Effect of menstrual cycle phase on background parenchymal uptake at molecular breast imaging

Enhancing the Understanding of Breast Vascularity Through Insights From Dynamic Contrast-Enhanced Magnetic Resonance Imaging: A Comprehensive Review

Breast vascularity plays a crucial role in both physiological and pathological processes, particularly in the development and progression of breast cancer. Understanding vascular changes within breast tissue is essential for accurate diagnosis, treatment planning, and monitoring therapeutic response. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has emerged as a valuable tool for evaluating breast vascularity due to its ability to provide detailed functional and morphological insights. DCE-MRI utilizes contrast agents to highlight blood flow and vessel permeability, making it especially useful in differentiating between benign and malignant lesions. This review explores the significance of DCE-MRI in breast vascularity assessment, highlighting its principles, clinical applications, and role in detecting malignancy through vascular changes. We also examine its utility in monitoring treatment response and quantitative analysis of perfusion metrics such as Ktrans and extracellular-extravascular volume (Ve). While DCE-MRI offers remarkable diagnostic accuracy, challenges remain regarding its cost, accessibility, and potential overlap of enhancement patterns between benign and malignant conditions. The review further discusses emerging technologies and future directions for DCE-MRI, including advanced imaging techniques and machine learning-based quantification. Overall, DCE-MRI stands out as a powerful tool in the comprehensive evaluation of breast vascularity, with significant potential to improve patient outcomes in breast cancer management.

Advances and Future Directions in Molecular Breast Imaging

Molecular breast imaging (MBI) using 99mTc-sestamibi has advanced rapidly over the past decade. Technical advances allow lower-dose, higher-resolution imaging and biopsy capability. MBI can be used for supplemental breast cancer screening with mammography for women with dense breasts, as well as to assess neoadjuvant therapy response, evaluate disease extent, and predict breast cancer risk. This article highlights the current state of the art and future directions in MBI.

Background parenchymal enhancement and uptake as breast cancer imaging biomarkers: A state-of-the-art review

Within the past decade, background parenchymal enhancement (BPE) and background parenchymal uptake (BPU) have emerged as novel imaging-derived biomarkers in the diagnosis and treatment monitoring of breast cancer. Growing evidence supports the role of breast parenchyma vascularity and metabolic activity as probable risk factors for breast cancer development. Furthermore, in the presence of a newly-diagnosed breast cancer, added clinically-relevant data was surprisingly found in the respective imaging properties of the non-affected contralateral breast. Evaluation of the contralateral BPE and BPU have been found to be especially instrumental in predicting the prognosis of a patient with breast cancer and even anticipating their response to neoadjuvant chemotherapy. Simultaneously, further research has found a link between these two biomarkers, even though they represent different physical properties. The aim of this review is to provide an up to date summary of the current clinical applications of BPE and BPU as breast cancer imaging biomarkers with the hope that it propels their further usage in clinical practice.

Background Parenchymal Uptake on Molecular Breast Imaging and Breast Cancer Risk: A Cohort Study

BACKGROUND. Background parenchymal uptake (BPU) on molecular breast imaging (MBI) was identified in a case-control study as a breast cancer risk factor beyond mammographic density. To our knowledge, this finding has not yet been confirmed in a cohort study. OBJECTIVE. The objectives of this study were to examine the association of BPU with breast cancer and to estimate the absolute risk and discriminatory accuracy of BPU in a cohort study. METHODS. A retrospective cohort was established that included women without a history of breast cancer who underwent MBI from 2004 to 2015. Radiologists who were blinded to future breast cancer diagnoses assessed BPU on baseline MBI examinations as low (photopenic or minimal) or elevated (mild, moderate, or marked). Associations of BPU with breast cancer were estimated using multivariable Cox proportional hazards models of the time to diagnosis. The 5-year absolute risk was calculated for study subgroups. The discriminatory accuracy of BPU was also assessed. RESULTS. Among 2992 women (mean age, 56.3 years; SD, 10.6 years) who underwent MBI, breast cancer events occurred in 144 women (median follow-up, 7.3 years). Median time to diagnosis after MBI was 4.2 years (range, 0.5-11.6 years). Elevated BPU was associated with a greater breast cancer risk (hazard ratio [HR], 2.39; 95% CI, 1.68-3.41; p ≤ .001). This association remained in postmenopausal women (HR, 3.50; 95% CI, 2.31-5.31; p < .001) but was not significant in premenopausal women (HR, 1.29; 95% CI, 0.72-2.32; p = .39). The 5-year absolute risk of breast cancer was 4.3% (95% CI, 2.9-5.7%) for women with elevated BPU versus 2.5% (95% CI, 1.8-3.1%) for those with low BPU. Postmenopausal women with dense breasts and elevated BPU had a 5-year absolute risk of 8.1% (95% CI, 4.3-11.8%) versus 2.8% (1.8-3.8%) for those with low BPU. Among postmenopausal women, discriminatory accuracy for invasive cancer was improved with the addition of BPU versus use of the Gail risk score alone (C statistic, 65.1 vs 59.1; p = .04) or use of the Breast Cancer Surveillance Consortium risk score alone (C statistic, 66.4 vs 60.4; p = .04). CONCLUSION. BPU on MBI is an independent risk factor for breast cancer, with the strongest association observed among postmenopausal women with dense breasts. In postmenopausal women, BPU provides incremental discrimination in predicting breast cancer when combined with either the Gail model or the Breast Cancer Surveillance Consortium model. CLINICAL IMPACT. Observation of elevated BPU on MBI may identify a subset of women with dense breasts who would benefit most from supplemental screening or preventive options.

99mTC-sestamibi breast imaging: Current status, new ideas and future perspectives

Here we proposed the most recent innovations in the use of Breast Specific Gamma Imaging with ⁹⁹mTc-sestamibi for the management of breast cancer patients. To this end, we reported the recent discoveries concerning: a) the implementation of both instrumental devices and software, b) the biological mechanisms involved in the ⁹⁹mTc-sestamibi uptake in breast cancer cells, c) the evaluation of Breast Specific Gamma Imaging with ⁹⁹mTc-sestamibi as predictive markers of metastatic diseases. In this last case, we also reported preliminary data about the capability of Breast Specific Gamma Imaging with ⁹⁹mTc-sestamibi to identify breast cancer lesions with high propensity to form bone metastatic lesions due to the presence of Breast Osteoblast-Like Cells.

Impact of short-term low-dose tamoxifen on molecular breast imaging background parenchymal uptake: a pilot study

BACKGROUND

High background parenchymal uptake (BPU) on molecular breast imaging (MBI) has been identified as a breast cancer risk factor. We explored the feasibility of offering a short-term intervention of low-dose oral tamoxifen to women with high BPU and examined whether this intervention would reduce BPU.

METHODS

Women with a history of high BPU and no breast cancer history were invited to the study. Participants had an MBI exam, followed by 30 days of low-dose oral tamoxifen at either 5 mg or 10 mg/day, and a post-tamoxifen MBI exam. BPU on pre- and post-tamoxifen MBI exams was quantitatively assessed as the ratio of average counts in breast fibroglandular tissue vs. average counts in subcutaneous fat. Pre-tamoxifen and post-tamoxifen BPU were compared with paired t tests.

RESULTS

Of 47 women invited, 22 enrolled and 21 completed the study (10 taking 5 mg tamoxifen, 11 taking 10 mg tamoxifen). Mean age was 47.7 years (range 41-56 years). After 30 days low-dose tamoxifen, 8 of 21 women (38%) showed a decline in BPU, defined as a decrease from the pre-tamoxifen MBI of at least 15%; 11 of 21 (52%) had no change in BPU (within ± 15%); 2 of 21 (10%) had an increase in BPU of greater than 15%. Overall, the average post-tamoxifen BPU was not significantly different from pre-tamoxifen BPU (1.34 post vs. 1.43 pre, p = 0.11). However, among women taking 10 mg tamoxifen, 5 of 11 (45%) showed a decline in BPU; average BPU was 1.19 post-tamoxifen vs. 1.34 pre-tamoxifen (p = 0.005). In women taking 5 mg tamoxifen, 2 of 10 (20%) showed a decline in BPU; average BPU was 1.51 post-tamoxifen vs.1.53 pre-tamoxifen (p = 0.99).

CONCLUSIONS

Short-term intervention with low-dose tamoxifen may reduce high BPU on MBI for some patients. Our preliminary findings suggest that 10 mg tamoxifen per day may be more effective than 5 mg for inducing declines in BPU within 30 days. Given the variability in BPU response to tamoxifen observed among study participants, future study is warranted to determine if BPU response could predict the effectiveness of tamoxifen for breast cancer risk reduction within an individual.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02979301 . Registered 01 December 2016.

Breast Lesions Detected via Molecular Breast Imaging: Physiological Parameters Affecting Interpretation

RATIONALE AND OBJECTIVES

To evaluate correlations between molecular breast imaging (MBI) descriptor characteristics and positive predictive value (PPV) in detecting breast cancer.

MATERIALS AND METHODS

A retrospective review was performed on 193 suspicious findings from 153 women (31-81 years) with positive MBI examinations. We assessed associations between (i) lesion pattern (mass vs. nonmass) and PPV; (ii) lesion pattern and suspected likelihood of cancer (low vs. moderate vs. high); (iii) background parenchymal uptake (BPU) (homogeneous vs. heterogeneous) and PPV; (iv) breast density (dense vs. non-dense) and PPV; and (v) BPU and density.

RESULTS

One hundred ten of 153 patients were diagnosed with malignancy or high-risk pathology (PPV1 = 71.9%), and 130/193 biopsies resulted in malignant or high-risk lesions (PPV3 = 67.4%). Biopsies of mass vs. nonmass findings had comparable PPV3 (71.7% vs. 61.3%; P = .0717). Mass findings were correlated with higher suspicion for cancer than nonmass findings (P < .001). There was no significant difference in PPV3 when comparing biopsies from homogeneous vs. heterogeneous BPU (72.5% vs. 60.7%; P = .103). No association was found between patients' BPU and diagnosed cancer or high-risk lesions (P = .513). Biopsies from nondense breasts demonstrated higher PPV3 than biopsies from dense breasts (85.4% vs. 60.6%; P = .0025); patients with nondense breasts were more likely to be diagnosed with cancer or high-risk pathology (PPV1 = 87.8% vs. 66.0%; P = .00844). Dense breasts had a greater association with heterogeneous BPU (P = .0844).

CONCLUSION

Neither variability in mass or nonmass positive MBI findings, nor variability in BPU on MBI were significant determinants for the probability of malignancy. Dense breasts were associated with lower predictability and heterogeneous BPU on MBI.

Quantitative background parenchymal uptake on molecular breast imaging and breast cancer risk: a case-control study

BACKGROUND

Background parenchymal uptake (BPU), which refers to the level of Tc-99m sestamibi uptake within normal fibroglandular tissue on molecular breast imaging (MBI), has been identified as a breast cancer risk factor, independent of mammographic density. Prior analyses have used subjective categories to describe BPU. We evaluate a new quantitative method for assessing BPU by testing its reproducibility, comparing quantitative results with previously established subjective BPU categories, and determining the association of quantitative BPU with breast cancer risk.

METHODS

Two nonradiologist operators independently performed region-of-interest analysis on MBI images viewed in conjunction with corresponding digital mammograms. Quantitative BPU was defined as a unitless ratio of the average pixel intensity (counts/pixel) within the fibroglandular tissue versus the average pixel intensity in fat. Operator agreement and the correlation of quantitative BPU measures with subjective BPU categories assessed by expert radiologists were determined. Percent density on mammograms was estimated using Cumulus. The association of quantitative BPU with breast cancer (per one unit BPU) was examined within an established case-control study of 62 incident breast cancer cases and 177 matched controls.

RESULTS

Quantitative BPU ranged from 0.4 to 3.2 across all subjects and was on average higher in cases compared to controls (1.4 versus 1.2, p < 0.007 for both operators). Quantitative BPU was strongly correlated with subjective BPU categories (Spearman's r = 0.59 to 0.69, p < 0.0001, for each paired combination of two operators and two radiologists). Interoperator and intraoperator agreement in the quantitative BPU measure, assessed by intraclass correlation, was 0.92 and 0.98, respectively. Quantitative BPU measures showed either no correlation or weak negative correlation with mammographic percent density. In a model adjusted for body mass index and percent density, higher quantitative BPU was associated with increased risk of breast cancer for both operators (OR = 4.0, 95% confidence interval (CI) 1.6-10.1, and 2.4, 95% CI 1.2-4.7).

CONCLUSION

Quantitative measurement of BPU, defined as the ratio of average counts in fibroglandular tissue relative to that in fat, can be reliably performed by nonradiologist operators with a simple region-of-interest analysis tool. Similar to results obtained with subjective BPU categories, quantitative BPU is a functional imaging biomarker of breast cancer risk, independent of mammographic density and hormonal factors.

BEST PRACTICES IN MOLECULAR BREAST IMAGING: A GUIDE FOR TECHNOLOGISTS

Molecular breast imaging (MBI) technologists are required to possess a combination of nuclear medicine skills and mammographic positioning techniques. Currently, no formal programs offer this type of hybrid technologist training. The purpose of this perspective is to provide a best practices guide for technologists performing MBI. Familiarity with best practices may aid in obtaining high-quality MBI examinations by decreasing the likelihood of image artifacts, positioning problems and other factors that contribute to false negative or false positive findings.

Breast Imaging Utilizing Dedicated Gamma Camera and (99m)Tc-MIBI: Experience at the Tel Aviv Medical Center and Review of the Literature Breast Imaging

The scope of the current article is the clinical role of gamma cameras dedicated for breast imaging and (99m)Tc-MIBI tumor-seeking tracer, as both a screening modality among a healthy population and as a diagnostic modality in patients with breast cancer. Such cameras are now commercially available. The technology utilizing a camera composed of a NaI (Tl) detector is termed breast-specific gamma imaging. The technology of dual-headed camera composed of semiconductor cadmium zinc telluride detectors that directly converts gamma-ray energy into electronic signals is termed molecular breast imaging. Molecular breast imaging system has been installed at the Department of Nuclear medicine at the Tel Aviv Sourasky Medical Center, Tel Aviv in 2009. The article reviews the literature well as our own experience.

Background parenchymal uptake on molecular breast imaging as a breast cancer risk factor: a case-control study

BACKGROUND

Molecular breast imaging (MBI) is a functional test used for supplemental screening of women with mammographically dense breasts. Additionally, MBI depicts variable levels of background parenchymal uptake (BPU) within nonmalignant, dense fibroglandular tissue. We investigated whether BPU is a risk factor for breast cancer.

METHODS

We conducted a retrospective case-control study of 3027 eligible women who had undergone MBI between February 2004 and February 2014. Sixty-two incident breast cancer cases were identified. A total of 179 controls were matched on age, menopausal status, and MBI year. Two radiologists blinded to case status independently assessed BPU as one of four categories: photopenic, minimal to mild, moderate, or marked. Conditional logistic regression analysis was performed to estimate the associations (OR) of BPU categories (moderate or marked vs. minimal to mild or photopenic) and breast cancer risk, adjusted for other risk factors.

RESULTS

The median age was 60.2 years (range 38-86 years) for cases vs. 60.2 years (range 38-88 years) for controls (p = 0.88). Women with moderate or marked BPU had a 3.4-fold (95 % CI 1.6-7.3) and 4.8-fold (95 % CI 2.1-10.8) increased risk of breast cancer, respectively, compared with women with photopenic or minimal to mild BPU, for two radiologists. The results were similar after adjustment for BI-RADS density (OR 3.3 [95 % CI 1.6-7.2] and OR 4.6 [95 % CI 2.1-10.5]) or postmenopausal hormone use (OR 3.6 [95 % CI 1.7-7.7] and OR 5.0 [95 % CI 2.2-11.4]). The association of BPU with breast cancer remained in analyses limited to postmenopausal women only (OR 3.8 [95 % CI 1.5-9.3] and OR 4.1 [95 % CI 1.6-10.2]) and invasive breast cancer cases only (OR 3.6 [95 % CI 1.5-8.8] and OR 4.4 [95 % CI 1.7-11.1]). Variable BPU was observed among women with similar mammographic density; the distribution of BPU categories differed across density categories (p < 0.0001).

CONCLUSIONS

This study provides the first evidence for BPU as a risk factor for breast cancer. Among women with dense breasts, who comprise >40 % of the screening population, BPU may serve as a functional imaging biomarker to identify the subset at greatest risk.