NeuroImage: Reports

Background: Hippocampal sclerosis (HS) is a common cause of drug-resistant focal epilepsy (DRFE) and amenable to neurosurgical treatment. Detection relies on MRI but can be challenging. 7 Tesla (T) ultra-high field MRI and automated MRI post-processing tools have independently been shown to improve radiological diagnosis of HS. However, combining these approaches remains underexplored. This study evaluated whether AID-HS, a tool for HS detection developed using 3T MRI, generalises to 7T MRI data. Methods: We collated a dataset of paired 3T and 7T T1-weighted MRI from four epilepsy centres, including 23 patients with HS, 39 healthy controls, and 23 individuals with focal cortical dysplasia as disease controls. Histopathology served as the gold standard for defining HS where available (n=7), otherwise radiological findings (n=16). AID-HS was applied to images acquired at both field strengths, and sensitivity and specificity for detection and lateralisation of HS were compared. Additionally, agreement of hippocampal features across 3T and 7T was evaluated. Results: We found no evidence of a difference in performance of AID-HS between 3T and 7T. Sensitivity for detection of unilateral HS was 63% (12/19) at 3T and 68% (13/19) at 7T (McNemar's exact test p=1.0). Specificity in controls was 97% (60/62) at 3T and 100% (62/62) at 7T (p=0.5). Bilateral HS was correctly flagged in 3 of 4 cases using feature-based criteria, with high specificity in controls. Quantitative hippocampal features showed moderate to good agreement across field strengths (ICC 0.70 to 0.98), with small differences observed for volume and thickness estimates. Conclusion: AID-HS provides robust detection and lateralisation of HS across multiple 7T MRI centres, highlighting its potential to enhance lesion detection. Future work is needed to investigate whether models trained on 7T data can leverage the improved image quality for further gains in HS detection performance.

Background: The Centiloid (CL) scale standardizes global amyloid PET quantification and is widely used to define amyloid positivity. As a global summary measure, however, CL may not fully reflect the regional distribution of amyloid deposition, which can carry additional prognostic information about the rate of cognitive decline. Objective: To develop and externally validate a fixed, regional amyloid PET composite score that complements CL for predicting cognitive decline in Alzheimer's disease. Methods: The Regional Amyloid PET Score (RAPS) was derived from 82 FreeSurfer regions using machine learning with bootstrap stability selection to predict the rate of change in CDR-Sum of Boxes (CDR-SB) in 433 amyloid-positive ADNI [18F]florbetapir participants. The fixed nine-region weights were applied without retraining in a cross-tracer ADNI [18F]florbetaben subset (N = 71; largely overlapping the discovery participants) and two external validation cohorts, NACC SCAN (N = 1531; four tracers) and OASIS-3 (N = 428). Results: RAPS comprised nine regions. In ADNI, RAPS correlated more strongly with CDR-SB slope than CL and showed higher discrimination of rapid decliners (AUC 0.813 vs 0.713). Performance was directionally consistent across validation cohorts; in NACC SCAN, RAPS and CL independently predicted clinical progression. Cross-cohort meta-analysis of the three independent cohorts supported incremental discrimination beyond CL (pooled {Delta}AUC +0.066; I2 = 0%). Conclusions: RAPS, a fixed regional amyloid PET-derived score, may complement CL for prognostic stratification in Alzheimer's disease research.

Abstract: Objective: Post-traumatic epilepsy (PTE) is a common sequela of traumatic brain injury (TBI). Research indicates that individuals with PTE tend to experience greater cognitive difficulties compared to those with TBI alone. However, it is plausible that a distinct cognitive profile exists that distinguishes between TBI cases with and without PTE. We aimed to identify longitudinal changes in cognitive measures among TBI patients to better assess the changes associated with developing PTE. Setting: Outpatient. Participants: Prospective subjects who had suffered TBI within 6 months post-injury (TBI-6M, n=32), retrospective subjects with pre-existing PTE diagnoses (PTE, n=20), and healthy control subjects (HC, n=41). Design: We examined cognitive performance for TBI patients within 6 months post-injury, then again within 12 months (TBI-12M, n=26), and within 18-months (TBI-18M, n=25), and compared this with cognitive performance among HC and PTE. Main Measures: Cognitive tests administered yielded 15 test components for analysis. We utilized linear mixed effects modeling to examine cohort-level differences cognitive function. Results: 11/15 tests showed a significant performance deficit in the PTE subjects compared to HC. TBI-6M was not significantly different from the PTE subjects; with time, 9/15 tests showed some degree of recovery in TBI subjects. Tests for information processing speed/working memory and executive function showed strong recovery (TBI-6M vs. TBI-18M, SDMT written: p<0.0001, SDMT oral and COWAT: p<0.001). Tests for visual attention/working memory also showed a smaller but significant recovery (TBI-18M vs. PTE, p<0.05). By contrast, tests for verbal memory [HVLT-R Delayed Recall] showed chronic impairment in TBI (TBI-18M vs HC, p<0.0001). TBI subjects generally trend towards recovery in cognitive performance post-TBI. Conclusions: Information processing speed/working memory are strong indicators for TBI recovery, while auditory learning/memory shows chronic impairment. The stagnation of recovery in cognitive domains typically characterized by robust recovery may correlate with an elevated risk of developing PTE.

Background: Bipolar disorder is associated with persistent social, cognitive, and functional impairment during euthymia, yet the neural mechanisms underlying these deficits remain unclear. Alterations to self-referential processing are a candidate mechanism, but existing electrophysiological studies rely on emotionally valenced paradigms that potentially confound self-processing with emotional biases. Methods: We analysed electroencephalography from 28 patients with bipolar disorder (type I or II) and 28 age- and sex-matched healthy controls during an emotionally neutral colour judgment task with self-related (preference) and non-self-related (similarity) conditions. Late positive potentials, temporal generalisation decoding, and frequency band decoding (theta, alpha, beta) were used to characterise the temporal dynamics and oscillatory correlates of self versus non-self processing. Results: Controls showed higher overall event-related potential amplitudes and greater self versus non-self differentiation than patients (condition by group interaction, 337 to 946 ms). Broadband temporal generalisation decoding revealed extensive cross-temporal generalisation of the self versus non-self representation in controls, spanning most of the trial, but no significant generalisation in patients. Frequency analyses showed that alpha and beta carried self versus non-self information in both groups, with broader extent in controls, and that anterior theta carried this information in patients but not controls. Exploratory correlations linked decoding measures to rumination and anxiety but not to manic symptoms. Conclusions: The neural representation distinguishing self-referential from externally guided processing was both smaller in amplitude and less temporally sustained in bipolar disorder. Reduced persistence is not detectable by conventional amplitude analyses, and may bear on the self-related and social cognitive difficulties reported in this population.

Background: Storage symptoms after stroke-isolated urgency, urgency with frequency, and isolated frequency are common but traditionally attributed to a single overactive bladder mechanism via suprapontine disinhibition. However, clinical heterogeneity in symptom presentation suggests distinct underlying mechanisms. We aimed to characterize the neural substrates of three storage symptom subtypes after stroke using comprehensive lesion-symptom mapping. Methods: We prospectively evaluated 1,498 consecutive subacute stroke patients admitted for inpatient rehabilitation (1,105 men, 73.8%; median age 61 years). Storage symptoms were classified into three subtypes: isolated urgency (n=109), urgency with frequency (n=32), and isolated frequency (n=19). Multivariable logistic regression models with Bonferroni correction identified independent predictors across demographic, clinical, white matter hyperintensity (WMH), brain atrophy, and lesion location variables. Results: The three subtypes demonstrated largely distinct sets of independent predictors. The left genu of the corpus callosum (aOR=20.06, 95% CI 7.78-51.74, P<0.001) and the inferior frontal gyrus (aOR=3.48, 95% CI 1.81-6.67, P<0.001) were independently associated with isolated urgency and survived Bonferroni correction, together with a right IFG-insula synergistic effect (OR=21.46, 95% CI 10.49-43.88, P<0.001). Urgency with frequency was associated with a broad fronto-cingulate network-the IFG (aOR=11.45, 95% CI 3.10-42.33, P<0.001, surviving Bonferroni correction) and the ACC (aOR=11.53, 95% CI 2.40-55.49, P=0.002) with diffuse right-hemisphere dominance, older age and brain atrophy. Isolated frequency was associated with anterior corona radiata involvement (aOR=5.46, 95% CI 1.92-15.54, P=0.002) and male sex (aOR=10.62, 95% CI 1.36-82.98, P=0.024), though none reached the strict Bonferroni threshold. Conclusions: These findings identify three mechanistically distinct post-stroke storage symptom subtypes with separable neural substrates, lateralization profiles, and clinical determinants. The triple dissociation across subtypes supports a discrete pathway model over the traditional unitary OAB framework, providing a neuroanatomically grounded basis for subtype-stratified treatment Keywords: storage symptoms; subacute stroke; hemispheric lateralization; structural synergy; lesion-syndrome mapping

Background: Aneurysmal subarachnoid haemorrhage (aSAH) is frequently complicated by delayed cerebral ischaemia (DCI), for which current therapies incompletely target the underlying multifactorial pathophysiology. Transauricular vagus nerve stimulation (taVNS) modulates inflammatory, vasoactive and autonomic pathways and may attenuate secondary brain injury after aSAH. Methods: We conducted a prospective, single-centre, single-blind, randomised, sham-controlled pilot trial in adults within 5 days of aneurysm securing for non-traumatic aSAH. Participants were allocated 1:1 to active taVNS (left tragus) or sham (left earlobe) using a portable device delivered for 45 minutes twice daily over 5 days. Primary outcomes were safety (taVNS-related serious adverse events), acceptability, and compliance; secondary outcomes included inflammatory biomarkers, DCI, in-hospital complications, and functional outcomes to 1 month. Results: Thirty patients were randomised (16 taVNS, 14 sham), with numerically more severe aSAH at baseline in the taVNS arm. No taVNS-related serious adverse events occurred; side effects were generally mild and transient, and over 80% of planned sessions were completed. TaVNS produced greater reductions in serum tumour necrosis factor- and trends towards reductions in interleukin-1{beta} and interleukin-10, with numerically fewer DCI events (6.6% vs 35.7%) and neurological impairments (16.7% vs 53.8%), although functional outcomes were not statistically different at 1 month. Conclusions: Early taVNS after aSAH is safe, acceptable, and feasible in the neurocritical care setting and shows biologically plausible signals warranting evaluation in larger multi-centre trials.

Major depressive disorder (MDD) has been associated with accelerated structural brain aging, yet whether this reflects a pre-existing neurobiological vulnerability, a dynamic acute state effect, or an accumulating biological residual remains unresolved. Across two longitudinal cohorts (N=3220), including a unique sample of 78 initially healthy individuals who transitioned into their first depressive episode during the study course, we systematically tested all three hypotheses. Patients with diagnosed MDD showed elevated MRI-derived brain age relative to healthy controls (1.4 and 2.5 years across cohorts). For the vulnerability hypothesis, individuals scanned prior to their first episode showed no baseline elevation, despite already demonstrating subclinical elevations in self-reported symptom severity, indicating that advanced brain age does not precede illness onset. For the state hypothesis, we found no acceleration of brain aging following the first depressive episode, and longitudinal brain age trajectories were independent of acute clinical symptom severity. Finally, neither episode duration nor recurrence scaled with brain age. Accelerated brain aging in depression is therefore neither an antecedent vulnerability nor an acute state marker of the first episode, but rather a stable biological feature of a long term illness course.

Despite extensive knowledge of the progressive sequence of cognitive and functional deficits in Alzheimer's Disease (AD), the impact of neurodegeneration on the conscious experience of patients remains largely unexplored. Understanding how the content of consciousness, particularly perceptual awareness, changes with the progression of AD is crucial to enable meaningful person-centred care. This is especially important in severe AD when impairments in language and other cognitive domains mean people are unable to report their experiences. We investigated whether electrophysiological (EEG) and fMRI signatures of perceptual awareness described in healthy older people are present in people with mild-moderate and severe AD using two "no-report" paradigms. Firstly, a visual masking paradigm examined visual awareness negativity (VAN) and late positive (LP) electrophysiological responses and activation in visual cortex and fronto-parietal regions that are characteristically associated with conscious perception of faces; and second, a complex audio-visual (movie) task examined activation in fronto-parietal networks previously associated with perceptual awareness. In healthy older controls we found cortical responses characteristic of awareness in both EEG and fMRI modalities, with VAN and LP markers and widespread occipital, fusiform face area and fronto-parietal activation. In people with mild-moderate AD, there were significant reductions in VAN and LP markers and reduced fronto-parietal activation. In participants with severe AD, who were behaviourally minimally responsive, there was only limited evidence of presence of frontoparietal markers of perceptual awareness, however this may reflect attentional and task insensitivity in people with advanced dementia. These results demonstrate that the brain mechanisms associated with perceptual awareness become increasingly impaired with progression of AD. Specifically, involvement of frontoparietal networks is reduced in AD, which may reflect reduced higher-level awareness. This suggests AD should be considered a disorder of consciousness and should motivate further investigation into the dimensions of awareness affected by the disorder with implications for treatment and management of people with dementia.

Clinical brain MRIs from pediatric health systems represent a viable resource for modeling early neurodevelopmental trajectories and studying neurodevelopmental risk in real-world populations. However, a limitation to date has been the performance of existing segmentation tools for measuring various brain phenotypes in clinical scans. In particular, many tools underperform in infant scans due to morphological and physical changes such as rapid myelination. Here, we introduce ClinSeg: a robust segmentation approach tailored to early-life clinical MRIs with variable orientation, resolution, and contrast. We leverage existing registration and synthetic data generation tools to construct a training corpus for a 3d U-Net spanning anatomical and contrast diversity, including scans with morphological abnormalities from a pediatric hospital. Validated against manual segmentations, ClinSeg outperforms existing models in infancy while matching them in childhood and adolescence. Finally, ClinSeg enables the construction of reference brain growth trajectories in 11,699 individuals from 0-21 years of age, leading to the detection of more nuanced age-related findings in clinical groups.

Background: Unruptured intracranial aneurysms (UIAs) are increasingly identified incidentally, and management balances rupture risk against treatment risk. UIA diagnosis has been linked to psychological distress, but psychotropic medication initiation after UIA discovery has not been compared across the full UIA management spectrum. Methods: We conducted a retrospective cohort study using IBM MarketScan claims (CCAE, MDCD, and MDCR; 2009-2023) among adults with a UIA diagnosis, continuous enrollment for 365 days before and after the index date, and no SAH/rupture on or before the index date. We compared the prevalence of 6 mental-health diagnoses before versus after UIA discovery and used adjusted logistic regression to examine psychotropic medication initiation within 365 days by management strategy (untreated observation as the reference). Results: Among 54,945 patients (untreated, 78.5%; endovascular, 11.3%; clipping, 3.0%; other/uncertain, 7.2%), prevalence of every mental-health diagnosis was higher after UIA discovery, most for depression (+4.6 percentage points) and anxiety (+4.5 points). Medication initiation was most common for benzodiazepines (8.7%). Endovascular treatment was associated with higher adjusted odds of benzodiazepine (aOR, 1.21), SSRI (aOR, 1.20), and sedative-hypnotic (aOR, 1.25) initiation.Surgical clipping demonstrated the broadest association, with higher odds across 5 of 6 classes, including benzodiazepines (aOR, 1.71) and sedative-hypnotics (aOR, 1.86). Benzodiazepines had the lowest 1-year persistence (10.5%) despite being the most commonly initiated class. Findings were consistent across sensitivity analyses, with the exception of the increase in panic disorder, which was no longer observed after applying a 30-day post-index lag. Conclusions: Mental-health diagnoses and psychotropic medication initiation increased after UIA discovery, and medication initiation was most pronounced among patients treated with surgical clipping. These findings support psychological assessment as part of aneurysm management regardless of strategy.

Background: The Boston Criteria v2.0 represent the gold standard for diagnosing Cerebral Amyloid Angiopathy (CAA), but their application is currently precluded in mixed small vessel disease (SVD), where deep and lobar hemorrhages coexist. The aims of this study are: (i) to determine which cerebrospinal fluid (CSF) biomarker (A{beta}42, A{beta}40, A{beta}42/40 ratio) is the best candidate to support the CAA diagnosis; (ii) to define a data-driven cut-off, and (iii) to explore if a biomarker-integrated classification significantly improves the phenotypical concordance with the suspected predominant SVD (CAA vs. arteriosclerosis). Methods: We analyzed data from a retrospective multicenter cohort of patients with suspected CAA, defined as probable CAA (Boston criteria v2.0) but allowing deep hemorrhagic lesions, and with available CSF biomarkers. We visually quantified MRI-visible SVD markers (e.g., cerebral microbleeds [CMB], cortical superficial siderosis [cSS], lacunes) and their association with MRI-visible SVD features. We employed a Gaussian Mixture Model (GMM) to identify a data-driven threshold for amyloid positivity (A+). Then, we compared the prevalence of MRI-visible manifestations of SVD between subgroups applying different frameworks, namely the current MRI-based classification (probable CAA vs. mixed SVD) and a CSF biomarker-integrated classification (A+ vs. A-). Results: We enrolled 121 patients (age: 72 [66-77] years; 60% probable CAA, 40% mixed SVD with suspected CAA). The CSF A{beta}42/40 ratio showed a bimodal distribution and consistent associations with all CAA-specific radiological features. The CSF biomarker-integrated reclassification, particularly using the GMM cut-off, significantly improved the distinction between subgroups regarding CAA- and arteriosclerosis-related MRI features (e.g., cSS presence: probable CAA vs. mixed SVD: aOR=2.84 [95%CI 1.27-6.39], p=0.011; A+ vs. A-: aOR=12.68 [95%CI 4.31-37.32], p<0.001; deep lacunes presence: probable CAA vs. mixed SVD: aOR=0.20 [95%CI 0.08-0.50], p<0.001; A+ vs. A-: aOR=0.04 [95%CI 0.01-0.11], p<0.001). Notably, patients classified as A+ never demonstrated more than four deep CMBs. Discussion: A CSF biomarker-integrated classification may improve the classification of CAA compared with the current MRI-based framework. These findings are cohort-specific and would benefit from further validation, especially with a neuropathological reference. Still, these results support a future transition toward an integrated biological-radiological framework, which may refine in vivo CAA diagnosis, particularly in mixed SVD.

Background: The primary neuroanatomical site of Huntington-s disease (HD) pathology resides in the striatum and its atrophy identifies important disease progression from HD-ISS Stage 0 to Stage 1. Immune-associated proteins may capture variation in HD that is incompletely represented by markers of neuroaxonal injury. Objectives: To determine whether cerebrospinal-fluid myeloperoxidase contributes information about striatal volume loss beyond genetic disease burden and neurofilament light. Methods: Cross-sectional data from 88 persons with HD were analyzed. Cerebrospinal-fluid myeloperoxidase and neurofilament light were measured with a nucleic acid-linked immunosandwich assay. Normalized putamen volume was derived from structural magnetic resonance imaging. Linear regression adjusted for genetic disease burden and sex. Results: Higher neurofilament light was associated with smaller normalized putamen volume (standardized {beta} = -0.322, (P=.0066)). Higher myeloperoxidase was associated with larger normalized putamen volume after adjustment for genetic disease burden, sex, and neurofilament light (standardized {beta} = 0.183, (P=.0386)). Adding myeloperoxidase increased explained variance in striatal loss. Conclusions: Cerebrospinal fluid myeloperoxidase contributed modest incremental information about striatal volume in this cross-sectional sample. Independent longitudinal studies are needed to determine its biological source, temporal behavior, and potential biomarker value. Findings advance efforts to characterize multicomponent biological markers of HD.

Background: Substance use is common among individuals with depression. Transcranial magnetic stimulation (TMS) is an effective treatment for depression, but current clinical guidelines have discouraged TMS treatment for individuals with depression and co-occurring substance use given concerns for limited efficacy. However, limited data exists on whether substance use affects response to TMS. Methods: Using electronic health record data from patients who received a standard course of TMS for major depressive disorder at an academic medical center, we investigated associations between substance use frequency and response to TMS, defined as change in Patient Health Questionnaire-9 (PHQ-9) scores. Substance use frequency was extracted for alcohol, cannabis, nicotine, stimulants, benzodiazepines, opioids, inhalants, psychedelics, and other drugs. We performed ANCOVA and multiple regression analyses to predict change in PHQ-9 score based on substance use frequency, controlling for pre-TMS PHQ-9 score, age, sex, and number of TMS sessions received. Results: We extracted data from 219 TMS courses. Alcohol was the substance used most commonly (34.2%), followed by prescription benzodiazepines (28.3%), and prescription stimulants (21.0%). Across all substance categories, substance use was not associated with change in PHQ-9 score (all p > 0.05, Cohens d=0.00 to 0.30). In multiple regression models to compare individual levels of substance use frequency (e.g., daily use vs. no use), level of substance use was not associated with change in PHQ-9 score (all p > 0.05). The range of plausible effects of substance use frequency on PHQ-9 change was generally below the minimal clinically important difference for PHQ-9, suggesting substance use was unlikely to have a meaningful clinical effect on antidepressant response to TMS. Conclusions: Low to moderate substance use does not have a clinically significant effect on antidepressant response to TMS. Low-level substance use should not exclude individuals with depression from receiving TMS.

Background Understanding the mechanisms underlying brain aging and age-related pathological changes is essential for advancing brain health research. Our group previously developed a mechanistic mathematical model of healthy brain, Chamberland et al. (2024) that integrates key biological processes involved in normal aging, from which Alzheimer's disease (AD) related changes may emerge naturally. Objectives To characterize and validate this brain model by evaluating its sensitivity, calibrating its parameters, and assessing generalizability in independent populations. Methods The model represents the evolution of key biological processes associated with brain aging, including amyloid beta (A{beta}), tau pathologies, neuroinflammation, and neuronal death. After identifying the 30 most influential parameters, we calibrated the model using cognitively normal (CN) participants from the AD Neuroimaging Initiative (ADNI) database (n = 211) by minimizing a loss function composed of three outcomes (AB) plaques, tau tangles, and neuronal density). The calibrated model was then applied to the UK Biobank cohort (n = 35,899) of normal controls (aged 44-82 years). The effects of sex and APOE were evaluated using stratified simulations. Results Parameter calibration significantly reduced the prediction errors for A{beta} and tau. Neuronal density predictions showed strong agreement in the UK Biobank cohort. The variance decomposition identified APOE status as a major contributor to variability in A{beta}. Conclusion Our validated brain health model links mechanistic pathways with population data and reproduces neuronal density patterns in an independent cohort. These findings support its use as a framework for studying brain aging and investigating how Alzheimer's disease related pathological changes may emerge with aging.

Background: On-call clinicians frequently report the anecdotal impression of 'theme shifts' during which specific acute neurological diagnoses appear to cluster. Whether such clustering reflects a statistically true and reproducible phenomenon has not been systematically investigated; the present paper examines seasonality and temporal clustering within six different acute neurological conditions. Methods: In this retrospective, single-center cohort study, we identified all patients admitted to a tertiary neurological department between July 2016 and June 2026 with acute unilateral vestibulopathy, cerebral artery dissection, generalized epileptic seizures, primary intracerebral hemorrhage, peripheral facial nerve palsy, or transient global amnesia (TGA) (n = 2,140). Monthly and seasonal distributions were assessed using chi-squared goodness-of-fit and cosinor analysis. Short-term temporal clustering was tested by Monte Carlo permutation across time windows from 24 hours to 90 days, and endogenous cluster dynamics were characterized using Hawkes self-exciting point process modeling. Results: Admissions for generalized epileptic seizures showed a statistically significant deviation from a uniform monthly distribution with a winter distribution (p<0.001 and q = 0.002), and a significant temporal clustering across time windows from 72 hours to 90 days (all q < 0.05). Peripheral facial nerve palsy presented significant clustering at the 90-day window (q = 0.029) and TGA at 60-day time window (q = 0.041) without seasonality; the diagnostic groups of acute unilateral vestibulopathy, cerebral artery dissection and primary intracerebral hemorrhage showed neither seasonality nor clustering after correction for multiple comparison. No diagnostic group showed clustering within a 24-hour window, statistically significant self-excitation in Hawkes process modelling, or a significant linear trend in monthly case counts over the study period. Conclusion: The anecdotal impression of diagnostic 'theme shifts' among on-call neurologists appears to have a measurable basis, although clustering is confined to specific conditions and rather on a time scale of weeks to months. Generalized epileptic seizures were the only diagnostic group that uniquely combined seasonality with temporal clustering, suggesting a shared trigger, while facial palsy and TGA showed episodic, yet non-seasonal clustering.

Importance: Patients are increasingly learning Alzheimers disease (AD) genetic and biomarker results through electronic health portals. Evaluation of alternative scalable delivery models for return of AD risk information is needed to best support patient understanding and psychological well-being. Objective: To determine whether a patient-centered digital platform is comparable to clinician-mediated telehealth sessions for returning APOE and plasma pTau-217 results on outcomes of knowledge and psychological well-being. Design: The Evaluation of Self-Mediated Alternatives for Risk Testing Education and Return of Results (eSMARTER) study was a noninferiority trial of a patient-centered digital platform compared to clinician-mediated disclosure of APOE genotype and optional pTau-217 disclosure. Setting: Decentralized, fully remote trial enrolled participants in the contiguous United States (U.S.) between October 2024 and February 2025, with follow-up completed in November 2025. Participants: Eligible participants were aged 60-80 and had previously undergone APOE genotyping (without disclosure) via the GeneMatch program, passed psychological screening, had internet access, and were English-speaking. Interventions: Participants were randomized, 2:1, to the eSMARTER digital platform or clinician-mediated disclosure of APOE genotype. Following the 6-month post-APOE assessment, participants were offered optional pTau-217 disclosure via the same randomized modality. Main Outcomes and Measures: Primary outcomes at 1-7 days following APOE disclosure included changes in anxiety, disease-specific distress, and AD-related knowledge within a priori non-inferiority margins. Results: 674 persons (mean [SD] age 68 [4.7] years; 451 [67%] female; mean [SD] telephone MoCA=19 [2]) were eligible and provided demographic information. 651 participants were randomized to clinician-mediated (n=216) or digital disclosure (n=435) and completed APOE disclosure (66 [10%] APOE4 homozygotes, 377 [58%] heterozygotes, 208 [32%] non-carriers). 604 participants completed the study; 500 completed optional pTau-217 disclosure. Baseline characteristics were balanced across groups. At 1-7 days following APOE disclosure, scores on AD-related knowledge, PROMIS Anxiety, and disease-specific distress measures met non-inferiority. Conclusions and Relevance: Disclosure of APOE genotype by the eSMARTER digital platform is non-inferior to clinician-mediated telehealth disclosure. No significant between group differences were found following disclosure of pTau-217 results. Together, these results suggest that this digital platform may provide an evidence-based scalable approach for returning AD genetic and biomarker results.

Purpose: The primary objective of the Stanford Knee Osteoarthritis PET/MRI Evaluation (SKOPE) study is to develop and evaluate a multimodal, dynamic [18F]NaF PET-MRI framework for characterizing whole-joint physiology and its relationship to osteoarthritis (OA) risk, pain, and disease progression. Specifically, we aim to integrate dynamic PET with quantitative and anatomical MRI, to characterize structural, compositional, and metabolic features across the knee and surrounding musculoskeletal system, evaluate acute tissue responses to exercise, and identify imaging biomarkers associated with OA risk, pain, and disease progression. Methods: The SKOPE study includes multimodal PET-MRI of the knee and surrounding musculoskeletal tissues, with imaging of the knee, tibia, ankle, thigh, hip, pelvis, and lumbosacral spine. Dynamic [18F]NaF PET is combined with conventional anatomical MRI and quantitative MRI techniques, including quantitative double-echo steady-state (qDESS) T2 mapping of cartilage, Dixon fat-fraction imaging, ultrashort echo time (UTE) T2* mapping of short-T2 tissues, UTE imaging of tibial bone, and zero echo time (ZTE) imaging for bone morphology and pseudo-CT generation. Additional MRI sequences characterize muscle composition, bone and joint anatomy, intervertebral discs, and regional vascular anatomy. Selected scans are acquired before and after a standardized exercise protocol to assess the acute physiological response of the joint. Automated segmentation is used to generate subject-specific masks of muscles, bones, vertebrae, and intervertebral discs. A subset of the MRI protocol is repeated at 1- and 2-year follow-up to assess longitudinal changes. Expected Impact: By combining dynamic bone metabolic imaging with quantitative measures of cartilage, menisci, muscle, bone, fat, vascular structures, and the spine and hip, the SKOPE protocol provides a whole-joint and multijoint framework for studying the structural, metabolic, and physiological processes associated with OA and pain. Exercise and longitudinal imaging further enable assessment of acute tissue responses and changes over time, supporting the development of quantitative imaging biomarkers for OA risk, pain, and disease progression.

Objective: Published P300-speller fusion schemes fix prior trust regardless of trial reliability; we tested whether a reliability estimate improves on it. Methods: We reanalyzed 3,373 archived P300-speller selections from 47 people with ALS (BigP3BCI). A fair, matched-search-space comparison, tuning both a fixed weight and an adaptive policy out-of-fold, was evaluated across 22 evaluable language-model priors up to 46.7B parameters. Two representative priors, GPT-2 and a classical 5-gram, additionally received detailed naive and mechanistic analyses. Results: No prior's 95% CI favored adaptive fusion under the fair comparison, despite unexploited oracle headroom at every scale. Under GPT-2, the naive comparison was significantly worse for adaptive fusion; both anchors converged to a degenerate or near-degenerate fair-comparison solution. For the representative anchors, three further controllers failed to convert that headroom into benefit; the fixed-fused posterior's output probability outperformed the best controller for flagging errors (2.8- to 3.8-fold enrichment). Conclusion: A tuned fixed weight is a difficult-to-beat default across the tested scale range; reliability estimation gave no deployable adaptive advantage. Significance: Adaptive weighting should be validated against a fairly tuned baseline across model families and scales; in this dataset, the fused output's confidence identified high-risk selections better than the tested purpose-built ranker.

Objective: Cognitive impairment is a common comorbidity among people with epilepsy (PWE) and is associated with disability and reduced quality of life. We characterized the burden of cognitive impairment and identified factors associated with cognitive performance in a large, population-based cohort of PWE living in Northern Peru, a region highly endemic for Taenia solium where neurocysticercosis (NCC) is a common cause of acquired epilepsy. Methods: PWE enrolled in a population-based cohort in Northern Peru between 2007 and 2020 completed the Mini-Mental State Examination (MMSE) at enrollment. Cognitive impairment was defined as an MMSE score <24. Demographic and clinical data, including epilepsy characteristics and NCC status, were collected. Negative binomial regression was used to identify factors associated with the number of MMSE errors. Results: Among 764 participants, the mean MMSE score was 26.4 (SD 4.2), and 16.4% met criteria for cognitive impairment. Memory and attention were the most affected domains. In multivariable analysis, older age and lower educational attainment were independently associated with poorer cognitive performance. Conclusion: In this large, community-based cohort from Northern Peru, approximately 1 in 6 PWE had abnormal global cognition on the MMSE, with memory and attention most affected. These findings underscore the importance of incorporating cognitive evaluation and management into comprehensive epilepsy care, particularly in resource-limited settings where cognitive morbidity may be underrecognized. Given the potential for cognitive difficulties to compound disability and adversely affect quality of life, identifying and addressing cognitive morbidity may be especially important in populations already facing substantial barriers to epilepsy care.

Background The time trend in long-term survival after a stroke is to some extent unknow due to (relatively) short follow up periods in available data. The objective of this study is to identify and quantify differences in long-term stroke survival in Sweden between men and women and patients with different attained educational levels, comparing two time-periods, 2000-2009 and 2010-2022. Methods This study employs total population Swedish register data pertaining to hospital-based care and mortality due to stroke for the period 2000-2022 in order to estimate survival (all-cause mortality) after ischaemic and haemorrhagic stroke, respectively, and pertaining to attained educational level. Kaplan-Meier survival functions are estimated stratifying for time-period, sex and educational level. Cox regressions are employed to quantify mortality hazard ratios between the strata. Age is taken into account in complementary analyses (supplement). Results Taking only time-period (2000-2009 vs 2010-2022) into account resulted in significantly higher survival in the second period for ischaemic stroke patients (HR: 0.84; 95% CI: 0.83-0.84), while no significant difference could be detected for haemorrhagic stroke. Stratifying for sex showed that men gained more than women in terms of reduced mortality hazard rate between the periods. Further stratifying by educational level and estimating survival separately for men and women showed that, for both men and women, patients with the lowest education were relatively worse off (compared to patients with higher education) in the second period. Further analyses, taking age into account, reversed the relative hazard ratio between men and women, but corroborated the result that low education is associated with poorer outcome than high education. Conclusions The results suggest that there are considerable differences in expected long-term survival after stroke between the sexes, but that this may be due to differences in age between the sexes at the time of stroke. Moreover, lower educational level is significantly associated with lower long-time survival.