Adding MRI to a multimodal AI model significantly improves breast cancer detection and risk prediction.
Key Details
- 1NYU Langone researchers evaluated a transformer AI model using mammography, DBT, ultrasound, breast MRI, and clinical variables.
- 2The training set included 1.3 million exams from 274,388 women (2010–2022).
- 3A separate test cohort comprised 1,944 women with 18,201 exams.
- 4Without MRI input, the AUROC for 5-year cancer risk prediction was 0.899; with MRI, it increased to 0.94.
- 5Improved model performance allows better identification of high-risk women for screening and prevention.
Why It Matters
This work demonstrates that integrating MRI with other imaging modalities in AI models can meaningfully enhance risk stratification and detection accuracy for breast cancer. Such advances support precision medicine, enabling more targeted screening and preventive interventions in clinical radiology.
Source
AuntMinnie
Related News
•Radiology Business
Lucida Medical Raises $11M for AI-Based Prostate MRI Diagnosis Expansion
Lucida Medical, specializing in AI-assisted prostate cancer diagnosis via MRI, raises $11.4M to drive US FDA approval and platform expansion.
•Radiology Business
AI Guidance Cuts Novice Ultrasound Exam Time by 34%
AI guidance significantly reduces exam times and enhances diagnostic quality for novice ultrasound operators performing shoulder exams.
•Radiology Business
NYC Health + Hospitals CEO Considers AI to Replace Radiologists
NYC Health + Hospitals CEO suggests AI could partially replace radiologists, pending regulatory approval.