There's lots of buzz about using artificial intelligence (AI) in radiology, but the enthusiasm has been somewhat curbed by a lack of reimbursement, according to a May 5 talk at AuntMinnnie.com's Spring 2021 Virtual Conference delivered by Dr. Melissa Chen.
This may be changing, however: Last September, the U.S. Centers for Medicare and Medicaid Services (CMS) created the new technology add-on payment (NTAP) program for reimbursement of some AI algorithms. Chen, of the University of Texas MD Anderson Cancer Center in Houston, offered session attendees tips on how to get reimbursed for the clinical use of radiology AI.
In addition to her duties at MD Anderson, Chen serves as alternate advisor for the American Society of Neuroradiology to the American Medical Association Relative Value Scale Update Committee and as vice chair of the economics committee for the American College of Radiology's Patient- and Family-Centered Care Commission.
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
