Cover Image

Deep learning model for breast shear wave elastography to improve breast cancer diagnosis (INSPiRED 006): an international, multicenter analysis

PURPOSE Shear wave elastography (SWE) has been investigated as a complement to B-mode ultrasound for breast cancer diagnosis. Although multicenter trials suggest benefits for patients with Breast Imaging Reporting and Data System (BI-RADS) 4(a) breast masses, widespread adoption remains limited becau...

Full description

Saved in:
Bibliographic Details
Main Authors: Cai, Lie (Author) , Pfob, André (Author) , Barr, Richard G. (Author) , Duda, Volker (Author) , Alwafai, Zaher (Author) , Balleyguier, Corinne (Author) , Clevert, Dirk-André (Author) , Fastner, Sarah (Author) , Gomez, Christina (Author) , Goncalo, Manuela (Author) , Gruber, Ines (Author) , Hahn, Markus (Author) , Kapetas, Panagiotis (Author) , Nees, Juliane (Author) , Ohlinger, Ralf (Author) , Riedel, Fabian (Author) , Rutten, Matthieu (Author) , Stieber, Anne (Author) , Togawa, Riku (Author) , Sidey-Gibbons, Chris (Author) , Tozaki, Mitsuhiro (Author) , Wojcinski, Sebastian (Author) , Heil, Jörg (Author) , Golatta, Michael (Author)
Format: Article (Journal)
Language:English
Published: August 20, 2025
In: Journal of clinical oncology
Year: 2025, Volume: 43, Issue: 32, Pages: 3482-3493
ISSN:1527-7755
DOI:10.1200/JCO-24-02681
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1200/JCO-24-02681
Verlag, lizenzpflichtig, Volltext: https://ascopubs.org/doi/10.1200/JCO-24-02681
Get full text
Author Notes: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
Description
Summary:PURPOSE Shear wave elastography (SWE) has been investigated as a complement to B-mode ultrasound for breast cancer diagnosis. Although multicenter trials suggest benefits for patients with Breast Imaging Reporting and Data System (BI-RADS) 4(a) breast masses, widespread adoption remains limited because of the absence of validated velocity thresholds. This study aims to develop and validate a deep learning (DL) model using SWE images (artificial intelligence [AI]-SWE) for BI-RADS 3 and 4 breast masses and compare its performance with human experts using B-mode ultrasound.
Item Description:Gesehen am 26.05.2026
Online veröffentlicht: 20. August 2025
Physical Description:Online Resource
ISSN:1527-7755
DOI:10.1200/JCO-24-02681

Similar Items