Despite a surge in FDA-cleared radiology AI tools, very few qualify for reimbursement due to lack of supporting clinical studies.
Key Details
- 1Radiology comprises roughly 80% of all FDA-cleared medical AI algorithms.
- 2Only one CPT category 1 payment code for newer AI tools exists today; a second will be added in January 2026.
- 3Both reimbursement codes are specific to cardiac imaging AI applications.
- 4Hundreds of approved algorithms lack reimbursement due to insufficient clinical evidence of patient benefit.
- 5Experts attribute the problem to a disconnect between regulatory clearance and payment policy.
Why It Matters
Without reimbursement, the financial incentives for clinical adoption of imaging AI are limited, slowing broader deployment of these technologies. Bridging the gap between regulatory approval and payment is critical for real-world impact of AI in radiology.
Source
Radiology Business
Related News
•Radiology Business
UCLA Appoints Inaugural Associate Dean for Health AI Strategy
UCLA has appointed Katherine P. Andriole as its first associate dean for Health AI Strategy and Innovation, with an initial focus on radiology.
•HealthExec
EFF Sues CMS For Transparency on AI-Powered Medicare Prior Authorization
EFF has sued CMS to compel disclosure about the WISeR pilot deploying AI for Medicare prior authorization.
•Radiology Business
AI Tool Developed to Detect Domestic Violence via Radiology Data
Mass General radiologists developed a machine learning tool to identify patients at risk of intimate partner violence using imaging and clinical records.