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A Comprehensive Guide to Artificial Intelligence in Endoscopic Ultrasound

JOURNAL OF CLINICAL MEDICINE (2023)

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Article Oncology

Contrast-enhanced harmonic endoscopic ultrasound (CH-EUS) MASTER: A novel deep learning-based system in pancreatic mass diagnosis

Anliu Tang et al.

Summary: The study aimed to develop a deep learning-based artificial intelligence system, CH-EUS MASTER, for diagnosing pancreatic masses and guiding real-time EUS-FNA. The results showed that CH-EUS MASTER significantly improved the accuracy of diagnosing pancreatic masses and increased the first-pass diagnostic yield in EUS-FNA.

CANCER MEDICINE (2023)

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Article Radiology, Nuclear Medicine & Medical Imaging

Endoscopic ultrasound diagnosis system based on deep learning in images capture and segmentation training of solid pancreatic masses

Anliu Tang et al.

Summary: A deep learning-based CH-EUS diagnosis system was designed for real-time capture and segmentation of solid pancreatic masses, and its value in EUS training was verified. The model successfully captured and segmented the pancreatic solid mass region, and the average IoU of trainees improved significantly after training.

MEDICAL PHYSICS (2023)

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Review Biochemical Research Methods

Artificial intelligence in clinical research of cancers

Dan Shao et al.

Summary: The extensive application of Artificial Intelligence (AI) in the biomedical domain, particularly in cancer research, has achieved expert-level performance. However, only a few AI-based applications have been approved for real-world use. This article summarizes the progress of AI in cancer research over the past two decades and discusses the challenges and future prospects of AI in cancer treatment.

BRIEFINGS IN BIOINFORMATICS (2022)

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Article Oncology

Artificial intelligence-based diagnosis of upper gastrointestinal subepithelial lesions on endoscopic ultrasonography images

Keiko Hirai et al.

Summary: This study investigated the efficacy of an AI system for classifying subepithelial lesions (SELs) on EUS images, and found that the AI system had higher diagnostic performance than experts, especially in differentiating gastrointestinal stromal tumors (GISTs) from non-GISTs. This AI system may assist in improving the diagnosis of SELs in clinical practice.

GASTRIC CANCER (2022)

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Article Computer Science, Interdisciplinary Applications

Voice-Assisted Image Labeling for Endoscopic Ultrasound Classification Using Neural Networks

Ester Bonmati et al.

Summary: This research proposes a convolutional neural network model that labels ultrasound images using verbal comments from clinicians. The results show a prediction accuracy of 76% at the image level.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2022)

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Review Pathology

Digital pathology and artificial intelligence in translational medicine and clinical practice

Vipul Baxi et al.

Summary: Recent technological advancements have enabled the development of digital pathology and AI-based solutions for quantitative pathologic assessments, revolutionizing disease diagnosis and drug development. These innovations provide valuable opportunities in immuno-oncology for deciphering complex pathophysiology and discovering novel biomarkers, while also supporting practitioners in selecting the most appropriate treatment based on patient profiles. The integration of AI-powered analysis tools enhances the traditional role of pathologists in delivering accurate diagnoses and assessing biomarkers, with potential applications in translational medicine and clinical settings.

MODERN PATHOLOGY (2022)

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Article Biochemistry & Molecular Biology

Comparison of Semi-Quantitative Scoring and Artificial Intelligence Aided Digital Image Analysis of Chromogenic Immunohistochemistry

Janos Bencze et al.

Summary: This study tested a newly established artificial intelligence (AI)-aided digital image analysis platform, Pathronus, and compared it to conventional scoring. The results showed that Pathronus provides a more accurate alternative for protein quantification.

BIOMOLECULES (2022)

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Article Medicine, General & Internal

Diagnostic Value of Artificial Intelligence-Assisted Endoscopic Ultrasound for Pancreatic Cancer: A Systematic Review and Meta-Analysis

Elena Adriana Dumitrescu et al.

Summary: A meta-analysis of published data demonstrated the promising diagnostic accuracy of artificial intelligence for pancreatic cancer. Based on the analysis of 10 studies, it was found that artificial intelligence-assisted endoscopic ultrasound could become an important tool for the computer-aided diagnosis of pancreatic cancer.

DIAGNOSTICS (2022)

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Article Medicine, General & Internal

Development of a Novel Evaluation Method for Endoscopic Ultrasound-Guided Fine-Needle Biopsy in Pancreatic Diseases Using Artificial Intelligence

Takuya Ishikawa et al.

Summary: The study aimed to develop a new AI-based method for evaluating EUS-FNB specimens in pancreatic diseases, with contrastive learning showing improved diagnostic performance, comparable to expert evaluation in terms of specificity and accuracy.

DIAGNOSTICS (2022)

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Review Gastroenterology & Hepatology

Enhanced endoscopic ultrasound imaging for pancreatic lesions: The road to artificial intelligence

Marco Spadaccini et al.

Summary: Early detection of small asymptomatic solid pancreatic lesions is crucial for improving outcomes. Endoscopic ultrasound (EUS) is a mature imaging tool that has been enhanced with various adjuncts, such as contrast-enhanced harmonic EUS and EUS-elastography. These adjuncts have improved the specificity of diagnosis, while ongoing research on artificial intelligence shows promise in further enhancing EUS imaging.

WORLD JOURNAL OF GASTROENTEROLOGY (2022)

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Article Gastroenterology & Hepatology

Diagnostic accuracy of endoscopic ultrasound with artificial intelligence for gastrointestinal stromal tumors: A meta-analysis

Xiao Hua Ye et al.

Summary: This meta-analysis evaluated the diagnostic accuracy of AI-based EUS in distinguishing GISTs from other SELs. The results showed that AI-based EUS had high sensitivity and specificity, which could be beneficial for clinical diagnosis.

JOURNAL OF DIGESTIVE DISEASES (2022)

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Review Gastroenterology & Hepatology

Current status of artificial intelligence analysis for endoscopic ultrasonography

Takamichi Kuwahara et al.

Summary: Artificial intelligence (AI) and deep learning techniques are playing an increasingly important role in medical image diagnosis, especially in identifying pancreatic diseases. While deep learning has shown promising results in the medical field, more empirical evidence is needed to support its effectiveness in clinical applications.

DIGESTIVE ENDOSCOPY (2021)

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Article Gastroenterology & Hepatology

Application of artificial intelligence using a novel EUS-based convolutional neural network model to identify and distinguish benign and malignant hepatic masses

Neil B. Marya et al.

Summary: This study developed an EUS-based CNN model that autonomously identified and classified FLLs with high sensitivity and specificity, achieving a high accuracy rate in classifying malignant FLLs. The occlusion heatmap analysis demonstrated the model's success in autonomously locating FLLs in EUS video assets.

GASTROINTESTINAL ENDOSCOPY (2021)

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Article Gastroenterology & Hepatology

Utilisation of artificial intelligence for the development of an EUS-convolutional neural network model trained to enhance the diagnosis of autoimmune pancreatitis

Neil B. Marya et al.

Summary: The study developed an endoscopic ultrasound-based convolutional neural network model that can differentiate autoimmune pancreatitis from other pancreatic diseases in real time with high accuracy. The use of this model can help in early diagnosis and improve patient outcomes.

GUT (2021)

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Review Oncology

Deep learning in cancer pathology: a new generation of clinical biomarkers

Amelie Echle et al.

Summary: Clinical workflows in oncology rely on molecular biomarkers for prediction and prognosis. Deep learning technology can extract biomarkers directly from routine histology images, potentially enhancing clinical decision-making, but require rigorous external validation in clinical settings.

BRITISH JOURNAL OF CANCER (2021)

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Article Medicine, General & Internal

A deep learning-based system for bile duct annotation and station recognition in linear endoscopic ultrasound

Liwen Yao et al.

Summary: The study focused on developing a system for enhancing endoscopic ultrasound bile duct scanning using deep learning technology. Results showed that the model achieved high accuracy in classification and segmentation, significantly reducing difficulty in interpreting ultrasound images.

EBIOMEDICINE (2021)

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Article Gastroenterology & Hepatology

Curriculum for ERCP and endoscopic ultrasound training in Europe: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement

Gavin Johnson et al.

ENDOSCOPY (2021)

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Article Gastroenterology & Hepatology

ID: 3521955 APPLICATION OF ARTIFICIAL INTELLIGENCE FOR REAL-TIME ANATOMICAL RECOGNITION DURING ENDOSCOPIC ULTRASOUND EVALUATION: A PILOT STUDY

Carlos Robles-Medranda et al.

GASTROINTESTINAL ENDOSCOPY (2021)

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Article Gastroenterology & Hepatology

Convolutional neural network-based object detection model to identify gastrointestinal stromal tumors in endoscopic ultrasound images

Chang Kyo Oh et al.

Summary: The study aimed to develop a CNN-based object detection model for distinguishing gastric GIST and leiomyomas, trained and evaluated using EUS images. The EUS-CNN demonstrated excellent performance, outperforming human assessment in accuracy and sensitivity.

JOURNAL OF GASTROENTEROLOGY AND HEPATOLOGY (2021)

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Article Medicine, General & Internal

Automatic Segmentation of Pancreatic Tumors Using Deep Learning on a Video Image of Contrast-Enhanced Endoscopic Ultrasound

Yuhei Iwasa et al.

Summary: The study found that automatic segmentation of pancreatic tumors using U-Net on CE-EUS video images had a decent concordance rate. The clarity of tumor boundary lowered the concordance rate, but respiratory movement did not have a significant impact.

JOURNAL OF CLINICAL MEDICINE (2021)

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Article Multidisciplinary Sciences

Machine Learning and Network Analyses Reveal Disease Subtypes of Pancreatic Cancer and their Molecular Characteristics

Musalula Sinkala et al.

SCIENTIFIC REPORTS (2020)

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Article Gastroenterology & Hepatology

Deep learning-based pancreas segmentation and station recognition system in EUS: development and validation of a useful training tool (with video)

Jun Zhang et al.

GASTROINTESTINAL ENDOSCOPY (2020)

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Review Surgery

Endoscopic Ultrasound

Shelini Sooklal et al.

SURGICAL CLINICS OF NORTH AMERICA (2020)

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Review Gastroenterology & Hepatology

Evolving role of artificial intelligence in gastrointestinal endoscopy

Gulshan Parasher et al.

WORLD JOURNAL OF GASTROENTEROLOGY (2020)

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Review Gastroenterology & Hepatology

Virtual reality simulation training in endoscopy: a Cochrane review and meta-analysis

Rishad Khan et al.

ENDOSCOPY (2019)

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Article Gastroenterology & Hepatology

Deep Learning to Classify Intraductal Papillary Mucinous Neoplasms Using Magnetic Resonance Imaging

Juan E. Corral et al.

PANCREAS (2019)

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Article Multidisciplinary Sciences

Diagnostic ability of artificial intelligence using deep learning analysis of cyst fluid in differentiating malignant from benign pancreatic cystic lesions

Yusuke Kurita et al.

SCIENTIFIC REPORTS (2019)

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Article Oncology

Artificial intelligence in digital pathology - new tools for diagnosis and precision oncology

Kaustav Bera et al.

NATURE REVIEWS CLINICAL ONCOLOGY (2019)

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Article Computer Science, Artificial Intelligence

Pancreatic Cancer Prediction Through an Artificial Neural Network

Wazir Muhammad et al.

FRONTIERS IN ARTIFICIAL INTELLIGENCE (2019)

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Article Gastroenterology & Hepatology

EUS elastography (strain ratio) and fractal-based quantitative analysis for the diagnosis of solid pancreatic lesions

Silvia Carrara et al.

GASTROINTESTINAL ENDOSCOPY (2018)

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Article Gastroenterology & Hepatology

Mo1296 RELIMINARY RESULT OF COMPUTER AIDED DIAGNOSIS (CAD) PERFORMANCE USING DEEP LEARNING IN EUS-FNA CYTOLOGY OF PANCREATIC CANCER

Yusuke Hashimoto et al.

GASTROINTESTINAL ENDOSCOPY (2018)

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Review Veterinary Sciences

Fundamental Concepts for Semiquantitative Tissue Scoring in Translational Research

David K. Meyerholz et al.

ILAR JOURNAL (2018)

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Review Engineering, Biomedical

Artificial intelligence in healthcare

Kun-Hsing Yu et al.

NATURE BIOMEDICAL ENGINEERING (2018)

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Review Radiology, Nuclear Medicine & Medical Imaging

Convolutional neural networks: an overview and application in radiology

Rikiya Yamashita et al.

INSIGHTS INTO IMAGING (2018)

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Article Radiology, Nuclear Medicine & Medical Imaging

Machine Learning for Medical Imaging1

Bradley J. Erickson et al.

RADIOGRAPHICS (2017)

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Review Gastroenterology & Hepatology

Endoscopic ultrasound: Current roles and future directions

Scott R. Friedberg et al.

WORLD JOURNAL OF GASTROINTESTINAL ENDOSCOPY (2017)

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Article Gastroenterology & Hepatology

Quantitative contrast-enhanced harmonic EUS in differential diagnosis of focal pancreatic masses (with videos)

Adrian Saftoiu et al.

GASTROINTESTINAL ENDOSCOPY (2015)

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Review Multidisciplinary Sciences

Deep learning

Yann LeCun et al.

NATURE (2015)

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Article Gastroenterology & Hepatology

Differential diagnosis of pancreatic cancer from normal tissue with digital imaging processing and pattern recognition based on a support vector machine of EUS images

Min-Min Zhang et al.

GASTROINTESTINAL ENDOSCOPY (2010)

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