Breast: Page 2

DBT surveillance screening after breast cancer treatment effective
By Amerigo Allegretto
Surveillance screening via digital breast tomosynthesis (DBT) immediately after breast cancer treatment is effective.
December 21, 2023
(A) Mammographic magnification view shows grouped calcifications in the left breast (circle). Stereotactic biopsy yielded grade 2 DCIS. Patient underwent a lumpectomy with tumor-negative surgical margins and radiation therapy. (B) Mammographic magnification view obtained four years after diagnosis shows new calcifications at the surgical site (circle). Stereotactic biopsy was performed, which revealed recurrent grade 2 DCIS. The patient then underwent a mastectomy. Image courtesy of the ARRS.
Volpara touts breast density, mammography studies
By AuntMinnie.com staff writers
Volpara Health Technologies is highlighting two peer-reviewed studies published during RSNA 2023 that featured the company's technology.
December 21, 2023
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FES-PET better than FDG-PET in breast cancer patients
By Will Morton
In a head-to-head comparison, F-18 fluoroestradiol (FES)-PET/CT was better than standard FDG-PET/CT for the initial staging of estrogen receptor-positive breast cancer patients.
December 21, 2023
Axial PET (a) and axial fusion (b) images of F-18 FES (top) and F-18 FDG (bottom) with concordant uptake of both radiotracers in a left breast mass and left axillary node metastasis in correlation with CT imaging (c). Image courtesy of the European Journal of Hybrid Imaging.
Lunit bids for Volpara Health
By Erik L. Ridley
Continuing its aggressive push for global growth, South Korean AI software developer Lunit signed a deal to acquire breast and lung imaging AI software firm Volpara Health Technologies for approximately $292 million Australian dollars ($193 million U.S.).
December 14, 2023
Lunit Res
AI predicts malignancy on breast ultrasound
By Amerigo Allegretto
An AI model can accurately predict malignancy on breast ultrasound based on BI-RADS assessment.
December 14, 2023
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New AI training strategies stiffen defense against adversarial attacks
By Liz Carey
Computer scientists are exploring how to protect against medical errors caused by adversarial attacks on AI machine learning diagnostic models.
December 15, 2023
An illustration of two types of adversarial attacks on breast imaging diagnosis. Adversarial noise applied in white-box attacks and adversarial samples produced by generative adversarial networks in black-box attacks can fool a deep learning diagnostic model to give wrong output, according to University of Pittsburgh researchers. The researchers have proposed two security schemes, called ARFL and LIDA, to make the models robust and resilient to adversarial attacks. (Image courtesy of Shandong Wu, PhD, Pittsburgh Center for AI Innovation in Medical Imaging)
Mammography AI model performs well in screening populations
By Amerigo Allegretto
A mammography-based AI model showed good and generalizable performance across European screening populations, according to study results presented December 7 at the San Antonio Breast Cancer Symposium in Texas.
December 8, 2023
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RSI predicts early response to chemotherapy in breast cancer
By Amerigo Allegretto
Restriction spectrum imaging (RSI) is a suitable method for evaluating neoadjuvant therapy response early for breast cancer.
December 8, 2023
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DCE-MRI shows treatment response for triple-negative breast cancer
By Amerigo Allegretto
DCE-MRI performs well in predicting early response to immunochemotherapy in women with triple-negative breast cancer.
December 7, 2023
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CEM shows value as surveillance imaging tool
By Amerigo Allegretto
Contrast-enhanced mammography (CEM) has utility as a surveillance tool for women with a personal history of breast cancer.
December 6, 2023
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DBT plus mammo detects breast cancers with higher histologic grades
By Amerigo Allegretto
Digital breast tomosynthesis (DBT) plus synthesized mammography screening leads to higher detection of early-stage invasive breast cancers grades 2 or 3.
December 6, 2023
Imaging depicts a screen-detected invasive breast cancer in the dense breast tissue of a 59-year-old woman. A section in the mediolateral oblique view from a DBT exam of the left breast shows an irregular mass with surrounding architectural distortion (circle). The participant had no history of breast cancer and had been screened previously in the German mammography screening program. Histologic analysis showed invasive carcinoma of no special type, grade 2, with tumor size of 18 mm. Image courtesy of the RSNA.
AI algorithm flags interval breast cancer cases
By Amerigo Allegretto
AI could help tackle the challenge of identifying interval breast cancers.
December 5, 2023
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