Chest-CAD

by Imagen Technologies  · Based in United States →
Emergency Medicine Pulmonology Radiology
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Regulatory Status Disclosed

Overview

Chest-CAD by Imagen Technologies is an FDA-cleared computer-assisted detection (CADe) software device designed to assist physicians in identifying and categorizing suspicious regions of interest (ROIs) on adult chest X-rays. The underlying AI model was trained on a massive proprietary dataset, encompassing all abnormalities screenable on a chest X-ray. In clinical studies, Chest-CAD was shown to reduce diagnostic errors by 40% for clinicians. It detects and highlights suspicious regions, assigning them to categories such as Cardiac, Mediastinum/Hila, Lungs, Pleura, Bones, Soft Tissues, Hardware, or Other. The device integrates seamlessly into existing PACS workflows, allowing physicians to toggle the AI overlay on or off for concurrent review. Imagen Technologies aims to democratize access to world-class imaging by providing AI-enabled diagnostic services that improve diagnostic accuracy, enhance the patient experience, reduce costs, and alleviate clinician burnout.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • AI-powered detection and categorization of ROIs on chest X-rays
  • Identifies suspicious regions in categories: Cardiac, Mediastinum/Hila, Lungs, Pleura, Bones, Soft Tissues, Hardware, Other
  • Reduces diagnostic errors by 40% in clinical studies
  • Concurrent reading aid for physicians
  • Integrates with Picture Archiving and Communication System (PACS) viewers
  • Cloud-based processing and delivery
  • Deep learning algorithms for computer vision
  • Provides bounding boxes and labels for detected ROIs

Use Cases

  • Assisting physicians in interpreting adult chest radiographs
  • Reducing misinterpretation rates in diagnostic imaging
  • Facilitating earlier disease detection and intervention
  • Improving diagnostic accuracy and consistency
  • Enhancing clinician efficiency and reducing burnout
  • Minimizing unnecessary ER and specialist visits

What Physicians Need to Know

Evidence Base
Chest-CAD analyzes chest radiographs using deep learning algorithms for computer vision. It identifies, categorizes, and highlights suspicious regions of interest (ROIs) in adult chest X-rays. These ROIs are assigned to categories such as Cardiac, Mediastinum/Hila, Lungs, Pleura, Bones, Soft Tissues, Hardware, or Other.
Clinical Validation Studies
Imagen conducted a retrospective reader study to assess Chest-CAD's impact on reader performance in detecting suspicious ROIs. The study aimed to determine if the accuracy of readers aided by Chest-CAD was superior to unaided readers, measured by the Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curve. Bench testing was performed on 20,000 chest radiograph cases from 12 U.S. hospitals, outpatient, and specialty centers. The software's level of concern is moderate, as a malfunction could lead to minor injury due to erroneous diagnosis or delayed care. AUC values ranged from 0.921 (Mediastinum/Hila) to 0.994 (Hardware). Sensitivity was highest for Hardware (0.967) and lowest for Bones (0.854), while specificity was highest for Hardware (0.960) and lowest for Mediastinum/Hila (0.830).
Alert Fatigue Management
While the product description does not specifically detail alert fatigue management features, general strategies for managing alert fatigue in clinical decision support systems include increasing alert specificity, conforming alerts to individual patient profiles, and tiering alerts by severity. Optimizing alert systems by filtering recipients, tailoring alerts by activity, eliminating redundant alerts, and composing brief, actionable messages can also help.
Differential Diagnosis Support
Chest-CAD identifies and categorizes suspicious ROIs into eight categories: Cardiac, Mediastinum/Hila, Lungs, Pleura, Bones, Soft Tissues, Hardware, or Other. This categorization assists physicians in narrowing down potential diagnoses related to findings in these areas.
Clinical Workflow Integration
Chest-CAD is designed to integrate into existing chest X-ray workflows. The output overlay, which highlights suspicious ROIs with bounding boxes, can be toggled on or off by the physician within their Picture Archiving and Communication System (PACS) viewer, allowing for concurrent review of the X-ray study. This integration does not require new PACS technology or extensive re-training.
Physician Tip

Chest-CAD functions as a concurrent reading aid for physicians interpreting adult chest X-rays. Physicians can toggle the Chest-CAD overlay on or off within their PACS viewer to assist in identifying suspicious regions of interest. The tool categorizes findings into specific areas like Cardiac, Lungs, and Bones, which can help focus diagnostic attention. It is important to remember that Chest-CAD is an aid and does not replace the physician's diagnosis.

Chest-CAD is a cloud-based, software-only medical device that integrates seamlessly into existing X-ray reading workflows. It does not necessitate new PACS technology or costly re-training for physicians. The device operates on digital X-rays from a DICOM node. The output is a DICOM Presentation State file (output overlay) that can be viewed within the PACS system.

Details

Category Clinical Decision Support & Reference, Radiology & Imaging AI
Pricing Unknown
DeploymentCloud-based, integrates with PACS viewers.
API AvailableUnknown
Compliance
BAA Available Yes AI-estimated
HIPAA Compliant Yes AI-estimated
FDA Status Cleared AI-estimated
SOC 2 Yes AI-estimated
GDPR Yes AI-estimated
Integrations
EHR Not specified
Specialties Emergency Medicine, Pulmonology, Radiology

What the Web Says

Chest-CAD by Imagen Technologies is a computer-assisted detection (CADe) software device designed to aid physicians in identifying suspicious regions of interest (ROIs) in adult chest X-rays. It uses machine learning to analyze radiographs, categorize findings (e.g., Cardiac, Lungs, Bones), and highlight them with bounding boxes. The device is intended as a concurrent reading aid, with its overlay toggleable within a Picture Archiving and Communication System (PACS) viewer.

Overall: Mixed

Strengths

  • Aids in detecting suspicious ROIs in chest X-rays
  • Categorizes findings into specific areas like Cardiac, Lungs, and Bones
  • Uses deep learning algorithms for computer vision
  • Provides annotations and bounding boxes to highlight suspicious areas
  • Overlay can be toggled on/off within PACS viewer for concurrent review
  • May improve diagnostic performance for inexperienced readers

Limitations

  • Minimal benefit for experienced radiologists
  • Some general concerns about AI in radiology regarding accuracy and over-reliance
  • Potential for false positives, which require review and dismissal by the reader
  • Some Reddit users express skepticism about the overall quality of AI-leveraged teleradiology reads

Based on reviews from: nih.gov, auntminnie.com, g2.com, reddit.com, dicardiology.com, fda.gov, fda.report, appliedradiology.com, prnewswire.com, massdevice.com, medicaldevice-network.com, capterra.ca, capterra.com

Last updated: 2026-10-30

Ratings & Reviews

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Press & Coverage

AuntMinnie.com
AI lifts nonradiologists' x-ray interpretation skill levels
A study published in Scientific Reports on October 24, 2024, found that Imagen Technologies' Chest-CAD, an AI model, performed on par with radiologists in detecting abnormalities on chest X-rays and eliminated the accuracy gap between radiologists and non-radiologist physicians. This suggests Chest-CAD can support various physician specialties in accurate chest X-ray interpretation.
2024-10
Diagnostic Imaging
FDA Clears AI-Enabled Chest CT Software for Aortic Analysis
While not directly about Chest-CAD, this article from October 27, 2026, mentions the FDA clearance of Aview Aorta Metrics software for automated segmentation and classification of aortic regions based on chest CT images, indicating ongoing regulatory activity in AI-powered chest imaging.
2026-10
FDA.gov
Chest-CAD 510(k) Summary
This regulatory document from July 20, 2021, details the FDA 510(k) clearance for Chest-CAD, a computer-assisted detection (CADe) software device designed to help physicians identify suspicious regions of interest (ROIs) in adult chest X-rays. It outlines the device's intended use, its deep learning algorithms, and the results of studies demonstrating its superiority in aiding physicians compared to unaided interpretations.
2021-07
FDA.gov
Aorta-CAD 510(k) Summary
This FDA 510(k) summary from September 20, 2022, identifies Imagen Technologies' Chest-CAD as the predicate device for Aorta-CAD. It describes Chest-CAD as a CADe software that analyzes chest radiographs using machine learning to identify, categorize, and highlight suspicious ROIs, serving as a concurrent reading aid for physicians.
2022-09
NIH.gov (Scientific Reports)
Artificial intelligence system for comprehensive detection of abnormalities on chest X-rays
Published on October 24, 2024, this peer-reviewed article describes the development of Imagen Technologies' FDA-cleared Chest-CAD system, which uses deep learning to assist physicians in interpreting chest X-rays. The study highlights the AI system's strong standalone performance and its ability to increase physician accuracy in detecting abnormalities, even eliminating the accuracy gap between radiologists and non-radiologist physicians.
2024-10
MDPI.com
Deep Learning for Medical Image Analysis: A Review of Recent Advances and Future Directions
This review article, published on November 11, 2025, discusses the rapid advancements in deep learning for chest X-ray image analysis. It references Anderson et al. [7] (referring to Imagen's Chest-CAD) as having developed an FDA-approved AI system that employs deep learning to assist in identifying anomalies in chest X-rays, enhancing physician accuracy with a 97.6% AUC.
2025-11
AIMS Medical Science
AI in Cancer Diagnosis: A Comprehensive Review of Its Role in Radiology and Medical Imaging
This review, published on May 16, 2024, explores the role of AI in cancer diagnosis, particularly in radiology. It mentions Chest-CAD by Imagen Technologies as an AI tool that helps identify missed spots or misinterpretations by clinicians, which historically occur at a rate of 47%.
2024-05
NIH.gov (Cureus)
Case Report: Missed Lung Cancer on Chest Radiograph Detected by Artificial Intelligence
This case report highlights the promising results of applying Imagen Technologies' FDA-cleared Chest-CAD AI tool to a chest X-ray where lung cancer was initially missed by a radiologist. The article, published in 2021, demonstrates Chest-CAD's ability to accurately detect and localize the region of interest containing the cancer, suggesting its potential to significantly improve diagnostic accuracy.
2021

Videos

Product demos, reviews, and walkthroughs for Chest-CAD.

View all on YouTube

Frequently Asked Questions

Imagen's Chest-CAD is designed to seamlessly integrate into existing X-ray reading workflows without requiring new PACS technology or extensive retraining. It provides an overlay with annotations that can be toggled on or off by the physician within their Picture Archiving and Communication System (PACS) viewer, allowing for concurrent review of the X-ray study.
Chest-CAD is a computer-assisted detection (CADe) software device that analyzes chest radiograph studies using machine learning to identify, categorize, and highlight suspicious regions of interest (ROIs). These ROIs are assigned to one of eight categories: Cardiac, Mediastinum/Hila, Lungs, Pleura, Bones, Soft Tissues, Hardware, or Other.
While Chest-CAD is intended as a concurrent reading aid for physicians, it does not replace the physician's role or other diagnostic testing in the standard of care. It is designed to assist in identifying suspicious regions, but the final diagnosis and treatment plan remain the responsibility of the physician.
Yes, there are other CAD systems available for chest X-rays. For example, Riverain's ClearRead X-ray offers applications for bone suppression and nodule detection, and Lunit INSIGHT CXR identifies 11 major thoracic abnormalities and supports tuberculosis screening. Rayscape CXR also provides pathology identification and AI-generated advanced visualizations.
Imagen Technologies offers different pricing plans for its AI tools, including 'Pay-as-you-go' and 'Limitless' options. The 'Pay-as-you-go' plan involves a monthly base fee plus charges for edits used, while the 'Limitless' plan offers a fixed monthly or annual fee for unlimited AI edits and tools. For teams and studios, a custom-priced 'Business' plan is available.

Compare Chest-CAD

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Suggest an Edit → | Report an issue | Last Verified: 2026-04-18 | First Added: 2026-04-18
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