[Image Feature Extraction and Discriminant Analysis of Xinjiang Uygur Medicine Based on Color Histogram].

Image feature extraction is an important part of image processing and it is an important field of research and application of image processing technology. Uygur medicine is one of Chinese traditional medicine and researchers pay more attention to it. But large amounts of Uygur medicine data have not been fully utilized. In this study, we extracted the image color histogram feature of herbal and zooid medicine of Xinjiang Uygur. First, we did preprocessing, including image color enhancement, size normalizition and color space transformation. Then we extracted color histogram feature and analyzed them with statistical method. And finally, we evaluated the classification ability of features by Bayes discriminant analysis. Experimental results showed that high accuracy for Uygur medicine image classification was obtained by using color histogram feature. This study would have a certain help for the content-based medical image retrieval for Xinjiang Uygur medicine.

Predicting the prognosis of lung cancer patients treated with intensity-modulated radiotherapy based on radiomic features.

AIMS: This study aimed to develop a method for predicting short-term outcomes of lung cancer patients treated with intensity-modulated radiotherapy (IMRT) using radiomic features detected through computed tomography images. METHOD: A prediction model was developed based on a dataset of radiomic features obtained from 132 patients with lung cancer receiving IMRT. Dimension reduction was performed for the features using the maximum-relevance and minimum-redundancy (mRMR) algorithm, and the least absolute shrinkage and selection operator (LASSO) regression model was utilized to optimize feature selection for the IMRT-sensitivity prediction model. The model was constructed using binary logistic regression analysis and was evaluated using the concordance index (C-index), calibration plots, receiver operating characteristic curve, and decision curve analysis. RESULTS: Fifty features were selected from 1348 radiomic features using the mRMR method. Of these, three radiomic features were selected by LASSO logistic regression to construct the radiomics nomogram. The C-index of the model was 0.776 (95% confidence interval: 0.689-0.862) and 0.791 (95% confidence interval: 0.607-0.974) in the training and validation cohorts, respectively. Decision curve analysis showed that the radiomics nomogram was clinically useful. CONCLUSION: Radiomic features have the potential to be applied to predict the short-term efficacy of IMRT in patients with inoperable lung cancer.

Downregulation of miR-146b-5p via iodine involvement repressed papillary thyroid carcinoma cell proliferation.

miR-146b-5p is overexpressed in papillary thyroid carcinoma (PTC) and is thought to be a related diagnostic marker. Previous studies have indicated the effects of iodine on oncogenic activation. However, the effect of iodine on the proliferation of PTC cells and the associated underlying mechanisms remain unclear. We found that miR-146b-5p was downregulated and smad4 was upregulated in patients exposed to high iodine concentration by in situ hybridisation (ISH) and immunohistochemical (IHC). NaI (10-3 M) treatment downregulated miR-146b-5p and upregulated Smad4 in PTC cell lines. Luciferase assay was used to confirm that Smad4 is a target of miR-146b-5p. Furthermore, MTT assay and cell cycle analysis indicated that 10-3 M NaI suppressed cell proliferation and caused G0/G1 phase arrest. Real-time PCR and Western blotting demonstrated that 10-3 M NaI increased p21, p27, and p57 levels and reduced cyclin D1 levels in PTC cells. Our findings suggest that 10-3 M NaI increases Smad4 levels through repression of miR-146b-5p expression, curbing the proliferation in PTC.

Which Bone Marrow Sparing Strategy and Radiotherapy Technology Is Most Beneficial in Bone Marrow-Sparing Intensity Modulated Radiation Therapy for Patients With Cervical Cancer?

BACKGROUND: To evaluate the dosimetric parameters of different bone marrow sparing strategies and radiotherapy technologies and determine the optimal strategy to reduce hematologic toxicity associated with concurrent chemoradiation (cCRT) for cervical cancer. METHODS: A total of 15 patients with Federation International of Gynecology and Obsterics (FIGO) Stage IIB cervical cancer treated with cCRT were re-planned for bone marrow (BM)-sparing plans. First, we determined the optimal BM sparing strategy for intensity modulated radiotherapy (IMRT), including a BMS-IMRT plan that used total BM sparing (IMRT-BM) as the dose-volume constraint, and another plan used os coxae (OC) and lumbosacral spine (LS) sparing (IMRT-LS+OC) to compare the plan without BM-sparing (IMRT-N). Then, we determined the optimal technology for the BMS-IMRT, including fixed-field IMRT (FF-IMRT), volumetric-modulated arc therapy (VMAT), and helical tomotherapy (HT). The conformity and homogeneity of PTV, exposure volume of OARs, and efficiency of radiation delivery were analyzed. RESULTS: Compared with the IMRT-N group, the average volume of BM that received ≥10, ≥20, ≥30, and ≥40 Gy decreased significantly in both two BM-sparing groups, especially in the IMRT-LS+OC group, meanwhile, two BMS-IMRT plans exhibited the similar effect on PTV coverage and other organs at risk (OARs) sparing. Among three common IMRT techniques in clinic, HT was significantly less effective than VMAT and FF-IMRT in the aspect of BM-Sparing. Additionally, VMAT exhibited more efficient radiation delivery. CONCLUSION: We recommend the use of VMAT with OC and LS as separate dose-volume constraints in cervical cancer patients aiming at reducing hematologic toxicity associated with cCRT, especially in developing countries.