Preoperative prediction of lymphovascular and perineural invasion in gastric cancer using spectral computed tomography imaging and machine learning

BACKGROUND Lymphovascular invasion(LVI)and perineural invasion(PNI)are important prognostic factors for gastric cancer(GC)that indicate an increased risk of metastasis and poor outcomes.Accurate preoperative prediction of LVI/PNI status could help clinicians identify high-risk patients and guide treatment deci-sions.However,prior models using conventional computed tomography(CT)images to predict LVI or PNI separately have had limited accuracy.Spectral CT provides quantitative enhancement parameters that may better capture tumor invasion.We hypothesized that a predictive model combining clinical and spectral CT parameters would accurately preoperatively predict LVI/PNI status in GC patients.AIM To develop and test a machine learning model that fuses spectral CT parameters and clinical indicators to predict LVI/PNI status accurately.METHODS This study used a retrospective dataset involving 257 GC patients(training cohort,n=172;validation cohort,n=85).First,several clinical indicators,including serum tumor markers,CT-TN stages and CT-detected extramural vein invasion(CT-EMVI),were extracted,as were quantitative spectral CT parameters from the delineated tumor regions.Next,a two-step feature selection approach using correlation-based methods and information gain ranking inside a 10-fold cross-validation loop was utilized to select informative clinical and spectral CT parameters.A logistic regression(LR)-based nomogram model was subsequently constructed to predict LVI/PNI status,and its performance was evaluated using the area under the receiver operating characteristic curve(AUC).RESULTS In both the training and validation cohorts,CT T3-4 stage,CT-N positive status,and CT-EMVI positive status are more prevalent in the LVI/PNI-positive group and these differences are statistically significant(P<0.05).LR analysis of the training group showed preoperative CT-T stage,CT-EMVI,single-energy CT values of 70 keV of venous phase(VP-70 keV),and the ratio of standardized iodine concentration of equilibrium phase(EP-NIC)were independent influencing factors.The AUCs of VP-70 keV and EP-NIC were 0.888 and 0.824,respectively,which were slightly greater than those of CT-T and CT-EMVI(AUC=0.793,0.762).The nomogram combining CT-T stage,CT-EMVI,VP-70 keV and EP-NIC yielded AUCs of 0.918(0.866-0.954)and 0.874(0.784-0.936)in the training and validation cohorts,which are significantly higher than using each of single independent factors(P<0.05).CONCLUSION The study found that using portal venous and EP spectral CT parameters allows effective preoperative detection of LVI/PNI in GC,with accuracy boosted by integrating clinical markers.

Computed tomography for prediction of esophageal variceal bleeding

This letter to the editor relates to the study entitled“The role of computed tomography for the prediction of esophageal variceal bleeding:Current status and future perspectives”.Esophageal variceal bleeding(EVB)is one of the most common and severe complications related to portal hypertension(PH).Despite marked advances in its management during the last three decades,EVB is still associated with significant morbidity and mortality.The risk of first EVB is related to the severity of both PH and liver disease,and to the size and endoscopic appearance of esophageal varices.Indeed,hepatic venous pressure gradient(HVPG)and esophagogastroduodenoscopy(EGD)are currently recognized as the“gold standard”and the diagnostic reference standard for the prediction of EVB,respectively.However,HVPG is an invasive,expensive,and technically complex procedure,not widely available in clinical practice,whereas EGD is mainly limited by its invasive nature.In this scenario,computed tomography(CT)has been recently proposed as a promising modality for the non-invasive prediction of EVB.While CT serves solely as a diagnostic tool and cannot replace EGD or HVPG for delivering therapeutic and physiological information,it has the potential to enhance the prediction of EVB more effectively when combined with liver disease scores,HVPG,and EGD.However,to date,evidence concerning the role of CT in this setting is still lacking,therefore we aim to summarize and discuss the current evidence concerning the role of CT in predicting the risk of EVB.

Computed tomography radiogenomics:A potential tool for prediction of molecular subtypes in gastric stromal tumor

BACKGROUND Preoperative knowledge of mutational status of gastrointestinal stromal tumors(GISTs)is essential to guide the individualized precision therapy.AIM To develop a combined model that integrates clinical and contrast-enhanced computed tomography(CE-CT)features to predict gastric GISTs with specific genetic mutations,namely KIT exon 11 mutations or KIT exon 11 codons 557-558 deletions.METHODS A total of 231 GIST patients with definitive genetic phenotypes were divided into a training dataset and a validation dataset in a 7:3 ratio.The models were constructed using selected clinical features,conventional CT features,and radiomics features extracted from abdominal CE-CT images.Three models were developed:ModelCT sign,modelCT sign+rad,and model CTsign+rad+clinic.The diagnostic performance of these models was evaluated using receiver operating characteristic(ROC)curve analysis and the Delong test.RESULTS The ROC analyses revealed that in the training cohort,the area under the curve(AUC)values for model_(CT sign),model_(CT sign+rad),and modelCT_(sign+rad+clinic)for predicting KIT exon 11 mutation were 0.743,0.818,and 0.915,respectively.In the validation cohort,the AUC values for the same models were 0.670,0.781,and 0.811,respectively.For predicting KIT exon 11 codons 557-558 deletions,the AUC values in the training cohort were 0.667,0.842,and 0.720 for model_(CT sign),model_(CT sign+rad),and modelCT_(sign+rad+clinic),respectively.In the validation cohort,the AUC values for the same models were 0.610,0.782,and 0.795,respectively.Based on the decision curve analysis,it was determined that the model_(CT sign+rad+clinic)had clinical significance and utility.CONCLUSION Our findings demonstrate that the combined modelCT_(sign+rad+clinic)effectively distinguishes GISTs with KIT exon 11 mutation and KIT exon 11 codons 557-558 deletions.This combined model has the potential to be valuable in assessing the genotype of GISTs.

Computed tomography for the prediction of oesophageal variceal bleeding:A surrogate or complementary to the gold standard?

In this editorial we comment on the in-press article in the World Journal of Gastrointestinal endoscopy about the role of computed tomography(CT)for the prediction of esophageal variceal bleeding.The mortality and morbidity are much increased in patients with chronic liver diseases when complicated with variceal bleeding.Predicting the patient at a risk of bleeding is extremely important and receives a great deal of attention,paving the way for primary prophylaxis either using medical treatment including carvedilol or propranolol,or endoscopic band ligation.Endoscopic examination and the hepatic venous pressure gradient are the gold standards in the diagnosis and prediction of variceal bleeding.Several non-invasive laboratory and radiological examinations are used for the prediction of variceal bleeding.The contrast-enhanced multislice CT is a widely used non-invasive,radiological examination that has many advantages.In this editorial we briefly comment on the current research regarding the use of CT as a non-invasive tool in predicting the variceal bleeding.

Predictive visual field outcomes after optic chiasm decompressive surgery by retinal vessels parameters using optical coherence tomography angiography

AIM:To evaluate the predictive value of superficial retinal capillary plexus(SRCP)and radial peripapillary capillary(RPC)for visual field recovery after optic cross decompression and compare them with peripapillary nerve fiber layer(pRNFL)and ganglion cell complex(GCC).METHODS:This prospective longitudinal observational study included patients with chiasmal compression due to sellar region mass scheduled for decompressive surgery.Generalized estimating equations were used to compare retinal vessel density and retinal layer thickness preand post-operatively and with healthy controls.Logistic regression models were used to assess the relationship between preoperative GCC,pRNFL,SRCP,and RPC parameters and visual field recovery after surgery.RESULTS:The study included 43 eyes of 24 patients and 48 eyes of 24 healthy controls.Preoperative RPC and SRCP vessel density and pRNFL and GCC thickness were lower than healthy controls and higher than postoperative values.The best predictive GCC and pRNFL models were based on the superior GCC[area under the curve(AUC)=0.866]and the tempo-inferior pRNFL(AUC=0.824),and the best predictive SRCP and RPC models were based on the nasal SRCP(AUC=0.718)and tempo-inferior RPC(AUC=0.825).There was no statistical difference in the predictive value of the superior GCC,tempo-inferior pRNFL,and tempo-inferior RPC(all P>0.05).CONCLUSION:Compression of the optic chiasm by tumors in the saddle area can reduce retinal thickness and blood perfusion.This reduction persists despite the recovery of the visual field after decompression surgery.GCC,pRNFL,and RPC can be used as sensitive predictors of visual field recovery after decompression surgery.

Computed tomography-based radiomics to predict early recurrence of hepatocellular carcinoma post-hepatectomy in patients background on cirrhosis

BACKGROUND The prognosis for hepatocellular carcinoma(HCC)in the presence of cirrhosis is unfavourable,primarily attributable to the high incidence of recurrence.AIM To develop a machine learning model for predicting early recurrence(ER)of posthepatectomy HCC in patients with cirrhosis and to stratify patients’overall survival(OS)based on the predicted risk of recurrence.METHODS In this retrospective study,214 HCC patients with cirrhosis who underwent curative hepatectomy were examined.Radiomics feature selection was conducted using the least absolute shrinkage and selection operator and recursive feature elimination methods.Clinical-radiologic features were selected through univariate and multivariate logistic regression analyses.Five machine learning methods were used for model comparison,aiming to identify the optimal model.The model’s performance was evaluated using the receiver operating characteristic curve[area under the curve(AUC)],calibration,and decision curve analysis.Additionally,the Kaplan-Meier(K-M)curve was used to evaluate the stratification effect of the model on patient OS.RESULTS Within this study,the most effective predictive performance for ER of post-hepatectomy HCC in the background of cirrhosis was demonstrated by a model that integrated radiomics features and clinical-radiologic features.In the training cohort,this model attained an AUC of 0.844,while in the validation cohort,it achieved a value of 0.790.The K-M curves illustrated that the combined model not only facilitated risk stratification but also exhibited significant discriminatory ability concerning patients’OS.CONCLUSION The combined model,integrating both radiomics and clinical-radiologic characteristics,exhibited excellent performance in HCC with cirrhosis.The K-M curves assessing OS revealed statistically significant differences.

Computed tomography-based nomogram of Siewert type Ⅱ/Ⅲ adenocarcinoma of esophagogastric junction to predict response to docetaxel, oxaliplatin and S-1

BACKGROUND Neoadjuvant chemotherapy(NAC)has become the standard care for advanced adenocarcinoma of esophagogastric junction(AEG),although a part of the patients cannot benefit from NAC.There are no models based on baseline computed tomography(CT)to predict response of Siewert type II or III AEG to NAC with docetaxel,oxaliplatin and S-1(DOS).AIM To develop a CT-based nomogram to predict response of Siewert type II/III AEG to NAC with DOS.METHODS One hundred and twenty-eight consecutive patients with confirmed Siewert type II/III AEG underwent CT before and after three cycles of NAC with DOS,and were randomly and consecutively assigned to the training cohort(TC)(n=94)and the validation cohort(VC)(n=34).Therapeutic effect was assessed by disease-control rate and progressive disease according to the Response Evaluation Criteria in Solid Tumors(version 1.1)criteria.Possible prognostic factors associated with responses after DOS treatment including Siewert classification,gross tumor volume(GTV),and cT and cN stages were evaluated using pretherapeutic CT data in addition to sex and age.Univariate and multivariate analyses of CT and clinical features in the TC were performed to determine independent factors associated with response to DOS.A nomogram was established based on independent factors to predict the response.The predictive performance of the nomogram was evaluated by Concordance index(C-index),calibration and receiver operating characteristics curve in the TC and VC.RESULTS Univariate analysis showed that Siewert type(52/55 vs 29/39,P=0.005),pretherapeutic cT stage(57/62 vs 24/32,P=0.028),GTV(47.3±27.4 vs 73.2±54.3,P=0.040)were significantly associated with response to DOS in the TC.Multivariate analysis of the TC also showed that the pretherapeutic cT stage,GTV and Siewert type were independent predictive factors related to response to DOS(odds ratio=4.631,1.027 and 7.639,respectively;all P<0.05).The nomogram developed with these independent factors showed an excellent performance to predict response to DOS in the TC and VC(C-index:0.838 and 0.824),with area under the receiver operating characteristic curve of 0.838 and 0.824,respectively.The calibration curves showed that the practical and predicted response to DOS effectively coincided.CONCLUSION A novel nomogram developed with pretherapeutic cT stage,GTV and Siewert type predicted the response of Siewert type II/III AEG to NAC with DOS.

Future directions of noninvasive prediction of esophageal variceal bleeding:No worry about the present computed tomography inefficiency

In this editorial,we comment on the minireview by Martino A,published in the recent issue of World Journal of Gastrointestinal Endoscopy 2023;15(12):681-689.We focused mainly on the possibility of replacing the hepatic venous pressure gradient(HVPG)and endoscopy with noninvasive methods for predicting esophageal variceal bleeding.The risk factors for bleeding were the size of the varices,the red sign and the Child-Pugh score.The intrinsic core factor that drove these changes was the HVPG.Therefore,the present studies investigating noninvasive methods,including computed tomography,magnetic resonance imaging,elastography,and laboratory tests,are working on correlating imaging or serum marker data with intravenous pressure and clinical outcomes,such as bleeding.A single parameter is usually not enough to construct an efficient model.Therefore,multiple factors were used in most of the studies to construct predictive models.Encouraging results have been obtained,in which bleeding prediction was partly reached.However,these methods are not satisfactory enough to replace invasive methods,due to the many drawbacks of different studies.There is still plenty of room for future improvement.Prediction of the precise timing of bleeding using various models,and extracting the texture of variceal walls using high-definition imaging modalities to predict the red sign are interesting directions to lay investment on.

Extravasated contrast volumetric assessment on computed tomography angiography in gastrointestinal bleeding:A useful predictor of positive angiographic findings

BACKGROUND Gastrointestinal bleeding(GIB)is a severe and potentially life-threatening condition,especially in cases of delayed treatment.Computed tomography angiography(CTA)plays a pivotal role in the early identification of upper and lower GIB and in the prompt treatment of the haemorrhage.AIM To determine whether a volumetric estimation of the extravasated contrast at CTA in GIB may be a predictor of subsequent positive angiographic findings.METHODS In this retrospective single-centre study,35 patients(22 men;median age 69 years;range 16-92 years)admitted to our institution for active GIB detected at CTA and further submitted to catheter angiography between January 2018 and February 2022 were enrolled.Twenty-three(65.7%)patients underwent endoscopy before CTA.Bleeding volumetry was evaluated in both arterial and venous phases via a semi-automated dedicated software.Bleeding rate was obtained from volume change between the two phases and standardised for unit time.Patients were divided into two groups,according to the angiographic signs and their concordance with CTA.RESULTS Upper bleeding accounted for 42.9%and lower GIB for 57.1%.Mean haemoglobin value at the admission was 7.7 g/dL.A concordance between positive CTA and direct angiographic bleeding signs was found in 19(54.3%)cases.Despite no significant differences in terms of bleeding volume in the arterial phase(0.55 mL vs 0.33 mL,P=0.35),a statistically significant volume increase in the venous phase was identified in the group of patients with positive angiography(2.06 mL vs 0.9 mL,P=0.02).In the latter patient group,a significant increase in bleeding rate was also detected(2.18 mL/min vs 0.19 mL/min,P=0.02).CONCLUSION In GIB of any origin,extravasated contrast volumetric analysis at CTA could be a predictor of positive angiography and may help in avoiding further unnecessary procedures.

企业投入数字化的污染减排效应——基于ICT产品进口的视角

ICT产品进口作为企业投入数字化的重要表现形式,可以为企业污染减排提供重要支撑。文章基于2002—2012年中国海关贸易数据库、中国工业企业污染数据库和中国工业企业数据库的合并数据,利用双重差分法识别ICT产品进口对企业污染减排的影响。结果显示,ICT产品进口能够显著降低企业污染物排放强度,且经过一系列稳健性检验后该结论仍然成立。机制检验表明:一方面,ICT产品进口通过提升全要素生产率,促进企业产出规模增长,进而降低企业污染物排放强度;另一方面,ICT产品进口通过优化能源结构、提高能源效率,降低企业污染物排放规模,进而降低企业污染物排放强度。此外,ICT产品进口对大规模企业、技术密集型行业企业和数字经济发展水平较高地区企业的污染减排效应更为明显。基于研究结论,未来可通过鼓励和扩大ICT产品进口、推动ICT产品核心技术研发创新、拓展ICT产品应用场景等途径,实现企业数字化转型与污染减排协同发展。

产教融合背景下的高校ICT类专业实训基地建设研究

产教融合是当前高等教育领域的热门话题,如何开展校企深度合作,打造一流的产教融合实训基地,改革创新校企共同育人的教学方法和教学模式,培养学生综合实践技能以及创新创业综合素质,提升人才培养质量是很多高等院校一直在思考的问题.通过对ICT类专业产教融合实训基地建设进行深入研究,提出了一些方法与途径,以促进高等院校与企业在教学、生产和创新创业工作方面的相互配合、相互支持,有效推进校企合作共赢.

ICT服务贸易与制造业全球价值链地位提升

ICT服务贸易作为当前中国数字服务贸易中发展最快的贸易类型,已经成为提升制造业在全球价值链地位的新“动能”。利用2007-2021年57个国家14个产业的面板数据,从理论和经验角度分析了ICT服务贸易对制造业全球价值链地位的影响。结果显示:ICT服务贸易的出口和进口都有助于提升一国制造业在全球价值链的地位,使用替换被解释变量和工具变量的方法检验后,结果依旧稳健。引入中介变量后发现,ICT服务贸易也可通过降低贸易成本和提升制造业投入信息化水平,间接地推动本国制造业在全球价值链地位的提升。进一步研究表明,ICT服务贸易对资本密集型产业在全球价值链地位的影响最强,劳动密集型次之,技术密集型最弱,而以技术水平为产业分类标准,ICT服务贸易在高技术产业对全球价值链地位的正向作用最强,低技术产业次之,中技术产业最弱。以上结论为提升中国ICT服务贸易水平和制造业全球价值链地位提供参考依据。

信息技术服务智慧城市建设的理论与方法——评《智慧城市建设——大数据分析、信息技术(ICT)与设计思维》

城市化是社会发展的必然趋势。现代社会,城市的发展主要依托信息技术,人们将信息技术与诸多产业相结合,可实现城市信息共享,为城市居民提供更完善的民生服务,从而构建新型智慧城市。本文参考由卡罗尔·斯蒂梅尔(Carol L.Stimmel)著,李晓峰译,机械工业出版社出版的《智慧城市建设——大数据分析、信息技术(ICT)与设计思维》一书,该书阐述了作者20余年来对智慧城市和新兴技术的思考,分析了当前人类对城市发展的真实需求,提出了利用信息技术建设现代化智慧城市的方法,为现代城市发展提供了参考。

基于华为ICT大赛为载体“课-证-赛”融通的ICT产业人才培养模式的改革研究

高技能人才已经成为国家的重要战略资源,培养高技能人才是应用型本科教育实现高端发展优化人才结构的必然选择。应用型本科教育急需创新体现类型教育特征的育人模式,桂林电子科技大学北海校区(以下简称桂电北海校区)多年协办华为ICT大赛区赛,在推广运营华为ICT大赛的过程中,建设了“课-证-赛”融通的ICT产业人才培养体系,全面将华为职业认证和华为ICT大赛比赛内容融入ICT产业人才培养课程体系中。 。

The role of computed tomography for the prediction of esophageal variceal bleeding:Current status and future perspectives

Esophageal variceal bleeding(EVB)is one of the most common and severe complications related to portal hypertension(PH).Despite marked advances in its management during the last three decades,EVB is still associated with significant morbidity and mortality.The risk of first EVB is related to the severity of both PH and liver disease,and to the size and endoscopic appearance of esophageal varices.Indeed,hepatic venous pressure gradient(HVPG)and esophagogastroduodenoscopy(EGD)are currently recognized as the“gold standard”and the diagnostic reference standard for the prediction of EVB,respectively.However,HVPG is an invasive,expensive,and technically complex procedure,not widely available in clinical practice,whereas EGD is mainly limited by its invasive nature.In this scenario,computed tomography(CT)has been recently proposed as a promising modality for the non-invasive prediction of EVB.Although CT is only a diagnostic modality,thus being not capable of supplanting EGD or HVPG in providing therapeutic and physiological data,it could potentially assist liver disease scores,HVPG,and EGD in a more effective prediction of EVB.However,to date,evidence concerning the role of CT in this setting is still lacking.Our review aimed to summarize and discuss the current evidence concerning the role of CT in predicting the risk of EVB.

Can visceral fat parameters based on computed tomography be used to predict occult peritoneal metastasis in gastric cancer?

BACKGROUND The preoperative prediction of peritoneal metastasis(PM)in gastric cancer would prevent unnecessary surgery and promptly indicate an appropriate treatment plan.AIM To explore the predictive value of visceral fat(VF)parameters obtained from preoperative computed tomography(CT)images for occult PM and to develop an individualized model for predicting occult PM in patients with gastric carcinoma(GC).METHODS A total of 128 confirmed GC cases(84 male and 44 female patients)that underwent CT scans were analyzed and categorized into PM-positive(n=43)and PM-negative(n=85)groups.The clinical characteristics and VF parameters of two regions of interest(ROIs)were collected.Univariate and stratified analyses based on VF volume were performed to screen for predictive characteristics for occult PM.Prediction models with and without VF parameters were established by multivariable logistic regression analysis.RESULTS The mean attenuations of VF_(ROI 1)and VF_(ROI 2)varied significantly between the PM-positive and PMnegative groups(P=0.044 and 0.001,respectively).The areas under the receiver operating characteristic curves(AUCs)of VF_(ROI 1)and VF_(ROI 2)were 0.599 and 0.657,respectively.The mean attenuation of VF_(ROI 2)was included in the final prediction combined model,but not an independent risk factor of PM(P=0.068).No significant difference was observed between the models with and without mean attenuation of VF(AUC:0.749 vs 0.730,P=0.339).CONCLUSION The mean attenuation of VF is a potential auxiliary parameter for predicting occult PM in patients with GC.

Radiomics model based on contrast-enhanced computed tomography to predict early recurrence in patients with hepatocellular carcinoma after radical resection

BACKGROUND Radical resection remains an effective strategy for patients with hepatocellular carcinoma(HCC).Unfortunately,the postoperative early recurrence(recurrence within 2 years)rate is still high.AIM To develop a radiomics model based on preoperative contrast-enhanced computed tomography(CECT)to evaluate early recurrence in HCC patients with a single tumour.METHODS We enrolled a total of 402 HCC patients from two centres who were diagnosed with a single tumour and underwent radical resection.First,the features from the portal venous and arterial phases of CECT were extracted based on the region of interest,and the early recurrence-related radiomics features were selected via the least absolute shrinkage and selection operator proportional hazards model(LASSO Cox)to determine radiomics scores for each patient.Then,the clinicopathologic data were combined to develop a model to predict early recurrence by Cox regression.Finally,we evaluated the prediction performance of this model by multiple methods.RESULTS A total of 1915 radiomics features were extracted from CECT images,and 31 of them were used to determine the radiomics scores,which showed a significant difference between the early recurrence and nonearly recurrence groups.Univariate and multivariate Cox regression analyses showed that radiomics scores and serum alphafetoprotein were independent indicators,and they were used to develop a combined model to predict early recurrence.The area under the receiver operating characteristic curve values for the training and validation cohorts were 0.77 and 0.74,respectively,while the C-indices were 0.712 and 0.674,respectively.The calibration curves and decision curve analysis showed satisfactory accuracy and clinical utilities.Kaplan-Meier curves based on recurrence-free survival and overall survival showed significant differences.CONCLUSION The preoperative radiomics model was shown to be effective for predicting early recurrence among HCC patients with a single tumour.

ICT资本对旅游绿色发展效率的影响机理研究

ICT资本赋能旅游业绿色转型,驱动旅游业走向高质量发展道路。文章创新性地核算了中国30个省(区、市)的ICT资本和旅游绿色发展效率,采用SYSGMM和空间杜宾模型验证了ICT资本对旅游绿色发展效率的影响机制及其空间溢出效应。研究结果表明:(1)ICT资本对旅游绿色发展效率具有持续的积极影响。(2)ICT资本主要通过激发旅游技术创新、优化旅游产业结构、提升旅游人力资本来提高旅游绿色发展效率。(3)ICT资本对旅游绿色发展效率具有正向的空间溢出效应,且空间间接效应强于直接效应。在地理矩阵下,ICT资本对东部和西部省(区、市)的旅游绿色发展效率具有显著的空间溢出效应;而在经济矩阵下,东部和中部省(区、市)旅游绿色发展效率受ICT资本影响较显著。这为中国充分释放ICT资本红利,塑造中国旅游绿色发展格局,全面提升旅游绿色发展效率提供了价值指导。

全球价值链参与度对ICT制造业产品出口的影响研究

数字经济时代,资本、技术密集型产业的代表——ICT制造业的全球价值链(GVC)分工最为深入。基于2000—2018年61个国家和地区的数据,深入考察了ICT产业GVC参与度对ICT制造业产品出口的影响。研究发现:ICT制造业GVC参与度对ICT制造业产品出口规模影响显著为正;分维度看,ICT制造业GVC前向参与度对ICT制造业产品出口额的影响显著为负,GVC后向参与度对ICT制造业产品出口额的影响显著为正;异质性检验结果表明,发达国家和地区ICT制造业GVC参与度对ICT制造业产品出口额的影响显著为正,且GVC后向参与度比GVC前向参与度更有利于出口规模的扩大,然而深化GVC后向参与度固然有助于其贸易规模扩大,但从盈利能力角度看却并非最优;发展中国家和地区ICT制造业GVC参与度对ICT制造业产品出口额的影响显著为负,且GVC后向参与度对出口规模的负向影响显然更深,加深GVC前向参与度有助于减轻其对出口规模的负向效应。

Biliary complications after liver transplantation:A computed tomography and magnetic resonance imaging pictorial review

Biliary complications are the most common complications after liver transplantation.Computed tomography(CT)and magnetic resonance imaging(MRI)are cornerstones for timely diagnosis of biliary complications after liver transplantation.The diagnosis of these complications by CT and MRI requires expertise,mainly with respect to identifying subtle early signs to avoid missed or incorrect diagnoses.For example,biliary strictures may be misdiagnosed on MRI due to size mismatch of the common ducts of the donor and recipient,postoperative edema,pneumobilia,or susceptibility artifacts caused by surgical clips.Proper and prompt diagnosis of biliary complications after transplantation allows the timely initiation of appropriate management.The aim of this pictorial review is to illustrate various CT and MRI findings related to biliary complications after liver transplantation,based on time of presentation after surgery and frequency of occurrence.