Br J Cancer: Quantitative breast density analysis can improve breast cancer screening options

Or layered risk-based breast cancer screening designed to optimize early detection of cancer, reducing the mortality of breast X-rays false positive rate, benign biopsies and over- diagnosis and so on
.

However, risk-based screening programs, including questionnaires, blood draws, and consultations, may eliminate the benefits of screening for some women and increase the complexity of the screening, ultimately reducing the effectiveness of the screening

Or layered risk-based breast cancer screening designed to optimize early detection of cancer, reducing the mortality of breast X-rays false positive rate, benign biopsies and over- diagnosis and so on

Breast density (BD) reflects the ratio of the number of glands and fibrous connective tissue to the number of fat tissue in the breast
.

BD has three attributes that support stratification for population screening

Breast density (BD) reflects the ratio of the number of glands and fibrous connective tissue to the number of fat tissue in the breast

The study aims to reveal whether BD can be used as an imaging biomarker for more intensive breast cancer screening by predicting the interval and lymph node-positive cancers
.

The study aims to reveal whether BD can be used as an imaging biomarker for more intensive breast cancer screening by predicting the interval and lymph node-positive cancers
.

The study aims to reveal whether BD can be used as an imaging biomarker for more intensive breast cancer screening by predicting the interval and lymph node-positive cancers

Analysis of the ability of BD to distinguish all, screen and detect cancers and interval cancers

Analysis of the ability of BD to distinguish all, screen and detect cancers and interval cancers

Researchers calculated fibocyte volume (FGV), breast volume density (VBD) and density grade (DG) through automatic BD software
.

Radiologists use a visual analog scale (VAS) from 0 to 100 to assess BD

The results showed that FGV, VBD, VAS, and DG can distinguish interval cancer from control
.

Analysis based on the AUC value shows that FGV can distinguish all cancer types better than VBD or VAS

BD distinguishes cancer types

BD distinguishes cancer types

All in all, the results of the study revealed that FGV, VBD, VAS and DG can distinguish interval cancer from the control group
.

Only FGV can distinguish cancers detected by screening, which also provides a theoretical basis for predicting the risk of breast cancer

FGV, VBD, VAS and DG can distinguish interval cancer from the control group
.
FGV, VBD, VAS and DG can distinguish interval cancer from the control group
.

Original source:

Burnside, ES, Warren, LM, Myles, J.
et al.
Quantitative breast density analysis to predict interval and node-positive cancers in pursuit of improved screening protocols: a case--control study.
Br J Cancer (24 June 2021).

Quantitative breast density analysis to predict interval and node-positive cancers in pursuit of improved screening protocols: a case–control study.

 

Leave a message here