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Enlarged Lymph Nodes on Screening Mammograms Predict Cardiometabolic Disease, Cardiovascular Risk

Imaging Technology

milla1cf Fri, 05/10/2024 - 08:10 May 10, 2024 — According to the Summa Cum Laude Award-Winning Online Poster presented during the 124th ARRS Annual Meeting , fat-enlarged axillary nodes on screening mammograms can predict high cardiovascular disease (CVD) risk, Type 2 diabetes (T2DM), and hypertension (HTN). Rubino et al. and HTN (OR = 2.5,

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ARRS: Dartmouth poster wins for CVD risk prediction potential using mammograms

AuntMinnie

A scientific poster on cardiovascular disease (CVD) risk prediction using fat-enlarged axillary nodes visualized on screening mammograms won the Summa Cum Laude Award at the 124th American Roentgen Ray Society (ARRS) annual meeting. This is defined by the American Heart Association as more than a 7.5%

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Late-stage breast cancer incidence increasing in U.S. women

AuntMinnie

The incidence of distant-stage breast cancer increased between 2004 and 2021 for the following: Asian women (APC, 2.90%; p White women meanwhile had an incident increase from 2004 to 2012 with an APC of 1.68%; (p = 0.01). However, the researchers did not observe such a trend from 2012 to 2021.

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Ultrasound nonmass breast lesion features may signal malignancy

AuntMinnie

It also found that having a negative mammogram was associated with a lower malignancy rate and lower positive predictive values for sonographic features compared with having an abnormal mammogram. The retrospective, multicenter study included data collected from 2012 to 2019 from 993 women with an average age of 50 years.

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AI scoring predicts DCIS recurrence

AuntMinnie

The multicenter, retrospective study included data collected between 2012 and 2017 from 1,740 women with an average of 51.5 The researchers analyzed preoperative routine mammograms via a commercially available AI algorithm (Lunit Insight MMG, Lunit ). years who were treated for DCIS.

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Combining AI Models Improves Breast Cancer Risk Assessment

Imaging Technology

“In recent years, AI has been studied for the purpose of diagnosing breast cancer earlier by automatically detecting breast cancers in mammograms and measuring the risk of future breast cancer.” Diagnostic AI models are trained to detect suspicious lesions on mammograms and are well suited to estimate short-term breast cancer risk.

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AI Software Firm Announces Support of DenseBreast-info.org Ahead of SBI 2023 Symposium

Imaging Technology

1) After a mammogram, other screening tests such as ultrasound, and especially MRI, find additional cancers in dense breasts. To date, only sixteen states and the District of Columbia (2) have laws that require insurance coverage for screening beyond mammograms for higher risk women and/or those with dense tissue. Epub 2012 Sep 19.