Neuroimaging Research Articles

Being Born Early Can Affect the Way We Control Our Emotions

Every year, 13 million babies are born before the usual 9 months of pregnancy. To understand what happens to these babies’ brains when they grow up, we used powerful brain scans to take detailed photos of the brain, and we compared the brains of children born early to those born at 9 months. We also studied the development of these children. We found that a part of the brain important for feelings and emotions, develops slightly differently in babies born early. These differences could explain why children born early may have more difficulty controlling their emotions. Brain differences could also explain why children born at 9 months may be less likely to develop anxiety and depression in later life. In this article, we will discuss the study findings, the impacts they might have, and how we can use this information to improve mental health in vulnerable children.

Associations of Postencephalitic Epilepsy Using Multi-Contrast Whole Brain MRI: A Large Self-Supervised Vision Foundation Model Strategy.

Postencephalitic epilepsy (PEE) is a severe neurological complication following encephalitis. Early identification of individuals at high risk for PEE is important for timely intervention. To develop a large self-supervised vision foundation model using a big dataset of multi-contrast head MRI scans, followed by fine-tuning with MRI data and follow-up outcomes from patients with PEE to develop a PEE association model. Retrospective. Fifty-seven thousand six hundred twenty-one contrast-enhanced head MRI scans from 34,871 patients for foundation model construction, and head MRI scans from 144 patients with encephalitis (64 PEE, 80 N-PEE) for the PEE association model. 1.5-T, 3-T, T1-weighted imaging, T2-weighted imaging, fluid attenuated inversion recovery, T1-weighted contrast-enhanced imaging. The foundation model was developed using self-supervised learning and cross-contrast context recovery. Patients with encephalitis were monitored for a median of 3.7 years (range 0.7-7.5 years), with epilepsy diagnosed according to International League Against Epilepsy. Occlusion sensitivity mapping highlighted brain regions involved in PEE classifications. Model performance was compared with DenseNet without pre-trained weights. Performance was assessed via confusion matrices, accuracy, sensitivity, specificity, precision, F1 score, and area under the receiver operating characteristic curve (AUC). The DeLong test evaluated AUC between the two models (P < 0.05 for statistical significance). The PEE association model achieved accuracy, sensitivity, specificity, precision, F1 score, and AUC of 79.3% (95% CI: 0.71-0.92), 92.3% (95% CI: 0.80-1.00), 68.8% (95% CI: 0.55-0.87), 70.6% (95% CI: 0.61-0.90), 80.0% (95% CI: 0.71-0.93), and 81.0% (95% CI: 0.68-0.92), respectively. A significant AUC improvement was found compared to DenseNet (Delong test, P = 0.03). The association model focused on brain regions affected by encephalitis. Using extensive unlabeled data via self-supervised learning addressed the limitations of supervised tasks with limited data. The fine-tuned foundation model outperformed DenseNet, which was trained exclusively on task data. This research develops a model to assess the occurrence epilepsy after encephalitis, a severe brain inflammation condition. By using over 57,000 brain scans, the study trains a computer program to recognize patterns in brain images. The model analyzes whole-brain scans to identify areas commonly affected by the disease, such as the temporal and frontal lobes. It was tested on data from patients with encephalitis and showed better performance than older methods. The model can assess the risk of secondary epilepsy in patients with encephalitis, allowing doctors to intervene early and improve treatment outcomes for those affected by this condition. 4 TECHNICAL EFFICACY: Stage 1.

ENSMBL-PASD: Spearheading early autism spectrum disorder detection through advanced genomic computational frameworks utilizing ensemble learning models.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition influenced by various genetic and environmental factors. Currently, there is no definitive clinical test, such as a blood analysis or brain scan, for early diagnosis. The objective of this study is to develop a computational model that predicts ASD driver genes in the early stages using genomic data, aiming to enhance early diagnosis and intervention. This study utilized a benchmark genomic dataset, which was processed using feature extraction techniques to identify relevant genetic patterns. Several ensemble classification methods, including Extreme Gradient Boosting, Random Forest, Light Gradient Boosting Machine, ExtraTrees, and a stacked ensemble of classifiers, were applied to assess the predictive power of the genomic features. TheEnsemble Model Predictor for Autism Spectrum Disorder (eNSMBL-PASD) model was rigorously validated using multiple performance metrics such as accuracy, sensitivity, specificity, and Mathew's correlation coefficient. The proposed model demonstrated superior performance across various validation techniques. The self-consistency test achieved 100% accuracy, while the independent set and cross-validation tests yielded 91% and 87% accuracy, respectively. These results highlight the model's robustness and reliability in predicting ASD-related genes. The eNSMBL-PASD model provides a promising tool for the early detection of ASD by identifying genetic markers associated with the disorder. In the future, this model has the potential to assist healthcare professionals, particularly doctors and psychologists, in diagnosing and formulating treatment plans for ASD at its earliest stages.

Rapid and quantitative CEST-MRI sequence using water presaturation.

Despite the significant potential for in vivo metabolic imaging in preclinical and clinical applications, CEST MRI suffers from long scan time and inaccurate quantification. This study aims to suppress the contaminations among signals under different frequencies, which could shorten the TR and thereby facilitate CEST imaging acceleration and quantification. A novel sequence is proposed by applying a water-presaturation (WPS) module at the beginning of each TR. WPS CEST quickly knocks down the residual signal from previous TRs so that the magnetization of all TRs recovers from zero, which aligns well with the formula of quasi-steady-state theorem and enables accurate quantification within shorter TR. WPS CEST was assessed by simulations, creatine phantom, and healthy human brain scans at 3 T. In simulation and phantom experiment, WPS CEST allows accurate estimation of exchange rate (ksw) using omega plot and using shorter delay time (Td) and saturation time (Ts) (e.g., 1 s/1 s) compared with the conventional CEST. Simulations further showed that WPS CEST could obtain consistent spin-lock relaxation (R1ρ) values over varied Tds and Tss. Six human scans indicated that R1ρ collected from conventional sequences showed significant differences between two groups with Td and Ts of (1 s/1 s) and (2 s/2 s) (amide: 1.721 ± 0.051 s-1 vs. 1.622 ± 0.050 s-1, p = 0.001; nuclear Overhauser enhancement: 1.792 ± 0.046 s-1 vs. 1.687 ± 0.053 s-1, p = 0.004), whereas WPS CEST scans using these 2 Td/Ts values obtained the same mean R1ρ (amide: 1.616 ± 0.053 s-1 vs. 1.616 ± 0.048 s-1, p = 0.862; nuclear Overhauser enhancement: 1.688 ± 0.064 s-1 vs. 1.684 ± 0.054 s-1, p = 0.544). WPS CEST demonstrated accurate quantitation within shorter TR compared with conventional sequences, and thereby may allow rapid quantitative CEST scans in various situations.

Predictors and Implications of Myocardial Injury in Intracerebral Hemorrhage.

Myocardial injury, indicated by an elevation of high-sensitive cardiac Troponin (hs-cTnT), is afrequent stroke-related complication. Most studies investigated patients with ischemic stroke, but only little is known about its occurrence in patients with intracerebral hemorrhage (ICH). This study aimed to assess the frequency, predictors, and implications of myocardial injury in ICH patients. Our retrospective analysis included 322 ICH patients. We defined myocardial injury as an elevation of hs-cTnT above the 99th percentile (i.e. 14 ng/L). Acute myocardial injury was defined as either achanging pattern of > 50% within 24 h or an excessive elevation of initial hs-cTnT (> 52 ng/L). 3D brain scans were assessed for ICH visually and quantitatively by adeep learning algorithm. Multiple regression models and Voxel-based Lesion-Symptom Mapping (VLSM) were applied. 63.0% (203/322) of patients presented with myocardial injury, which was associated with more severe strokes and worse outcomes during the in-hospital phase (P < 0.01). Acute myocardial injury occurred in 24.5% (79/322) of patients. The only imaging finding associated with acute myocardial injury was midline shift (69.8% vs. 44.6% for normal or stable hs-cTnT, P < 0.01), which also independently predicted it (odds ratio 3.29, confidence interval 1.38-7.87, P < 0.01). In contrast, VLSM did not identify any specific brain region significantly associated with acute myocardial injury. Acute myocardial injury did not correlate with preexisting cardiac diseases; however, the frequency of adverse cardiac events was higher in the acute myocardial injury group (11.4% vs.4.1% in patients with normal and/or stable patterns of hs-cTnT, P < 0.05). Myocardial injury occurs frequently in ICH and is linked to poor outcomes. Acute myocardial injury primarily correlates to space-occupying effects of ICH but is less dependent on premorbid cardiac status. Nonetheless, it is associated with ahigher rate of adverse cardiac events.

P-905. Post One-year Outcomes for Corticosteroid Use in Non-HIV Cryptococcal Meningoencephalitis

Abstract Background Cryptococcal meningoencephalitis (CM) is a major cause of mortality in HIV/AIDS, transplant recipients and previously healthy individuals. In the latter, a post-infectious inflammatory response syndrome (PIIRS) has been noted to have a favorable response to corticosteroids although long-term responses have not been studied. Methods In addition to standard antifungal therapy, 15 patients admitted with CM/PIIRS from 2015-2020 were treated with standard pulse – taper corticosteroid therapy (PCT) consisting of intravenous methylprednisolone 1 gm daily for 1 week followed by oral prednisone 1 mg/kg/d, tapered based on clinical and radiological response. One patient was excluded from the study due to death from an unrelated cause within 6 months of diagnosis. Comprehensive neurocognitive testing and MRI brain scans were performed one year after diagnosis to assess clinical status. Results 80% of patients were male, median age 51 years. Median time from antifungal treatment to steroid initiation was 6 weeks. Eleven of 14 patients were neuropsychologically evaluated using performance-based neurocognitive tests. A one-sample T- test showed that the cohort obtained significantly lower scores in memory, learning, language, and information processing/psychomotor speed test in comparison to a normative sample. Also, the mean memory, learning, psychomotor, and information processing speed scores were in the low average range. These findings suggest very mild cognitive deficits in this cohort one year post diagnosis. With the exception of one patient whose MRI brain showed worsened findings at the one-year mark due to a neuro-inflammatory flare, radiological findings suggested stability or improvement for the remaining 13 patients. CSF cultures remained negative. Conclusion Neurocognitive testing performed in a small cohort of previously healthy patients with CM-PIIRS showed an absence of moderate or major neurocognitive deficits one year post diagnosis with minimal adverse effects and no reoccurrence of infection. Brain MRI findings were also stable or improved for the majority. Disclosures All Authors: No reported disclosures

From circuits to lifespan: translating mouse and human timelines with neuroimaging based tractography.

Animal models are commonly used to investigate developmental processes and disease risk, but humans and model systems (e.g., mice) differ substantially in the pace of development and aging. The timeline of human developmental circuits is well known, butit is unclear how such timelines compare to those in mice. We lack age alignments across the lifespan of mice and humans. Here, we build upon our Translating Time resource, which is a tool that equates corresponding ages during development. We collected 1,125 observations from age-related changes in body, bone, dental, and brain processes to equate corresponding ages across humans, mice, and rats to boost power for comparison across humans and mice. We acquired high-resolution diffusion MR scans of mouse brains (n=16) of either sex at sequential stages of postnatal development (postnatal day 3, 4, 12, 21, 60) to track brain circuit maturation (e.g., olfactory association, transcallosal pathways). We found heterogeneity in white matter pathway growth. Corpus callosum growth largely ceases days after birth while the olfactory association pathway grows through P60. We found that a P3-4 mouse equates to a human at roughly GW24, and a P60 mouse equates to a human in teenage years. Therefore, white matter pathway maturation is extended in mice as it is in humans, but there are species-specific adaptations. For example, olfactory-related wiring is protracted in mice, which is linked to their reliance on olfaction. Our findings underscore the importance of translational tools to map common and species-specific biological processes from model systems to humans.Significance statement Mice are essential models of human brain development, but we currently lack precise age alignments across their lifespan. Here, we equate corresponding ages across mice and humans. We utilize high-resolution diffusion mouse brain scans to track the growth of brain white matter pathways, and we use our cross-species age alignments to map the timeline of these growth patterns from mouse to humans. In mice, olfactory association pathway growth continues well into the equivalent of human teenage years. The protracted development of olfactory association pathways in mice aligns with their specialized sense of smell. The generation of translational tools bridges the gap between animal models and human biology while enhancing our understanding of developmental processes generating variation across species.

Towards Sustainable Magnetic Resonance Neuro Imaging: Pathways for Energy Optimization and Cost Reduction Strategies

We evaluated the energy consumption of a 3T MRI using a central monitoring system, focusing on hospital energy costs during peak winter months from 2021 to 2023. We analyzed consumption during non-productive phases like end-of-day standby and assessed their impact. For active use, we compared standard and AI-enhanced protocols on phantoms, scheduling high-demand protocols during off-peak hours to benefit from lower energy prices. Standard protocols consumed 3.4 to 15 kWh, while optimized protocols used 2.3 to 10.6 kWh, reducing consumption by 32% on average. Savings per scan ranged from EUR 0.03 to EUR 3.7. The electrical consumption of a brain MRI protocol is equivalent to that of 3–4 knee protocols or 2–3 lumbar spine protocols. Using AI-optimized protocols and management, 41 protocols can be completed in 12 h, up from 30, reducing daily costs by EUR 2.38 to EUR 29.18. Annually, AI-optimized protocols could save 7900 to 8800 kWh per MRI unit, totaling 10,500 to 11,600 MWh across France’s MRI fleet, equivalent to the yearly consumption of about 4700 to 5300 people. Optimizing MRI resource use can expand patient access while significantly reducing the associated energy footprint. These findings support the implementation of more sustainable practices in medical imaging without compromising care quality.

COMPUTED TOMOGRAPHY CEREBRAL PERFUSION TO PREDICT FUNCTIONAL OUTCOME IN PAEDIATRIC HEAD INJURY: A COMPARITIVE STUDY OF VOXEL BASED AND WHOLE BRAIN PERFUSION.

This study evaluates the extent of perfusion abnormalities in pediatric traumatic head injury patients by using computed tomography perfusion (CTP) and compares the efficacy of voxel based and whole brain perfusion data clinically with functional outcome scales GOSE-P and MRS. In this Prospective study 100 eligible patients of age group 0-15 years were enrolled. Subjects were categorized into mild, moderate and severe traumatic brain injury using GCS.CT perfusion scans were performed at admission and at time of discharge. Both voxel-based and whole brain perfusion data were acquired at five regions of interest: orbitofrontal cortex, internal capsule, thalamus, caudate nucleus, and sensorimotor cortex for cerebral blood perfusion. The extent of perfusion abnormalities were noted in CTP scans. GOSE-P and MRS were utilised to clinically evaluate functional outcomes. Significant differences in CT perfusion findings between voxel-based and whole brain approaches were noted. Voxel-based scans demonstrated superior predictive value in severe cases, while whole brain scans were promising in moderate cases. GCS scores and specific CT parameters (CBF AND MTT) were also significant predictors of outcomes. The comparative analysis highlights the complementary roles of voxel-based and whole brain perfusion CT in predicting functional outcomes in pediatric head injury cases. Clinicians should consider both approaches when evaluating cerebral perfusion status and making treatment decisions. Further research is warranted to validate these findings and refine imaging protocols to optimize predictive accuracy in this vulnerable population.

Using neuroimaging to identify sex differences in adults with sports-related concussion: a systematic review.

Concussion is a common injury in sports that causes neurological damage, leading to memory loss and difficulty concentrating. Insufficient recovery time may result in significant long-term harm to individuals. Several neuroimaging techniques have been used to understand the pathophysiological changes following concussion, and how long individuals need to recover before returning to play. Despite the progress in neuroimaging concussion research, few studies have considered whether females sustain different effects on the brain and how recovery from concussion might differ from males. Thus, we conducted a systematic review of the existing literature to highlight sex differences in concussion with neuroimaging techniques. By searching four different databases, studies were selected if they used a neuroimaging technique to examine sex differences following concussion in athletes over the age of 18. After screening 2295 studies from an initial search, 15 were found to match the selection criteria. Nine papers established some difference between males and females, however many of these studies were not designed to specifically examine sex differences, and hence conclusions in this regard are somewhat limited. A further common limitation among these papers was a lack of whole brain scans, instead relying on regions of interest analyses, which reduces the ability to compare studies effectively. The current systematic review has highlighted the need for future studies to specifically consider whether, and how sex influences the impact and trajectory of brain recovery from concussion. This can then help to inform suitable amendments to current concussion return-to-play protocols for male and female athletes.

Multicentre, multitime, multidimension, prospective follow-up cohort study on patients during the first wave of COVID-19 in China: a study protocol

IntroductionDuring the first wave of the COVID-19 outbreak in China, the surge of COVID-19 cases was rapid and drastic. Emerging evidence suggests that beyond the acute phase, patients with COVID-19...

Exposure to Ambient Temperature and Functional Connectivity of Brain Resting-State Networks in Preadolescents.

Exposure to extreme temperatures has been linked to acute mental-health events in young populations, but the underlying neural mechanisms are not well understood. Resting-state functional magnetic resonance imaging allows for the assessment of connectivity patterns in brain functional networks, which have been associated with mental-health disorders. We investigated the short-term effects of ambient temperature on functional connectivity of brain resting-state networks in preadolescents. The study was embedded in the Generation R Study, Rotterdam, The Netherlands. Daily mean temperature estimates at the participants' residential address were obtained from a high-resolution urban climate model (UrbClim). Resting-state functional connectivity data was assessed with brain magnetic resonance images of 2,229 children aged 9-12 years. We fitted distributed lag non-linear models to assess the cumulative effects of temperature during the week before the brain scan on within- and between-network connectivity of 15 resting-state networks. Higher ambient temperature during the week before the imaging assessment was associated with lower functional connectivity within the medial-parietal, salience, and hippocampus networks. The effect was highest the day before the brain scan, and progressively decayed in the preceding days. Lower temperatures were not related to functional connectivity. Exposure to high ambient temperatures over a seven-day period was associated with lower within-network connectivity in preadolescents, suggesting impacts of heat on brain function. These findings raise new research questions on whether decreases in functional connectivity within the salience network may partially explain the association between high temperatures and suicide rates previously reported in the literature.

The neural ensembles activated by propofol and isoflurane anesthesia across the whole mouse brain.

General anesthesia has been widely used in surgical procedures. Propofol and isoflurane are the most commonly used injectable and inhaled anesthetics, respectively. The various adverse effects induced by propofol and isoflurane are highly associated with the anesthetic-dependent change of brain activities. In this work, we aim to delineate a brain-wide neuronal activity landscape of injectable versus inhaled anesthetics to understand the neural basis underlying the different physiological effects induced by these two major types of anesthetics. Through detailed scanning of the whole mouse brain subjected to propofol or isoflurane anesthesia, in total, we identified 17 subcortical regions, 3 of which (anterodorsal preoptic nucleus, ADP; lateral habenular, LHb; inferior olivary nucleus, ION) were specifically activated by propofol, and 3 (ventral part of the lateral septum, LSV; the intermediate part of the lateral septum, LSI; the solitary tract nucleus, Sol) were specifically activated by isoflurane, with the remaining 11 were activated by both two anesthetics. Moreover, within the 17 brain regions, ADP, SubCV (subcoeruleus nucleus, ventral part), PCRtA (parvicellular reticular nucleus, alpba part) and ION were newly identified that activated by propofol or isoflurane, respectively. By using Targeted Recombination in Active Populations (TRAP) technique, we further showed that propofol and isoflurane largely activate the same group of neurons in supraoptic nucleus (SON), but activate different groups of neurons in central amygdala (CeA). Our results reveals the neural ensembles activated by injectable and inhaled anesthetics, and provides detailed anatomical references for future studies on general anesthesia.

Unmasking the Dark Triad: A Data Fusion Machine Learning Approach to Characterize the Neural Bases of Narcissistic, Machiavellian and Psychopathic Traits.

The Dark Triad (DT), encompassing narcissism, Machiavellianism and psychopathy traits, poses significant societal challenges. Understanding the neural underpinnings of these traits is crucial for developing effective interventions and preventive strategies. Our study aimed to unveil the neural substrates of the DT by examining brain scans from 201 individuals (mean age: 32.43, 105 females) using the unsupervised learning algorithm transposed independent vector analysis (tIVA). tIVA, known for identifying complex patterns in neuroimaging data, detected 15 joint grey matter (GM) and white matter (WM) networks. Of these networks, four were associated with the DT. The first component comprises areas within the reward network, including the thalamus, caudate, anterior cingulate and prefrontal regions. The second component encompasses regions within the executive network, predominantly involving prefrontal and posterior areas. The third component includes regions within the default mode network (DMN), such as the angular gyrus, the precuneus and the posterior cingulate cortex. Lastly, the fourth component overlaps with areas of the visual network, primarily located in the occipital and temporal lobes. Within these networks, the reward-related component correlated with narcissism, suggesting an association with the need for constant interpersonal rewards to enhance self-esteem and grandiosity in narcissistic individuals. Conversely, the DM-related component correlated with Machiavellianism, potentially reflecting the heightened strategic thinking employed by Machiavellian individuals for manipulation purposes. In line with established trends, sex differences emerged, with males displaying notably higher DT scores. Our findings offer insights into the intricate neurobiological bases of the DT personality and hold implications for future research and interventions.

White Matter Tract Crossing and Bottleneck Regions in the Fetal Brain.

There is a growing interest in using diffusion MRI to study the white matter tracts and structural connectivity of the fetal brain. Recent progress in data acquisition and processing suggests that this imaging modality has a unique role in elucidating the normal and abnormal patterns of neurodevelopment in utero. However, there have been no efforts to quantify the prevalence of crossing tracts and bottleneck regions, important issues that have been investigated for adult brains. In this work, we determined the brain regions with crossing tracts and bottlenecks between 23 and 36 gestational weeks. We performed probabilistic tractography on 62 fetal brain scans and extracted a set of 51 distinct white matter tracts, which we grouped into 10 major tract bundle groups. We analyzed the results to determine the patterns of tract crossings and bottlenecks. Our results showed that 20%-25% of the white matter voxels included two or three crossing tracts. Bottlenecks were more prevalent. Between 75% and 80% of the voxels were characterized as bottlenecks, with more than 40% of the voxels involving four or more tracts. These results highlight the relevance of these regions to key developmental processes, specifically, the dispersion of projection fibers, the protracted growth of commissural pathways, and the emergence of association tracts that contribute to the formation of complex intersection regions. These developmental interactions lead to a high prevalence of crossing fibers and bottleneck areas, reflecting the intricate organization required for establishing structural and functional connectivity. Additionally, our results highlight the challenge of fetal brain tractography and structural connectivity assessment and call for innovative image acquisition and analysis methods to mitigate these problems.

Normative modeling of brain MRI data identifies small subcortical volumes and associations with cognitive function in youth with fetal alcohol spectrum disorder (FASD).

To quantify regional subcortical brain volume anomalies in youth with fetal alcohol spectrum disorder (FASD), assess the relative sensitivity and specificity of abnormal volumes in FASD vs. a comparison group, and examine associations with cognitive function. Participants: 47 children with FASD and 39 typically-developing comparison participants, ages 8-17years, who completed physical evaluations, cognitive and behavioral testing, and an MRI brain scan. A large normative MRI dataset that controlled for sex, age, and intracranial volume was used to quantify the developmental status of 7 bilateral subcortical regional volumes. Z-scores were calculated based on volumetric differences from the normative sample. T-tests compared subcortical volumes across groups. Percentages of atypical volumes are reported as are sensitivity and specificity in discriminating groups. Lastly, Pearson correlations examined the relationships between subcortical volumes and neurocognitive performance. Participants with FASD demonstrated lower mean volumes across a majority of subcortical regions relative to the comparison group with prominent group differences in the bilateral hippocampi and bilateral caudate. More individuals with FASD (89%) had one or more abnormally small volume compared to 72% of the comparison group. The bilateral hippocampi, bilateral putamen, and right pallidum were most sensitive in discriminating those with FASD from the comparison group. Exploratory analyses revealed associations between subcortical volumes and cognitive functioning that differed across groups. In this sample, youth with FASD had a greater number of atypically small subcortical volumes than individuals without FASD. Findings suggest MRI may have utility in identifying individuals with structural brain anomalies resulting from PAE.

Clinicians' perspectives on the use of artificial intelligence to triage MRI brain scans.

Artificial intelligence (AI) tools can triage radiology scans to streamline the patient pathway and also relieve clinician workload. Validated AI tools can mitigate the delays in reporting scans by flagging time-sensitive and actionable findings. In this study, we aim to investigate current stakeholder perspectives and identify obstacles to integrating AI in clinical pathways. We created a survey to ascertain the perspectives of 133 clinicians across the United Kingdom regarding the acceptability of an AI tool that triages MRI brain scans into 'normal' and 'abnormal'. As part of this survey, we supplied clinicians with information on training and validation case numbers, model performance, validation using unseen data, and explainability saliency maps. With regards to the specific use case of AI in MRI brain scans, 71% of respondents preferred the use of an AI-assisted triage compared to the current system without triage, typically chronologically. Notably, information that explained and helped visualise the AI model's decision making was found to improve clinician confidence. When shown a heatmap, 60% of participants felt more confident in the AI's decision. The results of this short communication demonstrate a positive support for the implementation of AI-assistive tools in triage.

ASSOCIATIONS OF MEAN COGNITIVE PERFORMANCE AND INTRAINDIVIDUAL VARIABILITY WITH WHITE MATTER LESIONS

Abstract White matter lesions (WMLs) are magnetic resonance imaging markers of small vessel cerebrovascular disease and have been associated with Alzheimer’s disease and related dementias. Intraindividual variability (IIV), often measured as variability in performance across neuropsychological tests at a single time point, has emerged as a sensitive marker of early cognitive difficulties that may have utility beyond measures of mean neuropsychological performance (MP). However, the associations of IIV with neuroimaging variables remains understudied. This study included 70 older adults without dementia (mean age=68.57) who completed a comprehensive neuropsychological battery and underwent MRI brain scans. WMLs were adjusted for estimated total intracranial volume and transformed to reduce skew. Linear regression models examined the associations of IIV, MP, and WMLs both across and within the cognitive domains of memory, attention/processing speed, and executive function. Covariates included age, sex, and education. IIV showed no significant association with WMLs, neither within nor across the domains examined (all p’s&amp;gt;.05). In the domains of memory (B=-.035, p=.025), executive function (B=-.039, p=.018), and in global cognition (B=-.065, p=.003) lower MP was associated with more WMLs. In the attention/processing speed domain, MP was not significantly associated with WMLs (all p’s &amp;gt;.05). The present study only examined cross-sectional data, so future studies should re-evaluate the associations with IIV, MP, and WMLs longitudinally. While the small sample size may limit the generalizability of this study, these findings suggest that measures of MP may better reflect WMLs relative to measures of IIV.

Prevalence of Neurodiversity in a UK High Secure Psychiatric Hospital Cohort: A Records Study

ABSTRACTBackgroundThe term neurodiversity is an umbrella term for any atypical pattern of cognitive ability, including but not confined to neurodevelopmental disorders. Research suggests that several neurodivergent conditions are overrepresented in offender populations, with a recent survey suggesting that over half of those coming into contact with the criminal justice system may have a neurodivergent condition. Considerable effort has been invested in trying to divert people with such conditions out of long‐stay hospitals, but nevertheless, a few studies in secure hospitals suggest that while prevalence in hospitals may be lower than in prisons, it is high relative to the general population.AimsTo determine the prevalence of recorded neurodivergent conditions in one high secure hospital.MethodsWe conducted a records survey of a resident cohort of men in one high secure hospital in England during December 2022.ResultsRecords were accessed for all 197 resident men. According to these records, over one‐half (115, 58%) of the men had at least one neurodivergent condition; nearly a third (56, 29%) had more than one form of neurodivergent condition. The most frequently recorded form of neurodivergent condition was general cognitive dysfunction (24%), followed by general language difficulties (16%), ADHD (15%) and autism (14%) and those with a history of seizures (14%) and atypical brain scans (12%). Dyslexia was reported within 6.5% of patient notes, acquired brain injury 5% and chromosomal disorders 2%. The survey also suggests some differences in the prevalence of neurodivergent disorders across clinical groups, with higher rates among people with mental illness than with personality disorder. Prevalence was also unevenly distributed across nature of ward type.ConclusionsWith the survey suggesting that the majority of patients in one high secure psychiatric hospital have at least one form of neurodivergent condition, it raises questions around how useful the term is and what the term neurodivergence means in this population. With each form of neurodiversity having different needs, the diversity of conditions present also raises questions around what a ‘neurodiverse informed model of care’ would look like in forensic mental health services.

An examination of cortical thickness relationships within the reading network of adults.

Much brain imaging work has underscored the functional connections among the inferior frontal gyrus (IFG; articulation), supramarginal gyrus (SMG; letter-sound correspondence), superior temporal gyrus (STG; sound) and fusiform gyrus (FFG; print) during basic reading processes. This reading network supports and coordinates the complex processes that contribute to successful reading. In line with the Hebbian notion that 'neurons that fire together, wire together' we examined cortical thickness among these regions and the extent to which these regions showed structural relationships in average and impaired readers. Structural high resolution brain scans from 87 adult participants including average (N = 56; 51 right-handed; females = 29; mean age = 20.5; SD = 2.14) and impaired (N = 31; 27 right-handed; females = 24; mean age = 23.1; SD = 4.23) readers were collated. Cortical thickness measurements of the left and right IFG, SMG, STG, and FFG were extracted. Average readers had significantly greater cortical thickness in the right IFG and right SMG compared to impaired readers. Within each group, similarly strong relationships between the left and right structures were observed. Average readers had a significantly stronger connection between the left IFG-FFG compared to impaired readers (p = 0.012). In contrast, the impaired readers had a significantly stronger connection between the left STG-FFG compared to average readers (p = 0.027). In conclusion, the findings suggest that structural relationships within the reading network may contribute to variations in reading proficiency, with average readers exhibiting distinct patterns of cortical thickness and relationships compared to impaired readers. Further exploration of these structural differences could offer valuable insights into the neural mechanisms underlying reading abilities and disabilities.