Stereotactic body radiation therapy ( SBRT ) for locally advanced pancreatic cancer ( LAPC) shows good signs of efficacy as measured by local control,which can also reduce toxicity. The dose fractionation in foreign countries have changed from conventional fractionation to single fraction and finally moderate hypofractionation. It is similar to that in China, with the dose fractionation changing from conventional fractionation to moderate hypofractionation. This review introduces the latest research results of dose fractionation of SBRT for LAPC.

Objective:To investigate the effect of improved partial graft excision (iPGE) in the treatment of infected arteriovenous grafts (AVG).Methods:It was a single-center retrospective study. A cohort database study of patients who underwent surgery for infected AVG from January 2019 to July 2022 was conducted. The cases were divided into total graft excision (TGE) group and iPGE group, and the postoperative reinfection rate and surgery-related complications, such as bleeding, nerve injury and limb ischemia, in the two groups were analyzed. The primary patency rate and the secondary patency rate at 3 months and 6 months after the surgery in the iPGE group were analyzed.Results:(1) General information: A total of 47 cases were included in the study. Among these 47 cases, 14 cases had undergone iPGE of infected AVG, and 33 cases had undergone TGE. The study population was of an average age of 59 years (21-81 years), including 18 males and 29 females. Dialysis age was 36 (14, 72) months. AVG age was 18 (4, 36) months. The shortest AVG age was half a month, and the longest AVG age was 72 months. (2)Comparative analysis of the two groups: The reinfection rate of the iPGE group was 21.4% (3/14), and the reinfection rate of the TGE group was 0 (0/33). The reinfection rate of the iPGE group was higher than that of the TGE group, and the difference was statistically significant (Fisher exact test, P=0.022). For 11 patients in the iPGE group (excluding 3 cases with reinfection), the shortest follow-up period was 5 months and the longest follow-up period was 18 months. In the iPGE group, the primary patency rate at 3 months was 72.7% (8/11), and the primary patency rate at 6 months was 72.7% (8/11); the secondary patency rate at 3 months was 100% (11/11) and the secondary patency rate at 6 months was 90.9% (10/11). There was no brachial artery rupture, nerve injury or limb ischemia in the iPGE group. In the TGE group, 1 case underwent secondary repair of brachial artery due to brachial artery rupture, and there was no nerve injury or limb ischemia in other cases. Conclusions:During the treatment of infected AVG, iPGE can preserve the original fistula, and avoid central venous catheterization. At the same time, the operation difficulty and risk are relatively low. Although the reinfection rate of iPGE is slightly higher than that of TGE in this study, the reinfection rate of iPGE is lower than that reported in the previous study. The key to prevent reinfection is to grasp the reasonable surgical adaptation signs in preoperative evaluation, perform intraoperative reevaluation and control surgical operation details. The iPGE represents an acceptable method for the treatment of some particular patients with infected AVG.

Objective:To develope a deep-learning-based auto-segmentation model to segment organs at risk (OARs) in head and neck (H&N) region and compare with atlas-based auto-segmentation software (Smart segmentation).Methods:The auto-segmentation model consisted of classification model and segmentation model based on deep learning neural network. The classification model was utilized to classify CT slices into six categories in the cranio-caudal direction, and then the CT slices corresponding to the categories for different OARs were pushed to the segmentation model respectively. The CT image data of 150 patients were used for auto-segmentation model training and building atlas library in Smart segmentation software. Another 20 patients were used as testing dataset for both auto-segmentation model and Smart segmentation software. Dice similarity coefficient (DSC) and Hausdorff distance (HD) were used to evaluate the accuracy of two method, and auto-segmentation time cost was recorded. Paired Student′s t-test or non-parametric Wilcoxon signed-rank test was performed depending on result of normality test. Results:The DSC and HD of auto-segmentation model for brainstem, left eye, right eye, left optic nerve, right optic nerve, left temporal lobe, right temporal lobe, mandible, left parotid and right parotid were 0.88 and 4.41 mm, 0.89 and 2.00 mm, 0.89 and 2.12 mm, 0.70 and 3.00 mm, 0.80 and 2.24 mm, 0.81 and 7.98 mm, 0.84 and 8.82 mm, 0.89 and 5.57 mm, 0.70 and 11.92 mm, 0.77 and 11.27 mm respectively. The results of auto-segmentation model were better than those of Smart segmentation ( t=3.115-7.915, Z=-1.352 to -3.921, P<0.05) except left and right parotids. In addition, the speed of auto-segmentation model was 51.28% faster than that of Smart segmentation. Conclusions:In this study, the deep-learning-based auto-segmentation model demonstrated superior performance in accuracy and efficiency on segmenting OARs in H&N CT images, which was better than Smart segmentation software.

OBJECTIVE: This study aimed to investigate the expression and clinical significance of proline-rich tyrosine kinase 2 (Pyk2) and phospho-protein kinase B (p-AKT) in tongue squamous cell carcinoma (TSCC) and adjacent nontumor tissues. METHODS: The Pyk2 and p-AKT protein levels were detected via immunohistochemistry in 45 cases of TSCC tissues and 30 cases of adjacent nontumor tissues. The relationships of the two protein levels and clinicopathological characteristics were also analyzed. RESULTS: Pyk2 and p-AKT levels were significantly higher in the TSCC tissues than in the adjacent nontumor tissues (P<0.05). Nontumor tissues showed poor or no expression. The expression levels of the two proteins were positively correlated (γs=0.412). The expression of Pyk2 was associated with histopathological differentiation type, regional lymph node metastasis, and TNM staging (P<0.05), but not with age and gender. The expression of p-AKT was only related to histopathological differentiation types (P<0.05). CONCLUSIONS The abnormal expression of Pyk2 and p-AKT proteins might be closely related to the development and progression of TSCC. Joint detection can be used as an indicator to estimate the degree of TSCC.
Carcinoma, Squamous Cell ; metabolism ; Focal Adhesion Kinase 2 ; metabolism ; Humans ; Prognosis ; Proto-Oncogene Proteins c-akt ; metabolism ; Tongue Neoplasms ; metabolism