BREAST DENSITY (1)
BREAST DENSITY-LOWER
DETERMINING BREAST DENSITY
For decades breast density was subjectively graded by radiologists. I think we were fairly accurate at recognizing patterns, but claims that these could be translated into actual volumetric measures were nonsense. This is explained in my article in 2008¹.
It is now possible to actually measure the amount of fibroglandular tissue in the field of view on a digital mammogram. By knowing the thickness of the breast, the mAs, and kVp, and the amount of radiation passing through the breast reaching a given detector element, the percentages of fibrous and fatty tissue, in the column of tissue overlying that detector element, can be calculated. By adding all the column measures together, the system can calculate the volume of tissue that is “dense” (water) and the amount that is fat. However, this only tells you the volume of dense tissues as a percent of the total volume of tissues in the field of view of the image. Since we do not image the entire breast, and since we actually have no idea where the breast ends, any accurate measure of the actual percent density of the breast is not possible.
Furthermore, why would a woman with a small breast that is 70% dense with a volume of 10 cc of fibroglandular tissue (ACR pattern “d”), be at higher risk than a woman with a much larger breast that has tissues scattered throughout the fat making it an ACR pattern “b”, but containing far more than 10 cc’s of fibroglandular tissue?
DENSITY AND RISK OF DEVELOPING BREAST CANCER
I do not think that tissue patterns are a useful measure of risk for developing breast cancer. The data that suggest this are probably due to the fact that in any study, if the women have had mammograms, those who have fatty breasts and have been diagnosed with breast cancer, have likely been detected early in the program, or prior to the start of the program. Consequently, the cancers that are found during (later in) the program will, more than likely, be those that were hidden in dense breast tissue.
In fact, studies linking density to risk are highly suspect. They have all tried to gauge the percent of the breast that is dense tissue compared to the amount of fat, and then associate that with breast cancer risk. As noted above, all such estimates suffer from the fact that the breast has no definable boundaries–where does it end? Without being able to accurately measure the total volume of the breast, it is impossible to measure the percent of the volume that is dense (percent volume=volume of dense tissue/total volume of the breast).
Claims of increased risk due to dense tissue are greatly exaggerated. In the first place, the vast majority (80%) of women under the age of 40 have dense breast tissues, yet these women have the lowest risk of developing breast cancer. The percent of women with dense breasts decreases as women age². Women who are using supplemental hormones after menopause are slower to become “fatty replaced”. There are some data that suggest that using hormones after menopause slightly increases the risk of breast cancer. Perhaps the persistence of dense breast tissue is coincident.
In our data, the same percentage of women in the population that have a particular pattern is similar to the percent of women diagnosed with breast cancer who have each pattern. The problem is that dense tissues can hide cancers and the delay in their detection is likely the source of claims of increased risk (cancers are found earlier in fatty breasts). Again, it is paradoxical to suggest that dense breasts are at higher risk when most women in their twenties and early thirties have “dense” breasts yet they have the lowest risk of breast cancer. Perhaps it is the persistence of dense breast tissue into the postmenopausal years that is a risk (hormones), but this is not known.
At the Massachusetts General Hospital our distribution of tissue patterns was somewhat different from the ACR numbers but our data were from the era of screen/film:
a. 9% of all women had pattern “a”.
b. 24% of all women had pattern “b”
c. 56% of all women had pattern “c”
d. 11% of all women had pattern “d”
In our experience the percentage of cancers was similar to the above distribution. Women with pattern:
a. Accounted for 9% of all women and 4% of the women diagnosed with cancer
b. Accounted for 24% of all women and 23% of the women diagnosed with cancer
c. Accounted for 56% of all women and 64% of the women diagnosed with cancer
d. Accounted for 11% of all women and 9% of the women diagnosed with cancer
Women with ACR patterns “c” and “d” accounted for approximately 67% of the population and 72% of the cancers. However, if women with ACR PPAT “a” or “b” (approx.33% of the population)had been excluded from screening because they are at slightly lower risk, we would overlook approximately27% of the women with cancer.
More recent MGH data³using Digital Mammography are similar:
a. Women with fatty breasts (ACR “a”) make up 7.6% of the population and account for 5.7% of the cancers
b. Women with scattered density (ACR “b”) make up 47.7% of the population and 47.2% of the cancers
c. Women with heterogeneous tissues (ACR “c”) make up 38.9% of the population and 42.2% of the cancers
d. Women with extremely dense tissues (ACR “d”) make up 4.9% of the population and 4.9% of the cancers
In our experience women with “extremely dense tissues (“d”)” were only at slightly elevated risk to not elevated at all, when compared to women with “all fat”, and the most women diagnosed with cancer had patterns “b” and “c”. Based on our experience (others have had similar experience), dense tissues are not a particularly increased risk of developing breast cancer, but there is no question that dense tissues can hide cancers on mammograms. Some are visible on ultrasound, and even more are visible on MRI. Until we can screen effectively and efficiently using ultrasound and MRI, mammogrpahy remains the mainstay of early detection.
SUMMARY
Breast density is not a major risk factor, but normal fibroglandular breast tissues can hide cancers. The use of Digital Breast Tomosynthesis (DBT) increases the cancer detection rate by about 30% by being able to remove superimposed tissues, but if a cancer actually grows in fibroglandular tissues it can be hidden. These cancers can be better detected using Ultrasound or MRI.
REFERENCES
1.Kopans DB.Basic physics and doubts about relationship between mammographically determined tissue density and breast cancer risk. Radiology. 2008;246:348-53.
2.Stomper PC, D'Souza DJ, DiNitto PA, Arredondo MA. Analysis of Parenchymal Density on Mammograms in 1353 Women 25-79 Years Old. AJR 1996;167:1261-1265.
3.Yala A, Lehman C, Schuster T, Portnoi T, Barzilay R. A Deep Learning Mammography-based Model for Improved Breast Cancer Risk Prediction. Radiology. 2019 Jul;292(1):60-66.
