Change Healthcare Anatomical AI

by Change Healthcare Canada Company  · Based in United States → — AI-powered anatomical intelligence for enhanced radiology workflows.
Radiology
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Not publicly available
Regulatory Status Disclosed

Overview

Change Healthcare Anatomical AI is a standalone image processing software application designed to analyze pixel data from CT or MR images. It generates comprehensive anatomic descriptors, which supplement traditional methods used for the selection, presentation, or analysis of image-based medical data. This AI tool is intended to enable physicians and other healthcare providers, as well as integrated healthcare systems, to rapidly identify images, series, and/or studies of interest. By automating the identification of body regions using image pixel data, it aims to remove barriers caused by inaccurate or incomplete metadata, thereby eliminating time spent on manual study searches and potentially reducing the ordering of unnecessary studies.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Analyzes pixel data from CT or MR images
  • Creates comprehensive anatomic descriptors
  • Supplements traditional image analysis methods
  • Rapidly identifies relevant images, series, and studies
  • Eliminates time spent on manual study searches
  • Helps reduce the ordering of unnecessary studies
  • Available in on-premise Change Healthcare Radiology Solutions (PACS)
  • Planned integration into Stratus Imaging cloud solution suite
  • Communicates via Application Programmable Interfaces (APIs)
  • Exports inference results, typically in JSON format

Use Cases

  • Improving radiology workflow efficiency
  • Streamlining study prioritization
  • Enhancing diagnostic confidence
  • Reducing manual image search times
  • Categorizing anatomy from patient images, series, or studies
  • Integration with existing Picture Archiving and Communication Systems (PACS) and Electronic Health Records (EHR)

What Physicians Need to Know

DICOM Support & Standards
Analyzes CT and MR DICOM images. Communicates via APIs for receiving DICOM images and returning inference results. Adheres to NEMA PS 3.1-3.20 (2016) u2013 Digital Imaging and Communications in Medicine (DICOM) set.
PACS Integration Method
Integrates with existing healthcare systems via Application Programmable Interfaces (APIs) for receiving DICOM images and returning inference results. Currently available with on-premise Change Healthcare Radiology Solutions (PACS) and planned for future releases in the Stratus Imaging cloud solution suite. Supports integration with third-party software (e.g., reporting tools, EMRs, advanced visualization tools) through APIs and standards like HL7 and DICOM.
Reading Room Workflow Impact
Works in parallel with the standard workflow, providing supplemental metadata without altering original images. Aims to improve efficiency by rapidly locating relevant studies, reducing manual search time, and potentially decreasing unnecessary studies. Helps prioritize urgent studies and ensures swift interpretations.
AI Model Architecture
Contains a machine learning-based (non-adaptive) AI algorithm that analyzes CT or MR image pixel data to generate anatomic descriptors. Models are trained by AI data scientists and expert clinicians and radiologists.
Processing Speed (per study)
Specific processing speed data (e.g., seconds per study) is not publicly available.
FDA Clearance Pathway
Cleared via the 510(k) pathway (K210719). Classified as a Class II device under 21 CFR 892.2050, product code QIH (Automated Radiological Image Processing Software).
Supported Modalities
Intended to analyze pixel data from CT and MR images.
Sensitivity & Specificity Data
Specific sensitivity and specificity data for this tool are not publicly available.
RSNA/ACR Validation
No specific RSNA/ACR validation data for this tool is publicly available. However, RSNA and ACR actively support and provide guidance on AI integration and validation in radiology.
Physician Tip

Leverage the anatomical descriptors generated by the AI to quickly identify images, series, and studies of interest, supplementing traditional reading methods. Utilize the AI to streamline your workflow by reducing the time spent on manual study searches, which can also help in prioritizing urgent cases. Remember that the AI operates in parallel with your standard workflow and does not alter the original medical images, providing valuable supplemental metadata for enhanced decision-making.

Change Healthcare Anatomical AI integrates with existing healthcare systems through Application Programmable Interfaces (APIs) for seamless DICOM image reception and results delivery in JSON format. It is currently available as part of Change Healthcare Radiology Solutions (PACS) for on-premise deployments and is slated for future integration into the Change Healthcare Stratus Imaging cloud solution suite. The system supports connectivity with various third-party software, including reporting tools, Electronic Medical Records (EMRs), and advanced visualization platforms, by adhering to industry standards such as HL7 and DICOM.

Details

Category Radiology & Imaging AI
Pricing Not publicly available — Enterprise solution; pricing typically customized based on deployment and scale.
DeploymentCurrently available on-premise within Change Healthcare Radiology Solutions (PACS); planned for cloud deployment in Stratus Imaging.
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status Yes AI-estimated

Change Healthcare Anatomical AI received 510(k) clearance (K210719) from the FDA on July 20, 2021. It is classified as a Class II medical device under Regulation Number 21 CFR 892.2050 (Medical image management and processing system) with Product Code QIH. The device is intended to analyze pixel data from CT or MR images to create comprehensive anatomic descriptors for export to integrated healthcare systems, aiding in the rapid identification of images, series, and/or studies of interest. It is not indicated for patients under the age of 18 years old.
Integrations
EHR Not specified
Specialties Radiology

What the Web Says

Change Healthcare Anatomical AI is a standalone image processing software designed to analyze CT and MR images to create comprehensive anatomical descriptors. It aims to supplement traditional methods for image analysis, enabling physicians and healthcare providers to rapidly identify images, series, and studies of interest. The application is intended to streamline processes and reduce administrative burdens by extracting diagnostic information from clinical narratives and radiology reports.

Overall: Mixed

Strengths

  • Analyzes pixel data from CT/MR images to create comprehensive anatomical descriptors.
  • Supplements traditional image analysis methods, allowing rapid identification of images/studies of interest.
  • Works in parallel with standard workflows and does not alter original medical images.
  • Can identify diagnostic information from unstructured clinical narratives and radiology reports, increasing efficiency of automated medical necessity reviews.
  • Reduces administrative burden for highly skilled clinical staff and case managers.
  • Offers a customizable user interface that integrates well with EHR systems.

Limitations

  • Not indicated for patients under 18 years old.
  • Change Healthcare (the parent company) has received feedback regarding poor customer support.
  • Challenges in configuration have been noted for Change Healthcare products, potentially hindering initial onboarding.
  • Some Reddit discussions about Change Healthcare (the parent company) mention concerns about a significant data breach and its impact on providers and cash flow.
  • General concerns about AI in healthcare include the potential for misdiagnosis, over-reliance leading to a weakening of doctors' skills, and the importance of human review to prevent bias.
  • The setup in defining parameters for Change Healthcare Data & Analytics Solutions can be cumbersome, and the usage of different file feeds can be difficult.

Based on reviews from: accessdata.fda.gov, G2, Imaging Technology News, Reddit, TIME, UC Davis Health, Medical Economics, Indeed.com, JMIR Preprints, MedCity Knowledge Hub, Capterra, rater8, Michigan Medicine, Healthcare IT Today, Health Tech Reviews, YouTube, PMC

Last updated: 2026-07-18

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Press & Coverage

IT Pro
Change Healthcare unveils its cloud-native medical imaging solution
Change Healthcare announced its cloud-native medical imaging solution, Change Healthcare Stratus Imaging PACS, which includes its FDA-approved Anatomical AI algorithm. The AI accurately outlines body parts via image pixels, addressing issues with inaccurate metadata.
2021-08
Nasdaq (Business Wire)
Change Healthcare Releases End-to-End, Cloud-Native Solution for Medical Imaging
Change Healthcare introduced Change Healthcare Stratus Imaging PACS, a new cloud software as a service (SaaS) solution for radiology practices, and highlighted its FDA-cleared Anatomical AI algorithm. This algorithm uses AI to identify body regions from image pixel data, improving workflow efficiency.
2021-08
Axis Imaging News
Six Tips for a Successful Cloud Imaging Migration in Radiology
This article discusses the benefits of cloud imaging migration in radiology, highlighting Change Healthcare Anatomical AI as a solution that uses machine learning to help radiologists locate the right images by identifying body regions from pixel data, thereby removing barriers from inaccurate metadata.
2023-06
accessdata.fda.gov
Change Healthcare Canada Company July 20, 2021 Chester Mccoy VP, QA/RA & Chief Quality Officer 10711 Cambie Road Richmon - accessdata.fda.gov
This FDA document details the 510(k) clearance for Change Healthcare Anatomical AI, stating its intended use is to analyze pixel data from CT or MR images to create comprehensive anatomic descriptors for export to integrated healthcare systems. It also notes the software is not indicated for patients under 18 years old.
2021-07
Orthogonal
SaMD Cleared by the FDA: The Ultimate Running List
Change Healthcare Anatomical AI is listed as an FDA-cleared Software as a Medical Device (SaMD) in the radiology category, with a clearance date of July 20, 2021.
2024-10
AJR Online
Opportunistic Screening on Chest CT, From the AJR Special Series on Screening
This medical journal article mentions Change Healthcare Anatomical AI (K210719, July 20, 2021) as an FDA-cleared AI algorithm for matching anatomic regions with images, categorized under Medical Image Management and Processing Systems (MIMPS).
2025-07
PMC (PubMed Central)
Practical applications of AI in body imaging - PMC
This peer-reviewed article discusses practical applications of AI in body imaging, citing Change Healthcare Anatomical AI as an FDA-cleared algorithm that provides functionality for identifying relevant prior studies and ensuring their availability during image interpretation.
2025-06
Innolitics
QIH u00b7 Automated Radiological Image Processing Software u2014 FDA Product Code | Innolitics
Change Healthcare Anatomical AI is listed under the FDA product code QIH for Automated Radiological Image Processing Software, with a clearance date of July 20, 2021.
unknown

Videos

Product demos, reviews, and walkthroughs for Change Healthcare Anatomical AI.

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Frequently Asked Questions

Change Healthcare Anatomical AI analyzes pixel data from CT and MR images to generate comprehensive anatomical descriptors, which are then exported to integrated healthcare systems. This technology helps physicians and other healthcare providers quickly identify images, series, and studies of interest, supplementing traditional methods for image analysis and improving diagnostic workflows.
Change Healthcare Anatomical AI adheres to cybersecurity requirements outlined by FDA Guidance for medical devices. As a physician, you are responsible for understanding that healthcare AI regulation is evolving, requiring continuous monitoring, robust data stewardship, and adherence to patient privacy laws like HIPAA. Organizations deploying AI must also establish clear governance policies and ensure transparency regarding AI use with patients.
Change Healthcare Anatomical AI is not indicated for patients under 18 years of age. General limitations of AI in healthcare include potential data bias, challenges with explainability in 'black-box' algorithms, and the inherent inability to provide emotional patient engagement.
While specific pricing for Change Healthcare Anatomical AI isn't publicly detailed, similar AI in medical imaging systems typically range from $200,000 to $800,000, encompassing specialized hardware, software integration, and regulatory approval. Overall AI implementation costs in healthcare can vary significantly, also including expenses for algorithm development, infrastructure, staff training, and ongoing maintenance.
Yes, for anatomical segmentation and analysis in medical imaging, several other platforms and tools exist. These include specialized medical image annotation tools like Encord, 3D Slicer, Labelbox, and Kili Technology, as well as broader AI platforms such as Google DeepMind's MedGemma, which focus on high-dimensional and longitudinal medical imaging.
Change Healthcare Anatomical AI is designed to comply with cybersecurity requirements, including those from FDA Guidance for medical devices, to protect data in use, in transit, and at rest. Ensuring patient data privacy and HIPAA compliance is critical for all healthcare AI, requiring robust data protection protocols, strict access controls, and secure business associate agreements with vendors.
Change Healthcare Anatomical AI is a standalone image processing software that communicates via Application Programmable Interfaces (APIs) to receive DICOM images and return inference results. While AI solutions aim to streamline operations, integrating new AI tools into entrenched legacy PACS and EHR systems can present significant barriers and may require careful planning, workflow redesign, and staff training.

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