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Objective: To establish a radiomics signature and a nomogram model based on enhanced CT images to predict the Ki-67 index of lung cancer. Methods: From January 2014 to December 2018, 282 patients with lung cancer who had undergone enhanced CT scans and Ki-67 examination within 2 weeks were retrospectively enrolled and analyzed. The clinical data of the patients were collected, such as age, sex, smoking history, maximum tumor diameter and serum tumor markers. Our primary cohort was randomly divided into a training group (n=197) and a validation group (n=85) at a 7:3 ratio. A Ki-67 index ≤ 40% indicated low expression, and a Ki-67 index > 40% indicated high expression. In total, 396 radiomics features were extracted using AK software. Feature reduction and selection were performed using the lasso regression model. Logistic regression analysis was used to establish a multivariate predictive model to identify high and low Ki-67 expression in lung cancer. A nomogram integrating the radiomics score was established based on multiple logistic regression analysis. Area under the curve (AUC) was used to evaluate the prediction efficiency of the radiomics signature and nomogram. Results: The AUC,sensitivity, specificity and accuracy of the radiomics signature in the training and validation groups were 0.88 (95% CI: 0.82~0.93),79.2%,84.3%,81.2% and 0.86 (95% CI: 0.78~0.94),74.6%,88.1%,79.8%, respectively. A nomogram combining radiomics features and clinical risk factors (smoking history and NSE) was developed. The AUC, sensitivity, specificity and accuracy were 0.87 (95% CI: 0.80~0.95), 75.0%, 90.2% and 83.5% in the validation group, respectively. Conclusion: The radiomics signature and nomogram based on enhanced CT images provide a way to predict the Ki-67 expression level in lung cancer. [ABSTRACT FROM AUTHOR]

Objectives: Preoperative differentiation between benign lymphoepithelial lesion (BLEL) and mucosa-associated lymphoid tissue lymphoma (MALToma) in the parotid gland is important for treatment decisions. The purpose of this study was to develop and validate a CT-based radiomics nomogram combining radiomics signature and clinical factors for the preoperative differentiation of BLEL from MALToma in the parotid gland.Methods: A total of 101 patients with BLEL (n = 46) or MALToma (n = 55) were divided into a training set (n = 70) and validation set (n = 31). Radiomics features were extracted from non-contrast CT images, a radiomics signature was constructed, and a radiomics score (Rad-score) was calculated. Demographics and CT findings were assessed to build a clinical factor model. A radiomics nomogram combining the Rad-score and independent clinical factors was constructed using multivariate logistic regression analysis. The performance levels of the nomogram, radiomics signature, and clinical model were evaluated and validated on the training and validation datasets, and then compared among the three models.Results: Seven features were used to build the radiomics signature. The radiomics nomogram incorporating the clinical factors and radiomics signature showed favorable predictive value for differentiating parotid BLEL from MALToma, with AUCs of 0.983 and 0.950 for the training set and validation set, respectively. Decision curve analysis showed that the nomogram outperformed the clinical factor model in terms of clinical usefulness.Conclusions: The CT-based radiomics nomogram incorporating the Rad-score and clinical factors showed favorable predictive efficacy for differentiating BLEL from MALToma in the parotid gland, and may help in the clinical decision-making process.Key Points: • Differential diagnosis between BLEL and MALToma in parotid gland is rather difficult by conventional imaging modalities. • A radiomics nomogram integrated with the radiomics signature, demographics, and CT findings facilitates differentiation of BLEL from MALToma with improved diagnostic efficacy. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the effect of Galla chinensis chemical compounds on enamel caries remineralization in rats.Methods: A total of 40 rats were inoculated with Streptococcus sobrinus 6715 and fed a cariogenic diet (Keyes 2000). The rats were randomly divided into 4 groups and treated topically twice a day with each of the following extracts (or control) for 5 weeks: distilled and deionized water (DDW, negative control); 1,000 ppm NaF (positive control); 4,000 ppm G. chinensis crude aqueous extract (GCE), or 4,000 ppm gallic acid (GA). After the experimental period, Keyes' caries diagnosis and scoring technique was applied as a preliminary evaluation on the molar teeth. For more accurate remineralization data, the residual enamel volume of the first molar and the mineral density (MD) of the enamel were further analyzed by micro-CT.Results: The severity of molar enamel caries decreased in the following order of treatment groups: DDW > GA > GCE > NaF (p < 0.05). In addition, the residual first molar enamel volume and MD values increased in the order of DDW, GA, GCE and NaF treatment groups (p < 0.05). In most molars, remineralization layers were observed on the surface of lesions.Conclusion: G. chinensis compounds remineralize enamel caries lesions in a rat model. [ABSTRACT FROM AUTHOR]