Lung Density Analysis

by IMBIO  · Based in United States → — AI-powered medical imaging analysis for personalized lung and cardiothoracic care.
Pulmonology Radiology

Contact for pricing
Regulatory Status Disclosed

Overview

IMBIO’s Lung Density Analysis is an AI-driven medical imaging software designed to provide quantitative analysis and 3D visualization of lung conditions from CT scans. The tool, which includes both an Inspiration (LDAi) and Functional (LDAf) assessment, helps physicians better understand and quantify components of chronic obstructive pulmonary disease (COPD), emphysema, air-trapping, asthma, and bronchiolitis obliterans syndrome (BOS).

The software transforms standard medical images into rich visual maps and detailed quantitative reports, enabling data-driven, personalized patient care from screening and diagnosis through procedure planning and therapy tracking. It is fully automated, integrating into existing workflows to receive image series and return results directly into the patient study in minutes, without requiring stand-alone workstations or extensive user interfaces.

Key features include automated detection of low attenuation areas, noise reduction technology for low-dose scans, and patient-centered LungMap™ reports to aid smoking cessation counseling. The Functional LDA, utilizing paired inspiratory/expiratory CT scans, offers comprehensive mapping of normal lung, air-trapping, and emphysema, providing detailed quantitative data by lung regions and volumes.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Automated detection, visualization, and quantification of emphysema
  • Validated for low-dose CT scans in lung cancer screening
  • Patient-centered LungMapu2122 report for smoking cessation counseling
  • Fully automated quantitative analysis and 3D visualization to PACS
  • Imbio Noise Reduction Technology (NRT) for low dose scans
  • Mapping of normal lung, air-trapping, and emphysema (Functional LDA)
  • Advanced density analysis for COPD, Asthma, BOS
  • Quantitative reports with coronal, axial, sagittal visuals and bar charts
  • Detailed quantitative data by lung regions and volumes
  • Integration into standard reading environments (PACS)

Use Cases

  • Lung cancer screening programs (emphysema quantification)
  • Assessment and management of COPD and emphysema
  • Diagnosis and assessment of Asthma, Bronchiolitis Obliterans Syndrome (BOS)
  • Personalized care decisions and surgical/interventional procedure planning
  • Smoking cessation counseling
  • Quantification of airspace disease severity and extent (e.g., for COVID-19 or pneumonia)

What Physicians Need to Know

Cardiac CT/MRI Analysis
While Lung Density Analysis focuses on pulmonary tissue from CT scans, Imbio, as a company, offers other AI algorithms for cardiothoracic imaging diagnostics, including RV/LV Analysis for pulmonary embolism and Coronary Artery Calcification (CAC) analysis, which can be performed on CT scans.
Coronary Artery Assessment
Imbio offers a separate Coronary Artery Calcification (CAC) analysis tool that quantifies calcium build-up in heart arteries from CT scans, including low-dose CTs used for lung cancer screening. This is distinct from Lung Density Analysis but part of Imbio's broader offerings in cardiothoracic imaging.
AHA/ACC Guideline Alignment
No specific mention of direct alignment with AHA/ACC guidelines for Lung Density Analysis, which focuses on pulmonary imaging. However, Imbio's CAC analysis would align with guidelines for cardiovascular risk assessment.
Real-Time Alert Capability
Lung Density Analysis provides automated quantitative analysis and reports from CT images, rather than real-time alerts for acute cardiac events.
Physician Tip

Imbio's Lung Density Analysis (LDA) is a valuable tool for detailed quantification and visualization of pulmonary conditions such as COPD, emphysema, air-trapping, and other density abnormalities from CT scans. It provides objective data that can aid in diagnosis, personalized treatment planning, and monitoring disease progression, especially when pulmonary function tests are inconclusive. While primarily a lung tool, the comprehensive nature of chest CTs means that clinicians should be aware of Imbio's other AI solutions, like Coronary Artery Calcification (CAC) analysis and RV/LV analysis, which can offer additional cardiac insights from the same imaging studies, contributing to a more holistic patient assessment.

Imbio's Lung Density Analysis is designed for seamless integration into existing radiology workflows. It is integrated with platforms such as the Nuance AI Marketplace and PowerShare Network, allowing for automated processing and inclusion of analysis results directly into radiology reports. It also integrates with the GE Health Cloud ecosystem for streamlined processing and delivery of quantitative insights.

Details

Category Cardiology AI, Radiology & Imaging AI
Pricing Contact for pricing — Not publicly disclosed.
DeploymentCloud-based, Locally virtualized (VM, Docker), Integration in PACS, AI marketplace/distribution platforms, Stand-alone web-based.
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status 1 AI-estimated

The Imbio CT Lung Density Analysis Software (K141069, cleared 09/17/2014) provides reproducible CT values for pulmonary tissue, essential for quantitative support in diagnosis and follow-up examinations, and aids physicians in documenting pulmonary tissue images from CT thoracic datasets.

Integrations
EHR Not specified
Specialties Pulmonology, Radiology

What the Web Says

Imbio's Lung Density Analysis (LDA) is a medical imaging software that provides automated quantification and visualization of lung conditions like emphysema and COPD from CT scans. It's designed to offer more precise and personalized insights beyond traditional methods, aiding in diagnosis, treatment planning, and patient communication. The technology has received FDA 510(k) clearance, CE Mark certification, and Health Canada approval, and has been validated by multiple studies.

Overall: Positive

Strengths

  • Provides rapid, automated quantification and visualization of emphysema and COPD.
  • Offers more precise and personalized insights for diagnosis and treatment planning.
  • Facilitates meaningful conversations with patients by providing clear visual maps and quantitative reports.
  • Integrates into existing clinical workflows (e.g., PACS and GE Health Cloud) for streamlined processing.
  • Validated for use with low-dose CT scans, making it suitable for lung cancer screening programs.
  • Includes a patient-centered LungMapu2122 report to assist with smoking cessation counseling.

Limitations

  • While increasingly used in research and clinical settings, consistent adoption for diagnostic work-up and treatment planning is still evolving.
  • Some products are for research use only in regions without regulatory clearance for clinical use.
  • No specific negative reviews or opinions from physicians, healthcare IT, tech reviewers, Reddit, G2, or Capterra were found in the search results.

Based on reviews from: Radiology, Imbio (via 4DMedical), Becker's Hospital Review, PMC (PubMed Central), Blackford Analysis, Health AI Register, FDA

Last updated: 2026-07-21

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Press & Coverage

Healthcare Business News
4D Medical to acquire AI developer Imbio, expanding lung CT analytics capabilities
4D Medical is acquiring Imbio, an AI algorithm developer, for up to $45 million to expand its CT analytics capabilities for assessing regional airflow and other functional lung characteristics. This acquisition will combine their technologies to provide more comprehensive cardiothoracic insights from standard chest CT scans.
2023-12
Imbio (via PRNewswire)
Imbio to be Acquired by 4DMedical Creating Comprehensive Cardiothoracic Image Analysis Portfolio
Imbio, a provider of medical imaging analysis technologies, has entered into an agreement to be acquired by 4DMedical, aiming to create a leading lung imaging AI suite. The combined offering will provide functional, structural, and risk-based analysis for both lung and heart disease from standard chest CTs.
2023-12
PMC (National Library of Medicine)
CT-Based Commercial Software Applications: Improving Patient Care Through Accurate COPD Subtyping
This article discusses Imbio's Lung Density Analysis (LDA) software, highlighting its use of parametric response mapping (PRM) to identify key functional information from CT scans in COPD patients, including healthy lung, air trapping, and emphysema. It notes that PRM is the only technique histologically validated to date for assessing small airway disease.
2022-04
Imbio (via PRNewswire)
Imbio and Riverain Technologies Partner to Offer a Comprehensive AI-Powered Lung Health Solution
Imbio and Riverain Technologies announced a partnership to deliver a more complete lung health solution by combining their FDA-cleared AI tools. Imbio's patented Functional Lung Density Analysisu2122 (LDAf) and Lung Density Analysis Inspiration (LDAi) algorithms provide detailed mapping and quantification of COPD components and emphysema.
2021-05
Imbio (via PRNewswire)
Imbio Partners with Siemens Healthineers to Deliver Image Analysis Tools to Clinicians Across the Globe
Imbio and Siemens Healthineers partnered to expand global access to Imbio's AI algorithms, allowing physicians to apply automated AI for quantitative image analysis directly through Siemens' syngo.via platform. This collaboration aims to provide easily accessible and cost-effective imaging AI applications for personalized patient care.
2020-10
Imbio
Imbio lung AI models support lung disease diagnosis and care via Nuance AI Marketplace
Imbio's FDA-cleared Lung Density Analysis (LDA) was integrated into PowerScribe radiology reporting workflows via the Nuance AI Marketplace, connecting to over 7,500 healthcare facilities in the U.S. This integration supports the diagnosis and care of conditions like COPD and emphysema, and aids lung cancer screening and smoking cessation programs.
2020-06
Imbio
Imbio And NTT DATA Services Announce Partnership For Lung Analytic Algorithms In The UCA Imaging Platform
Imbio partnered with NTT DATA Services to provide lung analytic algorithms within the UCA Imaging Platform, enhancing automated tools for identifying and quantifying lung disease in imaging studies. This collaboration aims to accelerate the availability and scalability of lung analysis tools in the cloud.
2017-08
Imbio (via PRNewswire)
Imbio and GE Healthcare Collaborate to Enable Lung Density Analysisu2122 Within GE Health Cloud Ecosystem
Imbio and GE Healthcare announced a collaboration to integrate Imbio's FDA-cleared and CE-marked Lung Density Analysis (LDA) software into the GE Health Cloud's clinical workflow. This integration will provide streamlined processing for quantifying and localizing areas of low lung density and air trapping.
2016-03

Videos

Product demos, reviews, and walkthroughs for Lung Density Analysis.

View all on YouTube

Frequently Asked Questions

AI-powered lung density analysis solutions are designed for seamless integration into existing radiology reporting workflows, such as PACS and dictation systems like PowerScribe. They automate quantitative analysis, provide 3D visualizations like heatmaps, and generate structured reports, aiming to enhance diagnostic efficiency and provide more personalized patient insights without adding significant burden to the clinician.
AI software for lung density analysis typically requires regulatory clearances such as FDA 510(k) in the US and CE Mark in Europe, with some products already obtaining these. Data privacy, particularly under regulations like HIPAA, is a critical concern, necessitating that companies plan for secondary data use for AI model training by explicitly including these provisions in original research protocols, consent forms, and IRB submissions.
Non-AI methods for lung density analysis primarily involve manual or semi-manual interpretation and visual estimation by trained radiologists, sometimes aided by basic computer-based tools. AI solutions offer significant advantages in automation, providing faster and more precise quantitative measurements of lung tissue, and have shown promise in enhancing accuracy and efficiency compared to traditional approaches, particularly in complex tasks like volumetric histogram analysis and segmentation.
The cost structure for AI lung density analysis solutions can vary, often including subscription-based, per-scan, value-based, or enterprise licensing models, with annual licensing for CT AI solutions potentially ranging from $75,000 to $150,000. Healthcare institutions should consider ROI based on factors like improved clinical efficiency, reduced callbacks, enhanced diagnostic accuracy, and the potential for earlier disease detection to lower overall treatment costs, alongside integration and maintenance expenses.
Recognized limitations include potential biases inherited from the training data, which can lead to skewed performance across diverse patient populations, such as differences based on race, ethnicity, or gender. Other sources of error include limited generalizability to varied clinical settings, difficulties in detecting subtle early-stage lesions, and the risk of automation bias where clinicians may over-rely on AI outputs without critical review.
AI models for lung density analysis are typically validated through retrospective studies comparing their performance against ground truth established by expert radiologists or clinical outcomes, using metrics like sensitivity, specificity, accuracy, and Area Under the Curve (AUC). Stronger evidence is encouraged through multi-site evaluations and prospective studies, with some AI models demonstrating accuracy that matches or even surpasses human readers in specific diagnostic tasks.
While AI tools aim for seamless integration, effective utilization by physicians and support staff requires specific training. This training typically covers how AI tools integrate into existing workflows, their intended use, strengths, and limitations, as well as relevant regulatory and ethical frameworks. Medical education programs are also evolving to incorporate AI methods for image interpretation and clinical decision support, fostering confidence and expertise in these new technologies.

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Suggest an Edit → | Last Verified: 2026-04-20 | First Added: 2026-04-20
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