Lung-CAD

by Imagen Technologies  · Based in United States → — Making High-Quality Healthcare Accessible To Everyone
Internal Medicine Pulmonology Radiology
Website
Claim this tool
Is this the maker? Claim the company →

Contact for pricing
Regulatory Status Disclosed

Overview

Imagen Technologies is a physician-led diagnostic imaging practice that delivers technology-enabled imaging services to improve diagnostic quality, efficiency, cost, and access to care. Their practice is powered by FDA-cleared, AI-enabled software, including Lung-CAD, which is fully integrated into PACS environments. This AI software supports radiologists and other physicians in working more efficiently and confidently while maintaining high standards of diagnostic accuracy. Imagen’s AI solutions aim to reduce medical expenses by aiding in early detection and intervention, preventing unnecessary ER and specialist visits, and improving accuracy to cut down on unnecessary referrals. The company combines clinical leadership with advanced technology to modernize radiology, equipping healthcare professionals with practical tools that enhance patient care and support sustainable, high-quality practice.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Detects and highlights interstitial thickening on chest radiographs
  • Detects and highlights lung hyperinflation on chest radiographs
  • AI algorithm trained on findings suggestive of Pulmonary Fibrosis and COPD
  • 48% relative reduction in misses of interstitial thickening in clinical study
  • 40% relative reduction in misses of lung hyperinflation in clinical study
  • 93% of physicians showed improvement when assisted by Lung-CAD in a clinical study
  • Generates DICOM Presentation State file (output overlay)
  • Integrated into PACS environment
  • Concurrent reading aid for physicians
  • Secure cloud-based processing and delivery

Use Cases

  • Assisting physicians in interpreting chest X-rays
  • Early detection of interstitial thickening
  • Early detection of lung hyperinflation
  • Improving diagnostic quality and efficiency in radiology
  • Supporting radiologists in working more efficiently and confidently
  • Reducing diagnostic errors in chest radiograph interpretation

What Physicians Need to Know

Key Capabilities
Lung-CAD is a computer-assisted detection (CADe) software that uses deep learning algorithms to analyze chest X-rays and identify suspicious regions of interest (ROIs). It categorizes these ROIs into several categories, including Cardiac, Mediastinum/Hila, Lungs, Pleura, Bones, Soft Tissues, Hardware, or Other. The software generates a DICOM Presentation State file (output overlay) for each image, indicating detected ROIs and their categories. Lung-CAD is designed to assist physicians in interpreting adult chest X-rays.
Clinical Utility
Lung-CAD aims to improve the detection rate of actionable lung nodules on chest radiographs. Studies suggest that AI-based CAD systems can enhance the detection of lung nodules, potentially optimizing workflow and reducing missed diagnoses. When used as a second reader, CAD systems can increase radiologists' sensitivity for detecting pulmonary nodules. However, some studies indicate that AI-based CAD systems, when used as a primary reader, may be inferior to radiologists in detecting lung nodules in chest phantoms. The system's effectiveness can vary based on nodule size and type, with lower sensitivity for ground-glass and cystic nodules.
Integration Options
Lung-CAD generates a DICOM Presentation State file (output overlay) for each image, which 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 suggests a direct integration with existing PACS infrastructure.
Compliance Status
Imagen Technologies, Inc. has received FDA 510(k) clearance for Chest-CAD (K210666) in July 2021 and for Lung-CAD (K230085 and K223811) in 2023. The device is classified as a Class II Medical Image Analyzer (21 CFR 892.2070, product code MYN).
Pricing Model
While specific pricing for Lung-CAD is not publicly available, Imagen offers various pricing models for its AI tools, including pay-as-you-go, yearly subscriptions, and enterprise plans. Some plans may include a monthly base fee and per-photo charges for additional AI tools. Free trials are typically available.
User Experience
The Chest-CAD overlay can be easily toggled on or off within the PACS viewer, suggesting a user-friendly interface for concurrent review. The design aims to assist physicians with their interpretations by providing relevant annotations.
Evidence Base
Lung-CAD analyzes radiographs using deep learning algorithms. Studies on AI-based CAD systems for lung nodule detection have shown promising results in improving detection rates, particularly when used as a second reader. However, some research indicates that the performance of AI-CAD can vary with nodule characteristics and may be inferior to radiologists as a primary reader. Further research is recommended to fully understand the clinical and cost-effectiveness of these technologies.
Physician Tip

Consider using Lung-CAD as a secondary reading tool to augment your initial interpretation of chest X-rays, especially for detecting subtle or easily missed nodules. Be aware that the tool's sensitivity may vary with nodule size and type, particularly for ground-glass and cystic nodules. While AI can enhance detection, it's crucial to integrate its findings with your clinical judgment and patient history. Continue to monitor emerging evidence regarding the clinical and cost-effectiveness of AI-CAD systems.

Lung-CAD is designed to integrate seamlessly with existing Picture Archiving and Communication Systems (PACS) through DICOM Presentation State files, allowing physicians to toggle the AI overlay on or off for concurrent review within their familiar workflow. This minimizes disruption and facilitates adoption into current radiological reading practices.

Details

Category Oncology AI, Radiology & Imaging AI
Pricing Contact for pricing
DeploymentCloud-based
Compliance
BAA Available Yes AI-estimated
HIPAA Compliant Yes AI-estimated
FDA Status Cleared AI-estimated
Integrations
EHR Not specified
Specialties Internal Medicine, Pulmonology, Radiology

What the Web Says

Lung-CAD, particularly the product from Imagen Technologies, is a computer-aided detection (CADe) tool designed to assist in identifying lung abnormalities like consolidation/atelectasis and pleural effusion in ultrasound scans, and pulmonary nodules in CT scans. Physicians generally find that AI-based CAD systems improve diagnostic accuracy and sensitivity, especially for detecting lesions that might be overlooked by human readers. However, there are concerns about false positives and the potential for complacency among radiologists.

Overall: Mixed

Strengths

  • Aids in detecting lung abnormalities, including consolidation/atelectasis, pleural effusion, and pulmonary nodules.
  • Can improve diagnostic accuracy and sensitivity for physicians, particularly in identifying missed lesions.
  • Offers high sensitivity and can reduce false negative findings.
  • May lead to faster reading times for radiologists.
  • Automated detection provides consistency, especially in repetitive tasks like screening for lung nodules in numerous thin-slice CT studies.
  • Can be particularly helpful for less experienced physicians and in early diagnosis of cancer.

Limitations

  • Can produce a significant number of false positives.
  • May have troubling false negatives, missing some cancers even when designed to detect them.
  • Radiologists may become complacent due to false positives, potentially degrading performance over time.
  • Performance may be spotty, and understanding its strengths and shortcomings is crucial.
  • Increased reading time in some cases when assisted by AI.
  • CAD systems trained on adult data may perform poorly when applied to pediatric CT scans.

Based on reviews from: fda.gov, diagnosticimaging.com, mdpi.com, radiologybusiness.com, innolitics.com, auntminnie.com, nih.gov, arxiv.org, itnonline.com, reddit.com, bioengineer.org, ai-imaging.org, ajronline.org, spie.org, csu.edu.au, researchgate.net, science.gov

Last updated: 2026-10-30

Ratings & Reviews

No reviews yet. Be the first to review this tool!

Rate Lung-CAD

Clinical Value
Ease of Use
Integration
Support & Docs
Value for Money

Press & Coverage

fda.gov
510(k) Premarket Notification for Lung-CAD
Imagen Technologies, Inc. received 510(k) premarket notification for its Lung-CAD device on October 3, 2023. The device is classified as a medical image analyzer with product code MYN.
2023-10
innolitics.com
Lung-CAD differs from Chest-CAD in that Lung-CAD
Imagen Technologies, Inc. has received FDA clearance for Lung-CAD, which is distinct from their Chest-CAD product. Lung-CAD is a computer-aided detection (CADe) software device.
2023-10
fda.report
IMAGEN TECHNOLOGIES, INC. FDA Filings
Imagen Technologies, Inc. has multiple FDA filings, including for Lung-CAD, with decision dates in October 2023 and September 2023. They also have clearances for Aorta-CAD and FractureDetect (FX).
2023-10
ajronline.org
AI applications for lung nodule detection on CT have been developed from the Lung Nodule Analysis Challenge using the publicly available Lung Image Database Consortium Image Database Resource Initiative (LIDC-IDRI) data-set
AI has been applied to pulmonary nodule detection since the 1980s, with modern AI solutions generally performing better at detecting solid nodules than subsolid and ground-glass nodules.
2022-05
nih.gov
AI and ML are increasingly reshaping lung infectious disease diagnosis with increased speed, accuracy, and accessibility.
AI and machine learning are significantly impacting lung infectious disease diagnosis by evaluating medical imaging data like chest X-rays and CT scans to identify conditions such as tuberculosis, pneumonia, and COVID-19.
2024-03
itnonline.com
Fully Integrated Lung CAD Solution | Imaging Technology News
The next-generation Vitrea solution integrates ImageChecker CT Lung CAD software to improve the detection of solid lung nodules during MSCT exams, enhancing workflow efficiency and including features like automatic nodule detection and temporal comparison.
2006-06
auntminnie.com
Lung CAD shows limited sensitivity gains, finds nodules radiologists missed
Studies presented at RSNA highlighted the clinical utility and limitations of computer-aided detection (CAD) for finding significant lung nodules with CT, showing incremental gains in sensitivity but also suggesting radiologists may search less diligently when CAD is used concurrently.
2005-12
radiologybusiness.com
Lung CAD: A Power Tool in the Imaging Toolset
Lung CAD has made steady progress, aiding imaging, decreasing false negatives, and reducing missed actionable nodules by 26%, according to Dr. David Naidich, who uses Siemens' syngo Lung CAD.
2007-11

Videos

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

View all on YouTube

Frequently Asked Questions

Lung-CAD aids physicians in oncology by improving early detection, optimizing treatment decisions, and personalizing care for lung cancer patients. It offers high-accuracy nodule detection and risk assessment, helping to minimize unnecessary biopsies and distinguish between benign and malignant nodules. Additionally, AI-driven algorithms assist oncologists in predicting treatment response, refining therapy selection, and optimizing radiation dose planning and tumor delineation.
While the specific regulatory status of Imagen's Lung-CAD is not detailed, AI-based CAD systems for lung nodule detection have received FDA approval. However, there is ongoing discussion regarding the need for robust clinical validation and external validation of these systems to ensure reliability and generalizability across diverse patient populations and clinical settings. Compliance also involves addressing concerns like algorithmic bias and data privacy.
Several other AI-powered CAD systems are available for lung cancer screening and diagnosis. These include products like Siemens AI-Rad Companion Chest CT, Aview LCS, and Optellum's Virtual Nodule Clinic. Other FDA-approved CAD applications for lung nodule detection have also been developed by companies such as Riverain Technologies and Medicsight.
Pricing for AI-based CAD systems can vary, with models including pay-per-case or one-time investments. Studies suggest that for deep learning CAD to be cost-effective, it must be priced substantially below €6 in a pay-per-case setting or used in high-workload environments. The cost-effectiveness can also depend on whether the software improves reporting workflow and increases reporting efficiency, potentially providing a business case for its integration.
Despite its promise, Lung-CAD technology has several limitations. These include high false positive rates, which can lead to image overload and unnecessary follow-ups, and challenges in differentiating between vessels and nodules. Some AI systems may also have limitations in detecting ground-glass opacities and may not perform as well in hilar areas or lower lung fields. Additionally, AI should complement, not replace, clinical judgment, and issues like algorithmic bias and data privacy remain concerns.

Related Tools

SOPHiA DDM
SOPHiA GENETICS
Oncology AI
SOPHiA DDM™ is an AI-driven and cloud-powered platform that helps clinicians generate real-time, actionable insights for patients with cancer and rare disorders by analyzing complex genomic, radiomic, and multimodal data.
Paid
CerviCARE AI
NTL Healthcare
OB/GYN AI
CerviCARE AI is an AI-powered cervical cancer screening system that analyzes smartphone images of the cervix to predict findings, aiming for early detection.
Lumonus AI
Lumonus
Clinical Decision Support & Reference
Lumonus AI is an AI-powered software that assists healthcare providers with prescriptions, dosing, and treatment for cancer patients, with a module (Sigma) that suggests treatment protocols based on prior plans for similar patients.
DeepBio DeepDx® Prostate
DeepBio
Oncology AI
DeepDx® Prostate leverages deep learning to standardize prostate cancer diagnostics by detecting abnormalities in digital slides with high precision, providing automated Gleason grading, tumor quantification, and tumor length measurements.
AIRA Matrix AI Solutions
AIRA Matrix
Lab & Diagnostics
AIRA Matrix offers AI solutions to improve efficiency and diagnostic accuracy in pathology lab workflows, primarily for prostate and breast cancer, with services like DPaaS and predictive toxicology.
Surgical Reality Viewer
Surgical Reality
Oncology AI
Surgical Reality offers CE- and FDA-certified AI-powered 3D medical imaging and surgical planning software that transforms CT scans into patient-specific 3D models for thoracic surgery, enhancing precision in complex lung procedures.

See all Oncology AI tools →

More from Imagen Technologies

Aorta-CAD
Imagen Technologies
Cardiology AI
Aorta-CAD by Imagen Technologies is an FDA-cleared, cloud-based AI software that assists physicians in detecting signs of Aortic Atherosclerosis and Aortic Ectasia on chest X-rays, integrating seamlessly into existing workflows.
Chest-CAD
Imagen Technologies
Clinical Decision Support & Reference
Chest-CAD by Imagen Technologies is an FDA-cleared AI software that detects, categorizes, and localizes suspicious regions on adult chest X-rays, shown to reduce diagnostic errors by 40%.
FractureDetect (FX)
Imagen Technologies
Radiology & Imaging AI
FractureDetect (FX) by Imagen Technologies is an FDA-cleared AI-powered computer-assisted detection and diagnosis (CAD) software device designed to assist clinicians in detecting hard-to-spot fractures on musculoskeletal radiographs in adults, thereby improving diagnostic accuracy and reducing missed fractures.
Contact for pricing
Imagen OsteoDetect
Imagen Technologies
Clinical Decision Support & Reference
Imagen OsteoDetect is an FDA-cleared AI-driven software that assists clinicians in detecting distal radius fractures on adult wrist X-rays, enhancing diagnostic accuracy and speed.

View company profile →

Suggest an Edit → | Report an issue | Last Verified: 2026-04-18 | First Added: 2026-04-18
AI Tool Finder
AI-powered search. Results may not be comprehensive.