FDA Radiology AI Devices

The OPUSWAVE Dual Sensor Imaging System is a medical device that uses Optical Coherence Tomography to capture detailed images of cardiovascular structures. It helps clinicians by providing high-resolution imaging to assist in diagnosis and treatment of cardiovascular conditions.

EchoGo Amyloidosis (1.0) is an automated AI decision support system that analyzes 2D echocardiograms (specifically apical four chamber view) to screen for cardiac amyloidosis in adults over 65 years with heart failure. It helps clinicians by classifying patients as suggestive or not suggestive of cardiac amyloidosis, enabling referral for confirmatory testing. The AI was trained on large datasets and validated clinically to ensure accuracy and safety.

The UbiqVue 2A Multi-parameter System is a wireless wearable biosensor system for continuous monitoring of vital signs such as ECG, heart rate, respiration, temperature, SpO2, and blood pressure (optional). It transmits data wirelessly to a central server for storage, display, and analysis, enabling healthcare professionals to remotely monitor multiple patients at home and in clinical settings with alert notifications and visual alarms for abnormal physiologic parameters.

Frontier X Plus is a wearable ECG event recorder that monitors heart rhythms by capturing single-channel ECG signals via a chest strap. It automatically analyzes the ECG data using an embedded algorithm to detect arrhythmias such as atrial fibrillation, bradycardia, and tachycardia. The device helps clinicians monitor and diagnose heart conditions in adult patients, particularly those with suspected or known cardiac issues, by storing and transferring ECG data for physician review.

The Affera Integrated Mapping System with the Impedance Localization Patch Kit is a computer-based diagnostic tool designed to assist clinicians in catheter-based cardiac electrophysiological mapping. It provides real-time visualization of catheters, maps cardiac signals, and helps guide therapeutic interventions by displaying detailed cardiac maps and signals, enhancing cardiac procedure accuracy and patient care.

The Artix™ MT and Artix™ Thin-Walled Thrombectomy Sheath are devices designed to remove clots non-surgically from peripheral blood vessels. They facilitate catheter insertion and vascular access, allowing for mechanical thrombectomy and thrombus aspiration, which assists clinicians in restoring blood flow during vascular interventions.

The Intra-Operative Positioning System (IOPS) by Centerline Biomedical uses a fiducial tracking pad and a guidewire handle for real-time tip positioning and navigation during endovascular interventions. By leveraging 3D vascular models derived from prior CT scans, it helps clinicians accurately guide catheters and guidewires inside the descending aorta as an adjunct to fluoroscopy, enhancing procedure precision without providing a diagnosis itself.

EchoGo Heart Failure 2.0 is an AI-powered software tool that analyzes echocardiogram images of the heart's apical four-chamber view to support clinicians in detecting heart failure with preserved ejection fraction (HFpEF). It provides a diagnostic aid by outputting a classification and a confidence score, enhancing cardiovascular assessments and helping guide clinical decision-making.

HeartKey Rhythm is a software platform designed to analyze ECG data from various ambulatory monitoring devices such as Holters and ECG patches. Using a combination of machine learning and signal processing, the software detects heartbeats, assesses rhythm, and identifies arrhythmias to assist healthcare professionals in diagnosing cardiac conditions. It integrates through an API into other ECG management or monitoring systems and supports non-urgent clinical decision making.

Tempus ECG-AF is an AI-powered software that analyzes standard 12-lead ECG recordings from patients aged 65 and older to detect signs indicating an increased risk of atrial fibrillation or atrial flutter within the next 12 months. It assists clinicians by providing risk notifications based on ECG data, improving early identification of patients who may require further diagnostic follow-up.