ScanNav Anatomy Peripheral Nerve Block
Overview
ScanNav Anatomy Peripheral Nerve Block is an AI-powered software medical device developed by Intelligent Ultrasound Limited. As of October 2024, the Clinical AI business, including this tool, was acquired by GE HealthCare and is now part of their ultrasound portfolio. The device is designed to assist qualified healthcare professionals, particularly anesthetists, in performing Ultrasound-Guided Regional Anesthesia (UGRA) procedures. It utilizes deep learning artificial intelligence (AI) to provide a real-time color overlay on live B-mode ultrasound images, highlighting relevant anatomical structures such as nerves, arteries, and bones. This technology aims to enhance the accuracy and standardization of ultrasound image interpretation, making UGRA techniques easier to learn and perform with greater safety and precision. ScanNav Anatomy PNB connects as an accessory to compatible general-purpose diagnostic ultrasound systems and supports the identification of anatomical structures for multiple common peripheral nerve blocks, including femoral blocks. It also offers 3D models and animations for reference and provides tips to improve access to each nerve. The device has demonstrated potential to support non-experts in training and clinical practice, and experts in teaching UGRA, ultimately aiding the uptake and generalizability of these techniques and improving patient access to regional anesthesia.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- Real-time AI-powered color overlay on ultrasound images
- Highlights relevant anatomical structures for peripheral nerve blocks (nerves, arteries, bones)
- Aids in ultrasound image interpretation
- Provides side-by-side images of live ultrasound feed with and without AI annotations
- Displays 3D models and animations for reference
- Offers tips to improve access to each nerve
- Supports multiple peripheral nerve block regions (initially 9, expanded to 10 including femoral nerve blocks)
- Connects to compatible diagnostic ultrasound systems
- Designed to enhance accuracy and standardization of ultrasound image interpretation
- Utilizes deep learning artificial intelligence technology
Use Cases
- Assisting anesthetists in performing Ultrasound-Guided Regional Anesthesia (UGRA)
- Training and teaching UGRA techniques for non-experts and experts
- Improving patient access to regional anesthesia
- Reducing risk of nerve block failure and needle trauma
- Pain relief after surgery and trauma
- Alternative to general anesthesia
What Physicians Need to Know
ScanNav Anatomy Peripheral Nerve Block can be a valuable tool for both training and clinical practice in ultrasound-guided regional anesthesia. For less experienced practitioners, it can enhance confidence and accuracy in identifying sonoanatomy. For experienced practitioners, it may serve as an effective teaching aid. While the AI provides real-time anatomical highlighting, clinicians should always maintain ultimate responsibility for image interpretation and needle placement. The system can help reduce the risk of needle trauma and block failure, but vigilance is still required. The device is an accessory to compatible general-purpose diagnostic ultrasound systems and is not intended as a standalone diagnostic tool.
ScanNav Anatomy Peripheral Nerve Block is sold as a standalone device that connects to compatible general-purpose diagnostic ultrasound systems via an external monitor output. Intelligent Ultrasound is also working on licensing its technology to major ultrasound manufacturers for integration directly into their scanners.
Details
| Category | Radiology & Imaging AI, Surgical AI |
| Pricing | Unknown |
| Mobile App | Surgical Science offers a mobile app for service and support, allowing users to show problems live with their smartphone's camera. There are also general surgical instrument identification and surgical simulation apps available on mobile platforms, but these are not directly tied to 'ScanNav Anatomy Peripheral Nerve Block' or Surgical Science. |
| Data Export | Unknown |
| Training | Unknown |
| Compliance | |
| BAA Available | Unknown |
| HIPAA Compliant | Unknown |
| FDA Status | Cleared AI-estimated |
| Integrations | |
| EHR | Not specified |
| Specialties | Anesthesiology, Interventional Radiology, Physical Medicine & Rehab |
Support & Reliability
| Training Provided | Unknown |
What the Web Says
ScanNav Anatomy Peripheral Nerve Block, developed by Intelligent Ultrasound, is an FDA-approved AI-powered software that assists healthcare professionals in identifying and labeling anatomical structures in real-time ultrasound images for ultrasound-guided regional anesthesia (UGRA). It uses deep learning AI to create color overlays of key anatomical structures, aiming to improve accuracy and reduce complications during nerve blocks. Studies suggest it significantly improves performance for novice practitioners in acquiring the correct block view and identifying anatomical structures.
Overall: PositiveStrengths
- Improved identification of anatomical landmarks and structures.
- Enhanced visualization of needle advancement and optimization of ultrasound image interpretation.
- Reduced risk of complications such as injury to surrounding structures or incorrect needle placement.
- Assists non-expert practitioners in achieving correct block views and identifying anatomical structures, potentially expanding safe regional anesthesia practice.
- Aids in training and teaching UGRA for both non-experts and experts.
- High accuracy in identifying structures (e.g., 96.7% accuracy in one study for femoral nerve block).
Limitations
- Current body of evidence is relatively limited, and further large-scale clinical trials are needed to confirm improved patient outcomes.
- Recognition of anatomical structures and obtaining correct views are only one aspect of UGRA; image interpretation and psychomotor skills for needle placement are also crucial.
- Potential for tracking failures or errors, and limited evidence on accuracy in diverse patient populations.
- Low perception of increased risk associated with AI highlighting (3.1%–4.7%), but potential complications like nerve injury are clinically important.
- Model-related limitation: recognizes only anatomical structures on images.
- Not open source.
Based on reviews from: anaesthesia-singapore.org.sg, nih.gov, fda.gov, ox.ac.uk, anaesthesiacollective.com, uky.edu, researchgate.net, innolitics.com, tmc.edu, frontiersin.org, globalrph.com
Last updated: 2026-10-30
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