Left and right breast densities should be highly correlated, but not identical—results in practice indicate this is what volumetric techniques have shown. Density should, over a population, generally reduce with age—results in practice indicate this is what volumetric techniques have shown. Sanity checks serve their purpose, but with volumetric methods, there are other ways of evaluating performance. For example, volumetric methods have more often been compared to measurements of breast density from intrinsically 3D imaging modalities, considered to be ground truth, such as breast MRI and breast CT.
Early results on doing volumetric from them are promising ,— —the same breast should get the same result, but tomosynthesis has unique issues compared to mammography, notably no grid in some systems implies very high scatter. In a study conducted by Tagliafico et al.
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However, we note here variations and differences between volumetric methods, which mean that although we might expect stronger correlations, there might be differences between the absolute measures. Do we include the subcutaneous fatty breast edge into the calculation of breast volume? It is hard to estimate but breast fat appears to be important in breast cancer development. On CT and MRI, with their more complete imaging of the breast and other body tissues—where does the breast end?
Phantoms have been experimented with as ground truth 87,92,,, but issues arise because the algorithms are devised for breast tissue with genuine compressed breast edge shapes. If the phantoms do not compress realistically as most do not , then to get the volumetric technique to work, the algorithm needs to be adjusted, which then begs the question of the phantom working in the first place. As an example, most algorithms will reject an image as not being a breast if it can find no tissue along where the chest wall should be.
Thus, a block phantom placed in the middle of the detector will be rejected. It is hard to envisage a phantom that can be devised to be reliable and robust enough to mimic a real breast, with real chest wall connections. For a physicist, moving from a continuous measure which is highly and continuously correlated to sensitivity and risk of developing cancer to a discrete category appears odd.
However, the current laws in the USA require reporting mammographic images using a category, i. We believe this will change in time to come as volumetric methods become more widely used and understood, albeit law changes are not simple. The first method is thresholding the volumetric numbers directly.
Some commercially available VBD measurement systems appear to be adopting this method, e. The second method is to map the volumetric density to an area density, and then thresholding the area density.
That mapping from volumetric to area at each pixel appears to be done using a simple thresholding of the volumetric numbers, but the details appear proprietary. The thresholds can be set either by performing a reader study volpara or by taking a big population, and then assuming the population should be certain percentages. In view of the various mapping methods, there is an urgent need for standardization to achieve a harmonized system. This paper began with an introduction about Capello; thus, it is timely to return to her story now to work out the immediate needs for breast density.
The declared main aim of the Are You Dense movement is that women should be informed of their breast density so that they understand the limitations of mammography screening and that on that basis they can decide to be imaged using another complementary modality. In short, Are You Dense is asking for women to be informed of the risk that their cancer might be missed.
The risk of cancer being missed, however, is not just about masking of a cancer by dense tissue.
However, MISS1—3 poses a problem because it can be argued that each and every mammogram of the same breast could, or should, give different answers to the risk of one of MISS1—3 happening. For example, in the CC view, the cancer might be obscured behind a patch of very dense tissue, which on the MLO view is much more spread out, thus making the cancer visible. However, we believe that Cappello and the other forces behind Are You Dense are not seeking a risk of missing a cancer in each and every view, which will get even more complicated with the multiple views of tomosynthesis.
Instead, it seems clear that Are You Dense is seeking an average risk of a cancer being missed by mammography for the particular breast in question. Fortunately, VBD fulfils these needs by being at least philosophically invariant to the view or imaging modality being utilized—it is a true, physical measure of the breast being imaged, and it meets the demands for physicists to have repeatable measurements which can be understood along with being able to describe, at least in an approximate way, each of the MISS criteria: MISS1— The higher the volumetric density, the higher the probability a cancer could be obscured.
Focal densities come in with high volumetric density and can hide larger cancers; smaller levels of density spread across the breast could hide smaller cancers so the volume and not the dispersion would appear to be more indicative. One of the remarkable findings from tomosynthesis is the finding of cancers in fatty breasts not seen in mammography—every single piece of dense tissue is a potential masking risk.
The higher the volumetric density, the higher the probability of part of that dense tissue forming a sign that could distract the reader and lead to a missed cancer. The higher the volumetric density, the more chance of overlapping tissue hiding some of the key signs of cancer. Measurement of breast composition continues to be a hot research topic globally. For example, Laidevant et al. Their work indicated the potential of using such technique in clinical settings for generating individual compositional diagnostic images, as well as improving the sensitivity and specificity of digital mammography.
They also reported potential improvement of the sensitivity and specificity of breast cancer diagnosis using such compositional analysis method. Since Wolfe first attempted to associate breast cancer risk with variations in the mammographic appearance of the breast, , several breast cancer risk prediction statistical models have been developed. One widely used model is the Gail model, ,, which takes into account a woman's age, hormonal or reproductive history, previous history of breast disease and family history of breast cancer.
Breast density had been shown to associate more strongly with breast cancer risk than most other variables included in the Gail model after age and some genetic factors. Warwick et al. Subsequently, breast cancer risk models can also be used in identifying women with low risk, and help avoiding many unnecessary procedures and examinations, as well as saving medical resources without compromising health care.
This is particularly the case in most younger women who normally have dense breast tissue in preparation for lactation. Breast density measures can help to determine which women would benefit from adjunctive screening. In addition, as opposed to most other risk factors, breast density can be changed with hormone interventions, combined hormone therapy, or tamoxifen, suggesting that it can potentially serve as a surrogate marker in clinical trials of breast cancer prevention.
In a recent review by Drukteinis et al. The current method of assessing breast density is through visual assessment by radiologists, but such assessment is fraught with great variability, thus affecting reliability and reproducibility. VBD assessment, on the other hand, offers an objective and more accurate means of breast density assessment. This may be the surrogate biomarker of risk of missing and possibly risk of breast cancer itself.
The current commercial implementations appear to be doing a good job, but greater improvements are expected in the future. For the enlightened women who have become aware of how breast density affects the accuracy of their mammograms such as through the Are You Dense movement , such developments are timely. It is also fortuitous that volumetric measures deliver a more robust tool for epidemiologists who can use it to correlate with the risk of developing cancer , clinicians and surgeons who can use its quantifiable measurements for making clinical decisions , and physicists who can obtain objective, reliable, and reproducible statistics.
Therefore, the role of VBD will directly and indirectly encompass the 4Ps in medicine. With the advancement of breast density assessment techniques, we are now witnessing a paradigm shift toward personalized breast screening, in which we are going to see more cancers being detected early. The authors would like to thank Professor Dr. The authors would also like to thank Dr.
Ralph Highnam and Dr. Ariane Chan from volpara Solutions, Ltd. Tao Wu from Hologic, Inc. Volume 42 , Issue If you do not receive an email within 10 minutes, your email address may not be registered, and you may need to create a new Wiley Online Library account. If the address matches an existing account you will receive an email with instructions to retrieve your username.
Medical Physics Volume 42, Issue Tools Request permission Export citation Add to favorites Track citation. Share Give access Share full text access. Share full text access. Please review our Terms and Conditions of Use and check box below to share full-text version of article. Abstract Breast density is a strong predictor of the failure of mammography screening to detect breast cancer and is a strong predictor of the risk of developing breast cancer. Figure 1 Open in figure viewer PowerPoint. The reader identifies the boundaries of the breast tissue and the threshold for dense tissue on the mammogram, and the software calculates the total area of the breast, the total area of dense tissue, and the percentage area of dense tissue.
Ursin of the University of Southern California School of Medicine to identify and quantify the extent of radiographic density patterns on a mammogram by measuring the percentage of the mammogram that contains densities in a specified range and to track changes in density patterns which occur over time or with medical treatment. Dense tissue and total breast areas are then estimated based on the pixels in the segmented area, and breast density is estimated as the ratio of the dense tissue area and the total breast area.
This analysis evaluates the appearance of structures and textures in the breast to differentiate between fatty and dense regions. It also incorporates additional features of mammographic images for improving the risk associations of breast density and breast cancer risk. Figure 2 Open in figure viewer PowerPoint. Figure 3 Open in figure viewer PowerPoint. Figure 4 Open in figure viewer PowerPoint. Figure 5 Open in figure viewer PowerPoint.
Figure 6 Open in figure viewer PowerPoint. In the resulting h int image, each pixel represents the thickness of interesting nonfat tissue of the compressed breast above that pixel during acquisition. This effectively provides objective quantitative information about the breast anatomy. From the compressed breast thickness, the SMF representation potentially provides a volumetric estimate of the amount of dense tissue in a breast.
A complete and substantial set of calibration data such as mAs and kVp is required to generate realistic breast composition measures. From the compressed breast thickness, technique factors used for taking the mammogram and the information from the calibration device, VBD is calculated. The fibroglandular tissue volume is found by referencing each pixel's attenuation to the attenuation of pixels that are labeled exclusively as fat.
The estimated fibroglandular tissue volume is then divided by the total breast volume to calculate the volumetric percentage of fibroglandular tissue in the breast. The key differences with SMF are in the robustness and reliability of the results, especially in dense breasts, and not including skin in the volume of dense tissue. The glandularity and the thickness are measured independently in each pixel of the image to objectively calculate the total volume and volumetric percentage of glandular tissue in the breast; it does not rely on estimations based on compressed breast thickness.
Note, due to these variations, volumetric techniques can give a range of densities. Nonetheless, some form of standardization is likely to be necessary just as in bone densitometry. MISS2— The cancer is not seen, possibly due to distraction by other dense tissue. MISS3— The cancer is seen, but it is interpreted wrongly, possibly due to overlapping tissues.
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MISS4— The cancer is not present on the image. MISS5— Cancer is present, but not visibly discernible as such. Good positioning is the key to MISS4, while there is not much to be done about MISS5 other than potentially trying to detect angiogenesis and other very early signs of cancer using more functional imaging techniques. MISS2— The higher the volumetric density, the higher the probability of part of that dense tissue forming a sign that could distract the reader and lead to a missed cancer.
MISS3— The higher the volumetric density, the more chance of overlapping tissue hiding some of the key signs of cancer. This was likely due to the application of advanced postprocessing software. Consequently, the currently accepted widespread notion of increasing breast density reducing mammographic performance should be revisited.
SUMMARY The current method of assessing breast density is through visual assessment by radiologists, but such assessment is fraught with great variability, thus affecting reliability and reproducibility. Google Scholar. Crossref PubMed Google Scholar.
Man Boob Treatments
Crossref Google Scholar. Wiley Online Library Google Scholar. PubMed Google Scholar. Citing Literature. If the underlying cause is drug use or prescription medication, the condition will resolve by stopping the drugs. If the gynecomastia is primarily fatty tissue, such as in pseudogynecomastia, the liposuction will most likely be prescribed. If it is caused by the decreased testosterone and increased estrogen, hormonal therapy may be used.
If the underlying cause of the condition is some other disease or disorder, then treatment will be directed at that problem. If the patient still suffers from gynecomastia after the primary cause has been treated, the a medical or surgical solution will be considered. The most common gynecomastia treatment is breast reduction surgery. The excess fatty or glandular tissue must be surgically removed from the breast by a mastectomy for gynecomastia. The surgery is an outpatient procedure.
In some extreme cases, or when other medical conditions are a concern, an overnight stay will be recommended.
Gynecomastia treatment is a plastic surgery procedure that is relatively safe and effective. They look at gynecomastia as a cosmetic problem and therefore is not medically necessary. The best course of treatment for the condition should be discussed with a qualified physician.