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Abstract
Objective The objective is to evaluate the diagnostic effectiveness of contrast-enhanced spectral mammography (CESM) in the diagnosis of breast cancer.
Data sources PubMed, Embase and Cochrane libraries up to 18 June 2022.
Eligibility criteria for selecting studies We included trials studies, compared the results of different researchers on CESM in the diagnosis of breast cancer, and calculated the diagnostic value of CESM for breast cancer.
Data extraction and synthesis Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) evaluated the methodological quality of all the included studies. The study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses specification. In addition to sensitivity and specificity, other important parameters were explored in an analysis of CESM accuracy for breast cancer diagnosis. For overall accuracy estimation, summary receiver operating characteristic curves were calculated. STATA V.14.0 was used for all analyses.
Results This meta-analysis included a total of 12 studies. According to the summary estimates for CESM in the diagnosis of breast cancer, the pooled sensitivity and specificity were 0.97 (95% CI 0.92 to 0.98) and 0.76 (95% CI 0.64 to 0.85), respectively. Positive likelihood ratio was 4.03 (95% CI 2.65 to 6.11), negative likelihood ratio was 0.05 (95% CI 0.02 to 0.09) and the diagnostic odds ratio was 89.49 (95% CI 45.78 to 174.92). Moreover, there was a 0.95 area under the curve.
Conclusions The CESM has high sensitivity and good specificity when it comes to evaluating breast cancer, particularly in women with dense breasts. Thus, provide more information for clinical diagnosis and treatment.
- breast imaging
- breast tumours
- diagnostic radiology
Data availability statement
Data sharing not applicable as no datasets generated and/or analysed for this study.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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STRENGTHS AND LIMITATIONS OF THIS STUDY
This systematic review was a comprehensive search of experimental and observational studies on contrast-enhanced spectral mammography (CESM) in the diagnosis of breast cancer.
We included only prospective studies. Prospective studies were of higher quality with less bias, and our study screening criteria were developed prior to the meta-analysis.
The study was conducted by two people and was strictly based on inclusion criteria.
The data in this study were summarised using sound statistical methods.
A recent literature was added, and a literature from the same institution included only the most recent or the largest sample size.
We summarised the sensitivity and specificity of CESM in the diagnosis of breast cancer.
Introduction
Globally, female breast cancer has overtaken lung cancer as the leading cause of cancer death, making it the fifth most common cause of death.1 From the mid-20th century, the incidence of breast cancer in women has been increasing slowly by about 0.5% per year.2 At present, the diagnostic methods of breast cancer include MRI, full field digital mammography (FFDM) and ultrasound (US). MRI is the most sensitive examination in the diagnosis of breast cancer at present.3 However, it has some disadvantages such as no claustrophobic and high price. In addition, although FFDM is an effective diagnostic method for breast cancer, it also has the hazard of recall and needs further testing.4 Ultrasonography has good diagnostic efficacy for breast cancer, especially in women with dense breasts; however, it has a relatively low positive predictive value.5 Contrast-enhanced spectral mammography (CESM), which visualises breast neovascularisation in a manner similar to MRI, is an emerging technology that uses iodine contrast agent.6 CESM has the advantages of patient friendliness and low cost. Previous studies have shown that CESM has obvious advantages in displaying lesions compared with US. The advantage of CESM is that it can show changes in anatomy and local blood perfusion, which may be caused by tumour angiogenesis.7 Moreover, CESM is useful in detecting the suspicious findings in routine breast imaging7 and the sensitivity and specificity of CESM are different in different studies.
It has been reported that several meta-analyses have been conducted regarding the diagnostic performance of CESM for breast cancer; however, their pooled results were different and had several limitations.8–11 On the one hand, the sensitivity and specificity differed across the above-mentioned meta-analyses.8 10 11 On the other hand, the numbers of included studies were limited. In addition, partial meta-analyses included none-English studies and overlapped studies, which might affect their pooled results. In the past few years, several studies evaluating the diagnostic value of CESM in breast cancer have been published. Therefore, we conducted this meta-analysis using available evidence to comprehensively determine whether CESM is effective in detecting breast cancer in women.
Material and methods
As recommended by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), we conducted our study followed the PRISMA specification,12 which met the requirements of diagnostic systematic review.
Search strategy
To evaluate the accuracy of CESM in diagnosing breast cancer, we retrieved the following databases: PubMed, Embase and Cochrane library. Two reviewers, JL and RX, independently searched the above databases up to the date of 18 June 2022. Our searching terms included ‘contrast-enhanced spectral mammography’, ‘Dual-Energy Contrast-Enhanced Spectral Mammography’, ‘CESM’, ‘contrast-enhanced digital mammography’, ‘CEDM’, ‘Breast Neoplasms’, ‘Breast Neoplasm’, ‘Breast Tumor’, ‘Breast Tumors’, ‘Breast Cancer’, ‘Malignant Neoplasm of Breast’, ‘Breast Malignant Neoplasm’, ‘Breast Carcinomas’, ‘Breast Carcinoma’, ‘breast mass’, ‘breast lesion’, ‘breast lesions’, ‘breast diseases’. In addition, the references of all the included studies were also reviewed.
Inclusion and exclusion criteria
Following is the list of inclusion criteria: (1) studies diagnosing breast cancer, (2) studies provided data on the sensitivity and specificity, (3) studies involving ≥10 patients or case, (4) English language and(5) prospective studies. Following is the list of exclusion criteria: (1) overlapped research, (2) commentaries, letters, editorials or abstracts or (3) studies referencing artificial intelligence and radiomics.
Study screening
The titles and abstracts of the literature in the electronic databases were initially screened by two authors, following the above criteria for inclusion and exclusion. Each of the two researchers screened two times to avoid omission. If there is any disagreement, the third author was consulted to decide. Eligibly downloaded full texts and further screened. First, if the authors and institutions of the study are the same, we will include the most recently published studies with the largest sample size. If the research institutions are the same, but the authors are different, we will send an email to the corresponding authors to ask. If we do not receive a reply, we will include the most recently published studies having the largest sample size.
Data abstraction
Two reviewers extracted data. If necessary, the difference shall be solved by the third reviewer. Each study was analysed for the following information: first author name, publication year, country, the numbers of patients and lesions, median age, the results of true positive (TP), false positive (FP), false negative (FN) and true negative (TN).
Quality assessment
The quality of the methodology included in the publication was assessed by the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2).13 QUADAS-2 were mainly focused on the following four domains: patient selection, index test, reference standard and flow and timing, with minimal overlapping, which present the main quality of the diagnostic study. Each domain is assessed according to risk of bias, with the three domains assessed according to applicability. The risk of bias was considered low if the study met the above criteria and high otherwise. Disagreements between the two reviewers on quality assessment were resolved by consensus.
Statistical analysis
STATA V.14.0 was used for all analyses. I2 measure was used to quantify the heterogeneity between studies. If there is no statistical heterogeneity, the fixed effect model is used to consolidate the data. On the contrary, the random effect model is used to summarise the data. The sensitivity was shown in the form TP/(TP+FN), where TP represents the number of true-positive results and FN represent the number of FN results. The specificity was shown in the form TN/(TN+FP), where TN represent the number of TN results and FP represent the number of FN results.14 We also computed other significant measures on the evaluation of diagnostic experiments such as positive likelihood ratio (PLR) and negative likelihood ratio (NLR) and diagnostic OR (DOR). The summary receiver operating characteristic curve ROC (SROC) curve and the area under the curve (AUC) of the SROC curve were also computed.
Results
Study characteristics
After a systematic search, we included 12 studies.15–26 The complete selection process is in detail in PRISMA flowchart (figure 1). From 544 screened studies, 85 studies were subjected to full text reading. The characteristics of all the 12 included studies are shown in table 1. These 12 studies are all prospective studies published between 2014 and 2022. Most patients had US, mammography and related examinations before CESM examination. The dense breast we collected account for approximately two-thirds. In addition, the methodological quality assessment of all included studies was shown in online supplemental table 1.
Supplemental material
Study characteristics of each included study
The figure shows the workflow for study screening and selection. CESM, contrast-enhanced spectral mammography.
Diagnostic accuracy of CESM
The sensitivity and specificity values were shown in Forest plots (figure 2). A very high pooled test sensitivity of 0.97 (95% CI 0.92 to 0.98) was estimated. The pooled specificity was 0.76 (95% CI 0.64 to 0.85). The PLR was 4.03 (95% CI 2.65 to 6.11), NLR was 0.05 (95% CI 0.02 to 0.09) (figure 3) and DOR was 89.49 (95% CI 45.78 to 174.92) (online supplemental figure 1). I2 values of sensitivity, specificity, PLR, NLR and DOR were 76.60%, 87.95%, 86.25%, 65.73% and 99.78%, respectively.
Supplemental material
Forest plot of estimates of sensitivity and specificity for contrast-enhanced spectral mammography in the diagnosis of breast cancer.
Forest plot of estimates of positive likelihood ratio and negative likelihood ratio for contrast-enhanced spectral mammography in the diagnosis of breast cancer.
As shown in figure 4, the SROC curve shows an AUC of 0.95 (0.93 to 0.97). CI is an interval estimation based on the average point estimation. The prediction interval is the interval estimation based on the individual value point estimation.
The plot shows the summary bivariate ROC curve for CESM diagnostic accuracy. AUC, area under the curve; CESM, contrast-enhanced spectral mammography; ROC, receiver operating characteristic curve; SENS, sensitivity; SPEC, specificity; SROC, summary receiver operating characteristic curve.
A confidence contour and a prediction contour were shown in the figure.
Fagan plots were drawn to understand the prior probability (current incidence) and the posterior probability (incidence estimated from this diagnostic experiment). In our sample, the pretest probability of malignancy was 50%, with a positive finding at CESM a post-test probability of 80% while a negative finding a post-test probability of 4% (online supplemental figure 2).
Supplemental material
Regression analysis
We analysed some covariates (number of lesions, number of patients, being dense breast or not, year of publication) possible influence on the diagnostic accuracy of CESM. The regression analysis showed that the sensitivity of the studies that only included dense breast was different from that of other studies, but both were high (online supplemental figure 3). In addition, a limited number of studies were included, which reduced the reliability of the regression analysis.
Supplemental material
Publication bias
A funnel plot drawn with Stata V.14.0 software was used to analyse the publication bias of the included studies (online supplemental figure 4). The included studies were evenly distributed on both sides of the regression line, showing that the included literatures had no obvious publication bias (p=0.78).
Supplemental material
Discussion
CESM is emerging as a valuable tool for the diagnosis and staging of breast cancer. CESM combines the contrast enhancement effect caused by tumour neovascularisation with the information of anatomical changes. The lesions were highlighted by reciprocal subtraction of the images, which further increased the sensitivity of CESM for the diagnosis of breast cancer. It improves the accuracy in diagnosing breast cancer, providing more accurate tumour size and identification of multifocal disease, especially in patients with the dense type of breast.27
Results showed that the pooled sensitivity (0.97, 95% CI 0.92 to 0.98) was higher and the pooled specificity (0.76, 95% CI 0.64 to 0.85) was slightly lower than a previous meta-analysis9 which indicated a pooled sensitivity of 0.89 (95% CI 0.88 to 0.91) and a pooled specificity of 0.84 (95% CI 0.82 to 0.85). The reason for the high sensitivity may be that our study went through more rigorous study screening, included the latest literature, and CESM has been increasingly used in clinical practice in recent years. Another point is that all the studies we included are prospective studies, which are less susceptible to bias than retrospective studies. Another previous meta-analysis8 has obtained that CESM has high sensitivity for the diagnosis of breast cancer, but it has low specificity. This may be due to the following reasons: three studies included by the meta-analysis were similar and written by the same first author; the meta-analysis only included eight studies and the pooled specificity were obtained by six literatures. All the reasons may result in some bias. However, during our screening, there are five studies from the same authors15 28–31 and with similar results, we only included one in which the study type was prospective and with large sample size and longest time span.
In addition, compared with other studies, this study included the latest studies in recent years, and conducted a more rigorous article screening, with each of the two researchers screening two times.
The DOR is a common statistic in epidemiology that expresses the strength of the association between exposure and disease.32 The diagnostic DOR for a test is the ratio of the odds of being positive in the disease to the odds of being positive in the non-disease. In our meta-analysis, the DOR was 89.49 (95% CI45.78 to 174.92), which was high. It indicated that if CESM showed a positive result, the probability of a true breast cancer being correctly diagnosed was 89.49 to 1. DOR offers considerable advantages in a meta-analysis of diagnostic studies by combining results from different studies into a more precise pooled estimate. The I2 statistic, also known as the inconsistency index, is a measure of heterogeneity or variability across studies in a meta-analysis. It quantifies the proportion of total variation in effect estimates that is due to heterogeneity rather than chance. Differences in study populations: the studies included in the meta-analysis may have varied in terms of patient characteristics, such as age, mammary gland type, disease severity or comorbidities. These differences can contribute to heterogeneity in the estimated DOR. Clinical and contextual factors: heterogeneity in DOR can also arise from differences in the clinical context, such as variations in disease prevalence, healthcare settings or geographic locations.
The SROC curve method takes into account the possible heterogeneity of thresholds.33 The SROC indicates the relationship between the TP rate and FP rate at different diagnostic thresholds.34 In general, the AUC of a diagnostic method between 0.5 and 0.7 means low accuracy, 0.7 and 0.9 means good accuracy, above 0.9 high accuracy. The SROC curve shows an AUC of 0.95, indicating high accuracy.
The study of Hobbs et al35 reminds of that patients’ preferences for CESM will provide further evidence supporting the adoption of CESM as an alternative to ce-MRI in selected clinical indications, if diagnostic non-inferiority of CESM is confirmed. Ferranti et al25 suggested that CESM may provide compensation for MRI through a slight FN tendency. Furthermore, Clauser et al36 thought the specificity of CESM is higher than that of MRI. CEM determines breast cancer based on tumour angiogenesis assessment.24 Growth factors secreted by cancer cells promote the formation of new blood vessels during division and proliferate to tumour cells. It is because of the increased vascular endothelial cell gap and permeability that the contrast in the tumour area is enhanced. CESM may combine the high sensitivity of MRI with the low cost and availability of FFDM.37
However, there are some limitations in the study. First, primary source participants were all patients with lesions diagnosed by breast US or mammography. This may induce a selection bias. Second, the majority of the main participants were with dense breast. This point, while highlighting the superiority of CESM over dense breast examination, may still be subject to some bias. Third, due to the excessive number of retrieved literatures, we only included prospective studies and studies writing in English. In this way, some reliable studies and results may be missed.
Conclusion
The CESM has high sensitivity and good specificity when it comes to evaluating breast cancer, particularly in women with dense breasts. Thus, provide more information for clinical diagnosis and treatment.
Data availability statement
Data sharing not applicable as no datasets generated and/or analysed for this study.
Ethics statements
Patient consent for publication
Ethics approval
Not applicable.
References
Footnotes
Contributors JL and RX designed the study. SZou and YH gathered data. JL and SZhen performed the analysis. HY and DH revised it critically for important intellectual content. DH acted as guarantor. All authors contributed to the article and approved the submitted version.
Funding This work has received funding by the Henan Medical Science and Technology Research Program (LHGJ20210498,LHGJ20230528).
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.