Flexible circuit-based spatially aware modular optical brain imaging system for high-density measurements in natural settings.

Significance: Functional near-infrared spectroscopy (fNIRS) presents an opportunity to study human brains in everyday activities and environments. However, achieving robust measurements under such dynamic conditions remains a significant challenge. Aim: The modular optical brain imaging (MOBI) system is designed to enhance optode-to-scalp coupling and provide a real-time probe three-dimensional (3D) shape estimation to improve the use of fNIRS in everyday conditions. Approach: The MOBI system utilizes a bendable and lightweight modular circuit-board design to enhance probe conformity to head surfaces and comfort for long-term wearability. Combined with automatic module connection recognition, the built-in orientation sensors on each module can be used to estimate optode 3D positions in real time to enable advanced tomographic data analysis and motion tracking. Results: Optical characterization of the MOBI detector reports a noise equivalence power of 8.9 and 7.3 pW / Hz at 735 and 850 nm, respectively, with a dynamic range of 88 dB. The 3D optode shape acquisition yields an average error of 4.2 mm across 25 optodes in a phantom test compared with positions acquired from a digitizer. Results for initial in vivo validations, including a cuff occlusion and a finger-tapping test, are also provided. Conclusions: To the best of our knowledge, the MOBI system is the first modular fNIRS system featuring fully flexible circuit boards. The self-organizing module sensor network and automatic 3D optode position acquisition, combined with lightweight modules ( 18 g / module ) and ergonomic designs, would greatly aid emerging explorations of brain function in naturalistic settings.

Dynamic Ultrasound Localization Microscopy Without ECG-Gating.

OBJECTIVE: Dynamic Ultrasound Localization Microscopy (DULM) has first been developed for non-invasive Pulsatility measurements in the rodent brain. DULM relies on the localization and tracking of microbubbles (MBs) injected into the bloodstream, to obtain highly resolved velocity and density cine-loops. Previous DULM techniques required ECG-gating, limiting its application to specific datasets, and increasing acquisition time. The objective of this study is to eliminate the need for ECG-gating in DULM experiments by introducing a motion-matching method for time registration. METHODS: We developed a motion-matching algorithm based on tissue Doppler that leverages the cyclic tissue motion within the brain. Tissue Doppler was estimated for each group of frames in the acquisitions, at multiple locations identified as local maxima in the skin above the skull. Subsequently, each group of frames was time-registered to a reference group by delaying it based on the maximum correlation value between their respective tissue Doppler signals. This synchronization ensured that each group of frames aligned with the brain tissue motion of the reference group, and consequently, with its cardiac cycle. As a result, velocities of MBs could be averaged to retrieve flow velocity variations over time. RESULTS: Initially validated in ECG-gated acquisitions in a rat model (n = 1), the proposed method was successfully applied in a mice model in 2D (n = 3) and in a feline model in 3D (n = 1). Performing time-registration with the proposed motion-matching method or by using ECG-gating leads to similar results. For the first time, dynamic velocity and density cine-loops were extracted without the need for any information on the animal ECG, and complex dynamic markers such as the Pulsatility index were estimated. CONCLUSION: Results suggest that DULM can be performed without external gating, enabling the use of DULM on any ULM dataset where enough MBs are detectable. Time registration by motion-matching represents a significant advancement in DULM techniques, making DULM more accessible by simplifying its experimental complexity.

A survey of brain functional network extraction methods using fMRI data.

Functional network (FN) analyses play a pivotal role in uncovering insights into brain function and understanding the pathophysiology of various brain disorders. This paper focuses on classical and advanced methods for deriving brain FNs from functional magnetic resonance imaging (fMRI) data. We systematically review their foundational principles, advantages, shortcomings, and interrelations, encompassing both static and dynamic FN extraction approaches. In the context of static FN extraction, we present hypothesis-driven methods such as region of interest (ROI)-based approaches as well as data-driven methods including matrix decomposition, clustering, and deep learning. For dynamic FN extraction, both window-based and windowless methods are surveyed with respect to the estimation of time-varying FN and the subsequent computation of FN states. We also discuss the scope of application of the various methods and avenues for future improvements.

NEATmap: a high-efficiency deep learning approach for whole mouse brain neuronal activity trace mapping.

Quantitative analysis of activated neurons in mouse brains by a specific stimulation is usually a primary step to locate the responsive neurons throughout the brain. However, it is challenging to comprehensively and consistently analyze the neuronal activity trace in whole brains of a large cohort of mice from many terabytes of volumetric imaging data. Here, we introduce NEATmap, a deep learning-based high-efficiency, high-precision and user-friendly software for whole-brain neuronal activity trace mapping by automated segmentation and quantitative analysis of immunofluorescence labeled c-Fos+ neurons. We applied NEATmap to study the brain-wide differentiated neuronal activation in response to physical and psychological stressors in cohorts of mice.

Cross-modal plasticity in children with cochlear implant: converging evidence from EEG and functional near-infrared spectroscopy.

Over the first years of life, the brain undergoes substantial organization in response to environmental stimulation. In a silent world, it may promote vision by (i) recruiting resources from the auditory cortex and (ii) making the visual cortex more efficient. It is unclear when such changes occur and how adaptive they are, questions that children with cochlear implants can help address. Here, we examined 7-18 years old children: 50 had cochlear implants, with delayed or age-appropriate language abilities, and 25 had typical hearing and language. High-density electroencephalography and functional near-infrared spectroscopy were used to evaluate cortical responses to a low-level visual task. Evidence for a 'weaker visual cortex response' and 'less synchronized or less inhibitory activity of auditory association areas' in the implanted children with language delays suggests that cross-modal reorganization can be maladaptive and does not necessarily strengthen the dominant visual sense.

Neuroimaging evaluation of the long term impact of a novel paired meditation practice on brain function.

Background: A growing number of advanced neuroimaging studies have compared brain structure and function in long term meditators to non-meditators. The goal is to determine if there may be long term effects on the brain from practicing meditation. In this paper, we present new data on the long term effects of a novel meditation practice in which the focus is on clitoral stimulation. The findings from such a study have implications for potential therapeutic uses with regard to various neurological or psychiatric conditions. Methods: We evaluated the cerebral glucose metabolism in 40 subjects with an extended history (>1 year of practice, 2-3 times per week) performing the meditation practice called Orgasmic Meditation (OM) and compared their brains to a group of non-meditating healthy controls (N = 19). Both meditation and non-meditation subjects underwent brain PET after injection with 148 to 296 MBq of FDG using a standard imaging protocol. Resting FDG PET scans of the OM group were compared to the resting scans of healthy, non-meditating, controls using statistical parametric mapping. Results: The OM group showed significant differences in metabolic activity at rest compared to the controls. Specifically, there was significantly lower metabolism in select areas of the frontal, temporal, and parietal lobes, as well as the anterior cingulate, insula, and thalamus, in the OM group compared to the controls. In addition, there were notable distinctions between the males and females with the females demonstrating significantly lower metabolism in the thalamus and insula. Conclusions: Overall, these findings suggest that the long term meditation practitioners of OM have different patterns of resting brain metabolism. Since these areas of the brain in which OM practitioners differ from controls are involved in cognition, attention, and emotional regulation, such findings have implications for understanding how this meditation practice might affect practitioners over long periods of time.

Imaging features for the identification of atrial fibrillation in cryptogenic stroke patients.

BACKGROUND: Whether specific imaging aspects can be used to identify cryptogenic stroke (CS) patients with high risk of underlying atrial fibrillation (AF) remains unclear. The purpose of this study was to evaluate brain-imaging features in CS patients and their utility as AF predictors. METHODS: The Nordic Atrial Fibrillation and Stroke study was a prospective observational study of CS and transient ischemic attack patients undergoing 12-month cardiac-rhythm monitoring, biomarker and clinical assessments. In this imaging sub-study, brain magnetic resonance imaging and computed tomography scans from 106 patients were assessed for acute and chronic ischemic lesions in relation to AF occurrence and included in a score to predict AF. Receiver operating characteristics (ROC) curve was used to evaluate the discriminative ability of the score and for its dichotomization for predictive model. RESULTS: Age, periventricular white-matter hyperintensities (PVWMH), acute lesion size, and vessel occlusion were significantly associated with AF. Acute and chronic cortical infarcts as well as chronic cerebellar infarcts were numerically more frequent in the AF group than the non-AF group. A score consisting of six features (0-6 points) was proposed (age ≥ 65 years, chronic cortical or cerebellar lesions, acute cortical lesions, PVWMH ≥ 2 in Fazekas scale, vessel occlusion, and acute lesion size ≥ 10 mm). Area under ROC curve was 0.735 and a score of ≥ 3 points was a predictor of AF. CONCLUSIONS: The suggested score was shown to identify CS patients with an increased risk of underlying AF.

Functional connectivity development in the prenatal and neonatal stages measured by functional magnetic resonance imaging: A systematic review.

The prenatal and neonatal periods are two of the most important developmental stages of the human brain. It is therefore crucial to understand normal brain development and how early connections are established during these periods, in order to advance the state of knowledge on altered brain development and eventually identify early brain markers of neurodevelopmental disorders and diseases. In this systematic review (Prospero ID: CRD42024511365), we compiled resting state functional magnetic resonance imaging (fMRI) studies in healthy fetuses and neonates, in order to outline the main characteristics of typical development of the functional brain connectivity during the prenatal and neonatal periods. A systematic search of five databases identified a total of 12 573 articles. Of those, 28 articles met pre-established selection criteria based determined by the authors after surveying and compiling the major limitations reported within the literature. Inclusion criteria were: (1) resting state studies; (2) presentation of original results; (3) use of fMRI with minimum one Tesla; (4) a population ranging from 20 weeks of GA to term birth (around 37-42 weeks of PMA); (5) singleton pregnancy with normal development (absence of any complications known to alter brain development). Exclusion criteria were: (1) preterm studies; (2) post-mortem studies; (3) clinical or pathological studies; (4) twin studies; (5) papers with a sole focus on methodology (i.e. focused on tool and analysis development); (6) volumetric studies; (7) activation map studies; (8) cortical analysis studies; (9) conference papers. A risk of bias assessment was also done to evaluate each article's methodological rigor. 1877 participants were included across all the reviewed articles. Results consistently revealed a developmental gradient of increasing functional brain connectivity from posterior to anterior regions and from proximal-to-distal regions. A decrease in local small-world organization shortly after birth was also observed; small-world characteristics were present in fetuses and newborns, but appeared weaker in the latter group. Also, the posterior-to-anterior gradient could be associated with earlier development of the sensorimotor networks in the posterior regions while more complex higher-order networks (e.g. attention-related) mature later in the anterior regions. The main limitations of this systematic review stem from the inherent limitations of functional imaging in fetuses, mainly: unevenly distributed populations and limited sample sizes; fetal movements in the womb and other imaging obstacles; and a large voxel resolution when imaging a small brain. Another limitation specific to this review is the relatively small number of included articles compared to very a large search result, which may have led to relevant articles having been overlooked.

Alice ROSENSTEIN(1898-1991) First German female Neurosurgeon.

Gender inequality has been a long-standing issue throughout history, with limited progress despite the rise of women in the workforce. Historically, women were deemed inferior to men, including within the medical profession, due to perceived bodily differences. This perception was reinforced in religious texts, depicting women as bearing the burden of the first woman's transgressions. Such attitudes also influenced the treatment of women's health, with menstruation viewed as a natural source of suffering. Nevertheless, a thorough examination of medical history unveils a deep-rooted bias against women.This antiquated and discriminatory notion lacks any foundation in scientific truth. Indeed, an examination of the contributions made by female physicians reveals that they deliver equivalent levels of care, attentiveness, preventive measures, and therapeutic efficacy as their male counterparts (1-2). The narratives of female trailblazers in the medical field, like Alice Rosenstein, the first female neurosurgeon in Germany, provide compelling evidence of this phenomenon. This paper delves into her professional journey and the significant influence she has had on the field of neurosurgery.

Recent treatment and novel imaging studies evaluating treatment of internet gaming disorder: a narrative review.

Internet Gaming Disorder (IGD) is an emerging public health concern; effective treatments are still under development. This mini-review focuses on summarizing the main scientific evidence from psychological, pharmacological, brain imaging, and emerging treatment approaches for IGD. We searched PubMed and Scopus databases using keywords related to IGD and treatment. Cognitive behavioral therapy (CBT) is the most extensively researched psychological treatment for IGD, supported by several randomized controlled trials (RCTs). Other promising approaches include mindfulness, relapse prevention, abstinence protocols, and family therapy. Pharmacological treatments like bupropion and escitalopram have shown benefits, especially when IGD is comorbid with conditions like major depressive disorder. However, the quality of evidence is moderate for psychological interventions but low to moderate for pharmacological approaches. Emerging treatments such as transcranial direct current stimulation (tDCS), repetitive transcranial magnetic stimulation (rTMS), and electro-acupuncture have demonstrated efficacy in reducing IGD symptoms and modulating brain activity. Brain imaging techniques like functional magnetic resonance imaging (fMRI) have provided insights into the neural mechanisms underlying IGD and treatment effects, although these studies lack randomized controlled designs. While multimodal approaches show promise, larger, well-designed RCTs are needed to establish effective IGD treatments.

Hemiplegic (unilateral) cerebral palsy in northern Stockholm: Intellectual disability and epilepsy.

PURPOSE: The purpose of this study was to describe intellectual disability and its association with epilepsy and brain imaging, in a population-based group of children with hemiplegic (unilateral) cerebral palsy, previously investigated and published in 2020. MATERIALS AND METHODS: Forty-seven children of school age in northern Stockholm, fulfilling the Surveillance of Cerebral Palsy in Europe-criteria of hemiplegic (unilateral spastic) cerebral palsy, were invited to participate in the study. Twenty-one children consented to participate. A WISC (Wechsler Intelligence Scale for Children)-test was performed by an experienced psychologist. RESULTS: In the study population of twenty-one children, 57 % (n 12) displayed uneven cognitive profiles, 38 % (n 8) intellectual disability and 62 % (n 13) had a normal IQ. 43 % (n 9) developed epilepsy. Children with extensive brain lesions had more severe intellectual disability. CONCLUSIONS: In this study intellectual disability and/or epilepsy were associated with the type and extent of the underlying brain lesion. Intellectual disability and uneven cognitive profiles were common. We therefore recommend individual cognitive assessment to ensure an optimal school start.

Exploring the dynamics of prefrontal cortex in the interaction between orienteering experience and cognitive performance by fNIRS.

Sporting experience plays a pivotal role in shaping exercise habits, with a mutually reinforcing relationship that enhances cognitive performance. The acknowledged plasticity of cognition driven by sports necessitates a comprehensive examination. Hence, this study delves into the dynamic intricacies of the prefrontal cortex, exploring the impact of orienteering experience on cognitive performance. Our findings contribute empirical evidence regarding the functional activation of specific brain regions bridging the nexus between experiential factors and cognitive capabilities. In this cross-sectional study, a cohort of forty-nine athletes was enrolled to meticulously examine behavioral variances and prefrontal cortex dynamics among orienteering athletes of varying experience levels across diverse non-specialized scenarios. These investigations involved the utilization of functional near-infrared spectroscopy (fNIRS) to detect alterations in oxygenated hemoglobin (HbO2). The high-experience expert group exhibited neurological efficiency, demonstrating significantly diminished brain activation in the dorsolateral prefrontal, left ventral lateral prefrontal, and right orbitofrontal regions compared to the low-experience group. Within the low-experience novice group, superior performance in the spatial memory task was observed compared to the mental rotation task, with consistently lower reaction times across all conditions compared to the high-experience group. Notably, cerebral blood oxygenation activation exhibited a significant reduction in the high-experience expert group compared to the low-experience novice group, irrespective of task type. The dorsolateral prefrontal lobe exhibited activation upon task onset, irrespective of experience level. Correct rates in the spatial memory task were consistently higher than those in the mental rotation task, while brain region activation was significantly greater during the mental rotation task than the spatial memory task." This study elucidates disparities in prefrontal cortex dynamics between highly seasoned experts and neophyte novices, showcasing a cognitive edge within the highly experienced cohort and a spatial memory advantage in the inexperienced group. Our findings contribute to the comprehension of the neural mechanisms that underlie the observed cognitive advantage and provide insights into the forebrain resources mobilized by orienteering experience during spatial cognitive tasks."

Cognitive and brain morphological deviations in middle-to-old aged autistic adults: A systematic review and meta-analysis.

Cognitive challenges and brain structure variations are common in autism spectrum disorder (ASD) but are rarely explored in middle-to-old aged autistic adults. Cognitive deficits that overlap between young autistic individuals and elderlies with dementia raise an important question: does compromised cognitive ability and brain structure during early development drive autistic adults to be more vulnerable to pathological aging conditions, or does it protect them from further decline? To answer this question, we have synthesized current theoretical models of aging in ASD and conducted a systematic literature review (Jan 1, 1980 - Feb 29, 2024) and meta-analysis to summarize empirical studies on cognitive and brain deviations in middle-to-old aged autistic adults. We explored findings that support different aging theories in ASD and addressed study limitations and future directions. This review sheds light on the poorly understood consequences of aging question raised by the autism community to pave the way for future studies to identify sensitive and reliable measures that best predict the onset, progression, and prognosis of pathological aging in ASD.

Compact and cost-effective laser-powered speckle contrast optical spectroscopy fiber-free device for measuring cerebral blood flow.

Significance: In the realm of cerebrovascular monitoring, primary metrics typically include blood pressure, which influences cerebral blood flow (CBF) and is contingent upon vessel radius. Measuring CBF noninvasively poses a persistent challenge, primarily attributed to the difficulty of accessing and obtaining signal from the brain. Aim: Our study aims to introduce a compact speckle contrast optical spectroscopy device for noninvasive CBF measurements at long source-to-detector distances, offering cost-effectiveness, and scalability while tracking blood flow (BF) with remarkable sensitivity and temporal resolution. Approach: The wearable sensor module consists solely of a laser diode and a board camera. It can be easily placed on a subject's head to measure BF at a sampling rate of 80 Hz. Results: Compared to the single-fiber-based version, the proposed device achieved a signal gain of about 70 times, showed superior stability, reproducibility, and signal-to-noise ratio for measuring BF at long source-to-detector distances. The device can be distributed in multiple configurations around the head. Conclusions: Given its cost-effectiveness, scalability, and simplicity, this laser-centric tool offers significant potential in advancing noninvasive cerebral monitoring technologies.

Cognitive driven gait freezing phase detection and classification for neuro-rehabilitated patients using machine learning algorithms.

BACKGROUND: The significance of diagnosing illnesses associated with brain cognitive and gait freezing phase patterns has led to a recent surge in interest in the study of gait for mental disorders. A more precise and effective way to characterize and classify many common gait problems, such as foot and brain pulse disorders, can improve prognosis evaluation and treatment options for Parkinson patients. Nonetheless, the primary clinical technique for assessing gait abnormalities at the moment is visual inspection, which depends on the subjectivity of the observer and can be inaccurate. RESEARCH QUESTION: This study investigates whether it is possible to differentiate between gait brain disorder and the typical walking pattern using machine learning driven supervised learning techniques and data obtained from inertial measurement unit sensors for brain, hip and leg rehabilitation. METHOD: The proposed method makes use of the Daphnet freezing of Gait Data Set, consisted of 237 instances with 9 attributes. The method utilizes machine learning and feature reduction approaches in leg and hip gait recognition. RESULTS: From the obtained results, it is concluded that among all classifiers RF achieved highest accuracy as 98.9 % and Perceptron achieved lowest i.e. 70.4 % accuracy. While utilizing LDA as feature reduction approach, KNN, RF and NB also achieved promising accuracy and F1-score in comparison with SVM and LR classifiers. SIGNIFICANCE: In order to distinguish between the different gait disorders associated with brain tissues freezing/non-freezing and normal walking gait patterns, it is shown that the integration of different machine learning algorithms offers a viable and prospective solution. This research implies the need for an impartial approach to support clinical judgment.

Silent brain infarctions in patients with acute cardioembolic stroke.

INTRODUCTION AND AIM: The advances and the wide use of brain imaging have considerably increased the prevalence of silent brain infarctions (SBI). We aim in this study to determine the prevalence of SBI in patients presenting with acute cardioembolic stroke and the predictive cardiovascular risk factors. METHODS: This retrospective study included 267 patients presenting with acute cardioembolic stroke in the emergency and/or neurology departments of the Hassan II University Hospital Center. Clinical, biological and echocardiographic characteristics were recorded. All patients were screened for SBI by brain imaging. RESULTS: The prevalence of SBI in our series was 46%. A group of 203 non-valvular patients and a group of 64 valvular patients were distinguished. In non-valvular group, the average age was 72.97±10.53years. The prevalence of SBI was 45.3%. Forty-four percent of patients with SBI had atrial fibrillation (AF). In multivariate regression analysis, the history of previous stroke, CHA2DS2-VASc Score≥4, enlarged left atrium (LA), the association of AF with enlarged LA and the lability of International Normalized Ratio in patients initially treated with anticoagulants were significantly associated with the occurrence of SBI (P=0.013, P=0.032, P=0.0001, P=0.01, P=0.03, respectively). Territorial location was significantly the most frequent (P=0.007). In valvular group, the average age was 57.19±14.38years. The prevalence of SBI was 48.4%. In multivariate regression analysis, SBI were significantly associated with moderate or severe mitral stenosis (P=0.02) and with the enlarged LA (P=0.02). In all patients, Modified Rankin Scale at 3 months of discharge from the acute stroke was significantly higher (mRS≥3) in patients with SBI (P=0.04). CONCLUSIONS: SBI requires good management of associated cardiovascular risk factors in a population presenting with initial cardioembolic stroke.

Dissociative Amnesia: Remembrances Under Cover.

The existence or questionability of "repressed memories" can be discussed as being a matter of definition. It seems, however, far-fetched to consider all "lost" memories as caused by encoding problems, brain damage, forgetfulness, failure to disclose events, and so on. We argue that dissociative amnesia (DA) (or "psychogenic amnesia," or "functional amnesia," or, as we favor to call it, "mnestic block syndrome") is caused by psychic alterations, but ultimately they can be traced to changes in the physiology of the brain, as we are of the opinion that all memory processes-positive or negative-alter brain functions, sometimes more permanently, sometimes transiently. We have proven this idea using functional imaging techniques, in particular fluoro-deoxy-d-glucose positron emission tomography. Having investigated dozens of patients with severe and long-lasting DA conditions, we believe it to be disrespectful to many (but not to all) of the affected patients to question their disease condition, which can be proven to be not caused by feigning, malingering, or direct brain damage.

Mobile neuroimaging: What we have learned about the neural control of human walking, with an emphasis on EEG-based research.

Our understanding of the neural control of human walking has changed significantly over the last twenty years and mobile brain imaging methods have contributed substantially to current knowledge. High-density electroencephalography (EEG) has the advantages of being lightweight and mobile while providing temporal resolution of brain changes within a gait cycle. Advances in EEG hardware and processing methods have led to a proliferation of research on the neural control of locomotion in neurologically intact adults. We provide a narrative review of the advantages and disadvantages of different mobile brain imaging methods, then summarize findings from mobile EEG studies quantifying electrocortical activity during human walking. Contrary to historical views on the neural control of locomotion, recent studies highlight the widespread involvement of many areas, such as the anterior cingulate, posterior parietal, prefrontal, premotor, sensorimotor, supplementary motor, and occipital cortices, that show active fluctuations in electrical power during walking. The electrocortical activity changes with speed, stability, perturbations, and gait adaptation. We end with a discussion on the next steps in mobile EEG research.

Regional Brain Net Water Uptake in Computed Tomography after Cardiac Arrest - A Novel Biomarker for Neuroprognostication.

BACKGROUND: Selective water uptake by neurons and glial cells and subsequent brain tissue oedema are key pathophysiological processes of hypoxic-ischemic encephalopathy (HIE) after cardiac arrest (CA). Although brain computed tomography (CT) is widely used to assess the severity of HIE, changes of brain radiodensity over time have not been investigated. These could be used to quantify regional brain net water uptake (NWU), a potential prognostic biomarker. METHODS: We conducted an observational prognostic accuracy study including a derivation (single center cardiac arrest registry) and a validation (international multicenter TTM2 trial) cohort. Early (<6 h) and follow-up (>24 h) head CTs of CA patients were used to determine regional NWU for grey and white matter regions after co-registration with a brain atlas. Neurological outcome was dichotomized as good versus poor using the Cerebral Performance Category Scale (CPC) in the derivation cohort and Modified Rankin Scale (mRS) in the validation cohort. RESULTS: We included 115 patients (81 derivation, 34 validation) with out-of-hospital (OHCA) and in-hospital cardiac arrest (IHCA). Regional brain water content remained unchanged in patients with good outcome. In patients with poor neurological outcome, we found considerable regional water uptake with the strongest effect in the basal ganglia. NWU >8% in the putamen and caudate nucleus predicted poor outcome with 100% specificity (95%-CI: 86-100%) and 43% (moderate) sensitivity (95%-CI: 31-56%). CONCLUSION: This pilot study indicates that NWU derived from serial head CTs is a promising novel biomarker for outcome prediction after CA. NWU >8% in basal ganglia grey matter regions predicted poor outcome while absence of NWU indicated good outcome. NWU and follow-up CTs should be investigated in larger, prospective trials with standardized CT acquisition protocols.

Cerebral 18F-FDG PET/CT Metabolism as Diagnostic Signature for Central Nervous System Toxicity After Immune Checkpoint Blockade Cancer Treatment.

Our aim was to investigate probable biomarkers specific to immune-related central nervous system toxicity (CNST) in cancer patients treated with immune checkpoint inhibitors (ICI) by analysis of 18F-FDG PET/CT images. Methods: Cancer patients receiving ICI treatment were enrolled in a multicenter observational study that analyzed regional metabolic changes before and during CNST onset from January 2020 to February 2022. In 1:1 propensity score-matched pairs, the regional SUVmean of each bilateral brain lobe of CNST patients (CNST+) was compared with that of patients who had central nervous system infections (CNSIs) and patients without CNST or CNSI (CNST-). In a validation cohort, patients were recruited from February 2022 to July 2023 and followed up for 24 wk after the start of ICI. Early changes in regional SUVmean at 5-6 wk after therapy initiation were evaluated for ability to predict later CNST onset. Results: Of 6,395 ICI-treated patients, 2,387 underwent prognostic 18F-FDG PET/CT and 125 of the scanned patients had CNST (median time from ICI treatment to onset, 9 wk; quartile range, 2-23 wk). Regional 18F-FDG PET/CT SUVmean changes were higher in CNST+ than in CNST- patients (117 patient pairs) but were lower than in CNSI patients (50 pairs). Differentiating analysis reached an area under the curve (AUC) of 0.83 (95% CI, 0.78-0.88) for CNST+ versus CNST- and of 0.80 (95% CI, 0.72-0.89) for CNST+ versus CNSI. Changes in SUVmean were also higher before CNST onset than for CNST- (60 pairs; AUC, 0.74; 95% CI, 0.66-0.83). In a validation cohort of 2,878 patients, preonset changes in SUVmean reached an AUC of 0.86 (95% CI, 0.79-0.94) in predicting later CNST incidence. Conclusion: Brain regional hypermetabolism could be detected during and before CNST clinical onset. CNST may be a distinct pathologic entity versus brain infections defined by 18F-FDG PET/CT brain scans. Regional SUV differences may be translated into early diagnostic tools based on moderate differentiating accuracy in our study.