One of the biggest radiology stories of 2023 was the release of impressive interim results from the MASAI study, a large-scale trial of AI for breast screening in Sweden. At ECR 2024, MASAI researchers put an emphatic cap on the conference by presenting final data indicating that AI could have an even bigger impact on mammography screening than we thought.
If you remember, MASAI’s interim results were published in August in Lancet Oncology and showed that ScreenPoint Medical’s Transpara AI algorithm was able to reduce radiologist workload by 44% when used as part of the kind of double-reading screening program that’s common in Europe.
- Another MASAI finding was that AI-aided screening had a 20% higher cancer detection rate than conventional double-reading with human radiologists, but the difference was not statistically significant.
That’s all changed with the final MASAI results, presented at ECR on March 2 by senior author Kristina Lång, MD, of Lund University.
- Lång presented data from 106k participants who were randomized to either screening with Transpara V. 1.7 or conventional double reading without AI.
Transpara triaged mammograms by giving them a risk score of 1-10, and only those classified as high risk received double reading; lower-risk mammograms got a single human reader. In the final analysis, AI-aided screening …
- Had a 28% higher cancer detection rate per 1k women (6.4 vs. 5.0), a difference that was statistically significant (p=0.002)
- Detected more cancers 10-20 mm (122 vs. 79)
- Detected more cancers of non-specific histologic type (204 vs. 155)
- Detected 20 more non-luminal A invasive cancers and 12 more DCIS grade 3 lesions
The Takeaway
When combined with the Lancet Oncology data, the new MASAI results indicate that AI could enable breast radiologists to have their cake and eat it too: a lower workload with higher cancer detection rates.
