A group of Norwegian researchers have utilized automated breast density measurements to find out that women with dense breasts are more susceptible to risks of breast cancer. Almost 100,000 women as well as 300,000 screening tests were involved in the study. The study’s findings were published in the ‘Radiology’ journal on June 26.
The senior author of the study and researcher as well as head of BreastScreen Norway for the Cancer Registry of Norway, Solveig Hofvind stated that screening tests of women with dense breasts implied higher rates of biopsy and recall as well as higher possibilities of interval breast cancers and screen-detected breast cancers as compared to women having non-dense breasts. She also added that dense breasts present a formidable challenge for screening of cancer since the appearance of dense tissue on a mammogram is white which is also similar to the appearance of breast tumors. Therefore, dense breast tissue has the potential for hiding cancers.
The author of an editorial accompanying the study and chief of breast imaging at the Yale School of Medicine, Dr. Liane Philpotts stated that dense breasts could not be recognized by a patient on their own and it requires a mammogram test to identify the same. She explained that radiologists utilize a standard scoring technique from the American College of Radiology (ACR) for identification of breast density. The scoring system involves a scale from A to D in which scores of A and B imply that the subject does not have dense breasts while C and D scores imply dense breasts. She also added that almost 50% of women in America screened for breast cancer were found to have dense breast tissue and informed regarding the reduction in breast density with age.
However, the study has implemented automated volumetric analysis instead of the ACR technique for classification of breast density. Furthermore, the findings of the study could not be generalized for the US population as the study involved aged women and were screened in alternate years rather than on an annual basis. This implies the necessity for further research in order to anticipate the risks and advantages of the automated software for the study.