If it's the week following Thanksgiving, the Radiological Society of North America's annual meeting takes place at McCormick Place in Chicago. From December 1st to 5th, tens of thousands of imaging, IT, and informatics professionals from over 120 countries gather to get a close look at new hardware and software and learn about clinical innovations. Just like in healthcare everywhere else, artificial intelligence is revolutionizing the imaging profession, as evidenced by a new KLAS study.

KLAS Study Highlights in Imaging AI

The Imaging AI 2024 research report shows that the number of FDA-approved AI tools for imaging has surged to over 300 in just a few years, with no sign of the approvals slowing down. In 2018, only 17% of interviewed organizations were piloting or using an AI solution, but now over 50% of surveyed organizations are using AI algorithms for at least one imaging use case. This indicates the rapid pace of change in the imaging industry. 1: The regulatory landscape has played a significant role in this transformation. As it has changed, attitudes towards and adoption of new imaging AI platforms, operational and reporting automations, and other AI tools have also evolved. This has opened up new possibilities and challenges for imaging professionals. 2: To understand the various ways AI is changing the imaging and radiology landscape, KLAS researchers surveyed over 200 organizations. About 25% of them were imaging groups, and the rest were US health systems. This data provides valuable insights into the current state of AI in imaging.

Agfa's Integration with CARPL.ai

Agfa is showcasing its integration of CARPL.ai into the AGFA Healthcare Enterprise Imaging platform. This integration offers expanded flexibility and efficiency to radiologists. RUBEE for AI provides expanded access to CARPL's marketplace of 140 applications, creating a unified platform that helps providers manage the large-scale adoption of AI and harness its value across different clinical domains. 1: The combination of these technologies allows radiologists to work more efficiently and make more accurate diagnoses. It streamlines the imaging process and improves patient care. 2: By integrating CARPL.ai, Agfa is at the forefront of using AI to enhance imaging workflows and deliver better patient outcomes.

Aidoc's New CARE1 Foundation Model

Aidoc announced its new CARE1 foundation model for CT imaging, which stands for Clinical AI Reasoning Engine, Version 1. This is the first step in a multi-year investment in its CARE framework. Trained on millions of exams, the model helps advance precision and speed in clinical AI, minimizing diagnostic delays, optimizing workflows, and improving patient outcomes. 1: The development of this model is a significant milestone in the field of imaging AI. It shows how AI can be used to enhance the diagnostic process and provide more accurate results. 2: Aidoc's commitment to innovation in clinical AI is evident through the introduction of the CARE1 model, which has the potential to transform the way CT imaging is performed.

Fujifilm's New Imaging Systems

Fujifilm announced several new imaging systems at RSNA, including a 1.5T MRI system with AI-powered workflow enhancements, an open 0.4T MRI system, a next-generation ultrasound system with cognitive technology for deep tissue visualization, an all-in-one compact fluoroscopy C-arm, and two digital radiography suites. 1: These new systems incorporate advanced technologies that improve imaging quality and workflow efficiency. The AI-powered enhancements in the MRI system, for example, allow for faster and more accurate diagnoses. 2: Fujifilm's diverse range of new imaging systems demonstrates its commitment to innovation and providing imaging professionals with the tools they need to deliver the best patient care.

GE HealthCare's Pristina Via Mammography System

GE HealthCare is touting its new Pristina Via mammography system, designed to improve the screening experience for both patients and technologists. It offers imaging professionals a new suite of leading-edge tools that balance the demands of diagnostic accuracy and fast-paced workflows, facilitating more patient-centered breast care. 1: In a global shortage of technologists, this system could help streamline workflow efficiencies and ensure high-quality mammography screening. 2: GE HealthCare's focus on patient-centered care and workflow optimization is evident in the design of the Pristina Via mammography system.

Hyland's Cloud Imaging SaaS Tool and NilShare

Hyland is showcasing its Cloud Imaging SaaS tool, which combines clinical imaging content with multiple specialties for AI-enabled insights in clinical research. NilShare, designed as a cost-effective image sharing approach, securely transfers imaging data without a VPN, eliminating the need for costly CD burning and ingesting. 1: These tools offer significant advantages in terms of data management and research capabilities. The Cloud Imaging SaaS tool enables imaging professionals to access and analyze data more efficiently. 2: NilShare provides a secure and cost-effective way to share imaging data, improving collaboration and research opportunities.

Konica Minolta and Fovia's Collaboration

Konica Minolta and Fovia are teaming up to offer advanced visualization technology in Konica Minolta's cloud-based Exa PACS. This partnership offers customers leading 3D visualization and segmentation functionality that is secure, fast, flexible, and scalable. Offered via AWS cloud, the tools provide flexibility for clinicians while offering significant advantages in cost management for healthcare organizations. 1: The collaboration between Konica Minolta and Fovia brings together two leading technologies to provide enhanced imaging capabilities. 2: By leveraging AWS cloud, the tools offer a scalable and cost-effective solution for healthcare organizations.

Lunit's Collaboration with AstraZeneca

Lunit, which develops technologies for cancer diagnostics and therapeutics, announced a new collaboration with AstraZeneca to develop an AI-enabled digital pathology tool - Lunit SCOPE Genotype Predictor. This tool is capable of analyzing H&E slide images to predict the likelihood of tumor harboring NSCLC driver mutations, such as Epidermal Growth Factor Receptor mutations. 1: The collaboration between Lunit and AstraZeneca holds great promise for advancing cancer diagnostics and therapeutics. 2: AI-enabled digital pathology tools like Lunit SCOPE have the potential to revolutionize the way cancer is diagnosed and treated.This is just a small sampling of the hundreds of announcements at RSNA this week. For a longer list, see here.