Radiomics in Oncology: A 10-Year Bibliometric Analysis

Predicting vertebral compression fracture prior to spinal SBRT using radiomics from planning CT

PURPOSE

The purpose of the study was to develop a predictive model for vertebral compression fracture (VCF) prior to spinal stereotactic body radiation therapy (SBRT) using radiomics features extracted from pre-treatment planning CT images.

METHODS

A retrospective analysis was conducted on 85 patients (114 spinal lesions) who underwent spinal SBRT. Radiomics features were extracted from pre-treatment planning CT images and used to develop a predictive model using a classification algorithm selected from nine different machine learning algorithms. Four different models were trained, including clinical features only, clinical and radiomics features, radiomics and dosimetric features, and all features. Model performance was evaluated using accuracy, precision, recall, F1-score, and area under the curve (AUC).

RESULTS

The model that used all features (radiomics, clinical, and dosimetric) showed the highest performance with an AUC of 0.871. The radiomics and dosimetric features model had the superior performance in terms of accuracy, precision, recall, and F1-score.

CONCLUSION

The developed predictive model based on radiomics features extracted from pre-treatment planning CT images can accurately predict the likelihood of VCF prior to spinal SBRT. This model has significant implications for treatment planning and preventive measures for patients undergoing spinal SBRT. Future research can focus on improving model performance by incorporating new data and external validation using independent data sets.

The landscape of hot topics and research frontiers in Kawasaki disease: Scientometric analysis

Purpose

Kawasaki disease(KD) is a vascular inflammatory disease that was first identified in 1967. Numerous studies have been conducted on KD and have yielded valuable recent insights. This current bibliometric analysis aimed to determine the intellectual landscape of research interest in KD.

Methods

Publications were collected from the Web of Science Core Collection. Bibliometric tools such as CiteSpace and VOSviewer were utilized to analyze the research focus, emerging trends, frontiers, and hot topics in this specific field.

Results

A total of 6122 articles on KD were retrieved. Pediatric Cardiology, Pediatrics International, and Pediatric Infections Disease Journal were the three most productive journals reporting KD development. The University of California San Diego was the most productive institution, with 230 publications. The USA was the most productive country, with 1661 articles in KD. SARS-CoV-2, diagnostic serum biomarkers, and risk factor prediction models for coronary arterial lesions and subtypes of KD are popular topics in KD research. Factors that induce smooth muscle cell transition to myofibroblastic cell, potentially halting the subacute/chronic vasculitis process and endothelial dysfunction in macrophage activation syndrome associated with KD were the frontiers in the study of KD.

Conclusion

KD has attracted widespread attention worldwide that has continued to increase since 1974. The most productive institution and country are the University of California San Diego and the USA, respectively. SARS-CoV-2, serum biomarkers, and prediction models are hot topics in this field.

Utilization of Radiomics Features Extracted From Preoperative Medical Images to Detect Metastatic Lymph Nodes in Cholangiocarcinoma and Gallbladder Cancer Patients: A Systemic Review and Meta-analysis

OBJECTIVES

This study aimed to determine the methodological quality and evaluate the diagnostic performance of radiomics features in detecting lymph node metastasis on preoperative images in patients with cholangiocarcinoma and gallbladder cancer.

METHODS

Publications between January 2005 and October 2022 were considered for inclusion. Databases such as Pubmed/Medline, Scopus, Embase, and Google Scholar were searched for relevant studies. The quality of the methodology of the manuscripts was determined using the Radiomics Quality Score and Quality Assessment of Diagnostic Accuracy Studies 2. Pooled results with corresponding 95% confidence intervals (CIs) were calculated using the DerSimonian-Liard method (random-effect model). Forest plots were used to visually represent the diagnostic profile of radiomics signature in each of the data sets pertaining to each study. Fagan plot was used to determine clinical applicability.

RESULTS

Overall sensitivity was 0.748 (95% CI, 0.703-0.789). Overall specificity was 0.795 (95% CI, 0.742-0.839). The combined negative likelihood ratio was 0.299 (95% CI, 0.266-0.350), and the positive likelihood ratio was 3.545 (95% CI, 2.850-4.409). The combined odds ratio of the studies was 12.184 (95% CI, 8.477-17.514). The overall summary receiver operating characteristics area under the curve was 0.83 (95% CI, 0.80-0.86). Three studies applied nomograms to 8 data sets and achieved a higher pooled sensitivity and specificity (0.85 [0.80-0.89] and 0.85 [0.71-0.93], respectively).

CONCLUSIONS

The pooled analysis showed that predictive models fed with radiomics features achieve good sensitivity and specificity in detecting lymph node metastasis in computed tomography and magnetic resonance imaging images. Supplementation of the models with biological correlates increased sensitivity and specificity in all data sets.

Trends and Hotspots in Global Radiomics Research: A Bibliometric Analysis

Objectives: The purpose of this research is to summarize the structure of radiomics-based knowledge and to explore potential trends and priorities by using bibliometric analysis. Methods: Select radiomics-related publications from 2012 to October 2022 from the Science Core Collection Web site. Use VOSviewer (version 1.6.18), CiteSpace (version 6.1.3), Tableau (version 2022), Microsoft Excel and Rstudio's free online platforms (http://bibliometric.com) for co-writing, co-citing, and co-occurrence analysis of countries, institutions, authors, references, and keywords in the field. The visual analysis is also carried out on it. Results: The study included 6428 articles. Since 2012, there has been an increase in research papers based on radiomics. Judging by publications, China has made the largest contribution in this area. We identify the most productive institutions and authors as Fudan University and Tianjie. The top three magazines with the most publications are《FRONTIERS IN ONCOLOGY》, 《EUROPEAN RADIOLOGY》, and 《CANCERS》. According to the results of reference and keyword analysis, "deep learning, nomogram, ultrasound, f-18-fdg, machine learning, covid-19, radiogenomics" has been determined as the main research direction in the future. Conclusion: Radiomics is in a phase of vigorous development with broad prospects. Cross-border cooperation between countries and institutions should be strengthened in the future. It can be predicted that the development of deep learning-based models and multimodal fusion models will be the focus of future research. Advances in knowledge: This study explores the current state of research and hot spots in the field of radiomics from multiple perspectives, comprehensively, and objectively reflecting the evolving trends in imaging-related research and providing a reference for future research.

The Application of Deep Brain Stimulation for Parkinson's Disease on the Motor Pathway: A Bibliometric Analysis across 10 Years

BACKGROUND AND OBJECTIVE

Since its initial report by James Parkinson in 1817, Parkinson's disease (PD) has remained a central subject of research and clinical advancement. The disease is estimated to affect approximately 1% of adults aged 60 and above. Deep brain stimulation, emerging as an alternative therapy for end-stage cases, has offered a lifeline to numerous patients. This review aimed to analyze publications pertaining to the impact of deep brain stimulation on the motor pathway in patients with PD over the last decade.

METHODS

Data were obtained from the Web of Science Core Collection through the library of Huazhong University of Science and Technology (China). The search strategy encompassed the following keywords: "deep brain stimulation", "Parkinson's disease", "motor pathway", and "human", from January 1, 2012, to December 1, 2022. Additionally, this review visualized the findings using the Citespace software.

RESULTS

The results indicated that the United States, the United Kingdom, Germany, and China were the primary contributors to this research field. University College London, Capital Medical University, and Maastricht University were the top 3 research institutions in the research area. Tom Foltynie ranked first with 6 publications, and the journals of Brain and Brain Stimulation published the greatest number of relevant articles. The prevailing research focal points in this domain, as determined by keywords "burst analysis", "encompassed neuronal activity", "nucleus", "hyper direct pathway", etc. CONCLUSION: This study has provided a new perspective through bibliometric analysis of the deep brain stimulation therapy for treating patients with PD, which can shed light on future research to advance our comprehension of this particular field of study.

Can radiomics be used to detect hypoxic-ischemic encephalopathy in neonates without magnetic resonance imaging abnormalities?

BACKGROUND

No study has assessed normal magnetic resonance imaging (MRI) findings to predict potential brain injury in neonates with hypoxic-ischemic encephalopathy (HIE).

OBJECTIVE

We aimed to evaluate the efficacy of MRI-based radiomics models of the basal ganglia, thalami and deep medullary veins to differentiate between HIE and the absence of MRI abnormalities in neonates.

MATERIALS AND METHODS

In this study, we included 38  full-term neonates with HIE and normal MRI findings and 89 normal neonates. Radiomics features were extracted from T1-weighted images, T2-weighted images, diffusion-weighted imaging and susceptibility-weighted imaging (SWI). The different models were evaluated using receiver operating characteristic curve analysis. Clinical utility was evaluated using decision curve analysis.

RESULTS

The SWI model exhibited the best performance among the seven single-sequence models. For the training and validation cohorts, the area under the curves (AUCs) of the SWI model were 1.00 and 0.98, respectively. The combined nomogram model incorporating SWI Rad-scores and independent predictors of clinical characteristics was not able to distinguish HIE in patients without MRI abnormalities from the control group (AUC, 1.00). A high degree of fitting and favorable clinical utility was detected using the calibration curve with the Hosmer-Lemeshow test. Decision curve analysis was used for the SWI, clinical and combined nomogram models. The decision curve showed that the SWI and combined nomogram models had better predictive performance than the clinical model.

CONCLUSIONS

HIE can be detected in patients without MRI abnormalities using an MRI-based radiomics model. The SWI model performed better than the other models.

Assessment of brain cancer atlas maps with multimodal imaging features

BACKGROUND

Glioblastoma Multiforme (GBM) is a fast-growing and highly aggressive brain tumor that invades the nearby brain tissue and presents secondary nodular lesions across the whole brain but generally does not spread to distant organs. Without treatment, GBM can result in death in about 6 months. The challenges are known to depend on multiple factors: brain localization, resistance to conventional therapy, disrupted tumor blood supply inhibiting effective drug delivery, complications from peritumoral edema, intracranial hypertension, seizures, and neurotoxicity.

MAIN TEXT

Imaging techniques are routinely used to obtain accurate detections of lesions that localize brain tumors. Especially magnetic resonance imaging (MRI) delivers multimodal images both before and after the administration of contrast, which results in displaying enhancement and describing physiological features as hemodynamic processes. This review considers one possible extension of the use of radiomics in GBM studies, one that recalibrates the analysis of targeted segmentations to the whole organ scale. After identifying critical areas of research, the focus is on illustrating the potential utility of an integrated approach with multimodal imaging, radiomic data processing and brain atlases as the main components. The templates associated with the outcome of straightforward analyses represent promising inference tools able to spatio-temporally inform on the GBM evolution while being generalizable also to other cancers.

CONCLUSIONS

The focus on novel inference strategies applicable to complex cancer systems and based on building radiomic models from multimodal imaging data can be well supported by machine learning and other computational tools potentially able to translate suitably processed information into more accurate patient stratifications and evaluations of treatment efficacy.

A bibliometric and visualized analysis of preoperative future liver remnant augmentation techniques from 1997 to 2022

Background

The size and function of the future liver remnant (FLR) is an essential consideration for both eligibility for treatment and postoperative prognosis when planning surgical hepatectomy. Over time, a variety of preoperative FLR augmentation techniques have been investigated, from the earliest portal vein embolization (PVE) to the more recent Associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) and liver venous deprivation (LVD) procedures. Despite numerous publications on this topic, no bibliometric analysis has yet been conducted.

Methods

Web of Science Core Collection (WoSCC) database was searched to identify studies related to preoperative FLR augmentation techniques published from 1997 to 2022. The analysis was performed using the CiteSpace [version 6.1.R6 (64-bit)] and VOSviewer [version 1.6.19].

Results

A total of 973 academic studies were published by 4431 authors from 920 institutions in 51 countries/regions. The University of Zurich was the most published institution while Japan was the most productive country. Eduardo de Santibanes had the most published articles, and Masato Nagino was the most frequently co-cited author. The most frequently published journal was HPB, and the most cited journal was Ann Surg, with 8088 citations. The main aspects of preoperative FLR augmentation technique is to enhance surgical technology, expand clinical indications, prevent and treat postoperative complications, ensure long-term survival, and evaluate the growth rate of FLR. Recently, hot keywords in this field include ALPPS, LVD, and Hepatobiliary Scintigraphy.

Conclusion

This bibliometric analysis provides a comprehensive overview of preoperative FLR augmentation techniques, offering valuable insights and ideas for scholars in this field.

A bibliometric analysis of the application of imaging in sleep in neurodegenerative disease

Objective

The purpose of this study was to examine the current state of the application of imaging in sleep research in degenerative disease, as well as hotspots and trends.

Materials and methods

A search was conducted on the Web of Science Core Collection (WoSCC) between 1 September 2012, and 31 August 2022 for literature related to sleep imaging. This study analyzed 7,679 articles published in this field over the past 10 years, using CiteSpace to analyze tendencies, countries, institutions, authors, and hotspots.

Results

There were 7,679 articles on the application of imaging to sleep research published by 566 institutions located in 135 countries in 1,428 journals; the number of articles was increasing on a yearly basis. According to keyword analysis, the research direction of the application of imaging in sleep research focused on the effects of degenerative diseases on sleep, such as Parkinson's disease, Alzheimer's disease, and small vessel disease. A literature evaluation found that Parkinson's disease, insomnia, sleep quality, and rapid eye movement sleep behavior disorder were the top research trends in this field.

Conclusion

A growing body of research has focused on sleep disorders caused by degenerative diseases. In the application of imaging to sleep research, magnetic resonance functional brain imaging represents a reliable research method. In the future, more aging-related diseases may be the subject of sleep-related research, and imaging could provide convenient and reliable evidence in this respect.

The interplay between the nerves and skeleton: a 30-year bibliometric analysis

Background

The mechanisms and effects of the interplay between the nerves and skeleton remain a popular research topic. This study aimed to analyze and evaluate publications on nerve-bone interactions using bibliometrics and to identify the state of the art of current research, hotspots, and future directions.

Methods

This study included 1989 articles and reviews from the Web of Science Core Collection (WoSCC) published from January 1, 1991, to June 22, 2022. The Bibliometrix package of R 4.2.0 (The R Foundation for Statistical Computing, Vienna, Austria) was used to analyze basic information about the publications, including the annual number of publications, institution analysis, author influence analysis, journal analysis, and the national cooperation network. We also used CiteSpace 5.8.R3 for bibliometric analysis, including co-occurrence, co-citation, and cluster analysis.

Results

We discovered a significant increase in the number of articles on nerve-bone interactions published over the last 10 years. The most active country and institution were the United States and the University of Minnesota, respectively. In terms of journals and cocited journals, Bone was ranked highest with respect to the number of publications, while Journal of Bone and Mineral Research was ranked highest among cited journals. Wang Lei was the author with the most publications, and Bjurholm A was the most cited author. The analysis of references and keywords revealed that the impact of nerve- and neuromodulation-related factors on stem cell differentiation was a persistently hot topic. Osteoarthritis, neuropeptide Y, and osteoclastogenic process are likely to be the next era of research hotspots. The neurovascular crosstalk within bone has received great attention, especially in skeletal diseases, which may provide potential targets for future treatments.

Conclusions

We used a bibliometric method to provide an efficient, objective, and comprehensive assessment of existing research about the interplay between the skeletal and nervous systems and to accurately identify hotspots and research frontiers, providing valuable information for future research.

Research topics and hotspot trends of lumbar spondylolisthesis: A text-mining study with machine learning

Objectives

The study aimed to conduct a bibliometric analysis of publications concerning lumbar spondylolisthesis, as well as summarize its research topics and hotspot trends with machine-learning based text mining.

Methods

The data were extracted from the Web of Science Core Collection (WoSCC) database and then analyzed in Rstudio1.3.1 and CiteSpace5.8. Annual publication production and the top-20 productive authors over time were obtained. Additionally, top-20 productive journals and top-20 influential journals were compared by spine-subspecialty or not. Similarly, top-20 productive countries/regions and top-20 influential countries/regions were compared by they were developed countries/regions or not. The collaborative relationship among countries and institutions were presented. The main topics of lumbar spondylolisthesis were classified by Latent Dirichlet allocation (LDA) analysis, and the hotspot trends were indicated by keywords with strongest citation bursts.

Results

Up to 2021, a total number of 4,245 articles concerning lumbar spondylolisthesis were finally included for bibliometric analysis. Spine-subspecialty journals were found to be dominant in the productivity and the impact of the field, and SPINE, EUROPEAN SPINE JOURNAL and JOURNAL OF NEUROSURGERY-SPINE were the top-3 productive and the top-3 influential journals in this field. USA, Japan and China have contributed to over half of the publication productivity, but European countries seemed to publish more influential articles. It seemed that developed countries/regions tended to produce more articles and more influential articles, and international collaborations mainly occurred among USA, Europe and eastern Asia. Publications concerning surgical management was the major topic, followed by radiographic assessment and epidemiology for this field. Surgical management especially minimally invasive technique for lumbar spondylolisthesis were the recent hotspots over the past 5 years.

Conclusions

The study successfully summarized the productivity and impact of different entities, which should benefit the journal selection and pursuit of international collaboration for researcher who were interested in the field of lumbar spondylolisthesis. Additionally, the current study may encourage more researchers joining in the field and somewhat inform their research direction in the future.

Hepatic arterial infusion chemotherapy in hepatocellular carcinoma: A bibliometric and knowledge-map analysis

Background

In recent years, hepatic arterial infusion chemotherapy (HAIC) has gained popularity in the treatment of hepatocellular carcinoma. Although several studies have been published, no bibliometric analysis have been conducted on this topic.

Objectives

To understand the development status and future trends in the application of HAIC, we conducted bibliometric analysis to examine the cooperation and influence among countries, institutions, authors, and journals.

Methods

All relevant articles and reviews on the use of HAIC in HCC treatment were retrieved from the Web of Science database. A bibliometric analysis of countries, institutions, journals, authors, and keywords related to this field was performed using R and VOSviewer software. The main aspects analyzed were the research status and key fields of HAIC in HCC treatment.

Results

A total of 1026 articles published in 292 journals by 4937 authors from 959 institutions between 1974 and 2021 were retrieved. A rapid increase in articles published after 1990 was observed, which reached the peak in 2021. Japan had the most publications and citations. Yonsei University, Sun Yat-sen University, and Hiroshima University were the three leading institutions in research on this topic. Kwang-Hyub Han and Masatoshi Kudo have the greatest academic influence in this field. Most publications were made in the Hepato-Gastroenterology, whereas cancer had the most citations. The main aspects of HAIC treatment of HCC include HAIC and TACE, chemotherapy drug selection, HAIC and targeted therapy and immunotherapy, HAIC and surgery, and hepatotoxicity. Keywords such as FOLFOX, lenvatinib, hepatic arterial infusion chemotherapy are hot words in this field in recent years.

Conclusion

The research on the use of HAIC in the treatment of HCC has been on the rise. Currently, HAIC combined with targeted therapy or immunotherapy has attracted significant attention.

A bibliometric and visualization analysis of global research on vestibular schwannoma

BACKGROUND

Vestibular schwannoma is the most common benign tumor in the pontocerebellar horn region. As the tumor grows, it often causes severe hearing loss due to compression of nearby nerves, resulting in a lower quality of life. This study examined vestibular schwannoma-related research through a bibliometric and visualization analysis, and it explored current trends and research hot spots.

METHODS

Research related to vestibular schwannoma published from 2002 to 2021 was searched using the Web of Science Core Collection. The processing and visualization analysis of the data were conducted using R software, VOSviewer, and CiteSpace.

RESULTS

A total of 3,909 publications were included in this study, and an overall increasing trend in the annual output of publications was found. The United States, Germany, and the United Kingdom were the most prolific countries, publishing the most articles. Germany had the most frequent international cooperation and the highest centrality score. The Mayo Clinic, University of California, and Harvard University were the three most productive institutions. Otology & Neurotology was the most prolific journal, and MJ Link was the most productive and highest scoring author for centrality. Current frontier topics mainly focused on "hearing preservation" and "radiosurgery". A map of trends in topics and a thematic graph revealed that "hearing loss", "vertigo", "magnetic resonance imaging", "radiosurgery", "stereotactic radiosurgery", and "gamma knife" were the topics of focus of current discussions.

CONCLUSION

Hearing preservation is a current frontier topic in this area. Radiosurgery has a promising future in the field of vestibular schwannoma, and stereotactic radiosurgery is a focus of global attention. Bibliometric and visualization analysis offer a unique and objective perspective of the field of vestibular schwannoma and may assist scholars in the identification of new research directions.

Role of Machine Learning in Precision Oncology: Applications in Gastrointestinal Cancers

Gastrointestinal (GI) cancers, consisting of a wide spectrum of pathologies, have become a prominent health issue globally. Despite medical imaging playing a crucial role in the clinical workflow of cancers, standard evaluation of different imaging modalities may provide limited information. Accurate tumor detection, characterization, and monitoring remain a challenge. Progress in quantitative imaging analysis techniques resulted in "radiomics", a promising methodical tool that helps to personalize diagnosis and treatment optimization. Radiomics, a sub-field of computer vision analysis, is a bourgeoning area of interest, especially in this era of precision medicine. In the field of oncology, radiomics has been described as a tool to aid in the diagnosis, classification, and categorization of malignancies and to predict outcomes using various endpoints. In addition, machine learning is a technique for analyzing and predicting by learning from sample data, finding patterns in it, and applying it to new data. Machine learning has been increasingly applied in this field, where it is being studied in image diagnosis. This review assesses the current landscape of radiomics and methodological processes in GI cancers (including gastric, colorectal, liver, pancreatic, neuroendocrine, GI stromal, and rectal cancers). We explain in a stepwise fashion the process from data acquisition and curation to segmentation and feature extraction. Furthermore, the applications of radiomics for diagnosis, staging, assessment of tumor prognosis and treatment response according to different GI cancer types are explored. Finally, we discussed the existing challenges and limitations of radiomics in abdominal cancers and investigate future opportunities.

Research trends and hotspots on connectomes from 2005 to 2021: A bibliometric and latent Dirichlet allocation application study

Background

This study aimed to conduct a bibliometric analysis of publications on connectomes and illustrate its trends and hotspots using a machine-learning-based text mining algorithm.

Methods

Documents were retrieved from the Web of Science Core Collection (WoSCC) and Scopus databases and analyzed in Rstudio 1.3.1. Through quantitative and qualitative methods, the most productive and impactful academic journals in the field of connectomes were compared in terms of the total number of publications and h-index over time. Meanwhile, the countries/regions and institutions involved in connectome research were compared, as well as their scientific collaboration. The study analyzed topics and research trends by R package "bibliometrix." The major topics of connectomes were classified by Latent Dirichlet allocation (LDA).

Results

A total of 14,140 publications were included in the study. NEUROIMAGE ranked first in terms of publication volume (1,427 articles) and impact factor (h-index:122) among all the relevant journals. The majority of articles were published by developed countries, with the United States having the most. Harvard Medical School and the University of Pennsylvania were the two most productive institutions. Neuroimaging analysis technology and brain functions and diseases were the two major topics of connectome research. The application of machine learning, deep learning, and graph theory analysis in connectome research has become the current trend, while an increasing number of studies were concentrating on dynamic functional connectivity. Meanwhile, researchers have begun investigating alcohol use disorders and migraine in terms of brain connectivity in the past 2 years.

Conclusion

This study illustrates a comprehensive overview of connectome research and provides researchers with critical information for understanding the recent trends and hotspots of connectomes.

Mapping the current trends and hotspots of vascular cognitive impairment from 2000-2021: A bibliometric analysis

AIMS

To visualize the trends and hotspots in the scientific research related to vascular cognitive impairment (VCI) quantitatively and qualitatively.

METHODS

Cross-sectional bibliometric analysis of publications that related to VCI was conducted. Publications were found by searching in the Web of Science Core Collection database (WoSCC) - Edition: Science Citation Index Expanded (SCI-Expanded) from January 2000 to December 2021. Publication type was restricted to article and review in the English language. The downloaded data were screened and analyzed in January 2022.

RESULTS

In total, 16,264 publications were identified, with a steady increase in annual publications. The United States was the leading country in VCI research regarding publication numbers and national influence. National Institute of Aging had the highest influence among all the institutes in the field of VCI. Philip Scheltens was the most active author. The top five active authors' publications focused on pathobiology, neuroimaging standards, risk factors, prevention, and the standard diagnosis of vascular dementia (VaD). A co-cited publication clustering resulted in 19 main clusters, and the prevention, blood-brain barrier, cholesterol, cerebral amyloid angiopathy, and VaD were the top 5 clusters. Moreover, burst keywords detection revealed that the "small vessel disease" is the current hotspot in the field of VCI.

CONCLUSIONS

This bibliometric analysis mapped the overall research structure of VCI and analyzed the current research trends and hotspots for future studies orientation. Neuroimaging, risk factors detection, and pathobiology are the current trends in VCI research. Small vessel disease and its mechanisms are the current hotspots of VCI research.

One hundred most cited articles related to Endoscopic retrograde cholangiopancreatography: A bibliometric analysis

Background

Endoscopic retrograde cholangiopancreatography (ERCP) has developed over the past few decades into a reliable technology for diagnostic and therapeutic purposes. Through a bibliometric analysis, this research attempted to evaluate the characteristics of the top 100 articles on ERCP that had the most citations.

Methods

We extracted pertinent publications from the Web of Science Core Collection (WoSCC) on July 9, 2022. The top 100 ERCP articles with the most citations were identified and analyzed. The following data were extracted: publication year, country/region, organization, total citation times, annual citation times, research type and research field, etc. To implement the network’s visual analysis, a bibliographic coupling network based on keywords was built using the VOSviewer 1.6.17 program.

Results

The journal with the most publications were GASTROINTESTINAL ENDOSCOPY, with 45 articles. Most of the top 100 articles came from the United States (n = 47) and Italy (n = 14). Indiana University and the University of Amsterdam were among the most important institutions in ERCP research. ML Freeman of the University of Minnesota contributed the highest number (n = 9) and the most highly cited paper. The age of the paper and article type is closely related to citation frequency. Of the 100 most-cited articles, clinical application in the field of ERCP has focused on three aspects: diagnosis, treatment, and complications. Clinical use of ERCP has shifted from diagnosis to treatment. Post-ERCP pancreatitis is the focus of attention, and the clinical application of technically complex therapeutic ERCP is the future development trend.

Conclusion

This study lists the most influential articles in ERCP by exposing the current state of the field, and showing the evolution of research trends to provide perspective for the future development of ERCP.

Frontiers and hotspots of 18F-FDG PET/CT radiomics: A bibliometric analysis of the published literature

Objective

To illustrate the knowledge hotspots and cutting-edge research trends of ¹⁸F-FDG PET/CT radiomics, the knowledge structure of was systematically explored and the visualization map was analyzed.

Methods

Studies related to ¹⁸F-FDG PET/CT radiomics from 2013 to 2021 were identified and selected from the Web of Science Core Collection (WoSCC) using retrieval formula based on an interview. Bibliometric methods are mainly performed by CiteSpace 5.8.R3, which we use to build knowledge structures including publications, collaborative and co-cited studies, burst analysis, and so on. The performance and relevance of countries, institutions, authors, and journals were measured by knowledge maps. The research foci were analyzed through research of keywords, as well as literature co-citation analysis. Predicting trends of ¹⁸F-FDG PET/CT radiomics in this field utilizes a citation burst detection method.

Results

Through a systematic literature search, 457 articles, which were mainly published in the United States (120 articles) and China (83 articles), were finally included in this study for analysis. Memorial Sloan-Kettering Cancer Center and Southern Medical University are the most productive institutions, both with a frequency of 17. ¹⁸F-FDG PET/CT radiomics–related literature was frequently published with high citation in European Journal of Nuclear Medicine and Molecular Imaging (IF9.236, 2020), Frontiers in Oncology (IF6.244, 2020), and Cancers (IF6.639, 2020). Further cluster profile of keywords and literature revealed that the research hotspots were primarily concentrated in the fields of image, textural feature, and positron emission tomography, and the hot research disease is a malignant tumor. Document co-citation analysis suggested that many scholars have a co-citation relationship in studies related to imaging biomarkers, texture analysis, and immunotherapy simultaneously. Burst detection suggests that adenocarcinoma studies are frontiers in ¹⁸F-FDG PET/CT radiomics, and the landmark literature put emphasis on the reproducibility of ¹⁸F-FDG PET/CT radiomics features.

Conclusion

First, this bibliometric study provides a new perspective on ¹⁸F-FDG PET/CT radiomics research, especially for clinicians and researchers providing scientific quantitative analysis to measure the performance and correlation of countries, institutions, authors, and journals. Above all, there will be a continuing growth in the number of publications and citations in the field of ¹⁸F-FDG PET/CT. Second, the international research frontiers lie in applying ¹⁸F-FDG PET/CT radiomics to oncology research. Furthermore, new insights for researchers in future studies will be adenocarcinoma-related analyses. Moreover, our findings also offer suggestions for scholars to give attention to maintaining the reproducibility of ¹⁸F-FDG PET/CT radiomics features.

Diagnostic performance of radiomics in adrenal masses: A systematic review and meta-analysis

Objectives

(1) To assess the methodological quality and risk of bias of radiomics studies investigating the diagnostic performance in adrenal masses and (2) to determine the potential diagnostic value of radiomics in adrenal tumors by quantitative analysis.

Methods

PubMed, Embase, Web of Science, and Cochrane Library databases were searched for eligible literature. Methodological quality and risk of bias in the included studies were assessed by the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) and Radiomics Quality Score (RQS). The diagnostic performance was evaluated by pooled sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC). Spearman’s correlation coefficient and subgroup analysis were used to investigate the cause of heterogeneity. Publication bias was examined using the Deeks’ funnel plot.

Results

Twenty-eight studies investigating the diagnostic performance of radiomics in adrenal tumors were identified, with a total of 3579 samples. The average RQS was 5.11 (14.2% of total) with an acceptable inter-rater agreement (ICC 0.94, 95% CI 0.93–0.95). The risk of bias was moderate according to the result of QUADAS-2. Nine studies investigating the use of CT-based radiomics in differentiating malignant from benign adrenal tumors were included in the quantitative analysis. The pooled sensitivity, specificity, DOR and AUC with 95% confidence intervals were 0.80 (0.68-0.88), 0.83 (0.73-0.90), 19.06 (7.87-46.19) and 0.88 (0.85–0.91), respectively. There was significant heterogeneity among the included studies but no threshold effect in the meta-analysis. The result of subgroup analysis demonstrated that radiomics based on unenhanced and contrast-enhanced CT possessed higher diagnostic performance, and second-order or higher-order features could enhance the diagnostic sensitivity but also increase the false positive rate. No significant difference in diagnostic ability was observed between studies with machine learning and those without.

Conclusions

The methodological quality and risk of bias of studies investigating the diagnostic performance of radiomics in adrenal tumors should be further improved in the future. CT-based radiomics has the potential benefits in differentiating malignant from benign adrenal tumors. The heterogeneity between the included studies was a major limitation to obtaining more accurate conclusions.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/ CRD 42022331999 .

Evolutions in the management of non-small cell lung cancer: A bibliometric study from the 100 most impactful articles in the field

Objective

The study was designed to explore the evolution of non-small cell lung cancer (NSCLC) management in the last 20 years.

Methods

The top 100 most-cited papers on NSCLC treatment were retrieved from the Web of Science Core Collection database. R and VOSviewer were used to extract bibliographic information, including the year of publication, countries/regions, institutions, authors, journals, keywords, impact factor, and total citations. The topic and type of papers were checked independently by authors. Bibliometric analysis was conducted and visualized with R, CiteSpace, Excel and VOSviewer to identify output dynamics, research forces, topics, hotspots, and frontiers in the field.

Results

The average citation of each retrieved top 100 most-cited NSCLC management papers was 1,725 (range: 615-7,340). Fifty-seven corresponding authors were from the United States. This country contributed the most papers (n=76), followed by Germany (n=34), France (n=33), and South Korea (n=32). The top contributors were Paz-Ares L. (n=12) and Reck M. (n=12). The Memorial Sloan Kettering Cancer Center published the largest number of papers (n=20). There were two significant citation paths, indicating publications in medicine/medical/clinical journals primarily cited journals in molecular/biology/genetics fields, partly cited health/nursing/medicine fields. Top-cited papers mainly came from the New England Journal of Medicine (n=33, citations=80,427), followed closely by the Journal of Clinical Oncology (n=28, citations=32,408). “Chemotherapy” (n=36) was the keyword with the greatest frequency of co-occurrence. “Open-label” was the keyword with the strongest burst strength (=4.01), followed by “nivolumab” (=3.85), “blockade” (=2.86), and “efficacy” (=2.85).

Conclusions

The United States as a nation and the Memorial Sloan Kettering Cancer Center as an institute contributed the most to this field. The New England Journal of Medicine is the most eye-catching journal. Hotspots of NSCLC management have almost undergone an evolution from chemotherapy and radiotherapy to targeted therapy to immunotherapy. Molecular/biological/genetic fields become the main research base for NSCLC treatment. Immunotherapy and combination therapy are research frontiers.

Epilepsy With Suicide: A Bibliometrics Study and Visualization Analysis via CiteSpace

Objective:

The purpose of this study was to analyze the research status of epilepsy with suicide and to determine the hotspots and frontiers via CiteSpace.

Method:

We searched the Web of Science Core Collection (WoSCC) for studies related to epilepsy and suicide from inception to September 30, 2021. We used CiteSpace to generate online maps of collaboration between countries, institutions, and authors, and revealed hot spots and frontiers in epilepsy with suicide.

Results:

A total of 631 publications related to epilepsy with suicide were retrieved from the WoSCC. Andres M. Kanner was the most published author (25 papers). The USA and Columbia University were the leading country and institution in this field, with 275 and 25 papers, respectively. There were active cooperation between institutions, countries, and authors. Hot topics focused on depression, antiseizure medications, pediatric epilepsy, and risk factors of suicide in patients with epilepsy (PWEs).

Conclusions:

Based on the CiteSpace findings, this study detected active collaboration among countries, institutions and authors. The main current research trends include suicide caused by depression, suicide caused by the use of antiseizure medications, suicide in children with epilepsy, and risk factors for suicide in PWEs. Thus, more attention should be paid to the psychiatric comorbidity of PWEs (especially pediatric epilepsy), the suicidal tendency of PWEs, and the rational use of antiseizure medications in the future.