Objective To study the factors influencing the curative effect of one-stage bihteral total hip arthroplasty in a sequential procedure.Methods Thirty-six patients were indicated for one-stage bilateral total hip arthroplasty from February 1998 to March 2008.All cases were made with Smith-Peterson incision.Results The operative time was(3.2±1.2)h.The volume of blood transfusion during operation was (620 4±120)ml.All the 36 patients were followed up for(22.0±6.0)months.Except for 1 case of deep venous thrombosis of lower limbs,1 case of limb length discrepancy,there were no severe complications,such as postoperative infection,pulmonary embelism,dislocation,loosening or subsiding of components.Postoperative Harris scoreg of the joint function[(88.0±3.6)points]was significantly improved compared with their preoperative Harris scores[(28.0±4.2)points](P<0.05).Conclusions One-stage bilateral total hip arthroplasty is an effective method.However.the satisfactory effects can only be achieved by strict case selection,sufficient preoperative preparation,attention to operation procedures,prevention of complications and active recovery after operations.

[ ABSTRACT] AIM:To investigate the effect of the overexpression of voltage-gated chloride channel family protein 3 ( ClC-3) gene on bones of mice .METHODS: The tail gene detection assay was used to confirm the overexpression of ClC-3.The male FVB mice of three months old were divided into two groups , the wild type ( WT) group and the ClC-3 overexpressed (ClC-3 transgene) group.The body weight, length and weight of the right tibias were measured .The upper and middle parts of the tibias were dissected , decalcified, paraffin-imbed, sectioned and stained with HE staining .The bone morphology metrology was used to analyze the changes of bone structures .The percent trabecular area (%Tb.Ar), trabecular number ( Tb.N) , trabecular width ( Tb.Wi) and trabecular separation ( Tb.Sp) of cancellous bone in the upper part of the tibia were measured.The total tissue area (T.Ar), cortical area (Ct.Ar), percent cortical area (%Ct.Ar), marrow area ( Ma.Ar) and percent marrow area (%Ma.Ar) of the cortical bone in the middle part of the tibia were detec-ted .RESULTS:The wild type mice and the ClC-3-overexpressed mice were verified by the tail gene detection assay . Compared with WT group , the body weight and the length and weight of the tibia were decreased in ClC -3 transgene mice (P<0.05).In the cancellous bones of ClC-3 transgene mice, the%Tb.Ar and Tb.Wi were decreased (P<0.05), the Tb.Sp was increased (P<0.05) and the Tb.N was not significantly changed .In the cortical bones of ClC-3 transgene mice, the T.Ar, Ct.Ar and%Ct.Ar were decreased (P<0.05), the%Ma.Ar was increased (P<0.05), and the Ma. Ar was not significantly changed .CONCLUSION:ClC-3 overexpression may lead to the reduction of the bone mass and the destructure of the cancellous and cortical bones .The results suggest that ClC-3 may be involved in the regulation of bone resorption and/or formation.

Objective:To resolve the issue of poor automatic segmentation of the bowel in women with pelvic tumors, a Dense V-Network model was established, trained and evaluated to accurately and automatically delineate the bowel of female patients with pelvic tumors.Methods:Dense Net and V-Net network models were combined to develop a Dense V-Network algorithm for automatic segmentation of 3D CT images. CT data were collected from 160 patients with cervical cancer, 130 of which were randomly selected as the training set to adjust the model parameters, and the remaining 30 were used as test set to evaluate the effect of automatic segmentation.Results:Eight parameters including Dice similarity coefficient (DSC) were utilized to quantitatively evaluate the segmentation effect. The DSC value, JD, ΔV, SI, IncI, HD (cm), MDA (mm), and DC (mm) of the small intestine were 0.86±0.03, 0.25±0.04, 0.10±0.07, 0.88±0.05, 0.85±0.05, 2.98±0.61, 2.40±0.45 and 4.13±1.74, which were better than those of any other single algorithm.Conclusion:Dense V-Network algorithm proposed in this paper can deliver accurate segmentation of the bowel organs. It can be applied in clinical practice after slight revision by physicians.

When applying deep learning to the automatic segmentation of organs at risk in medical images, we combine two network models of Dense Net and V-Net to develop a Dense V-network for automatic segmentation of three-dimensional computed tomography (CT) images, in order to solve the problems of degradation and gradient disappearance of three-dimensional convolutional neural networks optimization as training samples are insufficient. This algorithm is applied to the delineation of pelvic endangered organs and we take three representative evaluation parameters to quantitatively evaluate the segmentation effect. The clinical result showed that the Dice similarity coefficient values of the bladder, small intestine, rectum, femoral head and spinal cord were all above 0.87 (average was 0.9); Jaccard distance of these were within 2.3 (average was 0.18). Except for the small intestine, the Hausdorff distance of other organs were less than 0.9 cm (average was 0.62 cm). The Dense V-Network has been proven to achieve the accurate segmentation of pelvic endangered organs.
Algorithms ; Humans ; Image Processing, Computer-Assisted ; Imaging, Three-Dimensional ; Neural Networks, Computer ; Organs at Risk ; Pelvis ; Tomography, X-Ray Computed