943 consecutive patients. Criterion validity versus autopsy-confirmed LATE neuropathologic changes were studied in the pathological subset of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort (N = 96).ResultsIntra- and inter-rater agreements of amygdalar visual ratings were between substantial and almost perfect (weighted Cohen’s Kappa 0.71 to 0.93). Visual ratings were strongly associated with amygdalar volumes (p ≤ 0.001 on the Kruskal–Wallis test). LATE neuropathologic changes were associated with visual ratings of amygdalar atrophy (p = 0.057 on a test for trend).ConclusionThe proposed visual amygdalar atrophy scale is a reliable and valid tool to assess amygdalar atrophy on MRI and can be a useful adjunct in routine radiological reporting.Key PointsQuestionAssessment of amygdalar atrophy is crucial for diagnosing neurodegenerative diseases, as the limbic predominant age-related TDP-43 encephalopathy, yet no validated visual rating scale exists.FindingsThe proposed amygdalar atrophy scale demonstrated high intra-rater and inter-rater reliability, strong correlation with amygdalar volumetry, and association with limbic predominant age-related TDP-43 encephalopathy (LATE).Clinical relevanceThe amygdalar atrophy scale provides a reliable practical assessment tool that enhances diagnostic accuracy for dementia-related conditions, particularly aiding in identifying limbic predominant age-related TDP-43 encephalopathy.