Brain Magnetic Resonance Imaging Research Articles

Plasma trimethylamine-n-oxide associates with reduced hippocampal volume and cognitive impairment in atrial fibrillation

Abstract Background/Introduction Atrial fibrillation (AF) is the most common cardiac arrhythmia in modern society and affected patients appear particularly vulnerable to cognitive dysfunction. Yet, the pathomechanism of this association other than thromboembolism (TE) is not fully understood. We have shown earlier an association of cognitive dysfunction with the gut microbiome derivate trimethylamine-N-oxide (TMAO), which predominantly results from the consumption of red meat. We therefore hypothesized that TMAO may affect hippocampal volume (HV) as a brain structure relevant for cognition. Purpose To demonstrate the structure-function correlation of high TMAO levels with reduced cognitive function and lower HV in a large cohort of patients with atrial fibrillation. Methods We included 1’736 patients with confirmed AF from the Swiss-AF-cohort with both, available blood samples for TMAO measurement and with brain magnetic resonance imaging (bMRI) for the determination of HV at baseline. TMAO levels were measured by liquid chromatography-mass spectrometry (LC-MS). bMRI were obtained by 1.5 or 3 Tesla scanners. HV was assessed by the FreeSurfer software (v 7.4.0) subregion segmentation module and normalized by using Sequence Adaptive Multimodal SEGmentation (SAMSEG) to determine the segmentation based intracranial volume. Patients were divided into TMAO quartiles (Q1: 0.6-3.8, Q2: 3.8-5.5, Q3: 5.5-8.5, Q4: 8.5-164.3μmol/l). Their TMAO levels were compared with their HV (unit = mm3) in linear mixed effect models adjusted for multiple covariates (model 1: age, sex, total intracranial volume (ICV), education level; model 2 = model 1 + smoking status, body mass index (BMI), alcohol consumption, physical activity; model 3 = model 2 + hypertension, coronary artery disease, previous stroke, geriatric depression scale). We assessed both unilateral HV (right = RHV, left = LHV) and bilateral HV standardized by the individual total ICV. Results Overall mean age was 72.5 years (+/-8.4 SD), 27.2% were female. Most of the patients were well educated (39.4% advanced, 48.8% middle education) and 44% never smoked. After multivariable adjustments, patients in the highest TMAO quartile showed a significant reduction of bilateral HV volume of 93.4mm3 (95% CI -179.0 to -7.8, p = 0.03). The RHV appeared more affected and was significantly reduced by 48.2mm3 (CI -93.4, -3.0, p=0.04), whereas LHV was decreased by 44.2mm3 (-89.4, 1.0, p=0.06) in the highest TMAO quartile. Conclusion(s) TMAO negatively associates with bilateral HV in patients with AF. Our results suggest a structure-function-correlation between high TMAO levels and cognitive dysfunction. The findings may be relevant for the high TMAO-exposed patients and advocates for the importance of (possible dietary) prevention in AF.

Direct synchronized cardioversion not independently associated with infarcts on cerebral magnetic resonance imaging and clinical outcomes in patients with atrial fibrillation

Abstract Background Direct synchronized cardioversion (DCV) is frequently performed in atrial fibrillation (AF). In general, DCV is considered a safe procedure. A rare, but feared complication following DCV is an overt ischemic stroke resulting from embolization of a left atrial clot to the cerebral circulation. Purpose The aim of the present study was to assess the association of DCV with infarcts on brain magnetic resonance imaging (bMRI) and clinical outcomes. Methods 2386 patients of the Swiss AF cohort were included. 1731 patients were evaluated by bMRI. DCVs were recorded by questionnaire. Patients were categorized by number of DCVs performed before enrollment (0,1,≥2). BMRI were conducted at baseline and after 2 years (n=1227) and analyzed for large noncortical or cortical infarcts (LNCCI) and small noncortical infarcts (SNCI). Clinical outcomes were recorded during follow-up. Associations of DCV and outcome-measures were assessed by multivariate analyses. Results There was no independent association between the number of DCV and infarct prevalence (LNCCI + SNCI) on baseline bMRI (DCV 1 vs. 0: OR 0.95 [95% CI 0.73-1.26]; DCV ≥2 vs. 0: OR 1.04 [0.73-1.51]) or between DCV performed during follow-up and new infarcts on bMRI at 2 years (OR 1.46 [0.54-3.31]). DCVs were not associated with overt stroke or transient ischemic attack (DCV 1 vs. 0: HR 1.35 [0.87-2.03]; DCV ≥2 vs. 0: HR 1.54 [0.95-2.49]), hospitalization for heart failure (DCV 1 vs. 0: HR 1.03 [0.80-1.33]; DCV ≥2 vs. 0: HR 1.03 [0.77-1.37]), or death (DCV 1 vs. 0: HR 0.85 [0.67-1.09]; DCV ≥2 vs. 0: HR 0.92 [0.70-1.22]). Conclusions There was no association between DCV performed before enrollment and cerebral infarcts on baseline bMRI or between DCV performed during follow-up and new infarcts at 2 years. Moreover, DCV were not associated with clinical events.

Effect of nelonemdaz for patients with out-of-hospital cardiac arrest: the AWAKE phase II randomised clinical trial

Abstract Background Hypoxic brain injury is a major hurdle that limits the survival of out-of-hospital cardiac arrest (OHCA). Nelonemdaz is a dual-target neuroprotectant, serving as a moderate NR2B-selective N-methyl-D-aspartate (NMDA) receptor antagonist while also exhibiting potent free radical scavenger properties. This dual neuroprotective action of nelonemdaz has the potential to reduce hypoxic brain injury in OHCA. We investigated the efficacy and safety of nelonemdaz for patients with OHCA. Methods AWAKE trial was a double-blind, placebo-controlled, randomised, multicentre phase II trial at 5 sites in South Korea. OHCA patients undergoing targeted temperature management were randomly assigned to high-dose (5250 mg), low-dose (3250 mg), and placebo groups at a 1:1:1 ratio. The primary outcome was the blood level of neuron-specific enolase (NSE) after 4th administration of drug. Secondary outcomes comprised blood biomarkers including neuron specific enolase (NSE) and S100beta, brain magnetic resonance imaging (MRI), and Cerebral Performance Category (CPC) and Modified Rankin Scale (mRS) up to day 90. Safety is assessed by serious adverse event. Findings: A total of 105 patients were enrolled between November 18, 2018 to February 23, 2023. Patients with a median age of 61 years and 82% male were assigned to the high-dose (N=37), low-dose (N=35), and placebo (N=33) groups. Primary outcome was evaluated in 93 patients. There was no difference of neuron specific enolase (NSE, ng/mL), which served as the primary endpoint, between high-dose (median and interquartile range; 23·7, 15·0–69·9) and placebo (17·5, 13·6–113·0) groups and also between low-dose (26·6, 16·2–83·4) versus placebo groups (all p>0·05). Among secondary outcomes, fractional anisotropy of brain MRI was significantly higher in high-dose group compared to placebo group (0·465, 0·449–0·485 versus 0·441, 0·431–0·464; p=0·028), and was not different between low-dose (0·462, 0·439–0·480) and placebo groups (p>0·05). At day 90, the common odds ratio (95% confidence interval) indicating a favourable shift in the modified Rankin Scale was 1·25 (0·48–3·24) and 1·22 (0·47–3·20) in the high-dose and low-dose groups respectively, compared to placebo group (all p>0·05). No serious adverse events were reported. Interpretation: Nelonemdaz did not reduced blood NSE level of OHCA patients. However, patients treated with high-dose nelonemdaz showed better fractional anisotropy that suggests reduced cerebral white matter damage. Patients treated with nelonemdaz also showed a favourable tendency of neurological recovery at day 90 without significant adverse effects. These results justify the initiation of a large-scale phase III trial.Neurological function up to day 90

Brain tumor classification utilizing pixel distribution and spatial dependencies higher-order statistical measurements through explainable ML models

Brain tumors are among the most fatal and devastating diseases, and they often result in a significant reduction in life expectancy. The devising of treatment plans that can extend the lives of affected individuals hinges on an accurate diagnosis of these tumors. Identifying and analyzing large volumes of magnetic resonance imaging (MRI) data manually proves to be both challenging and time-consuming. As a result, there exists a pressing need for a reliable machine-learning approach to accurately diagnose brain tumors, and numerous methods have already been proposed over the last decade. In this paper, a novel, comprehensive approach is proposed for identifying and classifying a given MR brain image as abnormal. Three common brain diseases, namely glioma, meningioma, and pituitary tumor, are chosen as abnormal brains, and the Figshare MRI brain image dataset was collected from the Kaggle and IEEE websites. The proposed method is initiated by employing 1st-order statistics, 2nd-order statistics, and higher-order transformed (DWT) feature extraction to extract features from images. Then missing data is addressed and handled using KNNImputer, followed by the application of the ExtratreesClassifier and PCA feature selection methods to identify the most relevant features and reduce the dimensions of these features. Subsequently, the reduced features are submitted to seven machine learning models, namely RF, GB, CB, SVM, LGBM, DT, and LR. The strategy of k-fold cross-validation is utilized to enhance the performance of those models. Finally, the models are evaluated using XAI approaches, which ensure transparent decision-making processes and provide insights into the model’s predictions. Remarkably, our approach achieves the highest accuracy, precision, recall, F1 score, MCC, Kappa, AUC-ROC, and R2, as well as the lowest loss, among the seven models evaluated, proving its effectiveness and applicability in multiple analytic applications relying on publicly available datasets.

Ex vivo magnetic resonance imaging of the human fetal brain.

The fetal brain undergoes a dynamic process of development during gestation, marked by well-orchestrated events such as neuronal proliferation, migration, axonal outgrowth, and dendritic arborization, mainly elucidated through histological studies. Ex vivo magnetic resonance imaging (MRI) has emerged as a useful tool for 3D visualization of the developing fetal brain, serving as a complementary tool to traditional histology. In this review, we summarized the commonly employed ex vivo MRI techniques and their advances in fetal brain imaging, as well as a standard protocol for postmortem fetal brain specimen collection and fixation. We then provided an overview of ex vivo MRI-based studies on the fetal brain. According to our review, ex vivo T1- or T2-weighted structural MRI has contributed to the characterization of the anatomy of transient neuronal proliferative zones, the basal ganglia, and the cortex. Diffusion MRI related techniques, such as diffusion tensor imaging and tractography, have helped to investigate the microstructural patterns of fetal brain tissue, as well as the early emergence and development of neuronal migration pathways and white matter bundles. Ex vivo MRI findings have shown strong histological correlations, supporting the potential of MRI in evaluating the developmental events in the fetal brain. Postmortem MRI examinations have also demonstrated comparable, and in certain cases, superior performance to traditional autopsy in revealing fetal brain abnormalities. In conclusion, ex vivo fetal brain MRI is an invaluable tool that provides unique insights into the early stages of brain development.

Large sample size MRI measurements to assess the relation between cardiac function and structure and white matter hyperintensity volumes

Abstract Background People with established cardiovascular disease (CVD) are at risk of early cognitive decline, and neurological diseases such as dementia. CVD and neurological diseases share common risk factors, such as blood pressure, sedentary lifestyle, as well as genomic risk factors such as mutations in APOE4 [1]. It's unclear to what extent the co-occurrence of CVD and neurological diseases is explained by these risk factors, or whether there is a direct association where CVD is a first step towards poorer neurological health. White matter hyperintensities (WMH) of presumed vascular origin are damaged areas in the brain observed through magnetic resonance imaging (MRI). These lesions are associated with progressive neurological disease such as vascular dementia, as well with risk factors for CVD [2]. Purpose We set out to determine to what extent CMR measurements associated with WMH independent of known cerebrovascular risk factors. Methods Cardiac and brain MRI images were analysed for 23,963 UK biobank (UKB) participants. WMH analysis included 5 brain regions (Frontal[F], Parietal[P], Temporal[T], Occipital[O], Basal Ganglia and Thalami [BGT]) and total brain WMH volume. Cardiac traits included stroke volumes, atrial volumes, ejection fractions of right and left chambers, left ventricular (LV) strain, LV wall thickness and aortic areas. Multivariable regression analysis was carried out, where each cardiac trait was regressed on each brain region and adjusted for: age, difference between age at initial visit and imaging visit, sex, systolic and diastolic blood pressure, Hba1c, household income, educational status, Townsend score and family history of disease (Alzheimer’s, Parkinson's, high blood pressure, stroke, heart disease) . Results were evaluated against a multiple testing correct p-value threshold of 0.05, reflecting the number of principle components(n=10) necessary to explain 90% of the cardiac trait variability. Results For 5 cardiac traits (right ventricular stroke volume, left atrial stroke volume, left ventricular stroke volume, left ventricular ejection fraction and right ventricular end diastolic volume) higher values were associated with lower WMH volumes in all brain regions. Additionally, some cardiac traits such as LV cardiac output associated with specific brain regions (T, O, BGT). Additionally, APOE- ε4 stratified analyses indicated, homozygous carriers show a greater association between higher minimum LA and RA volumes and higher WMH volumes in the occipital lobe. Conclusions This study gives an insight into the WMH burden in a large population of adults. It highlights the associations of cardiac traits with white matter hyperintensity volumes in different brain regions independent of known risk factors. Using cardiac traits as surrogate markers of different cardiac disease could explain how cardiac functionality defines WMH volume distribution and subsequently the wider relationship between CVD and cerebrovascular disease.Figure 1Graphical Abstract

Phosphorylated tau protein serum levels increase over time in patients with chronic heart failure

Abstract Background/Introduction Amongst various potential biomarkers associated with cognitive deficits, phosphorylated Tau (pTau) appears to link brain and cardiac abnormalities through a systemic tauopathy pathway. Purpose A recent report on the potential importance of myocardial pTau in chronic heart failure (HF) prompted the here described longitudinal quantification of circulating pTau serum levels in patients with HF. We hypothesized that serum pTau accumulates in HF and is associated with markers of myocardial dysfunction. Methods Eligible patients within the prospective, investigator-initiated, monocentric follow-up study Cognition.Matters-HF were older than 18 years, suffered from stable chronic HF and were free from major neurological or psychiatric disorders. Beyond the cardiological assessment including transthoracic echocardiography and six minute walking distance (6-MWD), investigations at baseline, 1 year and 3 years comprised extensive, domain-specific psychological testing and volumetric brain magnetic resonance imaging. Serum pTau was measured using the pTau181 advantage kit. Results Serum samples were available from 78 patients. Mean age was 63±10 years and 87% were men. Serum pTau longitudinally increased from a median of 1.05 (quartiles 0.26, 1.21) pg/ml at baseline to 1.84 (1.36, 3.60) pg/ml after 3 years (p<0.001). During that time period, LVEF, NT-proBNP, 6-MWD and the hippocampal volume remained unaltered, whereas global brain volume and cortical thickness shrank age-appropriately. Cognitive testing revealed that domain-specific T-scores within 36 months remained stable for attentional intensity and executive functioning, and even improved for memory. When we entered baseline values of age and above-mentioned cardiac, brain-volumetric, and cognitive parameters into a multivariable regression model predicting log-transformed pTau, only age (β=0.34), NT-proBNP (β=0.24) and GBV (β=0.26) were independently associated with pTau serum levels (R2=0.18). Consistently, at 36 months, the same predictors were selected by the model (R2=0.29): age (β=0.41), NT-proBNP (β=0.43), and global brain volume (β=0.26). Moreover, higher baseline pTau (β=0.23) and lower 6-MWD (β=-0.39) independently predicted ΔpTau with an explained variance (R2) of 0.24. Conclusions We observed a prominent increase of serum pTau over time, which was predicted by prevalent myocardial dysfunction. Moreover, absolute NT-proBNP levels were independently associated with absolute pTau serum levels, along with age and global brain volume. Mechanistically, phosphorylation of cardiac tau is thought to destabilize its interaction with microtubules causing microtubule detyronisation and increased myocardial stiffness through enhancing the mechanical resistance of contracting cardiomyocytes. The etiological role of pTau in the development of HF and the potential of serum pTau as a novel biomarker of chronic HF warrants further studies.

Association of obesity and metabolic health status with cerebral small vessel disease in stroke-free individuals

Abstract Background It remains unclear whether obesity itself or metabolic abnormalities coexisting with obesity, are associated with stroke. Purpose We aimed to investigate the association of obesity and metabolic health status with cerebral small vessel disease (SVD) in stroke-free participants from a brain health check-up. Methods We conducted a cross-sectional study of 6088 stroke-free participants who underwent brain magnetic resonance imaging at a brain check-up between 2013 and 2020. Participants were categorised according to sex-specific waist circumference and metabolic health status. A metabolically healthy status was defined as the absence of components of metabolic syndrome other than a large waist circumference, such as high blood pressure, hyperglycaemia, and dyslipidaemia. The total SVD score was derived from four magnetic resonance imaging markers: silent lacunar infarcts, cerebral microbleeds, moderate-to-severe white matter hyperintensities, and enlarged perivascular spaces. Results The mean age of the participants was 55±12 years and 46% were women. The prevalence of metabolically healthy obesity was 650 (11%) and the proportion of metabolically healthy obesity among individuals with obesity was 24%. The prevalence of metabolically unhealthy obesity was 2043 (34%), and the proportion of metabolically unhealthy obesity among individuals with metabolically unhealthy individuals was 58%. The prevalence of moderate-to-severe SVD scores (≥2) was 348 (6%), which was higher in metabolically unhealthy individuals, regardless of obesity status. Compared with the metabolically healthy non-obesity group, the metabolically unhealthy non-obesity (odds ratio 2.22 [95% CI, 1.44–3.42]) and metabolically unhealthy obesity (odds ratio, 2.76 [95% CI, 1.80–4.24]) groups had a significantly higher multivariable-adjusted risk for a total SVD score of ≥2. Further sensitivity analyses using BMI-defined obesity instead of waist circumference-defined obesity yielded similar results. Conclusions Abdominal and general obesity alone are not associated with higher total SVD scores in stroke-free individuals. Unhealthy metabolic components, especially high blood pressure and hyperglycaemia, are important risk factors for SVD.

Multidomain cognitive improvement in patients with severe aortic valve stenosis undergoing transcatheter aortic valve implantation

Abstract Background Cognitive impairment is prevalent in one third of patients with symptomatic severe aortic valve stenosis scheduled for transcatheter aortic valve implantation (TAVI). How TAVI affects cognitive functioning in these patients remains unknown. Purpose The CAPITA study (CArdiac outPut, cerebral blood flow and cognition In patients with severe aortic valve stenosis undergoing Transcatheter Aortic valve implantation) assessed the effects of TAVI on cerebral lesions and cognitive functioning. Methods CAPITA is a prospective study of cerebral and cognitive outcomes in 148 patients undergoing TAVI. One day before and three months after TAVI, patients underwent a standardized multidomain neuropsychological assessment, and simultaneous brain magnetic resonance imaging. The primary outcome was change in global cognitive functioning as measured with z-scores. Also, we assessed the cognitive subdomains of attention/psychomotor speed, memory, language, and executive functioning. Z-scores for each cognitive domain were constructed as: (test score - mean baseline score) / standard deviation. Global cognitive function was calculated as the mean from the four domain scores. Results Mean age was 80.5±5.7 years, 43% was female and median STS-PROM (Society for Thoracic Surgeons Predicted Risk for 30-day Mortality) was 2.0% (IQR 1.4%-2.9%). MoCA scores improved from 23.3±3.7 to 24.4±3.3, (p<0.001) and MMSE scores from 26.4±2.6 to 26.9±2.4 (p=0.01). There was an overall increase in global cognitive z-scores (0.02±0.52 to 0.15±0.48, p<0.001). Cognitive domains of memory (0.03±0.77 to 0.18±0.80, p=0.003) and language (-0.07±1.07 to 0.20±0.80, p=0.02) significantly improved, whereas executive function (0.01±0.70 to 0.06±0.76, p=0.42) and attention (0.10±0.69 to 0.17±0.69, p=0.06) did not significantly change. Quality of life on the visual analogue scale improved from 66.4±15.9 to 72.9±12.8, (p<0.001). Patients in the lowest tertile of baseline cognitive functioning (i.e., those with worst baseline cognitive functioning), had the largest increase in cognitive functioning, compared with patients in the intermediate or highest tertile of baseline cognitive functioning (0.30±0.55 vs 0.09±0.27 vs 0.01±0.16, p=0.002). Patients with >0.5 SD decline in cognitive functioning (12%), had a higher volume of new white matter hyperintensities on follow-up MRI than patients with stable or improved cognitive functioning (1.26±2.96, vs 0.29±0.45 vs 0.31±0.91 mL, p=0.06). Conclusions In 148 patients who underwent TAVI, there was an overall improvement in cognitive functioning at three months follow-up. This improvement was consistent through different cognitive domains and most prominent in patient with lowest baseline cognitive functioning.Change in cognitive functionin

Atypical posterior reversible encephalopathy syndrome following craniotomy for a metastatic lesion: illustrative case.

An 80-year-old male was found to have a metastatic lesion in his cerebrum. He underwent uncomplicated resection with prolonged inhalational anesthesia due to issues with intravenous access prior to surgery. Postoperatively, the patient had persistent altered mental status. Immediate postoperative head computed tomography and continuous electroencephalography were negative for possible causes. Standard brain magnetic resonance imaging (MRI) after metastatic resection demonstrated the development of edema in his pons and thalami, concerning for posterior reversible encephalopathy syndrome (PRES). Tight blood pressure control was initiated. His neurological examination returned to baseline. Follow-up MRI showed the resolution of edema. This is a report of PRES hypothesized to be attributable to prolonged inhalational anesthetic. PRES is a disorder in which patients present with altered mentation, seizures, visual impairment, or headache. PRES often occurs due to acute uncontrolled hypertension; however, other conditions, including autoimmune disease and cancer chemotherapy, have been linked. In severe cases, permanent brain damage and death have been reported. The authors present a case of PRES as the cause of severe neurological decline following craniotomy without severe or sustained hypertension. The authors hypothesize that PRES could be caused by blood pressure variability in the perioperative period and prolonged anesthesia. https://thejns.org/doi/10.3171/CASE24245.

Recognisable Neuroradiological Findings in Five Neurogenetic Disorders.

The rate of discovery and increased understanding of genetic causes for neurodevelopmental disorders has peaked over the past decade. It is well recognised that some genes show marked variability in neuroradiological phenotypes, and inversely, some radiological phenotypes are associated with several different genetic conditions. However, some readily recognisable brain magnetic resonance imaging (MRI) patterns, especially in the context of corresponding associated clinical findings, should prompt consideration of a pathogenic variant in a specific gene or gene pathway. As these conditions can often prove challenging to diagnose, a clinical suspicion of a specific disorder may be invaluable to guide and interpret genetic testing. This review focuses on five neurogenetic syndromes with recognisable brain findings that radiologists, paediatric neurologists, geneticists, and other specialists involved in neurodevelopmental disorders should be able to recognise in order to pinpoint the gene or gene groups involved and delve into their molecular mechanisms. The comprehensively reviewed conditions include DDX3X-related neurodevelopmental disorder, Van Maldergem syndrome, NMDAR-related disorders, EML1-associated disorder and ARFGEF2-related periventricular nodular heterotopia with microcephaly.

Efficient and Compressed Deep Learning Model for Brain Tumour Classification With Explainable AI for Smart Healthcare and Information Communication Systems

ABSTRACTThe detection of brain tumours presents a significant challenge in the medical domain, where prompt and precise diagnosis is crucial as patient outcomes depend on it. Conventional deep neural networks perform well in carrying out various imaging tasks within the healthcare sector; however, their effectiveness often falls short of expectations in practical applications due to the substantial computational resources required and issues with reliability. In this research, an optimised and effective deep learning model founded on the DenseNet‐169 architecture is introduced for the classification of magnetic resonance imaging brain tumours, which is particularly advantageous for smart healthcare systems and information and communication technology (ICT) settings with limited computational capabilities. The model compression methodologies, including pruning and quantization, have been employed to significantly diminish the dimensions and intricacy of the model while achieving a classification accuracy of 97.07%. Furthermore, this endeavour necessitates the enhancement of the model's interpretability through the utilisation of explainable artificial intelligence methodologies such as Gradient‐weighted Class Activation Mapping (Grad‐CAM) and SHapley Additive exPlanations (SHAP), which will aid clinicians in highlighting crucial areas of the images and validating feature importance concerning the decisions rendered by the model. A comparative performance evaluation is conducted against DenseNet‐169, ResNet‐50 and various other models to delineate the superior efficacy of our model, rendering it exceptionally adept for knowledge‐driven, real‐time brain tumour diagnosis within smart healthcare and ICT systems where resources are constrained.

Influence of brain metastases on the classification, treatment, and outcome of patients with extracranial oligometastasis: a single-center cross-sectional analysis

Background and introductionIncreasing evidence suggests that a subgroup of patients with oligometastatic cancer might achieve a prolonged disease-free survival through local therapy for all active cancer lesions. Our aims are to investigate the impact of brain metastases on the classification, treatment, and outcome in these patients.Materials and methodsWe analyzed a total of 7,000 oncological positron emission tomography scans to identify patients with extracranial oligometastatic disease (defined as ≤ 5 intra- or extra-cranial metastases). Concurrent magnetic resonance imaging brain was assessed to quantify intracranial tumor burden. We investigated the impact of brain metastases on oligometastatic disease state, therapeutic approaches, and outcome. Predictors for transitioning from oligo- to polymetastatic states were evaluated using regression analysis.ResultsA total of 106 patients with extracranial oligometastases and simultaneous brain metastases were identified, primarily originating from skin or lung/pleura cancers (90%, n = 96). Brain metastases caused a transition from an extracranial oligometastatic to a whole-body polymetastatic state in 45% (n = 48) of patients. While oligometastatic patients received systemic therapy (55% vs. 35%) more frequently and radiotherapy for brain metastases was more often prescribed to polymetastatic patients (44% vs. 26%), the therapeutic approach did not differ systematically between both sub-groups. The oligometastatic sub-group had a median overall survival of 28 months compared to 10 months in the polymetastatic sub-group (p < 0.01).ConclusionIn patients with brain metastases, a low total tumor burden with an oligometastatic disease state remained a significant prognostic factor for overall survival. Presence of brain metastases should therefore not serve as exclusion criterion for clinical trials in the field of oligometastatic disease. Moreover, it underscores the importance of considering a multimodality treatment strategy in oligometastatic cancer patients.

Segmentation of MR images for brain tumor detection using autoencoder neural network

Medical images often require segmenting into different regions in the first analysis stage. Relevant features are selected to differentiate various regions from each other, and the images are segmented into meaningful (anatomically significant) regions based on these features. The purpose of this study is to present a model for segmenting and identifying the local tumor formation in MR images of the human brain. The proposed system operates in an unsupervised manner to minimize the intervention of expert users and to achieve an acceptable speed in the tumor classification process. The proposed method includes several steps of preprocessing for different brain image classify that Perform the normalization task. These preprocessing steps lead to more accurate results in high-resolution images and ultimately improve the accuracy and sensitivity of tumor separation from brain tissue. The output of this stage is applied to a self-encoding neural network for image zoning. By nature of self-encoding networks, leads to reduce the dimensionality of tumor pixels from the surrounding healthy environment, which significantly helps remove regions incorrectly extracted as tumors. Finally, by extracting features from the previous stage's output through Otsu thresholding, the surrounding area and type of tumor are also extracted. The proposed method was trained and tested using the BRATS2020 database and evaluated by various performance metrics. The results based on the Dice Similarity Coefficient (DSC) show an accuracy of 97% for the entire MR image and improved detection accuracy compared to other methods, as well as a reduction in the cost of the diagnostic process.

MELAS Presenting as Bilateral Symmetric Occipital and Temporal Cortices Lesions: A Case Report and Literature Review.

Mitochondrial myopathy, encephalopathy, lactic acidosis, and stroke-like episode (MELAS) is one of the most common maternally inherited mitochondrial diseases. The stroke-like episode affecting the cortical cortex is the hallmark of MELAS; however, it rarely presents as simultaneously bilateral symmetric cortices lesions. We reported a case of MELAS in a 46-year-old female patient with bilateral symmetric occipital and internal temporal cortices involvements on brain magnetic resonance imaging (MRI). A literature review of MELAS patients and a retrospective analysis were performed. She had a family history of diabetes. Although she denied a history of diabetes, elevated blood glucose was noted after admission, and diabetes was diagnosed. Laboratory examination revealed elevated lactate acid and creatine kinase levels in blood. Cranial computed tomography (CT) image demonstrated basal ganglia calcification, as well as subtle decreased attenuation in bilateral symmetric occipital and internal temporal cortices. Brain magnetic resonance imaging (MRI) demonstrated symmetric gyriform hyperintensity in bilateral occipital lobes and internal temporal lobes in both grey and white matter on fluid-attenuated inversion recovery (FLAIR) images with restricted diffusion on diffusion weighted images (DWI). A genetic test revealed a point mutation in the mtDNA(3243A > G) by blood examination. Literature review showed that there were 231 eligible patients with MELAS identified from 212 published papers. Symmetric cortical involvements were seen in 15 (6.5%) patients on brain MRI. MELAS should be considered as a potential diagnosis in the patients with bilateral symmetric stroke-like cortices lesions.

Adult-Onset EIF2B-Pathies: A Clinical, Imaging and Genetic Profiling with Literature Review.

Vanishing white matter syndrome is one of the leukoencephalopathies caused by recessive mutations in gene EIF2B1-5. Adult-onset EIF2B-pathies (clinical onset after age 16 years) have been reported to be less common. Description of the clinical, imaging and genetic profile of adult-onset EIF2B-pathies and comparison of Indian cohort with Asian and European cohorts. Report of two cases of adult-onset EIF2B-pathies and a comprehensive review of genetically confirmed adult-onset EIF2B-pathies since 2001 from Indian, Asian and European cohorts. Two patients were females, with median age at presentation of 25.5 years (24-27 years) and onset at 19 years (18-20 years). The median duration of symptoms was 6.5 years (6-7 years). Both had cerebellar ataxia, spasticity, cognitive impairment and bladder involvement. Brain magnetic resonance imaging (MRI) showed leukoencephalopathy with rarefaction in both patients and corpus callosum involvement in one patient. Genetics showed homozygous missense variant in the EIF2B3 gene in both patients. The Indian cohort of seven patients had similar clinical and radiological features and common variants in EIF2B3 (n = 4). The Asian cohort had 24 cases, and the European cohort had 61 cases with similar clinical features, radiological features and common variants in EIF2B5. Adult-onset EIF2B-pathies have a distinct clinical profile of female predominance with cerebellar ataxia, spasticity and cognitive decline as the commonest triad of clinical manifestations and leukoencephalopathy with rarefaction on brain MRI. Variants in EIF2B5 were common in the Asian and European cohorts and EIF2B3 in the Indian cohort.

Simulation study on parameter optimization of transcranial direct current stimulation based on rat brain slices

Transcranial direct current stimulation (tDCS) is an important method for treating mental illnesses and neurodegenerative diseases. This paper reconstructed two ex vivo brain slice models based on rat brain slice staining images and magnetic resonance imaging (MRI) data respectively, and the current densities of hippocampus after cortical tDCS were obtained through finite element calculation. Subsequently, a neuron model was used to calculate the response of rat hippocampal pyramidal neuron under these current densities, and the neuronal responses of the two models under different stimulation parameters were compared. The results show that a minimum stimulation voltage of 17 V can excite hippocampal pyramidal neuron in the model based on brain slice staining images, while 24 V is required in the MRI-based model. The results indicate that the model based on brain slice staining images has advantages in precision and electric field propagation simulation, and its results are closer to real measurements, which can provide guidance for the selection of tDCS parameters and scientific basis for precise stimulation.

Short Sleep Duration and Hypertension: A Double Hit for the Brain.

Short sleep duration has been associated with an increased risk of cognitive impairment and dementia. Short sleep is associated with elevated blood pressure, yet the combined insult of short sleep and hypertension on brain health remains unclear. We assessed whether the association of sleep duration with cognition and vascular brain injury was moderated by hypertensive status. A total of 682 dementia-free participants (mean age, 62±9 years; 53% women) from the Framingham Heart Study completed assessments of cognition, office blood pressure, and self-reported habitual and polysomnography-derived sleep duration; 637 underwent brain magnetic resonance imaging. Linear regressions were performed to assess effect modification by hypertensive status on total sleep time (coded in hours) and cognitive and magnetic resonance imaging outcomes. There was a significant interaction between sleep duration and hypertensive status when predicting executive function/processing speed (Trail Making B-A) and white matter hyperintensities. When results were stratified by hypertensive status, longer sleep duration was associated with better executive functioning/processing speed scores in the hypertensive group (meaning that shorter sleep duration was associated with poorer executive function/processing speed scores) (self-report sleep: β=0.041 [95% CI, 0.012-0.069], P=0.005; polysomnography sleep: β=0.045 [95% CI, 0.002-0.087], P=0.038), but no association was observed for the normotensive group. Similarly, shorter subjective sleep duration was associated with higher white matter hyperintensity burden in the hypertensive group (β=-0.115 [95% CI, -0.227 to -0.004], P=0.042), but not in the normotensive group. In individuals with hypertension, shorter sleep duration was associated with worse cognitive performance and greater brain injury.

Chronic active lesions preferentially localize in watershed territories in multiple sclerosis.

Paramagnetic rim lesions (PRLs) are a biomarker of chronic active lesions (CALs), and an important driver of neurological disability in multiple sclerosis (MS). The reason subtending some acute lesions evolvement into CALs is not known. Here we ask whether a relatively lower oxygen content is linked to CALs. In this prospective cross-sectional study, 64 people with multiple sclerosis (PwMS), clinically isolated syndrome and radiologically isolated syndrome underwent a 7.0 Tesla (7 T) brain magnetic resonance imaging (MRI). The scanning protocol included a T2-w fluid-attenuated inversion recovery (FLAIR), and a single echo gradient echo from which susceptibility-weighted imaging (SWI) was derived. WM lesions were identified on the T2-w-FLAIR whilst PRLs were identified on the SWI sequence. T2-lesions were classified as PRLs and rimless lesions (PRLs-). We registered a universal vascular atlas to each subject's T2-w-FLAIR and classified each T2-lesions according to its location into watershed- (ws), non-watershed- (nws), and mixed-lesion (m). Ws-lesions were defined as lesions that were fully located in a region between the territories of two major arteries. Out of 1,975 T2-lesions, 88 (4.5%) were PRLs. Ws-regions had a higher number (p = 0.005) and proportion (p < 0.001) of PRLs- compared to nws-regions. Ws-PRL- were larger compared to nws-ones (p = 0.009). The number (p = 0.043) and proportion (p < 0.001) of PRLs was higher in ws-regions compared to nws-ones. Ws-PRLs were not significantlylarger than nws-ones (p = 0.195). We propose the novel concept of a link between arterial vascularization and chronic activity in MS by demonstrating a preferential localization of CALs in ws-territories.

Environmental Enrichment and Health Outcomes Among Low-Grade Glioma Brain Tumor Survivors.

BACKGROUND: Brain tumor survivors who received radiotherapy (RT) are at a disproportionately increased risk of accelerated aging and symptom burden. We aim to examine the association between environmental enrichment (EE) and health outcomes among low-grade glioma survivors who received brain RT. METHODS: The study used a cross-sectional cohort design, enrolling participants approximately 5 years from diagnosis. The construct of EE consisted of social network, physical activity, employment status, and financial stability. Berkman-Syme Social Network Index, International Physical Activity Questionnaire, Vocational Index Scale, and a Socioeconomic Questionnaire were used to measure the construct of EE. Health outcome measures included the Montreal Cognitive Assessment, Symbol Digit Modality Test, clinical brain magnetic resonance images (pre-RT, approximately 2-3 years after RT, and approximately 5 years after RT), Karnofsky Performance Status Scale, and the MD Anderson Symptom Inventory Brain Tumor Module. Ordinal logistic regression estimated the association between levels of EE and health outcomes. RESULTS: Thirty-nine participants completed the study and experienced varying levels of EE. The median age was 44 years old, ranging from 26 to 78 years old. Nineteen individuals were diagnosed with oligodendroglioma, and 18 were diagnosed with astrocytoma. Thirteen participants had low EE, 17 had moderate EE, and 9 had high EE. Although not statistically significant, we observed patterns of increasing health outcomes (Montreal Cognitive Assessment, Symbol Digit Modality Test, and Karnofsky Performance Status Scale) related to increasing levels of EE. CONCLUSION: This study is an initial exploration into the role of EE in health outcomes and survivorship programs for persons with glioma. Future research should assess EE before treatment or at the time of diagnosis and be longitudinal to accurately ascertain the association between EE and health outcomes. Comprehensive neuro-oncology survivorship programs structured to facilitate EE may reduce symptom burden, promote neuroplasticity, and improve cognitive and functional outcomes after brain radiation.