AI-Rad Companion (Pulmonary)

by Siemens Healthineers  · Based in Germany → — AI-powered augmented workflows for precise pulmonary imaging analysis.
Oncology Pulmonology Radiology
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Regulatory Status Disclosed

Overview

The AI-Rad Companion (Pulmonary) is an advanced image processing software developed by Siemens Healthineers, designed to provide quantitative and qualitative analysis from previously acquired Computed Tomography (CT) DICOM images. It leverages machine learning and deep learning algorithms to support radiologists and physicians in emergency medicine, specialty care, urgent care, and general practice in the evaluation and assessment of lung diseases. The tool aims to enhance diagnostic precision and speed up workflows by automating routine, repetitive tasks with high case volumes. It integrates seamlessly into the image interpretation workflow, providing automated measurements and DICOM structured reports, while allowing clinicians to maintain control over every step for evidence-based decisions. The AI-Rad Companion (Pulmonary) is part of a broader family of AI-powered solutions deployed via the secure teamplay digital health platform.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Quantitative and qualitative analysis of CT DICOM images
  • Automatic lung lobe segmentation and measurements
  • Detection and highlighting of lung nodules (solid and sub-solid)
  • Pulmonary density quantification and opacity scoring
  • Detection of pulmonary lesions, atelectasis, pneumothorax, consolidation, and pleural effusion
  • Automated generation of DICOM Structured Reports and secondary capture objects
  • Seamless integration into PACS and reading workflows
  • AI-powered algorithms for automatic post-processing
  • Comparison of volumes to normative databases (for relevant metrics)
  • Workflow automation to reduce repetitive tasks and increase efficiency

Use Cases

  • Diagnostic aid for radiologists in interpreting pulmonary CT images
  • Evaluation and assessment of various lung diseases
  • Lung cancer screening and nodule detection
  • Pneumonia analysis, including ground-glass opacities and consolidations
  • Opportunistic screening for other conditions (e.g., osteoporosis via Chest CT)
  • Reducing radiologist workload and increasing diagnostic precision

What Physicians Need to Know

DICOM Support & Standards
AI-Rad Companion (Pulmonary) supports the DICOM format and conforms to the DICOM 2016a Standard. It outputs DICOM GSPS, DICOM SC, and DICOM SR (TID 5000 format) for Chest X-ray, and generates standardized, reproducible, and quantitative reports in DICOM SC format for Chest CT.
PACS Integration Method
The tool integrates into standard reading environments (PACS) and can be deployed via an AI marketplace, distribution platform, or as a stand-alone web-based solution. It is a hybrid solution. Results, including DICOM structured reports, can be accessed by radiologists on the PACS. The AI-Rad Companion with Notifier allows review of AI results independent of PACS limitations, and the level of automation for sending datasets to PACS is configurable. It is deployed via the teamplay digital health platform.
Reading Room Workflow Impact
AI-Rad Companion (Pulmonary) is designed to reduce the burden of repetitive tasks, potentially increasing diagnostic precision and speeding up workflows through automatic post-processing. It automatically highlights abnormalities, segments anatomies, and generates standardized, quantitative reports. It acts as a diagnostic aid, intended for concurrent use with original images before a final determination is made, and is not meant to replace the professional review by a qualified medical professional.
AI Model Architecture
The tool utilizes machine learning and deep learning algorithms. These algorithms were trained on extensive datasets and annotated by qualified clinical specialists to detect and characterize various findings in the lung and pleura, indicating their probability with confidence scores.
FDA Clearance Pathway
AI-Rad Companion (Pulmonary) has received FDA clearance via the Traditional 510(k) pathway. The latest version, VA40, is an enhancement to a previously cleared device (K213713).
Supported Modalities
AI-Rad Companion (Pulmonary) specifically provides quantitative and qualitative analysis from previously acquired Computed Tomography (CT) DICOM images. The broader AI-Rad Companion family supports MRI, CT, and X-ray datasets.
Sensitivity & Specificity Data
For the lesion follow-up feature in AI-Rad Companion (Pulmonary) (CT), a non-clinical bench test showed a sensitivity of 94.3% and an average Positive Predictive Value (PPV) of 99.1%. For the related AI-Rad Companion Chest X-ray, studies indicate superior AI sensitivity for lung lesions (85.5% vs. 35.5% for readers), pleural effusion (95.7% vs. 83.4%), pneumothorax (78.7% vs. 30%), consolidations (0.88 vs. 0.78), and atelectasis (0.54 vs. 0.43), often with high Negative Predictive Values (NPVs), though sometimes accompanied by higher false-detection rates.
RSNA/ACR Validation
AI-Rad Companion Chest CT was presented at the 2018 Radiological Society of North America (RSNA) annual meeting. The algorithms are trained on extensive datasets and annotated by qualified clinical specialists. The Chest CT module also supports the detection of nine anatomical landmarks as identified by American Heart Association (AHA) guidelines.
Physician Tip

AI-Rad Companion (Pulmonary) serves as an intelligent assistant, automating routine tasks like lesion detection, segmentation, and quantitative analysis from CT images. It's crucial to use it as a diagnostic aid, concurrently reviewing AI results with original images to enhance diagnostic precision and efficiency, rather than as a standalone diagnostic tool. Leverage its structured reporting capabilities to streamline documentation and focus on complex cases. Be aware that while it offers high sensitivity for various findings, it may also present higher false-detection rates in some instances, emphasizing the need for expert radiologist review. The high Negative Predictive Values (NPVs) can boost confidence in ruling out certain pathologies.

The AI-Rad Companion platform is designed for seamless integration into existing clinical workflows and PACS via the teamplay digital health platform. It supports DICOM standards for input and output, including structured reports and image annotations. The system's cloud-based architecture facilitates regular updates and integration of new features. The configurable level of automation for sending data to PACS and the 'Notifier' feature provide flexibility for integration into diverse IT environments and reading preferences.

Details

Category Radiology & Imaging AI
Pricing Contact for pricing — Not publicly available; quote directly from manufacturer.
DeploymentCloud-based (teamplay digital health platform) with optional Edge (on-premises) deployment
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status Yes AI-estimated

AI-Rad Companion (Pulmonary) (K233753) is FDA-cleared as image processing software for quantitative and qualitative analysis of CT DICOM images to support clinicians in evaluating lung diseases. It was cleared on March 21, 2024, as an enhancement to a previously cleared device.
Integrations
EHR Not specified
Specialties Oncology, Pulmonology, Radiology

What the Web Says

AI-Rad Companion (Pulmonary) by Siemens Healthineers is generally viewed as a valuable tool for radiologists, primarily praised for its ability to automate measurements and provide quantitative analysis of lung structures. It aims to improve efficiency and consistency in reporting, particularly for follow-up studies and complex cases, though some users note a learning curve and integration challenges.

Overall: Positive

Strengths

  • Automates quantitative analysis of lung nodules and other structures, saving time.
  • Enhances consistency and standardization in reporting, especially for follow-up studies.
  • Provides objective measurements that can aid in clinical decision-making.
  • Integrates with existing PACS systems, streamlining workflow for some users.
  • Potential to reduce inter-reader variability and improve diagnostic accuracy.
  • Useful for detecting subtle changes over time in chronic lung conditions.

Limitations

  • Initial setup and integration with existing IT infrastructure can be complex and time-consuming.
  • Requires a learning curve for radiologists to fully utilize its features and trust its outputs.
  • May not be suitable for all types of pulmonary cases or all clinical settings.
  • Cost can be a barrier for smaller institutions or those with limited budgets.
  • Reliance on AI might lead to over-reliance or a decrease in critical human review if not used judiciously.
  • Some users report occasional discrepancies or 'false positives' that require manual verification.

Based on reviews from: Siemens Healthineers official site, Radiology forums and journals (e.g., AuntMinnie.com, European Society of Radiology), Healthcare IT publications, Physician reviews and testimonials (e.g., LinkedIn, professional networks), Reddit discussions (r/radiology, r/healthcareit), G2 (limited specific reviews for this product, general AI in radiology trends)

Last updated: 2026-07-19

Ratings & Reviews

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Press & Coverage

X-ray Interpreter
AI-Rad Companion (Pulmonary) | FDA Radiology AI Device - X-ray Interpreter
AI-Rad Companion (Pulmonary) by Siemens Healthcare GmbH received FDA approval on March 21, 2024, as software utilizing machine learning and deep learning to analyze chest CT scans. It assists radiologists in segmenting lungs and lung lobes, identifying and measuring lung nodules, and tracking changes over time to improve diagnostic accuracy and workflow efficiency.
2024-03
Health AI Register
AI-Rad Companion Chest CT - Siemens Healthineers - Health AI Register
Reviewed on May 11, 2026, the AI-Rad Companion Chest CT solution from Siemens Healthineers offers a multiorgan approach with pulmonary, cardiovascular, and musculoskeletal functionalities. It is CE and FDA certified, assisting physicians in evaluating the lung by detecting and measuring lung lesions and segmenting lung lobes.
2026-05
accessdata.fda.gov
K233753 - Kira Morales - accessdata.fda.gov
This FDA 510(k) premarket notification from March 21, 2024, details the AI-Rad Companion (Pulmonary) software (SW version VA40) by Siemens Medical Solutions USA, Inc. It provides quantitative and qualitative analysis from CT DICOM images to support clinicians in evaluating lung diseases, building on the AI-Rad Companion Engine and teamplay digital platform.
2024-03
unknown
From X-Rays to AI: Navigating US Regulations in Radiological Health
Published in June 2023, this article discusses US regulations in radiological health, citing AI-Rad Companion (Pulmonary) as an example of an FDA-cleared image processing device. It highlights the software's role in providing quantitative and qualitative analysis from CT DICOM images for lung disease assessment.
2023-06
unknown
Artificial Intelligence u2013 Revolutionizing the Healthcare Industry
An October 2023 article highlights AI-Rad Companion (Pulmonary) as an AI-powered, augmented, image-based clinical decision-making procedure by Siemens Healthineers. It helps radiologists with image interpretation and treatment planning by automatically analyzing CT, MR, or X-ray images.
2023-10
Scribd
AI-Rad Companion Chest CT Overview | PDF | Aorta - Scribd
This whitepaper from Siemens Healthcare GmbH in 2021 provides an overview of AI-Rad Companion Chest CT, which includes the Pulmonary component. It details the detection and segmentation of lung nodules, analysis of lung parenchyma, and the system's vendor-neutral capability to evaluate image data from any CT system.
2021-XX
BMJ Health & Care Informatics
How machine learning is embedded to support clinician decision making: an analysis of FDA-approved medical devices | BMJ Health & Care Informatics
An article published in April 2021 analyzes FDA-approved medical devices utilizing machine learning, listing AI-Rad Companion (Pulmonary) by Siemens Medical Solutions USA, Inc. as a 510(k) Premarket Notification device from 2019. It highlights how such devices assist with diagnostic tasks like disease detection and assessment.
2021-04
PMC
Progress and challenges of artificial intelligence in lung cancer clinical translation - PMC
A July 2025 review discusses the transformative impact of AI in lung cancer management, mentioning Siemens AI-Rad Companion (Pulmonary) as a CT-based tool for segmentation of lung lesions, liver, and lymph nodes. It emphasizes AI's potential in screening, diagnosis, prognosis, treatment, and monitoring.
2025-07

Videos

Product demos, reviews, and walkthroughs for AI-Rad Companion (Pulmonary).

View all on YouTube

Frequently Asked Questions

AI-Rad Companion (Pulmonary) seamlessly integrates into the image interpretation workflow by automatically post-processing CT datasets to detect and highlight lung nodules, segment lung lobes, and quantify hyperdense areas. This automation aims to reduce repetitive tasks, potentially increasing diagnostic precision and supporting radiologists by acting as a first or second reader in clinical decision-making.
AI-Rad Companion (Pulmonary) has received FDA clearance (e.g., K183271, K213713, VA40) and is CE-marked, classifying it as a Class II medical device. Key compliance considerations involve adhering to FDA guidance for software in medical devices and ensuring robust patient data privacy measures, especially given its cloud-based processing capabilities.
Yes, several companies offer alternative AI solutions for pulmonary imaging analysis. Prominent competitors include GE HealthCare, Koninklijke Philips N.V., Canon Medical Systems Corporation, Fujifilm Holdings Corporation, Lunit Inc., Qure.ai, Annalise.ai, Milvue, and Oxipit. These alternatives often focus on similar functionalities like lung nodule detection, quantification, and integration into existing radiology workflows.
While specific pricing for AI-Rad Companion (Pulmonary) is not publicly detailed, AI radiology solutions generally follow subscription-based, pay-per-use, or custom/tiered pricing models. Factors influencing overall cost include initial licensing fees, installation, integration with existing IT systems, staff training, required infrastructure, and ongoing maintenance and support.
AI-Rad Companion (Pulmonary) is intended as an adjunct tool and does not replace the need for a qualified medical professional to review original images for all suspected pathologies. It is designed to detect prespecified radiographic findings, meaning it may have limitations in identifying other pathologies or subtle findings. Studies on similar AI-Rad Companion modules have indicated that while AI can offer high sensitivity for certain findings, this might be accompanied by a higher false discovery rate.
AI-Rad Companion (Pulmonary) operates on the teamplay digital health platform, which incorporates 'privacy by design and by default' principles. Patient data is de-identified or pseudonymized during the upload process, and institutions can select various privacy levels to control the extent of patient-related data uploaded. All external communications with the platform are secured using Transport Layer Security (TLS) protocol V1.2.

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Suggest an Edit → | Last Verified: 2026-04-19 | First Added: 2026-04-19
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