Comparison of different radiomic models based on enhanced T1-weighted images to predict the meningioma grade.

AIM: To compare different models in predicting meningioma grade based on enhanced T1-weighted images. MATERIALS AND METHODS: One hundred and eighty-eight patients with meningioma were analysed retrospectively. There were 94 high-grade meningiomas which formed the high-grade group comprising 68 World Health Organization (WHO) grade II meningiomas and 26 WHO grade III meningiomas. Ninety-four low-grade meningiomas were selected randomly to form the low-grade group. Least absolute shrinkage and selection operator (LASSO) regression was used to reduce the dimensions of the texture parameters. Support vector machine (SVM), decision tree (DT), conditional inference trees (CIT), random forest (RF), k-nearest neighbours (KNN), back-propagation neural network (BPNet), and Bayes were used to construct models. Receiver operating characteristic (ROC) analysis and decision curve analysis (DCA) was applied and compared among different models. RESULTS: Every model performed well and had a high area under the ROC curve (AUC; all >0.80). In the seven models, the highest accuracy was obtained with SVM and KNN (0.79), the highest sensitivity was obtained with DT and Bayes (0.85), and the highest specificity was obtained with SVM and CIT (0.83). SVM and RF had the highest AUC (0.884). KNN had the largest net benefit when the threshold probability was <0.50, whereas SVM had the largest net benefit when the threshold probability was >0.50. CONCLUSIONS: Different radiomic models based on enhanced T1-weighted images can be used to predict meningioma grade. The model of SVM and KNN performed better than other models with a larger net benefit.

CYP4A in tumor-associated macrophages promotes pre-metastatic niche formation and metastasis.

Tumor-associated macrophages (TAMs) play an essential role in metastasis. However, what enables TAMs to have a superior capacity to establish pre-metastatic microenvironment in distant organs is unclear. Here we have begun to uncover the effects of cytochrome P450 (CYP) 4A in TAMs on lung pre-metastatic niche formation and metastasis. CYP4A+ TAM infiltration was positively associated with metastasis, pre-metastatic niche formation and poor prognosis in breast cancer patients. The pharmacological inhibition of CYP4A reduced lung pre-metastatic niche formation (evidenced by a decrease in vascular endothelial growth factor receptor 1 positive (VEGFR1+) myeloid cell recruitment and pro-metastatic protein expression) and metastatic burden, accompanied with TAM polarization away from the M2 phenotype in spontaneous metastasis models of 4T1 breast cancer and B16F10 melanoma. Co-implantation of 4T1 cells with CYP4A10high macrophages promoted lung pre-metastatic niche formation and metastasis. Depletion of TAMs disrupted lung pre-metastatic niches and thereby prevented metastasis. Treatment with the CM from CYP4A10high M2 macrophages (M2) increased pre-metastatic niche formation and metastatic burden in the lungs, whereas CYP4A inhibition attenuated these effects. In vitro TAM polarization away from the M2 phenotype induced by CYP4A inhibition decreased VEGFR1+ myeloid cell migration and fibronectin expression, accompanied with downregulation of STAT3 signaling. Conversely, overexpression of CYP4A or exogenous addition of 20-hydroxyeicosatetraenoic acid promoted M2 polarization and cytokine production of macrophages and thereby enhanced migration of VEGFR1+ myeloid cells, which were reversed by siRNA or pharmacological inhibition of STAT3. Importantly, a combined blocking M2 macrophage-derived factors TGF-ß, VEGF and SDF-1 abolished VEGFR1+ myeloid cell migration and fibroblast activation induced by CYP4A. In summary, CYP4A in TAMs is crucial for lung pre-metastatic niche formation and metastasis, and may serve as a potential therapeutic target in human cancer.

Correlation between magnetic resonance perfusion weighted imaging of radiation brain injury and pathology.

We used magnetic resonance perfusion weighted imaging and pathological evaluation to examine different stages of radiation-induced brain injury and to investigate the correlation between the relative cerebral blood volume (rCBV) ratio and vascular endothelial growth factor (VEGF). Thirty adult rats were randomly divided into 2 groups: control and radiation group. The control group was not subjected to irradiation. The irradiation group rats were examined by magnetic resonance imaging and magnetic resonance perfusion weighted imaging at 1, 3, 6, 9, and 12 months after radiation treatment. We measured the rCBV, mean transit time, and time to peak. Hematoxylin and eosin staining, immunohistochemical staining, and electron microscopy were performed. VEGF absorbance was evaluated by immunohistochemical staining. Compared with the control group, the differences in rCBV, mean transit time, time to peak, and VEGF absorbance after 3 months were statistically significant (P < 0.05). rCBV was positively correlated with VEGF (r = 0.94, P < 0.05). Magnetic resonance perfusion weighted imaging can reflect pathophysiological changes in brain tissue after irradiation. Decreased expression of VEGF plays a critical role in the pathogenesis of radiation-induced brain injury.

[Pathomorphological observation of oviducts of women with inserted IUDs].

PIP: The tissues of isthmus tubae uterinae from 101 women with IUDs in place and 113 women without IUDs were observed by microscopy. The rate changes of the covered area of ciliated cells were observed in oviducts in 30 patients with IUDs and 17 without. Results showed that the incidence of salpingitis was 71.29% in the IUD group and 56.64% in the controls (p.05), and the rate of covered area of ciliated cells was 22.63% in the IUD group and 38.18% in the controls (p.05). It is suggested that salpingitis incidence was raised and the rate of covered area of ciliated cells reduced significantly in relation to IUD use. (author's modified)^ieng