Impact of stroke imaging selection modality on endovascular thrombectomy outcomes in the early and extended time windows: A meta-analysis.

BACKGROUND: The effect of imaging selection modality on endovascular thrombectomy (EVT) clinical outcomes in patients with acute ischemic stroke due to large vessel occlusion (AIS-LVO) remains unclear. This study aims to compare post-EVT outcomes in patients with AIS-LVO who underwent basic imaging (computed tomography with or without computed tomography angiography) and advanced imaging (computed tomography perfusion or magnetic resonance imaging) in early and late time windows. METHOD: A systematic literature search was conducted on PubMed, Cochrane Library, and Embase databases from inception until June 10, 2023. Studies investigating the relationship between the imaging selection modality and post-EVT outcomes in patients with AIS-LVO were retrieved. A random-effects model was used to pool the effect estimates of successful reperfusion, symptomatic intracranial hemorrhage (sICH), functional independence, and mortality. The meta-analysis was performed using Review Manager software v.4.3, and the outcomes were assessed using odds ratios (ORs) and 95% confidence intervals (CIs). RESULT: A total of 13 non-randomized observational studies, comprising 19,694 patients, were included in this meta-analysis. In the early time windows, AIS-LVO patients receiving advanced imaging demonstrated a higher likelihood of functional independence (OR, 1.25, 95% CI, 1.08-1.46) and a lower risk of mortality (OR,.73 95% CI,.61-.86) compared to those receiving basic imaging. In the extended time windows, AIS-LVO patients undergoing advanced imaging had a lower mortality rate (OR,.79, 95% CI,.68-.92). Regardless of the time of onset, there were no significant differences between the two groups in terms of sICH or successful reperfusion. CONCLUSION: Advanced imaging combined with EVT may achieve better clinical outcomes in patients with AIS-LVO. Further high-quality studies are needed to validate these findings.

Clinical pattern, neuroimaging findings and outcome of Acute Disseminated Encephalomyelitis in children: A retrospective study.

Objective: To determine the clinical spectrum, neuroimaging findings, and outcome of Acute Disseminated Encephalomyelitis (ADEM) in children. Method: We conducted a descriptive cross sectional study of all children aged 6 months to 18 years, diagnosed with ADEM at Aga Khan University Hospital, Karachi from January 2018 till December 2022. Results: This retrospective study enrolled 30 cases of ADEM, with a mean age of 6.43 ± 4.079, including 13 males and 17 females. The average hospital stay was 7.29 ± 4.379 days. The most common clinical features were fever, headache, and altered consciousness, while motor deficit was observed in 15 (53.5%) patients. Abnormal cerebrospinal fluid was found in 14 (46.6%) patients. Brain MRI identified bilateral and multifocal lesions in 22 (78.6%) patients, with brainstem lesions detected in 7 (25%) patients. Treatment included IV methylprednisolone (22; 73%), IVIG (9; 30%), or both (6; 20%). Clinical improvement was observed in 25 (89.3%) patients, with residual weakness present in eight (26%) patients at discharge. There was one reported death. Long-term complications included motor deficits, seizures, poor scholastic performance, and behavioral issues. Conclusion: The clinical presentation of ADEM is variable, but the most common symptoms are fever, headache, and altered consciousness. Despite generally favorable outcome, long-term monitoring revealed that patients may experience motor deficits, seizures, cognitive impairment, and academic difficulties.

Advances in Neuroimaging Biomarkers and Scoring.

MRI of the brain is a critical tool in the diagnosis, evaluation, and management of neonatal encephalopathy (NE). More than simply a diagnostic and prognostic tool, MRI informs the biology, nature, and timing of the disease process resulting in NE, of which the largest single etiology is hypoxic-ischemic encephalopathy (HIE). Historically, 2 major patterns of injury were seen in HIE: a basal ganglia/thalamus predominant pattern and a watershed pattern of injury. The advent of therapeutic hypothermia for NE/HIE, alongside improvements in the application of imaging technology in newborn infants, has resulted in progressively more advanced MRI scoring systems.

Characterization of white matter hyperintensities in Down syndrome.

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.

Evaluating the role of 7-Tesla magnetic resonance imaging in neurosurgery: Trends in literature since clinical approval.

BACKGROUND: After approval for clinical use in 2017, early investigations of ultra-high-field abdominal magnetic resonance imaging (MRI) have demonstrated its feasibility as well as diagnostic capabilities in neuroimaging. However, there are no to few systematic reviews covering the entirety of its neurosurgical applications as well as the trends in the literature with regard to the aforementioned application. AIM: To assess the impact of 7-Tesla MRI (7T MRI) on neurosurgery, focusing on its applications in diagnosis, treatment planning, and postoperative assessment, and to systematically analyze and identify patterns and trends in the existing literature related to the utilization of 7T MRI in neurosurgical contexts. METHODS: A systematic search of PubMed was conducted for studies published between January 1, 2017, and December 31, 2023, using MeSH terms related to 7T MRI and neurosurgery. The inclusion criteria were: Studies involving patients of all ages, meta-analyses, systematic reviews, and original research. The exclusion criteria were: Pre-prints, studies with insufficient data (e.g., case reports and letters), non-English publications, and studies involving animal subjects. Data synthesis involved standardized extraction forms, and a narrative synthesis was performed. RESULTS: We identified 219 records from PubMed within our defined period, with no duplicates or exclusions before screening. After screening, 125 articles were excluded for not meeting inclusion criteria, leaving 94 reports. Of these, 2 were irrelevant to neurosurgery and 7 were animal studies, resulting in 85 studies included in our systematic review. Data were categorized by neurosurgical procedures and diseases treated using 7T MRI. We also analyzed publications by country and the number of 7T MRI facilities per country was also presented. Experimental studies were classified into comparison and non-comparison studies based on whether 7T MRI was compared to lower field strengths. CONCLUSION: 7T MRI holds great potential in improving the characterization and understanding of various neurological and psychiatric conditions that may be neurosurgically treated. These include epilepsy, pituitary adenoma, Parkinson's disease, cerebrovascular diseases, trigeminal neuralgia, traumatic head injury, multiple sclerosis, glioma, and psychiatric disorders. Superiority of 7T MRI over lower field strengths was demonstrated in terms of image quality, lesion detection, and tissue characterization. Findings suggest the need for accelerated global distribution of 7T magnetic resonance systems and increased training for radiologists to ensure safe and effective integration into routine clinical practice.

Establishment and evaluation of a clinical prediction model for cognitive impairment in patients with cerebral small vessel disease.

BACKGROUND: There are currently no effective prediction methods for evaluating the occurrence of cognitive impairment in patients with cerebral small vessel disease (CSVD). AIMS: To investigate the risk factors for cognitive dysfunction in patients with CSVD and to construct a risk prediction model. METHODS: A retrospective study was conducted on 227 patients with CSVD. All patients were assessed by brain magnetic resonance imaging (MRI), and the Montreal Cognitive Assessment (MoCA) was used to assess cognitive status. In addition, the patient's medical records were also recorded. The clinical data were divided into a normal cognitive function group and a cognitive impairment group. A MoCA score < 26 (an additional 1 point for education < 12 years) is defined as cognitive dysfunction. RESULTS: A total of 227 patients (mean age 66.7 ± 6.99 years) with CSVD were included in this study, of whom 68.7% were male and 100 patients (44.1%) developed cognitive impairment. Age (OR = 1.070; 95% CI = 1.015 ~ 1.128, p < 0.05), hypertension (OR = 2.863; 95% CI = 1.438 ~ 5.699, p < 0.05), homocysteine(HCY) (OR = 1.065; 95% CI = 1.005 ~ 1.127, p < 0.05), lacunar infarct score(Lac_score) (OR = 2.732; 95% CI = 1.094 ~ 6.825, P < 0.05), and CSVD total burden (CSVD_score) (OR = 3.823; 95% CI = 1.496 ~ 9.768, P < 0.05) were found to be independent risk factors for cognitive decline in the present study. The above 5 variables were used to construct a nomogram, and the model was internally validated by using bootstrapping with a C-index of 0.839. The external model validation C-index was 0.867. CONCLUSIONS: The nomogram model based on brain MR images and clinical data helps in individualizing the probability of cognitive impairment progression in patients with CSVD.

Empathy-related abnormalities among women with premenstrual dysphoric disorder: clinical and functional magnetic resonance imaging study.

BACKGROUND: Empathy refers to the cognitive and emotional reactions of an individual to the experiences of another. Women with premenstrual dysphoric disorder (PMDD) report severe social difficulties during the luteal phase of their menstrual cycle. AIMS: This clinical and functional magnetic resonance imaging study aimed to explore affective and cognitive empathy in women with PMDD, during the highly symptomatic luteal phase. METHOD: Overall, 32 women with PMDD and 20 healthy controls participated in the study. The neuroimaging data were collected using a highly empathy-engaging movie. First, we characterised the synchrony of neural responses within PMDD and healthy groups, using the inter-individual correlation approach. Next, using network cohesion analysis, we compared connectivity within and between brain networks associated with affective and cognitive empathy between groups, and assessed the association of these network patterns with empathic measures. RESULTS: A consistent, although complex, picture of empathy abnormalities was found. Patients with PMDD showed decreased neural synchrony in parietal and frontal key nodes of cognitive empathy processing (theory-of-mind network), but higher neural synchrony in the anterior insula and anterior cingulate cortex, a part of the salience network, implicated in affective empathy. Positive correlations between cognitive perspective-taking scores and neural synchrony were found within the theory-of-mind network. Interestingly, during highly emotional moments, the PMDD group showed increased functional connectivity within this network. CONCLUSIONS: Similar to major depression, individuals with PMDD show enhanced affective empathy and reduced cognitive empathy. These findings echo clinical observations reported when women with PMDD have a dysregulated emotional response to negative stimuli.

Multivariate pattern analysis of medical imaging-based Alzheimer's disease.

Alzheimer's disease (AD) is a devastating brain disorder that steadily worsens over time. It is marked by a relentless decline in memory and cognitive abilities. As the disease progresses, it leads to a significant loss of mental function. Early detection of AD is essential to starting treatments that can mitigate the progression of this disease and enhance patients' quality of life. This study aims to observe AD's brain functional connectivity pattern to extract essential patterns through multivariate pattern analysis (MVPA) and analyze activity patterns across multiple brain voxels. The optimized feature extraction techniques are used to obtain the important features for performing the training on the models using several hybrid machine learning classifiers for performing binary classification and multi-class classification. The proposed approach using hybrid machine learning classification has been applied to two public datasets named the Open Access Series of Imaging Studies (OASIS) and the AD Neuroimaging Initiative (ADNI). The results are evaluated using performance metrics, and comparisons have been made to differentiate between different stages of AD using visualization tools.

Paradoxical Brain Herniation: An Unexpected Diagnosis.

Paradoxical herniation is a dreadful neurosurgical complication often underdiagnosed, which typically becomes evident over the course of weeks to months after the initial intervention. Here we present a unique case with manifestations in the post-operative period. A patient initially referred to neurosurgery for a meningioma underwent an uneventful surgical excision, followed by the transient placement of a lumbar drain for 48 hours. On the first post-operative day, the patient exhibited progressively altered neurological status, with corresponding imaging revealing a transfalcine herniation, necessitating emergent decompressive craniectomy. Despite the medical and surgical interventions, there were continuous signs of neurological and imaging worsening, with increase in herniation, which led to the diagnosis suspicion of a paradoxical brain herniation. Consequently, a rapid reversal of neurological deficits was observed after applying maneuvers to augment the intracranial pressure, followed by cranioplasty. This case illustrates the utmost importance of clinical suspicion for the uncommon complications of neurointerventions.

A new ontology for numerical cognition: Integrating evolutionary, embodied, and data informatics approaches.

Numerical cognition is a field that investigates the sociocultural, developmental, cognitive, and biological aspects of mathematical abilities. Recent findings in cognitive neuroscience suggest that cognitive skills are facilitated by distributed, transient, and dynamic networks in the brain, rather than isolated functional modules. Further, research on the bodily and evolutionary bases of cognition reveals that our cognitive skills harness capacities originally evolved for action and that cognition is best understood in conjunction with perceptuomotor capacities. Despite these insights, neural models of numerical cognition struggle to capture the relation between mathematical skills and perceptuomotor systems. One front to addressing this issue is to identify building block sensorimotor processes (BBPs) in the brain that support numerical skills and develop a new ontology connecting the sensorimotor system with mathematical cognition. BBPs here are identified as sensorimotor functions, associated with distributed networks in the brain, and are consistently identified as supporting different cognitive abilities. BBPs can be identified with new approaches to neuroimaging; by examining an array of sensorimotor and cognitive tasks in experimental designs, employing data-driven informatics approaches to identify sensorimotor networks supporting cognitive processes, and interpreting the results considering the evolutionary and bodily foundations of mathematical abilities. New empirical insights on the BBPs can eventually lead to a revamped embodied cognitive ontology in numerical cognition. Among other mathematical skills, numerical magnitude processing and its sensorimotor origins are discussed to substantiate the arguments presented. Additionally, an fMRI study design is provided to illustrate the application of the arguments presented in empirical research.

Effects of chronic naltrexone treatment on relapse-related behavior and neural responses to fentanyl in awake nonhuman primates.

Naltrexone, an opioid antagonist that blocks the reinforcing properties of opioid agonists, is often prescribed to preclude relapse to opioid use disorder (OUD) following detoxification. However, few laboratory studies have directly investigated the ability of naltrexone to alter relapse-inducing effects of opioid agonists, including their priming strength in reinstatement studies and their impact in brain regions known to be involved in drug-induced reinforcement in MRI studies. Here we directly address this issue by investigating the effects of continuous exposure to naltrexone on 1) fentanyl-induced reinstatement of drug-seeking behavior, 2) fentanyl-induced patterns of blood oxygenation level dependent (BOLD) activation in the nucleus accumbens (NAcc), and 3) fentanyl-induced changes in NAcc functional connectivity (FC) in awake non-human primates that are engaged in ongoing opioid self-administration studies. We found that naltrexone antagonizes the priming strength of fentanyl as shown by a rightward shift in its reinstatement dose-effect curve and that naltrexone surmountably antagonizes the BOLD response induced by fentanyl. However, while naltrexone also countered fentanyl's effects on NAcc FC, the effects were not surmounted by a higher dose of fentanyl. Together, these data suggest that, in contrast to naltrexone's modulation of fentanyl's effects on behavior and BOLD responses, their interactive effects on FC between multiple brain regions do not reflect their receptor-mediated activity. Additionally, we demonstrated opposing effects in the absence and presence of naltrexone on NAcc FC at baseline (i.e., in the absence of any fentanyl prime) suggesting that naltrexone alters FC at baseline, even though naltrexone appears behaviorally silent in the absence of an agonist prime. Together these data provide additional insight into ways in which naltrexone interacts with opioid agonists, both behaviorally and in the brain. Further understanding the effects of opioid agonists on patterns of FC could help elucidate our understanding of the neural processes that contribute to the initiation of and relapse to opioid-seeking behavior in OUD.

Leveraging distributed brain signal at rest to predict internalizing symptoms in youth.

BACKGROUND: The prevalence of internalizing psychopathology rises precipitously from early to mid-adolescence, yet the underlying neural phenotypes that give rise to depression and anxiety during this developmental period remain unclear. METHODS: Youth from the Adolescent Brain and Cognitive DevelopmentSM Study (ages 9-10 years at baseline) with a resting-state fMRI scan and mental health data were eligible for inclusion. Internalizing subscale scores from the Brief Problem Monitor - Youth Form were combined across two years of follow-up to generate a cumulative measure of internalizing symptoms. The total sample (n = 6521) was split into a large discovery dataset and a smaller validation dataset. Brain-behavior associations of resting-state functional connectivity (RSFC) with internalizing symptoms were estimated in the discovery dataset. The weighted contributions of each functional connection were aggregated using multivariate statistics to generate a polyneuro risk score (PNRS). The predictive power of the PNRS was evaluated in the validation dataset. RESULTS: The PNRS explained 10.73% of the observed variance in internalizing symptom scores in the validation dataset. Model performance peaked when the top 2% functional connections identified in the discovery dataset (ranked by absolute ß-weight) were retained. The RSFC networks that were implicated most prominently were the default mode, dorsal attention, and cingulo-parietal networks. These findings were significant (p < 1*10-6) as accounted for by permutation testing (n = 7000). CONCLUSIONS: These results suggest that the neural phenotype associated with internalizing symptoms during adolescence is functionally distributed. The PNRS approach is a novel method for capturing relationships between RSFC and behavior.

Non-voluntary BCI explantation: assessing possible neurorights violations in light of contrasting mental ontologies.

In research involving patients with implantable brain-computer interfaces (BCIs), there is a regulatory gap concerning post-trial responsibilities and duties of sponsors and investigators towards implanted patients. In this article, we analyse the case of patient R, who underwent non-voluntary explantation of an implanted BCI, causing a discontinuation in her sense of agency and self. To clarify the post-trial duties and responsibilities involved in this case, we first define the ontological status of the BCI using both externalist (EXT) and internalist (INT) theories of cognition. We then give particular focus to the theories of extended and embedded cognition, hence considering the BCI either as a constitutive component of the patient's mind or as a causal supporter of her brain-based cognitive capacities. We argue that patient R can legitimately be considered both as an embedded and extended cognitive agent. Then, we analyse whether the non-voluntary explantation violated patient R's (neuro)rights to cognitive liberty, mental integrity, psychological continuity and mental privacy. We analyse whether and how different mental ontologies may imply morally relevant differences in interpreting these prima facie neurorights violations and the correlational duties of sponsors and investigators. We conclude that both mental ontologies support the identification of emerging neurorights of the patient and give rise to post-trial obligations of sponsors and investigators to provide for continuous technical maintenance of implanted BCIs that play a significant role in patients' agency and sense of self. However, we suggest that externalist mental ontologies better capture patient R's self-conception and support the identification of a more granular form of mental harm and associated neurorights violation, thus eliciting stricter post-trial obligations.

Does an improvement in cord-level intraoperative neuromonitoring data lead to a reduced risk for postoperative neurologic deficit in spine deformity surgery?

PURPOSE: To determine if an improvement in cord-level intraoperative neuromonitoring (IONM) data following data loss results in a reduced risk for new postoperative motor deficit in pediatric and adult spinal deformity surgery. METHODS: A consecutive series of 1106 patients underwent spine surgery from 2015 to 2023 by a single surgeon. Cord alerts were defined by Somatosensory-Evoked Potentials (SSEP; warning criteria: 10% increase in latency or > 50% loss in amplitude) and Motor-Evoked Potentials (MEP; warning criteria: 75% loss in amplitude without return to acceptable limits after stimulation up 100 V above baseline level). Timing of IONM loss and recovery, interventions, and baseline/postoperative day 1 (POD1) lower extremity motor scores were analyzed. RESULTS: IONM Cord loss was noted in 4.8% (53/11,06) of patients and 34% (18/53) with cord alerts had a POD1 deficit compared to preoperative motor exam. MEP and SSEP loss attributed to 98.1% (52/53) and 39.6% (21/53) of cord alerts, respectively. Abnormal descending neurogenic-evoked potential (DNEP) was seen in 85.7% (12/14) and detected 91.7% (11/12) with POD1 deficit. Abnormal wake-up test (WUT) was seen in 38.5% (5/13) and detected 100% (5/5) with POD1 deficit. Most cord alerts occurred during a three-column osteotomy (N = 23/53, 43%); decompression (N = 12), compression (N = 7), exposure (N = 4), and rod placement (N = 14). Interventions were performed in all 53 patients with cord loss and included removing rods/less correction (N = 11), increasing mean arterial pressure alone (N = 10), and further decompression with three-column osteotomy (N = 9). After intervention, IONM data improved in 45(84.9%) patients (Full improvement: N = 28; Partial improvement: 17). For those with full and partial IONM improvement, the POD1 deficit was 10.7% (3/28) and 41.2% (7/17), respectively. For those without any IONM improvement (15.1%, 8/53), 100% (8/8) had a POD1 deficit, P < 0.001. CONCLUSION: A full or partial improvement in IONM data loss after intraoperative intervention was significantly associated with a lower risk for POD1 deficit with an absolute risk reduction of 89.3% and 58.8%, respectively. All patients without IONM improvement had a POD1 neurologic deficit.

Brain network localization of gray matter atrophy, neurocognitive and social cognitive dysfunction in schizophrenia.

BACKGROUND: Numerous studies have established the presence of gray matter atrophy and brain activation abnormalities during neurocognitive and social cognitive tasks in schizophrenia. Despite a growing consensus that diseases localize better to distributed brain networks than individual anatomical regions, there is still a dearth of literature examining brain network localization of gray matter atrophy, neurocognitive and social cognitive dysfunction in schizophrenia. METHODS: To address this gap, we initially identified brain locations of structural and functional abnormalities in schizophrenia from 301 published neuroimaging studies with 8712 schizophrenia individuals and 9275 healthy controls. By applying novel functional connectivity network mapping to large-scale resting-state functional magnetic resonance imaging datasets, we mapped these affected brain locations to 3 brain abnormality networks of schizophrenia. RESULTS: The gray matter atrophy network of schizophrenia comprised a broadly distributed set of brain areas predominantly implicating the ventral attention, somatomotor, and default networks. The neurocognitive dysfunction network was also composed of widespread brain areas primarily involving the frontoparietal and default networks. By contrast, the social cognitive dysfunction network consisted of circumscribed brain regions mainly implicating the default, subcortical, and visual networks. CONCLUSIONS: Our findings suggest shared and unique brain network substrates of gray matter atrophy, neurocognitive and social cognitive dysfunction in schizophrenia, which may not only refine the understanding of disease neuropathology from a network perspective, but also potentially contribute to more targeted and effective treatments for impairments in different cognitive domains in schizophrenia.

Measuring and reducing the carbon footprint of fMRI preprocessing in fMRIPrep.

Computationally expensive data processing in neuroimaging research places demands on energy consumption-and the resulting carbon emissions contribute to the climate crisis. We measured the carbon footprint of the functional magnetic resonance imaging (fMRI) preprocessing tool fMRIPrep, testing the effect of varying parameters on estimated carbon emissions and preprocessing performance. Performance was quantified using (a) statistical individual-level task activation in regions of interest and (b) mean smoothness of preprocessed data. Eight variants of fMRIPrep were run with 257 participants who had completed an fMRI stop signal task (the same data also used in the original validation of fMRIPrep). Some variants led to substantial reductions in carbon emissions without sacrificing data quality: for instance, disabling FreeSurfer surface reconstruction reduced carbon emissions by 48%. We provide six recommendations for minimising emissions without compromising performance. By varying parameters and computational resources, neuroimagers can substantially reduce the carbon footprint of their preprocessing. This is one aspect of our research carbon footprint over which neuroimagers have control and agency to act upon.

Impact of repetitive negative thinking on subjective cognitive decline: insights into cognition and brain structure.

Introduction: Individuals with subjective cognitive decline (SCD) express concern about self-perceived cognitive decline despite no objective impairment and are at higher risk of developing Alzheimer's disease. Despite documented links between SCD and repetitive negative thinking (RNT), the specific impact of RNT on brain integrity and cognition in exacerbating the SCD condition remains unclear. We aimed to investigate the influence of RNT on global cognition and brain integrity, and their interrelationships among healthy middle-aged and older adults experiencing SCD. Methods: Out of 616 individuals with neuroimaging and neuropsychological data available, 89 (mean age = 56.18 years; 68.54% females) met SCD criteria. Eighty-nine non-SCD individuals matched by age, sex, and education were also selected and represented the control group (mean age = 56.09 years; 68.54% females). Global cognition was measured using the preclinical Alzheimer's cognitive composite (PACC5), which includes dementia screening, episodic memory, processing speed, and category fluency tests. RNT was calculated through three questionnaires assessing intrusive thoughts, persistent worry, and rumination. We generated cortical thickness (CTh) maps and quantified the volume of white matter lesions (WML) in the whole brain, as grey and white matter integrity measures, respectively. Results: SCD individuals exhibited higher RNT scores, and thinner right temporal cortex compared to controls. No differences were observed in PACC5 and WML burden between groups. Only the SCD group demonstrated positive associations in the CTh-PACC5, CTh-RNT, and WML-RNT relationships. Discussion: In this cross-sectional study, RNT was exclusively associated with brain integrity in SCD. Even though our findings align with the broader importance of investigating treatable psychological factors in SCD, further research may reveal a modulatory effect of RNT on the relationship between cognition and brain integrity in SCD.