Lung Vision

by Body Vision Medical  · Based in Israel → — Transforming Lung Cancer Intervention with Real-Time AI Imaging
Interventional Radiology Oncology Pulmonology

Regulatory Status Disclosed

Overview

LungVision by Body Vision Medical is an AI-powered, intraoperative imaging system designed to revolutionize lung cancer diagnostics and treatment. It transforms X-ray images from any conventional 2D C-arm into real-time 3D imaging, providing pulmonologists and thoracic surgeons with enhanced visualization during endobronchial biopsies.

The system addresses the challenge of CT-to-body divergence by enabling visual confirmation of tool-in-lesion, thereby empowering clinicians to accurately locate and biopsy smaller, more difficult-to-access lung lesions. LungVision integrates multimodal image fusion of preoperative CT and intraoperative fluoroscopy, and is compatible with standard biopsy instruments, including cryoprobes.

Its hardware-light design offers an affordable, low-cost solution with a small, mobile footprint, and it can seamlessly integrate with various navigation platforms, bronchoscopes (including robotic systems), and biopsy tools. The technology aims to improve diagnostic yield, reduce radiation exposure compared to traditional 3D C-arms, and facilitate earlier, more confident diagnosis of lung cancer.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • AI-powered intraoperative imaging
  • Transforms 2D C-arm images into real-time 3D imaging
  • Visual confirmation of tool-in-lesion
  • Corrects for CT-to-body divergence
  • Enables biopsy of smaller, difficult-to-access lung lesions
  • Multimodal image fusion (preoperative CT & intraoperative fluoroscopy)
  • Integrates with standard biopsy instruments (e.g., cryoprobe)
  • Augmented fluoroscopy
  • Reduced radiation exposure (compared to 3D C-arms)
  • Seamless integration with various C-arms, navigation platforms, and bronchoscopes

Use Cases

  • Early lung cancer diagnosis
  • Biopsy of peripheral pulmonary nodules
  • Image-guided navigation during bronchoscopic procedures
  • Delivery of localized therapies for lung lesions
  • Enhancing robotic bronchoscopy platforms
  • Single-anesthesia diagnosis and treatment of lung lesions

What Physicians Need to Know

Key Capabilities
LungVision uses AI to transform X-ray images from any 2D C-arm into real-time 3D intraoperative CT scans, enabling precise navigation and visualization of lung nodules during bronchoscopy procedures. It provides real-time tool-in-lesion confirmation and augmented fluoroscopy. The system also offers AI-driven suggested lesion location features and can be used as a standalone platform or to augment robotic bronchoscopy platforms. It supports biopsy of small, difficult-to-access lung lesions.
Clinical Utility
The system aims to improve the diagnostic yield of peripheral lung nodule biopsies, potentially leading to earlier lung cancer detection and improved survival rates. It helps physicians accurately locate and biopsy lesions, reducing the need for additional procedures. Studies have shown diagnostic accuracy of 88.2% at 12 months follow-up. It also helps reduce radiation exposure compared to traditional 3D C-arms.
Integration Options
LungVision seamlessly integrates with existing procedural workflows and leverages existing hospital equipment, including 2D and 3D C-arms, navigation platforms, bronchoscopes (including robotic systems like Ethicon MONARCH™ and Ion by Intuitive), and standard biopsy tools (including cryoprobes). It is designed to work with any C-arm.
Compliance Status
The LungVision 2.0 System received FDA 510(k) clearance in May 2019. It complies with ANSI/AAMI/ES 60601-1:2005(2012) and IEC 60601-1-2:2014 standards. It has also received regulatory approvals in Australia, India, Brazil, and Singapore.
Pricing Model
Body Vision Medical offers a subscription model to make LungVision more accessible, allowing hospitals to acquire the system without significant capital expenditures. It is presented as a cost-effective solution compared to electromagnetic navigation, robotics, or cone-beam CT systems, aiming to reduce implementation costs by utilizing existing hospital equipment.
User Experience
The system is designed to be easy-to-use, empowering users with real-time intraoperative imaging for precise and confident lesion localization and biopsy. Recent software updates have focused on improving the user interface with a clean, modern aesthetic and streamlined procedural workflow, aiming for a reduced learning curve and a more intuitive experience.
Support Quality
Body Vision Medical provides extended warranty plans for reliable, certified, and expedited support. They also offer advanced clinical training, refresher training, and education for new staff.
Implementation Complexity
LungVision is designed for seamless integration into existing procedural workflows, leveraging existing hospital equipment to reduce implementation costs. Its hardware-light design offers a small, mobile footprint.
Evidence Base
The LungVision system has been the subject of clinical case studies and scientific articles demonstrating its clinical efficacy. A prospective, single-center study reported an average distance of 5.9 mm between the lesion location shown by LungVision augmented fluoroscopy and the actual location measured by cone beam CT (CBCT), with an 88.2% diagnostic accuracy at 12 months follow-up. The Cleveland Clinic reported an improvement in diagnostic yield by 14.5% (from 74% to 88%) using LungVision.
Physician Tip

LungVision's real-time, AI-powered 3D imaging from any C-arm can significantly enhance confidence in biopsying small, peripheral lung lesions, potentially improving diagnostic yield and reducing radiation exposure. Its compatibility with existing bronchoscopy setups and robotic platforms allows for flexible integration into current practice. The ability to confirm tool-in-lesion in real-time addresses the challenge of CT-to-body divergence, making it a valuable tool for interventional pulmonologists and thoracic surgeons. Consider its use for challenging cases where precise localization is critical.

LungVision is designed for broad compatibility, integrating with various 2D and 3D C-arms, navigation platforms, and both traditional and robotic bronchoscopes (e.g., Ethicon MONARCH™ and Ion by Intuitive). This flexibility allows it to augment existing equipment and workflows without requiring a complete overhaul of the bronchoscopy suite. It also works with standard biopsy tools, including cryoprobes.

Details

Category Oncology AI, Radiology & Imaging AI, Surgical AI
Pricing Unknown
DeploymentThe LungVision system is a hardware-light, mobile platform that integrates with any conventional 2D C-arm, transforming it into an advanced 3D imaging system. It can be used as a standalone system or as an adjunct to robotic bronchoscopy platforms.
TrainingUnknown
Compliance
BAA AvailableUnknown
HIPAA CompliantUnknown
FDA Status Cleared AI-estimated
Integrations
EHR Not specified
Specialties Interventional Radiology, Oncology, Pulmonology

Support & Reliability

Training ProvidedUnknown

What the Web Says

LungVision is generally viewed as a promising technology for improving the accuracy and safety of bronchoscopic procedures for lung cancer diagnosis. Reviewers highlight its ability to provide real-time, intraoperative CT-like imaging, which can enhance navigation and lesion targeting. The system aims to address limitations of traditional bronchoscopy, potentially leading to better diagnostic yields and reduced complications.

Overall: Positive

Strengths

  • Real-time, intraoperative CT-like imaging for enhanced navigation
  • Improved accuracy in targeting peripheral lung lesions
  • Potential to increase diagnostic yield in bronchoscopy
  • Reduces the need for repeat procedures
  • Integration with existing bronchoscopy equipment
  • Aids in confirming biopsy tool placement

Limitations

  • Steep learning curve for new users
  • Requires additional setup time in the operating room
  • Cost of implementation may be a barrier for some institutions
  • Reliance on pre-operative CT scans for initial planning
  • Potential for increased radiation exposure compared to standard bronchoscopy (though often less than repeat CTs)
  • Limited availability in all medical centers

Based on reviews from: Physician reviews and clinical studies, Healthcare technology publications, Medical device review sites

Last updated: 2026-10-29

Ratings & Reviews

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Ease of Use
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Press & Coverage

PR Newswire
Yashoda Hospitals First in India and Asia to Perform Diagnostic Bronchoscopy with LungVision AI-Driven Intraoperative CT Imaging
Yashoda Hospitals in Hyderabad, India, became the first in India and Asia to utilize Body Vision Medical's LungVision System for diagnostic bronchoscopy, employing its AI-driven intraoperative CT imaging capabilities. This technology transforms X-ray images into real-time CT scans, enabling more precise biopsies of smaller lung nodules.
2023-03
Frontiers in Medicine
Integration of robotic-assisted bronchoscopy with the LungVision system for peripheral pulmonary lesions: a real-world experience
A study published in Frontiers in Medicine details the successful integration of robotic-assisted bronchoscopy with the LungVision system for diagnosing peripheral pulmonary lesions. The combination of AI-aided augmented fluoroscopy and robotic technology demonstrated high diagnostic efficacy and a strong safety profile for targeting lesions.
2026-07
FDA.gov
Lung Vision System 510(k) Premarket Notification
The FDA's 510(k) premarket notification for the Lung Vision System from Bodyvision Medical, Ltd. was cleared in April 2019. This regulatory document outlines the device's classification as a radiological image processing system.
2019-04
AIPO Rassegna
LungVision: A New Technology for Endoscopic Diagnosis of Peripheral Pulmonary Nodules
This article discusses LungVision as a navigation and augmented fluoroscopy system that integrates pre-procedural CT images with real-time fluoroscopy using AI algorithms to improve visualization and sampling of lung nodules. It highlights the system's ability to visualize nodules not visible with conventional fluoroscopy.
2023-08
MDPI
Diagnostic Yield and Safety of Ultrathin Cryoprobe with Lung Vision Platform for Peripheral Lung Nodules
A study published in MDPI in October 2024 investigated the diagnostic yield and safety of using an ultrathin cryoprobe in conjunction with an ultrathin bronchoscope and the Lung Vision platform. The integration of these technologies showed a favorable safety profile and significant diagnostic yield for early detection and characterization of lung nodules.
2024-10
MDPI
Real-Time Imaging for Navigational Bronchoscopy: A Review of Current Technologies and Future Directions
This review article from MDPI, published in March 2023, discusses various real-time imaging technologies used in navigational bronchoscopy, including LungVision. It highlights LungVision's use of augmented fluoroscopy and AI to assist with intra-operative nodule localization and its ability to track tools in real-time.
2023-03
Translational Lung Cancer Research
Cone-beam CT in lung biopsy: a clinical practice review on lessons learned and future perspectives
This review article from August 2023 discusses novel hybrid technological systems like Lung Vision (Body Vision Medical) that integrate multiple information sources for reconstructing and confirming navigation pathways and lesion positions during lung biopsies. It notes that Lung Vision uses advanced image processing to integrate fluoroscopy with pre-procedural CT scans.
2023-08
Beyond Air, Inc.
Beyond Air Appoints Douglas Webster as Chief Operating Officer
Beyond Air, Inc. announced the appointment of Douglas Webster as Chief Operating Officer in June 2024. The press release notes that Webster previously served as CEO of Body Vision Medical, where he led the global commercialization of the Lung Vision system.
2024-06

Videos

Product demos, reviews, and walkthroughs for Lung Vision.

View all on YouTube

Frequently Asked Questions

The LungVision system utilizes proprietary AI Tomo® technology to correct for CT-to-body divergence, which is the discrepancy between a lesion's preoperative CT location and its actual position during bronchoscopy. This technology transforms X-ray images from any conventional 2D C-arm into real-time 3D imaging, enabling visual confirmation of the tool-in-lesion during endobronchial biopsies and increasing diagnostic confidence.
LungVision offers several advantages, including real-time, AI-enhanced 3D imaging for precise navigation and biopsy of small, peripheral lesions, even those invisible on standard fluoroscopy. It integrates with existing equipment, such as 2D and 3D C-arms, navigation platforms, and bronchoscopes (including robotic systems), which can significantly lower implementation costs. Additionally, it aims to reduce radiation exposure compared to some 3D C-arms and can achieve diagnostic yields approaching 90% and beyond.
While LungVision offers significant advancements, early studies evaluating its feasibility and safety had small sample sizes and lacked control groups or active comparator groups. Although the diagnostic yield is reported to be high, randomized controlled trials are needed to accurately ascertain its diagnostic yield compared to other methods. The system also requires a standard chest CT scan with a slice thickness of less than 1.5 mm for planning.
LungVision is designed for seamless integration with existing procedural workflows and leverages equipment hospitals already possess, such as 2D and 3D C-arms. It is compatible with various biopsy tools, including cryoprobes, and can augment robotic bronchoscopy platforms with real-time intraoperative imaging.
The LungVision System is intended to enable users to segment previously acquired 3D CT datasets and overlay and register these 3D segmented data sets with fluoroscopic live X-ray images to support catheter/device navigation during pulmonary procedures. It has received regulatory approvals in various regions, including Singapore, India, and Australia, indicating its compliance with local medical device regulations.
Alternatives to LungVision include other advanced navigational bronchoscopy systems such as electromagnetic navigation bronchoscopy (ENB), virtual bronchoscopy (VB), radial endobronchial ultrasound (r-EBUS), ultrathin bronchoscopy, robotic-assisted bronchoscopy (RAB), and cone-beam computed tomography (CBCT) guided bronchoscopy. Each of these technologies has its own advantages and limitations regarding diagnostic yield, cost, and integration with existing equipment.
Body Vision Medical aims to provide a cost-effective solution by designing LungVision to integrate with existing equipment, thereby reducing implementation costs. The company has also introduced a subscription model to allow hospitals to acquire the system without depleting capital budgets. This approach positions LungVision as a more affordable option compared to some electromagnetic navigation, robotics, or cone-beam CT systems.

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The LungVision® System is an AI-powered, intraoperative imaging and navigation system from Body Vision Medical that transforms 2D C-arm images into real-time 3D for precise peripheral lung biopsy and intervention. It offers augmented fluoroscopy with tool-in-lesion confirmation, improving diagnostic yield and reducing radiation exposure.

View company profile →

Suggest an Edit → | Report an issue | Last Verified: 2026-04-17 | First Added: 2026-04-17
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