Automatic delineation of organs at risk in non-small cell lung cancer radiotherapy based on deep learning networks

Objective To introduce an end-to-end automatic segmentation method for organs at risk(OARs)in chest computed tomography(CT)images based on dense connection deep learning and to provide an accurate auto-segmentation model to reduce the workload on radiation oncologists.Methods CT images of 36 lung cancer cases were included in this study.Of these,27 cases were randomly selected as the training set,six cases as the validation set,and nine cases as the testing set.The left and right lungs,cord,and heart were auto-segmented,and the training time was set to approximately 5 h.The testing set was evaluated using geometric metrics including the Dice similarity coefficient(DSC),95%Hausdorff distance(HD95),and average surface distance(ASD).Thereafter,two sets of treatment plans were optimized based on manually contoured OARs and automatically contoured OARs,respectively.Dosimetric parameters including Dmax and Vx of the OARs were obtained and compared.Results The proposed model was superior to U-Net in terms of the DSC,HD95,and ASD,although there was no significant difference in the segmentation results yielded by both networks(P>0.05).Compared to manual segmentation,auto-segmentation significantly reduced the segmentation time by nearly 40.7%(P<0.05).Moreover,the differences in dose-volume parameters between the two sets of plans were not statistically significant(P>0.05).Conclusion The bilateral lung,cord,and heart could be accurately delineated using the DenseNet-based deep learning method.Thus,feature map reuse can be a novel approach to medical image auto-segmentation.

Hotspots and difficulties of biliary surgery in older patients

With the accelerated aging society in China,the incidence of biliary surgical diseases in the elderly has increased significantly.The clinical characteristics of these patients indicate that improving treatment outcomes and realizing healthy aging are worthy of attention.How to effectively improve the treatment effect of geriatric biliary surgical diseases has attracted widespread attention.This paper reviews and comments on the hotspots and difficulties of biliary surgery in older patients from six aspects:(1)higher morbidity associated with an aging society,(2)prevention and control of pre-operative risks,(3)extending the indications of laparoscopic surgery,(4)urgent standardization of minimally invasive surgery,(5)precise technological progress in hepatobiliary surgery,and(6)guarantee of peri-operative safety.It is of great significance to fully understand the focus of controversy,actively make use of its favorable factors,and effectively avoid its unfavorable factors,for further improving the therapeutic effects of geriatric biliary surgical diseases,and thus benefits the vast older patients with biliary surgical diseases.Accordingly,a historical record with the highest age of 93 years for laparoscopic transcystic common bile duct exploration has been created by us recently.

Gold nanorods/tetrahedral DNA composites for chemo-photothermal therapy

Combination therapy is extensively developed for cancer treatment in recent years due to its high efficiency.Herein,we constructed a nanocomposite based on gold nanorods(GNRs)and drug-loaded tetrahedral DNA nanostructures(TDN)for chemophotothermal combinational therapy.Anti-tumor drug doxorubicin(DOX)was loaded via the insertion within GC base pairs of TDN.The aptamer AS1411 was attached to the apex of TDN(ATDN)to target tumor cells.The DOX-loaded DNA tetrahedron(ATDN-DOX)was compressed by the GNRs coated with PEI(GNRs@ATDN-DOX)to realize the photothermal function and lysosome escape.GNRs under the illumination of 808nm infrared laser showed high photothermal conversion and stability due to the protection of PEI layer.The drug-loading capacity of ATDN-DOX was as high as 314 DOX molecules in per ATDN.The positive charge of PEI in GNRs@ATDN-DOX nanocomposites was utilized to achieve excellent cell penetration and induce proton sponge effect for lysosomal escape.The nanocomposites presented HeLa and 4T1 cells targeting and resulted in efficient anticancer activity.

Received signal strength indication-based localisation method with unknown path-loss exponent for HVDC electric field measurement

The electric field environment under high-voltage direct current(HVDC)transmission lines is an important design consideration.In the wireless sensor networks for electric field measurement system under the HVDC transmission lines,it is necessary to obtain the electric field distribution with multiple sensors.The accurate localisation of sensing nodes is essential to the analysis of measurement results.However,most current techniques are limited to constant measurement environment with fixed and known path-loss exponent.Here,the authors report a localisation method based on received signal strength indication with unknown path-loss exponent for the localisation of one-dimensional linear topology wireless networks in the electric field measurement system.The optimisation method is utilised to obtain the optimal pass-loss parameter without involving the previous environment parameters.Afterwards,simulations are employed to demonstrate the feasibility and the effectiveness of the proposed method by comparing with other methods.