April 25th 2024
An emerging deep learning radiomics model, based on B-mode ultrasound and color Doppler flow imaging, demonstrated a 91 percent AUC for predicting lymphovascular invasion in a multicenter study of women with invasive breast cancer.
Multicenter Breast Ultrasound Study: AI Bolsters Accuracy and Specificity of BI-RADS Classifications
May 24th 2023Emerging breast ultrasound research showed the use of computer-aided diagnosis (CAD), powered by deep learning, led to 24 percent and 36.9 percent improvements in accuracy and specificity, respectively, in the use of BI-RADS classifications by radiologists without breast ultrasound expertise.
New Study Shows Viability of Adjunctive AI for Breast Ultrasound
May 8th 2023Adjunctive use of an artificial intelligence (AI) software demonstrated nearly equivalent sensitivity and over 28 percent higher accuracy in comparison to radiologist assessment of breast ultrasound images for breast lesions, according to new research presented at the recent Society of Breast Imaging (SBI) conference.
Could Controlled Imaging Rein in Suboptimal Use of MRI, CT and Ultrasound Exams?
April 24th 2023Lamenting a lack of control over imaging requests from referring clinicians, this author suggests that a more collaborative approach between referrers and radiologists may facilitate more efficient use of imaging.
Automated Breast Ultrasound: Is it a Viable Second-Look Option for Women with Dense Breasts?
April 4th 2023Emerging research shows the adjunctive use of automated breast ultrasound with mammography has similar sensitivity for breast cancer detection as adjunctive handheld ultrasound but may offer reduced false-positive rates in women with dense breasts.