-
European Journal of Radiology Jun 2024This review provides an overview of the current state of artificial intelligence (AI) technology for automated detection of breast cancer in digital mammography (DM) and... (Review)
Review
PURPOSE
This review provides an overview of the current state of artificial intelligence (AI) technology for automated detection of breast cancer in digital mammography (DM) and digital breast tomosynthesis (DBT). It aims to discuss the technology, available AI systems, and the challenges faced by AI in breast cancer screening.
METHODS
The review examines the development of AI technology in breast cancer detection, focusing on deep learning (DL) techniques and their differences from traditional computer-aided detection (CAD) systems. It discusses data pre-processing, learning paradigms, and the need for independent validation approaches.
RESULTS
DL-based AI systems have shown significant improvements in breast cancer detection. They have the potential to enhance screening outcomes, reduce false negatives and positives, and detect subtle abnormalities missed by human observers. However, challenges like the lack of standardised datasets, potential bias in training data, and regulatory approval hinder their widespread adoption.
CONCLUSIONS
AI technology has the potential to improve breast cancer screening by increasing accuracy and reducing radiologist workload. DL-based AI systems show promise in enhancing detection performance and eliminating variability among observers. Standardised guidelines and trustworthy AI practices are necessary to ensure fairness, traceability, and robustness. Further research and validation are needed to establish clinical trust in AI. Collaboration between researchers, clinicians, and regulatory bodies is crucial to address challenges and promote AI implementation in breast cancer screening.
Topics: Breast Neoplasms; Humans; Female; Artificial Intelligence; Mammography; Radiographic Image Interpretation, Computer-Assisted; Early Detection of Cancer
PubMed: 38640824
DOI: 10.1016/j.ejrad.2024.111457 -
Health Education Research Oct 2015Identifying factors that increase mammography use among Latinas is an important public health priority. Latinas are more likely to report mammography intentions and use,... (Randomized Controlled Trial)
Randomized Controlled Trial
Identifying factors that increase mammography use among Latinas is an important public health priority. Latinas are more likely to report mammography intentions and use, if a family member or friend recommends that they get a mammogram. Little is known about the mechanisms underlying the relationship between social interactions and mammography intentions. Theory suggests that family/friend recommendations increase perceived mammography norms (others believe a woman should obtain a mammogram) and support (others will help her obtain a mammogram), which in turn increase mammography intentions and use. We tested these hypotheses with data from the ¡Fortaleza Latina! study, a randomized controlled trial including 539 Latinas in Washington State. Women whose family/friend recommended they get a mammogram within the last year were more likely to report mammography intentions, norms and support. Perceived mammography norms mediated the relationship between family/friend recommendations and intentions, Mediated Effect = 0.38, 95%CI [0.20, 0.61], but not support, Mediated Effect = 0.002, 95%CI [-0.07, 0.07]. Our findings suggest perceived mammography norms are a potential mechanism underlying the effect of family/friend recommendations on mammography use among Latinas. Our findings make an important contribution to theory about the associations of social interactions, perceptions and health behaviors.
Topics: Adult; Aged; Breast Neoplasms; Family; Female; Friends; Health Behavior; Hispanic or Latino; Humans; Mammography; Middle Aged; Social Support
PubMed: 26324395
DOI: 10.1093/her/cyv040 -
Canadian Association of Radiologists... Feb 2022The Covid pandemic has taught many lessons, including the importance of mental health. The value of the radiologist in holistic patient care may be underestimated and... (Review)
Review
The Covid pandemic has taught many lessons, including the importance of mental health. The value of the radiologist in holistic patient care may be underestimated and underresearched. Barriers to the acceptance of imaging as an important component in reassurance may be rooted in old ideas minimizing the importance of mental health.
Topics: Anxiety; Breast Neoplasms; Clinical Decision-Making; Female; Humans; Mammography; Paternalism; Patient Participation
PubMed: 34227431
DOI: 10.1177/08465371211021996 -
Frontiers in Public Health 2022The sensitivity of mammography screening is lower in women with dense breast. Increasing the efficacy of breast cancer screening have received special attention...
INTRODUCTION
The sensitivity of mammography screening is lower in women with dense breast. Increasing the efficacy of breast cancer screening have received special attention recently. The automated breast ultrasound (ABUS) shows promising results to complement mammography. Our aim was to expand the existing breast cancer screening protocol with ABUS within a Hungarian pilot project.
METHODS
First, we developed a protocol for the screening process focusing on integrating ABUS to the current practice. Consensus among clinical experts was achieved considering information from the literature and the actual opportunities of the hospital. Then we developed a protocol for evaluation that ensures systematic data collection and monitoring of screening with mammography and ABUS. We identified indicators based on international standards and adapted them to local setting. We considered their feasibility from the data source and timeframe perspective. The protocol was developed in a partnership of researchers, clinicians and hospital managers.
RESULTS
The process of screening activity was described in a detailed flowchart. Human and technological resource requirements and communication activities were defined. We listed 23 monitoring indicators to evaluate the screening program and checked the feasibility to calculate these indicators based on local data collection and other sources. Partnership between researchers experienced in planning and evaluating screening programs, interested clinicians, and hospital managers resulted in a locally implementable, evidence-based screening protocol.
DISCUSSION
The experience and knowledge gained on the implementation of the ABUS technology could generate real-world data to support the decision on using the technology at national level.
Topics: Female; Humans; Breast Neoplasms; Mammography; Breast Density; Pilot Projects; Early Detection of Cancer; Ultrasonography, Mammary
PubMed: 36684917
DOI: 10.3389/fpubh.2022.1071317 -
Radiography (London, England : 1995) Mar 2023This narrative review aims to identify what factors are linked to diagnostic performance variation for those who interpret mammograms. Identification of influential... (Review)
Review
OBJECTIVES
This narrative review aims to identify what factors are linked to diagnostic performance variation for those who interpret mammograms. Identification of influential factors has potential to contribute to the optimisation of breast cancer diagnosis. PubMed, ScienceDirect and Google Scholar databases were searched using the following terms: 'Radiology', 'Radiologist', 'Radiographer', 'Radiography', 'Mammography', 'Interpret', 'read', 'observe' 'report', 'screen', 'image', 'performance' and 'characteristics.' Exclusion criteria included articles published prior to 2000 as digital mammography was introduced at this time. Non-English articles language were also excluded. 38 of 2542 studies identified were analysed.
KEY FINDINGS
Influencing factors included, new technology, volume of reads, experience and training, availability of prior images, social networking, fatigue and time-of-day of interpretation. Advancements in breast imaging such as digital breast tomosynthesis and volume of mammograms are primary factors that affect performance as well as tiredness, time-of-day when images are interpreted, stages of training and years of experience. Recent studies emphasised the importance of social networking and knowledge sharing if breast cancer diagnosis is to be optimised.
CONCLUSION
It was demonstrated that data on radiologist performance variability is widely available but there is a paucity of data on radiographers who interpret mammographic images.
IMPLICATIONS FOR PRACTICE
This scarcity of research needs to be addressed in order to optimise radiography-led reporting and set baseline values for diagnostic efficacy.
Topics: Humans; Female; Mammography; Breast Neoplasms; Breast; Radiologists; Radiology
PubMed: 36731351
DOI: 10.1016/j.radi.2023.01.004 -
AJR. American Journal of Roentgenology Nov 2017The objective of this study was to investigate the impact of decreasing breast compression during digital mammography and breast tomosynthesis (DBT) on perceived pain...
OBJECTIVE
The objective of this study was to investigate the impact of decreasing breast compression during digital mammography and breast tomosynthesis (DBT) on perceived pain and image quality.
MATERIALS AND METHODS
In this two-part study, two groups of women with prior mammograms were recruited. In part 1, subjects were positioned for craniocaudal (CC) and mediolateral oblique (MLO) views, and four levels of compression force were applied to evaluate changes in breast thickness, perceived pain, and relative tissue coverage. No imaging was performed. In part 2, two MLO DBT images of one breast of each patient were acquired at standard and reduced compression. Blurring artifacts and tissue coverage were judged by three breast imaging radiologists, and compression force, breast thickness, relative tissue coverage, and perceived pain were recorded.
RESULTS
Only the first reduction in force was feasible because further reduction resulted in inadequate breast immobilization. Mean force reductions of 48% and 47% for the CC and MLO views, respectively, resulted in a significantly reduced perceived pain level, whereas the thickness of the compressed breast increased by 0.02 cm (CC view) and 0.09 (MLO view, part 1 of the study) and 0.38 cm (MLO view, part 2 of the study), respectively, with no change in tissue coverage or increase in motion blurring.
CONCLUSION
Mammography and DBT acquisitions may be possible using half of the compression force used currently, with a significant and substantial reduction in perceived pain with no clinically significant change in breast thickness and tissue coverage.
Topics: Adult; Aged; Breast Neoplasms; Feasibility Studies; Female; Humans; Mammography; Middle Aged; Observer Variation; Pain; Pressure; Stress, Mechanical
PubMed: 28929809
DOI: 10.2214/AJR.16.17615 -
Asian Pacific Journal of Cancer... Dec 2021Breast cancer patients who have a rapid diagnosis have been better prognosis than late diagnosis. The popular screening is mammogram or ultrasound. In recent years,...
OBJECTIVE
Breast cancer patients who have a rapid diagnosis have been better prognosis than late diagnosis. The popular screening is mammogram or ultrasound. In recent years, researchers try to develop data driven models to predict early cancer staging from the first screening. However, data elements are not complete such as lymph node status. Therefore, the Integrated dataset approach will be challenging.
METHODS
Because the data elements are not collected from the same source, joining between mammography and biopsy data were performed using latent variables that determine by tumor severity. The datasets consist of 445 mammography reports and 183 pathological reports. The latent variables of the mammogram dataset were determined by the severity of mass, while latent variables of the pathological dataset were determined by TNM Staging. The latent variables were used to join between two datasets. Then, the prediction models were built using the machine learning technique. The modeling is divided into three steps; staging prediction, lymph node prediction, and prognosis.
RESULTS
Integrated dataset from mammography and biopsy extend more factors and built the models to predict breast cancer staging in the mammography process. The staging prediction is 100% accuracy. The lymph node prediction are 72.47% accuracy, 73.94% specificity, and 72.5% sensitivity. An area under ROC curve is 0.74. The prognosis model prediction are 72.72% accuracy, 80% specificity, and 77% sensitivity. An area under ROC curve is 0.87. There are also built the rule for early staging, diagnosis, and prognosis. Conclusion: This study aims to build the models for early staging, diagnosis, and prognosis using the less aggressive method. The advantages are (1) predict staging from the first screening (2) estimate the lymph node metastases for planning to ALND or SLNB (3) evaluate overall survival time. These advantages help the physician planning the best treatment for cancer patients.
Topics: Aged; Breast Neoplasms; Clinical Decision Rules; Early Detection of Cancer; Female; Humans; Lymphatic Metastasis; Machine Learning; Mammography; Middle Aged; Neoplasm Staging; Predictive Value of Tests; Prognosis; ROC Curve; Reproducibility of Results; Sensitivity and Specificity; Sentinel Lymph Node Biopsy
PubMed: 34967591
DOI: 10.31557/APJCP.2021.22.12.4069 -
The British Journal of Radiology Aug 2020This review details the aetiology of the PERFORMS self-assessment scheme in breast screening, together with its subsequent development, current implementation and future... (Review)
Review
This review details the aetiology of the PERFORMS self-assessment scheme in breast screening, together with its subsequent development, current implementation and future function. The purpose of the scheme is examined and the importance of its continuing role in a changing screening service described, together with current evolution.
Topics: Aged; Breast; Breast Neoplasms; Early Detection of Cancer; Female; Humans; Mammography; Middle Aged; United Kingdom
PubMed: 32501766
DOI: 10.1259/bjr.20190908 -
The New England Journal of Medicine Jan 2018The Affordable Care Act (ACA) required most insurers and the Medicare program to eliminate cost sharing for screening mammography. (Comparative Study)
Comparative Study
BACKGROUND
The Affordable Care Act (ACA) required most insurers and the Medicare program to eliminate cost sharing for screening mammography.
METHODS
We conducted a difference-in-differences study of biennial screening mammography among 15,085 women 65 to 74 years of age in 24 Medicare Advantage plans that eliminated cost sharing to provide full coverage for screening mammography, as compared with 52,035 women in 48 matched control plans that had and maintained full coverage.
RESULTS
In plans that eliminated cost sharing, adjusted rates of biennial screening mammography increased from 59.9% (95% confidence interval [CI], 54.9 to 65.0) in the 2-year period before cost-sharing elimination to 65.4% (95% CI, 61.8 to 69.0) in the 2-year period thereafter. In control plans, the rates of biennial mammography were 73.1% (95% CI, 69.2 to 77.0) and 72.8% (95% CI, 69.7 to 76.0) during the same periods, yielding a difference in differences of 5.7 percentage points (95% CI, 3.0 to 8.4). The difference in differences was 9.8 percentage points (95% CI, 4.5 to 15.2) among women living in the areas with the highest quartile of educational attainment versus 4.3 percentage points (95% CI, 0.2 to 8.4) among women in the lowest quartile. As indicated by the difference-in-differences estimates, after the elimination of cost sharing, the rate of biennial mammography increased by 6.5 percentage points (95% CI, 3.7 to 9.4) for white women and 8.4 percentage points (95% CI, 2.5 to 14.4) for black women but was almost unchanged for Hispanic women (0.4 percentage points; 95% CI, -7.3 to 8.1).
CONCLUSIONS
The elimination of cost sharing for screening mammography under the ACA was associated with an increase in rates of use of this service among older women for whom screening is recommended. The effect was attenuated among women living in areas with lower educational attainment and was negligible among Hispanic women. (Funded by the National Institute on Aging.).
Topics: Aged; Cost Sharing; Early Detection of Cancer; Ethnicity; Female; Humans; Mammography; Medicare; Medicare Part C; Patient Protection and Affordable Care Act; Socioeconomic Factors; United States
PubMed: 29342379
DOI: 10.1056/NEJMsa1706808 -
Nature Communications Sep 2023The UK NHS Women's National Breast Screening programme aims to detect breast cancer early. The reference standard approach requires mammograms to be independently...
The UK NHS Women's National Breast Screening programme aims to detect breast cancer early. The reference standard approach requires mammograms to be independently double-read by qualified radiology staff. If two readers disagree, arbitration by an independent reader is undertaken. Whilst this process maximises accuracy and minimises recall rates, the procedure is labour-intensive, adding pressure to a system currently facing a workforce crisis. Artificial intelligence technology offers an alternative to human readers. While artificial intelligence has been shown to be non-inferior versus human second readers, the minimum requirements needed (effectiveness, set-up costs, maintenance, etc) for such technology to be cost-effective in the NHS have not been evaluated. We developed a simulation model replicating NHS screening services to evaluate the potential value of the technology. Our results indicate that if non-inferiority is maintained, the use of artificial intelligence technology as a second reader is a viable and potentially cost-effective use of NHS resources.
Topics: Humans; Female; Breast Neoplasms; Cost-Benefit Analysis; Artificial Intelligence; Early Detection of Cancer; Mammography; United Kingdom
PubMed: 37777510
DOI: 10.1038/s41467-023-41754-0