Advanced Endoscopic Ultrasound (EUS) Techniques: Current and Future Directions

Topic Information

Dear Colleagues,

In recent years, we have made significant progress in the field of interventional endoscopy, specifically in therapeutic endoscopic ultrasound (EUS), which drastically extended th therapeutic armamentarium in several gastrointestinal diseases and finally contributed the improvement of patients’ treatment and outcome. Among the therapeutic implications including EUS-guided drainage using lumen apposing metal stents (LAMSs), EUS has been increasingly used for creating gastrointestinal anastomosis, including gastro-jejunostomy and EUS-directed trans-gastric intervention (EDGI), and used in antegrade procedures such as hepatico-gastrostomy and antegrade maneuvers to reach the biliary tree in altered anatomy and inaccessible retrograde biliary approaches. Additionally, some advancements in diagnostic techniques have been made regarding ultrasensitive Doppler, shear wave elastography and 3D EUS as well as molecular analyses of EUS-FNA/FNB specimen in pancreaticobiliary tumors.

Given the rapidly evolving shift in EUS, as part of the following Topic, entitled “Advanced Endoscopic Ultrasound (EUS) Techniques: Current and Future Directions”, we aim to publish outstanding manuscripts focused on advanced EUS techniques. Priority will be given to high-quality original articles, but well-designed, systematic reviews (with or without meta-analysis) and narrative reviews addressing the latest updated insights on a specific topic will be welcomed.

Dr. Bertrand V. Napoleón
Dr. Andrea Lisotti
Dr. Tawfik Khoury
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Cancers cancers	4.8	9.0	2009	17.5 Days	CHF 2900	Submit
Current Oncology curroncol	3.6	6.1	1994	22.6 Days	CHF 2200	Submit
Diagnostics diagnostics	3.8	6.9	2011	20.4 Days	CHF 2600	Submit
Gastroenterology Insights gastroent	1.6	2.1	2009	19.5 Days	CHF 1800	Submit

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Published Papers (2 papers)

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All Cancers Current Oncology Diagnostics Gastroenterology Insights

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14 pages, 292 KB  

Open AccessReview

Endoscopic Ultrasound-Guided Gallbladder Drainage in the Treatment of Acute Cholecystitis and Malignant Biliary Obstruction: A Literature Review

by Xinyue Zhao and Nan Ge

Gastroenterol. Insights 2026, 17(2), 36; https://doi.org/10.3390/gastroent17020036 - 6 Jun 2026

Viewed by 478

Abstract

Endoscopic ultrasound-guided gallbladder drainage (EUS-GBD) is an emerging intervention that provides a minimally invasive approach to drainage of the gallbladder, showing promising results in treating acute cholecystitis (AC) and malignant biliary obstruction (MBO). This review summarizes the current applications of EUS-GBD and compares [...] Read more.

Endoscopic ultrasound-guided gallbladder drainage (EUS-GBD) is an emerging intervention that provides a minimally invasive approach to drainage of the gallbladder, showing promising results in treating acute cholecystitis (AC) and malignant biliary obstruction (MBO). This review summarizes the current applications of EUS-GBD and compares its clinical effectiveness with traditional methods such as percutaneous transhepatic gallbladder drainage (PT-GBD) and endoscopic transpapillary gallbladder drainage (ET-GBD). Available evidence suggests that EUS-GBD may offer potential advantages in terms of success rates and complication profiles, particularly in patients who are not candidates for surgery or those at high surgical risk. The method is effective in reducing inflammation, alleviating symptoms from obstruction, and improving patient quality of life. This article also discusses the technical evolution of EUS-GBD, its indications, complications, and its comparative advantages over other drainage techniques. These observations suggest that EUS-GBD may represent a valuable addition to the therapeutic armamentarium for selected high-risk patients. Full article

(This article belongs to the Topic Advanced Endoscopic Ultrasound (EUS) Techniques: Current and Future Directions)

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20 pages, 415 KB  

Open AccessReview

Applications of Artificial Intelligence in Endobronchial Ultrasound for Lung Cancer Diagnosis and Staging: A Scoping Review

by Jacobo Echeverri-Hoyos, Jaime A. Echeverri-Franco, Nicole Bonilla, Gustavo Monsalve-Morales and Eduardo Tuta-Quintero

Curr. Oncol. 2026, 33(5), 287; https://doi.org/10.3390/curroncol33050287 - 13 May 2026

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Abstract

Introduction: Lung cancer remains highly lethal. Endobronchial ultrasound (EBUS) enables minimally invasive diagnosis and staging. Artificial intelligence (AI) improves image analysis and diagnostic accuracy, though current evidence is limited by retrospective, small, single center studies. Methods: A scoping review following Arksey–O’Malley, [...] Read more.

Introduction: Lung cancer remains highly lethal. Endobronchial ultrasound (EBUS) enables minimally invasive diagnosis and staging. Artificial intelligence (AI) improves image analysis and diagnostic accuracy, though current evidence is limited by retrospective, small, single center studies. Methods: A scoping review following Arksey–O’Malley, Levac, and JBI frameworks, was reported as per PRISMA-ScR. Databases were searched for studies (2015–2026) on AI in EBUS. Two reviewers screened, extracted standardized data, and performed narrative synthesis grouped by algorithm type, application, and performance metrics. Results: A total of 26 studies were included. Of these, 73.1% (19/26) employed deep learning-based models, while 26.9% (7/26) used traditional or hybrid machine learning approaches. The most frequent clinical objective was diagnostic classification of malignancy (14/26; 53.8%), followed by segmentation or cytological analysis (5/26; 19.2%), anatomical navigation or lymph node station classification (3/26; 11.5%), and multimodal predictive or staging support models (4/26; 15.4%). Most studies were based on EBUS-derived images or videos (18/26; 69.2%), including both convex-probe and radial-probe applications. Studies were distributed among Convex Probe-EBUS for mediastinal staging, Radial Probe-EBUS for peripheral lesion assessment, and rapid on-site evaluation-based cytology analysis, reflecting diverse clinical contexts. Most models were developed using static images. Conclusions: AI applications in EBUS are predominantly based on deep learning and mainly focused on diagnostic classification, with growing but still limited exploration of segmentation, navigation, and multimodal approaches. The evidence reflects diverse clinical contexts and data sources, particularly image-based inputs, but remains unevenly distributed across applications. Full article

(This article belongs to the Topic Advanced Endoscopic Ultrasound (EUS) Techniques: Current and Future Directions)

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