Obesity is associated with alterations in anatomical connectivity of frontal-corpus callosum.

Obesity has been linked to abnormal frontal function, including the white matter fibers of anterior portion of the corpus callosum, which is crucial for information exchange within frontal cortex. However, alterations in white matter anatomical connectivity between corpus callosum and cortical regions in patients with obesity have not yet been investigated. Thus, we enrolled 72 obese and 60 age-/gender-matched normal weight participants who underwent clinical measurements and diffusion tensor imaging. Probabilistic tractography with connectivity-based classification was performed to segment the corpus callosum and quantify white matter anatomical connectivity between subregions of corpus callosum and cortical regions, and associations between corpus callosum-cortex white matter anatomical connectivity and clinical behaviors were also assessed. Relative to normal weight individuals, individuals with obesity exhibited significantly greater white matter anatomical connectivity of corpus callosum-orbitofrontal cortex, which was positively correlated with body mass index and self-reported disinhibition of eating behavior, and lower white matter anatomical connectivity of corpus callosum-prefrontal cortex, which was significantly negatively correlated with craving for high-calorie food cues. The findings show that alterations in white matter anatomical connectivity between corpus callosum and frontal regions involved in reward and executive control are associated with abnormal eating behaviors.

Covariation of preadult environmental exposures, adult brain imaging phenotypes, and adult personality traits.

Exposure to preadult environmental exposures may have long-lasting effects on mental health by affecting the maturation of the brain and personality, two traits that interact throughout the developmental process. However, environment-brain-personality covariation patterns and their mediation relationships remain unclear. In 4297 healthy participants (aged 18-30 years), we combined sparse multiple canonical correlation analysis with independent component analysis to identify the three-way covariation patterns of 59 preadult environmental exposures, 760 adult brain imaging phenotypes, and five personality traits, and found two robust environment-brain-personality covariation models with sex specificity. One model linked greater stress and less support to weaker functional connectivity and activity in the default mode network, stronger activity in subcortical nuclei, greater thickness and volume in the occipital, parietal and temporal cortices, and lower agreeableness, consciousness and extraversion as well as higher neuroticism. The other model linked higher urbanicity and better socioeconomic status to stronger functional connectivity and activity in the sensorimotor network, smaller volume and surface area and weaker functional connectivity and activity in the medial prefrontal cortex, lower white matter integrity, and higher openness to experience. We also conducted mediation analyses to explore the potential bidirectional mediation relationships between adult brain imaging phenotypes and personality traits with the influence of preadult environmental exposures and found both environment-brain-personality and environment-personality-brain pathways. We finally performed moderated mediation analyses to test the potential interactions between macro- and microenvironmental exposures and found that one category of exposure moderated the mediation pathways of another category of exposure. These results improve our understanding of the effects of preadult environmental exposures on the adult brain and personality traits and may facilitate the design of targeted interventions to improve mental health by reducing the impact of adverse environmental exposures.

Neurovascular decoupling measured with quantitative susceptibility mapping is associated with cognitive decline in patients with type 2 diabetes.

Disturbance of neurovascular coupling (NVC) is suggested to be one potential mechanism in type 2 diabetes mellitus (T2DM) associated mild cognitive impairment (MCI). However, NVC evidence derived from functional magnetic resonance imaging ignores the relationship of neuronal activity with vascular injury. Twenty-seven T2DM patients without MCI and thirty healthy controls were prospectively enrolled. Brain regions with changed susceptibility detected by quantitative susceptibility mapping (QSM) were used as seeds for functional connectivity (FC) analysis. NVC coefficients were estimated using combined degree centrality (DC) with susceptibility or cerebral blood flow (CBF). Partial correlations between neuroimaging indicators and cognitive decline were investigated. In T2DM group, higher susceptibility values in right hippocampal gyrus (R.PHG) were found and were negatively correlated with Naming Ability of Montreal Cognitive Assessment. FC increased remarkably between R.PHG and right middle temporal gyrus (R.MTG), right calcarine gyrus (R.CAL). Both NVC coefficients (DC-QSM and DC-CBF) reduced in R.PHG and increased in R.MTG and R.CAL. Both NVC coefficients in R.PHG and R.MTG increased with the improvement of cognitive ability, especially for executive function. These demonstrated that QSM and DC-QSM coefficients can be promising biomarkers for early evaluation of cognitive decline in T2DM patients and help to better understand the mechanism of NVC.

Habenular connectivity predict weight loss and negative emotional-related eating behavior after laparoscopic sleeve gastrectomy.

Habenular (Hb) processes negative emotions that may drive compulsive food-intake. Its functional changes were reported following laparoscopic-sleeve-gastrectomy (LSG). However, structural connectivity (SC) of Hb-homeostatic/hedonic circuits after LSG remains unclear. We selected regions implicated in homeostatic/hedonic regulation that have anatomical connections with Hb as regions-of-interest (ROIs), and used diffusion-tensor-imaging with probabilistic tractography to calculate SC between Hb and these ROIs in 30 obese participants before LSG (PreLSG) and at 12-month post-LSG (PostLSG12) and 30 normal-weight controls. Three-factor-eating-questionnaire (TFEQ) and Dutch-eating-behavior-questionnaire (DEBQ) were used to assess eating behaviors. LSG significantly decreased weight, negative emotion, and improved self-reported eating behavior. LSG increased SC between the Hb and homeostatic/hedonic regions including hypothalamus (Hy), bilateral superior frontal gyri (SFG), left amygdala (AMY), and orbitofrontal cortex (OFC). TFEQ-hunger negatively correlated with SC of Hb-Hy at PostLSG12; and increased SC of Hb-Hy correlated with reduced depression and DEBQ-external eating. TFEQ-disinhibition negatively correlated with SC of Hb-bilateral SFG at PreLSG. Increased SC of Hb-left AMY correlated with reduced DEBQ-emotional eating. Higher percentage of total weight-loss negatively correlated with SC of Hb-left OFC at PreLSG. Enhanced SC of Hb-homeostatic/hedonic regulatory regions post-LSG may contribute to its beneficial effects in improving eating behaviors including negative emotional eating, and long-term weight-loss.

Noninvasive Isocitrate Dehydrogenase 1 Status Prediction in Grade II/III Glioma Based on Magnetic Resonance Images: A Transfer Learning Strategy.

OBJECTIVE: The aim of this study was to evaluate transfer learning combined with various convolutional neural networks (TL-CNNs) in predicting isocitrate dehydrogenase 1 ( IDH1 ) status of grade II/III gliomas. METHODS: Grade II/III glioma patients diagnosed at the Tangdu Hospital (August 2009 to May 2017) were retrospectively enrolled, including 54 patients with IDH1 mutant and 56 patients with wild-type IDH1 . Convolutional neural networks, AlexNet, GoogLeNet, ResNet, and VGGNet were fine-tuned with T2-weighted imaging (T2WI), fluid attenuation inversion recovery (FLAIR), and contrast-enhanced T1-weighted imaging (T1CE) images. The single-modal networks were integrated with averaged sigmoid probabilities, logistic regression, and support vector machine. FLAIR-T1CE-fusion (FC-fusion), T2WI-T1CE-fusion (TC-fusion), and FLAIR-T2WI-T1CE-fusion (FTC-fusion) were used for fine-tuning TL-CNNs. RESULTS: IDH1 -mutant prediction accuracies using AlexNet, GoogLeNet, ResNet, and VGGNet achieved 70.0% (AUC = 0.660), 65.0% (AUC = 0.600), 70.0% (AUC = 0.700), and 80.0% (AUC = 0.730) for T2WI images, 70.0% (AUC = 0.660), 70.0% (AUC = 0.620), 70.0% (AUC = 0.710), and 80.0% (AUC = 0.720) for FLAIR images, and 73.7% (AUC = 0.744), 73.7% (AUC = 0.656), 73.7% (AUC = 0.633), and 73.7% (AUC = 0.700) for T1CE images, respectively. The highest AUC (0.800) was achieved using VGGNet and FC-fusion images. CONCLUSIONS: TL-CNNs (especially VGGNet) had a potential predictive value for IDH1 -mutant status of grade II/III gliomas.

Functional to structural plasticity in unilateral sudden sensorineural hearing loss: neuroimaging evidence.

A cortical plasticity after long-duration single side deafness (SSD) is advocated with neuroimaging evidence while little is known about the short-duration SSDs. In this case-cohort study, we recruited unilateral sudden sensorineural hearing loss (SSNHL) patients and age-, gender-matched health controls (HC), followed by comprehensive neuroimaging analyses. The primary outcome measures were temporal alterations of varied dynamic functional network connectivity (dFNC) states, neurovascular coupling (NVC) and brain region volume at different stages of SSNHL. The secondary outcome measures were pure-tone audiograms of SSNHL patients before and after treatment. A total of 38 SSNHL patients (21 [55%] male; mean [standard deviation] age, 45.05 [15.83] years) and 44 HC (28 [64%] male; mean [standard deviation] age, 43.55 [12.80] years) were enrolled. SSNHL patients were categorized into subgroups based on the time from disease onset to the initial magnetic resonance imaging scan: early- (n = 16; 1-6 days), intermediate- (n = 9; 7-13 days), and late- stage (n = 13; 14-30 days) groups. We first identified slow state transitions between varied dFNC states at early-stage SSNHL, then revealed the decreased NVC restricted to the auditory cortex at the intermediate- and late-stage SSNHL. Finally, a significantly decreased volume of the left medial superior frontal gyrus (SFGmed) was observed only in the late-stage SSNHL cohort. Furthermore, the volume of the left SFGmed is robustly correlated with both disease duration and patient prognosis. Our study offered neuroimaging evidence for the evolvement from functional to structural brain alterations of SSNHL patients with disease duration less than 1 month, which may explain, from a neuroimaging perspective, why early-stage SSNHL patients have better therapeutic responses and hearing recovery.

α-Subunit Tyrosine Phosphorylation Is Required for Activation of the Large Conductance Ca2+-Activated Potassium Channel in the Rabbit Sphincter of Oddi.

Large conductance Ca2+-activated potassium (BKCa) channels are regulated by intracellular free Ca2+ concentrations ([Ca2+]i) and channel protein phosphorylation. In hypercholesterolemia (HC), motility impairment of the sphincter of Oddi (SO) is associated with abnormal [Ca2+]i accumulation in smooth muscle cells of the rabbit SO (RSOSMCs), which is closely related to BKCa channel activity. However, the underlying mechanisms regulating channel activity remain unclear. In this study, an HC rabbit model was generated and used to investigate BKCa channel activity of RSOSMCs via SO muscle tone measurement in vitro and manometry in vivo, electrophysiological recording, intracellular calcium measurement, and Western blot analyses. BKCa channel activity was decreased, which correlated with [Ca2+]i overload and reduced tyrosine phosphorylation of the BKCa α-subunit in the HC group. The abnormal [Ca2+]i accumulation and decreased BKCa channel activity were partially restored by Na3VO4 pretreatment but worsened by genistein in RSOSMCs in the HC group. This study suggests that α-subunit tyrosine phosphorylation is required for [Ca2+]i to activate BKCa channels, and there is a negative feedback between the BKCa channel and the L-type voltage-dependent Ca2+ channel that regulates [Ca2+]i. This study provides direct evidence that tyrosine phosphorylation of BKCa α-subunits is required for [Ca2+]i to activate BKCa channels in RSOSMCs, which may be the underlying physiological and pathologic mechanism regulating the activity of BKCa channels in SO cells.

Functional Abnormality of the Executive Control Network in Individuals With Obesity During Delay Discounting.

Individuals with obesity (OB) prefer immediate rewards of food intake over the delayed reward of healthy well-being achieved through diet management and physical activity, compared with normal-weight controls (NW). This may reflect heightened impulsivity, an important factor contributing to the development and maintenance of obesity. However, the neural mechanisms underlying the greater impulsivity in OB remain unclear. Therefore, the current study employed functional magnetic resonance imaging with a delay discounting (DD) task to examine the association between impulsive choice and altered neural mechanisms in OB. During decision-making in the DD task, OB compared with NW had greater activation in the dorsolateral prefrontal cortex (DLPFC) and posterior parietal cortex, which was associated with greater discounting rate and weaker cognitive control as measured with the Three-Factor Eating Questionnaire (TFEQ). In addition, the association between DLPFC activation and cognitive control (TFEQ) was mediated by discounting rate. Psychophysiological interaction analysis showed decreased connectivity of DLPFC-inferior parietal cortex (within executive control network [ECN]) and angular gyrus-caudate (ECN-reward) in OB relative to NW. These findings reveal that the aberrant function and connectivity in core regions of ECN and striatal brain reward regions underpin the greater impulsivity in OB and contribute to abnormal eating behaviors.

Intersubject correlation analysis reveals the plasticity of cerebral functional connectivity in the long-term use of social media.

Owing to the limitations of cross-sectional studies, it is unclear whether social media induce brain changes, or if individuals with certain biological traits are more likely to use social media. Functional connectivity (FC) can reflect cerebral functional plasticity, and if social media can influence cerebral FC, then the FC of light social media users should be more similar to that of heavy users after they "heavily" used social media for a long period. We combined longitudinal study design and intersubject correlation (ISC) analysis to investigate this similarity. Thirty-five heavy and 21 light social media users underwent cognitive tests and functional MRIs. The 21 light social media users underwent another functional MRI scan after completing an additional four-week social media task. We conducted the ISC at the group, individual, and brain-region levels to investigate the similarity of FC and locate the brain regions most affected by social media. The FC of light social media users was more similar to that of heavy social media users after they completed the four-week social media task. Then, social media had an impact on half of the brain, involving almost all brain networks. Finally, cerebral FC that mostly affected by social media was associated with selective attention. We concluded that the impact of social media use on cerebral functional connectivity changes is revealed by ISC method and longitudinal design, which may provide guidance for clinical practice. The methods used in the current research could also be applied to similar domains.

Differentiating thymoma, thymic carcinoma and lymphoma based on collagen fibre patterns with T2- and diffusion-weighted magnetic resonance imaging.

OBJECTIVES: The amount and distribution of intratumoural collagen fibre vary among different thymic tumours, which can be clearly detected with T2- and diffusion-weighted MR images. To explore the incidences of collagen fibre patterns (CFPs) among thymomas, thymic carcinomas and lymphomas on imaging, and to evaluate the efficacy and reproducibility of CFPs in differential diagnosis of thymic tumours. MATERIALS AND METHODS: Three hundred and ninety-eight patients with pathologically diagnosed thymoma, thymic carcinoma and lymphoma who underwent T2- and diffusion-weighted MR imaging were retrospectively enrolled. CFPs were classified into four categories: septum sign, patchy pattern, mixed pattern and no septum sign. The incidences of CFPs were compared among different thymic tumours, and the efficacy and reproducibility in differentiating the defined tumour types were analysed. RESULTS: There were significant differences in CFPs among thymomas, thymic squamous cell carcinomas (TSCCs), other thymic carcinomas and neuroendocrine tumours (OTC&NTs) and thymic lymphomas. Septum signs were found in 209 (86%) thymomas, which differed between thymomas and any other thymic neoplasms (all p < 0.005). The patchy, mixed patterns and no septum sign were mainly seen in TSCCs (80.3%), OTC&NTs (78.9%) and thymic lymphomas (56.9%), respectively. The consistency of different CFP evaluation between two readers was either good or excellent. CFPs achieved high efficacy in identifying the thymic tumours. CONCLUSION: The CFPs based on T2- and diffusion-weighted MR imaging were of great value in the differential diagnosis of thymic tumours. KEY POINTS: • Significant differences are found in intratumoural collagen fibre patterns among thymomas, thymic squamous cell carcinomas, other thymic carcinomas and neuroendocrine tumours and thymic lymphomas. • The septum sign, patchy pattern, mixed pattern and no septum sign are mainly seen in thymomas (86%), thymic squamous cell carcinomas (80.3%), other thymic carcinomas and neuroendocrine tumours (79%) and thymic lymphomas (57%), respectively. • The collagen fibre patterns have high efficacy and reproducibility in differentiating thymomas, thymic squamous cell carcinomas and thymic lymphomas.

Alterations in Functional and Structural Connectivity of Basal Ganglia Network in Patients with Obesity.

Obesity is related to overconsumption of high-calorie (HiCal) food, which is modulated by brain reward and inhibitory control circuitries. The basal ganglia (BG) are a key set of nuclei within the reward circuitry, but obesity-associated functional and structural abnormalities of BG have not been well studied. Resting-state functional MRI with independent component analysis (ICA) and probabilistic tractography were employed to investigate differences in BG-related functional-(FC) and structural connectivity (SC) between 32 patients with obesity (OB) and 35 normal-weight (NW) participants. Compared to NW, OB showed significantly lower FC strength in the caudate nucleus within the BG network, and seed-based FC analysis showed lower FC between caudate and dorsolateral prefrontal cortex (DLPFC), which was negatively correlated with craving for HiCal food cues. Further SC analysis revealed that OB showed lower SC than NW between left caudate and left DLPFC as measured with fractional anisotropy (FA). Alterations in FC and SC between caudate and DLPFC in obese patients, which highlights the role of BG network in modulating the balance between reward and inhibitory-control.

Connectome-Based Prediction of Optimal Weight Loss Six Months After Bariatric Surgery.

Despite bariatric surgery being the most effective treatment for obesity, a proportion of subjects have suboptimal weight loss post-surgery. Therefore, it is necessary to understand the mechanisms behind the variance in weight loss and identify specific baseline biomarkers to predict optimal weight loss. Here, we employed functional magnetic resonance imaging (fMRI) with baseline whole-brain resting-state functional connectivity (RSFC) and a multivariate prediction framework integrating feature selection, feature transformation, and classification to prospectively identify obese patients that exhibited optimal weight loss at 6 months post-surgery. Siamese network, which is a multivariate machine learning method suitable for small sample analysis, and K-nearest neighbor (KNN) were cascaded as the classifier (Siamese-KNN). In the leave-one-out cross-validation, the Siamese-KNN achieved an accuracy of 83.78%, which was substantially higher than results from traditional classifiers. RSFC patterns contributing to the prediction consisted of brain networks related to salience, reward, self-referential, and cognitive processing. Further RSFC feature analysis indicated that the connection strength between frontal and parietal cortices was stronger in the optimal versus the suboptimal weight loss group. These findings show that specific RSFC patterns could be used as neuroimaging biomarkers to predict individual weight loss post-surgery and assist in personalized diagnosis for treatment of obesity.

Obese Individuals Show Disrupted Dynamic Functional Connectivity between Basal Ganglia and Salience Networks.

Previous functional magnetic resonance imaging (fMRI) studies have showed obesity (OB)-related alterations in intrinsic functional connectivity (FC) within and between different resting-state networks (RSNs). However, few studies have examined dynamic functional connectivity (DFC). Thus, we employed resting-state fMRI with independent component analysis (ICA) and DFC analysis to investigate the alterations in FC within and between RSNs in 56 individuals with OB and 46 normal-weight (NW) controls. ICA identified six RSNs, including basal ganglia (BG), salience network (SN), right executive control network/left executive control network, and anterior default-mode network (aDMN)/posterior default-mode network. The DFC analysis identified four FC states. OB compared with NW had more occurrences and a longer mean dwell time (MDT) in state 2 (positive connectivity of BG with other RSN) and also had higher FC of BG-SN in other states. Body mass index was positively correlated with MDT and FCs of BG-aDMN (state 2) and BG-SN (state 4). DFC analysis within more refined nodes of RSNs showed that OB had more occurrences and a longer MDT in state 1 in which caudate had positive connections with the other network nodes. The findings suggest an association between caudate-related and BG-related positive FC in OB, which was not revealed by traditional FC analysis, highlighting the utility of adding DFC to the more conventional methods.

Brain Connectivity, and Hormonal and Behavioral Correlates of Sustained Weight Loss in Obese Patients after Laparoscopic Sleeve Gastrectomy.

The biological mediators that support cognitive-control and long-term weight-loss after laparoscopic sleeve gastrectomy (LSG) remain unclear. We measured peripheral appetitive hormones and brain functional-connectivity (FC) using magnetic-resonance-imaging with food cue-reactivity task in 25 obese participants at pre, 1 month, and 6 month after LSG, and compared with 30 normal weight controls. We also used diffusion-tensor-imaging to explore whether LSG increases brain structural-connectivity (SC) of regions involved in food cue-reactivity. LSG significantly decreased BMI, craving for high-calorie food cues, ghrelin, insulin, and leptin levels, and increased self-reported cognitive-control of eating behavior. LSG increased FC between the right dorsolateral prefrontal cortex (DLPFC) and the pregenual anterior cingulate cortex (pgACC) and increased SC between DLPFC and ACC at 1 month and 6 month after LSG. Reduction in BMI correlated negatively with increased FC of right DLPFC-pgACC at 1 month and with increased SC of DLPFC-ACC at 1 month and 6 month after LSG. Reduction in craving for high-calorie food cues correlated negatively with increased FC of DLPFC-pgACC at 6 month after LSG. Additionally, SC of DLPFC-ACC mediated the relationship between lower ghrelin levels and greater cognitive control. These findings provide evidence that LSG improved functional and structural connectivity in prefrontal regions, which contribute to enhanced cognitive-control and sustained weight-loss following surgery.

Predicting Subtype of Growth Hormone Pituitary Adenoma based on Magnetic Resonance Imaging Characteristics.

PURPOSE: This study aimed to investigate the value of magnetic resonance (MR) characteristics in differentiating the subtypes of growth hormone pituitary adenomas. MATERIALS AND METHODS: The clinical and MR imaging data of 70 patients with growth hormone pituitary adenoma confirmed by surgery and pathology were retrospectively analyzed. The tumors were divided into dense granular (DG; 36 cases) and sparse granular subtypes (SG; 34 cases). The tumors' MR features were analyzed, including the mean and maximum diameters, T2 signal intensity, T2 relative signal intensity (rSI), homogeneity, enhancement degree, and invasiveness (Knosp grade). Mann-Whitney U test and χ2 test were used to analyze MR characteristics between the 2 groups. The independent predictors and predictive probabilities of tumor subtypes were obtained via a logistic regression model, and the efficacy was compared by receiver operating characteristic curve. RESULTS: The mean and maximum diameters of growth hormone adenoma in DG and SG were 1.77 versus 2.45 and 1.95 versus 3.00 cm (median, P < 0.05), respectively. There was a significant difference between the 2 groups in T2 signal intensity and rSI (P values were 0.02 and 0.001, respectively). Most DG adenomas (86.1%) appeared as hypointense on T2 images, and 38.2% of SG adenomas were hyperintense. There was no significant difference in tumor homogeneity (P = 0.622). A significant difference was found in the Knosp grade between the 2 subtypes (P = 0.004). In addition, the enhancement degree of SG adenomas was significantly higher than that of DG adenomas (P = 0.001). Logistic regression analysis showed that high T2 rSI value and marked contrast enhancement were independent predictors of the 2 subtypes, and the odds ratios were 4.811 and 4.649, respectively. The multivariate logistic model obtained relatively high predicting efficacy, and the area under the curve, sensitivity, and specificity were 0.765, 0.882, and 0.500, respectively. CONCLUSIONS: There are significant differences in tumor size, T2 signal intensity, T2 rSI, enhancement degree, and invasiveness between DG and SG adenomas. The logistic model based on the marked contrast enhancement and high T2 rSI value has an important value in predicting the subtype of growth hormone adenoma.

Long-term changes in insula-mesolimbic structural and functional connectivity in obese patients after laparoscopic sleeve gastrectomy.

OBJECTIVE: Brain imaging studies have shown insula-related functional and structural abnormalities in patients with obesity. Laparoscopic sleeve gastrectomy is currently an effective procedure for treating obesity, which promotes acute recovery of brain functional and structural abnormalities in obese patients. The aim of this study was to investigate the long-term impact of laparoscopic sleeve gastrectomy on insula-related structural and functional connectivity. METHODS: Diffusion tensor imaging and resting-state functional magnetic resonance imaging were employed to investigate laparoscopic sleeve gastrectomy-induced changes in insula-related structural connectivity and corresponding resting-state functional connectivity in 25 obese patients prior to (PreLSG) and 12 months post-surgery (PostLSG12). RESULTS: Results showed significant increases in fractional anisotropy and axial diffusivity between the right insula and anterior cingulate cortex, and higher fractional anisotropy of left insula-putamen, left insula-caudate and anterior cingulate cortex-right posterior cingulate cortex/precuneus at PostLSG12 compared with PreLSG. There were significant negative correlations between axial diffusivity of right insula-anterior cingulate cortex and body mass index, and fractional anisotropy of right insula-anterior cingulate cortex with scores on external eating at PostLSG12. Anxiety and depressive status ratings were negatively correlated with fractional anisotropy of left insula-putamen at PostLSG12. In addition, there was a significant decrease in resting-state functional connectivity between left insula and left caudate. CONCLUSIONS: These findings demonstrate long-term changes in insula-related structural and functional connectivity abnormalities promoted by laparoscopic sleeve gastrectomy, which highlight its strong association with long-term weight loss and improvement in eating behaviors.

Alterations in functional connectivity and interactions in resting-state networks in female patients with functional constipation.

BACKGROUND : Patients with functional constipation (FCon) have been reported with brain functional and structural abnormalities. However, no studies have been performed to investigate the differences in resting-state networks (RSNs) and changes in functional connectivity (FC) between RSNs in patients with FCon. Thus, the current study aimed to identify abnormal FC within and interaction between RSNs in patients with FCon to reveal the underlying neural mechanism. METHODS: Functional MRI with independent component analysis was applied to investigate alterations in FC within and functional network connectivity (FNC) between RSNs including default mode- (DMN), basal ganglia- (BGN), salience- (SN), and left and right control executive-networks (LCEN/RCEN) in 39 female patients with FCon and 36 female healthy controls (HC). Patient Assessment of Constipation Quality of Life Scale (PAC-QOL) and Patient Assessment of Constipation Symptom Scale (PAC-SYM) were used to assess the constipation symptoms. RESULTS: FCon patients had changed regional FC between different networks contributing to the abnormal FNC among RSNs compared with HC. Patients with greater stool syndromes had increased FNC of BGN-SN and DMN-LCEN, and patients with greater worries/concerns and PAC-QOL total score had reduced FNC of SN-RCEN. The greater strength changes in FC in prefrontal and parietal cortices were associated with higher negative emotion scores and greater rectal symptoms, respectively. CONCLUSION: The findings suggested that FCon patients had altered FC within and interactions between RSNs and the brain FC changes were associated with constipation symptoms and altered emotions.

Distinct Basal Brain Functional Activity and Connectivity in the Emotional-Arousal Network and Thalamus in Patients With Functional Constipation Associated With Anxiety and/or Depressive Disorders.

OBJECTIVE: Functional constipation (FC) is a common gastrointestinal disorder. Anxiety and/or depressive disorders are common in patients with FC (FCAD). Brain dysfunction may play a role in FC, but the contribution of comorbid anxiety and/or depression in patients with FC is poorly understood. METHODS: Sixty-five FC patients and 42 healthy controls (HCs) were recruited, and a hierarchical clustering algorithm was used to classify FC patients into FCAD and patients without anxiety/depressive status (FCNAD) based on neuropsychological assessment. Resting-state functional magnetic resonance imaging measures including fractional amplitude of low-frequency fluctuation (fALFF) and functional connectivity were used to investigate brain functional differences. RESULTS: Thirty-seven patients were classified as FCAD, and 28 patients were classified as FCNAD; as compared with HC, both groups showed decreased activity (fALFF) in the perigenual anterior cingulate cortex (pACC), dorsomedial prefrontal cortex (DMPFC), and precuneus; enhanced precentral gyrus-thalamus connectivity and attenuated precuneus-thalamus connectivity in FCAD/FCNAD highlighted the thalamus as a critical connectivity node in the brain network (pFWE < .05). In comparison with FCNAD/HC, the FCAD group also had decreased fALFF in the orbitofrontal cortex (OFC) and thalamus, and increased OFC-hippocampus connectivity. In the FCNAD group, brain activities (pACC/DMPFC) and connection (precuneus-thalamus) had correlations only with symptoms; in the FCAD group, brain activities (OFC, pACC/DMPFC) and connectivities (OFC-hippocampus/precentral gyrus-thalamus) showed correlations with both constipation symptoms and anxiety/depressive status ratings. Mediation analysis indicated that the relationship between abdominal distension and OFC activity was completely mediated by anxiety in FCAD. CONCLUSIONS: These findings provide evidence of differences in brain activity and functional connectivity between FCAD and FCNAD, potentially providing important clues for improving treatment strategies.

CHIMGEN: a Chinese imaging genetics cohort to enhance cross-ethnic and cross-geographic brain research.

The Chinese Imaging Genetics (CHIMGEN) study establishes the largest Chinese neuroimaging genetics cohort and aims to identify genetic and environmental factors and their interactions that are associated with neuroimaging and behavioral phenotypes. This study prospectively collected genomic, neuroimaging, environmental, and behavioral data from more than 7000 healthy Chinese Han participants aged 18-30 years. As a pioneer of large-sample neuroimaging genetics cohorts of non-Caucasian populations, this cohort can provide new insights into ethnic differences in genetic-neuroimaging associations by being compared with Caucasian cohorts. In addition to micro-environmental measurements, this study also collects hundreds of quantitative macro-environmental measurements from remote sensing and national survey databases based on the locations of each participant from birth to present, which will facilitate discoveries of new environmental factors associated with neuroimaging phenotypes. With lifespan environmental measurements, this study can also provide insights on the macro-environmental exposures that affect the human brain as well as their timing and mechanisms of action.

MR imaging of thymomas: a combined radiomics nomogram to predict histologic subtypes.

OBJECTIVES: Accurately predicting the WHO classification of thymomas is urgently needed to optimize individualized therapeutic strategies. We aimed to develop and validate a combined radiomics nomogram for personalized prediction of histologic subtypes in patients with thymomas. METHODS: A total of 182 thymoma patients were divided into training (n = 128) and test (n = 54) cohorts. Radiomics features were extracted from T2-weighted, T2-weighted fat suppression, and diffusion-weighted images to establish a radiomics signature in the training cohort. Multivariate logistic regression analysis was used to develop a combined radiomics nomogram that incorporated clinical, conventional MR imaging variables, apparent diffusion coefficient (ADC) value, and radiomics signature. The efficacy of clinical, conventional MR imaging, or ADC model was also evaluated respectively. The performances of different models were compared by receiver operating characteristic analysis and Delong test. The discrimination, calibration, and clinical usefulness of the combined radiomics nomogram were assessed. RESULTS: The radiomics signature, consisting of 14 features, achieved favorable predictive efficacy in differentiating low-risk from high-risk thymomas, outperforming clinical, conventional MR imaging, and ADC models. The combined radiomics nomogram incorporating tumor shape, ADC value, and radiomics signature yielded the best performance (training cohort: area under the curve [AUC] = 0.946, test cohort: AUC = 0.878). The calibration curve and decision curve analysis indicated the clinical utility of the combined radiomics nomogram. CONCLUSIONS: The radiomics signature is a useful tool that can be used to predict histologic subtypes of thymomas. The combined radiomics nomogram improved the individualized subtype prediction in patients with thymomas. KEY POINTS: • Fourteen robust features were selected to develop a radiomics signature for preoperative prediction of thymoma subtype. • MRI-based radiomics signature can differentiate low-risk thymomas from high-risk thymomas with favorable predictive efficacy compared with clinical, conventional MR imaging, and ADC models. • Combined radiomics nomogram based on tumor shape, ADC value, and radiomics signature could improve the individualized subtype prediction in patients with thymomas.