The American College of Radiology (ACR) and several other radiological societies submitted proposals at the May meeting of the AMA CPT Editorial Panel, advocating for emerging imaging tools.
Their proposals included a new Category III CPT code for software that generates an AI malignancy risk score from medical imaging data, as well as revisions to two current Category III codes (0721T and 0722T) related to quantitative CT tissue characterization. All were deferred for refinement, the ACR said in a May 7 update.
Radiology CPT advisers met with other specialty societies and vendors and reviewed approximately 65 proposals submitted to the AMA, many that could affect radiologists, according to the ACR.
The update also highlighted anticipated radiology code changes for calendar year 2027. The ACR urged members to review the changes for their potential impact on contracts in the coming year.
Find the details here.
![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)
