Release of Use Cases Aims to Increase AI Adoption in Medical Imaging

Philips' Illumeo software showing a small tumor highlighted by the user, which the AI will use as a landmark to search all the patient's prior exams of this same area.

The American College of Radiology (ACR) Data Science Institute (DSI) announced the release of its first series of freely available standardized artificial intelligence (AI) use cases to increase the utilization of AI adoption in medical imaging. At present, the ACR DSI has use cases for breast imaging, cardiology, musculoskeletal, neurology, oncology, pediatrics and thoracic.

The use cases are designed to guarantee that algorithms are applied to address clinical questions, used across several different electronic workflow systems and allow for quality assessment measures and comply with legal, regulatory and ethical measures.

“The ACR DSI use cases present a pathway to help AI developers solve health care problems in a comprehensive way that turns concepts for AI solutions into safe and effective tools to help radiologists provide better care for our patients,” said ACR DSI Chief Medical Officer Bibb Allen Jr., MD, in a prepared statement.

Multispecialty, multi-industry expert panels determined which use cases would be utilized for the project. These cases give clinicians and researchers the tools to create and test the AI algorithms while monitoring their efficacy.

“The ACR DSI framework promotes standardization, interoperability, reportability and patient safety in radiological artificial intelligence development that can help usher in a new era of advanced medicine,” ACR DSI Chief Science Officer Keith J. Dreyer, DO, PhD, said in the same statement.

Here is an overview of the uses cases from the ACR website: Technically Oriented Use Cases for Healthcare-AI (TOUCH-AI) describe specific clinical scenarios in which an AI application adds value and suggest features to garner trust and endorsement from the community. Use cases define basic requirements to complete certain automation and nest within broader IT environments. In addition to guidance and standards for developers, this list indicates the applications the DSI supports with curated datasets codified according to TOUCH-AI specifications.

Building wide-scale health care AI requires access to robust structured data. The DSI is part of a global initiative to open access to data for AI development and is engaging institutions across the country on data access projects. These projects rest upon the foundation of the use case, and each use case spells out the conditions algorithms are expected to reliably execute.

For a given use case, the DSI develops validation models, some of which are part of ongoing demonstration projects with the FDA to support expedited approval processes for AI algorithms. Once in the field, the DSI leverages the ACR registry infrastructure connected to facilities across the country to provide analytics on algorithm performance, which can be used as real-world evidence or a basis for updates. All of these initiatives begin with scrupulously describing relevant algorithmic functions and clinical insights which ensure the application is effectively utilized.

Read the source article in Radiology Business.

View the use cases on the American College of Radiology website.