Introducing the New ACR AICentral.org: Improving Transparency & Product Information in the Imaging AI Marketplace

Our new American College of Radiology (ACR) Data Science Institute® (DSI) AICentral.org programs — Transparent-AI and AI Central PRO — empower Radiologists and practices to access increasingly transparent AI product information and make better informed AI purchases. AICentral.org enables facilities to select algorithm candidates that may work best for their patients: enhanced knowledge about how an algorithm was trained and what it was trained to do allows users to match characteristics of their patients to commercially available models.

Since its inception in 2018, the AICentral.org directory has evolved from an online listing of FDA-cleared Imaging AI products to the most up-to-date, complete and interactively searchable directory of commercial Imaging AI products in the United States.  

The new AICentral.org updates represent the College’s enduring effort to enhance informed decision making in an ever-growing imaging AI marketplace through a regularly updated online resource. It is available to ACR members but also to non-members, the latter can simply create a profile before proceeding to the content. This updated directory drives access to comprehensive information about FDA-cleared AI imaging products by combining objective data about models, including manufacturer’s instruction for use (Transparent-AI) and branded product information (AI Central PRO) which facilitate convenient one-stop shopping insights for potential buyers and users.

Transparent-AI 

The ACR responded to a call from clinical end users and the FDA to help drive more transparency about commercially available Imaging AI algorithms. This is done by asking a series of factual questions of manufacturers about how the models were developed and how they were validated. Transparent-AI is composed of data elements manufacturers provide voluntarily and is designed to help end users have better informed discussions and selection criteria when making decisions about which algorithm might be most appropriate for their local target population. 

Manufacturers can choose to disclose detailed product information, including training data demographics and machine specifications. If they are unable to provide the information, or it does not exist, that will be noted on the site. 

The transparency content is posted on AICentral.org as it becomes available. It is important to note that the requests have only gone out recently, and the resulting information is being posted as it becomes available, a rolling process over time. Data obtained fall within the following general categories: Model Identification, Characteristics, Indications for Use, Performance, Training Details and Limitations. Examples of data elements include intended user, age range, scanner manufacturer and scanner models used in stand-alone performance. For the full list of data elements, check out the Transparent-AI Data Dictionary.

Manufacturers who participate in this program will receive the Transparent-AI badge on their product listing, allowing AICentral.org users to easily spot those already participating in the program. Access to this information is expected to drive identification of products that may work within local workflows, populations and equipment environments. Importantly, ACR is soliciting and including the so-called “instructions for use” (IFU), a software labeling document required of manufacturers by FDA that specifies use case, specific function and user interfaces, as well as standalone performance testing data for each product. Not infrequently, the IFU has been received and filed by those tasked with AI implementation in a given institution, often members of the informatics team. As a result, this important information may not have reached clinical end users. By posting the IFUs on AICentral.org, ACR is working with manufacturers to facilitate access to this information to both users and (not yet)-users of their models. 

Several manufacturers committed to the process before its launch at RSNA, including: 

  • GE HealthCare  
  • Siemens Healthineers  
  • Whiterabbit.ai  
  • Therapixel  
  • Aidoc  
  • AIRS Medical  
  • Cortechs.ai 

AI Central PRO 

AI Central PRO further bridges the knowledge gap by offering AI imaging manufacturers the ability to post their own, branded product information to the directory, including explanations of product use and value, images of their products in use and their contact information. Supplemental information about products by manufacturers participating in the PRO program will make it easier to understand how they can best support unique patients and workflows. The product specific marketing materials round out the one stop shopping experience on AiCentral.org as they represent an important source of information about products. This streamlines the experience for front line users who no longer have to visit many separate websites to find the corresponding information. 

The Future of AI Central  

AICentral.org is a long-term commitment by the ACR to help promote our collective understanding of the evolving AI marketplace. The new content and function expansions will help our members gain a better understanding of the available commercial offerings while increasing product transparency in the imaging AI marketplace — but it’s only the beginning. 

A few of the ways we plan to expand these goals in the future include:  

  • Representation of Imaging Ai platform companies, their portfolios and value-add functionality. 
  • Expanding categories such as software in a medical device (SiMD), and non-interpretive Ai in addition to FDA cleared SaMD.  
  • Functionality for ACR members to comment and provide insight on products they are using, with appropriate information provided back to the manufacturers.  
  • Include other products critical to AI operations such as AI orchestration vendors.  

If you would like to learn more about AICentral.org and our new programs, please visit our website.

Christoph Wald, MD, PhD, MBA, FACR | Chair, ACR Commission on Informatics | Chair, Radiology, Lahey Hosptial & Medical Center | Burlington, MA

Introducing the New ACR AICentral.org: Improving Transparency & Product Information in the Imaging AI Marketplace

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