MRI characteristics predict BRAF V600E status in gangliogliomas and pleomorphic xanthoastrocytomas and provide survival prognostication.

BACKGROUND: BRAF V600E mutation is a common genomic alteration in gangliogliomas (GGs) and pleomorphic xanthoastrocytomas (PXAs) with prognostic and therapeutic implications. PURPOSE: To investigate the ability of magnetic resonance imaging (MRI) features to predict BRAF V600E status in GGs and PXAs and their prognostic values. MATERIAL AND METHODS: A cohort of 44 patients with histologically confirmed GGs and PXAs was reviewed retrospectively. BRAF V600E status was determined by immunohistochemistry (IHC) staining and fluorescence quantitative polymerase chain reaction (PCR). Demographics and MRI characteristics of the two groups were evaluated and compared. Univariate and multivariate Cox regression analyses were performed to identify MRI features that were prognostic for progression-free survival (PFS). RESULTS: T1/FLAIR ratio, enhancing margin, and mean relative apparent diffusion coefficient (rADCmea) value showed significant differences between the BRAF V600E-mutant and BRAF V600E-wild groups (all P < 0.05). Binary logistic regression analysis revealed only rADCmea value was the independent predictive factor for BRAF V600E status (P = 0.027). Univariate Cox regression analysis showed age at diagnosis (P = 0.032), WHO grade (P = 0.020), enhancing margin (P = 0.029), and rADCmea value (P = 0.005) were significant prognostic factors for PFS. In multivariate Cox regression analysis, increasing age (P = 0.040, hazard ratio [HR] = 1.04, 95% confidence interval [CI] = 1.002-1.079) and lower rADCmea values (P = 0.021, HR = 0.036, 95% CI = 0.002-0.602) were associated with poor PFS in GGs and PXAs. CONCLUSION: Imaging features are potentially predictive of BRAF V600E status in GGs and PXAs. Furthermore, rADCmea value is a valuable prognostic factor for patients with GGs or PXAs.

Characterization of parotid gland tumors: Whole-tumor histogram analysis of diffusion weighted imaging, diffusion kurtosis imaging, and intravoxel incoherent motion - A pilot study.

PURPOSE: To investigate the diagnostic performance of histogram features of diffusion parameters in characterizating parotid gland tumors. METHOD: From December 2018 to January 2023, patients who underwent diffusion weighted imaging (DWI), diffusion kurtosis imaging (DKI), and intravoxel incoherent motion (IVIM) were consecutively enrolled in this retrospective study. The histogram features of diffusion parameters, including apparent diffusion coefficient (ADC), diffusion coefficient (Dk), diffusion kurtosis (K), pure diffusion coefficient (D), pseudo-diffusion coefficient (DP), and perfusion fraction (FP) were analyzed. The Mann-Whitney U test was used for comparison between benign parotid gland tumors (BPGTs) and malignant parotid gland tumors (MPGTs). Receiver operating characteristic curve and logistic regression analysis were used to identify the differential diagnostic performance. The Spearman's correlation coefficient was used to analyze the correlation between diffusion parameters and Ki-67 labeling index. RESULTS: For diffusion MRI, twenty-three histogram features of diffusion parameters showed significant differences between BPGTs and MPGTs (all P < 0.05). Compared with the DWI model, the IVIM model and combined model had better diagnostic specificity (58 %, 94 %, and 88 %, respectively; both corrected P < 0.001) and accuracy (64 %, 89 %, and 86 %, respectively; both corrected P = 0.006). The combined model was superior to the single DWI model with improved IDI (IDI improvement 0.25). Significant correlations were found between Ki-67 and ADCmean, Dkmean, Kmean, and Dmean (r = -0.57 to 0.53; all P < 0.05). CONCLUSIONS: Whole-tumor histogram analysis of IVIM and combined diffusion model could further improve the diagnostic performance for differentiating BPGTs from MPGTs.

Environmental Determinants for Snail Density in Dongting Lake Region: An Ecological Study Incorporating Spatial Regression.

This study explored the environmental determinants of different months on snail density measured in April at different types of snail habitats (marshlands, inner embankments, and hills) by considering spatial effects. Data were gathered from surveys on snails that were conducted in Hunan Province in April 2016, and information was collected on environmental variables. To investigate the environmental factors influencing snail density in various types of snail habitats, the ordinary least square model, spatial lag model, and spatial error model were all used. The environmental determinants for snail density showed different effects in the three types of snail habitats. In marshlands, snail density measured in April was associated positively with the normalized difference vegetation index (NDVI) and was associated negatively with flooding duration and annual hours of sunshine. Extreme temperatures correlated strongly to snail density measured in April (P < 0.05). In areas inside embankments, snail density measured in April increased with a decreased distance between snail habitat and the nearest river (P < 0.05). In hills, extreme heat, annual hours of sunshine, NDVI in September, and annual average land surface temperature (LST) were associated negatively with snail density measured in April, whereas index of moisture (IM) was associated positively with snail density measured in April (P < 0.05). The effects of LST and hours of sunshine on snail density measured in April varied with months of the year in the three different types of snail habitats (P < 0.05). Our study might provide a theoretical foundation for preventing snail transmission and subsequent spread of schistosomiasis.

Performances of clinical characteristics and radiological findings in identifying COVID-19 from suspected cases.

BACKGROUND: To identify effective factors and establish a model to distinguish COVID-19 patients from suspected cases. METHODS: The clinical characteristics, laboratory results and initial chest CT findings of suspected COVID-19 patients in 3 institutions were retrospectively reviewed. Univariate and multivariate logistic regression were performed to identify significant features. A nomogram was constructed, with calibration validated internally and externally. RESULTS: 239 patients from 2 institutions were enrolled in the primary cohort including 157 COVID-19 and 82 non-COVID-19 patients. 11 features were selected by LASSO selection, and 8 features were found significant using multivariate logistic regression analysis. We found that the COVID-19 group are more likely to have fever (OR 4.22), contact history (OR 284.73), lower WBC count (OR 0.63), left lower lobe involvement (OR 9.42), multifocal lesions (OR 8.98), pleural thickening (OR 5.59), peripheral distribution (OR 0.09), and less mediastinal lymphadenopathy (OR 0.037). The nomogram developed accordingly for clinical practice showed satisfactory internal and external validation. CONCLUSIONS: In conclusion, fever, contact history, decreased WBC count, left lower lobe involvement, pleural thickening, multifocal lesions, peripheral distribution, and absence of mediastinal lymphadenopathy are able to distinguish COVID-19 patients from other suspected patients. The corresponding nomogram is a useful tool in clinical practice.

Longitudinal Radiological Findings in Patients With COVID-19 With Different Severities: From Onset to Long-Term Follow-Up After Discharge.

Objective: This study aimed to investigate the evolution of radiological findings in the patients with coronavirus disease 2019 (COVID-19) pneumonia with different severities from onset to 1-year follow-up and identify the predictive factors for different pulmonary lesion absorption status in the patients infected with COVID-19. Methods: A retrospective study was performed on the clinical and radiological features of 175 patients with COVID-19 pneumonia hospitalized at three institutions from January 21 to March 20, 2020. All the chest CT scans during hospitalization and follow-ups after discharge were collected. The clinical and radiological features from the chest CT scans both at the peak stage and before discharge from the hospital were used to predict whether the pulmonary lesions would be fully absorbed after discharge by Cox regression. Then, these patients were stratified into two groups with different risks of pulmonary lesion absorption, and an optimal timepoint for the first CT follow-up was selected accordingly. Results: A total of 132 (75.4%) patients were classified into the non-severe group, and 43 (24.6%) patients were classified into the severe group, according to the WHO guidelines. The opacification in both the groups changed from ground-glass opacity (GGO) to consolidation and then from consolidation to GGO. Among the 175 participants, 135 (112 non-severe and 23 severe patients with COVID-19) underwent follow-up CT scans after discharge. Pulmonary residuals could be observed in nearly half of the patients (67/135) with the presentation of opacities and parenchymal bands. The parenchymal bands in nine discharged patients got fully absorbed during the follow-up periods. The age of patient [hazard ratio (HR) = 0.95, 95% CI, 0.95-0.99], level of lactate dehydrogenase (LDH) (HR = 0.99; 95% CI, 0.99-1.00), level of procalcitonin (HR = 8.72; 95% CI, 1.04-73.03), existence of diffuse lesions (HR = 0.28; 95% CI, 0.09-0.92), subpleural distribution of lesions (HR = 2.15; 95% CI, 1.17-3.92), morphology of residuals (linear lesion: HR = 4.58, 95% CI, 1.22-17.11; nodular lesion: HR = 33.07, 95% CI, 3.58-305.74), and pleural traction (HR = 0.41; 95% CI, 0.22-0.78) from the last scan before discharge were independent factors to predict the absorption status of COVID-19-related pulmonary abnormalities after discharge. According to a Kaplan-Meier analysis, the probability of patients of the low-risk group to have pulmonary lesions fully absorbed within 90 days reached 91.7%. Conclusion: The development of COVID-19 lesions followed the trend from GGO to consolidation and then from consolidation to GGO. The CT manifestations and clinical and laboratory variables before discharge could help predict the absorption status of pulmonary lesions after discharge. The parenchymal bands could be fully absorbed in some COVID-19 cases. In this study, a Cox regression analysis indicated that a timepoint of 3 months since onset was optimal for the radiological follow-up of discharged patients.

Distance to highway and factory density related to lung cancer death and associated spatial heterogeneity in effects in Jiading District, Shanghai.

This study aimed to determine the spatial effects of traffic- and industrial-related pollution on the mortality for lung cancer (LC). We conducted a retrospective cohort study by using the data from LC registry in Jiading District for the period from 2002 to 2012. Standard parametric model with Weibull distribution was used for spatial survival analysis. Shorter distance to highway (adjusted odds ratio (aOR) = 1.15, 95% confidence interval (CI): 1.03-1.30) and higher factory density (aOR = 1.20, 95% CI: 1.05-1.37) were significantly associated with an increased risk of LC death, and there was a spatial difference in the associations between northern and southern areas of Jiading District. The risk was high in suburbs as compared with urban areas. Traffic- and industrial-related pollution were significantly associated with an increased risk of LC death, which showed a spatial variation. Further studies are needed to better understand the current LC status in the suburbs and to reduce health disparities.

Machine learning algorithms to predict the 1 year unfavourable prognosis for advanced schistosomiasis.

Short-term prognosis of advanced schistosomiasis has not been well studied. We aimed to construct prognostic models using machine learning algorithms and to identify the most important predictors by utilising routinely available data under the government medical assistance programme. An established database of advanced schistosomiasis in Hunan, China was utilised for analysis. A total of 9541 patients for the period from January 2008 to December 2018 were enrolled in this study. Candidate predictors were selected from demographics, clinical features, medical examinations and test results. We applied five machine learning algorithms to construct 1 year prognostic models: logistic regression (LR), decision tree (DT), random forest (RF), artificial neural network (ANN) and extreme gradient boosting (XGBoost). An area under the receiver operating characteristic curve (AUC) was used to evaluate the model performance. The important predictors of the optimal model for unfavourable prognosis within 1 year were identified and ranked. There were 1249 (13.1%) cases having unfavourable prognoses within 1 year of discharge. The mean age of all participants was 61.94 years, of whom 70.9% were male. In general, XGBoost showed the best predictive performance with the highest AUC (0.846; 95% confidence interval (CI): 0.821, 0.871), compared with LR (0.798; 95% CI: 0.770, 0.827), DT (0.766; 95% CI: 0.733, 0.800), RF (0.823; 95% CI: 0.796, 0.851), and ANN (0.806; 95% CI: 0.778, 0.835). Five most important predictors identified by XGBoost were ascitic fluid volume, haemoglobin (HB), total bilirubin (TB), albumin (ALB), and platelets (PT). We proposed XGBoost as the best algorithm for the evaluation of a 1 year prognosis of advanced schistosomiasis. It is considered to be a simple and useful tool for the short-term prediction of an unfavourable prognosis for advanced schistosomiasis in clinical settings.

Cohort study of patients with Stevens-Johnson syndrome and toxic epidermal necrolysis in China: evaluation of risk models and new predictor of pulmonary consolidation on computed tomography.

Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are rare but severe diseases. This study aimed to validate the predictive ability of risk models in patients with SJS/TEN and propose possible refinement in China. Patients in the Department of Dermatology of Huashan Hospital from January 2008 to January 2019 were included. Results showed that the severity-of-illness score for TEN (SCORTEN) had a good discrimination (area under the receiver operating characteristic curve (AUC), 0.78), and it was superior to auxiliary score (AS) and ABCD-10, which indicates age, bicarbonate level, cancer, dialysis, and 10% involved body surface area (AUC, 0.69 and 0.68, respectively). The calibration of SCORTEN (Hosmer-Lemeshow goodness-of-fit test, P = 0.69) was also better than that of AS (P = 0.25) and ABCD-10 (P = 0.55). SCORTEN and ABCD-10 were similar (Brier score (BS), 0.04 and 0.04) in terms of accuracy of predictions. In addition, the imaging appearance of pulmonary consolidation on computed tomography was associated with high mortality. Refined models were formed using the variables and this imaging appearance. The refined AS and ABCD-10 models were similar in discrimination compared with the original SCORTEN (0.74 vs. 0.78, P = 0.23; 0.74 vs. 0.78, P = 0.30, respectively). Therefore, SCORTEN showed good discrimination performance, calibration, and accuracy, and refined AS or ABCD-10 model may be an option when SCORTEN variables are not available.

Inequalities in changing mortality and life expectancy in Jiading District, Shanghai, 2002-2018.

BACKGROUND: Improvements of population health in China have been unevenly distributed among different sexes and regions. Mortality Registration System provides an opportunity for timely assessments of mortality trend and inequalities. METHODS: Causes of death were reclassified following the method of Global Burden of Disease Study (GBD). Age-standardized mortality rate (ASMR) and ring-map of the rate by town were used to describe inequalities in changing mortality. Life expectancy (LE) and cause-deleted LE were calculated on the basis of life table technique. RESULTS: The burden of death from 2002 to 2018 was dominated by cardiovascular diseases (CVD), neoplasms, chronic respiratory diseases and injuries in Jiading district, accounting for almost 80% of total deaths. The overall ASMR dropped from 407.6/100000 to 227.1/100000, and LE increased from 77.86 years to 82.31 years. Women lived about 3.0-3.5 years longer than men. Besides, a cluster of lower LE was found for CVD in the southeast corner and one cluster for neoplasms in the southern corner of the district. The largest individual contributor to increment in LE was neoplasms, ranged from 2.41 to 3.63 years for males, and from 1.60 to 2.36 years for females. CONCLUSIONS: Improvement in health was mainly attributed to the decline of deaths caused by CVD and neoplasms, but was distributed with sex and town. This study served as a reflection of health inequality, is conducive to formulate localized health policies and measures.

Geographical Variation of COPD Mortality and Related Risk Factors in Jiading District, Shanghai.

Background: Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in China. Although numerous studies have been conducted to determine the risk factors for COPD mortality such as ambient air pollution, the results are not fully consistent. Methods: This study included mortality analysis and a case-control design by using the data extracted from the Mortality Registration System in Jiading District, Shanghai. Traditional logistic regression, geographically weighted logistic regression (GWLR), and spatial scan statistical analysis were performed to explore the geographic variation of COPD mortality and the possible influencing factors. Results: Traditional logistic regression showed that extreme lower temperature in the month prior to death, shorter distance to highway, lower GDP level were associated with increased COPD mortality. GWRL model further demonstrated obvious geographical discrepancies for the above associations. We additionally identified a significant cluster of low COPD mortality (OR = 0.36, P = 0.002) in the southwest region of Jiading District with a radius of 3.55 km by using the Bernoulli model. The geographical variation in age-standardized mortality rate for COPD in Jiading District was explained to a certain degree by these factors. Conclusion: The risk of COPD mortality in Jiading District showed obvious geographical variation, which were partially explained by the geographical variations in effects of the extreme low temperature in the month prior to death, residential proximity to highway, and GDP level.

Prevalence and incidence of advanced schistosomiasis and risk factors for case fatality in Hunan Province, China.

Advanced schistosomiasis has become a major public health problem in areas with a heavy burden of schistosomiasis infection. Our objective was to determine the incidence and prevalence of advanced schistosomiasis and risk factors associated with case fatality of advanced schistosomiasis. Data were abstracted from hospitalization records of patients with advanced schistosomiasis from Hunan Province, China. The incidence and prevalence of advanced schistosomiasis were determined and the risk factors for death in advanced patients were assessed using logistic regression analysis. A total of 10,362 patients with advanced schistosomiasis were recruited into our study and 65% of them were categorized as the ascites type. There were 1249 deaths between 2005 and 2018 and the case fatality was 12.05%. The incidence of advanced schistosomiasis increased from 2002 to 2010, peaked in 2010 and then leveled off. The prevalence of advanced schistosomiasis increased from 2005 to 2014, and was stable afterwards. HBV was a risk factor for death in advanced patients (adjusted odds ratio (aOR=1.93, 95% confidence interval (CI: 1.55 to 2.41). Patients without splenectomy had a higher risk of death (aOR=1.29, 95%CI: 1.08 to 1.56). Upper gastrointestinal bleeding was positively associated with the risk of death (aOR=1.42, 95% CI: 1.15 to 1.76). Besides, abnormal ALT, ascites and anemia were also significantly associated with the risk of death in advanced patients. Advanced schistosomiasis was effectively controlled in recent years. Splenectomy could reduce the case fatality of advanced patients. HBV infection, abnormal ALT, upper gastrointestinal bleeding and anemia also predicted the risk of death for advanced patients.

Spatio-temporal variations of emerging sites infested with schistosome-transmitting Oncomelania hupensis in Hunan Province, China, 1949-2016.

BACKGROUND: Constant emerging sites infested with Oncomelania hupensis (O. hupensis) impede the goal realization of eliminating schistosomiasis. The study assessed the spatial and temporal distributions of new Oncomelania snail habitats in Hunan Province from 1949 to 2016. METHODS: We used the data from annual snail surveys throughout Hunan Province for the period from 1949 to 2016. Global Moran's I, Anselin local Moran's I statistics (LISA) and a retrospective space-time permutation model were applied to determine the spatial and temporal distributions of emerging snail-infested sites. RESULTS: There were newly discovered snail-infested sites almost every year in 1949-2016, except for the years of 1993, 2009 and 2012. The number of emerging sites varied significantly in the five time periods (1949-1954, 1955-1976, 1977-1986, 1986-2003 and 2004-2016) (H = 25.35, p < 0.05). The emerging sites lasted 37.52 years in marshlands, 30.04 years in hills and 24.63 at inner embankments on average, with the values of Global Moran's I being 0.52, 0.49 and 0.44, respectively. High-value spatial clusters (HH) were mainly concentrated along the Lishui River and in Xiangyin County. There were four marshland clusters, two hill clusters and three inner embankment clusters after 1976. CONCLUSIONS: Lower reaches of the Lishui River and the Dongting Lake estuary were the high-risk regions for new Oncomelania snail habitats with long durations. Snail surveillance should be strengthened at stubborn snail-infested sites at the inner embankments. Grazing prohibition in snail-infested grasslands should be a focus in marshlands. The management of bovines in Xiangyin County is of great importance.

Prognostic value of pretreatment MRI texture features in breast cancer brain metastasis treated with Gamma Knife radiosurgery.

BACKGROUND: Gamma Knife radiosurgery (GKS) was recommended for treating patients with breast cancer brain metastasis (BCBM), but predictions of the existing prognostic models for therapeutic responsiveness vary substantially. PURPOSE: To investigate the prognostic value of pretreatment clinical, MRI radiologic, and texture features in patients with BCBM undergoing GKS. MATERIAL AND METHODS: The data of 81 BCBMs in 44 patients were retrospectively reviewed. Progressive disease was defined as an increase of at least 20% in the longest diameter of the target lesion or the presence of new intracranial lesions on contrast-enhanced T1-weighted (CE-T1W) imaging. Radiomic features were extracted from pretreatment CE-T1W images, T2-weighted (T2W) images, and ADC maps. Cox proportional hazard analyses were performed to identify independent predictors associated with BCBM-specific progression-free survival (PFS). A nomogram was constructed and its calibration ability was assessed. RESULTS: The cumulative BCBM-specific PFS was 52.27% at six months and 11.36% at one year, respectively. Age (hazard ratio [HR] 1.04; 95% confidence interval [CI] 1.01-1.06; P = 0.004) and CE-T1W-based kurtosis (HR 0.72; 95% CI 0.57-0.92; P = 0.008) were the independent predictors. The combination of CE-T1W-based kurtosis and age displayed a higher C-index (C-index 0.70; 95% CI 0.63-0.77) than did CE-T1W-based kurtosis (C-index 0.65; 95% CI 0.57-0.73) or age (C-index 0.63; 95% CI 0.56-0.70) alone. The nomogram based on the combinative model provided a better performance over age (P < 0.05). The calibration curves elucidated good agreement between prediction and observation for the probability of 7- and 12-month BCBM-specific PFS. CONCLUSION: Pretreatment CE-T1W-based kurtosis combined with age could improve prognostic ability in patients with BCBM undergoing GKS.

Magnetic resonance imaging differentiates locoregional flaps from free flaps after reconstructive surgical treatment of tongue cancer.

OBJECTIVE: The aim of this study was to compare magnetic resonance imaging (MRI) features of reconstruction with locoregional flaps (LRFs) with free flaps (FFs) after surgical treatment for tongue cancer. STUDY DESIGN: In total, 115 cases of postoperative tongue carcinoma (67 cases of LRF surgery and 48 cases of FF surgery) were retrospectively reviewed. All patients had undergone nonenhanced and contrast-enhanced MRI at 0-4, 5-12, and 13-48 months after surgery. Signal intensity, margins, maximal size, contrast enhancement, change in the hyoglossus and mylohyoid muscles, recurrence, lymph node metastasis, and complications were evaluated. RESULTS: Significant differences were found between LRF and FF for signal intensity (P < .001) in all 3 periods, with LRF mostly isointense with muscle on T1-weighted images (T1WIs) and FF producing mixed hyperintensity with muscular striations in all cases in T1WIs and T2-weighted images (T2 WIs). Margin definition was similar between groups in the early period, but sharp margins were more common in FF after 4 months (P ≤ .018). LRF was significantly smaller than FF in all periods (P ≤ .017). Both mylohyoid and hyoglossus enlargements were common in the early period in both groups, but all cases became atrophic later. CONCLUSIONS: MRI can differentiate LRFs from FFs in a variety of parameters after flap reconstructive surgery for tongue cancer.

The Evaluation of Radiomic Models in Distinguishing Pilocytic Astrocytoma From Cystic Oligodendroglioma With Multiparametric MRI.

PURPOSE: To assess whether a machine-learning model based on texture features extracted from multiparametric magnetic resonance imaging could yield an accurate diagnosis in differentiating pilocytic astrocytoma from cystic oligodendrogliomas. MATERIALS AND METHODS: The preoperative images from multisequences were used for tumor segmentation. Radiomic features were extracted and selected for machine-learning models. Semantic features and selected radiomic features from training data set were built, and the performance of each model was evaluated by receiver operating characteristic curve and accuracy from isolated testing data set. RESULTS: In terms of different sequences, the best classifier was built by radiomic features extracted from enhanced T1WI-based classifier. The best model in our study turned out to be the gradient boosted trees classifier with an area under curve value of 0.99. CONCLUSION: Our study showed that gradient boosted trees based on texture features extracted from enhanced T1WI could become an additional tool for improving diagnostic accuracy to differentiate pilocytic astrocytoma from cystic oligodendroglioma.

Diffusion tensor imaging in the evaluation of the long-term efficacy of HBO2 therapy in rats after traumatic spinal cord injury.

Objective: This study explored the feasibility of diffusion tensor imaging (DTI) in the evaluation of the long-term efficacy of hyperbaric oxygen (HBO2) therapy in rats after traumatic spinal cord injury (TSCI) with different degrees of injury. Method: Adult Sprague-Dawley rats (total n = 60) were randomly separated into three groups of mild, moderate and severe TSCI (20 rats per group). Each group was then randomly divided into TSCI and TSCI+HBO2 subgroups (10 rats per subgroup). Basso Beattie and Bresnahan (BBB) scores and DTI parameters including fractional anisotropy (FA), mean apparent diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD) were collected at pre-TSCI and at 0, six and 24 hours, and three, seven, 14, 21, 28 and 56 days post-TSCI. Two-way repeated measures analysis of variance was used for comparison between the TSCI and TSCI+HBO2 subgroups over time in the mild, moderate and severe TSCI groups. Pearson correlation analysis was applied to analyze the correlations between BBB scores and DTI parameters. Results: BBB scores, FA, MD and RD values showed significant differences between the TSCI and TSCI+HBO2 subgroups over time in the mild, moderate and severe TSCI groups (all p<0.01). FA, MD and RD values were positively correlated with BBB scores in all TSCI and TSCI+HBO2 subgroups (all p<0.05). Conclusions: DTI parameters, especially MD, could quantifiably assess the long-term efficacy of HBO2 therapy and reflect the functional recovery in rats after TSCI with different degrees of injury.

A cation exchange strategy to construct a targeting nanoprobe for enhanced T1-weighted MR imaging of tumors.

Excellent imaging performance and good biocompatibility of contrast agents are considered as prerequisites for accurate tumor diagnosis. In this study, a novel imaging nanoprobe with actively targeting performance based on ultrasmall paramagnetic iron oxide (USPIO) nanoparticles was constructed by a facile cation exchange strategy followed by conjugation with transferrin (Tf). The stable gadolinium (Gd3+) chelation endows the nanoparticles (NPs) with a low value of r2/r1 (1.28) and a relatively high r1 value of 3.2 mM-1 s-1, enabling their use for T1-weighted positive magnetic resonance (MR) imaging. This constructed transferrin modified gadolinium-iron chelate nanoprobe, named as TUG, shows high biocompatibility within a given dose range. More importantly, compared with clinically used Gd-based small molecule contrast agents, the obtained TUG can be more engulfed by breast cancer cells, showing much enhanced T1-weighted positive MR imaging in both subcutaneous and orthotopic tumor models of breast cancer. This novel nanoprobe holds great promise to be utilized as a targeting contrast agent with high efficacy for T1-weighted positive MR imaging.

Influence of coarse particulate matter on chickenpox in Jiading District, Shanghai, 2009-2018: A distributed lag non-linear time series analysis.

Although the link between ambient air pollution and some infectious diseases has been studied, few studies have explored so far, the relationship between chickenpox and particulate matter. Daily chickenpox counts in Jiading District, Shanghai, were collected from 2009 to 2018. Time series analysis was conducted to describe the trends of the daily number of chickenpox cases and the concentration of particulate matter 10 µm or less (PM10). The distributed lag non-linear model (DLNM) was developed to assess the lag and non-linear relationship between the number of chickenpox cases and PM10 concentration adjusting for meteorological factors and other pollutants. Spatiotemporal scanning was used to detect the clustering of chickenpox cases. There was a concomitant relationship between the number of chickenpox cases and PM10 concentration, especially in the period of high PM10 concentration. DLNM results showed a nonlinear relationship between the number of chickenpox cases and PM10 concentration with the maximum effect of PM10 being lagged for 13-14 days, which was consistent with the average incubation period of chickenpox. PM10 was significantly associated with the daily number of chickenpox cases when above 300 µg/m3. The risk of chickenpox increased with increasing PM10 concentration and the association was strongest at the lag of 14 day (RR = 1.13, 95% CI: 1.04-1.23) for PM10 concentration of 500 µg/m3 versus 50 µg/m3. The study provides evidence that high PM10 concentration increases the risk of chickenpox spreading.

Development and Validation of a Prognostic Nomogram Based on Clinical and CT Features for Adverse Outcome Prediction in Patients with COVID-19.

OBJECTIVE: The purpose of our study was to investigate the predictive abilities of clinical and computed tomography (CT) features for outcome prediction in patients with coronavirus disease (COVID-19). MATERIALS AND METHODS: The clinical and CT data of 238 patients with laboratory-confirmed COVID-19 in our two hospitals were retrospectively analyzed. One hundred sixty-six patients (103 males; age 43.8 ± 12.3 years) were allocated in the training cohort and 72 patients (38 males; age 45.1 ± 15.8 years) from another independent hospital were assigned in the validation cohort. The primary composite endpoint was admission to an intensive care unit, use of mechanical ventilation, or death. Univariate and multivariate Cox proportional hazard analyses were performed to identify independent predictors. A nomogram was constructed based on the combination of clinical and CT features, and its prognostic performance was externally tested in the validation group. The predictive value of the combined model was compared with models built on the clinical and radiological attributes alone. RESULTS: Overall, 35 infected patients (21.1%) in the training cohort and 10 patients (13.9%) in the validation cohort experienced adverse outcomes. Underlying comorbidity (hazard ratio [HR], 3.35; 95% confidence interval [CI], 1.67-6.71; p < 0.001), lymphocyte count (HR, 0.12; 95% CI, 0.04-0.38; p < 0.001) and crazy-paving sign (HR, 2.15; 95% CI, 1.03-4.48; p = 0.042) were the independent factors. The nomogram displayed a concordance index (C-index) of 0.82 (95% CI, 0.76-0.88), and its prognostic value was confirmed in the validation cohort with a C-index of 0.89 (95% CI, 0.82-0.96). The combined model provided the best performance over the clinical or radiological model (p < 0.050). CONCLUSION: Underlying comorbidity, lymphocyte count and crazy-paving sign were independent predictors of adverse outcomes. The prognostic nomogram based on the combination of clinical and CT features could be a useful tool for predicting adverse outcomes of patients with COVID-19.

Differentiating intracranial solitary fibrous tumor/hemangiopericytoma from meningioma using diffusion-weighted imaging and susceptibility-weighted imaging.

PURPOSE: Intracranial solitary fibrous tumor/hemangiopericytoma (SFT/HPC) and meningioma are difficult to distinguish owing to their overlapping imaging manifestation on routine magnetic resonance imaging. The purpose of this study was to assess whether SFT/HPC can be differentiated from meningioma with diffusion-weighted imaging (DWI) and susceptibility-weighted imaging (SWI). METHODS: We retrospectively reviewed DWI, SWI, conventreional MR, and CT imaging features of 16 patients with SFT/HPC and 96 patients with meningioma. The apparent diffusion coefficient (ADC) value, normalized ADC (nADC) value, and degree of intratumoral susceptibility signal intensity (ITSS) were compared between SFT/HPCs and meningiomas using two-sample t tests, and among SFT/HPCs, low-grade and high-grade meningioma were tested using one-way analysis of variance (ANOVA). Receiver operating characteristic (ROC) curve and logistic regression analyses were performed to determine the differentiation capacity. RESULTS: The ADC value, nADC value, and the degree of ITSS in SFT/HPC were significantly higher than those in low-grade and high-grade meningiomas (all p < 0.05). The threshold value of > 1.15 for nADC provided 75.00% sensitivity and 60.42% specificity for differentiating SFT/HPC from meningioma. Compared with nADC, the degree of ITSS had a moderate sensitivity (62.50%) and a higher specificity (85.42%) using the threshold value of > 1.00. Furthermore, combining DWI and SWI can achieve a relatively high differentiation capacity with a sensitivity of 81.25% and specificity of 78.12%. CONCLUSIONS: The nADC ratios and ITSS are useful for differentiating SFT/HPC from meningioma. Combining ITSS and nADC value appears to be a promising option for differential diagnosis.