Efficacy and safety of duodenal-jejunal bypass liner for obesity and type 2 diabetes: A systematic review and meta-analysis.

This study aimed to evaluate the efficacy and safety of duodenal-jejunal bypass liner (DJBL) for obesity and type 2 diabetes mellitus. A comprehensive search of electronic databases was conducted up to September 15, 2022. Thirty studies involving 1751 patients were included. At 12 months post-implantation, the reduction in body mass index (BMI) was 4.8 kg/m2 (95% CI 4.1, 5.5), with an excess weight loss of 41.3% (95% CI 33.4%,49.2%) and a total weight loss of 13.1% (95% CI 10.1%, 16.0%). Significant decrease was observed in HbA1c and fasting glucose, with a standardized mean difference of - 0.72 (95% CI - 0.95, - 0.48) and - 0.62 (95% CI - 0.82, - 0.42), respectively. However, these improvements in weight loss and glycemic control were only partially sustained after explantation. In situ, DJBL significantly improves blood pressure and lipid levels. The pooled early removal rate was 19%, and the incidence of severe adverse events was 17%, including device migration (6%), gastrointestinal hemorrhage (4%), device obstruction (4%), and hepatic abscess (2%). DJBL offers significant improvement in weight loss and glycemic control, as well as cardiovascular parameters while in situ. Further studies are warranted to better understand the long-term efficacy and safety of DJBL. The benefits of DJBL need to be carefully weighed against the risks in clinical decision-making.

Cerebral involvement in sitosterolemia.

BACKGROUND: Sitosterolemia, an autosomal recessive condition, is characterized by impaired metabolism of plant sterols. Clinical symptoms include skin xanthoma, premature atherosclerotic disease, arthritis, and unexplained hematological abnormalities. However, there is a dearth of studies on sitosterolemia-related brain damage. METHODS: This study focused on the family of two sitosterolemia patients who presented with severe hypercholesterolemia and xanthoma. Radiological examinations, biopsies, whole-exome sequencing (WES), and plant sterol tests were conducted. RESULTS: The index patient, a 66-year-old female, initially exhibited weakness in both lower limbs and later developed urinary and fecal incontinence. Neuroimaging showed that the falx of the brain had irregular fusiform thickening. Significant tissue edema was observed around the lesions in the bilateral frontal-parietal lobes. Pathological analysis of the biopsied brain lesion revealed extensive cholesterol crystal deposition and lymphocyte infiltration in the matrix. The index patient who experienced cerebral impairment and her sister both carried two compound heterozygous variants in ATP binding cassette transporter G5 (ABCG5). These included the nonsense variants NM_022436: c.751 C > T (p.Q251X) in exon 6 and NM_022436: c.1336 C > T (p.R446X) in exon 10. A notable increase in plant sterol levels was observed in the younger sister of the index patient. CONCLUSION: This study highlights a previously unreported neurological aspect of sitosterolemia. Imaging and pathology findings suggest that cholesterol crystals may be deposited in connective tissues such as the cerebral falx and pia mater through blood circulation.

Construction and validation of a nomogram for predicting diabetes remission at 3 months after bariatric surgery in patients with obesity combined with type 2 diabetes mellitus.

AIM: Bariatric metabolic surgery (BMS) is a proven treatment option for patients with both obesity and type 2 diabetes mellitus (T2DM). However, there is a lack of comprehensive reporting on the short-term remission rates of diabetes, and the existing data are inadequate. Hence, this study aimed to investigate the factors that may contribute to diabetes remission (DR) in patients with obesity and T2DM, 3 months after undergoing BMS. Furthermore, our objective was to develop a risk-predicting model using a nomogram. METHODS: In total, 389 patients with obesity and T2DM, who had complete preoperative information and underwent either laparoscopic sleeve gastrectomy or laparoscopic gastric bypass surgery between January 2014 and May 2023, were screened in the Chinese Obesity and Metabolic Surgery Database. The patients were randomly divided into a training set (n = 272) and a validation set (n = 117) in a 7:3 ratio. Potential factors for DR were analysed through univariate and multivariate logistic regression analyses and then modelled using a nomogram. The model's performance was evaluated using receiver operating characteristic curves and the area under the curve (AUC). Calibration plots were used to assess prediction accuracy and decision curve analyses were conducted to evaluate the clinical usefulness of the model. RESULTS: Glycated haemoglobin, triglycerides, duration of diabetes, insulin requirement and hypercholesterolaemia were identified as independent factors influencing DR. We have incorporated these five indicators into a nomogram, which has shown good efficacy in both the training cohort (AUC = 0.930) and validation cohort (AUC = 0.838). The calibration plots indicated that the model fits well in both the training and the validation cohorts, and decision curve analyses showed that the model had good clinical applicability. CONCLUSION: The prediction model developed in this study holds predictive value for short-term DR following BMS in patients with obesity and T2DM.

Bariatric surgery and mental health outcomes: an umbrella review.

Aims: To evaluate the breadth, depth and effectiveness of the evidence quality of all existing studies on bariatric surgery and mental health outcomes. Design: Umbrella review of existing Systematic review and meta-analyses. Data sources: PubMed, Embase, Web of Science, and the Cochrane Liberally databases of Systematic review and meta-analyses, and hand searching the reference lists of eligible publications. Results: The search identified nine studies and 20 mental health outcomes from 1251 studies. Evidence shows that bariatric surgery is associated with significant improvement in areas such as anxiety, depression and eating disorders (including binge-eating disorder), and there is a significant harmful association with suicide, self-harm and alcohol use disorder (AUD). Among them, the most studied outcome is depression (4 articles). High-quality evidence proves that the score of depressive symptoms can be significantly improved after bariatric surgery within a two-year follow-up period and is not affected by the follow-up time. Low-quality evidence shows that bariatric surgery can significantly reduce depressive symptoms regardless of age and BMI, with an odds ratio (OR) of 0.49. Regardless of the postoperative BMI, the anxiety symptoms of women over 40 still decreased significantly, with an OR of 0.58. Regardless of the type of surgery, surgery can significantly reduce the incidence of eating disorders and symptoms. However, there is no obvious change in the follow-up time of AUD in the first two years after bariatric surgery, and the risk increases obviously in the third year, with an OR of 1.825. The evidence of moderate research shows that the risk of suicide and self-harm increases after bariatric surgery. The odds ratios in the same population and the control group were 1.9 and 3.8 times, respectively. Conclusion: Bariatric surgery is beneficial for improving most mental health-related outcomes. However, we should be cautious about the increased risk of adverse mental health after surgery, such as suicide, self-harm, and AUD.

Development and validation of a CT radiomics and clinical feature model to predict omental metastases for locally advanced gastric cancer.

""We employed radiomics and clinical features to develop and validate a preoperative prediction model to estimate the omental metastases status of locally advanced gastric cancer (LAGC). A total of 460 patients (training cohort, n = 250; test cohort, n = 106; validation cohort, n = 104) with LAGC who were confirmed T3/T4 stage by postoperative pathology were continuously collected retrospectively, including clinical data and preoperative arterial phase computed tomography images (APCT). Dedicated radiomics prototype software was used to segment the lesions and extract features from the preoperative APCT images. The least absolute shrinkage and selection operator (LASSO) regression was used to select the extracted radiomics features, and a radiomics score model was constructed. Finally, a prediction model of omental metastases status and a nomogram were constructed combining the radiomics scores and selected clinical features. An area under the curve (AUC) of the receiver operating characteristic curve (ROC) was used to validate the capability of the prediction model and nomogram in the training cohort. Calibration curves and decision curve analysis (DCA) were used to evaluate the prediction model and nomogram. The prediction model was internally validated by the test cohort. In addition, 104 patients from another hospital's clinical and imaging data were gathered for external validation. In the training cohort, the combined prediction (CP) model (AUC 0.871, 95% CI 0.798-0.945) of the radiomics scores combined with the clinical features, compared with clinical features prediction (CFP) model (AUC 0.795, 95% CI 0.710-0.879) and radiomics scores prediction (RSP) model (AUC 0.805, 95% CI 0.730-0.879), had the better predictive ability. The Hosmer-Lemeshow test of the CP model showed that the prediction model did not deviate from the perfect fitting (p = 0.893). In the DCA, the clinical net benefit of the CP model was higher than that of the CFP model and RSP model. In the test and validation cohorts, the AUC values of the CP model were 0.836 (95% CI 0.726-0.945) and 0.779 (95% CI 0.634-0.923), respectively. The preoperative APCT-based clinical-radiomics nomogram showed good performance in predicting omental metastases status in LAGC, which may contribute to clinical decision-making.

Deep learning model for diagnosing early gastric cancer using preoperative computed tomography images.

Background: Early gastric cancer (EGC) is defined as a lesion restricted to the mucosa or submucosa, independent of size or evidence of regional lymph node metastases. Although computed tomography (CT) is the main technique for determining the stage of gastric cancer (GC), the accuracy of CT for determining tumor invasion of EGC was still unsatisfactory by radiologists. In this research, we attempted to construct an AI model to discriminate EGC in portal venous phase CT images. Methods: We retrospectively collected 658 GC patients from the first affiliated hospital of Nanchang university, and divided them into training and internal validation cohorts with a ratio of 8:2. As the external validation cohort, 93 GC patients were recruited from the second affiliated hospital of Soochow university. We developed several prediction models based on various convolutional neural networks, and compared their predictive performance. Results: The deep learning model based on the ResNet101 neural network represented sufficient discrimination of EGC. In two validation cohorts, the areas under the curves (AUCs) for the receiver operating characteristic (ROC) curves were 0.993 (95% CI: 0.984-1.000) and 0.968 (95% CI: 0.935-1.000), respectively, and the accuracy was 0.946 and 0.914. Additionally, the deep learning model can also differentiate between mucosa and submucosa tumors of EGC. Conclusions: These results suggested that deep learning classifiers have the potential to be used as a screening tool for EGC, which is crucial in the individualized treatment of EGC patients.

CT-based radiomic nomogram for preoperative prediction of DNA mismatch repair deficiency in gastric cancer.

Background: DNA mismatch repair (MMR) deficiency has attracted considerable attention as a predictor of the immunotherapy efficacy of solid tumors, including gastric cancer. We aimed to develop and validate a computed tomography (CT)-based radiomic nomogram for the preoperative prediction of MMR deficiency in gastric cancer (GC). Methods: In this retrospective analysis, 225 and 91 GC patients from two distinct hospital cohorts were included. Cohort 1 was randomly divided into a training cohort (n = 176) and an internal validation cohort (n = 76), whereas cohort 2 was considered an external validation cohort. Based on repeatable radiomic features, a radiomic signature was constructed using the least absolute shrinkage and selection operator (LASSO) regression analysis. We employed multivariable logistic regression analysis to build a radiomics-based model based on radiomic features and preoperative clinical characteristics. Furthermore, this prediction model was presented as a radiomic nomogram, which was evaluated in the training, internal validation, and external validation cohorts. Results: The radiomic signature composed of 15 robust features showed a significant association with MMR protein status in the training, internal validation, and external validation cohorts (both P-values <0.001). A radiomic nomogram incorporating a radiomic signature and two clinical characteristics (age and CT-reported N stage) represented good discrimination in the training cohort with an AUC of 0.902 (95% CI: 0.853-0.951), in the internal validation cohort with an AUC of 0.972 (95% CI: 0.945-1.000) and in the external validation cohort with an AUC of 0.891 (95% CI: 0.825-0.958). Conclusion: The CT-based radiomic nomogram showed good performance for preoperative prediction of MMR protein status in GC. Furthermore, this model was a noninvasive tool to predict MMR protein status and guide neoadjuvant therapy.

Development and validation of a predictive model combining clinical, radiomics, and deep transfer learning features for lymph node metastasis in early gastric cancer.

Background: This study aims to develop and validate a predictive model combining deep transfer learning, radiomics, and clinical features for lymph node metastasis (LNM) in early gastric cancer (EGC). Materials and methods: This study retrospectively collected 555 patients with EGC, and randomly divided them into two cohorts with a ratio of 7:3 (training cohort, n = 388; internal validation cohort, n = 167). A total of 79 patients with EGC collected from the Second Affiliated Hospital of Soochow University were used as external validation cohort. Pre-trained deep learning networks were used to extract deep transfer learning (DTL) features, and radiomics features were extracted based on hand-crafted features. We employed the Spearman rank correlation test and least absolute shrinkage and selection operator regression for feature selection from the combined features of clinical, radiomics, and DTL features, and then, machine learning classification models including support vector machine, K-nearest neighbor, random decision forests (RF), and XGBoost were trained, and their performance by determining the area under the curve (AUC) were compared. Results: We constructed eight pre-trained transfer learning networks and extracted DTL features, respectively. The results showed that 1,048 DTL features extracted based on the pre-trained Resnet152 network combined in the predictive model had the best performance in discriminating the LNM status of EGC, with an AUC of 0.901 (95% CI: 0.847-0.956) and 0.915 (95% CI: 0.850-0.981) in the internal validation and external validation cohorts, respectively. Conclusion: We first utilized comprehensive multidimensional data based on deep transfer learning, radiomics, and clinical features with a good predictive ability for discriminating the LNM status in EGC, which could provide favorable information when choosing therapy options for individuals with EGC.

Is Brain Network Efficiency Reduced in Young Survivors of Acute Lymphoblastic Leukemia?-Evidence from Individual-Based Morphological Brain Network Analysis.

Altered cerebral structure and function have been observed in young survivors of acute lymphoblastic leukemia (ALL). However, the topological organization of the morphological brain networks (MBNs) has not yet been investigated at the individual level. Twenty-three young survivors of ALL and twenty healthy controls (HCs) were recruited and underwent T1-weighted magnetic resonance imaging (MRI) scanning. After preprocessing and segmentation, individual-based MBNs were constructed based on the morphological similarity of gray matter using the combined Euclidean distance. Young survivors showed a significantly lower global clustering coefficient (p = 0.008) and local efficiency (p = 0.035) compared with HCs. In addition, ALL survivors exhibited bidirectional alterations (decreases and increases) in nodal centrality and efficiency around the Rolandic operculum and posterior occipital lobe (p < 0.05, false discovery rate (FDR) corrected). Altered nodal topological efficiencies were associated with off-therapy duration and verbal memory capacity in the digit span test (p < 0.05, FDR corrected). Network-based statistical analysis revealed decreased morphological connections mainly in the pallidum subnetwork, which was negatively correlated with off-therapy durations (p < 0.05). Overall, the topological organization of the individual-based MBNs was disrupted in the young survivors of ALL, which may play a crucial role in executive efficiency deficits.

Classification of Chemotherapy-Related Subjective Cognitive Complaints in Breast Cancer Using Brain Functional Connectivity and Activity: A Machine Learning Analysis.

The aim of this study was combining multi-level resting-state functional magnetic resonance imaging (rs-fMRI) features with machine learning method to distinguish breast cancer patients with chemotherapy-related subjective cognitive complaints (SCC) from non-chemotherapy (BC) and healthy controls (HC). Forty subjects in SCC group, forty-nine in BC group and thirty-four in HC group were recruited and underwent rs-fMRI scanning. Based on the anatomical automatic labeling brain atlas, the functional metrics of all subjects included functional connectivity, amplitude of low frequency fluctuation and fractional amplitude of low frequency fluctuation, regional homogeneity, voxel-mirrored homotopic connectivity and degree centrality were calculated and extracted as features set. Then, the rs-fMRI features were selected by two-sample t-test, removing variables with a high pairwise correlation and least absolute shrinkage and selection operator regression. Finally, the support vector machine models were built for classification (SCC vs. BC, SCC vs. HC). Thirty-eight features (SCC vs. BC) and seventeen features (SCC vs. HC) were selected separately, and the accuracy of the models were 82.0% and 91.9%, respectively. These findings demonstrated a valid machine learning approach that effectively distinguished breast cancer patients with chemotherapy-related SCC from non-chemotherapy and healthy controls, providing potential neuroimaging evidence for early diagnosis and clinical intervention of chemotherapy-related SCC.

DualMMP-GAN: Dual-scale multi-modality perceptual generative adversarial network for medical image segmentation.

Multi-modality magnetic resonance imaging (MRI) can reveal distinct patterns of tissue in the human body and is crucial to clinical diagnosis. But it still remains a challenge to obtain diverse and plausible multi-modality MR images due to expense, noise, and artifacts. For the same lesion, different modalities of MRI have big differences in context information, coarse location, and fine structure. In order to achieve better generation and segmentation performance, a dual-scale multi-modality perceptual generative adversarial network (DualMMP-GAN) is proposed based on cycle-consistent generative adversarial networks (CycleGAN). Dilated residual blocks are introduced to increase the receptive field, preserving structure and context information of images. A dual-scale discriminator is constructed. The generator is optimized by discriminating patches to represent lesions with different sizes. The perceptual consistency loss is introduced to learn the mapping between the generated and target modality at different semantic levels. Moreover, generative multi-modality segmentation (GMMS) combining given modalities with generated modalities is proposed for brain tumor segmentation. Experimental results show that the DualMMP-GAN outperforms the CycleGAN and some state-of-the-art methods in terms of PSNR, SSMI, and RMSE in most tasks. In addition, dice, sensitivity, specificity, and Hausdorff95 obtained from segmentation by GMMS are all higher than those from a single modality. The objective index obtained by the proposed methods are close to upper bounds obtained from real multiple modalities, indicating that GMMS can achieve similar effects as multi-modality. Overall, the proposed methods can serve as an effective method in clinical brain tumor diagnosis with promising application potential.

Disruption of human brain connectivity networks in patients with cervical spondylotic myelopathy.

BACKGROUND: Brain functional plasticity and reorganization in patients with cervical spondylotic myelopathy (CSM) is increasingly being explored and validated. However, specific topological alterations in functional networks and their role in CSM brain functional reorganization remain unclear. This study investigates the topological architecture of intrinsic brain functional networks in CSM patients using graph theory. METHODS: Functional MRI was conducted on 67 CSM patients and 60 healthy controls (HCs). The topological organization of the whole-brain functional network was then calculated using theoretical graph analysis. The difference in categorical variables between groups was compared using a chi-squared test, while that between continuous variables was evaluated using a two-sample t-test. Nonparametric permutation tests were used to compare network measures between the two groups. RESULTS: Small-world architecture in functional brain networks were identified in both CSM patients and HCs. Compared with HCs, CSM patients showed a decreased area under the curve (AUC) of the characteristic path length (FDR q=0.040), clustering coefficient (FDR q=0.037), and normalized characteristic path length (FDR q=0.038) of the network. In contrast, there was an increased AUC of normalized clustering coefficient (FDR q=0.014), small-worldness (FDR q=0.009), and global network efficiency (FDR q=0.027) of the network. In local brain regions, nodal topological properties revealed group differences which were predominantly in the default-mode network (DMN), left postcentral gyrus, bilateral putamen, lingual gyrus, and posterior cingulate gyrus. CONCLUSIONS: This study reported altered functional topological organization in CSM patients. Decreased nodal centralities in the visual cortex and sensory-motor regions may indicate sensory-motor dysfunction and blurred vision. Furthermore, increased nodal centralities in the cerebellum may be compensatory for sensory-motor dysfunction in CSM, while the increased DMN may indicate increased psychological processing in CSM patients.

Clinical features of velamentous umbilical cord insertion and vasa previa: A retrospective analysis based on 501 cases.

ABSTRACT: To identify the risk factors associated with velamentous cord insertion (VCI) and investigate the association between adverse pregnancy outcomes and VCI in singleton pregnancies and those with vasa previa.A total of 59,976 single cases admitted from Qinhuangdao Maternal and Child Health Hospital and Qinhuangdao Beidaihe Hospital from January 2004 to January 2014 were included in this study. We retrospectively analyzed the perinatal complications, neonatal complications, and the clinical features, as well as the Color Doppler ultrasonography findings of the velamentous placenta and placenta previa.We reviewed the clinical data of 59,976 women with singleton pregnancies delivered in Qinhuangdao Maternal and Child Health Hospital and Qinhuangdao Beidaihe Hospital from January 2004 to January 2014. Risk factors and the risks of adverse pregnancy outcomes including admission to a neonatal unit, fetal death, preterm delivery, low birth weight of <2500 g, the infant being small for its gestation age, low Apgar scores (<7) at 1 and 5 minute were evaluated separately among women with and without VCI by means of logistic regression analyses.The prevalence of velamentous umbilical cord insertion was 0.84%, and the prevalence of vasa previa was 0.0017%. The independent risk factors for VCI were nulliparity, obesity, fertility problems, placenta previa, and maternal smoking. VCI was associated with a 1.83-, 2.58-, 3.62-, and 1.41-fold increase in the risk of retention in the neonatal unit, preterm delivery (<37 gestation weeks), low birth weight, and small-for-gestational age, compared to pregnancies involving normal cord insertion. Of the women with VCI, 16.1% underwent emergency cesarean section compared to 8.9% (P < .001) of women without VCI.The prevalence of VCI was 0.84% in singletons. The results suggest that VCI is a moderate risk condition resulted in increased risks of prematurity and impairment of fetal growth.

Altered Functional Connectivity Density in Young Survivors of Acute Lymphoblastic Leukemia Using Resting-State fMRI.

OBJECTIVE: Using functional connectivity density (FCD) mapping measured by resting-state functional magnetic resonance imaging (rs-fMRI), an ultrafast data-driven graph theory approach, we attempted to study the abnormalities in neural activity of young survivors of acute lymphoblastic leukemia (ALL) and to explore the neuropathological evidence of chemotherapy-related cognitive impairment of patients. METHODS: Twenty young survivors of ALL and 18 well-matched healthy controls (HCs) were recruited in this study. All ALL patients and healthy controls underwent rs-fMRI scans and completed neurocognitive testing. The between-group differences in short-range and long-range FCD were calculated by the option of degree centrality (DC) in MATLAB software after preprocessing. The correlations between the FCD value and each of the neurocognitive outcomes were analyzed in the ALL patients. RESULTS: The group-averaged FCD maps showed similar spatial patterns between the two groups. Compared with the HCs, ALL patients showed decreased long-range FCD in regions of the bilateral lingual gyrus, cingulate cortex, hippocampal gyrus, and right calcarine fissure. Simultaneously, decreased regions in the short-range FCD map were the bilateral lingual gyrus, cingulate cortex, parahippocampal gyrus and right calcarine fissure. Increased functional connectivity (FC) was observed between the region with decreased long-range FCD and the posterior cerebellar lobe, and decreased FC was observed between the region and the middle occipital gyrus, cuneus and lingual gyrus. Thus, there existed no brain areas with increased FCD. The decreased short-range FCD value of ALL patients was positively correlated with the score on the Digit Span Test (Forward), and the increased FC value was negatively correlated with the score on the Trail Making Test part A. CONCLUSION: Our results suggest the altered functional connectivity of young survivors of ALL in the posterior region of the brain and posterior lobe of the cerebellum. Alterations in spontaneous neuronal activity seem to parallel the neurocognitive testing, which indicates that the rs-fMRI could be used as a neuroimaging marker for neurological impairment in ALL patients.

Frequency-Specific Abnormalities Of Functional Homotopy In Alcohol Dependence: A Resting-State Functional Magnetic Resonance Imaging Study.

PURPOSE: Alcohol dependence (AD) is a relapsing mental disorder, typically occurring with concurrent tobacco misuse. Studies have reported disruption of the structural connectivity between hemispheres in the brain of individuals with AD. However, alterations in interhemispheric interactions and the specificity of frequency bands in individuals with AD remain unknown. Voxel-mirrored homotopic connectivity (VMHC) allows examination of functional interactions between mirrored interhemispheric voxels. Here, we use VMHC to investigate homotopic connectivity in AD and alcohol and nicotine co-dependence (AND) subjects. PATIENTS AND METHODS: VMHC and seed-based functional connectivity (FC) in 24 AD, 30 AND, and 35 sex-, age-, and education-matched healthy control (HC) subjects were calculated for different frequency bands (slow-5, slow-4, and typical bands). RESULTS: Individuals with AD demonstrated significantly reduced VMHC in bilateral cerebellum posterior lobe (CPL) and increased VMHC in bilateral middle frontal gyrus (MFG) compared to that in HCs in the typical and slow-4 bands; higher VMHC in the MFG was positively correlated with the dependence-severity score. In all bands of the VMHC analysis, no significant differences were found between the AND and other groups. Subsequent seed-based FC analysis demonstrated all regions with abnormal VMHC exhibited altered FC with its counterpart in the contralateral hemisphere in the typical and slow-4 frequency bands. The FC value between bilateral CPL within AD subjects negatively correlated with alcohol intake. CONCLUSION: Our findings provide further evidence of the role of disruptions within the brain circuitry supporting cognitive control in the development of AD. Alterations in neural activities in the CPL and MFG might be a biomarker of dependence severity in AD patients as assessed using clinical questionnaire and features. Because of the frequency specificity in VMHC, we must consider frequency effects in future AD functional magnetic resonance imaging studies.

Imaging findings of inflammatory pseudotumor-like follicular dendritic cell tumors of the liver: Two case reports and literature review.

BACKGROUND: Inflammatory pseudotumor-like follicular dendritic cell (IPT-like FDC) tumors of the liver is an uncommon tumor with extremely low incidence. To date, the radiologic findings of this tumor in multiphase computed tomography (CT) and magnetic resonance imaging (MRI) imaging have not been described. CASE SUMMARY: Patient 1 is a 31-year-old Chinese female, whose complaining incidentally coincided with the finding of multiple liver masses. In the local hospital, an abdominal enhanced CT found two hypo-dense solid lesions, with heterogeneous sustained hypoenhancement, in the upper segment of the liver's right posterior lobe. In our hospital, enhanced magnetic resonance imaging (MRI) with hepatocyte-specific contrast agents showed a similar enhanced pattern of lesions with patchy hyperintensity in the hepatobiliary phase (HBP). The patient underwent surgery and recovered well. The final pathology confirmed an IPT-like FDC tumor. No recurrence was found on the regular re-examination. Patient 2 is a 48-year-old Chinese male admitted to our hospital for a huge unexpected hepatic lesion. A dynamic enhanced abdominal CT revealed a huge heterogeneous enhanced solid tumor in the right lobe of the liver with a size of 100 mm × 80 mm, which showed a heterogeneous sustained hypoenhancement. In addition, enlarged lymph nodes were found in the hilum of the liver. This patient underwent a hepatic lobectomy and lymph node dissection. The final pathology confirmed an IPT-like FDC tumor. No recurrence was found upon regular re-examination. CONCLUSION: When a hepatic tumor shows heterogeneous sustained hypoenhancement with a patchy enhancement during HBP, an IPT-like FDC tumor should be considered in the differential diagnosis.

Altered functional connectivity density in primary angle-closure glaucoma patients at resting-state.

BACKGROUND: Primary angle-closure glaucoma (PACG) is a neurodegenerative disease. Previous structural and functional studies of functional magnetic resonance imaging (fMRI) have demonstrated widespread dysfunction of spontaneous activity in the PACG brain. In this study, we applied a data-driven graph theory approach of functional connectivity density (FCD) mapping to investigate the altered local and global functional connectivity (FC) of the cortex in PACG. METHODS: Forty-five PACG patients (53.28±10.79 years, 17 males/28 females) and 46 well-matched healthy controls (HCs) (52.67±11.01 years,18 males/28 females) received resting-state fMRI scans. All PACG patients finished complete ophthalmologic examinations, including retinal nerve fiber layer thickness (RNFLT), intraocular pressure (IOP), average cup to disc ratio (A-C/D), and vertical cup to disc ratio (V-C/D). We calculated the between-group FCD difference for short-range and long-range in each voxel. Then, we generated the intrinsic FC of the seed region with the whole brain. Finally, correlations were investigated between FCD value of the altered regions and clinical variables. RESULTS: PACG patients showed increased short-range FCD in the left inferior frontal gyrus (IFG)/insula/parahippocampal gyrus and right IFG/insula (P<0.05, corrected), compared with the HCs. Simultaneously, the decreased regions in short-range FCD map were the occipital/cuneus/precuneus/superior parietal/postcentral lobe (P<0.05, corrected). In the PACG groups, decreased long-range FCD was observed in the left middle frontal gyrus compared to the HC (P<0.05, corrected). RNFLT was positively correlated with decreased short-range FCD value of the occipital/cuneus/precuneus/superior parietal/postcentral lobes, and the A-C/D was negatively correlated with the increased short-range FCD value of the left IFG/insula/parahippocampal gyrus, and the right IFG/insula. CONCLUSIONS: Our findings suggest that PACG can induce extensive brain dysfunction, and showed different spatial distribution in short- and long-range FCD.

Myoepithelioma of the lateral abdominal wall: A case report.

RATIONALE: Soft-tissue myoepithelioma is a rare neoplasm. It usually occurs in the distal or proximal extremities, but seldomly arises in the abdominal wall. PRESENTING CONCERNS OF THE PATIENT: The patient is a 40-year-old woman who presented with a painless mass at the lateral abdominal wall for 6 months. Computed tomography scan revealed a lobulated and well-defined iso-density mass showing heterogeneously moderate enhancement. The mass exhibited intermediate T1 signal and obvious high T2 signal on magnetic resonance imaging. INTERVENTIONS: The tumor was excised. Hematoxylin-eosin stain and immunohistochemical stain showed that the tumor was myoepithelioma. OUTCOMES: The patient did not undergo chemotherapy and radiotherapy. No recurrence or metastasis was noted during the 1 year follow-up. LESSONS: Radiologists should consider myoepithelioma in the differential diagnosis when finding a tumor in the abdominal wall.

Computed tomography findings of primary pulmonary meningioma: A case report.

RATIONALE: Primary pulmonary meningiomas are extremely rare, and only a few cases have been reported in the medical literature. Imaging findings of primary pulmonary meningiomas have been reported even more rarely. PATIENT CONCERNS: We present the case of a 54-year-old male patient with cough and sputum lasting for 20 years. This was a case of primary pulmonary meningioma with initial suspicion of a chest wall intercostal neurinoma. DIAGNOSES: A lung lesion was detected on chest computed tomography (CT) imaging 4 years ago. This case appeared as a solitary well-defined round nodule close to the left chest wall, with heterogeneous enhancement on CT, which inaccurately led to the suspicion of a chest wall intercostal neurinoma. INTERVENTIONS: A thoracoscopic wedge resection was performed. OUTCOMES: The postoperative histological diagnosis was primary pulmonary meningioma. After 2 years of follow-up, the patient is still alive without evidence of metastasis or recurrence. LESSONS: Increased awareness of the CT characteristics of this rare tumor may broaden the radiologist's knowledge base.

Intrinsic Functional Connectivity Alterations of the Primary Visual Cortex in Primary Angle-Closure Glaucoma Patients before and after Surgery: A Resting-State fMRI Study.

PURPOSE: To investigate the altered intrinsic functional connectivity (iFC) of the primary visual cortex (V1) in primary angle-closure glaucoma (PACG) patients before and after surgery using resting-state functional MRI. MATERIALS AND METHODS: Twenty-five preoperative PACG (pre-PACG) patients and 25 well-matched healthy controls (HCs) were included in this study, and 9 PACG patients were assessed again at least 3 months after treatment (post-PACG). We generated the iFC maps of the seed regions in the centers of the left and right V1 and conducted group comparisons. Then, the relationships between the altered iFC coefficients and clinical variables were investigated in the pre-PACG patients. RESULTS: Compared with the HCs, the pre-PACG patients showed decreased iFC between the left V1 and right V2 (covering the cuneus, calcarine and lingual gyrus) and increased iFC between the left V1 and left temporal-parietal region, left frontal opercula-insula-basal ganglia region, right insula-basal ganglia region, and right inferior parietal lobule (P < 0.01, corrected). Compared with the pre-PACG patients, the post-PACG patients showed increased iFC between the left V1 and bilateral V2, and between the left V1 and left or right postcentral gyrus; in addition, they showed decreased iFC between the left V1 and the dorsal-attention and frontoparietal-control networks. In the pre-PACG patients, visual activity (VA) was positively correlated with increased iFC between the left V1 and the left temporal-parietal region or the right inferior parietal lobule. Similar patterns of alterations were observed in the right V1-iFC in both the pre- and post-PACG patients. CONCLUSIONS: The primary findings have demonstrated a gradual decrease in visual information integration in the left V1-V2 pathway and VA-related functional compensation in the pre-PACG patients, generating further evidence of functional restoration in post-PACG patients.