Predicting the formation of mixed pattern hemorrhages in ruptured middle cerebral artery aneurysms based on a decision tree model: A multicenter study.

OBJECTIVE: Mixed-pattern hemorrhages (MPH) commonly occur in ruptured middle cerebral artery (MCA) aneurysms and are associated with poor clinical outcomes. This study aimed to predict the formation of MPH in a multicenter database of MCA aneurysms using a decision tree model. METHODS: We retrospectively reviewed patients with ruptured MCA aneurysms between January 2009 and June 2020. The MPH was defined as subarachnoid hemorrhages with intracranial hematomas and/or intraventricular hemorrhages and/or subdural hematomas. Univariate and multivariate logistic regression analyses were used to explore the prediction factors of the formation of MPH. Based on these prediction factors, a decision tree model was developed to predict the formation of MPH. Additional independent datasets were used for external validation. RESULTS: We enrolled 436 patients with ruptured MCA aneurysms detected by computed tomography angiography; 285 patients had MPH (65.4%). A multivariate logistic regression analysis showed that age, aneurysm size, multiple aneurysms, and the presence of a daughter dome were the independent prediction factors of the formation of MPH. The areas under receiver operating characteristic curves of the decision tree model in the training, internal, and external validation cohorts were 0.951, 0.927, and 0.901, respectively. CONCLUSION: Age, aneurysm size, the presence of a daughter dome, and multiple aneurysms were the independent prediction factors of the formation of MPH. The decision tree model is a useful visual triage tool to predict the formation of MPH that could facilitate the management of unruptured aneurysms in routine clinical work.

Machine learning prediction model for the rupture status of middle cerebral artery aneurysm in patients with hypertension: a Chinese multicenter study.

Background: Hypertension is a common comorbidity in patients with unruptured intracranial aneurysms and is closely associated with the rupture of aneurysms. However, only a few studies have focused on the rupture risk of aneurysms comorbid with hypertension. This retrospective study aimed to construct prediction models for the rupture of middle cerebral artery (MCA) aneurysm associated with hypertension using machine learning (ML) algorithms, and the constructed models were externally validated with multicenter datasets. Methods: We included 322 MCA aneurysm patients comorbid with hypertension who were being treated in four hospitals. All participants underwent computed tomography angiography (CTA), and aneurysm morphological features were measured. Clinical characteristics included sex, age, smoking, and hypertension history. Based on the clinical and morphological characteristics, the training datasets (n=277) were used to fit the ML algorithms to construct prediction models, which were externally validated with the testing datasets (n=45). The prediction performances of the models were assessed by receiver operating characteristic (ROC) curves. Results: The areas under the ROC curve (AUCs) of the k-nearest-neighbor (KNN), neural network (NNet), support vector machine (SVM) and logistic regression (LR) models in the training datasets were 0.83 [95% confidence interval (CI): 0.78-0.88], 0.87 (95% CI: 0.82-0.92), 0.91 (95% CI: 0.88-0.95), and 0.83 (95% CI: 0.77-0.88), respectively, and in the testing datasets were 0.74 (95% CI: 0.59-0.89), 0.82 (95% CI: 0.69-0.94), 0.73 (95% CI: 0.58-0.88), and 0.76 (95% CI: 0.61-0.90), respectively. The aspect ratio (AR) was ranked as the most important variable in the ML models except for NNet. Further analysis showed that the AR had good diagnostic performance, with AUC values of 0.75 in the training datasets and 0.77 in the testing datasets. Conclusions: The ML models performed reasonably accurately in predicting MCA aneurysm rupture comorbid with hypertension. AR was demonstrated as the leading predictor for the rupture of MCA aneurysm with hypertension.

The interaction of global small vessel disease burden and Alzheimer's disease pathologies do not change the independent association of amyloid-beta with hippocampal volume: A longitudinal study on mild cognitive impairment subjects.

The purpose of this study was to investigate whether the co-existence of global small vessel disease (SVD) burdens and Alzheimer's disease (AD) pathologies change hippocampal volume (HV) and cognitive function of mild cognitive impairment (MCI) subjects. We obtained MRI images, cerebrospinal fluid biomarkers (Aß1-42 and p-tau), and neuropsychological tests of 310 MCI subjects from ADNI. The global SVD score was assessed. We used linear regression and linear mixing effect to analyze the effects of global SVD burdens, AD pathologies, and their interactions (SVD*AD) on baseline and longitudinal HV and cognition respectively. We used simple mediation effect to analyze the influencing pathways. After adjusting for global SVD and SVD*AD, Aß remained independently correlated with baseline and longitudinal HV (std ß = 0.294, p = .007; std ß = 0.292, p < .001), indicating that global SVD did not affect the correlation between Aß and HV. Global SVD score was correlated with longitudinal but not baseline HV (std ß = 0.470, p = .050), suggesting that global SVD may be more representative of long-term permanent impairment. Global SVD, AD pathologies, and SVD*AD were independently correlated with baseline and longitudinal cognitions, in which the association of Aß (B = 0.005, 95% CI: 0.005; 0.024) and p-tau (B = -0.002, 95% CI: -0.004; -0.000) with cognition were mediated by HV, suggesting that HV is more likely to explain the progression caused by AD pathology than SVD. The co-existence of global SVD and AD pathologies did not affect the individual association of Aß on HV; HV played a more important role in the influence of AD pathology on cognition than in SVD.

A double-blind, randomized, placebo-controlled, single-center clinical trial of jiaotaiwan for the treatment of insomnia symptoms caused by disharmony of the heart and kidney.

Background: Jiaotaiwan (JTW) is a classical tranquillizing prescription in traditional Chinese medicine (TCM) for the treatment of insomnia symptoms caused by disharmony of the heart and kidney (ISDHK). This study aimed to evaluate the effectiveness and safety of JTW for treating ISDHK in a double-blind, randomized, placebo-controlled trial. Methods: From September 2018 to February 2020, 128 participants with ISDHK were included in this single-center clinical trial. All participants were equally and randomly divided into either the JTW group (2-g JTW granules, b.i.d. for 7 days) or placebo group (2-g placebo granules, b.i.d. for 7 days). Pittsburgh Sleep Quality Index (PSQI) scores were set as the primary outcome, and polysomnography (PSG), 1H-magnetic resonance spectroscopy (1H-MRS), blood tests, and Disharmony of Heart and Kidney Scoring System (DHKSS) and clinical global impression (CGI) scores were used as secondary outcomes. Laboratory tests were used to evaluate the safety of JTW. All data were collected at baseline and posttreatment. Results: A total of 106 participants completed this clinical trial. Symptom relief was more apparent in the JTW group than the placebo group (PSQI total score: 9.34 ± 3.578 vs. 10.98 ± 3.073, respectively; p = 0.006). However, no PSG changes were observed between the two groups (p > 0.05). Higher CGI and lower DHKSS scores were observed after JTW treatment. Serum melatonin was increased in patients with ISDHK after JTW treatment (JTW, 339.09 ± 256.894 vs. placebo, 219.59 ± 169.045; p = 0.004). There were significant posttreatment differences in metabolites in the left cerebellum between the two groups (myoinositol: JTW, 13.47 ± 2.094 vs. placebo, 12.48 ± 2.449; p = 0.021; choline: JTW, 3.96 ± 0.657 vs. placebo, 3.65 ± 0.562; p = 0.008). In terms of safety, JTW had no noticeable adverse effects relative to placebo. Conclusion: JTW was effective and well tolerated for the treatment of ISDHK. The development of large-scale trials with longer follow-up durations is recommended to provide further evidence. Clinical Trial Registration: clinicaltrials.gov, identifier ChiCTR1800019239.

Predicting the rupture status of small middle cerebral artery aneurysms using random forest modeling.

Objective: Small intracranial aneurysms are increasingly being detected; however, a prediction model for their rupture is rare. Random forest modeling was used to predict the rupture status of small middle cerebral artery (MCA) aneurysms with morphological features. Methods: From January 2009 to June 2020, we retrospectively reviewed patients with small MCA aneurysms (<7 mm). The aneurysms were randomly split into training (70%) and internal validation (30%) cohorts. Additional independent datasets were used for the external validation of 78 small MCA aneurysms from another four hospitals. Aneurysm morphology was determined using computed tomography angiography (CTA). Prediction models were developed using the random forest and multivariate logistic regression. Results: A total of 426 consecutive patients with 454 small MCA aneurysms (<7 mm) were included. A multivariate logistic regression analysis showed that size ratio (SR), aspect ratio (AR), and daughter dome were associated with aneurysm rupture, whereas aneurysm angle and multiplicity were inversely associated with aneurysm rupture. The areas under the receiver operating characteristic (ROC) curves (AUCs) of random forest models using the five independent risk factors in the training, internal validation, and external validation cohorts were 0.922, 0.889, and 0.92, respectively. The random forest model outperformed the logistic regression model (p = 0.048). A nomogram was developed to assess the rupture of small MCA aneurysms. Conclusion: Random forest modeling is a good tool for evaluating the rupture status of small MCA aneurysms and may be considered for the management of small aneurysms.

White matter alterations in heart-kidney imbalance insomnia and Jiao-Tai-Wan treatment: A diffusion-tensor imaging study.

Previous studies have reported changes in white matter microstructures in patients with insomnia. However, few neuroimaging studies have focused specifically on white matter tracts in insomnia patients after having received treatment. In this prospective study, diffusion-tensor imaging was used in two samples of heart-kidney imbalance insomnia patients who were treated with placebo or Jiao-Tai-Wan, a traditional Chinese medicine commonly used to treat heart-kidney imbalance insomnia, to assess the changes in white matter tracts. Tract-based spatial statistical analyses were first applied to compare the changes in mean diffusivity and fractional anisotropy of white matter between 75 heart-kidney imbalance insomnia patients and 41 healthy control participants. In subsequent randomized, double-blind, placebo-controlled trials, comparisons of mean diffusivity and fractional anisotropy were also performed in 24 heart-kidney imbalance insomnia patients (8 males; 16 females; 42.5 ± 10.4 years) with Jiao-Tai-Wan and 26 heart-kidney imbalance insomnia patients (11 males; 15 females; 39.7 ± 9.4 years) with a placebo, with age and sex as covariates. Fractional anisotropy values in left corticospinal tract were increased in heart-kidney imbalance insomnia patients. Heart-kidney imbalance insomnia patients showed lower mean diffusivity and fractional anisotropy values of several white matter tracts than healthy control participants, such as the bilateral anterior limb of internal capsule, bilateral superior longitudinal fasciculus and bilateral posterior corona radiata. After being treated with Jiao-Tai-Wan, heart-kidney imbalance insomnia patients showed a trend towards reduced fractional anisotropy values in the left corticospinal tract. Jiao-Tai-Wan may improve the sleep quality by reversing the structural changes of the left corticospinal tract caused by heart-kidney imbalance insomnia.

Intravoxel incoherent motion diffusion-weighted imaging in the characterization of Alzheimer's disease.

OBJECTIVES: Alzheimer's disease (AD) is the most common type of dementia, and characterizing brain changes in AD is important for clinical diagnosis and prognosis. This study was designed to evaluate the classification performance of intravoxel incoherent motion (IVIM) diffusion-weighted imaging in differentiating between AD patients and normal control (NC) subjects and to explore its potential effectiveness as a neuroimaging biomarker. METHODS: Thirty-one patients with probable AD and twenty NC subjects were included in the prospective study. IVIM data were subjected to postprocessing, and parameters including the apparent diffusion coefficient (ADC), slow diffusion coefficient (Ds), fast diffusion coefficient (Df), perfusion fraction (fp) and Df*fp were calculated. The classification model was developed and confirmed with cross-validation (group A/B) using Support Vector Machine (SVM). Correlations between IVIM parameters and Mini-Mental State Examination (MMSE) scores in AD patients were investigated using partial correlation analysis. RESULTS: Diffusion MRI revealed significant region-specific differences that aided in differentiating AD patients from controls. Among the analyzed regions and parameters, the Df of the right precuneus (PreR) (ρ = 0.515; P = 0.006) and the left cerebellum (CL) (ρ = 0.429; P = 0.026) demonstrated significant associations with the cognitive function of AD patients. An area under the receiver operating characteristics curve (AUC) of 0.84 (95% CI: 0.66, 0.99) was calculated for the validation in dataset B after the prediction model was trained on dataset A. When the datasets were reversed, an AUC of 0.90 (95% CI: 0.75, 1.00) was calculated for the validation in dataset A, after the prediction model trained in dataset B. CONCLUSION: IVIM imaging is a promising method for the classification of AD and NC subjects, and IVIM parameters of precuneus and cerebellum might be effective biomarker for the diagnosis of AD.

Classifying Ruptured Middle Cerebral Artery Aneurysms With a Machine Learning Based, Radiomics-Morphological Model: A Multicentral Study.

OBJECTIVE: Radiomics and morphological features were associated with aneurysms rupture. However, the multicentral study of their predictive power for specific-located aneurysms rupture is rare. We aimed to determine robust radiomics features related to middle cerebral artery (MCA) aneurysms rupture and evaluate the additional value of combining morphological and radiomics features in the classification of ruptured MCA aneurysms. METHODS: A total of 632 patients with 668 MCA aneurysms (423 ruptured aneurysms) from five hospitals were included. Radiomics and morphological features of aneurysms were extracted on computed tomography angiography images. The model was developed using a training dataset (407 patients) and validated with the internal (152 patients) and external validation (73 patients) datasets. The support vector machine method was applied for model construction. Optimal radiomics, morphological, and clinical features were used to develop the radiomics model (R-model), morphological model (M-model), radiomics-morphological model (RM-model), clinical-morphological model (CM-model), and clinical-radiomics-morphological model (CRM-model), respectively. A comprehensive nomogram integrating clinical, morphological, and radiomics predictors was generated. RESULTS: We found seven radiomics features and four morphological predictors of MCA aneurysms rupture. The R-model obtained an area under the receiver operating curve (AUC) of 0.822 (95% CI, 0.776, 0.867), 0.817 (95% CI, 0.744, 0.890), and 0.691 (95% CI, 0.567, 0.816) in the training, temporal validation, and external validation datasets, respectively. The RM-model showed an AUC of 0.848 (95% CI, 0.810, 0.885), 0.865 (95% CI, 0.807, 0.924), and 0.721 (95% CI, 0.601, 0.841) in the three datasets. The CRM-model obtained an AUC of 0.856 (95% CI, 0.820, 0.892), 0.882 (95% CI, 0.828, 0.936), and 0.738 (95% CI, 0.618, 0.857) in the three datasets. The CRM-model and RM-model outperformed the CM-model and M-model in the internal datasets (p < 0.05), respectively. But these differences were not statistically significant in the external dataset. Decision curve analysis indicated that the CRM-model obtained the highest net benefit for most of the threshold probabilities. CONCLUSION: Robust radiomics features were determined related to MCA aneurysm rupture. The RM-model exhibited good ability in classifying ruptured MCA aneurysms. Integrating radiomics features into conventional models might provide additional value in ruptured MCA aneurysms classification.

Radiomics in Stroke Neuroimaging: Techniques, Applications, and Challenges.

Stroke is a leading cause of disability and mortality worldwide, resulting in substantial economic costs for post-stroke care each year. Neuroimaging, such as cranial computed tomography or magnetic resonance imaging, is the backbone of stroke management strategies, which can guide treatment decision-making (thrombolysis or hemostasis) at an early stage. With advances in computational technologies, particularly in machine learning, visual image information can now be converted into numerous quantitative features in an objective, repeatable, and high-throughput manner, in a process known as radiomics. Radiomics is mainly used in the field of oncology, which remains an area of active research. Over the past few years, investigators have attempted to apply radiomics to stroke in the hope of gaining benefits similar to those obtained in cancer management, i.e., in promoting the development of personalized precision medicine. Currently, radiomic analysis has shown promise for a variety of applications in stroke, including the diagnosis of stroke lesions, early prediction of outcomes, and evaluation for long-term prognosis. In this article, we elaborate the contributions of radiomics to stroke, as well as the subprocesses and techniques involved in radiomics studies. We also discuss the potential challenges facing its widespread implementation in routine practice and the directions for future research.

Maternal High-Fat Diet Alters the Characteristics of Astrocytes and Worsens the Outcome of Stroke in Rat Offspring, Which Improves After FGF21 Administration.

Background: Maternal high-fat diet (MHFD) has been shown to increase susceptibility to neurological disease in later offspring, but the underlying mechanism is not clear. Fibroblast growth factor 21 (FGF21) has been reported to have a neuroprotective effect in stroke, but its mechanism of action remains unknown. In this study, we investigated the mechanism of the effect of MHFD on stroke in offspring in adulthood and the mechanism by which FGF21 acts on stroke and restores neurological function. Methods: We performed transcriptome sequencing analysis on D21 neonatal rats. Bodyweight and blood indicators were recorded in the adult rats after MHFD. FGF21 was administered 7 h after photochemical modeling twice a day for three consecutive days. Results: We found numerous mRNA changes between the MHFD group and a normal maternal normal diet (MND) group at D21, including genes related to astrocyte and PI3K/Akt pathways. The body weight, blood glucose, and triglycerides of the MHFD offspring were higher, ischemic lesions were larger, the number of activated astrocytes was lower, and the neurological function score was worse than that of the MND group. After FGF21 administration, WB and qPCR analyses showed that astrocytes and the PI3K/Akt pathway were upregulated, while NF-κB and inflammatory cytokines expression were inhibited in stroke and peri-stroke regions. Conclusion: Taken together, we conclude that MHFD alters the characteristics of astrocytes and other transcriptome changes in their offspring, leading to a worse prognosis of stroke, while FGF21 plays a neuroprotective role by inhibiting NF-κB and inflammatory factors and activating the PI3K/Akt pathway and activating more astrocytes in the MND group than the MHFD group.

Prediction of Clinical Outcome at Discharge After Rupture of Anterior Communicating Artery Aneurysm Using the Random Forest Technique.

Background: Aneurysmal subarachnoid hemorrhage (SAH) is a devastating disease. Anterior communicating artery (ACoA) aneurysm is the most frequent location of intracranial aneurysms. The purpose of this study is to predict the clinical outcome at discharge after rupture of ACoA aneurysms using the random forest machine learning technique. Methods: A total of 607 patients with ruptured ACoA aneurysms were included in this study between December 2007 and January 2016. In addition to basic clinical variables, 12 aneurysm morphologic parameters were evaluated. A multivariate logistic regression analysis was performed to determine the independent predictors of poor outcome. Of the 607 patients, 485 patients were randomly selected for training and the remaining for internal testing. The random forest model was developed using the training data set. An additional 202 patients from February 2016 to December 2017 were collected for externally validating the model. The prediction performance of the random forest model was compared with two radiologists. Results: Patients' age (odds ratio [OR] = 1.04), ventilated breathing status (OR = 4.23), World Federation of Neurosurgical Societies (WFNS) grade (OR = 2.13), and Fisher grade (OR = 1.50) are significantly associated with poor outcome. None of the investigated morphological parameters of ACoA aneurysm is an independent predictor of poor outcome. The developed random forest model achieves sensitivities of 78.3% for internal test and 73.8% for external test. The areas under receiver operating characteristic (ROC) curve of the random forest model were 0.90 for the internal test and 0.84 for the external test. Both sensitivities and areas under ROC curves of our model are superior to those of two raters in both internal and external tests. Conclusions: The random forest model presents good performance in predicting the outcome after rupture of ACoA aneurysms, which may aid in clinical decision making.

NMR-based metabolomics characterizes metabolic changes in different brain regions of streptozotocin-induced diabetic mice with cognitive decline.

Diabetes at advanced age increases rise of cognitive impairment, but its potential mechanisms are still far from being fully understood. In this study, we analyzed the metabolic alterations in six different brain regions between streptozotocin (STZ)-induced diabetic mice with cognitive decline (DM) and age-matched controls (CON) using a 1H NMR-based metabolomics approach, to explore potential metabolic mechanisms underlying diabetes-induced cognitive decline. The results show that DM mice had a peculiar metabolic phenotype in all brain regions, mainly involving increased lactate level, decreased choline and energy metabolism as well as disrupted astrocyte-neuron metabolism. Furthermore, these metabolic changes exhibited a brain region-specific pattern. Collectively, our results suggest that brain region-specific metabolic disorders may be responsible for diabetes-induced cognitive dysfunction.

Jiao-tai-wan for insomnia symptoms caused by the disharmony of the heart and kidney: a study protocol for a randomized, double-blind, placebo-controlled trial.

BACKGROUND: Insomnia seriously affects people's normal lives and work. However, effective treatment strategies are scarce. The purpose of this study is to explore the efficacy and safety of Jiao-tai-wan (JTW) for ameliorating insomnia symptoms caused by disharmony of the heart and kidney. DESIGN: This is a randomized, double-blind, placebo-controlled pilot clinical trial. A total of 124 participants suffering from insomnia symptoms will be randomly assigned to the JTW or placebo group in an equal ratio. The participants will be asked to take JTW or placebo granules twice a day for 1 week. All data will be gathered at baseline and at the end of the drug intervention. The primary outcome measures will be the mean change in the Pittsburgh Sleep Quality Index (PSQI) from baseline to the end of the drug intervention. Secondary outcome measures will include the altered sleep parameters in polysomnography, 1H-magnetic resonance spectroscopy (1H-MRS) evaluation, the Disharmony of Heart and Kidney Scoring System score, and blood tests, including the levels of serum adenosine and melatonin. A laboratory test will be taken before and after treatment to assess the safety of JTW. DISCUSSION: The outcomes of this study will confirm the efficacy of JTW for the treatment of insomnia symptoms and will also be used to monitor the safety of JTW. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR1800019239. Registered on 1st November 2018.

Neurochemical changes in unilateral cerebral hemisphere during the subacute stage of focal cerebral ischemia-reperfusion in rats: An ex vivo 1H magnetic resonance spectroscopy study.

Understanding the subacute may shed light on the mechanism of cerebral ischemia. The present study aimed to explore metabolic features underlying subacute stage of ischemia-reperfusion injury and developing effective treatments. Rats were divided into three groups: the permanent middle cerebral artery occlusion (pMCAO), transient cerebral focal ischemia (tMCAO) and sham group. Evaluation of animal models was performed by the neurological deficit, MR images and pathological morphological abnormality. To elucidate metabolic changes, we conducted a comparative analysis of metabolic composition of unilateral brain tissue using 1H nuclear magnetic resonance spectroscopy. The successful model was observed low signal on T1WI and high signal on T2WI lesions in the left cerebral. Histopathological results confirmed the formation of apparent lesions in the left striatum, hippocampus CA1 and cortex tissues of subacute cerebral ischemia rats and showed that rats with focal cerebral ischemia-reperfusion could alleviate the extent of pathological damage degree. In pMCAO rats 7 days after surgery, decreased levels of N-acetyl aspartate (NAA), γ-aminobutyric acid (GABA), glutamate (Glu) and succinate (Suc) concomitantly with increased levels of glutamine (Gln), myo-inositol (m-Ins) and lactate (Lac) were observed compared to the control. Whereas, increased level of Lac with decreased levels of NAA, GABA, Glu, Suc, creatine (Cre) were observed in the tMCAO rats. This demonstrated that experimental subacute ischemic stroke in rats caused extensive perturbation in energy metabolism, the tricarboxylic acid cycle and GABA shunt, which provided essential information for understanding the pathogenesis of subacute cerebral ischemia-reperfusion and provided guidance in choosing the suitable therapeutic schedule.

Metabolic alterations in the rat cerebellum following acute middle cerebral artery occlusion, as determined by 1H NMR spectroscopy.

Supratentorial focal ischemia may reduce cerebral blood volume and cerebellar glucose metabolic rate contralateral to the region of ischemia. The present study investigated the effects of middle cerebral artery occlusion (MCAO) on cerebral metabolism in the ischemic cerebral hemisphere and the non­ischemic cerebellum in rats 1, 3, 9 and 24 h following ischemia using ex vivo proton nuclear magnetic resonance (1H NMR) spectroscopy. The results demonstrated that focal ischemia induced increases in the levels of lactate and alanine, and a decrease in succinate, as early as 1 h following ischemia in the left cerebral hemisphere and the right cerebellum. A continuous increase in lactate levels and decrease in creatine levels were detected in both cerebral areas 3 and 24 h post­MCAO. The most obvious difference between the two cerebral areas was that there was no statistically significant difference in N­acetyl aspartate (NAA) levels in the right cerebellum at all time points; however, the amino acid levels of NAA in the left cerebral hemisphere were markedly decreased 3, 9 and 24 h post­MCAO. In addition, an obvious increase in glutamine was observed in the right and left cerebellum at 3, 9 and 24 h post­MCAO. Furthermore, the present study demonstrated that γ­aminobutyric acid levels were decreased at 1 h in the left and right cerebellum and were evidently increased at 24 h in the right cerebellum post­MCAO. In conclusion, supratentorial ischemia has been indicated to affect the activities of the non­ischemic contralateral cerebellum. Therefore, these results suggested that an NMR­based metabonomic approach may be used as a potential means to elucidate cerebral and cerebellar metabolism following MCAO, which may help improve understanding regarding cerebral infarction at a molecular level. Ex vivo 1H NMR analysis may be useful for the assessment of clinical biopsies.

Metabolite changes in the ipsilateral and contralateral cerebral hemispheres in rats with middle cerebral artery occlusion.

Cerebral ischemia not only causes pathological changes in the ischemic areas but also induces a series of secondary changes in more distal brain regions (such as the contralateral cerebral hemisphere). The impact of supratentorial lesions, which are the most common type of lesion, on the contralateral cerebellum has been studied in patients by positron emission tomography, single photon emission computed tomography, magnetic resonance imaging and diffusion tensor imaging. In the present study, we investigated metabolite changes in the contralateral cerebral hemisphere after supratentorial unilateral ischemia using nuclear magnetic resonance spectroscopy-based metabonomics. The permanent middle cerebral artery occlusion model of ischemic stroke was established in rats. Rats were randomly divided into the middle cerebral artery occlusion 1-, 3-, 9- and 24-hour groups and the sham group. 1H nuclear magnetic resonance spectroscopy was used to detect metabolites in the left and right cerebral hemispheres. Compared with the sham group, the concentrations of lactate, alanine, γ-aminobutyric acid, choline and glycine in the ischemic cerebral hemisphere were increased in the acute stage, while the concentrations of N-acetyl aspartate, creatinine, glutamate and aspartate were decreased. This demonstrates that there is an upregulation of anaerobic glycolysis (shown by the increase in lactate), a perturbation of choline metabolism (suggested by the increase in choline), neuronal cell damage (shown by the decrease in N-acetyl aspartate) and neurotransmitter imbalance (evidenced by the increase in γ-aminobutyric acid and glycine and by the decrease in glutamate and aspartate) in the acute stage of cerebral ischemia. In the contralateral hemisphere, the concentrations of lactate, alanine, glycine, choline and aspartate were increased, while the concentrations of γ-aminobutyric acid, glutamate and creatinine were decreased. This suggests that there is a difference in the metabolite changes induced by ischemic injury in the contralateral and ipsilateral cerebral hemispheres. Our findings demonstrate the presence of characteristic changes in metabolites in the contralateral hemisphere and suggest that they are most likely caused by metabolic changes in the ischemic hemisphere.

Larger size ratio associated with the rupture of very small (≤3†mm) anterior communicating artery aneurysms.

BACKGROUND: Anterior communicating artery (AcoA) aneurysms have a high rupture risk, and ruptured AcoA aneurysms tend to be smaller than other intracranial aneurysms. We aimed to determine the incidence and morphologic predictors of aneurysm rupture of very small AcoA aneurysms. METHODS: We conducted a retrospective analysis of 519 consecutive patients with single AcoA aneurysms between December 2007 and February 2015 in our hospital. Aneurysm morphologies were re-measured using CT angiography images. Very small aneurysms were defined as those with a maximum size ≤3 mm, and small aneurysms were defined as those with a maximum size ≤5 mm. Multivariate regression analyses were used to determine the association between aneurysm morphology and aneurysm rupture status. RESULTS: Of the 474 ruptured AcoA aneurysms, 134 (28.3%) aneurysms were very small and 278 (58.6%) aneurysms were small. In the univariate analysis for very small aneurysms, larger aneurysm size (p=0.037), larger size ratio (p=0.002), higher aneurysm height (p=0.038), smaller vessel size (p=0.012), and dominant A1 segment configuration (p=0.011) were associated with aneurysm rupture. Multivariate analysis revealed that a larger size ratio was independently associated with the rupture status of the very small aneurysms (OR 3.69, 95% CI 1.5 to 9.0; p=0.004), and larger aneurysm size, larger size ratio, and dominant A1 segment configuration were associated with the rupture of small aneurysms. CONCLUSIONS: About one-third of ruptured AcoA aneurysms were very small. A larger size ratio, rather than other aneurysm morphologies, was independently associated with the rupture of very small AcoA aneurysms.

Predicting intraprocedural rupture and thrombus formation during coiling of ruptured anterior communicating artery aneurysms.

BACKGROUND: Intraprocedural rupture and thrombus formation are serious complications during coiling of ruptured intracranial aneurysms, and they more often occur in patients with anterior communicating artery (ACoA) aneurysms. OBJECTIVE: To identify independent predictors of intraprocedural rupture and thrombus formation during coiling of ruptured ACoA aneurysms. METHODS: Between January 2008 and February 2015, 254 consecutive patients with 255 ACoA aneurysms were treated with coiling. We retrospectively reviewed intraoperative angiograms and medical records to identify intraprocedural rupture and thrombus formation, and re-measured aneurysm morphologies using CT angiography images. Multivariate logistic regression models were used to determine independent predictors of intraprocedural rupture and thrombus formation. RESULTS: Of the 231 patients included, intraprocedural rupture occurred in 10 (4.3%) patients, and thrombus formation occurred in 15 (6.5%) patients. Patients with smaller aneurysms more often experienced intraprocedural rupture than those with larger aneurysms (3.5±1.3 mm vs 5.7±2.3 mm). Multivariate analysis showed that smaller ruptured aneurysms (p=0.003) were independently associated with intraprocedural rupture. The threshold of aneurysm size separating rupture and non-rupture groups was 3.5 mm. Multivariate analysis showed that a history of hypertension (p=0.033), aneurysm neck size (p=0.004), and parent vessel angle (p=0.023) were independent predictors of thrombus formation. The threshold of parent vessel angle separating thrombus and non-thrombus groups was 60.0°. CONCLUSIONS: Ruptured aneurysms <3.5 mm were associated with an increased risk of intraprocedural rupture, and parent vessel angle <60.0°, wider-neck aneurysms, and a history of hypertension were associated with increased risk of thrombus formation during coiling of ruptured ACoA aneurysms.

Smoking Associated with Increased Aneurysm Size in Patients with Anterior Communicating Artery Aneurysms.

BACKGROUND: Hypertension and smoking are risk factors for aneurysm formation or rupture. We aimed to identify differences in aneurysm morphologies associated with hypertension or smoking in patients with anterior communicating artery (AcoA) aneurysms. METHODS: Between December 2007 and February 2015, 574 consecutive patients with AcoA aneurysms were identified from the Electronic Medical Record System. We extracted data on histories of hypertension alone, smoking alone, nonhypertension and nonsmoking, and both hypertension and smoking. The morphologic parameters of aneurysms were remeasured via computed tomography angiography image reconstruction. Multivariate logistic regression analyses were used to determine the differences in morphologies in patients with hypertension or who smoked. RESULTS: In the study, 495 patients with single AcoA aneurysm were included. Age, sex, vessel size, aneurysm size and height, size ratio, A1 segment configuration, and aneurysm shape were significantly different among the groups. A larger aneurysm occurred more often in patients who only smoked compared with those without hypertension who did not smoke (adjusted odds ratio, 1.19; 95% confidence interval, 1.04-1.36; P = 0.012). Patients with hypertension who also smoked more commonly had a larger aneurysm size than those with hypertension alone (adjusted odds ratio, 0.89; 95% confidence interval, 0.79-0.99; P = 0.040). There were significant differences in age, sex, and aneurysm morphology between the smoking patients and those with hypertension alone. CONCLUSIONS: Aneurysm size was an independent morphologic parameter associated with smoking in patients with ACoA aneurysms compared with other aneurysm morphologies. Smoking may be associated independently with increased aneurysm size and should be given up in patients with AcoA aneurysms.

Whole-brain 320-detector row dynamic volume CT perfusion detected crossed cerebellar diaschisis after spontaneous intracerebral hemorrhage.

INTRODUCTION: The purpose of this study was to evaluate the value of 320-detector row CT used to detect crossed cerebellar diaschisis (CCD) in patients with unilateral supratentorial spontaneous intracerebral hemorrhage (SICH). METHODS: We investigated 62 of 156 patients with unilateral supratentorial SICH using 320-detector row CT scanning. Regional cerebral blood flow (rCBF), cerebral blood volume (rCBV), mean transit time (rMTT), and time to peak (rTTP) levels were measured in different regions of interest (ROIs) that were manually outlined on computed tomography perfusion (CTP) for the cerebrum, including normal-appearing brain tissue that surrounded the perilesional low-density area (NA) and the perihematomal low-density area (PA) in all patients and the cerebellum (ipsilateral and contralateral) in CCD-positive patients. RESULTS: Of 62 cases, a total of 14 met the criteria for CCD due to cerebellar perfusion asymmetry on CTP maps. In the quantitative analysis, significant differences were found in the perfusion parameters between the contralateral and ipsilateral cerebellum in CCD-positive cases. No significant differences were found between the CCD-positive group and the CCD-negative group according to the hematoma volume, NIHSS scores, and cerebral perfusion abnormality (each P > 0.05). The correlation analysis of the degree of NA, PA perfusion abnormality, and the degree of CCD severity showed negative and significant linear correlations (R, -0.66∼-0.56; P < 0.05). CONCLUSION: 320-detector row CT is a robust and practicable method for the comprehensive primary imaging work-up of CCD in unilateral supratentorial SICH patients.