Chest-CAD
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
Leverage Chest-CAD as a concurrent reading aid to significantly enhance your accuracy in detecting suspicious regions on chest X-rays, especially if you are a non-radiologist. Utilize the categorized ROIs (Cardiac, Mediastinum/Hila, Lungs, Pleura, Bones, Soft Tissues, Hardware, or Other) to efficiently guide your further investigation and refine differential diagnoses. Take advantage of the toggle function within your PACS viewer to manage the AI overlay, ensuring it complements your workflow without causing distraction. Always remember that Chest-CAD is an assistive tool intended to augment, not replace, your clinical judgment and diagnostic role.
Chest-CAD is engineered for seamless integration into existing X-ray reading workflows and Picture Archiving and Communication Systems (PACS), eliminating the need for new PACS technology or extensive re-training. Its output is delivered as a DICOM Presentation State file, ensuring broad compatibility with standard imaging infrastructure. As part of Imagen's 'Diagnostics as a Service (DaaS) platform,' it offers comprehensive integration support, including EMR integration and IT services, to streamline its adoption into your practice.
Details
| Category | Clinical Decision Support & Reference, Radiology & Imaging AI |
| Pricing | Contact for pricing — Solution-based; Contact Imagen Technologies for specific pricing models and tiers. |
| Deployment | Cloud-based |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
1 AI-estimated Chest-CAD received FDA 510(k) clearance (K210666) on July 20, 2021, as a Class II medical image analyzer (Product Code MYN) for computer-assisted detection (CADe) of suspicious regions in adult chest X-rays. |
| Integrations | |
| EHR | Not specified |
| Specialties | Emergency Medicine, Pulmonology, Radiology |
What the Web Says
Chest-CAD, developed by Imagen Technologies, is an FDA-approved deep-learning AI software designed to assist physicians in interpreting adult chest X-rays by identifying and categorizing suspicious regions of interest. Studies indicate that Chest-CAD can significantly improve the accuracy of chest X-ray interpretation, particularly for non-radiologist physicians, making their diagnostic performance comparable to that of radiologists when aided by the system. The software has demonstrated high overall accuracy, sensitivity, and specificity in detecting various chest abnormalities, including lung nodules, consolidation, and pneumothorax.
Overall: PositiveStrengths
- Improves overall physician accuracy in chest X-ray interpretation, especially for non-radiologists.
- Helps bridge the accuracy gap between radiologists and non-radiologist physicians.
- High overall AUC, sensitivity, and specificity in identifying chest abnormalities.
- Detects, categorizes, and localizes suspicious regions across eight clinical categories.
- Can reduce errors in chest X-ray interpretation.
- Potentially valuable in settings with limited access to radiologists, such as rural areas or low-resource environments.
Limitations
- Some older CAD systems showed low specificity and high false-positive rates when used as a primary reader.
- The effectiveness of CAD can vary based on the experience level of the reader, with less significant benefits for highly experienced radiologists.
- One study suggested that CAD did not improve the performance of chest or general radiologists in terms of follow-up rates for actionable nodules, and non-radiologists were more vulnerable to false-positive marks.
- One AI-based CAD system was found to be inferior to radiologists as a primary reader for lung nodule detection in chest phantoms.
Based on reviews from: AuntMinnie, EMJ, accessdata.fda.gov, Imagen Technologies, PMC, AJR Online
Last updated: 2026-07-18
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Press & Coverage
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Frequently Asked Questions
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