Purpose This retrospective study was designed to investigate the ability of radiomics to predict the mutation status of epidermal growth factor receptor (EGFR) subtypes (19Del and L858R) in patients with non‐small cell lung cancer (NSCLC). Methods In total, 312 patients with NSCLC were included, and 580 radiomic features were extracted from the computed tomography images of each patient. In the training set, univariate analysis was performed on the clinical and radiomic features; logistic regression models were established using a 5‐fold cross validation strategy for the prediction of EGFR subtypes 19Del and L858R. Subsequently, the predictive ability of the joint models was evaluated using the test set. Results The results revealed that the radiomic features specific for EGFR 19Del and L858R were Gabor’s MTRVariance, Gabor’s PTREntropy, and sphericity. Additionally, the respective areas under the receiver operating characteristic curves of the EGFR 19Del and L858R joint models were 0.7925 and 0.7750 for the test set. Conclusions Our study demonstrated the potential for radiomics to predict EGFR 19Del and L858R. Epidermal growth factor receptor 19Del and L858R exhibited distinct imaging phenotypes, which may help to guide the selection of more accurate and personalized treatment programs for patients with NSCLC.

Purpose To investigate the use of radiomics in the in‐depth identification of epidermal growth factor receptor (EGFR) mutation status in patients with lung adenocarcinoma. Methods Computed tomography images of 438 patients with lung adenocarcinoma were collected in two different institutions, and 496 radiomic features were extracted. In the training set, lasso logistic regression was used to establish radiomic signatures. Combining radiomic index and clinical features, five machine learning methods, and a tenfold cross‐validation strategy were used to establish combined models for EGFR+ vs EGFR−, and 19Del vs L858R, groups. The predictive power of the models was then evaluated using an independent external validation cohort. Results In the EGFR+ vs EGFR− and 19Del vs L858R groups, radiomic signatures consisting of 12 and 7 radiomic features were established, respectively; the area under the curves (AUCs) of the lasso logistic regression model on the validation set was 0.76 and 0.71, respectively. After inclusion of the clinical features, the maximum AUC of combined models on the validation set was 0.79 and 0.74, respectively. Logistic regression analysis showed good performance in the two groups, with AUCs of 0.79 and 0.71 on the validation set. Additionally, the AUC of combined models in the EGFR+ vs EGFR− group was higher than that of the 19Del vs L858R group. Conclusions Our study shows the potential of radiomics to predict EGFR mutation status. There are imaging phenotypic differences between EGFR+ and EGFR−, and between 19Del and L858R; these can be used to allow patients with lung adenocarcinoma to choose more appropriate and personalized treatment options.

The scanning around left atrium method proved to be the most suited for detecting pulmonary veins in clinical practice. 4D BF-STIC was superior in detecting the greatest number of pulmonary veins before 32 gestational weeks, but had limited clinical usage because it was very time-consuming and experience-dependent. The 4D method should be considered as a complement to traditional two-dimensional sonography, because it facilitates understanding of the anatomy and the spatial relationships of the cardiac structures.

A small ROI DWI can provide morphological and functional information on the parotid gland in Sjögren's syndrome patients, and can aid in the diagnosis and evaluation of therapeutic efficacy.

To investigate the thymic regenerative potential in adults accepting chemotherapy for lymphoma. The dynamics of thymic activity in 54 adults from baseline to 12 mo post-chemotherapy was analyzed by assessing thymic structural changes with serial computed tomography (CT) scans, and correlating these with measurements of thymic output by concurrent analysis of single-joint (sj) T-cell receptor excision circles (sjTREC) and CD31+ recent thymic emigrants (RTE) in peripheral blood. Furthermore, the consequence of thymic renewal on peripheral CD4+ T cell recovery after chemotherapy was evaluated. Time-dependent changes of thymic size and thymic output assessed by both sjTREC levels and CD31+ RTE counts in peripheral blood were observed during and after chemotherapy. Enlargement of thymus over baseline following chemotherapy regarded as rebound thymic hyperplasia (TH) was identified in 20 patients aged 18−53 y (median 33 y). By general linear models repeated measure analysis, it was found that, patients with TH (n = 20) had a faster recovery of sjTREC levels and CD31+ RTE counts after chemotherapy than patients with comparable age, gender, diagnosis, disease stage, thymic volume and output function at baseline but without TH (n = 18) (p = 0.035, 0.047); besides, patients with TH had a faster repopulation of both naïve CD4+ T cell and natural regulatory CD4+ T cell subsets than those without TH (p = 0.042, 0.038). These data suggested that adult thymus retains the capacity of regeneration after chemotherapy, especially in young adults. The presence of TH could contribute to the renewal of thymopoiesis and the replenishment of peripheral CD4+ T cell pool following chemotherapy in adults.