VisR Ultrasound Improves Diagnosis of Breast Cancer by the Elastogram-to-B-Mode Ratio in a Blinded Reader Study
Year: 2025
Type: article
Study design: Observational Study
Abstract: Ultrasound elastography is increasingly being used alongside mammography for breast cancer diagnosis, particularly in women with radiographically dense breasts. The elastogram-to-B-Mode ratio (E/B), which compares lesion sizes in B-Mode and stiffness images, has been shown to differentiate malignant (E/B >1) from benign (E/B <1) masses. However, the diagnostic utility of E/B has not yet been evaluated using viscosity images, despite viscosity being an emerging biomarker for malignancy. Furthermore, neglecting viscosity can confound elasticity estimation in viscoelastic media like breast tissue. To address this limitation, we used Viscoelastic Response (VisR) ultrasound to assess the diagnostic value of E/B derived from both relative stiffness (RE) and relative viscosity (RV) images. In a blinded reader study, E/B values from viscosity images exhibited similar trends (>1 in malignant lesions and <1 in benign lesions) to those observed in stiffness images. Additionally, E/B values calculated from RE alone, RV alone, or a combination of RE and RV achieved 4-16% higher AUCs for discriminating malignant lesions compared to E/B derived solely from Acoustic Radiation Force Impulse (ARFI) peak displacement. These results suggest that incorporating VisR-derived viscosity and elasticity metrics into E/B calculations could significantly improve diagnostic accuracy for breast cancer detection.
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,075
Awards: Transcutaneous ARFI Ultrasound for Differentiating Carotid Plaque with High Stroke Risk, VisR Ultrasound for Monitoring Antibody-Mediated Rejection in Renal Transplant Patients, VisR Ultrasound for Noninvasively Interrogating Stromal Collagen Organization in Women as a Breast Cancer Biomarker
OpenAlex ID: W4409426141
