Background enhancement is prevalent in DCE-MRI of the breast, and may decrease the specificity of breast DCE-MRI for detecting malignant lesions. Given the increasing utilization of DCE-MRI for breast cancer screening and assessment of treatment response, understanding the potential effects of background enhancement is an important clinical issue. To our knowledge, there are currently no robust, quantitative methods to measure background enhancement. Authors have evaluated background enhancement measures using manually selected regions of interest in the breast (15
), however manual methods are inherently dependent on the subjective nature of the region determination. There is clearly a need for a more systematic quantitative measure of background enhancement suitable for clinical use.
There are a number of factors that may affect breast tissue background enhancement (7
). Background enhancement is known to be higher in premenopausal women. It also varies with the phase of the menstrual cycle, with the lowest level of background enhancement found in the early days of the cycle, although there has been some variation in study findings. A limitation of our study may be that despite selecting days 5–13 of the menstrual cycle for performing the MRI scans of all volunteers, the DCE-MRIs may have been taken in different phases of the menstrual cycle for people with irregular cycles (2/16 patients in our study). In a recent study Ellis suggested the measurement of serum progesterone levels to better synchronize DCE-MRI with the follicular phase in women who do not have regular menstrual cycle (16
). Monitoring hormone levels could help optimize the timing of MR examinations in the screening population. A few studies have suggested a potential correlation between background enhancement and breast density. As high breast density is a known strong factor of breast cancer risk, several authors hypothesized that dense breasts may exhibit higher levels of background enhancement, but results are mixed. While Arkani found a significant correlation between qualitative assessment of MR density and enhancement levels in his cohort of 185 normal volunteers (15
), others found no correlation (17
). Differences in results may also be attributed to the lack of systematic quantitative tools to assess density and enhancement levels in these studies. Some recent studies have shown that background enhancement does not to change with chemotherapy (18
Very few studies have investigated quantitative assessment of selective estrogen-receptor modulator (SERM) treatment effects and variation of these effects among patients. SERM treatments affect growth of cancer cells by blocking estrogen in the breast. Tamoxifen has been shown to reduce the risk of ductal and recurrent invasive breast cancer, and also to reduce the risk of contralateral breast cancer. In addition, long term tamoxifen therapy was shown to mildly decrease mammographic breast density (19
) however the measured changes varied among authors (20
). A small study described the reduction of unspecific DCE-MRI enhancement in a very small cohort of peri- and postmenopausal women (n=10) who were given 8 weeks of tamoxifen (8
). The MRIs were visually assessed in that small study.
The availability of a robust semi-automated tool to measure background enhancement in the breast could facilitate the use of tamoxifen as a much-needed short-term therapy to help reduce MRI false positive cases. As MRI is becoming more and more prevalent in screening high-risk patients and in breast cancer management, the ability to quantify normal enhancement and compare any changes to this baseline enhancement could have a huge impact on improving screening.
In addition, if breast tissue compositional and functional changes due to short-term treatment can be measured, the same technique could be used to study longer-term treatment effects. In particular it has been shown that the efficacy of long-term tamoxifen treatment efficacy decreases for certain patients after several years of treatment. Using our quantitative image analysis method on larger populations could potentially help assess when therapy has ceased to be effective in these patients to expedite the initiation of alternative therapy. Future larger studies will help test this hypothesis.
We have described our technique to measure global background enhancement in the normal breast. This technique is flexible and can also be utilized to evaluate MRI data from breast cancer patients. The segmentation allows the user to extract invasive tumor regions using the Signal Enhancement Ratio (SER) method described in (1
), in order to separate these regions from the fibroglandular volume under study. Therefore two enhancement measures can be produced, a level of enhancement in the tumor and a level of enhancement in the breast parenchyma around the tumor. Another key element for application of our technique to the clinic is its simplicity of use: it uses standard clinical breast MRI data producing a pre-contrast and 2 post-contrast injection of gadolinium data.
Our results also showed that qualitative visual interpretations provided by radiologists cover a wide range of background enhancement values (as measured with our novel technique) that often overlap, due to subjectivity in readings. This indicates the need for a more objective quantitative and clinically accessible technique to quantify background enhancement.
Our preliminary quantification tool has been defined and tested using a semi-automated technique requiring significant trained user interaction, which would limit its use in the clinic. However, further automation of our technique using a coronal orientation of the MRI volumes for the breast delineation has been shown to greatly decrease the background enhancement processing time to less than 3 minutes, which could be greatly reduced with the use of specific commercial platforms in the clinic. This automation allows for the development of a background enhancement measurement tool suitable for use in clinical MRI readings.
In conclusion, we have presented our novel, semi-automated segmentation tool that provides quantitative measures of background enhancement in breast MRI with application on the MRI data of 16 normal volunteers. This is a much-needed technique that may aid clinicians better quantify and understand the effects of background enhancement on the interpretation of breast MRI. Our technique also proved to be useful to measure treatment-induced changes in background enhancement in a high-risk patient following a 3-month tamoxifen treatment. This quantitative assessment may potentially be of interest in future studies evaluating the use of short-term SERM treatments as potential means to reduce background enhancement in addition to reducing cancer risk in premenopausal women. We believe that this work holds promise to better assess breast MRI, in particular for women with the type of breast tissue which displays multiple unspecific regions of enhancement.