EUS mapping · Lymph-node assessment
Find the node. Clarify the risk.
AI-assisted detection and characterization of lymph nodes, differentiating benign from malignant findings during live and previously acquired endoscopic ultrasound examinations.
01 · Intended use
AI assistance for lymph‑node assessment.
Smart Node® is a deep-learning technology developed to detect and characterize lymph nodes during endoscopic ultrasound.
It differentiates benign from malignant findings in live and previously acquired EUS images, supports precision biopsy targeting and generates standardized AI-driven reports.
The clinical challenge
Visual criteria alone may not reliably predict malignancy.
Lymph-node shape, borders and echogenicity can overlap between benign and malignant findings. Inconclusive assessment may delay staging decisions or lead to additional procedures.
“The critical step is identifying the right node and the right biopsy target.”
How it works
One continuous path from ultrasound to targeted sampling.
Smart Node® supports the EUS workflow while keeping sampling strategy and final interpretation in expert hands.
EUS acquisition
Live or previously acquired endoscopic ultrasound images enter the analysis workflow.
Lymph-node detection
The AI detects and tracks lymph nodes across the EUS examination.
Node characterization
Shape, margins and internal echo patterns are assessed within each detected node.
Malignancy prediction
The finding is differentiated as benign or malignant for clinician review.
Targeted biopsy
Bounding-box guidance and a standardized report support precision tissue sampling.
AI capabilities
Designed for focused lymph‑node assessment.
Diagnostic accuracy presented for Smart Node®
Lymph-node detection
Automatically detects and localizes lymph nodes in endoscopic ultrasound images.
Benign–malignant characterization
Analyzes EUS features to support malignancy prediction for detected lymph nodes.
Real-time and retrospective analysis
Works during live EUS and with previously acquired examinations.
Sampling-target guidance
Places bounding boxes around relevant tissue to support precise sampling.
Standardized AI reporting
Generates a structured AI-driven diagnostic report for expert validation.
Scientific validation
Multicenter validation across nine clinical centers.
Artificial Intelligence for Lymph Node Detection and Malignancy Prediction in Endoscopic Ultrasound: A Multicenter Study
Cancers · 2025 · 59,992 images from 82 EUS procedures
Read publication ↗Clinical benefits
Earlier clarity. Better‑targeted sampling.
Earlier and more accurate lymph-node diagnosis
↗Fewer unnecessary procedures through more focused decision-making
↗Target selection for sampling with bounding-box guidance
↗Real-time and post-procedural EUS analysis in one workflow
↗Standardized AI-driven diagnostic reporting
↗Smart Node®
Find the node. Target with precision.
Talk to our team ↗This technology is part of DigestAID's research and development pipeline. Availability and regulatory status may vary by market.