Value of turbo spin echo-based diffusion-weighted imaging in the differential diagnosis of benign and malignant solitary pulmonary lesions.

To quantitatively assess the diagnostic efficacy of multiple parameters derived from multi-b-value diffusion-weighted imaging (DWI) using turbo spin echo (TSE)-based acquisition techniques in patients with solitary pulmonary lesions (SPLs). A total of 105 patients with SPLs underwent lung DWI using single-shot TSE-based acquisition techniques and multiple b values. The apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) parameters, and lesion-to-spinal cord signal intensity ratio (LSR), were analyzed to compare the benign and malignant groups using the Mann-Whitney U test and receiver operating characteristic analysis. The Dstar values observed in lung cancer were slightly lower than those observed in pulmonary benign lesions (28.164 ± 31.950 versus 32.917 ± 34.184; Z = -2.239, p = 0.025). The LSR values were significantly higher in lung cancer than in benign lesions (1.137 ± 0.581 versus 0.614 ± 0.442; Z = - 4.522, p < 0.001). Additionally, the ADC800, ADCtotal, and D values were all significantly lower in lung cancer than in the benign lesions (Z = - 5.054, -5.370, and -6.047, respectively, all p < 0.001), whereas the f values did not exhibit any statistically significant difference between the two groups. D had the highest area under the curve (AUC = 0.887), followed by ADCtotal (AUC = 0.844), ADC800 (AUC = 0.824), and LSR (AUC = 0.789). The LSR, ADC800, ADCtotal, and D values did not differ statistically significantly in diagnostic effectiveness. Lung DWI using TSE is feasible for differentiating SPLs. The LSR method, conventional DWI, and IVIM have comparable diagnostic efficacy for assessing SPLs.

Aberrant brain entropy in posttraumatic stress disorder comorbid with major depressive disorder during the coronavirus disease 2019 pandemic.

Aim: Previously, neuroimaging studies on comorbid Posttraumatic-Major depression disorder (PTSD-MDD) comorbidity found abnormalities in multiple brain regions among patients. Recent neuroimaging studies have revealed dynamic nature on human brain activity during resting state, and entropy as an indicator of dynamic regularity may provide a new perspective for studying abnormalities of brain function among PTSD-MDD patients. During the COVID-19 pandemic, there has been a significant increase in the number of patients with PTSD-MDD. We have decided to conduct research on resting-state brain functional activity of patients who developed PTSD-MDD during this period using entropy. Methods: Thirty three patients with PTSD-MDD and 36 matched TCs were recruited. PTSD and depression symptoms were assessed using multiple clinical scales. All subjects underwent functional magnetic resonance imaging (fMRI) scans. And the brain entropy (BEN) maps were calculated using the BEN mapping toolbox. A two-sample t-test was used to compare the differences in the brain entropy between the PTSD-MDD comorbidity group and TC group. Furthermore, correlation analysis was conducted between the BEN changes in patients with PTSD-MDD and clinical scales. Results: Compared to the TCs, PTSD-MDD patients had a reduced BEN in the right middle frontal orbital gyrus (R_MFOG), left putamen, and right inferior frontal gyrus, opercular part (R_IFOG). Furthermore, a higher BEN in the R_MFOG was related to higher CAPS and HAMD-24 scores in the patients with PTSD-MDD. Conclusion: The results showed that the R_MFOG is a potential marker for showing the symptom severity of PTSD-MDD comorbidity. Consequently, PTSD-MDD may have reduced BEN in frontal and basal ganglia regions which are related to emotional dysregulation and cognitive deficits.

Altered Cerebral Blood Flow in the Progression of Chronic Kidney Disease.

Background: In chronic kidney disease (CKD), cognitive impairment is a definite complication. However, the mechanisms of how CKD leads to cognitive impairment are not clearly known. Methods: Cerebral blood flow (CBF) information was collected from 37 patients with CKD (18 in stage 3; 19 in stage 4) and 31 healthy controls (HCs). For CKD patients, we also obtained laboratory results as well as neuropsychological tests. We conducted brain perfusion imaging studies using arterial spin labeling and calculated the relationship between regional CBF changes and various clinical indicators and neuropsychological tests. We also generated receiver operator characteristic (ROC) curves to explore whether CBF value changes in certain brain regions can be used to identify CKD. Results: Compared with HCs, CBF decreased in the right insula and increased in the left hippocampus in the CKD4 group; through partial correlation analysis, we found that CBF in the right insula was negatively correlated with the number connection test A (NCT-A) (r = −0.544, p = 0.024); CBF in the left hippocampus was positively correlated with blood urea nitrogen (r = 0.649, p = 0.005) and negatively correlated with serum calcium level (r = −0.646, p = 0.005). By comparing the ROC curve area, it demonstrated that altered CBF values in the right insula (AUC = 0.861, p < 0.01) and left hippocampus (AUC = 0.862, p < 0.01) have a good ability to identify CKD. Conclusions: Our study found that CBF alterations in the left hippocampus and the right insula brain of adult patients with stage 4 CKD were correlated with disease severity or laboratory indicators. These findings provide further insight into the relationship between altered cerebral perfusion and cognitive impairment in patients with non-end-stage CKD as well as, additional information the underlying neuropathophysiological mechanisms.

Patterns of eHealth Website User Engagement Based on Cross-site Clickstream Data: Correlational Study.

BACKGROUND: User engagement is a key performance variable for eHealth websites. However, most existing studies on user engagement either focus on a single website or depend on survey data. To date, we still lack an overview of user engagement on multiple eHealth websites derived from objective data. Therefore, it is relevant to provide a holistic view of user engagement on multiple eHealth websites based on cross-site clickstream data. OBJECTIVE: This study aims to describe the patterns of user engagement on eHealth websites and investigate how platforms, channels, sex, and income influence user engagement on eHealth websites. METHODS: The data used in this study were the clickstream data of 1095 mobile users, which were obtained from a large telecom company in Shanghai, China. The observation period covered 8 months (January 2017 to August 2017). Descriptive statistics, two-tailed t tests, and an analysis of variance were used for data analysis. RESULTS: The medical category accounted for most of the market share of eHealth website visits (134,009/184,826, 72.51%), followed by the lifestyle category (46,870/184,826, 25.36%). The e-pharmacy category had the smallest market share, accounting for only 2.14% (3947/184,826) of the total visits. eHealth websites were characterized by very low visit penetration and relatively high user penetration. The distribution of engagement intensity followed a power law distribution. Visits to eHealth websites were highly concentrated. User engagement was generally high on weekdays but low on weekends. Furthermore, user engagement gradually increased from morning to noon. After noon, user engagement declined until it reached its lowest level at midnight. Lifestyle websites, followed by medical websites, had the highest customer loyalty. e-Pharmacy websites had the lowest customer loyalty. Popular eHealth websites, such as medical websites, can effectively provide referral traffic for lifestyle and e-pharmacy websites. However, the opposite is also true. Android users were more engaged in eHealth websites than iOS users. The engagement volume of app users was 4.85 times that of browser users, and the engagement intensity of app users was 4.22 times that of browser users. Male users had a higher engagement intensity than female users. Income negatively moderated the influence that platforms (Android vs iOS) had on user engagement. Low-income Android users were the most engaged in eHealth websites. Conversely, low-income iOS users were the least engaged in eHealth websites. CONCLUSIONS: Clickstream data provide a new way to derive an overview of user engagement patterns on eHealth websites and investigate the influence that various factors (eg, platform, channel, sex, and income) have on engagement behavior. Compared with self-reported data from a questionnaire, cross-site clickstream data are more objective, accurate, and appropriate for pattern discovery. Many user engagement patterns and findings regarding the influential factors revealed by cross-site clickstream data have not been previously reported.

Abnormal white matter within brain structural networks is associated with high-impulse behaviour in codeine-containing cough syrup dependent users.

Codeine-containing cough syrup (CCS) is considered as one of the most popular drug of dependence among adolescents because of its inexpensiveness and easy availability. However, its relationship with neurobiological effects remains sparsely explored. Herein, we examined how high-impulse behaviours relate to changes in the brain structural networks. Forty codeine-containing cough syrup dependent (CCSD) users and age-, gender-, and number of cigarettes smoked per day -matched forty healthy control (HC) subjects underwent structural brain imaging via MRI. High-impulse behaviour was assessed using the 30-item self-rated Barratt Impulsiveness Scale (BIS-11), and structural networks were constructed using diffusion tensor imaging and AAL-90 template. Between-group topological metrics were compared using nonparametric permutations. Benjamin-Hochberg false discovery rate correction was used to correct for multiple comparisons (P < 0.05). The relationships between abnormal network metrics and clinical characteristics of CCS dependent (BIS-11 total score, CCS- dependent duration and mean dose) were examined by Spearman's correlation. Structural networks of the CCSD group demonstrated lower small-world properties than those of the HC group. Abnormal changes in nodal properties among CCSD users were located mainly in the frontal gyrus, inferior parietal lobe and olfactory cortex. NBS analysis further indicated disrupted structural connections between the frontal gyrus and multiple brain regions. There were significant correlations between abnormal nodal properties of the frontal gyrus and clinical characteristics (BIS-11 total score, CCS dependent duration and mean dose) in the CCSD group. These findings suggest that the high-impulse behavioural expression in CCS addiction is associated with widespread brain regions, particularly within those in the frontal cortex. Aberrant brain regions and disrupted connectivity of structural network may be the bases of neuropathology for underlying symptoms of high-impulse behaviours in CCSD users, which may provide a novel sight to better treat and prevent codeine dependency in adolescents.

Suspected SARS-CoV-2 infection with fever and coronary heart disease: A case report.

BACKGROUND: The coronavirus disease 2019 (COVID-19) is an emerging infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Suspected cases accounted for a large proportion in the early stage of the COVID-19 outbreak. The deviation of the nucleic acid test by throat swab (the current gold standard of COVID-19) caused by variation in sampling techniques and reagent kits and coupled with nonspecific clinical manifestations make confirmation of the suspected cases difficult. Proper management of the suspected cases of COVID-19 is crucial for disease control. CASE SUMMARY: A 65-year-old male presented with fever, lymphopenia, and chest computed tomography (CT) images similar to COVID-19 after percutaneous coronary intervention. The patient was diagnosed as having bacterial pneumonia with cardiogenic pulmonary edema instead of COVID-19. This was based on four negative results for throat swab detection of SARS-CoV-2 nucleic acid using reverse transcriptase-polymerase chain reaction assay and one negative result for serological antibody of SARS-CoV-2 with the serological assay. Additionally, the distribution of ground-glass opacities and thickened blood vessels from the CT images differed from COVID-19 features, which further supported the exclusion of COVID-19. CONCLUSION: Distinguishing COVID-19 patients from those with bacterial pneumonia with cardiogenic pulmonary edema can be difficult. Therefore, it requires serious identification.

Abnormal Rich Club Organization of Structural Network as a Neuroimaging Feature in Relation With the Severity of Primary Insomnia.

PURPOSE: Insomnia is the most prevalent sleep complaint in the general population but is often intractable due to uncertainty regarding the underlying pathomechanisms. Sleep is regulated by a network of neural structures interconnected with the core nodes of the brain connectome referred to as the "rich club". We examined alterations in brain rich-club organization as revealed by diffusion tensor imaging (DTI) and the statistical relationships between abnormalities in rich-club metrics and the clinical features of primary insomnia (PI). METHODS: This study recruited 43 primary insomnia (PI) patients and 42 age-, sex-, and education level-matched healthy controls (HCs). Differences in global and regional network parameters between PI and healthy control groups were compared by nonparametric tests, and Spearman's correlations were calculated to assess associations of these network metrics with PI-related clinical features, including disease duration and scores on the Pittsburgh Sleep Quality Index, Insomnia Severity Index, Self-Rating Anxiety Scale, and Self-Rating Depression Scale. RESULTS: Weighted white matter networks exhibited weaker rich-club organization in PI patients than HCs across different thresholds (50%, 75%, and 90%) and parcellation schemes [automated anatomical labeling (AAL)-90 and AAL-1024]. Aberrant rich-club organization was found mainly in limbic-cortical-basal ganglia circuits and the default-mode network. CONCLUSIONS: Abnormal rich-club metrics are a characteristic feature of PI-related to disease severity. These metrics provide potential clues to PI pathogenesis and may be useful as diagnostic markers and for assessment of treatment response.

Aberrant regional homogeneity in post-traumatic stress disorder after traffic accident: A resting-state functional MRI study.

OBJECTIVES: The present study explored the changes in spontaneous regional activity in post-traumatic stress disorder (PTSD) patients, who experienced severe traffic accidents. METHODS: 20 drug-naive PTSD patients and 18 healthy control subjects were imaged using resting-state functional magnetic resonance imaging (rs-fMRI) and analyzed by the algorithm of regional homogeneity (ReHo). RESULTS: Compared to the healthy control group, the PTSD group showed decreased ReHo values in the right angular gyrus. In addition, a negative correlation was found between the activity level of the angular gyrus and the CAPS score. CONCLUSION: The dysfunctions were found in the memory- and emotion-related areas, suggested a possible mechanism of memory dysregulation that might be related to the intrusive memory symptoms of PTSD. These results provided imaging evidence that might provide an in-depth understanding of the intrinsic functional architecture of PTSD.

Abnormal degree centrality in chronic users of codeine-containing cough syrups: A resting-state functional magnetic resonance imaging study.

Codeine-containing cough syrups (CCS) have become one of the most popular drugs of abuse in young population worldwide. However, the neurobiological mechanisms underlying CCS-dependence are yet ill-defined. Therefore, understanding the brain abnormalities in chronic users of CCS is crucial for developing effective interventions. The present study depicted the intrinsic dysconnectivity pattern of whole-brain functional networks at the voxel level in chronic users of CCS. In addition, the degree centrality (DC) changes were correlated to the Barratt Impulsiveness Scale (BIS-11) total score, dose, duration of CCS use, and the age at first use of cough syrups. The current study included 38 chronic CCS users and 34 matched control subjects. All patients were evaluated using the BIS-11. Next, resting-state functional magnetic resonance imaging (rs-fMRI) datasets were acquired from these CCS users and controls. Whole-brain connectivity was analyzed using a graph theory approach: degree centrality (DC). CCS-dependent individuals exhibited low DC values in the left inferior parietal lobule and the left middle temporal gyrus, while high DC values were noted in the right pallidum and the right hippocampus (P < 0.01, AlphaSim corrected). Also, significant correlations were established between average DC value in the left inferior parietal lobule and attentional impulsivity scores and the age at first CCS use. The rs-fMRI study suggested that the abnormal intrinsic dysconnectivity pattern of whole-brain functional networks may provide an insight into the neural substrates of abnormalities in the cognitive control circuit, the reward circuit, and the learning and memory circuit in CCS-dependent individuals.