Radiomics based on preoperative rectal cancer MRI to predict the metachronous liver metastasis.

PURPOSE: At present, there are few effective method to predict metachronous liver metastasis (MLM) from rectal cancer. We aim to investigate the efficacy of radiomics based on multiparametric MRI of first diagnosed rectal cancer in predicting MLM from rectal cancer. METHODS: From 301 consecutive histopathologically confirmed rectal cancer patients, 130 patients who have no distant metastasis detected at the time of diagnosis were enrolled and divided into MLM group (n = 49) and non-MLM group (n = 81) according to whether liver metastasis be detected later than 6 month after the first diagnosis of rectal cancer within 3 years' follow-up. The 130 patients were divided into a training set (n = 91) and a testing set (n = 39) at a ratio of 7:3 by stratified sampling using SPSS 24.0 software. The DWI model, HD T2WI model, and DWI + HD T2WI model were constructed respectively. The best performing model was selected and combined with the screened clinical features (including non-radiomics MRI features) to construct a fusion model. The testing set was used to evaluate the performance of the models, and the area under the curve (AUC) of receiver operating characteristics (ROC) was calculated for both the training set and the testing set. RESULTS: The AUC of the DWI + HD T2WI model in the testing set was higher than that of the DWI or the HD T2 model alone with statistically significance (P < 0.05). The screened clinical features were extramural vascular invasion (EMVI), T and N stages in MRI (mrT, mrN), and the distance from the lower edge of the tumor to the anal verge. The AUC of the fusion model in the testing set was 0.911. Decision curves and nomogram also showed that the fusion model had excellent clinical performance. CONCLUSION: The fusion model of primary rectal cancer MRI based radiomics combing clinical features can effectively predict MLM from rectal cancer, which may assist clinicians in formulating individualized monitoring and treatment plans.

[Comparison of low temperature- induced proteins in tillering node of winter wheat cultivars with different cold resistance].

By using two-dimensional electrophoresis and mass spectrometry techniques, the proteomes in the tillering node of cold-resistant winter wheat Dongnongdongmai 1 and cold-susceptible winter wheat Jimai 22 before and after low temperature treatment were comparatively analyzed. It was observed that within the range of pH 4-7, there was a significant difference in the expression level of 55 protein spots in the protein profiles of tillering node before and after low temperature treatment, and 47 of the 55 protein spots were expressed in the two cultivars. After low temperature treatment, the abundance value of 23 protein spots increased, with the absolute abundance being higher in Dongnongdongmai 1 than in Jimai 22, while that of 7 protein spots decreased, with the absolute abundance being lower in Dongnongdongmai 1 than in Jimai 22. The expression level of 8 protein spots specific in Dongnongdongmai 1 was up-regulated. In all of the up-regulated proteins, their expression level in Dongnongdongmai 1 was 2.1 - 16.5 times as high as that in Jimai 22, among which, 10 protein spots had an expression level of 4 times high. In the down-regulated proteins, their expression level in Dongnongdongmai 1 was 0.1-0.4 times as high as that in Jimai 22. The differential protein spots were detected by mass spectrometry, and identified by compared with retrieval database. A total of 51 protein spots fingerprints were obtained, among which, 15.7% were of stress protein, 27.5% were of metabolism-related protein, 19.6% were signaling molecules, 9.8% were of unknown protein, and other proteins took up 27.4%. These variously expressed proteins might play an important role in the cold resistance of Dongnongdongmai 1.