Individuals with Down Syndrome (DS) almost invariably develop Alzheimer's Disease (AD), but detecting early clinical changes is challenging due to comorbid intellectual disability, highlighting the importance of non-invasive biomarkers. Neuroimaging of the medial temporal lobe (MTL), a key site of tau pathology, shows promise as an early AD biomarker. Here, we aimed to characterise volumetric patterns of the MTL in DS across the AD clinical continuum, and define associations with AD cerebrospinal fluid (CSF) biomarkers. 253 adults with DS and 190 euploid controls from the Down Alzheimer Barcelona Neuroimaging Initiative underwent a 3T-MRI protocol, and a comprehensive clinical assessment. T1-weighted images were used to parse the medial temporal lobe using the Automated Segmentation of Hippocampal Subfields (ASHS) pipeline. Segmentation quality was visually inspected and W-scores were computed for MTL subregions (anterior and posterior hippocampus, entorhinal cortex (ERC), parahippocampal cortex (PHC), and Brodmann areas Br35 and Br36) to adjust volumes for total intracranial volume, age and MRI scanner. Non-parametric statistical tests were employed to assess volumes by AD clinical stage, age, and CSF biomarkers of AD. Hippocampal and Br36 volumes gradually decreased with AD clinical stage, and all subregions were decreased at the dementia stage (dDS) compared to asymptomatic (aDS) and prodromal (pDS) stages (Figure 1). Surprisingly, significantly larger ERC, PHC and Br35 volumes were found at the asymptomatic DS stage compared to controls. All subregions had decreased volumes with age, with inflexion points around 40y for the hippocampus, ERC and Br36, 45y for Br35 and 50y for PHC (Figure 2). Most subregions exhibited significant correlations with CSF Aβ 42/40 ratio, p-tau-181 and neurofilament light chain, and the strongest associations were found with anterior and posterior hippocampus (Figure 3). AD clinical stage and age are associated with progressive decreasing MTL volumes. Among all subregions, the hippocampus correlated best with CSF measures and appears particularly sensitive to detect early disease processes. These results indicate effectiveness of MTL volumes as a biomarker of early AD pathological changes in DS. Further studies are required to determine the pathological substrate of MTL atrophy and understand the increased volumes in some subregions.

Importance:A leading cause of surgically remediable, drug-resistant focal epilepsy is focal cortical dysplasia (FCD). FCD is challenging to visualize and often considered magnetic resonance imaging (MRI) negative. Existing automated methods for FCD detection are limited by high numbers of false-positive predictions, hampering their clinical utility. Objective:To evaluate the efficacy and interpretability of graph neural networks in automatically detecting FCD lesions on MRI scans. Design, Setting, and Participants:In this multicenter diagnostic study, retrospective MRI data were collated from 23 epilepsy centers worldwide between 2018 and 2022, as part of the Multicenter Epilepsy Lesion Detection (MELD) Project, and analyzed in 2023. Data from 20 centers were split equally into training and testing cohorts, with data from 3 centers withheld for site-independent testing. A graph neural network (MELD Graph) was trained to identify FCD on surface-based features. Network performance was compared with an existing algorithm. Feature analysis, saliencies, and confidence scores were used to interpret network predictions. In total, 34 surface-based MRI features and manual lesion masks were collated from participants, 703 patients with FCD-related epilepsy and 482 controls, and 57 participants were excluded during MRI quality control. Main Outcomes and Measures:Sensitivity, specificity, and positive predictive value (PPV) of automatically identified lesions. Results:In the test dataset, the MELD Graph had a sensitivity of 81.6% in histopathologically confirmed patients seizure-free 1 year after surgery and 63.7% in MRI-negative patients with FCD. The PPV of putative lesions from the 260 patients in the test dataset (125 female [48%] and 135 male [52%]; mean age, 18.0 [IQR, 11.0-29.0] years) was 67% (70% sensitivity; 60% specificity), compared with 39% (67% sensitivity; 54% specificity) using an existing baseline algorithm. In the independent test cohort (116 patients; 62 female [53%] and 54 male [47%]; mean age, 22.5 [IQR, 13.5-27.5] years), the PPV was 76% (72% sensitivity; 56% specificity), compared with 46% (77% sensitivity; 47% specificity) using the baseline algorithm. Interpretable reports characterize lesion location, size, confidence, and salient features. Conclusions and Relevance:In this study, the MELD Graph represented a state-of-the-art, openly available, and interpretable tool for FCD detection on MRI scans with significant improvements in PPV. Its clinical implementation holds promise for early diagnosis and improved management of focal epilepsy, potentially leading to better patient outcomes.

BACKGROUND AND OBJECTIVES:Cerebral hemorrhages are an exclusion criterion and potential adverse effect of antiamyloid agents. It is, therefore, critical to characterize the natural history of cerebral microbleeds in populations genetically predisposed to Alzheimer disease (AD), such as Down syndrome (DS). We aimed to assess microbleed emergence in adults with DS across the AD spectrum, defining their topography and associations with clinical variables, cognitive outcomes, and fluid and neuroimaging biomarkers. METHODS:This cross-sectional study included participants aged 18 years or older from the Down-Alzheimer Barcelona Neuroimaging Initiative and Sant Pau Initiative on Neurodegeneration with T1-weighted and susceptibility-weighted images. Participants underwent comprehensive assessments, including apolipoprotein E (APOE) genotyping; fluid and plasma determinations of beta-amyloid, tau, and neurofilament light; cognitive outcomes (Cambridge Cognitive Examination and modified Cued Recall Test); and vascular risk factors (hypertension, diabetes mellitus, and dyslipidemia). We manually segmented microbleeds and characterized their topography. Associations between microbleed severity and AD biomarkers were explored using between-group comparisons (none vs 1 vs 2+) and multivariate linear models. RESULTS:We included 276 individuals with DS and 158 healthy euploid controls (mean age = 47.8 years, 50.92% female). Individuals with DS were more likely to have microbleeds than controls (20% vs 8.9%, p < 0.001), with more severe presentation (12% with 2+ vs 1.9%). Microbleeds increased with age (12% 20-30 years vs 60% > 60 years) and AD clinical stage (12.42% asymptomatic, 27.9% prodromal, 35.09% dementia) were more common in APOEε4 carriers (26% vs 18.3% noncarriers, p = 0.008), but not associated with vascular risk factors (p > 0.05). Microbleeds were predominantly posterior (cerebellum 33.66%; occipital 14.85%; temporal 21.29%) in participants with DS. Associations with microbleed severity were found for neuroimaging and fluid AD biomarkers, but only hippocampal volumes (standardized β = -0.18 [-0.31, -0.06], p < 0.005) and CSF p-tau-181 concentrations (β = 0.26 [0.12, 0.41], p < 0.005) survived regression controlling for age and disease stage, respectively. Microbleeds had limited effect on cognitive outcomes. DISCUSSION:In participants with DS, microbleeds present with a posterior, lobar predominance, are associated with disease severity, but do not affect cognitive performance. These results suggest an interplay between AD pathology and vascular lesions, implicating microbleeds as a risk factor limiting the use of antiamyloid agents in this population.

INTRODUCTION:In Down syndrome (DS), white matter hyperintensities (WMHs) are highly prevalent, yet their topography and association with sociodemographic data and Alzheimer's disease (AD) biomarkers remain largely unexplored. METHODS:In 261 DS adults and 131 euploid controls, fluid-attenuated inversion recovery magnetic resonance imaging scans were segmented and WMHs were extracted in concentric white matter layers and lobar regions. We tested associations with AD clinical stages, sociodemographic data, cerebrospinal fluid (CSF) AD biomarkers, and gray matter (GM) volume. RESULTS:In DS, total WMHs arose at age 43 and showed stronger associations with age than in controls. WMH volume increased along the AD continuum, particularly in periventricular regions, and frontal, parietal, and occipital lobes. Associations were found with CSF biomarkers and temporo-parietal GM volumes. DISCUSSION:WMHs increase 10 years before AD symptom onset in DS and are closely linked with AD biomarkers and neurodegeneration. This suggests a direct connection to AD pathophysiology, independent of vascular risks. HIGHLIGHTS:White matter hyperintensities (WMHs) increased 10 years before Alzheimer's disease symptom onset in Down syndrome (DS). WMHs were strongly associated in DS with the neurofilament light chain biomarker. WMHs were more associated in DS with gray matter volume in parieto-temporal areas.

OBJECTIVE:Psychogenic non-epileptic seizures (PNES) mimic epileptic seizures without electroencephalographic correlation. Although classified as psychiatric disorders, their neurobiological or structural basis remains unclear. This study aimed to assess the prevalence and characteristics of MRI abnormalities in patients with PNES and those with comorbid epilepsy, compared to the general population, to enhance radiological evaluation and management. METHOD:We retrospectively identified patients with a definitive diagnosis of PNES, evaluated in the refractory epilepsy unit of our tertiary epilepsy center. Patients were classified into two groups according to their comorbidity with epilepsy (PNES and PNES+). The MRI findings were evaluated and classified by two radiologists, who reported the category of the findings, laterality, and location. The two groups were compared using the chi-square test, as well as the frequencies of findings in the general population extracted from the literature. RESULTS:Forty-six patients fulfilled the inclusion criteria. Thirty females and 16 males. MRI findings were present in 25/35 (71.4%) patients in the PNES group and 9/11 (81.8%) In the PNES + group, showing statistically significant differences in the frequency of findings with the general population (8.4-28.1%). SIGNIFICANCE:MRI anomalies are common in PNES patients and even more prevalent in complex cases referred to epilepsy units, underscoring the necessity of correlating MRI findings with clinical-electrical patterns. PLAIN LANGUAGE SUMMARY:In this article, we observed a higher frequency of cerebral magnetic resonance findings in patients with psychogenic non-epileptic seizures than in the general population. We also observed a higher frequency of this pathology among women, as well as right cerebral hemisphere affections. The exposed findings suggest a potential structural basis of this pathology. This hypothesis requires confirmation with larger studies.

BACKGROUNDCortical microinfarcts (CMI) were attributed to cerebrovascular disease and cerebral amyloid angiopathy (CAA). CAA is frequent in Down syndrome (DS) while hypertension is rare, yet no studies have assessed CMI in DS.METHODSWe included 195 adults with DS, 63 with symptomatic sporadic Alzheimer's disease (AD), and 106 controls with 3T magnetic resonance imaging. We assessed CMI prevalence in each group and CMI association with age, AD clinical continuum, vascular risk factors, vascular neuroimaging findings, amyloid/tau/neurodegeneration biomarkers, and cognition in DS.RESULTSCMI prevalence was 11.8% in DS, 4.7% in controls, and 17.5% in sporadic AD. In DS, CMI increased in prevalence with age and the AD clinical continuum, was clustered in the parietal lobes, and was associated with lacunes and cortico-subcortical infarcts, but not hemorrhagic lesions.DISCUSSIONIn DS, CMI are posteriorly distributed and related to ischemic but not hemorrhagic findings suggesting they might be associated with a specific ischemic CAA phenotype.Highlights This is the first study to assess cortical microinfarcts (assessed with 3T magnetic resonance imaging) in adults with Down syndrome (DS). We studied the prevalence of cortical microinfarcts in DS and its relationship with age, the Alzheimer's disease (AD) clinical continuum, vascular risk factors, vascular neuroimaging findings, amyloid/tau/neurodegeneration biomarkers, and cognition. The prevalence of cortical microinfarcts was 11.8% in DS and increased with age and along the AD clinical continuum. Cortical microinfarcts were clustered in the parietal lobes, and were associated with lacunes and cortico-subcortical infarcts, but not hemorrhagic lesions. In DS, cortical microinfarcts are posteriorly distributed and related to ischemic but not hemorrhagic findings suggesting they might be associated with a specific ischemic phenotype of cerebral amyloid angiopathy.

Epilepsy, a neurological disorder characterised by recurrent seizures, poses significant challenges in diagnosis, treatment, and management. Understanding the underlying causes and identifying precise anatomical locations of epileptogenic foci are critical for effective management strategies, particularly in drug-resistant patients. Neuroimaging techniques, particularly magnetic resonance (MR), play a pivotal role in the evaluation of epilepsy patients, offering insights into structural abnormalities, epileptogenic lesions, and functional alterations within the brain. Diverse clinical scenarios that warrant neuroimaging in epilepsy patients, ranging from first-onset seizures to drug-resistant epilepsy, will be presented, elucidating the considerations and recommendations for imaging modalities. The dedicated MR protocol for epilepsy patients will be discussed, justifying the rationale behind sequence selection and optimisation strategies and providing clues about how to read these magnetic resonance imaging (MRI) exams. Finally, MR findings associated with common epileptogenic lesions, such as hippocampal sclerosis, focal cortical dysplasia, and long-term epilepsy-associated tumours, will be described. This article reviews essential concepts, including definitions, classification, imaging indications, protocols, and neuroradiological findings, aiming to understand how neuroimaging contributes to diagnosing and managing epilepsy comprehensively.

BACKGROUND:Cortical mean diffusivity is a novel imaging metric sensitive to early changes in neurodegenerative syndromes. Higher cortical mean diffusivity values reflect microstructural disorganization and have been proposed as a sensitive biomarker that might antedate macroscopic cortical changes. We aimed to test the hypothesis that cortical mean diffusivity is more sensitive than cortical thickness to detect cortical changes in primary progressive aphasia (PPA).METHODS:In this multicenter, case-control study, we recruited 120 patients with PPA (52 non-fluent, 31 semantic, and 32 logopenic variants; and 5 GRN-related PPA) as well as 89 controls from three centers. The 3-Tesla MRI protocol included structural and diffusion-weighted sequences. Disease severity was assessed with the Clinical Dementia Rating scale. Cortical thickness and cortical mean diffusivity were computed using a surface-based approach.RESULTS:The comparison between each PPA variant and controls revealed cortical mean diffusivity increases and cortical thinning in overlapping regions, reflecting the canonical loci of neurodegeneration of each variant. Importantly, cortical mean diffusivity increases also expanded to other PPA-related areas and correlated with disease severity in all PPA groups. Cortical mean diffusivity was also increased in patients with very mild PPA when only minimal cortical thinning was observed and showed a good correlation with measures of disease severity.CONCLUSIONS:Cortical mean diffusivity shows promise as a sensitive biomarker for the study of the neurodegeneration-related microstructural changes in PPA.

Cortical microinfarcts (CMI) are emerging biomarkers of vascular damage associated with cognitive decline and are frequent in sporadic AD (sAD) patients. However, no study assessed CMI in Down syndrome (DS), a genetically determined form of AD. Therefore, we aimed to assess CMI’s frequency in adults with DS, sAD, and cognitively unimpaired euploid controls and its relationship with age, sex, clinical status, and APOE ε4 carriership. Cross-sectional study. We included 175 participants with 3T-MRI: 64 with DS (39 asymptomatic [aDS], 11 prodromal AD [pDS], and 14 AD-dementia [dDS]), 62 with sAD (41 prodromal AD, 21 AD dementia), and 49 controls. A neuroradiologist blind to participants’ data visually analyzed the 3T-MRI images following a validated protocol to detect CMI (Figure 1). We compared CMI’s prevalence in the different clinical groups along the AD continuum in DS and sAD, in APOE ε4 carriers vs. non-carriers, and males vs. females using Chi-square, Mann-Whitney, or Kruskal-Wallis tests when appropriate. CMI’s prevalence was 7.8% in DS (5.1% in aDS, 21.4% in pDS, and 0% in dDS [p = 0.085]), 17.7% in sAD (22.0% in prodromal AD and 9.5% in AD dementia [p = 0.389]), and 10.2% in controls (p = 0.207). CMI frequency increased with age in DS, sAD, and controls (Table 1). Regarding sex, CMI’s frequency was 10% in men and 5.9% in women with DS (p = 0.884), and 27.3% in men and 12.5% in women with sAD (p = 0.267). In controls, CMIs’ frequency was 10% in men and 10.3% in women (p = 1.000). Regarding APOEε4 carriership, CMI’s prevalence was 21.4% in APOEε4 carriers and 9.1% in non-carriers in sAD (p = 0.428), 8.7% in carriers and 6.0% in non-carriers in DS (p = 1.000), and 8.3% in carriers and 8.6% in non-carriers controls (p = 1.000) (Table 2). CMI’s prevalence increased with age, but was not different in DS, sporadic AD, and controls. Also, sex and APOEε4 carriership did not impact the prevalence of CMI in the three study groups.

Due to the triplication of the APP gene on chromosome 21, virtually all individuals with Down’s syndrome (DS) present AD neuropathological hallmarks by the age of 40, and have a lifetime risk of developing dementia >90%. However, whether DS follows a stereotypical pattern of AD atrophy has not been investigated. Here, we aimed at defining the sequential grey matter (GM) volume loss across the whole AD continuum in adults with DS. Cross-sectional design. 248 adults with DS (n = 145 asymptomatic [preclinical], n = 93 prodromal/demented AD) and 181 euploid cognitively unimpaired (CU) individuals from the Down Alzheimer Barcelona Neuroimaging Initiative underwent a 3T-MRI protocol (Table.1). T1-weighted images were preprocessed using CAT12. GM volumes adjusted for demographics (age, sex) and nuisance variables (TIV, MRI scanner) were computed for each cortical region of the Hammer Atlas and for each DS participant, using the CU group as a reference. Adjusted volumes (W-scores) were binarized using a threshold of -2.33 (corresponding to a regional volume <99th percentiles of the CU group) to examine the brain regions most frequently atrophied in DS compared to CU. Conditional probability analyses were additionally performed in DS to assess if a brain region was more likely to present with atrophy than another. Adults with DS most frequently showed atrophy in the medial temporal lobe, anterior cingulate, and temporo-parietal regions. This pattern remains essentially similar when using a dynamic range of thresholds (Fig1.A) and across clinical AD stages (Fig1.B), even though the proportion of individuals showing atrophy increased with disease progression (Fig1.C). Interestingly, the anterior cingulate was the most frequently atrophied region in asymptomatic but not prodromal/demented DS. Conditional probability analyses revealed that the hippocampus, amygdala, and anterior cingulate have a significantly higher probability of showing GM loss before any other regions. A second cluster of tempo-parietal regions appears more likely to show atrophy than most other regions. In DS, GM atrophy appears to follow a stereotypical pattern that strongly resembles the one of sporadic AD. Brain developmental specificities (e.g., anterior cingulate) are coupled with AD-like atrophy early in the disease and become less predominant with AD progression.

Atrophy of basal forebrain (BF) cholinergic neurons is an early event in Alzheimer’s disease (AD) and is associated with cognitive impairment. Down syndrome (DS) is now recognized as a genetically determined form of AD. Therefore, people with DS represent a priority population to study biomarkers of AD pathology and neurodegeneration. Degeneration of BF neurons occurs both in sporadic AD and in DS brains with advanced AD pathology. However, the dynamics of BF atrophy and its changes with age and AT(N) biomarkers have not been studied in DS. We included 246 adults with DS (mean age 43.2 ±11.0 years; 43% female). Volumes of antero-medial and posterior areas of the BF (amBF and pBF, respectively) were extracted from T1-weighted 3T MR images using voxel-based morphometry in SPM12 in combination with a stereotactic atlas of BF functional subdivisions (Figure 1). Differences in amBF and pBF volume in each AD clinical stage (Asymptomatic, Prodromal and Demented) were assessed with Kruskall-Wallis and pairwise Wilcoxon tests. The relationship of BF volumes with age and AT(N) biomarkers in the cerebrospinal fluid (CSF) (amyloid-β 42/40 ratio [aβ ratio], phosphorylated Tau 181 [pTau], total Tau [tTau] and neurofilament light [NFL]) was assessed in a subset of subjects (n = 161 [aβ ratio, pTau and tTau] and n = 95 [NFL]) with locally estimated scatterplot smoothing (LOESS) and linear regression in R, respectively. Volumes of amBF and pBF decreased significantly with age (Figure 2), with a steeper decline during the fifth decade of life. BF volumes also declined with AD clinical stage (Figure 3), and had significant correlations with CSF aβ ratio (p<0.001 r2 = 0.22), pTau (p<0.001 r2 = 0.20), tTau (p<0.001 r2 = 0.20) and NFL (p<0.001 r2 = 0.33) (Figure 4). In DS, BF volume decreases with age, AT(N) biomarkers and along the cognitive stages of the AD continuum.

Down’s syndrome (DS) is a genetically determined form of Alzheimer’s disease (AD). Typically not complicated by systemic vascular risk factors, the DS population represents a unique opportunity to unravel the complex relationship between AD and cerebrovascular disease. Here, we aim at studying the evolution over time of white matter hyperintensities (WMHs), a key hallmark of cerebrovascular disease frequently found in AD, and to assess their topographical progression and associations with AD biomarkers in adults with DS. This longitudinal study included 43 DS adults (age = 39.8±10.4y; females = 41.9%; n = 37 asymptomatic AD, n = 6 symptomatic AD) and 81 euploid controls (age = 53.7±6.2y; females = 67.3%) from the Down-Alzheimer Barcelona Neuroimaging Initiative, with at least 2 MRI visits with T1 and FLAIR acquisitions (time delay = 3.4±1.6y). WMHs were segmented using the Lesion Prediction Algorithm implemented in the Lesion Segmentation Toolbox (SPM12). WMH volumes were extracted in 36 regions of interest and used to compute total and regional annual volume changes. Non-parametric statistical tests were performed to assess the effect of disease severity on WMH volume changes over time and define associations between longitudinal WMHs and baseline demographic and genetic data, and fluid biomarkers. Total annual WMH volume change increased in symptomatic DS compared to both asymptomatic DS and controls (Figure 1A). Regionally, WMH load increased in regions showing WMH at baseline in all groups (Figure 2). These changes were greater and more distributed, involving layers more distant from the ventricles (especially in occipito-parietal regions) in symptomatic DS. Age, but not sex, intellectual disability, or APOEε4 status, was associated with longitudinal WMH in DS (Figure 1B-F): the annual WMH volume changes in DS differed from controls at age ∼45y. Finally, WMH volume changes were negatively related to CSF-Aβ42/40 and positively related to plasma and CSF ptau-181 and neurofilament light (Figure 3). Pathological increases in WMH volume start ∼10 years before the mean age at onset for AD (53.8y) in DS and relate to underlying AD pathology and neurodegeneration. Regional analyses suggest that WMH volume changes increase with disease progression and progressively involve deeper white matter areas. Together, these results support that WMHs are tightly related to AD pathogenesis.

BACKGROUND:Basal forebrain (BF) degeneration occurs in Down syndrome (DS)-associated Alzheimer's disease (AD). However, the dynamics of BF atrophy with age and disease progression, its impact on cognition, and its relationship with AD biomarkers have not been studied in DS. METHODS:We included 234 adults with DS (150 asymptomatic, 38 prodromal AD, and 46 AD dementia) and 147 euploid controls. BF volumes were extracted from T-weighted magnetic resonance images using a stereotactic atlas in SPM12. We assessed BF volume changes with age and along the clinical AD continuum and their relationship to cognitive performance, cerebrospinal fluid (CSF) and plasma amyloid/tau/neurodegeneration biomarkers, and hippocampal volume. RESULTS:In DS, BF volumes decreased with age and along the clinical AD continuum and significantly correlated with amyloid, tau, and neurofilament light chain changes in CSF and plasma, hippocampal volume, and cognitive performance. DISCUSSION:BF atrophy is a potentially valuable neuroimaging biomarker of AD-related cholinergic neurodegeneration in DS.

With the development of amyloid-modifying therapeutic agents that can lead to cerebral microhaemorrhages, it is critical to meticulously characterise the natural history of cerebral microbleeds (MBs) in populations genetically predisposed to develop Alzheimer’s disease (AD), such as Down syndrome (DS). We aimed to investigate MB prevalence in a large cohort of adults with DS and define associations with demographic, genetic, fluid and imaging biomarkers of AD, and cognitive performance. Cross-sectional design. Adults with DS and euploid controls from the Down Alzheimer Barcelona Neuroimaging Initiative underwent a 3T-MRI protocol, including susceptibility-weighted imaging (SWI) acquisition. Manual tracing of MBs was performed by two independent raters using ITK-SNAP. Participants were classified according to MB status (MB-/MB+) and severity (0, 1, 2+ MBs). Non-parametric statistical tests were used to assess the effect of MBs on demographic, clinical, genetic, CSF and neuroimaging AD biomarkers, and cognitive tests. We included 247 participants with DS along the AD continuum, and 167 euploid controls (Table 1). The proportion of MB+ was higher in DS participants than controls, and progressively increased with AD clinical stages and age in the DS group (Fig. 1). By contrast, MB status did not differ by APOEε4 status, intellectual disability, or sex. In DS, the MB+ group had increased white matter hyperintensity volume and decreased hippocampal volumes compared to MB-. DS MB+ also had lower CSF Aβ 42/40 ratio, higher CSF t-tau and p-tau-181 concentrations, and tended toward worse cognitive performance. Most effects gradually evolved with MB severity, although significant differences were mainly between MB- vs MB 2+ (Fig. 2). Finally, sensitivity analyses showed that most results became non-significant when comparing DS MB+ to a 1:1 DS MB- group matched for age, sex, intellectual disability and/or AD diagnosis. MB presence and severity are increased in adults with DS, and worsen with clinical progression and AD pathology. Yet, matched group analyses suggest that MB have limited impact on cognition and neurodegeneration. These results provide better characterisation of the presence and effect of MB in a population with an ultra-high risk of developing AD who could benefit from new disease modifying drugs.

Abstract The study of sex differences in Alzheimer’s disease is increasingly recognized as a key priority in research and clinical development. People with Down syndrome represent the largest population with a genetic link to Alzheimer’s disease (>90% in the 7th decade). Yet, sex differences in Alzheimer’s disease manifestations have not been fully investigated in these individuals, who are key candidates for preventive clinical trials. In this double-centre, cross-sectional study of 628 adults with Down syndrome [46% female, 44.4 (34.6; 50.7) years], we compared Alzheimer’s disease prevalence, as well as cognitive outcomes and AT(N) biomarkers across age and sex. Participants were recruited from a population-based health plan in Barcelona, Spain, and from a convenience sample recruited via services for people with intellectual disabilities in England and Scotland. They underwent assessment with the Cambridge Cognitive Examination for Older Adults with Down Syndrome, modified cued recall test and determinations of brain amyloidosis (CSF amyloid-β 42 / 40 and amyloid-PET), tau pathology (CSF and plasma phosphorylated-tau181) and neurodegeneration biomarkers (CSF and plasma neurofilament light, total-tau, fluorodeoxyglucose-PET and MRI). We used within-group locally estimated scatterplot smoothing models to compare the trajectory of biomarker changes with age in females versus males, as well as by apolipoprotein ɛ4 carriership. Our work revealed similar prevalence, age at diagnosis and Cambridge Cognitive Examination for Older Adults with Down Syndrome scores by sex, but males showed lower modified cued recall test scores from age 45 compared with females. AT(N) biomarkers were comparable in males and females. When considering apolipoprotein ɛ4, female ɛ4 carriers showed a 3-year earlier age at diagnosis compared with female non-carriers (50.5 versus 53.2 years, P = 0.01). This difference was not seen in males (52.2 versus 52.5 years, P = 0.76). Our exploratory analyses considering sex, apolipoprotein ɛ4 and biomarkers showed that female ɛ4 carriers tended to exhibit lower CSF amyloid-β 42/amyloid-β 40 ratios and lower hippocampal volume compared with females without this allele, in line with the clinical difference. This work showed that biological sex did not influence clinical and biomarker profiles of Alzheimer’s disease in adults with Down syndrome. Consideration of apolipoprotein ɛ4 haplotype, particularly in females, may be important for clinical research and clinical trials that consider this population. Accounting for, reporting and publishing sex-stratified data, even when no sex differences are found, is central to helping advance precision medicine.

The spectrum of distribution of white matter hyperintensities (WMH) may reflect different functional, histopathological, and etiological features. We examined the relationships between cerebrovascular risk factors (CVRF) and different patterns of WMH in MRI using a qualitative visual scale in ischemic stroke (IS) patients. We assembled clinical data and imaging findings from patients of two independent cohorts with recent IS. MRI scans were evaluated using a modified visual scale from Fazekas, Wahlund, and Van Swieten. WMH distributions were analyzed separately in periventricular (PV-WMH) and deep (D-WMH) white matter, basal ganglia (BG-WMH), and brainstem (B-WMH). Presence of confluence of PV-WMH and D-WMH and anterior-versus-posterior WMH predominance were also evaluated. Statistical analysis was performed with SPSS software. We included 618 patients, with a mean age of 72 years (standard deviation [SD] 11 years). The most frequent WMH pattern was D-WMH (73%). In a multivariable analysis, hypertension was associated with PV-WMH (odds ratio [OR] 1.79, 95% confidence interval [CI] 1.29–2.50, p = 0.001) and BG-WMH (OR 2.13, 95% CI 1.19–3.83, p = 0.012). Diabetes mellitus was significantly related to PV-WMH (OR 1.69, 95% CI 1.24–2.30, p = 0.001), D-WMH (OR 1.46, 95% CI 1.07–1.49, p = 0.017), and confluence patterns of D-WMH and PV-WMH (OR 1.62, 95% CI 1.07–2.47, p = 0.024). Hyperlipidemia was found to be independently related to brainstem distribution (OR 1.70, 95% CI 1.08–2.69, p = 0.022). Different CVRF profiles were significantly related to specific WMH spatial distribution patterns in a large IS cohort. • An observational study of WMH in a large IS cohort was assessed by a modified visual evaluation. • Different CVRF profiles were significantly related to specific WMH spatial distribution patterns. • Distinct WMH anatomical patterns could be related to different pathophysiological mechanisms.

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy.

Objective Intraoperative imaging is a chief asset in neurosurgical oncology, it improves the extent of resection and postoperative outcomes. Imaging devices have evolved considerably, in particular ultrasound (iUS) and magnetic resonance (iMR). Although iUS is regarded as a more economically convenient and yet effective asset, no formal comparison between the efficiency of iUS and iMR in neurosurgical oncology has been performed. Methods A cost-effectiveness analysis comparing two single-center prospectively collected surgical cohorts, classified according to the intraoperative imaging used. iMR (2013-2016) and iUS (2021-2022) groups comprised low- and high-grade gliomas, with a maximal safe resection intention. Units of health gain were gross total resection and equal or increased Karnofsky performance status. Surgical and health costs were considered for analysis. The incremental cost-effectiveness ratio (ICER) was calculated for the two intervention alternatives. The cost-utility graphic and the evolution of surgical duration with the gained experience were also analyzed. Results 50 patients followed an iMR-assisted operation, while 17 underwent an iUS-guided surgery. Gross total resection was achieved in 70% with iMR and in 60% with iUS. Median postoperative Karnofsky was similar in both group (KPS 90). Health costs were € 3,220 higher with iMR, and so were surgical-related costs (€ 1,976 higher). The ICER was € 322 per complete resection obtained with iMR, and € 644 per KPS gained or maintained with iMR. When only surgical-related costs were analyzed, ICER was € 198 per complete resection with iMR and € 395 per KPS gained or maintained. Conclusion This is an unprecedented but preliminary cost-effectiveness analysis of the two most common intraoperative imaging devices in neurosurgical oncology. iMR, although being costlier and time-consuming, seems cost-effective in terms of complete resection rates and postoperative performance status. However, the differences between both techniques are small. Possibly, iMR and iUS are complementary aids during the resection: iUS real-time images assist while advancing towards the tumor limits, informing about the distance to relevant landmarks and correcting neuronavigation inaccuracy due to brain shift. Yet, at the end of resection, it is the iMR that reliably corroborates whether residual tumor remains.