Artificial intelligence got its start in radiology as a tool to help medical image interpretation, but much of AI’s recent progress is in data reconstruction: improving images before radiologists even get to see them. Two new studies underscore the potential of AI-based reconstruction to reduce CT radiation dose while preserving image quality.
Radiology vendors and clinicians have been remarkably successful in reducing CT radiation dose over the past two decades, but there’s always room for improvement.
- In addition to adjusting CT scanning protocols like tube voltage and current, data reconstruction protocols have been introduced to take images acquired at lower radiation levels and “boost” them to look like full-dose images.
The arrival of AI and other deep learning-based technologies has turbocharged these efforts.
- In the first study, Italian researchers used GE HealthCare’s DLIR deep learning data reconstruction protocol to reduce both radiation and contrast dose for cardiac CT angiography exams in a group of 255 patients.
They compared DLIR operating at high strength to GE’s older ASiR-V protocol in CCTA scans with lower tube voltage (80 kVp), finding that deep learning reconstruction led to …
- 42% reduction in radiation dose (2.36 mSv vs. 4.07)
- 13% reduction in contrast dose (50 mL vs. 58 mL).
- Better signal- and contrast-to-noise ratios.
- Higher image quality ratings.
In the second study, researchers from China including two employees of United Imaging Healthcare used a deep learning reconstruction algorithm to test ultralow-dose CT scans for coronary artery calcium scoring.
- They wanted to see if CAC scoring could be performed with lower tube voltage and current (80 kVp/20 mAs) and how the protocol compared to existing low-dose scans.
In tests with 156 patients, they found the ultralow-dose protocol produced …
- Lower radiation dose (0.09 vs. 0.49 mSv).
- No difference in CAC scoring or risk categorization.
- Higher contrast-to-noise ratio.
The Takeaway
AI-based data reconstruction gives radiologists the best of both worlds: lower radiation dose with better-quality images. These two new studies illustrate AI’s potential for lowering CT dose to previously unheard-of levels, with major benefits for patients.
