OBJECTIVES: The automatic delineation of organs at risk (OARs) can help doctors make radiotherapy plans efficiently and accurately, and effectively improve the accuracy of radiotherapy and the therapeutic effect. Therefore, this study aims to propose an automatic delineation method for OARs in cervical cancer scenarios of both after-loading and external irradiation. At the same time, the similarity of OARs structure between different scenes is used to improve the segmentation accuracy of OARs in difficult segmentations. METHODS: Our ensemble model adopted the strategy of ensemble learning. The model obtained from the pre-training based on the after-loading and external irradiation was introduced into the integrated model as a feature extraction module. The data in different scenes were trained alternately, and the personalized features of the OARs within the model and the common features of the OARs between scenes were introduced. Computer tomography (CT) images for 84 cases of after-loading and 46 cases of external irradiation were collected as the train data set. Five-fold cross-validation was adopted to split training sets and test sets. The five-fold average dice similarity coefficient (DSC) served as the figure-of-merit in evaluating the segmentation model. RESULTS: The DSCs of the OARs (the rectum and bladder in the after-loading images and the bladder in the external irradiation images) were higher than 0.7. Compared with using an independent residual U-net (convolutional networks for biomedical image segmentation) model [residual U-net (Res-Unet)] delineate OARs, the proposed model can effectively improve the segmentation performance of difficult OARs (the sigmoid in the after-loading CT images and the rectum in the external irradiation images), and the DSCs were increased by more than 3%. CONCLUSIONS Comparing to the dedicated models, our ensemble model achieves the comparable result in segmentation of OARs for different treatment options in cervical cancer radiotherapy, which may be shorten time for doctors to sketch OARs and improve doctor's work efficiency.
Female ; Humans ; Image Processing, Computer-Assisted/methods* ; Machine Learning ; Organs at Risk/radiation effects* ; Radiotherapy Planning, Computer-Assisted/methods* ; Uterine Cervical Neoplasms/radiotherapy*

Objective To investigate the effect of bone marrow mesenchymal stem cells(BMSCs)on the inflamma-tory response of lipopolysaccharide(LPS)induced acute lung injury(ALI)in mice.Methods 32 SPF KM mice,aged 4 weeks were randomly divided into four groups,control group,LPS group,dexamethasone treatment group(LPS+DEX)and BMSCs treatment group(LPS+BMSCs).The latter three groups were injected with LPS by tra-cheal puncture to establish mouse ALI model 24 h after modeling,BMSCs isolated from the femur of mice were in-jected into the caudal vein,and DEX were injected into caudal vein at the same time in LPS+DEX group for 3 consecutive days.On the 4th day after cell transplantation or 24 h after DEX injection,the survival quantity of mice was recorded,lung function was detected,and the wet/dry weight ratio(W/D)of lung was measured.Then in-flammatory cells in bronchoalveolar lavage fluid(BALF),lung pathological changes and serum inflammatory cyto-kines were collected.Green fluorescent protein(GFP)staining was used to observe the homing of BMSCs in lung tissues.The mRNA and protein expression of TLR4,MyD88 and NF-κB in lung tissues were detected by RT-PCR and Western blot assay respectively.Results Compared with the control group,LPS model group showed de-creased lung function,significantly increase in the W/D weight ratio of lung,inflammatory cytokines in serum and inflammatory cells in BALF,and severe damage in lung tissue.Compared with LPS group,LPS+DEX group and LPS+BMSCs group showed improved lung function,reduced lung tissue damage,significantly decrease in the W/D weight ratio of lung,inflammatory cytokines in serum and inflammatory cells in BALF.And the expression of TLR4-MyD88-NF-κB signaling pathway-related genes and proteins decreased,the survival quantity increased.Conclusion Homologous BMSCs transplantation can effectively treat LPS-induced acute lung injury,and the mechanism may be related to the regulation of TLR4-MyD88-NF-κB signaling pathway and the reduction of inflam-matory response.These findings provide the experimental basis for BMSCs homologous transplantation for ALI.