-
European Journal of Radiology Nov 2017Double reading is the strategy of choice for mammogram interpretation in screening programmes. It remains, however, unknown whether double reading is still the strategy... (Meta-Analysis)
Meta-Analysis Review
PURPOSE
Double reading is the strategy of choice for mammogram interpretation in screening programmes. It remains, however, unknown whether double reading is still the strategy of choice in the context of digital mammography. Our aim was to determine the effectiveness and cost-effectiveness of double reading versus single reading of digital mammograms in screening programmes.
METHODS
We performed a systematic review by searching the PubMed, Embase, and Cochrane Library databases up to April 2017. We used the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies) tool and CHEERS (Consolidated Health Economic Evaluation Reporting Standards) checklist to assess the methodological quality of the diagnostic studies and economic evaluations, respectively. A proportion's meta-analysis approach, 95% Confidence Intervals (95% CI) and test of heterogeneity (P values) were used for pooled results. Costs are expressed US$ PPP (United States Dollar purchasing power parities). The PROSPERO ID of this Systematic Review's protocol is CRD42014013804.
RESULTS
Of 1473 potentially relevant hits, four high-quality studies were included. The pooled cancer detection rate of double reading was 6.01 per 1000 screens (CI: 4.47‰-7.77‰), and it was 5.65 per 1000 screens (CI: 3.95‰-7.65‰) for single reading (P=0.76). The pooled proportion of false-positives of double reading was 47.03 per 1000 screens (CI: 39.13‰-55.62‰) and it was 40.60 per 1000 screens (CI: 38.58‰-42.67‰) for single reading (P=0.12). One study reported, for double reading, an ICER (Incremental Cost-Effectiveness Ratio) of 16,684 Euros (24,717 US$ PPP; 2015 value) per detected cancer. Single reading+CAD (computer-aided-detection) was cost-effective in Japan.
CONCLUSION
The evidence of benefit for double reading compared to single reading for digital mammography interpretation is scarce. Double reading seems to increase operational costs, have a not significantly higher false-positive rate, and a similar cancer detection rate.
Topics: Breast Neoplasms; Cost-Benefit Analysis; Female; Humans; Image Interpretation, Computer-Assisted; Mammography; Reproducibility of Results
PubMed: 29103474
DOI: 10.1016/j.ejrad.2017.09.013 -
BMC Bioinformatics Oct 2023Recent advancements in computing power and state-of-the-art algorithms have helped in more accessible and accurate diagnosis of numerous diseases. In addition, the...
BACKGROUND
Recent advancements in computing power and state-of-the-art algorithms have helped in more accessible and accurate diagnosis of numerous diseases. In addition, the development of de novo areas in imaging science, such as radiomics and radiogenomics, have been adding more to personalize healthcare to stratify patients better. These techniques associate imaging phenotypes with the related disease genes. Various imaging modalities have been used for years to diagnose breast cancer. Nonetheless, digital breast tomosynthesis (DBT), a state-of-the-art technique, has produced promising results comparatively. DBT, a 3D mammography, is replacing conventional 2D mammography rapidly. This technological advancement is key to AI algorithms for accurately interpreting medical images.
OBJECTIVE AND METHODS
This paper presents a comprehensive review of deep learning (DL), radiomics and radiogenomics in breast image analysis. This review focuses on DBT, its extracted synthetic mammography (SM), and full-field digital mammography (FFDM). Furthermore, this survey provides systematic knowledge about DL, radiomics, and radiogenomics for beginners and advanced-level researchers.
RESULTS
A total of 500 articles were identified, with 30 studies included as the set criteria. Parallel benchmarking of radiomics, radiogenomics, and DL models applied to the DBT images could allow clinicians and researchers alike to have greater awareness as they consider clinical deployment or development of new models. This review provides a comprehensive guide to understanding the current state of early breast cancer detection using DBT images.
CONCLUSION
Using this survey, investigators with various backgrounds can easily seek interdisciplinary science and new DL, radiomics, and radiogenomics directions towards DBT.
Topics: Humans; Female; Deep Learning; Radiographic Image Enhancement; Breast; Breast Neoplasms; Mammography
PubMed: 37884877
DOI: 10.1186/s12859-023-05515-6 -
Radiation Protection Dosimetry Dec 2015This study aims to review the literature on existing diagnostic reference levels (DRLs) in digital mammography and methodologies for establishing them. To this end, a... (Review)
Review
This study aims to review the literature on existing diagnostic reference levels (DRLs) in digital mammography and methodologies for establishing them. To this end, a systematic search through Medline, Cinahl, Web of Science, Scopus and Google scholar was conducted using search terms extracted from three terms: DRLs, digital mammography and breast screen. The search resulted in 1539 articles of which 22 were included after a screening process. Relevant data from the included studies were summarised and analysed. Differences were found in the methods utilised to establish DRLs including test subjects types, protocols followed, conversion factors employed, breast compressed thicknesses and percentile values adopted. These differences complicate comparison of DRLs among countries; hence, an internationally accepted protocol would be valuable so that international comparisons can be made.
Topics: Breast Neoplasms; Female; Humans; Mammography; Radiation Dosage; Reference Values
PubMed: 25543130
DOI: 10.1093/rpd/ncu365 -
Journal of Personalized Medicine Mar 2023The current systematic review and meta-analysis was conducted to estimate the incidence of overdiagnosis due to screening mammography for breast cancer among women aged... (Review)
Review
The current systematic review and meta-analysis was conducted to estimate the incidence of overdiagnosis due to screening mammography for breast cancer among women aged 40 years and older. A PRISMA systematic search appraisal and meta-analysis were conducted. A systematic literature search of English publications in PubMed, Web of Science, EMBASE, Scopus, and Google Scholar was conducted without regard to the region or time period. Generic, methodological, and statistical data were extracted from the eligible studies. A meta-analysis was completed by utilizing comprehensive meta-analysis software. The effect size estimates were calculated using the fail-safe N test. The funnel plot and the Begg and Mazumdar rank correlation tests were employed to find any potential bias among the included articles. The strength of the association between two variables was assessed using Kendall's tau. Heterogeneity was measured using the I-squared (I2) test. The literature search in the five databases yielded a total of 4214 studies. Of those, 30 articles were included in the final analysis, with sample sizes ranging from 451 to 1,429,890 women. The vast majority of the articles were retrospective cohort designs (24 articles). The age of the recruited women ranged between 40 and 89 years old. The incidence of overdiagnosis due to screening mammography for breast cancer among women aged 40 years and older was 12.6%. There was high heterogeneity among the study articles (I2 = 99.993), and the pooled event rate was 0.126 (95% CI: 15 0.101-0.156). Despite the random-effects meta-analysis showing a high degree of heterogeneity among the articles, the screening tests have to allow for a certain degree of overdiagnosis (12.6%) due to screening mammography for breast cancer among women aged 40 years and older. Furthermore, efforts should be directed toward controlling and minimizing the harmful consequences associated with breast cancer screening.
PubMed: 36983705
DOI: 10.3390/jpm13030523 -
The Canadian Journal of Cardiology Dec 2023Recent studies have shown that breast arterial calcification (BAC) detected on screening mammography is linked to cardiovascular diseases via medial calcification.... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Recent studies have shown that breast arterial calcification (BAC) detected on screening mammography is linked to cardiovascular diseases via medial calcification. However, its effect on cardiovascular outcomes remains unclear. Therefore, we conducted a meta-analysis to determine the effect of BAC on cardiovascular outcomes in patients.
METHODS
Three electronic databases (Pubmed, Embase, and Scopus) were searched on May 1, 2022, for studies examining the relationship between BAC and cardiovascular outcomes including cardiac death, acute myocardial infarction, ischemic heart disease, stroke, peripheral artery disease, and heart failure. A random-effects meta-analysis model was used to summarise the studies.
RESULTS
A total of 5 longitudinal studies were included with a combined cohort of 87,865 patients. Significantly, the pooled risk ratio (RR) of the association between BAC and cardiac death was 2.06 (P < 0.00001). BAC was associated with a significantly increased risk of developing other cardiovascular diseases, such as ischemic/hemorrhagic stroke (RR 1.51; P = 0.003), ischemic stroke (RR 1.82; P < 0.00001), peripheral vascular disease (RR 1.24; P = 0.003), and heart failure (RR 1.84; P < 0.00001). There was no significant relationship for developing myocardial infarction or for total cardiovascular diseases.
CONCLUSIONS
Our findings suggest that BAC was associated with an increased risk of cardiovascular mortality, and certain cardiovascular outcomes. There is thus a potential to use BAC as a sex-specific cardiovascular risk assessment tool. Furthermore, there is a need for more widespread reporting of BAC to better understand the pathophysiologic mechanisms behind its correlation with cardiovascular disease and to apply it in clinical practice.
Topics: Female; Male; Humans; Cardiovascular Diseases; Breast; Mammography; Breast Neoplasms; Risk Factors; Early Detection of Cancer; Breast Diseases; Myocardial Infarction; Heart Failure; Death
PubMed: 37506765
DOI: 10.1016/j.cjca.2023.07.024 -
Insights Into Imaging Dec 2023Calcifications on mammography can be indicative of breast cancer, but the prognostic value of their appearance remains unclear. This systematic review and meta-analysis... (Review)
Review
BACKGROUND
Calcifications on mammography can be indicative of breast cancer, but the prognostic value of their appearance remains unclear. This systematic review and meta-analysis aimed to evaluate the association between mammographic calcification morphology descriptors (CMDs) and clinicopathological factors.
METHODS
A comprehensive literature search in Medline via Ovid, Embase.com, and Web of Science was conducted for articles published between 2000 and January 2022 that assessed the relationship between CMDs and clinicopathological factors, excluding case reports and review articles. The risk of bias and overall quality of evidence were evaluated using the QUIPS tool and GRADE. A random-effects model was used to synthesize the extracted data. This systematic review is reported according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA).
RESULTS
Among the 4715 articles reviewed, 29 met the inclusion criteria, reporting on 17 different clinicopathological factors in relation to CMDs. Heterogeneity between studies was present and the overall risk of bias was high, primarily due to small, inadequately described study populations. Meta-analysis demonstrated significant associations between fine linear calcifications and high-grade DCIS [pooled odds ratio (pOR), 4.92; 95% confidence interval (CI), 2.64-9.17], (comedo)necrosis (pOR, 3.46; 95% CI, 1.29-9.30), (micro)invasion (pOR, 1.53; 95% CI, 1.03-2.27), and a negative association with estrogen receptor positivity (pOR, 0.33; 95% CI, 0.12-0.89).
CONCLUSIONS
CMDs detected on mammography have prognostic value, but there is a high level of bias and variability between current studies. In order for CMDs to achieve clinical utility, standardization in reporting of CMDs is necessary.
CRITICAL RELEVANCE STATEMENT
Mammographic calcification morphology descriptors (CMDs) have prognostic value, but in order for CMDs to achieve clinical utility, standardization in reporting of CMDs is necessary.
SYSTEMATIC REVIEW REGISTRATION
CRD42022341599 KEY POINTS: • Mammographic calcifications can be indicative of breast cancer. • The prognostic value of mammographic calcifications is still unclear. • Specific mammographic calcification morphologies are related to lesion aggressiveness. • Variability between studies necessitates standardization in calcification evaluation to achieve clinical utility.
PubMed: 38051355
DOI: 10.1186/s13244-023-01529-z -
European Radiology Dec 2011To determine the diagnostic accuracy of surveillance mammography for detecting ipsilateral breast tumour recurrence and metachronous contralateral breast cancer in women... (Review)
Review
OBJECTIVES
To determine the diagnostic accuracy of surveillance mammography for detecting ipsilateral breast tumour recurrence and metachronous contralateral breast cancer in women previously treated for primary breast cancer.
METHODS
A systematic review of surveillance mammography compared with ultrasound, magnetic resonance imaging (MRI), specialist-led clinical examination or unstructured primary care follow-up, using histopathological assessment for test positives and follow-up for test negatives as the reference standard.
RESULTS
Nine studies met our inclusion criteria. Variations in study comparisons precluded meta-analysis. For routine ipsilateral breast tumour detection, surveillance mammography sensitivity ranged from 64-67% and specificity ranged from 85-97%. For MRI, sensitivity ranged from 86-100% and specificity was 93%. For non-routine ipsilateral breast tumour detection, sensitivity and specificity for surveillance mammography ranged from 50-83% and 57-75% and for MRI 93-100% and 88-96%. For routine metachronous contralateral breast cancer detection, one study reported sensitivity of 67% and specificity of 50% for both surveillance mammography and MRI.
CONCLUSION
Although mammography is associated with high sensitivity and specificity, MRI is the most accurate test for detecting ipsilateral breast tumour recurrence and metachronous contralateral breast cancer in women previously treated for primary breast cancer. Results should be interpreted with caution because of the limited evidence base. Key Points • Surveillance mammography is associated with high sensitivity and specificity • Findings suggest that MRI is the most accurate test for detecting further breast cancer • Robust conclusions cannot be made due to the limited evidence base • Further research comparing surveillance mammography and other diagnostic tests is required.
Topics: Breast Neoplasms; Evaluation Studies as Topic; Female; Follow-Up Studies; Humans; Magnetic Resonance Imaging; Mammography; Mass Screening; Neoplasm Recurrence, Local; Neoplasms, Second Primary; Palpation; Population Surveillance; Primary Health Care; Sensitivity and Specificity; Ultrasonography
PubMed: 21833567
DOI: 10.1007/s00330-011-2226-z -
Journal of the American College of... Feb 2024To summarize the literature regarding the performance of mammography-image based artificial intelligence (AI) algorithms, with and without additional clinical data, for...
PURPOSE
To summarize the literature regarding the performance of mammography-image based artificial intelligence (AI) algorithms, with and without additional clinical data, for future breast cancer risk prediction.
MATERIALS AND METHODS
A systematic literature review was performed using six databases (medRixiv, bioRxiv, Embase, Engineer Village, IEEE Xplore, and PubMed) from 2012 through September 30, 2022. Studies were included if they used real-world screening mammography examinations to validate AI algorithms for future risk prediction based on images alone or in combination with clinical risk factors. The quality of studies was assessed, and predictive accuracy was recorded as the area under the receiver operating characteristic curve (AUC).
RESULTS
Sixteen studies met inclusion and exclusion criteria, of which 14 studies provided AUC values. The median AUC performance of AI image-only models was 0.72 (range 0.62-0.90) compared with 0.61 for breast density or clinical risk factor-based tools (range 0.54-0.69). Of the seven studies that compared AI image-only performance directly to combined image + clinical risk factor performance, six demonstrated no significant improvement, and one study demonstrated increased improvement.
CONCLUSIONS
Early efforts for predicting future breast cancer risk based on mammography images alone demonstrate comparable or better accuracy to traditional risk tools with little or no improvement when adding clinical risk factor data. Transitioning from clinical risk factor-based to AI image-based risk models may lead to more accurate, personalized risk-based screening approaches.
Topics: Humans; Female; Breast Neoplasms; Mammography; Artificial Intelligence; Early Detection of Cancer; Breast; Retrospective Studies
PubMed: 37949155
DOI: 10.1016/j.jacr.2023.10.018 -
European Journal of Radiology Jul 2022This systematic review and meta-analysis focuses on breast cancer screening performance outcomes stratified into breast density, age, and reading procedure using... (Meta-Analysis)
Meta-Analysis Review
Tomosynthesis with synthesised two-dimensional mammography yields higher cancer detection compared to digital mammography alone, also in dense breasts and in younger women: A systematic review and meta-analysis.
OBJECTIVES
This systematic review and meta-analysis focuses on breast cancer screening performance outcomes stratified into breast density, age, and reading procedure using 'digital breast tomosynthesis (DBT) with synthesised two-dimensional mammography (s2D)' compared to 'digital mammography (DM) alone'.
METHODS
Studies comparing 'DBT with s2D' and 'DM' were searched in PubMed and Cochrane library. Pooled risk ratios (RR) using fixed or random effects models (F-/REM) for cancer detection rates (CDR), recall rates, interval cancer rates (ICR), biopsy rates, and positive predictive values (PPV) 1-3 were calculated. Outcomes were stratified into breast density (non-dense and dense), age (<60, ≥60), and reading procedure (double-/non-double reading). Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 tool.
RESULTS
We identified 13 studies. Using DBT plus s2D compared to DM alone resulted in a higher increase in CDR for dense ([number of studies included, FEM RR, 95% confidence interval (CI)]; n = 3, 1.60, 1.16-2.22) versus non-dense breasts (n = 3, 1.32, 1.08-1.61). Recall rates were lower in dense (n = 2, 0.84, 0.75-0.94), but much lower for non-dense breasts (n = 2, 0.65, 0.59-0.72). Age stratification resulted in small differences in CDR (<60: n = 2, 1.64, 1.18-2.29 / ≥60: n = 2, 1.56, 1.19-2.05). After screening with DBT plus s2D compared to DM alone the risk of being recalled was less in non-double (n = 3, 0.57, 0.54-0.60) than in double reading (n = 5, 0.95, 0.81-1.11) and the risk of cancer detection was higher in double reading (n = 6, 1.53, 1.40-1.67) than in non-double reading (n = 4, 1.17, 1.02-1.33).
CONCLUSION
Since only few studies are available for meta-analyses statistical significance strongly depends on single study results. Taking this into account, the most important results concern the increase of CDR in women with dense breasts, the increased CDR in double reading, and the lower recall rates particularly with non-double reading.
Topics: Breast Density; Breast Neoplasms; Early Detection of Cancer; Female; Humans; Mammography; Mass Screening
PubMed: 35576720
DOI: 10.1016/j.ejrad.2022.110324 -
Acta Radiologica (Stockholm, Sweden :... Mar 2023Computerized image analysis is a viable technique for evaluating image quality as a complement to human observers. (Review)
Review
BACKGROUND
Computerized image analysis is a viable technique for evaluating image quality as a complement to human observers.
PURPOSE
To systematically review the image analysis software used in the assessment of 2D image quality using mammography phantoms.
MATERIAL AND METHODS
A systematic search of multiple databases was performed from inception to July 2020 for articles that incorporated computerized analysis of 2D images of physical mammography phantoms to determine image quality.
RESULTS
A total of 26 studies were included, 12 were carried out using direct digital imaging and 14 using screen film mammography. The ACR phantom (model-156) was the most frequently evaluated phantom, possibly due to the lack of accepted standard software. In comparison to the inter-observer variations, the computerized image analysis was more consistent in scoring test objects. The template matching method was found to be one of the most reliable algorithms, especially for high-contrast test objects, while several algorithms found low-contrast test objects to be harder to distinguish due to the smaller contrast variations between test objects and their backgrounds. This was particularly true for small object sizes.
CONCLUSION
Image analysis software was in agreement with human observers but demonstrated higher consistency and reproducibility of quality evaluation. Additionally, using computerized analysis, several quantitative metrics such as contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR) could be used to complement the conventional scoring method. Implementing a computerized approach for monitoring image quality over time would be crucial to detect any deteriorating mammography system before clinical images are impacted.
Topics: Humans; Reproducibility of Results; Mammography; Algorithms; Software; Signal-To-Noise Ratio; Phantoms, Imaging; Radiographic Image Enhancement
PubMed: 35866198
DOI: 10.1177/02841851221112856