V5med Lung AI is an AI-powered software that helps radiologists detect pulmonary nodules in chest CT images. It automatically analyzes scans and highlights areas with suspected nodules between 4 and 30 mm, acting as a supportive tool to improve accuracy and reduce missed findings. The system integrates easily with clinical imaging workflows and has been clinically validated to improve radiologist performance and reduce reading time.
V5med Lung AI is a Computer-Aided Detection (CAD) software designed to assist radiologists in detecting pulmonary nodules (with diameter of 4-30 mm) during CT examinations of the chest for asymptomatic populations. It provides adjunctive information to alert radiologists to regions of interest with suspected lung nodules that may otherwise be overlooked, used in concurrent read mode alongside original CT images.
V5med Lung AI uses a Deep Convolutional Neural Network (CNN)-based algorithm to automatically detect lung nodules from 4 to 30 mm in chest CT images. The system integrates algorithm and database on a single server, accepts chest CT images from PACS, RIS, or CT scanners, and outputs annotations of nodules. It supports multi-vendor CT scanners and non-contrast images, providing DICOM GSPS output for visualization.
Performance testing included software validation with unit, system, and integration testing confirming functional correctness and stability. Measurement accuracy was validated on phantom and clinical data. A pivotal multi-reader multi-case (MRMC) clinical study with 16 radiologists and 340 chest CT scans demonstrated that using V5med Lung AI significantly improved radiologist nodule detection performance (AUC increase from 0.734 to 0.830) and reduced reading time by 13%.
No predicate devices specified
Submission
9/24/2024
FDA Approval
3/27/2025
Join hundreds of your peers who rely on RadAI Slice. Get the essential weekly briefing that empowers you to navigate the future of radiology.
We respect your privacy. Unsubscribe at any time.