Rishabh Jain, Medical Oncologist at AIIMS, shared a post on X about a paper by Lie Cai et al., published in Journal of Clinical Oncology.
“INSPiRED by AI: smarter breast imaging, fewer unnecessary biopsies
INSPiRED-006 Trial (Intl, multicenter, n=1,294; 4,776 images). AI–Shear Wave Elastography (AI-SWE) vs B-mode US for BI-RADS 3/4 breast masses
Results:
- AUROC: 0.94–0.93 across external validations
- Sensitivity: ~98% (on par with B-mode)
- False positives: ↓ 38–62%
- Population impact: 234/1,000 women could skip unnecessary biopsies while cancers still detected
Take-home:
AI-SWE = expert-level accuracy plus far fewer false alarms.
A step toward safer, leaner breast cancer diagnostics.”
Title: Deep Learning Model for Breast Shear Wave Elastography to Improve Breast Cancer Diagnosis (INSPiRED 006): An International, Multicenter Analysis
Authors: Lie Cai, André Pfob, Richard G. Barr, Volker Duda, Zaher Alwafai, Corinne Balleyguier, Dirk-André Clevert, Sarah Fastner, Christina Gomez, Manuela Goncalo, Ines Gruber, Markus Hahn, Panagiotis Kapetas, Juliane Nees, Ralf Ohlinger, Fabian Riedel, Matthieu Rutten, Anne Stieber, Riku Togawa, Chris Sidey-Gibbons, Mitsuhiro Tozaki, Sebastian Wojcinski, Joerg Heil, Michael Golatta
Read The Full Article.
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