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Journal of the National Cancer Institute Sep 2021Screening mammography was assessed in 9 randomized trials initiated between 1963 and 1990, with breast cancer-specific mortality as the primary endpoint. In contrast,...
Screening mammography was assessed in 9 randomized trials initiated between 1963 and 1990, with breast cancer-specific mortality as the primary endpoint. In contrast, breast cancer detection has been the primary endpoint in most screening trials initiated during the past decade. These trials have evaluated digital breast tomosynthesis, magnetic resonance imaging, and ultrasound, and novel screening strategies have been recommended solely on the basis of improvements in breast cancer detection rates. Yet, the assumption that increases in tumor detection produce reductions in cancer mortality has not been validated, and tumor-detection endpoints may exacerbate the problem of overdiagnosis. Indeed, the detection of greater numbers of early stage breast cancers in the absence of a subsequent decline in rates of metastatic cancers and cancer-related mortality is the hallmark of overdiagnosis. There is now evidence to suggest that both ductal carcinoma in situ and invasive cancers are overdiagnosed as a consequence of screening. For each patient who is overdiagnosed with breast cancer, the adverse consequences include unnecessary anxiety, financial hardships, and a small risk of morbidity and mortality from unnecessary treatments. Moreover, the overtreatment of breast cancer, as a consequence of overdiagnosis, is costly and contributes to waste in health-care spending. In this article, we argue that there is a need to establish better endpoints in breast cancer screening trials, including quality of life and composite endpoints. Tumor-detection endpoints should be abandoned, because they may lead to the implementation of screening strategies that increase the risk of overdiagnosis.
Topics: Breast Neoplasms; Early Detection of Cancer; Female; Humans; Mammography; Mass Screening; Overdiagnosis; Quality of Life
PubMed: 32898241
DOI: 10.1093/jnci/djaa140 -
Journal of Medical Economics 2023To evaluate the cost-effectiveness of supplemental breast imaging modalities for women with heterogeneously and extremely dense breasts and average or intermediate risk...
Economic evaluation of supplemental breast cancer screening modalities to mammography or digital breast tomosynthesis in women with heterogeneously and extremely dense breasts and average or intermediate breast cancer risk in US healthcare.
OBJECTIVE
To evaluate the cost-effectiveness of supplemental breast imaging modalities for women with heterogeneously and extremely dense breasts and average or intermediate risk of breast cancer (BC) in the USA, and analyze capacity requirements for supplemental magnetic resonance imaging (MRI) and contrast-enhanced mammography (CEM).
METHODS
Clinical and economic outcomes for supplemental imaging modalities including full- and abbreviated-protocol MRI (Fp-MRI, Ab-MRI), CEM, and ultrasound (U/S) as add-on to x-ray mammography (XM) or digital breast tomosynthesis (DBT), were compared to XM or DBT alone, in a decision tree linked to a Markov chain validated by comparison with a microsimulation analysis. A Delphi panel supplemented model input parameters from the literature. A capacity model evaluated the number of additional daily scans and scanners required for Fp-MRI and CEM.
RESULTS
Compared to XM or DBT alone, all supplemental imaging protocols were cost-effective. Both Fp- and Ab-MRI, and to a lesser extent CEM and U/S, yielded superior clinical outcomes to XM or DBT. Compared to XM alone, U/S and Ab-MRI had the lowest incremental cost-effectiveness ratios (ICER). For U/S, the ICER was $23,394 for the average-risk population and $13,241 for the intermediate-risk population. For CEM, the ICER was $38,423 and $23,772, respectively. For the extremely dense subpopulation with intermediate risk, supplemental screening requirements could be accommodated by conducting one Fp-MRI scan per day per existing general scanner.
CONCLUSIONS
While ultrasound had the lowest ICER, MRI and CEM demonstrated the best clinical outcomes, compared to XM or DBT alone for women with dense breasts and intermediate and high risk. Existing MRI scanner capacity has the potential to meet most of the supplemental screening needs of this population.
Topics: Female; Humans; Breast Neoplasms; Mammography; Cost-Benefit Analysis; Breast Density; Early Detection of Cancer; Delivery of Health Care; Mass Screening
PubMed: 37278659
DOI: 10.1080/13696998.2023.2222035 -
Journal of Cancer Research and... 2020This study is carried out to report on the knowledge and practice regarding breast self-examination (BSE) among women from the city of Mosul in Iraq and to evaluate the... (Observational Study)
Observational Study
AIMS
This study is carried out to report on the knowledge and practice regarding breast self-examination (BSE) among women from the city of Mosul in Iraq and to evaluate the prevalence of performing clinical breast examination (CBE) and mammography among them.
SETTINGS AND DESIGN
A descriptive, cross-sectional survey carried out among females working in the University of Mosul, as a sample of the female population of Mosul city.
SUBJECTS AND METHODS
The sample was collected conveniently, and the data were collected from July to November 2018. Data were collected by interviews with 405 participants. Knowledge answers were scored and categorized into two groups: good and poor level of knowledge.
RESULTS
A final sample of 384 participants were included in the analysis, with a mean age of 42.58 ± 8.9. Only 39 (10.1%) and 37 (9.6%) participants performed mammographic examination and CBE of their breasts, respectively. Just 100 (30.3%) of the 330 females who knew BSE performed BSE routinely or intermittently. The mean knowledge score was 4.22 ± 1.66, and only 141 females (42.7%) were found to have a good level of knowledge. A statistically significant association of knowledge level with marital status (P = 0.015), perceived benefit of BSE (P = 0.001), previous gain of instructions of BSE (P < 0.05), and the provider (P < 0.05) was found.
CONCLUSIONS
The performance results of BSE were poor as well as for CBE and mammography among the study participants. There is a need for educational programs to create awareness and improve knowledge about routine breast cancer screening behavior.
Topics: Adult; Breast Neoplasms; Breast Self-Examination; Cities; Cross-Sectional Studies; Early Detection of Cancer; Female; Health Education; Health Knowledge, Attitudes, Practice; Health Services Needs and Demand; Humans; Iraq; Mammography; Middle Aged; Surveys and Questionnaires; Young Adult
PubMed: 33342800
DOI: 10.4103/jcrt.JCRT_736_19 -
Medicina (Kaunas, Lithuania) Mar 2024Breast cancer remains a significant contributor to morbidity and mortality within oncology. Risk factors, encompassing genetic and environmental influences,... (Review)
Review
Breast cancer remains a significant contributor to morbidity and mortality within oncology. Risk factors, encompassing genetic and environmental influences, significantly contribute to its prevalence. While germline mutations, notably within the BRCA genes, are commonly associated with heightened breast cancer risk, a spectrum of other variants exists among affected individuals. Diagnosis relies on imaging techniques, biopsies, biomarkers, and genetic testing, facilitating personalised risk assessment through specific scoring systems. Breast cancer screening programs employing mammography and other imaging modalities play a crucial role in early detection and management, leading to improved outcomes for affected individuals. Regular screening enables the identification of suspicious lesions or abnormalities at earlier stages, facilitating timely intervention and potentially reducing mortality rates associated with breast cancer. Genetic mutations guide screening protocols, prophylactic interventions, treatment modalities, and patient prognosis. Prophylactic measures encompass a range of interventions, including chemoprevention, hormonal inhibition, oophorectomy, and mastectomy. Despite their efficacy in mitigating breast cancer incidence, these interventions carry potential side effects and psychological implications, necessitating comprehensive counselling tailored to individual cases.
Topics: Humans; Female; Breast Neoplasms; Romania; Early Detection of Cancer; Prophylactic Mastectomy; Mammography; Risk Factors
PubMed: 38674216
DOI: 10.3390/medicina60040570 -
Radiology Dec 2021Background While digital breast tomosynthesis (DBT) is rapidly replacing digital mammography (DM) in breast cancer screening, the potential of DBT density measures for...
Background While digital breast tomosynthesis (DBT) is rapidly replacing digital mammography (DM) in breast cancer screening, the potential of DBT density measures for breast cancer risk assessment remains largely unexplored. Purpose To compare associations of breast density estimates from DBT and DM with breast cancer. Materials and Methods This retrospective case-control study used contralateral DM/DBT studies from women with unilateral breast cancer and age- and ethnicity-matched controls (September 19, 2011-January 6, 2015). Volumetric percent density (VPD%) was estimated from DBT using previously validated software. For comparison, the publicly available Laboratory for Individualized Breast Radiodensity Assessment software package, or LIBRA, was used to estimate area-based percent density (APD%) from raw and processed DM images. The commercial Quantra and Volpara software packages were applied to raw DM images to estimate VPD% with use of physics-based models. Density measures were compared by using Spearman correlation coefficients (), and conditional logistic regression was performed to examine density associations (odds ratios [OR]) with breast cancer, adjusting for age and body mass index. Results A total of 132 women diagnosed with breast cancer (mean age ± standard deviation [SD], 60 years ± 11) and 528 controls (mean age, 60 years ± 11) were included. Moderate correlations between DBT and DM density measures ( = 0.32-0.75; all < .001) were observed. Volumetric density estimates calculated from DBT (OR, 2.3 [95% CI: 1.6, 3.4] per SD for VPD%) were more strongly associated with breast cancer than DM-derived density for both APD% (OR, 1.3 [95% CI: 0.9, 1.9] [ < .001] and 1.7 [95% CI: 1.2, 2.3] [ = .004] per SD for LIBRA raw and processed data, respectively) and VPD% (OR, 1.6 [95% CI: 1.1, 2.4] [ = .01] and 1.7 [95% CI: 1.2, 2.6] [ = .04] per SD for Volpara and Quantra, respectively). Conclusion The associations between quantitative breast density estimates and breast cancer risk are stronger for digital breast tomosynthesis compared with digital mammography. © RSNA, 2021 See also the editorial by Yaffe in this issue.
Topics: Breast; Breast Density; Breast Neoplasms; Case-Control Studies; Female; Humans; Mammography; Middle Aged; Retrospective Studies
PubMed: 34519572
DOI: 10.1148/radiol.2021210190 -
Scientific Reports Feb 2023In this study, we aimed to evaluate the benefits and losses of mammography with and without implant displacement (ID) and propose an appropriate imaging protocol for the...
In this study, we aimed to evaluate the benefits and losses of mammography with and without implant displacement (ID) and propose an appropriate imaging protocol for the screening of breasts with implants. We evaluated mammograms of 162 breasts in 96 patients including 71 breasts with biopsy-proven cancers. Mammography of each breast included standard MLO and ID MLO images. We reviewed the mammograms using clinical image quality criteria, which consist of parameters that evaluate the proper positioning of the breast and the image resolution. Standard MLO images showed significantly higher scores for proper positioning but showed significantly lower scores for image resolution than the ID MLO images. Moreover, standard MLO images showed significantly higher kVp, mAs, and compressed breast thickness than the ID MLO images. The organ dose was also higher in the standard MLO images than in the ID MLO images, but the difference was not statistically significant. In mammography with proven cancer, ID MLO images showed significantly higher degree of cancer visibility than standard MLO images. For screening mammography in patients with breast implants, ID MLO view alone is sufficient for MLO projection with reducing the patient's radiation dose without compromising the breast cancer detection capability, especially in dense breasts with subpectoral implants.
Topics: Female; Humans; Breast; Breast Implants; Breast Neoplasms; Early Detection of Cancer; Mammography
PubMed: 36725965
DOI: 10.1038/s41598-023-28399-1 -
Technology in Cancer Research &... 2023Breast Cancer (BC) is a major health issue in women of the age group above 45. Identification of BC at an earlier stage is important to reduce the mortality rate.... (Review)
Review
Breast Cancer (BC) is a major health issue in women of the age group above 45. Identification of BC at an earlier stage is important to reduce the mortality rate. Image-based noninvasive methods are used for early detection and for providing appropriate treatment. Computer-Aided Diagnosis (CAD) schemes can support radiologists in making correct decisions. Computational intelligence paradigms such as Machine Learning (ML) and Deep Learning (DL) have been used in the recent past in CAD systems to accelerate diagnosis. ML techniques are feature driven and require a high amount of domain expertise. However, DL approaches make decisions directly from the image. The current advancement in DL approaches for early diagnosis of BC is the motivation behind this review. This article throws light on various types of CAD approaches used in BC detection and diagnosis. A survey on DL, Transfer Learning, and DL-based CAD approaches for the diagnosis of BC is presented in detail. A comparative study on techniques, datasets, and performance metrics used in state-of-the-art literature in BC diagnosis is also summarized. The proposed work provides a review of recent advancements in DL techniques for enhancing BC diagnosis.
Topics: Female; Humans; Breast Neoplasms; Deep Learning; Diagnosis, Computer-Assisted; Machine Learning; Mammography
PubMed: 37282580
DOI: 10.1177/15330338231177977 -
Annual Review of Biomedical Data Science Aug 2023Breast cancer risk is highly variable within the population and current research is leading the shift toward personalized medicine. By accurately assessing an individual... (Review)
Review
Breast cancer risk is highly variable within the population and current research is leading the shift toward personalized medicine. By accurately assessing an individual woman's risk, we can reduce the risk of over/undertreatment by preventing unnecessary procedures or by elevating screening procedures. Breast density measured from conventional mammography has been established as one of the most dominant risk factors for breast cancer; however, it is currently limited by its ability to characterize more complex breast parenchymal patterns that have been shown to provide additional information to strengthen cancer risk models. Molecular factors ranging from high penetrance, or high likelihood that a mutation will show signs and symptoms of the disease, to combinations of gene mutations with low penetrance have shown promise for augmenting risk assessment. Although imaging biomarkers and molecular biomarkers have both individually demonstrated improved performance in risk assessment, few studies have evaluated them together. This review aims to highlight the current state of the art in breast cancer risk assessment using imaging and genetic biomarkers.
Topics: Female; Humans; Breast Neoplasms; Mammography; Breast Density; Breast; Risk Assessment
PubMed: 37159874
DOI: 10.1146/annurev-biodatasci-020722-092748 -
European Journal of Radiology Jun 2022According to the World Health Organization (WHO), at the end of 2020, 7.8 million women alive were diagnosed with breast cancer in the past 5 years, making it the...
According to the World Health Organization (WHO), at the end of 2020, 7.8 million women alive were diagnosed with breast cancer in the past 5 years, making it the world's most prevalent cancer. It is largely recognized and demonstrated that early detection represents the first strategy to follow in the fight against cancer. The effectiveness of mammography screening for early breast cancer detection has been proven in several surveys and studies over the last three decades. The estimation of the Mean Glandular Dose (MGD) is important to understand the radiation-associated risk from breast x-ray imaging exams. It continues to be the subject of numerous studies and debates, since its accuracy is directly related to risk estimation and for optimizing breast cancer screening programs. This manuscript reviews the main dosimetry formalisms used to estimate the MGD in mammography and to understand the continuing efforts to reduce the absorbed dose over the last forty years. The dosimetry protocols were formulated initially for mammography. Digital breast tomosynthesis (DBT) either in conjunction with synthesized digital mammogram (SDM) or with digital mammography (DM), is routinely used in many breast cancer screening programs and consequently the dosimetry protocols were extended for these techniques.
Topics: Breast; Breast Neoplasms; Early Detection of Cancer; Female; Humans; Mammography; Mass Screening; X-Rays
PubMed: 35430441
DOI: 10.1016/j.ejrad.2022.110278 -
BioMed Research International 2022Breast cancer is the most prevalent form of cancer that can strike at any age; the higher the age, the greater the risk. The presence of malignant tissue has become more...
Breast cancer is the most prevalent form of cancer that can strike at any age; the higher the age, the greater the risk. The presence of malignant tissue has become more frequent in women. Although medical therapy has improved breast cancer diagnostic and treatment methods, still the death rate remains high due to failure of diagnosing breast cancer in its early stages. A classification approach for mammography images based on nonsubsampled contourlet transform (NSCT) is proposed in order to investigate it. The proposed method uses multiresolution NSCT decomposition to the region of interest (ROI) of mammography images and then uses Z-moments for extracting features from the NSCT-decomposed images. The matrix is formed by the components that are extracted from the region of interest and are then subjected to singular value decomposition (SVD) in order to remove the essential features that can generalize globally. The method employs a support vector machine (SVM) classification algorithm to categorize mammography pictures into normal, benign, and malignant and to identify and classify the breast lesions. The accuracy of the proposed model is 96.76 percent, and the training time is greatly decreased, as evident from the experiments performed. The paper also focuses on conducting the feature extraction experiments using morphological spectroscopy. The experiment combines 16 different algorithms with 4 classification methods for achieving exceptional accuracy and time efficiency outcomes as compared to other existing state-of-the-art approaches.
Topics: Algorithms; Breast; Breast Neoplasms; Female; Humans; Mammography; Support Vector Machine
PubMed: 35993044
DOI: 10.1155/2022/6392206