An automatic visual inspection method based on supervised machine learning for rapid on-site evaluation in EUS-FNA

Inoue, Hirofumi; Ogo, Kazuki; Tabuchi, Motohiro; Yamane, Nobumoto; Oka, Hiroyuki

doi:10.1109/sice.2014.6935253

Cited by 6 publications

(4 citation statements)

References 2 publications

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“…The histopathologic evaluation of samples obtained by EUS-guided FNA or FNB can be challenging, the use of an FNB needle can provide more tissue for satisfactory diagnosis and further ancillary testing (Figure 2A-D). Other promising onsite pathological evaluation methods under investigation include telecytopathology and artificial intelligence (AI) using an automated visual inspection system [159,160].…”

Section: Onsite Pathologic Evaluation Methodsmentioning

confidence: 99%

The Role of Endoscopic Ultrasonography in the Diagnosis and Staging of Pancreatic Cancer

Zakaria

Al-Share

Klapman

et al. 2022

Cancers

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Pancreatic cancer is the fourth leading cause of cancer-related death and the second gastrointestinal cancer-related death in the United States. Early detection and accurate diagnosis and staging of pancreatic cancer are paramount in guiding treatment plans, as surgical resection can provide the only potential cure for this disease. The overall prognosis of pancreatic cancer is poor even in patients with resectable disease. The 5-year survival after surgical resection is ~10% in node-positive disease compared to ~30% in node-negative disease. The advancement of imaging studies and the multidisciplinary approach involving radiologists, gastroenterologists, advanced endoscopists, medical, radiation, and surgical oncologists have a major impact on the management of pancreatic cancer. Endoscopic ultrasonography is essential in the diagnosis by obtaining tissue (FNA or FNB) and in the loco-regional staging of the disease. The advancement in EUS techniques has made this modality a critical adjunct in the management process of pancreatic cancer. In this review article, we provide an overall description of the role of endoscopic ultrasonography in the diagnosis and staging of pancreatic cancer.

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Section: Onsite Pathologic Evaluation Methodsmentioning

confidence: 99%

The Role of Endoscopic Ultrasonography in the Diagnosis and Staging of Pancreatic Cancer

Zakaria

Al-Share

Klapman

et al. 2022

Cancers

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“…AI-guided EUS-FNA has shown promising results in numerous studies. AI-enabled automatic visual inspection has proven to be helpful in rapid onsite tissue evaluation by indicating specific areas that are highly likely to indicate tumor cells in patients with pancreatic ductal adenocarcinoma with a sensitivity, specificity, and accuracy of about 80% [118,119]. Jiang et al showed that the accuracy of AI was 99.6% in differentiating low-versus high-grade neoplasia, and Nuon et al and Machicado demonstrated accuracies of 83% and 82% for AI models in differentiating mucinous cystic neoplasm versus serous cystadenocarcinoma and low versus high-grade dysplasia in intrapapillary mucinous neoplasm, respectively [120][121][122].…”

Section: Artificial-intelligence-augmented Endoscopic Ultrasoundmentioning

confidence: 99%

Basic Principles and Role of Endoscopic Ultrasound in Diagnosis and Differentiation of Pancreatic Cancer from Other Pancreatic Lesions: A Comprehensive Review of Endoscopic Ultrasound for Pancreatic Cancer

Dahiya,

Shah,

Ali

et al. 2024

JCM

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Pancreatic cancer is one of the leading causes of cancer-related deaths worldwide. Pancreatic lesions consist of both neoplastic and non-neoplastic lesions and often pose a diagnostic and therapeutic challenge due to similar clinical and radiological features. In recent years, pancreatic lesions have been discovered more frequently as incidental findings due to the increased utilization and widespread availability of abdominal cross-sectional imaging. Therefore, it becomes imperative to establish an early and appropriate diagnosis with meticulous differentiation in an attempt to balance unnecessary treatment of benign pancreatic lesions and missing the opportunity for early intervention in malignant lesions. Endoscopic ultrasound (EUS) has become an important diagnostic modality for the identification and risk stratification of pancreatic lesions due to its ability to provide detailed imaging and acquisition of tissue samples for analysis with the help of fine-needle aspiration/biopsy. The recent development of EUS-based technology, including contrast-enhanced endoscopic ultrasound, real-time elastography–endoscopic ultrasound, miniature probe ultrasound, confocal laser endomicroscopy, and the application of artificial intelligence has significantly augmented the diagnostic accuracy of EUS as it enables better evaluation of the number, location, dimension, wall thickness, and contents of these lesions. This article provides a comprehensive overview of the role of the different types of EUS available for the diagnosis and differentiation of pancreatic cancer from other pancreatic lesions while discussing their key strengths and important limitations.

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“…In a study by Inoue et al, an automatic visual inspection method based on supervised machine learning was proposed to assist rapid on-site evaluation (ROSE) for endoscopic ultrasound-guided fine needle aspiration (EUS-FNA) biopsy. The proposed method was effective in assisting on-site visual inspection of cellular tissue in ROSE for EUS-FNA, indicating highly probable areas including tumor cells [33].…”

Section: Integrating Ai In Eus-guided Tissue Acquisitionmentioning

confidence: 99%

A Comprehensive Guide to Artificial Intelligence in Endoscopic Ultrasound

Khalaf

Terrin

Jovani

et al. 2023

JCM

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Background: Endoscopic Ultrasound (EUS) is widely used for the diagnosis of bilio-pancreatic and gastrointestinal (GI) tract diseases, for the evaluation of subepithelial lesions, and for sampling of lymph nodes and solid masses located next to the GI tract. The role of Artificial Intelligence in healthcare in growing. This review aimed to provide an overview of the current state of AI in EUS from imaging to pathological diagnosis and training. Methods: AI algorithms can assist in lesion detection and characterization in EUS by analyzing EUS images and identifying suspicious areas that may require further clinical evaluation or biopsy sampling. Deep learning techniques, such as convolutional neural networks (CNNs), have shown great potential for tumor identification and subepithelial lesion (SEL) evaluation by extracting important features from EUS images and using them to classify or segment the images. Results: AI models with new features can increase the accuracy of diagnoses, provide faster diagnoses, identify subtle differences in disease presentation that may be missed by human eyes, and provide more information and insights into disease pathology. Conclusions: The integration of AI in EUS images and biopsies has the potential to improve the diagnostic accuracy, leading to better patient outcomes and to a reduction in repeated procedures in case of non-diagnostic biopsies.

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An automatic visual inspection method based on supervised machine learning for rapid on-site evaluation in EUS-FNA

Cited by 6 publications

References 2 publications

The Role of Endoscopic Ultrasonography in the Diagnosis and Staging of Pancreatic Cancer

The Role of Endoscopic Ultrasonography in the Diagnosis and Staging of Pancreatic Cancer

Basic Principles and Role of Endoscopic Ultrasound in Diagnosis and Differentiation of Pancreatic Cancer from Other Pancreatic Lesions: A Comprehensive Review of Endoscopic Ultrasound for Pancreatic Cancer

A Comprehensive Guide to Artificial Intelligence in Endoscopic Ultrasound

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