FDA Radiology AI Devices

The SpotLight / SpotLight Duo with Low Dose Lung Cancer Screening Option is a CT X-ray system that produces cross-sectional images of the body, particularly the cardiovascular and thoracic regions. It includes protocols for low dose CT scans aimed at lung cancer screening, ensuring minimal radiation exposure while maintaining image quality. This device assists clinicians in diagnosing lung cancer and planning related therapies, utilizing advanced image reconstruction algorithms and adaptable scan techniques for patients of various sizes.

Brainomix 360 e-Lung is a software tool designed to assist physicians by providing automated, quantitative analysis of chest CT images. It offers 3D segmentation, volumetric measurements, and density evaluations of lung tissue to support diagnosis and longitudinal assessment of lung diseases, enhancing workflow efficiency and accuracy in radiological interpretation of CT thoracic scans.

The SpotLight/SpotLight Duo with Low Dose Lung Cancer Screening Option is a computed tomography (CT) X-ray system developed by Arineta Ltd. It produces detailed cross-sectional images of the body, especially of the cardiovascular and thoracic areas, enabling clinicians to screen and diagnose lung cancer using low-dose CT protocols. This device helps physicians detect lung nodules and other thoracic abnormalities with reduced radiation exposure, supporting effective lung cancer screening programs following clinical guidelines.

ClearRead CT CAC is software that helps physicians assess coronary artery calcification on non-contrast, non-gated chest CT scans. It automatically detects and quantifies calcified coronary lesions, providing an Agatston score and categorization to aid in cardiovascular risk assessment. This allows clinicians to efficiently obtain quantitative calcium scoring to help guide patient management, supplementing but not replacing clinical expert review.

The Gating Reflector Block is a reusable hardware accessory used during radiotherapy treatment and imaging to track patient respiratory motion. It helps monitor breathing patterns by reflecting infrared light detected by cameras in compatible radiation therapy and imaging systems, improving motion management during imaging or treatment delivery.

AI-Rad Companion (Pulmonary) by Siemens Healthcare GmbH is software that uses machine learning and deep learning to analyze previously acquired chest CT scans. It helps radiologists and physicians segment lungs and lung lobes, identify and measure solid and sub-solid lung nodules, and track changes over time. This supports clinicians in assessing lung diseases, improving workflow efficiency and diagnostic accuracy.

LungQ v3.0.0 is a software tool that helps physicians analyze CT scans of the lungs by automatically segmenting lung structures, measuring lung volumes and densities, evaluating fissures, and generating reports. It supports diagnosis and monitoring of lung conditions by providing quantitative assessments from CT scans, streamlining clinical workflows.

BriefCase-Quantification by Aidoc Medical is an AI-driven software designed to analyze non-cardiac-gated, non-contrast CT scans including the heart to detect and categorize coronary artery calcification (CAC). It provides physicians with a four-category risk assessment for coronary artery disease along with preview images of detected calcium, assisting clinical evaluation but not replacing full image review or clinical judgement.

The iCAC Device is a software tool that analyzes routine chest CT scans to automatically detect and quantify coronary artery calcium, which helps physicians assess cardiovascular risk. It provides outputs such as calcium segmentation visualizations and quantitative calcium scores during standard clinical workflows, assisting physicians without replacing original reports or scans.

AI-Rad Companion (Pulmonary) is AI-powered software that analyzes chest CT scans to help radiologists and clinicians identify and measure lung structures and lesions. It segments lungs and lung lobes, detects lung nodules, compares current images to prior scans for lesion follow-up, and quantifies pulmonary density. These features support the clinical assessment and monitoring of lung diseases, improving workflow efficiency and diagnostic accuracy.