ObjectiveTo investigate the hotspots from researches on imaging of pancreatic neuroendocrine tumor in recent five years. MethodsThe bibliographies from research literatures on imaging of pancreatic neuroendocrine tumor from 2010 to 2015 in PubMed database were downloaded. The Bicomb 2.0 bibliographies analysis software was used to count high-frequency of Mesh major topics (MJMEs). SPSS 22.0 statistical software was applied for clustering analysis with MJMEs, then to get the topic hotspots. ResultsA total of 357 literatures were screened out during the years of 2010-2015. The MJMEs which frequency > 13 were 28. Taken the 28 MJMEs into clustering analysis, then three research hotspots were clustered. ConclusionResearches on imaging of the pancreatic neuroendocrine tumor in recent five years are mainly in terms of imaging techniques, a comparative study of pathology and endoscopic ultrasonography-fine needle aspiration, imaging and disease treatment.
Objective To analyze relevant literatures of three-dimensional (3D ) imaging in liver using bibiometric analysis, and to provide a current status and hotspot in this filed in future for liver surgeon. Methods The bibliographies of liver 3D imaging from November 2007 to November 2017 in the PubMed database were downloaded. The publication years, journals, the first authors, and the frequency of subject headings+subheadings were extracted by Bicomb 2.0 software. The subject headings+subheadings appeared more than 10 times were intercepted as high frequency ones, then created the high frequency subject headings+subheadings co-occurrence matrix. SPSS 22.0 software was applied for clustering analysis with this matrix to get the topic hotspot. Results A total of 269 literatures were screened out. The research in this field reached its peak in 2016. The core area of journals contained 12 journals. There were 6 authors published at least 3 relevant literatures. The number of high frequency subject headings+subheadings was 16. The research hotspot of liver 3D imaging was precise liver surgery. Conclusion Research hotspot of application of 3D imaging in liver is precise liver surgery in recent 10 years.
ObjectiveTo summarize the application of radiomics in colorectal cancer.MethodsRelevant literatures about the therapeutic decision-making, therapeutic, and prognostic evaluation of colorectal cancer using radiomics were collected to make an review.ResultsRadiomics is of great value in preoperative stages, therapeutic, and prognostic evaluation in colorectal cancer.ConclusionRadiomics is an important part of precision medical imaging for colorectal cancer.
ObjectiveTo realize the current status and hot issues in the field of gastric cancer imaging research, and to provide references for radiologists and gastrointestinal surgeons to grasp the overall overview of gastric cancer imaging.MethodWe downloaded the relevant literatures of gastric cancer imaging published in 2010–2020 in the Web of Science database, and used Citespace 5.7.R3 software for related visual analysis.ResultsA total of 726 articles in the field of gastric cancer imaging research were retrieved and screened. The number of gastric cancer imaging studies published from 2010 to 2020 was on the rise, with the top three countries published in China, Japan, and the United States. The clusters of co-cited literature on gastric cancer imaging: confocal laser microendoscopy, gastric cancer, gastric mucosal intestinal metaplasia, preoperative T staging, convolutional neural network, deep learning, advanced gastric cancer, in vivo differentiation, early stage gastric cancer, surgical treatment, perigastric lymph nodes, nearest neighbor algorithm, and so on. Hot words in recent research fields included: risk factors, characteristics, deep learning, chemotherapy, and neural networks.ConclusionThe imaging diagnosis of early gastric cancer and the application of artificial intelligence are the research hotspots in this field.
ObjectiveTo summarize the application of image texture analysis in the diagnosis and treatment of gastric cancer.MethodsReviewed the literatures on the application of image texture analysis related methods in the diagnosis and treatment of gastric cancer, and summarized the value of texture analysis in the diagnosis and treatment of gastric cancer in terms of diagnosis, staging, curative effect evaluation, and prognosis prediction.ResultsImage texture analysis had been widely used in diagnosis, staging, curative effect evaluation, prognosis prediction of gastric cancer, and other related diagnosis and treatment applications.ConclusionsImage texture analysis is an important part of the diagnosis and treatment of gastric cancer, which has a good development prospect.
ObjectiveTo explore the correlation between the texture features of gastric cancer plain CT images and the expression of HER2.MethodsA retrospective collection the datas of 62 patients with gastric cancer who underwent CT scans of the upper abdomen and (or) the whole abdomen from January 2017 to January 2021 in Leshan City People’s Hospital. The treatment method was surgery. The HER2 expression of gastric cancer tissue was detected after the operation. There were 45 male patients and 17 female patients. Lauren classification: 18 cases of intestinal type, 30 cases of diffuse type, and 14 cases of mixed type. Fifty-two cases were HER2 expression negative [age: (63.54±10.32) years], and 10 cases were HER2 expression positive [age: (61.70±11.70) years]. The MaZda module in the MaZda 4.6 version software was used to perform the image normalization, interest area delineation, texture feature extraction, and texture feature selection on the CT plain scan image, and perform texture feature discrimination and misjudgment rate analysis in the B11 module.ResultsThere was no correlation between HER2 expression and age, gender of patients and Lauren classification of tumors (P>0.05). The analysis methods of nonlinear discriminant analysis (NDA)/artificial neural network (ANN), linear discriminant analysis (LDA)/1-nearest-neighbor (1-NN), principal component analysis (PCA)/1-NN, and raw-data analysis (RDA)/1-NN can better correspond to the CT plain scan texture feature parameters of gastric cancer and the expression level of HER2.ConclusionsTexture analysis based on CT plain images has the potential to non-invasively detect the HER2 expression in gastric cancer. The best comprehensive performance texture discrimination method is NDA/ANN and LDA/1-NN.
ObjectiveTo explore the current status and tendency of the application of CT or MRI in the pancreatic pseudocyst using bibiometric analysis for relative documents, and provide reference information for the future research of radiology. MethodsBibliographies from research literatures of CT or MRI application in the pancreatic pseudocyst from January 1, 2003 to September 20, 2014 in PubMed database were downloaded.The publication years, journals, the first authors, and the frequency of subject headings and subheadings were extracted from them by Bicomb 2.0 software.The subject headings and subheadings appeared more than five times were intercepted as high frequency ones, then created the high frequency subject headings and subheadings co-occurrence matrix.SPSS 22.0 statistical software was applied for clustering analysis with this matrix, then got the major hotspots. ResultsA total of 342 literatures were screened out.The research of CT or MRI application in the pancreatic pseudocyst increased slowly year by year in recent 10 years, then slowly decreased after 2008 year.The related literatures were published in the 164 journals, in which 16 journals (115 literatures were published) were core area distribution according to the Bradford law.There were 10 authors at least 2 published literatures, in who Bhasin DK in USA published 7 literatures, was the most active researcher in this field.The number of high frequency subject headings and subheadings was 33 and among which 5 research hotspots were clustered. ConclusionResearch hotspots about CT or MRI application in pancreatic pseudocyst mainly focuses on five aspects below:pathology, diagnosis, therapy, complications, and etiology.
ObjectiveTo evaluate the predictive value of pancreatic duct diameter and pancreatic gland thickness measured using preoperative CT imaging on pancreatic fistula(PF)following pancreaticoduodenectomy (PD). MethodsOne hundred and fifty-one patients who underwent PD consecutively from January 2013 to April 2014 were reviewed retrospectively. Associations between the gender, age and the pancreatic duct diameter and pancreatic gland thickness from preoperative CT imaging and PF were analyzed. The diagnostic values of the pancreatic duct diameter and pancreatic gland thickness in patients with PF were evaluate by receiver operating characteristic (ROC) analysis. The reliability analysis was done for the pancreatic duct diameter and pancreatic gland thickness by using the intraclass correlation coefficient (ICC). The Spearman rank correlation analysis was done between the pancreatic duct diameter and pancreatic gland thickness. Results①PF occurred in 46 cases (30.1%).②The gender and age were not associated with PF (Gender: χ2=1.698, P=0.193; Age: χ2=0.016, P=0.900). The pancreatic duct diameter and pancreatic gland thickness were associated with PF (Pancreatic duct diameter: OR=0.275, 95% CI 0.164-0.461, P=0.000; Pancreatic gland thickness: OR=1.319, 95% CI 1.163-1.496, P=0.000).③There was no correlation between the pancreatic duct diameter and the pancreatic gland thickness (rs=-0.120, P=0.145).④The area under curve of ROC was 0.814 (95% CI 0.745-0.883, P < 0.001) for the pancreatic duct diameter in predicting the PF, the sensitivity and specificity was 68.6% and 78.3% respectively when the best critical value was 3.5 mm. The area under curve of ROC was 0.762 (95% CI 0.674-0.849, P < 0.001) for the pancreatic gland thickness in predicting PF, the sensitivity and specificity was 63.0% and 85.7% respectively when the best critical value was 31 mm.⑤The ICC of the pancreatic duct diameter and pancreatic gland thickness was 0.984 and 0.992 respectively by two medical diagnostic measurement. ConclusionPancreatic duct diameter and pancreatic gland thickness measured using preoperative CT imaging might be useful in predicting PF following PD.
ObjectiveTo evaluate the CT findings and causes of thrombosis formation after transjugular intrahepatic portosystemic shunt (TIPS). MethodsOne hundred forty-two patients with cirrhosis after TIPS were included. The imaging features of thrombus in the stent after TIPS were recorded and causes of thrombosis formation were analyzed. The presence, location and amount of thrombus, the location of ends of TIPS stent were analyzed. ResultsThe incidence of thrombosis formation after TIPS was 19.0% (27/142). The thrombus could locate around the upper end (7.4%), lower end (18.6%) of the stent and inside the stent (74.0%), there was significant differences in the incidence of stent thrombosis in different locations (P < 0.05). The thrombus might presented as little mural thrombus (12/27, 44.4%), marked thrombus (3/27, 11.1%) and thrombotic occlusion (12/27, 44.4%), there was a significant difference in the incidence of stent thrombosis with different thrombus volume (P < 0.05). There were stent outlet vascular stenosis in most patients with stent thrombosis (88.9%). ConclusionsStent thrombosis after TIPS is common. Dual source computed tomography angiography could evaluate the thrombotic features. Stent outlet vascular stenosis might be associated with thrombosis formation after TIPS.
ObjectiveTo investigate researches on pancreatic neoplasms and molecular imaging in recent five years and provide reference information for the majority of professionals in deep research. MethodsBibliographies from research literature of pancreatic neoplasms and molecular imaging in recent five years in PubMed database were downloaded. The publication years, journals, countries of publication, the first authors and the frequency of MJMEs were counted by Bicomb 2.0 software. The affiliations were analyzed artificially. MJMEs appeared no less than two times were intercepted as high frequency ones and the high frequency MJMEs co-occurrence matrix were formed. SPSS 22.0 statistical software were applied for clustering analysis with matrix, then to get the topic hotspots. ResultsA total of 28 literatures were screened out. The data of research trend, journals, research degree of countries were acquired. The number of high frequency MJMEs were 20 and among which 5 research hotspots were clustered. ConclusionsResearches on pancreatic neoplasms and molecular imaging are mainly in terms of therapy and genetics, diagnosis and metabolism, radionuclide imaging, pharmacology and pathology.