Objective To study preliminary the accuracy of clinical target volume (CTV) and internal target volume (ITV) automatically generated by an in-house deformable registration software on fourdimensional CT (4DCT),and evaluate its feasibility of clinical application.Methods Clinic treated one lung cancer patient and one liver cancer patient were selected for the study.CTV was delineated by radiation oncologist according to a single respiratory phase image of 4DCT scanning,and then deformed to the other phases and generated the CTVdefm on each phase image.Differences between the CTVdefm and CTVmanu were then compared.A composite ITVcopm was created by overlapping all the CTVdefm of 10 phases and compared with the ITVMIP which was contoured on the maximum intensity projection (MIP) CT images,including the shape,volume and geometric center position of the ITV contour.Results For the tested lung case,average volume difference between the CTVdefm and CTV was (-2.59 ± 5.02)％ for the all 10 phases,and the vector departure of the two ITV centers was (1.04 ± 0.89) mm.The ITVcomp almost completely matched the ITVMIP on the tested liver case with a volume difference smaller the 1％ and only 1.4 mm vector departure between their geometric centers.Conclusion The validity of the CTVdefm and ITVcomp gained from automatic deformation of manual delineation reference based on 4DCT images were preliminary evaluated and proved to be good enough for clinic planning.

A novel multi-spectral MR image segmentation method based on multi-modality image fusion is presented in this paper. The basic idea of the method is that every single image is clustered using the FCM clustering method first, and then the final clustering results can be obtained by data fusion. The experimental results show that the presented method separates the white matter, gray matter and cerebro-spinal fluid (CSF) more accurately than does any single image segmentation method.
Algorithms ; Brain ; anatomy & histology ; pathology ; Data Interpretation, Statistical ; Fuzzy Logic ; Humans ; Image Interpretation, Computer-Assisted ; methods ; Magnetic Resonance Imaging ; methods ; Pattern Recognition, Automated ; methods

Objective To evaluate the clinical efficacy of staged treatment of complex tibial plateau fractures with temporary transarticular external fixation and delayed plate fixation.Methods Enrolled in this study were 44 cases of complex tibial plateau fracture who had been treated from January 2011 to January 2014.Temporary transarticular external fixation and delayed plate fixation was adopted in 22 patients (observation group),involving 14 men and 8 women with an average age of 45.5 ± 11.4 years,and 10 left sides and 12 right sides.By the Schatzker classification,13 cases were type Ⅴ and 9 type Ⅵ.Calcaneal traction and plate fixation was adopted in the other 22 patients (control group),involving 13 men and 9 women with an average age of 43.8 ± 10.4 years,and 8 left sides and 14 right sides.By the Schatzker classification,12 cases were type Ⅴ and l0 type Ⅵ.The 2 groups were evaluated by the time from hospitalization to plate fixation,operation time,intra-operative bleeding volume,hospitalization time,healing time,complications and Hospital for Special Surgery (HSS) scoring at the final follow-ups.The 2 groups were compatible with no significant differences regarding the preoperative general data (P ＞ 0.05).Results The 44 patients were followed up for 12 to 30 months (mean,18.6 months).There were significant differences between the 2 groups in the time from hospitalization to plate fixation,operation time,intra-operative bleeding volume and hospitalization time (P ＜ 0.05).There was also a significant difference in the complications rate (4.5％ (1/22) for the observation group versus 27.3％ (6/22) for the control group) (P ＜ 0.05),but there was no significant difference in the good to excellent rate by HSS scoring [86.3％ (19/22) versus 81.8％ (18/22)] (P ＞ 0.05).Conclusions Although both methods can treat complex tibial plateau fractures,temporary transarticular external fixation and delayed plate fixation may be preferable because it can lead to decreased hospitalization time,less intra-operative bleeding volume,fewer surgical complications and good functional recovery of the knee.

Breathing motion is a rule-based motion. The traditional breathing motion is described by mathematical model which can not reflect the different properties of different patients or the different breathing periods of the same patient. So, it can not satisfy the needs of the real-time and accurate analysis. Accordingly, in this paper is proposed a method to establish the breathing model through tracking the cone beam CT images which are gained when the patient is breathing freely. The model obtained by the proposed method is similar to the traditional model, which verifies the feasibility and effectiveness of the proposed method. Simultaneously, the proposed method has "real-time" and "accurate" properties, which make it valuable in clinical application.
Cone-Beam Computed Tomography ; Diaphragm ; diagnostic imaging ; physiology ; Humans ; Models, Biological ; Movement ; Radiographic Image Interpretation, Computer-Assisted ; methods ; Respiration

Objective To evaluate the accuracy of sentinel lymph node biopsy (SLNB) in predicting the axillary lymph node status in breast cancer patients undergoing a breastectomy. Methods From Mar 2002 to Jun 2003,patent blue dye and/or 99m Tc-Sc were used to detect sentinel lymph nodes,samples were sent for fast pathology.Three patients in which the SLN were judged as negative by both the two tests were freed of futher axillary lymph node dissection (ALND). Results SLN were successfully identified in 78 of 81 (96.3%) patients. The accuracy rate of SLNB to predict axillary lymph node status was 97.5%,with 9.7% false negative rate. The success rate,accuracy rate and false negative rate by blue dye only and by a combination of two above methods were 92.5%,94.2%,15.8%,and 100%,100%,0, respectively . Conclusions SLNB accurately predict the axillary status in clinically node negative breast cancer patients .

In order to solve the time-consuming problem in volume CT image reconstruction field, we brought forward a fast reconstructive algorithm method to fit the clinic medicine. First, using the great parallel and Floating-Point power of graphic processing unit (GPU), we proposed a volume CT GPU- based reconstruction method. Second, in order to reduce the repetitive operation, we separated the geometry computation and pixel computation. As a result, the computation efficiency was further improved. At last, based on the background of medical engineering, the parallel of volume CT scan and reconstruction was implemented. The results demonstrated that the volume CT reconstruction time could reduce up to 70 times compared to the previous one in common PC by the fast reconstructive algorithm method.
Algorithms ; Computer Graphics ; Cone-Beam Computed Tomography ; instrumentation ; methods ; Humans ; Image Processing, Computer-Assisted ; methods ; Radiographic Image Enhancement ; methods ; Radiographic Image Interpretation, Computer-Assisted ; methods

Objective To compare the dosimetric data between preoperative plans and postoperative verification in computed tomography (CT)-guided and 3D-printing non-coplanar templateassisted 125I seed implantation for pelvic tumor,and to explore the feasibility and accuracy of the personalized template designmethod.Methods A total of 51 patients registered from Dec 2015 to Dec 2016 who were applied with 3D-printing guided template assisted radioactive seed implantations in the hospital were included in this study.A prescribed dose of 110-160 Gy was adopted.3D-printing templates were designed and produced for 51 cases.The dosimetric parameters:Dg0,minimum peripheral dose (mPD),V100,V150,V200,conformal index (CI),external index (EI),and homogeneity index (HI) were compared between pre-and post-plans.Results 51 cases' templates were in place well during the operations.Compared with the preoperative planning,the postoperative D90,V100,V150,V200,CI,EI and HI differences had no statistical difference (P ＞ 0.05);mPD is larger than before (t =-2.96,P ＜ 0.05).Conclusions The main dosimetric parameters of postoperative verification were consistent well with the preoperative planning and have good accuracy,which could meet the clinical requirements.

OBJECTIVETo investigate the effect of apigenin on the protein expression levels of peroxisome proliferator-activated receptors (PPARs) in liver tissues of rats with nonalcoholic steatohepatitis (NASH).

METHODSThe NASH rat model was established by feeding of a high-fat diet. Unmodeled rats served as the normal controls. The modeled rats were divided into a model control group, Essentiale treatment grouP(300 mg/kg/day),and three apigenin treatment groups for low-dose (15 mg/kg/day), moderate-dose (30 mg/kg/day) and high-dose (60 mg/kg/day). After 13 weeks of treatment,changes in insulin sensitivity from pre-treatment baseline were assessed by measuring the alanine aminotransferase (ALT), aspartate aminotransferase (AST),total cholesterol (TC),triglycerides (TG),low-density and high-density lipoprotein cholesterol (LDL-C and HDL-C),fasting blood glucose (FBG) and fasting insulin (FINS).The liver index and HOMA-IR were also calculated.Protein and gene expression of PPARα and PPARgamma in liver tissue were assessed by immunohistochemistry and RT-PCR.Statistical analysis was performed by the LSD test and Games-Howell test.

RESULTSThe apigenin-treated groups showed a significantly greater change in insulin sensitivity than the untreated model group,with the most significant change occurring in the high-dose grouP(P less than 0.05).Compared with the untreated model group,the apigenin-treated groups showed lower levels of ALT (95.4+/-7.3),AST (183.7+/-14.3),TC (1.61+/-0.25),TG (1.23+/-0.21),LDL-C (1.86+/-0.14),FBG (5.29+/-1.45) and FINS (0.76+/-0.86),but a higher level of HDL-C (1.04+/-0.17); again,the high-dose group showed the greatest change (all P less than 0.05).Compared to the untreated model group,the apigenin-treated groups showed significantly lower liver index (3.75+/-0.25 vs.2.90+/-0.17) and HOMA-IR (1.34+/-0.06 vs.0.18+/-0.04),with the high-dose group showing the greatest change (both P less than 0.05). Compared to the untreated model group,the apigenin-treated groups showed higher levels of protein and mRNA of PPARα (18.27+/-4.05 and 0.63+/-0.02,respectively) and PPARgamma(8.48+/-5.05 and 0.39+/-0.02),with the high-dose group showing the greatest change (all P < 0.05).

CONCLUSIONApigenin can improve glucose tolerance,lipid metabolism and insulin resistance while decreasing blood levels of TC,TG,LDL-C,FBG,FINS and HOMA-IR,and increasing HDL-C in NASH,as shown in a high-fat diet induced rat model, and may have therapeutic potential.

Alanine Transaminase ; metabolism ; Animals ; Apigenin ; pharmacology ; Aspartate Aminotransferases ; metabolism ; Blood Glucose ; metabolism ; Cholesterol ; metabolism ; Disease Models, Animal ; Insulin ; metabolism ; Insulin Resistance ; Lipid Metabolism ; Liver ; enzymology ; Non-alcoholic Fatty Liver Disease ; metabolism ; PPAR alpha ; metabolism ; PPAR gamma ; metabolism ; Peroxisome Proliferator-Activated Receptors ; metabolism ; Rats ; Rats, Sprague-Dawley ; Triglycerides ; metabolism

Objective:To design a semi-spherical applicator for delivery of semi-spherical dose distributions and assess its dosemetric characteristics.Methods:The applicator was designed in the following way. First, the scattering angle and dose rate of the electron beam having passed through a series of scattering foils of different thicknesses were calculated to determine the thickness of the scattering foil. And then, a series of location model was designed, and the variances of the mean electron energy on the surface of these models were calculated to determine the foil location. Finally, the relationship between the geometric characteristics of the layer and the surface dose on the applicator was established to design the modulator. Monte Carlo (MC) codes EGSnrc/BEAMnrc and EGS4/DOSXYZ were employed to model the head of the Mobetron, the location model, the layer, the semi-spherical applicator, and to calculate the dose distributions.Results:A semi-spherical applicator was designed for electron beam of energy 12 MeV, which consisted of a 2.5 cm diametre cylindrical collimator with 0.5 cm thick wall made of 0.3 cm thick steel and 0.2 cm thick water equivalent material (WEM), a 0.14 cm-thick foil made of tansgen, and a 2.5 cm diametre hollow semi-sphere containing a crescent modulator made of WEM. The dose rate was about 160 cGy/min, and the depth of the 50% isodose curve was 0.85 cm.Conclutions:We designed and performed a MC simulation of a semi-spherical applicator to deliver a semi-spherical dose distribution from a high energy electron beam.

Objective To evaluate the application of three deep learning algorithms in automatic segmentation of clinical target volumes (CTVs) in high-dose-rate brachytherapy after surgery for endometrial carcinoma. Methods A dataset comprising computed tomography scans from 306 post-surgery patients with endometrial carcinoma was divided into three subsets: 246 cases for training, 30 cases for validation, and 30 cases for testing. Three deep convolutional neural network models, 3D U-Net, 3D Res U-Net, and V-Net, were compared for CTV segmentation. Several commonly used quantitative metrics were employed, i.e., Dice similarity coefficient, Hausdorff distance, 95th percentile of Hausdorff distance, and Intersection over Union. Results During the testing phase, CTV segmentation with 3D U-Net, 3D Res U-Net, and V-Net showed a mean Dice similarity coefficient of 0.90 ± 0.07, 0.95 ± 0.06, and 0.95 ± 0.06, a mean Hausdorff distance of 2.51 ± 1.70, 0.96 ± 1.01, and 0.98 ± 0.95 mm, a mean 95th percentile of Hausdorff distance of 1.33 ± 1.02, 0.65 ± 0.91, and 0.40 ± 0.72 mm, and a mean Intersection over Union of 0.85 ± 0.11, 0.91 ± 0.09, and 0.92 ± 0.09, respectively. Segmentation based on V-Net was similarly to that performed by experienced radiation oncologists. The CTV segmentation time was < 3.2 s, which could save the work time of clinicians. Conclusion V-Net is better than other models in CTV segmentation as indicated by quantitative metrics and clinician assessment. Additionally, the method is highly consistent with the ground truth, reducing inter-doctor variability and treatment time.