Abstract Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global health burden with limited therapeutic options. Cinnamomum cassia, a medicinal-food homologous plant, contains principal bioactive cinnamaldehyde (CA), whose anti-MASLD mechanisms require clarification. ‌This study employed both a high-fat diet (HFD)-induced MASLD model and a free fatty acid (FFA)-stimulated cell model. CA administration attenuated intracellular lipid accumulation in vitro and ameliorated both hepatic steatosis and systemic hyperlipidemia in vivo, while inhibiting hepatic lipid peroxidation. Mechanistically, integrated RNA-seq, network pharmacology, siRNA, immunofluorescence, and transmission electron microscopy analyses identified the SIRT1/FOXO1–autophagy axis as CA’s key regulatory pathway. Gut microbiome profiling revealed CA’s capacity to ameliorate HFD-induced dysbiosis, particularly enriching Lachnospiraceae_NK4A136. Fecal microbiota transplantation (FMT) and Spearman correlations link serum lipids and hepatic injury factors to gut microbiota, indicating partially microbiota-mediated metabolic modulation by CA. Collectively, CA ameliorates MASLD through coordinated autophagy enhancement and microbial homeostasis restoration, holding promise as a functional food ingredient for ‌metabolic liver disease prevention.

Objectives Postoperative brain injury in congenital heart disease (CHD) impairs neurodevelopment. We aimed to identify risk factors for postoperative brain injury in infants and young children with CHD and explore age- and cyanosis-related patterns. Methods Infants and young children undergoing open-heart surgery with pre- and postoperative brain magnetic resonance imaging (MRI) were retrospectively enrolled. Postoperative new brain injury (intracranial hemorrhage, white matter injury, stroke, venous thrombosis) was assessed. Demographic, intraoperative, intensive care, hematological, and echocardiographic data were collected. Participants were classified according to the presence or absence of new postoperative brain injury. Differences between groups were assessed using independent t test, Mann-Whitney U, and chi-square testing, as appropriate. Multivariable logistic regression (exclusion criteria p>0.1) was used to identify risk factors for new postoperative brain injury, supplemented by stratification analyses based on age categories and cyanotic status. Results Among 172 infants and young children (35.5% with new brain injury), independent risk factors included older age (OR=1.049), longer cardiopulmonary bypass time (CPB, OR=1.029), smaller main pulmonary artery diameter (OR=0.800), lower postoperative mean corpuscular hemoglobin concentration (MCHC, OR=0.779), and lower platelet count (OR=0.993). Stratified analyses revealed age-cyanosis interactions: in non-cyanotic children ≤365 days, younger age, lower platelets and MCHC increased risk; in non-cyanotic children >365 days, prolonged CPB was dominant; cyanotic subgroups showed borderline age and sex effects. Conclusions Postoperative brain injury risk in children with CHD follows age-dependent and cyanosis-stratified patterns. Modifiable predictors include CPB duration and perioperative hematological parameters, enabling tailored neuroprotective strategies.

Background: Cardiovascular disease (CVD) remains the leading cause of global mortality, necessitating a largescale bioimaging database to advance personalized precision medicine strategies. Objectives: The Dongzong Cardiovascular Bio-imaging Registry (DAILY) study was designed to establish a largescale Chinese cardiovascular bioimaging database (NCT06894095). It aims to address ethnic disparities in genetics and imaging, and to elucidate crucial driving mechanisms and effects of genetic biology and exposure factors on imaging-derived intermediate phenotypes and CVD. Methods: This prospective, multicenter study plans to enroll 50,000 adults from six medical centers across China. It employs a comprehensive data framework, systematically collecting information on exposure factors, highthroughput multiomics (blood and saliva samples), and cardiopulmonary computed tomography (CT) imaging (chest CT, cardiac CT) for cardiac, coronary and pulmonary phenotypes assessment. The primary outcome is a composite major adverse cardiovascular event, including all-cause death, nonfatal myocardial infarction, and nonfatal stroke. Results: To September 10, 2025, the study has recruited 8699 participants in Nanjing, China. Standardized biospecimen collection was performed, obtaining blood samples from 8632 participants and saliva specimens from 8621 individuals, and cardiopulmonary CT scans have been completed in 8699 participants. The cohort maintains a 1-year follow-up rate of 98.9%. Conclusions: The DAILY study will deepen our understanding of ethnic disparities in CVD, help elucidate the effects of genetic and exposure factors on cardiopulmonary intermediate phenotypes, and decipher the pathophysiological mechanisms underlying CVD.

Background: Neurodevelopmental deficits is a common complication in congenital heart disease (CHD). However, the effect of cardiac surgery on brain structure and neurodevelopment remains unclear.PurposeTo quantify perioperative cortical alterations in infants with CHD and evaluate their associations with clinical factors and neurodevelopment.Materials and Methods: In this longitudinal study, infants with CHD underwent brain MRI and neurodevelopmental assessment before and after cardiac surgery, with neurodevelopmental testing at 6 months. Cortical volume (CV), cortical thickness (CT), and cortical surface area (CSA) were quantified using automated cortical parcellation. Linear mixed effects models assessed perioperative cortical changes, and surgery × disease severity interaction analysis were performed to investigate the effect of severity on perioperative cortical changes. Associations between cortical alterations, perioperative variables, and neurodevelopmental scores were evaluated using generalized linear models and mediation analyses. Exploratory elastic net regression was further used to predict 6-month neurodevelopmental outcomes. Results: The study included 106 infants with CHD. Compared with preoperative condition, postoperative CHD exhibited widely reduced CV, CT and CSA in multiple brain regions (PFDR < 0.05). There was a significant surgery × disease severity interaction for CT. Postoperative CT reduction in the left inferior parietal lobule was observed in the moderate-severe group but not the mild group. Cortical changes were associated with perioperative variables and language performance (PFDR < 0.05). Additionally, in exploratory analyses integrating perioperative risk factors, the personal social domain showed a modest predictive value (cross-validated R2 = 0.338, Ppermutation = 0.004). Conclusion: Cardiac surgery may be associated with short-term cortical structural alterations in infants with CHD, and these alterations are linked to early neurodevelopmental outcomes. The findings suggest that integrating brain protection strategies into perioperative management may be considered to potentially improve neurodevelopmental performance.

The aim of this study was to characterise the cortical structure in toddlers with congenital heart disease (CHD) of varying severities and to investigate its associations with preoperative laboratory values and neurodevelopmental outcomes. A cohort of 109 toddlers with CHD and 56 healthy controls (HCs) underwent magnetic resonance imaging between August 2021 and December 2023. All toddlers with CHD were assessed using the Gesell Developmental Schedules and stratified into mild, moderate, and severe groups. Generalised linear models were used to compare cortical structural (grey matter volume (GMV) and thickness) differences across CHD severity groups and HCs and to examine their relationships with preoperative laboratory values and neurodevelopmental outcomes. Compared with HCs, toddlers with mild and moderate-to-severe CHD exhibited reduced total brain volume and total GMV. Significant reductions in cortical GMV and thickness were observed in specific brain regions (p < 0.001, family-wise error corrected). Altered cortical structures demonstrated overlapping spatial distributions between the mild and moderate-to-severe CHD groups. In the mild and moderate-to-severe CHD groups, regional alterations were correlated with scores across multiple neurodevelopmental domains (adaptive, gross motor, and fine motor skills), and haemoglobin levels were associated with cortical thickness in the right superior frontal area (β = 0.422; pfwe = 0.021; 95

Objectives: Postoperative brain injury in congenital heart disease (CHD) impairs neurodevelopment. We aimed to identify risk factors for postoperative brain injury in infants with CHD and explore age- and cyanosis-related patterns.Methods: Infants undergoing open-heart surgery with pre- and postoperative brain MRI were retrospectively enrolled. Postoperative new brain injury (intracranial hemorrhage, white matter injury, stroke, venous thrombosis) was assessed. Demographic, intraoperative, intensive care, hematological, and echocardiographic data were collected. According to the postoperative presence of new brain damage is divided into two groups, differences between the two groups were assessed using independent t test, Mann-Whitney U, and χ2 exact. Multivariable logistic regression (exclusion criteria P>0.1) was used to identify risk factors for new postoperative brain injury, supplemented by stratification analyses based on age categories and cyanotic status.Results: Among 172 infants (35.5% with new brain injury), independent risk factors included older age (OR=1.049), longer cardiopulmonary bypass time (CPB, OR=1.029), smaller main pulmonary artery diameter (OR=0.800), lower postoperative mean corpuscular hemoglobin concentration (MCHC, OR=0.779), and lower platelet count (OR=0.993). Stratified analyses revealed age-cyanosis interactions: in non-cyanotic infants ≤365 days, younger age, lower platelets and MCHC increased risk; in non-cyanotic infants >365 days, prolonged CPB was dominant; cyanotic subgroups showed borderline age and sex effects.Conclusions: Postoperative brain injury risk in CHD infants follows age-dependent and cyanosis-stratified patterns. Modifiable predictors include CPB duration and perioperative hematological parameters, enabling tailored neuroprotective strategies.

Heart-brain comorbidities are common and devastating, yet their genetic mechanisms remain unclear. Here, we explored the genetic mechanisms underlying comorbidities between five heart diseases and ten brain disorders. We observed varying degrees of polygenic overlap (dice coefficient: 0.04-0.60) among heart-brain disease pairs, along with 12 positive genetic correlations, 25 colocalizations, and 392 shared loci with consistent effects. Genes shared across different disease pairs were enriched for distinct biological processes; for example, genes shared by coronary artery disease with stroke, Alzheimer's disease, depression, and multiple sclerosis showed enrichment for heart development, lipid metabolism, synapse development, and immune cell differentiation, respectively. We conducted genome-wide association studies for the first time on ten heart-brain comorbidities and identified 51 associations, including 12 attributable to genetic sharing between diseases and six unique to comorbidity. This study improves our understanding of genetic mechanisms underlying heart-brain comorbidities and highlight the value of genome-wide association studies of comorbidity.

Background: Moyamoya angiopathy (MMA) can be potentially missed in the initial magnetic resonance (MR) examination without MR angiography (MRA). The aim of this study was to develop an optimal deep learning model based on T2-weighted imaging (T2WI) for MMA detection. Methods: This retrospective multicenter study included MMA patients, control group patients with normal MRA and patients with cerebrovascular disease except MMA from seven hospitals (site 1 to site 7). Convolutional Network (DenseNet), were used for training and validation. The model training and internal validation were performed with data from sites 1-4. Data from sites 5-7 were used for independent external validation, and the optimal model was selected according to the results of accuracy. Chi-squared test was used to further verify the influence of different MR manufacturers, field strength, age at the MR examination and MRA score on the optimal model. Results: A total of 1,038 MMA patients, 1,211 normal MRA and 271 patients with cerebrovascular disease except MMA were included. DenseNet showed the highest accuracy (0.859, 95% CI: 0.833, 0.884) in the independent external validation, which was not significantly different from that of VGG (0.834, 95% CI: 0.807, 0.861) and ResNet (0.855, 95% CI: 0.829, 0.880) but was significantly higher than that of SCNN (0.631, 95% CI: 0.595, 0.665; P<0.001) and LeNet (0.563, 95% CI: 0.527, 0.599; P=0.001). The accuracy of 1.5 T data was higher than 3.0 T data (chi 2=6.559, P=0.01). The accuracy of MMA with MRA who scored more than 5 was higher than that scoring <= 5 (<= 5 vs. 6-10: chi 2=10.734, P=0.001; <= 5 vs. >= 11: chi 2=10.369, VGG and ResNet. The MRA score of MMA affected the DenseNet accuracy.

ABSTRACT Congenital heart disease (CHD) is the most common congenital anomaly, leading to an increased risk of neurodevelopmental abnormalities in many children with CHD. Understanding the neurological mechanisms behind these neurodevelopmental disorders is crucial for implementing early interventions and treatments. In this study, we recruited 83 infants aged 12–26.5 months with complex CHD, along with 86 healthy controls (HCs). We collected multimodal data to explore the abnormal patterns of cerebral cortex development and explored the complex interactions among blood oxygen‐carrying capacity, cortical development, and gross motor skills. We found that, compared to healthy infants, those with complex CHD exhibit significant reductions in cortical surface area development, particularly in the default mode network. Most of these developmentally abnormal brain regions are significantly correlated with the blood oxygen‐carrying capacity and gross motor skills of infants with CHD. Additionally, we further discovered that the blood oxygen‐carrying capacity of infants with CHD can indirectly predict their gross motor skills through cortical structures, with the left middle temporal area and left inferior temporal area showing the greatest mediation effects. This study identified biomarkers for neurodevelopmental disorders and highlighted blood oxygen‐carrying capacity as an indicator of motor development risk, offering new insights for the clinical management CHD.

This study aimed to utilize aged laying hens as a model to investigate the effects of naringin on the occurrence and progression of metabolic dysfunction-associated fatty liver disease (MAFLD), along with its underlying regulatory mechanisms. A total of 288 aged laying hens, 50-week-old, were divided into four groups: a normal diet (ND) group, and three naringin groups receiving 200 mg/kg (N1), 400 mg/kg (N2), and 600 mg/kg (N3). The experiment lasted for 10 weeks, after which serum, liver, and cecal contents were collected from the hens. Results indicated that dietary naringin supplementation reduced hepatic lipid deposition, lowered blood lipid levels, improved antioxidant capacity, and promoted estradiol secretion. Additionally, 16S rDNA analysis revealed that naringin enhanced microbial diversity in the cecum and regulated the abundance of gut microbes associated with fatty liver. Untargeted metabolomics of blood demonstrated that naringin decreased the concentration of glycerophospholipid and sterol lipid metabolites while increasing levels of pantothenic acids and amino acid metabolites. Furthermore, liver transcriptome analysis indicated that naringin interfered with fatty acid synthesis and transport processes while enhancing fatty acid oxidation. Dietary naringin supplementation can mitigate the occurrence of MAFLD by regulating the gut-liver axis and estrogen signaling, particularly in postmenopausal women.

BACKGROUND AND PURPOSE:Obstructive sleep apnea (OSA) is linked to cognitive impairment and altered motor-related brain networks. This study examined functional connectivity (FC) changes in subregions of the primary motor cortex (M1) in patients with OSA and their association with sleep structure, cognition, and clinical features. METHODS:Sixty-five patients with OSA and 65 healthy controls (HC) participants matched in age and educational background were included. Resting-state functional MRI data were acquired for all participants using a 3T MRI system. Based on the Human Brainnetome Atlas, we analyzed FC changes of 12 subregions of M1 across the whole brain in patients with OSA. The two-sample t-tests were conducted to compare FC values between subregions of M1 and other brain regions in two groups. Partial correlation analyses examined the association between FC and clinical variables in patients with OSA. Additionally, we employed three machine learning algorithms-support vector machine (SVM), random forest (RF), and logistic regression (LR)-to distinguish patients with OSA from HC based on FC features. RESULTS:Compared to HC, the OSA group found that significant FC enhancements were identified in right A6cdl with the left inferior parietal lobule (IPL); left A4tl with the left inferior frontal gyrus (IFG), bilateral middle frontal gyrus (MFG), and left IPL; and left A6cvl with the right parahippocampal gyrus, bilateral MFG, left IFG, left superior temporal gyrus, and right cingulate gyrus. After Bonferroni correction, a negative correlation was observed between the FC value of A4tl (L)-IPL (L) and N2 (p < 0.05). Furthermore, SVM yielded the highest area under the receiver operating characteristic (ROC) curve (AUC) among all classifiers, indicating its superior performance in discriminating OSA patients from HC based on FC features. CONCLUSION:The study demonstrates that OSA significantly impacts brain functional networks, particularly affecting motor control through altered FC in subregions of M1. These alterations correlate with upper airway dysfunction and cognitive impairments, increasing accident risks. The high-accuracy SVM classification based on FC patterns demonstrates potential as a diagnostic biomarker for OSA. Future research should explore M1 FC patterns as diagnostic markers and neuromodulation therapies.

Congenital heart disease is linked to substantial variability in neurodevelopmental outcomes, with sex being a key contributing factor. Compared with females, male congenital heart disease infants often show greater impairments in motor, cognitive, and language development. However, studies on sex differences in early brain development among congenital heart disease patients remain limited. To fill these gaps, this study included 79 infants with complex congenital heart disease (42 males, 37 females) and 87 healthy controls (47 males, 40 females), collecting magnetic resonance imaging data, clinical information, and neurodevelopmental assessments. We examined sex-specific effects on global and regional brain development in congenital heart disease infants aged 1 to 2 yr using imaging and statistical analysis. Male congenital heart disease infants showed global brain volume reduction and regional cortical delays, including increased cortical thickness and gray matter volume. In contrast, female congenital heart disease infants had no significant global volume change but exhibited localized structural abnormalities, such as reduced surface area and increased cortical thickness. Notably, reduced global brain volume in congenital heart disease males was associated with poorer gross motor skills. Distinct sex differences in brain development exist among congenital heart disease infants during early life. Recognizing these differences is critical for developing sex-specific treatment and neuroprotective strategies.

Heart failure (HF) frequently suffers from brain abnormalities and cognitive impairments. This study aims to investigate brain structure and function alteration in patients with chronic HF. This retrospective study included 49 chronic HF and 49 health controls (HCs). Voxel-based morphometry was conducted on structural MRI to quantify gray matter volume (GMV), and functional connectivity (FC) was assessed with seed-based analysis using resting-state fMRI. White matter microstructure integrity was also evaluated through tract-based spatial statistics employing DTI. Correlations between multimodal MRI features and cognitive performance were further investigated in patients with chronic HF. Patients with chronic HF exhibited significantly reduced regional GMV, white matter microstructure injury (Family wise error correction, p＜0.05), and decreased FC in multiple brain regions involved in cognition, sensorimotor, visual function (Gaussian random field correction, voxel level p＜0.0001 and cluster-level p＜0.01). There was no observed increases in GMV or FC compared with HCs. Decreased GMV showed positive correlations with cognitive performance (r = 0.025-0.577, p = 0.025-0.001), while decreased fractional anisotropy was negatively correlated with anxiety scores (r = -0.339, p = 0.040) in patients with chronic HF. This study revealed that patients with chronic HF exhibited brain structure injury affecting gray matter and white matter, as well as FC abnormalities of brain regions responsible for cognition, sensorimotor and visual function. These findings suggest GMV could serve as a neuroimaging biomarker for cognitive impairments and a potential target for neuroprotective therapies in patients with chronic HF.

Background:Despite the improved survival rates of children with tetralogy of Fallot (TOF), various degrees of neurodevelopmental disorders persist. Currently, there is a lack of quantitative and objective imaging markers to assess the neurodevelopment of individuals with TOF. This study aimed to noninvasively examine potential quantitative imaging markers of TOF neurodevelopment by combining radiomics signatures and morphological features and to further clarify the relationship between imaging markers and clinical neurodevelopment metrics. Methods:This study included 33 preschool children who had undergone surgical correction for TOF and 29 healthy controls (36 in the training cohort and 26 in the testing cohort), all of whom underwent three-dimensional T1-weighted high-resolution (T1-3D) head magnetic resonance imaging (MRI). Radiomics features were extracted by Pyradiomics to construct radiomics models, while surface morphometry (surface and volumetric) features were analyzed to build morphometry models. Merged models integrating radiomics and morphometry features were subsequently developed. The optimal discriminative radiomics signatures were identified via least absolute shrinkage and selection operator (LASSO). Machine learning classification models include support vector machine (SVM) with radial basis function (RBF) and multivariable logistic regression (MLR) models, both of which were used to evaluate the potential imaging biomarkers. Performances of models were evaluated based on their calibration and classification metrics. The area under the receiver operating characteristic curves (AUCs) of the models were evaluated using the Delong test. Neurodevelopmental assessments for children with corrected TOF were conducted with the Wechsler Preschool and Primary Scale of Intelligence-Fourth Edition (WPPSI-IV). Furthermore, the correlation of the significant discriminative indicators with clinical metrics and neurodevelopmental scales was evaluated. Results:Twelve discriminative radiomics signatures, optimized for classification, were identified. The performance of the merged model (AUCs of 0.922 and 0.917 for the training set and test set with SVM, respectively) was superior to that of the single radiomics model (AUCs of 0.915 and 0.917 for the training set and test set with SVM, respectively) and that of the single morphometric models (AUCs of 0.803 and 0.756 for the training set and test set with SVM, respectively). The radiomics model demonstrated higher significance than did the morphometric models in training set with SVM (AUC: 0.915 vs. 0.803; P<0.001). Additionally, the significant indicators showed a correlation with clinical indicators and neurodevelopmental scales. Conclusions:MRI-based radiomics features combined with morphometry features can provide complementary information to identify neurodevelopmental abnormalities in children with corrected TOF, which will provide potential evidence for clinical diagnosis and treatment.

BACKGROUND:Cognitive impairment is the most common long-term complication in children with congenital heart disease (CHD) and is closely related to the brain network. However, little is known about the impact of CHD on brain network organization. This study aims to investigate brain structural network properties that may underpin cognitive deficits observed in children with Tetralogy of Fallot (TOF). METHODS:In this prospective study, 29 preschool-aged children diagnosed with TOF and 19 without CHD (non-CHD) were enrolled. Participants underwent diffusion tensor imaging (DTI) scans alongside cognitive assessment using the Chinese version of the Wechsler Preschool and Primary Scale of Intelligence-fourth edition (WPPSI-IV). We constructed a brain structural network based on DTI and applied graph analysis methodology to investigate alterations in diverse network topological properties in TOF compared with non-CHD. Additionally, we explored the correlation between brain network topology and cognitive performance in TOF. RESULTS:Although both TOF and non-CHD exhibited small-world characteristics in their brain networks, children with TOF significantly demonstrated increased characteristic path length and decreased clustering coefficient, global efficiency, and local efficiency compared with non-CHD (p < 0.05). Regionally, reduced nodal betweenness and degree were found in the left cingulate gyrus, and nodal efficiency was decreased in the right precentral gyrus and cingulate gyrus, left inferior frontal gyrus (triangular part), and insula (p < 0.05). Furthermore, a positive correlation was identified between local efficiency and cognitive performance (p < 0.05). CONCLUSION:This study elucidates a disrupted brain structural network characterized by impaired integration and segregation in preschool TOF, correlating with cognitive performance. These findings indicated that the brain structural network may be a promising imaging biomarker and potential target for neurobehavioral interventions aimed at improving brain development and preventing lasting impairments across the lifetime.

BACKGROUND:Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart disease. Children with TOF would be confronted with neurological impairment across their lifetime. Our study aimed to identify the risk factors for cerebral morphology changes and cognition in postoperative preschool-aged children with TOF.METHODS:We used mass spectrometry (MS) technology to assess the levels of serum metabolites, Wechsler preschool and primary scale of intelligence-Fourth edition (WPPSI-IV) index scores to evaluate neurodevelopmental levels and multimodal magnetic resonance imaging (MRI) to detect cortical morphological changes.RESULTS:Multiple linear regression showed that preoperative levels of serum cortisone were positively correlated with the gyrification index of the left inferior parietal gyrus in children with TOF and negatively related to their lower visual spaces index and nonverbal index. Meanwhile, preoperative SpO2 was negatively correlated with levels of serum cortisone after adjusting for all covariates. Furthermore, after intervening levels of cortisone in chronic hypoxic model mice, total brain volumes were reduced at both postnatal (P) 11.5 and P30 days.CONCLUSIONS:Our results suggest that preoperative serum cortisone levels could be used as a biomarker of neurodevelopmental impairment in children with TOF. Our study findings emphasized that preoperative levels of cortisone could influence cerebral development and cognition abilities in children with TOF.

A mounting body of evidences suggests that patients with chronic heart failure (HF) frequently experience cognitive impairments, but the neuroanatomical mechanism underlying these impairments remains elusive. In this retrospective study, 49 chronic HF patients and 49 healthy controls (HCs) underwent brain structural MRI scans and cognitive assessments. Cortical morphology index (cortical thickness, complexity, sulcal depth and gyrification) were evaluated. Correlations between cortical morphology and cognitive scores and clinical variables were explored. Logistic regression analysis was employed to identify risk factors for predicting 3-year major adverse cardiovascular events. Compared with HCs, patients with chronic HF exhibited decreased cognitive scores (p < .001) and decreased cortical thickness, sulcal depth and gyrification in brain regions involved cognition, sensorimotor, autonomic nervous system (family-wise error correction, all p values <.05). Notably, HF duration and New York Heart Association (NYHA) demonstrated negative correlations with abnormal cortex morphology, particularly HF duration and thickness in left precentral gyrus (r = -.387, p = .006). Cortical morphology characteristics exhibited positive associations with global cognition, particularly cortical thickness in left pars opercularis (r = .476, p < .001). NYHA class is an independent risk factor for adverse outcome (p = .001). The observed correlation between abnormal cortical morphology and global cognition suggested that cortical morphology may serve as a promising imaging biomarker and provide insights into neuroanatomical underpinnings of cognitive impairment in patients with chronic HF.

Granulocytic sarcoma (GS) is a soft mass formed by immature myeloid cells invading extramedullary tissues and organs, which is common in myeloid leukemia. In this case, a two years and four months girl diagnosed with acute myeloid leukemia showed intracranial lesion with right occipital bone involvement on Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Follow-up CT showed that the mass had disappeared after chemotherapy. As intracranial GS is difficult to diagnose accurately, early detection and treatment is vital for good prognosis. GS should be part of differential diagnosis when patients with acute myelogenous leukemia showed intracranial soft mass.