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The purpose of this paper is to determine the efficacy of combining radiation therapy with endostar, a recombined humanized endostatin, in human nasopharyngeal carcinoma and human lung adenocarcinoma xenografts. Tumor xenografts were established in the hind limb of male athymic nude mice (BALB/c-nu) by subcutaneous transplantation. The tumor-bearing mice were assigned into four treatment groups: sham therapy (control), endostar (20 mg/kg, once daily for 10 days), radiation therapy (6 Gray per day to 30 Gray, once a day for 1 week), and endostar plus radiation therapy (combination). The experiment was repeated and mice were killed at days 3, 6, and 10 after initiation therapy, and the tumor tissues and blood samples were collected to analyze the kinetics of antitumor, antiangiogenesis, and antivascularization responses of different therapies. In human nasopharyngeal carcinoma and human lung adenocarcinoma xenografts, endostar significantly enhanced the effects of tumor growth inhibition, endothelial cell and tumor cell apoptosis induction, and improved tumor cell hypoxia of radiation therapy. Histological analyses demonstrated that endostar plus radiation also induced a significant reduction in microvascular density, microvascular area, and vascular endothelial growth factor and matrix metalloproteinase-2 expression compared with radiation and endostar alone respectively. We concluded that endostar significantly sensitized the function of radiation in antitumor and antiangiogenesis in human nasopharyngeal carcinoma and human lung adenocarcinoma xenografts by increasing the apoptosis of the endothelial cell and tumor cell, improving the hypoxia of the tumor cell, and changing the proangiogenic factors. These data provided a rational basis for clinical practice of this multimodality therapy.

In this study, we present deep learning‐based approaches to automatic segmentation and applicator reconstruction with high accuracy and efficiency in the planning computed tomography (CT) for cervical cancer brachytherapy (BT). A novel three‐dimensional (3D) convolutional neural network (CNN) architecture was proposed and referred to as DSD‐UNET. The dataset of 91 patients received CT‐based BT of cervical cancer was used to train and test DSD‐UNET model for auto‐segmentation of high‐risk clinical target volume (HR‐CTV) and organs at risk (OARs). Automatic applicator reconstruction was achieved with DSD‐UNET‐based segmentation of applicator components followed by 3D skeletonization and polynomial curve fitting. Digitization of the channel paths for tandem and ovoid applicator in the planning CT was evaluated utilizing the data from 32 patients. Dice similarity coefficient (DSC), Jaccard Index (JI), and Hausdorff distance (HD) were used to quantitatively evaluate the accuracy. The segmentation performance of DSD‐UNET was compared with that of 3D U‐Net. Results showed that DSD‐UNET method outperformed 3D U‐Net on segmentations of all the structures. The mean DSC values of DSD‐UNET method were 86.9%, 82.9%, and 82.1% for bladder, HR‐CTV, and rectum, respectively. For the performance of automatic applicator reconstruction, outstanding segmentation accuracy was first achieved for the intrauterine and ovoid tubes (average DSC value of 92.1%, average HD value of 2.3 mm). Finally, HDs between the channel paths determined automatically and manually were 0.88 ± 0.12 mm, 0.95 ± 0.16 mm, and 0.96 ± 0.15 mm for the intrauterine, left ovoid, and right ovoid tubes, respectively. The proposed DSD‐UNET method outperformed the 3D U‐Net and could segment HR‐CTV, bladder, and rectum with relatively good accuracy. Accurate digitization of the channel paths could be achieved with the DSD‐UNET‐based method. The proposed approaches could be useful to improve the efficiency and consistency of treatment planning for cervical cancer BT.

Ablative hypofractionated radiotherapy (HFRT) significantly improves the overall survival of inoperable non-small cell lung cancer (NSCLC) patients compared with conventional radiation therapy. However, the radiobiological mechanisms of ablative HFRT remain largely unknown. The purpose of this study was to investigate the dynamic changes of tumor vessels and perfusion during and after ablative hypofractionated radiotherapy. Lewis lung carcinoma-bearing mice were treated with sham (control) and ablative hypofractionated radiotherapy of 12 Gy in 1 fraction (12 Gy/1F) and 36 Gy in 3 fractions (36 Gy/3F). Tumor microvessel density (MVD), morphology and function were examined at different times after irradiation. The results showed that, compared to the controls the MVD and hypoxia in ablative HFRT groups decreased, which were accompanied by an increase in the number of pericytes and their coverage of vessels. Functional tests revealed that tumor hypoxia and perfusion were improved, especially in the 36 Gy/3F group. Our results revealed that ablative hypofractionated radiotherapy not only repressed MVD and hypoxia, but also increased the vascular perfusion and the number of pericyte-covered vessels, suggesting that ablative HFRT normalized the tumor vasculature.