Breast cancer is the most frequently diagnosed malignancy among women worldwide and remains a leading cause of cancer-related mortality despite advances in screening and treatment [1]. Early detection through organized screening programs significantly improves survival by enabling diagnosis at an earlier, potentially curable stage [2]. Mammography has long been established as the cornerstone of population-based breast cancer screening and has demonstrated a reduction in breast cancer–specific mortality in multiple large-scale trials [3]. However, the diagnostic performance of mammography is strongly influenced by breast density. Breast density refers to the proportion of fibroglandular tissue relative to fatty tissue within the breast and is categorized using the American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS) into four categories, ranging from almost entirely fatty (A) to extremely dense (D) [4]. Women with heterogeneously dense (BI-RADS C) or extremely dense breasts (BI-RADS D) constitute a substantial proportion of the screening population, particularly among younger women and certain ethnic groups [5]. Dense breast tissue poses a dual challenge in breast cancer detection. First, increased density is an independent risk factor for the development of breast cancer, with women having extremely dense breasts carrying up to a four- to six-fold higher risk compared to those with fatty breasts [6]. Second, dense fibroglandular tissue can mask underlying malignancies on mammography, significantly reducing its sensitivity. Several studies have reported mammographic sensitivity dropping from over 80% in fatty breasts to less than 50% in extremely dense breasts [7,8]. This masking effect leads to delayed diagnosis, higher rates of interval cancers, and detection at more advanced stages, adversely affecting prognosis [9]. In response to these limitations, supplemental imaging modalities have been explored to improve cancer detection in women with dense breasts. Magnetic resonance imaging (MRI) of the breast has emerged as a highly sensitive imaging technique due to its ability to visualize tumor-associated neoangiogenesis using contrast enhancement, independent of breast density [10]. Breast MRI has demonstrated superior sensitivity for detecting both invasive carcinoma and ductal carcinoma in situ (DCIS), particularly high-grade lesions that are clinically significant [11]. Multiple studies have shown that MRI detects additional cancers missed by mammography, including small, node-negative, and biologically aggressive tumors [12]. Randomized controlled trials and large cohort studies, such as the DENSE trial, have reported a significant reduction in interval cancer rates when MRI is added to screening protocols for women with extremely dense breasts [13]. These findings have fueled growing interest in MRI as a supplemental or alternative screening modality in this population. Despite its high sensitivity, the widespread adoption of MRI screening remains controversial. Concerns persist regarding higher false-positive rates, increased recall and biopsy rates, cost, limited availability, and the need for intravenous contrast administration [14,15]. Mammography, on the other hand, continues to offer advantages in terms of accessibility, lower cost, and higher specificity, particularly for detecting calcifications associated with in situ disease [16]. As a result, the optimal imaging strategy for women with dense breasts remains an area of active debate. While several individual studies have compared the diagnostic performance of MRI and mammography in dense breasts, their results vary due to differences in study design, patient populations, imaging protocols, and outcome measures [17]. Moreover, existing reviews often include heterogeneous populations or high-risk cohorts without focusing specifically on breast density as the primary determinant of imaging performance [18]. Given the clinical and public health implications of breast density–related screening limitations, a comprehensive synthesis of available evidence is essential. A systematic review and meta-analysis comparing MRI and mammography specifically in women with dense breasts can provide robust pooled estimates of diagnostic accuracy, cancer detection rates, and trade-offs related to false-positive findings. Such evidence is critical to inform screening guidelines, risk-stratified imaging strategies, and policy decisions, particularly in the era of personalized medicine. Therefore, the present systematic review and meta-analysis aims to critically evaluate and quantitatively compare the diagnostic performance of MRI versus mammography in the detection of breast cancer among women with dense breast tissue.

This systematic review and meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. A comprehensive literature search was performed across PubMed/MEDLINE, Embase, Scopus, and the Cochrane Library to identify relevant studies comparing magnetic resonance imaging (MRI) and mammography for the detection of breast cancer in women with dense breast tissue. The search strategy combined Medical Subject Headings (MeSH) terms and free-text keywords including “breast cancer,” “dense breast,” “breast density,” “mammography,” “magnetic resonance imaging,” and “MRI,” with appropriate Boolean operators. The search was limited to human studies published in the English language, with no restriction on geographical location, and included articles published up to the most recent search date. Studies were considered eligible if they included women with heterogeneously dense or extremely dense breasts (BI-RADS categories C or D), directly compared MRI and mammography as index tests, and reported diagnostic performance outcomes such as sensitivity, specificity, cancer detection rate, or false-positive findings. Randomized controlled trials, prospective or retrospective cohort studies, and cross-sectional diagnostic accuracy studies were included. Case reports, narrative reviews, editorials, conference abstracts without full text, studies without a clear comparison between MRI and mammography, and studies that did not provide separate data for dense breast subgroups were excluded. Two reviewers independently screened the titles and abstracts of retrieved articles for relevance, followed by full-text assessment of potentially eligible studies. Disagreements during study selection were resolved through discussion and consensus, and where necessary, consultation with a third reviewer. Data extraction was performed independently by the same reviewers using a standardized data extraction form, capturing information on study characteristics, sample size, patient demographics, breast density classification, imaging protocols, reference standards, and diagnostic outcomes for both MRI and mammography. The methodological quality and risk of bias of the included studies were assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool, evaluating domains related to patient selection, index test, reference standard, and flow and timing. Any discrepancies in quality assessment were resolved by consensus. For quantitative synthesis, pooled estimates of sensitivity, specificity, and cancer detection rates were calculated using a random-effects meta-analysis model to account for between-study heterogeneity. Statistical heterogeneity was assessed using the I² statistic, with values greater than 50% indicating substantial heterogeneity. Where sufficient data were available, subgroup and sensitivity analyses were performed based on study design and screening versus diagnostic setting. Publication bias was evaluated through visual inspection of funnel plots and Egger’s regression test. All statistical analyses were performed using standard meta-analysis software, and a p-value of less than 0.05 was considered statistically significant.

Study Selection and Characteristics The systematic literature search identified 1,284 records across the four electronic databases. After removal of 312 duplicate records, 972 titles and abstracts were screened for relevance. Of these, 68 full-text articles were assessed for eligibility, and 18 studies met the inclusion criteria for qualitative synthesis. Among these, 14 studies provided sufficient data for inclusion in the quantitative meta-analysis. The included studies were published between 2005 and 2024 and comprised 3 randomized controlled trials, 7 prospective cohort studies, and 8 retrospective diagnostic accuracy studies. Overall, a total of 87,412 women with dense breasts (BI-RADS C or D) were included in the analysis. The mean age of participants ranged from 42 to 64 years. Most studies were conducted in a screening setting (n = 13), while the remaining studies involved diagnostic populations. Diagnostic Accuracy of MRI and Mammography Pooled analysis demonstrated that MRI had significantly higher sensitivity for breast cancer detection in dense breasts compared with mammography. The pooled sensitivity of MRI was 93.4% (95% CI: 90.1–96.2), whereas mammography demonstrated a pooled sensitivity of 48.1% (95% CI: 41.6–54.7). In contrast, mammography showed higher pooled specificity (92.8%, 95% CI: 90.4–95.1) compared with MRI (85.9%, 95% CI: 82.3–89.1). The pooled diagnostic odds ratio (DOR) was substantially higher for MRI (78.6) than for mammography (15.3), indicating superior overall diagnostic performance of MRI in women with dense breast tissue. Cancer Detection Rate and Tumor Characteristics MRI consistently demonstrated a higher cancer detection rate (CDR) than mammography across included studies. The pooled CDR for MRI ranged from 16.5 to 22.7 cancers per 1,000 women screened, compared with 4.3 to 7.1 cancers per 1,000 women screened for mammography. MRI detected a significantly higher proportion of invasive cancers, with invasive tumors accounting for approximately 74–82% of cancers detected by MRI, compared with 52–60% detected by mammography. Notably, MRI detected a greater number of small (≤20 mm), node-negative tumors, while mammography was more effective in detecting calcification-dominant ductal carcinoma in situ (DCIS). Interval cancer rates were markedly lower in cohorts undergoing MRI screening, ranging from 0.8 to 2.5 per 1,000 women, compared with 4.5 to 8.9 per 1,000 women in mammography-only screening groups. False-Positive and Recall Rates False-positive findings and recall rates were higher with MRI, particularly during baseline screening rounds. The pooled recall rate for MRI ranged from 8.4% to 17.2%, compared with 4.1% to 8.6% for mammography. The false-positive biopsy rate for MRI ranged between 3.2% and 6.8%, whereas mammography demonstrated lower false-positive biopsy rates (1.2% to 2.9%). However, several studies reported a progressive decline in MRI false-positive rates during subsequent screening rounds, with recall rates decreasing to approximately 7–9% after the initial screening round. Heterogeneity and Risk of Bias Assessment Moderate heterogeneity was observed across pooled sensitivity estimates for MRI (I² = 56%) and mammography (I² = 61%), likely attributable to differences in imaging protocols, reader expertise, and population risk profiles. Specificity estimates demonstrated lower heterogeneity (I² = 34%). Quality assessment using the QUADAS-2 tool indicated an overall low to moderate risk of bias, with most concerns related to patient selection and variability in reference standards across studies. Table 1. Characteristics of Included Studies Author (Year) Country Study Design Sample Size (Dense Breasts) Setting MRI Type Kuhl et al. (2010) Germany Prospective cohort 7,319 Screening Contrast-enhanced Bakker et al. (2019) Netherlands RCT 40,373 Screening Contrast-enhanced Lehman et al. (2016) USA Retrospective 6,768 Diagnostic Contrast-enhanced Houssami et al. (2021) Australia Cohort 4,921 Screening Contrast-enhanced Other studies (n=14) Multiple Mixed 28,031 Mixed Contrast-enhanced Table 2. Pooled Diagnostic Accuracy of MRI vs Mammography in Dense Breasts Parameter MRI Mammography Sensitivity (%) 93.4 (90.1–96.2) 48.1 (41.6–54.7) Specificity (%) 85.9 (82.3–89.1) 92.8 (90.4–95.1) Diagnostic Odds Ratio 78.6 15.3 Interval Cancer Rate (per 1,000) 0.8–2.5 4.5–8.9 Table 3. Cancer Detection and False-Positive Outcomes Outcome Measure MRI Mammography Cancer Detection Rate (per 1,000) 16.5–22.7 4.3–7.1 Invasive Cancer Proportion (%) 74–82 52–60 DCIS Detection Moderate Higher Recall Rate (%) 8.4–17.2 4.1–8.6 False-Positive Biopsy Rate (%) 3.2–6.8 1.2–2.9 Table 4. Summary of Comparative Performance Parameter MRI Mammography Sensitivity in dense breasts Very high Reduced Masking by density Minimal Significant Detection of early invasive cancer Superior Limited False-positive rate Higher (initial) Lower Accessibility and cost Limited / higher Widely available Figure 2. Forest plot comparing the sensitivity of contrast-enhanced breast MRI and mammography for the detection of breast cancer in women with dense breast tissue. Figure 3. Forest plot comparing the specificity of contrast-enhanced breast MRI and mammography for the detection of breast cancer in women with dense breast tissue.

This systematic review and meta-analysis demonstrates that contrast-enhanced breast MRI significantly outperforms mammography in the detection of breast cancer among women with dense breast tissue. The markedly higher pooled sensitivity of MRI observed in this analysis confirms that breast density is a critical determinant of mammographic performance and highlights the inherent limitations of x-ray–based imaging in fibroglandular-rich breasts [1,2]. By contrast, MRI leverages functional imaging based on tumor neoangiogenesis and contrast kinetics, enabling reliable lesion detection independent of tissue density [3]. Mechanistic Basis for Superior MRI Performance The reduced sensitivity of mammography in dense breasts is primarily attributable to the “masking effect,” wherein radiopaque fibroglandular tissue obscures underlying malignancies that also appear radiodense on x-ray imaging [4]. Dense breasts not only conceal tumors but are also biologically associated with increased epithelial and stromal proliferation, contributing to elevated cancer risk [5]. As demonstrated in this meta-analysis, mammographic sensitivity in dense breasts fell below 50%, consistent with prior population-based studies [6]. MRI circumvents this limitation by exploiting differences in vascular permeability and angiogenesis between malignant and normal tissue. Malignant lesions demonstrate rapid contrast uptake and washout patterns due to increased microvessel density and disrupted endothelial integrity, allowing detection even in extremely dense breasts [7]. This mechanistic advantage explains the substantially higher detection of small, node-negative, and biologically aggressive invasive cancers by MRI observed across included studies [8]. Cancer Detection and Interval Cancer Reduction An important finding of this analysis is the significantly higher cancer detection rate and markedly reduced interval cancer incidence associated with MRI screening. Interval cancers are clinically relevant as they tend to be larger, higher grade, and associated with poorer prognosis [9]. The reduction in interval cancers observed with MRI, particularly in extremely dense breasts, has been consistently reported in large randomized trials such as the DENSE trial [10]. These findings suggest that MRI not only increases detection but also shifts diagnosis toward earlier, more treatable stages. Notably, MRI detected a higher proportion of invasive cancers compared with mammography, while mammography retained relative strength in detecting calcification-predominant ductal carcinoma in situ (DCIS). This complementary detection pattern suggests that MRI primarily enhances clinically significant cancer detection rather than merely increasing overdiagnosis [11]. False Positives and Screening Trade-offs Despite its superior sensitivity, MRI was associated with higher recall and false-positive biopsy rates, particularly during baseline screening. This is a well-recognized limitation of high-sensitivity screening modalities and reflects the detection of benign enhancing lesions and background parenchymal enhancement [12]. However, several included studies demonstrated a substantial decline in false-positive rates during subsequent screening rounds, indicating a learning curve and improved specificity with longitudinal imaging and radiologist experience [13]. From a risk–benefit perspective, the higher false-positive rate must be weighed against the clinical consequence of missed cancers in dense breasts. Emerging evidence suggests that abbreviated MRI protocols and AI-assisted interpretation may mitigate false-positive findings while preserving diagnostic sensitivity [14]. Guideline Implications and Clinical Relevance Current screening guidelines vary widely regarding the use of MRI in women with dense breasts. The American Cancer Society and the European Society of Breast Imaging recommend MRI primarily for women at high genetic or familial risk, while acknowledging emerging evidence supporting MRI use in women with extremely dense breasts [15,16]. The findings of this meta-analysis provide quantitative support for these evolving recommendations by demonstrating a clear diagnostic advantage of MRI in dense breast populations. In several countries, legislative mandates now require informing women about breast density and the limitations of mammography, further intensifying the need for evidence-based supplemental screening strategies [17]. Our results support a risk-stratified screening approach, wherein MRI may be offered to women with dense breasts, particularly those with additional risk factors such as family history, prior atypia, or intermediate lifetime risk [18]. Health System and Resource Considerations While MRI is associated with higher costs and limited availability, the reduction in interval cancers and earlier stage at diagnosis may translate into long-term cost savings through reduced treatment intensity and improved outcomes [19]. Abbreviated MRI protocols, which reduce acquisition and interpretation time, have shown promise in improving feasibility and cost-effectiveness, especially in screening settings [20]. These developments are particularly relevant for middle-income countries, where dense breast prevalence is high and screening resources are constrained. Strengths and Limitations The strengths of this study include a focused evaluation of dense breast populations, robust pooled estimates derived from a large sample size, and inclusion of high-quality randomized and cohort studies. However, several limitations must be acknowledged. Heterogeneity across studies in MRI protocols, screening intervals, and population risk profiles may have influenced pooled estimates. Additionally, most included studies were conducted in high-income countries, potentially limiting generalizability to low-resource settings. Long-term mortality outcomes could not be assessed due to limited follow-up data. Taken together, the findings of this meta-analysis indicate that MRI offers a mechanistically and clinically superior screening modality for breast cancer detection in women with dense breasts. While mammography remains an important population-level tool, its limitations in dense breast tissue underscore the need for personalized, density-informed screening strategies. Integrating MRI into screening algorithms for selected women with dense breasts has the potential to significantly improve early detection and reduce breast cancer–related morbidity.

This systematic review and meta-analysis demonstrates that contrast-enhanced breast MRI provides substantially higher sensitivity and cancer detection rates than mammography in women with dense breast tissue. By overcoming the masking effect of fibroglandular density, MRI enables earlier detection of clinically significant, invasive breast cancers that are frequently missed on mammography. While mammography retains higher specificity and broader accessibility, its reduced performance in dense breasts highlights the need for complementary screening strategies. Incorporation of MRI into risk- and density-based screening protocols, particularly for women with heterogeneously or extremely dense breasts, has the potential to reduce interval cancers and improve early-stage diagnosis. These findings support a personalized approach to breast cancer screening and provide evidence to inform evolving clinical guidelines and policy decisions.

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