Breast cancer (BC) is one of the most prevalent cancers and the leading cause of death among women [1]. Various advanced diagnostic techniques currently being used for the early detection and progression of BC have facilitated its precise and timely treatment [2, 3]. Among the most difficult aspects of diagnosing BC is distinguishing it from benign lesions, including breast fibroma, fibroadenosis, and lobular proliferation. In the vast majority of countries, mammography is employed to detect or screen for BC. It has a wide range of diagnostic applications; however, its clinical applicability is limited to breast tissue density. Because the breast tissue of young women and Asian women is dense in general, mammography may only provide limited information to distinguish benign from malignant breast tumors. Magnetic resonance imaging (MRI) has recently been used in the differential diagnosis and clinical research of BC, which not only adds to the diagnostic method but also raises several questions, such as how to combine these methods with other diagnostic tools to achieve precise diagnoses [4]. The quality of an MRI scan is less affected by breast density when compared to mammography and can distinguish between malignant and benign tumors with great accuracy. Furthermore, mammography may show more false positives than MRI test [4]. As a result, MRI was used to examine breast abnormalities, and studies showed that MRI may detect lesions in high-risk women that mammography or ultrasound fails to detect. In March 2007, the American Cancer Society published a guideline that recommended annual MRI screening for women with a lifetime risk of BC greater than 20–25 percent [5]. Various MRI-associated diagnostic protocols are incorporated for the analysis of BC in populations bearing high-risk screening, including the ULTRAFAST protocol, Digital Breast Tomosynthesis (DBT), Abbreviated MRI protocol (ABB-MRI), and Full Diagnostic Protocol MRI (FDP-MRI) [4]. The applicability of ABB-MRI protocol in BC detection has been evaluated in various independent studies and is by far considered an ideal approach with several advantages over other MRI diagnostic protocols. Besides offering comparable performance metrics, ABB-MRI requires only a few hours to complete the image acquisition cycle, thus allowing the screening of more patients each day as compared to the FDP-MRI [6]. Another potential advantage is that ABB-MRI can reduce the number of diagnostic tests needed for BC diagnosis, making it a powerful supplement for the treatment of BC [6]. Overall, the available data suggest that the ABB-MRI protocol has better applicability in BC screening and detection, considering its cost-effectiveness, short detection time, and comparable accuracy to the FDP protocol [6, 7, 8, 9, 10, 11, 12, 13, 14, 15]. It is a valid protocol utilized to examine preoperative staging and reduce the complexity of image acquisition [10]. Numerous studies have been performed to assess the diagnostic performance of MRI in the evaluation of breast lesions and therapeutic response to chemotherapy [4, 5, 16, 17, 18]. However, the patient characteristics, MRI techniques, and diagnostic criteria for malignancy in the studies differ substantially, which may have compromised the comparison of the diagnostic performance of breast MRI between the studies. As a result, a thorough evaluation of the diagnostic accuracy and characteristics of the MRI data is needed, which will help with the choice of breast imaging technologies and the interpretation of study outcomes. To provide strong validation to ABB-MRI, pooled data from independent studies, when combined inculcate convincing results highlighting the diagnostic power and accuracy of this technique. Meta-analysis is a quantitative and formal epidemiological study design used to systematically assess previous research studies to derive conclusions about that body of research [19]. It is useful in increasing the statistical power of the original and replicated studies. Pooling data from different independent studies and performing a meta-analysis on the pooled data helps to validate the specificity of the MRI technique in BC diagnosis. Our study aimed to perform a meta-analysis of the available data to check the accuracy of ABB-MRI in patients with breast lesions. The analysis will hopefully indicate if ABB-MRI detects the pathologic condition in BC patients with improved sensitivity and specificity.

Recently, Baxter et al. [11] performed a meta-analysis on data pooled from five screening and eight enriched cohort studies to compare ABB-MRI with FDP-MRI and concluded that no statistically significant difference exists between these two protocols in the diagnosis of BC. However, the authors reported a reduced specificity of both protocols in the pooled enriched cohort (0.83 and 0.84 in ABB-MRI and FDP-MRI, respectively) when compared with the pooled screening cohort (0.92 and 0.95 in ABB-MRI and FDP-MRI, respectively). Since then, more independent studies on ABB-MRI in BC detection have been published [13, 14, 15], all consistently demonstrating the advantage of ABB-MRI in BC detection and screening; therefore, these data clearly support the large-scale use of ABB-MRI-based BC screening, especially in women who have dense breast tissue for whom mammography is not sensitive enough to detect malignant BC. The current meta-analysis was performed by pooling all available data to evaluate the specificity and sensitivity of ABB-MRI with high statistical power due to increased patient number (n = 12,689). In addition to the studies included in the Baxter et al. [11] meta-analysis except for three studies that were published before 2017, we included eight more studies published between 2017–2022 in our meta-analysis, based on our inclusion criteria [8, 9, 10, 13, 14, 15, 23, 30]. The diagnostic testing mentioned in the meta-analysis primarily focused on the high efficiency offered by the ABB-MRI protocol considering sensitivity and specificity as widely used markers. We estimated a high specificity (0.90) and sensitivity (0.87) of ABB-MRI from our pooled dataset, which corroborates with a previous report [11]. We also made a comparison between screening and enriched cohorts, similar to Baxter et al. [11], and detected a specificity of 0.91 and a sensitivity of 0.75 in the screening cohort and a specificity of 0.77 and a sensitivity of 0.95 in the enriched cohort. These findings broadly corroborate with the Baxter et al. [11] meta-analysis; however, we observed a slightly low sensitivity in the screening cohort than in the enriched cohort (0.75 vs 0.95). This could be due to the increased sample size.

For breast cancer detection, mammography, a commonly used test, was found to be less sensitive (0.75) and specific (0.71) than MRI-based detection (sensitivity = 0.92 and specificity = 0.70) [2], suggesting a stronger discriminating power of MRI over mammography [32]. Since the development of the MRI technique as a diagnostic tool, many different variants have been developed, including ABB-MRI. ABB-MRI has a high specificity and sensitivity than mammography and is considered a valid diagnostic tool for future screening and BC characterization in enriched cohorts [10, 11]. Being less time-consuming, cost-effective, comparable in sensitivity and specificity to FDP-MRI, and superior to mammography, especially in women with dense breast tissue [15], ABB-MRI is gaining greater acceptance among clinicians for its faster interpretation time with high diagnostic accuracy. Comstock et al. [9] performed a comparative study between ABB-MRI and digital breast tomosynthesis (DBT) for BC detection in women with dense breast tissue and concluded that ABB-MRI significantly increased the detection rate compared with DBT. Similarly, data comparing ABB-MRI and full diagnostic MRI showed concurrence with the standard MRI protocols and were reliable enough to confer high diagnostic performance [11].

Based on the findings of this meta-analysis and many other similar previous studies, several diagnostic approaches can be used to guide therapeutic care: (1) Mammography is less expensive than MRI, despite its lower sensitivity; as a result, mammography will continue to be the gold standard in clinical BC imaging [32]. (2) MRI exams especially ABB-MRI should be prioritized for young women, taking into account the effects of ionizing radiation on the breasts and young women with a dense breast ratio and favorable physiological characteristics [33]. (3) The likelihood ratio (LR), which is a sensitivity-specificity ratio that better indicates the diagnostic test’s accuracy should be used. According to epidemiological studies, LR+ $>$10 is a positive value for BC diagnosis, while LR– $\le$0.1 is a negative value.

Findings-based diagnosis is the process of making the best diagnostic and treatment decisions for patients based on the “best” research results. Evidence-based medicine is the application of research findings to clinical practice to solve practical problems. When specific disease characteristics are found in BC, such as “refined salt calcification”, mammography has a higher sensitivity and specificity than other procedures. Mammography is also preferred when detecting microcalcification, as patients with ductal carcinoma in situ (DCIS) give better interpretation with mammography [34]. MRI, including ABB-MRI, should be used to generate soft tissue-rich anatomical images, as mammography has difficulty demonstrating a lesion in dense breast tissue. To improve diagnostic accuracy, breast lesions are being diagnosed utilizing a variety of integrated imaging technologies [34, 35]. Their diagnostic values differ, with each technique having its own advantages and disadvantages. Subgroup analysis may provide important information for diagnosis and identification in the future. The lack of benefit in terms of preventing additional surgery is particularly noteworthy in light of the rising rate of mastectomy associated with MRI use. Patients with a relatively limited disease on MRI scan should be more likely to require only one surgery for successful breast conservation and patients with a more extensive disease who have identified appropriately before surgery and undergo initial mastectomy, but this was not the case in the meta-analysis reported by Houssami et al. [36]. Preoperative MRI was linked to an increased likelihood of contralateral prophylactic mastectomy (CPM) for the secondary outcome [OR 1.91 (95% CI 1.25–2.91)] [36].

Breast cancer detection through MRI imaging is the most sensitive diagnostic tool, outperforming conventional detection techniques like mammography, digital breast tomography, or ultrasound. Interestingly, the use of MRI has dramatically increased since 2003, despite a lack of evidence that it is effective in newly diagnosed BC patients [37]. According to a recent survey of 377 surgeons (with a 77% response rate) who treated BC patients between 2013 and 2015, 26% would request an MRI for a basic, screen-detected clinical stage-1 BC, 60% for BC patients 45 years or younger, and 54% for triple-negative BC patients. Additionally, the survey also reported that 29% of responding surgeons incorrectly indicated that preoperative MRI minimizes the need for re-excision in patients undergoing breast-conserving surgery, and 41% stated that preoperative MRI does not increase the likelihood of mastectomy. These findings show that a significant number of surgeons are unaware of the lack of benefit of MRI on preoperative outcomes, underscoring the importance of more educational outreach to the surgical community, supported by a comprehensive and up-to-date synthesis of the literature. These data can also be used to help with the development of therapeutic recommendations for BC treatment.

Besides, ABB-MRI and FDP-MRI, many other MRI-based techniques are also used in BC detection. A meta-analysis of combined dynamic contrast-enhanced MRI and diffusion-weighted imaging for BC diagnosis was reported in 2016. Similarly, a recent meta-analysis was reported by Zhou et al. [37], who showed the combined sensitivity and specificity of dynamic contrast-enhanced MRI (DCE-MRI) were 93.2% and 71.1%, respectively. The area under the curve for the SROC was 0.85. According to this meta-analysis, which is consistent with previous findings on the issue, the combined diagnostic sensitivity, specificity, and AUC-SROC were 0.87, 0.74, and 0.86, respectively [37]. The accuracy of diagnosing malignant and benign lesions was greatly improved after receiving a DCE-MRI scan. As a result of the higher diagnostic accuracy, a breast biopsy may be avoided [4].

The heterogeneity between groups and studies and the fact that most studies used a comparator group rather than randomization are all limitations of this meta-analysis. As a result, bias and confounding cannot be eliminated, and the interpretation of our findings should take this heterogeneity into account. Although we searched for but were unable to find unpublished data, the possibility of publication bias could not be ruled out due to the non-inclusion of such data if available. Due to the restrictions imposed by the basic data from the included studies, additional subgroup analysis was avoided. In addition, the ability to make statistical adjustments was limited by variability in the reporting of study-level data on variables such as age and tumor size. To account for the observed variance in the median or mean age across some of the nonrandomized trials, we employed stratification around the median study-level aggregate age in our core analysis (studies of all BC histological classifications).

The present meta-analysis focused on the utilization of highly efficient ABB-MRI protocol for improved diagnosis of BC with high sensitivity and specificity at low cost and high turnover rate, indicating advanced detection rates for better breast cancer treatment outcomes. This pooled analysis and other similar analyses convincingly prove the importance of ABB-MRI as a useful supplement for advanced breast cancer treatment. Growing interest enables improved validation of these parameters, including ABB-MRI in future trials, to screen cancer patients. However, before its routine use in clinical practice, ABB-MRI protocol needs further improvisation, standardization across various platforms, and validation by prospective multicenter clinical trials [38, 39]. Future studies should focus on assessing the application of ABB-MRI in the detection of breast cancer stages, which will improve the quality of life of these patients through fast and cost-effective precise detection of the cancer stage. Nevertheless, it is believed that ABB-MRI will gain traction not only for providing advanced diagnosis and treatment of breast cancer but will serve as a useful tool in decreasing the incidence of late-stage breast cancer-related complications, consequently reducing the risk of mortality.

BZ, WH, and JK performed the literature search, data compilation, and analyses and wrote the first draft. QC, AB, and QL reviewed the literature and edited the manuscript. QL conceived the project. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript. All authors have participated sufficiently in the work to take public responsibility for appropriate portions of the content and agreed to be accountable for all aspects of the work in ensuring that questions related to its accuracy or integrity.

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This research received no external funding.

The authors declare no conflict of interest.