October 2025 - The Imaging Wire

For radiologists – the medical detectives who find clues in our medical images – the daily grind can feel like a “death by a thousand cuts.” Much of their time is spent not on diagnosis, but on tedious reporting.

Now, a new generation of artificial intelligence is stepping in to serve as a high-tech scribe, automating the drudgery.

This AI tackles reporting, the most time-consuming part of radiologists’ workflow.

AI-enabled radiology reporting makes transcribing data from technologist worksheets a thing of the past, using Optical Character Recognition (OCR) to decipher everything, even what looks like “chicken scratch handwriting.” Then…

A large language model (LLM) applies clinical context to ensure it understands the meaning.
It intelligently injects that data into the correct sections of the radiologist’s personal report template.
Finally, it performs its own “inference,” like calculating a TI-RADS score and dropping it right into the impression.

Modern AI also learns from a radiologist’s actions, providing a hands-free way to build a report, with features such as…

Smart Measurements: When a lesion is measured, the AI recognizes the location and automatically adds the data and comparisons to prior scans into the report.

Automated Prior Population: Instead of struggling with speech-to-text, the AI notices when a prior study is opened for comparison and automatically populates that exam’s date.

Streamlined Expert Findings: A radiologist can simply state positive findings, and the AI acts as both writer and editor.

AI-enabled radiology reporting weaves dictated phrases into complete sentences, generates an impression based on clinical guidelines like BI-RADS, and serves as a vigilant proofreader, flagging errors like laterality mistakes or semantic impossibilities.

As AI technology matures, the software itself is becoming easier to build. The true differentiator is the team behind it.

For radiologists evaluating these new reporting tools, it’s critical to look for teams that are “AI native” – built from the ground up with AI at their core.

Companies founded on these principles, such as New Lantern, are pioneering these all-in-one radiology reporting solutions, treating the challenge not as a problem to be fixed with another widget, but as an opportunity to build one complete, intelligent platform.

The Takeaway

The evolution in AI-enabled radiology reporting isn’t about replacing radiologists; it’s a tool to augment their skills. Radiologists who harness AI to create reports faster will significantly outpace those who do not, allowing them to return their full focus to the art of diagnosis.

Increased use of CT drove a boom in medical imaging utilization in the emergency department setting over the past 10 years. That’s according to a new study in Radiology that comes amid increased scrutiny over the long-term health effects of CT radiation.

CT is tailor-made for evaluating patients in the emergency setting. It’s fast, relatively inexpensive, and provides high-quality images that can deliver a diagnosis quickly.

For these reasons, emergency departments have been quick to install workhorse CT scanners running at all hours in the hope that faster diagnoses will lead to better patient outcomes.

But there are also downsides to the growth in CT utilization. It can put strains on radiology departments to read all the new scans – a particular challenge in an era of workforce shortages.

Concerns about the link between CT radiation dose and cancer also persist. Two controversial studies were published this year on the subject, one linking CT to future cancers across the U.S. population and the other specifically to pediatric blood cancer.

The new study offers a useful benchmark for tracking CT’s growth in the ED. Researchers chronicled changes in U.S. emergency imaging use in Medicare from 2013 to 2023, finding that per 100 Medicare beneficiaries…

CT use grew 96% (37 vs. 19 encounters).
While ultrasound only grew 20% (2.8 vs. 2.3 encounters).
And radiography use remained flat at 37 encounters in both years.

In addition, the number of overall ED encounters actually declined 16% (55 vs. 65 encounters), showing that imaging’s growth was due to more imaging per ED encounter rather than overall increased ED visits by beneficiaries.

On a per-encounter basis, CT use grew 134% over the study period compared to 43% for ultrasound and 19% for radiography.

Researchers believe that the difference in modality growth rates could be due to the use of CT to accelerate patient turnover in the ED.

Meanwhile, ultrasound use may have grown more modestly due to the proliferation of point-of-care handheld scanners among non-radiologists.

The Takeaway

The new findings underscore the conundrum behind emergency CT – it’s an incredibly powerful technology that nevertheless requires restraint in order to be used judiciously. Let’s hope emergency physicians take note.

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