Mammographic Screening For Breast Cancer Research Articles

Cost-Effectiveness Analysis of Digital Breast Tomosynthesis and Mammography in Breast Cancer Screening: A Markov Modeling Study.

Mammography (MG) has demonstrated its effectiveness in diminishing mortality and advanced-stage breast cancer incidences in breast screening initiatives. Notably, research has accentuated the superior diagnostic efficacy and cost-effectiveness of digital breast tomosynthesis (DBT). However, the scope of evidence validating the cost-effectiveness of DBT remains limited, prompting a requisite for more comprehensive investigation. The present study aimed to rigorously evaluate the cost-effectiveness of DBT plus MG (DBT-MG) compared to MG alone within the framework of Taiwan's National Health Insurance program. All parameters for the Markov decision tree model, encompassing event probabilities, costs, and utilities (quality-adjusted life years, QALYs), were sourced from reputable literature, expert opinions, and official records. With 10,000 iterations, a 2-year cycle length, a 30-year time horizon, and a 2% annual discount rate, the analysis determined the incremental cost-effectiveness ratio (ICER) to compare the cost-effectiveness of the two screening methods. Probabilistic and one-way sensitivity analyses were also conducted to demonstrate the robustness of findings. The ICER of DBT-MG compared to MG was US$5971.5764/QALYs. At a willingness-to-pay (WTP) threshold of US$33,004 (Gross Domestic Product of Taiwan in 2021) per QALY, more than 98% of the probabilistic simulations favored adopting DBT-MG versus MG. The one-way sensitivity analysis also shows that the ICER depended heavily on recall rates, biopsy rates, and positive predictive value (PPV2). DBT-MG shows enhanced diagnostic efficacy, potentially diminishing recall costs. While exhibiting a higher biopsy rate, DBT-MG aids in the detection of early-stage breast cancers, reduces recall rates, and exhibits notably superior cost-effectiveness.

Abstract PO5-21-02: Breast cancer screening based on physical breast examination: ITABERAÍ randomized trial

Abstract Introduction: Approximately 70% of the Brazilian population depends on the public healthcare system (Sistema Único de Saúde - SUS). However, only 16% of SUS users have access to mammography for breast cancer screening, which necessitates the evaluation of new strategies to reduce mortality from the disease, including expanding physical breast examination (PBE) by non-medical professionals. Within the primary healthcare network, the Community Health Agent (CHA) is a technical-level professional who performs activities through home visits. The primary objective of this study is to evaluate the effectiveness of screening actions based on PBE performed by CHA in reducing advanced tumors (Stage III and IV) and breast cancer mortality rates. Secondary objectives include comparing the number of breast cancer diagnoses between the groups, establishing the overdiagnosis rate, comparing cancer-specific survival, comparing overall survival, comparing the number of diagnostic procedures, assessing the interval between the first symptom and diagnosis, evaluating the interval between diagnosis and the start of treatment, and comparing the financial cost of diagnosis and treatment for breast cancer patients. Trial design: Multicenter, phase III, prospective, randomized clinical trial. The target population comprises women aged 40 years or older and users of SUS. The randomization process will be carried out based on the spatial analysis of each participating center, using sociodemographic information on women from each macroregion to verify the homogeneity of data between groups. Intervention: After randomization, CHA in each group underwent training at different times. CHA in the CG received guidance on breast cancer screening and prevention according to Ministry of Health recommendations, while CHA in the IG received the same guidance and participated in theoretical and practical training for PBE (only female professionals). Variables and data collection: An application was developed to be installed on mobile devices, which the CHA used during home visits. The graphical interface of the application was developed in Dart/Flutter. For the backend, Python programming language was used along with the Flask framework to create the Application Programming Interface (API) responsible for the communication between the database and the application. The MySQL software was used for the relational database. The variables used for building the application included sociodemographic data, lifestyle habits, medical history, information on previous examinations, and physical breast examination. Statistical analysis: For the analyses, the database will be exported to the REDCap (Research Electronic Data Capture) platform. The calculations were defined to detect a reduction in severe cases and mortality (10% and 20%, respectively). For this purpose, a sample power of 80% and a Type I error of 5% were adopted after adjusting for intraclass correlation and sampling effect (0.032 and 1.892, respectively). The calculations were estimated using nQuery software (version 9.1). For the city of Itaberaí, a population of 1,894 women was estimated in each group, resulting in a total of 3,788. Present and target accrual: The trial was activated in December 2022, and as of June 30th, 2023, 2,467 patients had been accrued. The study will last for 16 years, and the first data analyses will be conducted in 2024. Registration and ethical aspects: The trial is registered in ReBEC (Brazilian register): RBR-39vm2nd. Contact information: Prof. Dr. Ruffo Freitas-Junior, Federal University of Goiás, ruffojr@terra.com.br. Citation Format: Ruffo Freitas-Junior, Danielle Rodrigues, Rosangela Corrêa, Leonardo Soares. Breast cancer screening based on physical breast examination: ITABERAÍ randomized trial [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-21-02.

Abstract PO1-07-09: Benefit of Adherence to Annual Mammography Screening: Results from 8,305 Cancers in an Institutional Database

Abstract Purpose: There is much debate on the starting age and frequency for asymptomatic mammographic breast cancer screening. We analyzed data from our medical center to determine the effect of the frequency of screening on the likelihood of a woman being diagnosed with a late-stage cancer and on the all-cause mortality. Method: For this study, we used our institutional breast cancer care data mart, which contains data for all patients who had breast imaging or were treated for breast cancer at a University of Pittsburgh Medical Center (UPMC) facility between 2004 and 2019 inclusive. Including only women 40 years and older, 8,145 had at least one screening mammogram prior to their diagnosis of breast cancer. Screening exams less than 260 days apart were considered to be from the same screening episode. For the 8,145 women, we determined the interval between their two most recent screening mammograms and grouped them into: (i) Baseline (only 1 prior screening episode prior to diagnosis); (ii) Compliant (less than or equal to 15 months between the two most recent screening episodes); (iii) Delayed (more than 15 months but less than 27 months between the two most recent screening episodes); and (iv) Missed (more than 27 months between the two most recent screening episodes. Late-stage cancer was defined as TNM stage 2b or worst. In cancers arising in those with at least two prior screening examinations, we estimated and tested significance of effects of adherence category on risk of late-stage cancer using logistic regression. We estimated the corresponding effects on survival to death from any cause using proportional hazards model. The effect of compliance was evaluated univariately followed by the multivariable analysis accounting for demographic and clinical characteristics including age, race, and menopausal status. Analysis within practically relevant subgroups was performed for additional illustration. Results: For all-cause death 5-year mortality rate post-diagnosis was 4.2% for the Compliant group (n=3369, median follow-up 5.13 years), 5.9% for the Delayed group (n=1340, median follow-up 4.64 years), and 12.2% for the Missed group (n=1129, median follow-up 3.36 years). The overall 5-year mortality rate was 6.1% (n=8145, median follow 5.12 years). Both unadjusted and adjusted for age, menopausal status, and ethnicity, the poorer survival with lesser compliance was highly significant (with the adjusted hazard ratios relative to the baseline group of 0.5, 0.8, and 1.3 for the three compliance groups respectively, p< 0.001). In the population overall, there was a significant trend of increasing risk of stage 2B or worse with lesser adherence to annual screening, the proportions being 9%, 14%, and 19% for the compliant, delayed, and missed groups respectively (p< 0.001). This remained significant when adjusted for age, menopausal status, or ethnicity (p< 0.001). The trend was significant within major demographic subgroups, except for a relatively small subpopulation of women with unknown menopausal status. Conclusions: Annual mammographic screening resulted in lower all-cause mortality and lower risk of late-stage cancers, for both white and black women and pre- and post-menopausal women. Our study clearly shows a benefit to screening all women over the age of 40 annually over longer periods between screens. Table of Late-Stage Cancers by Screening Adherence and Demographic Factors Diagnosis of breast cancer at stage 2B or higher by screening adherence group and demographic factors Citation Format: Robert Nishikawa, Andriy Bandos, Stephen Duffy, Durwin Logue, Margarita Zuley. Benefit of Adherence to Annual Mammography Screening: Results from 8,305 Cancers in an Institutional Database [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-07-09.

Abstract PO1-10-09: The Performance Of Mobile Units Versus Hospital Units In National Breast Cancer Screening Program In Taiwan, 2010-2020

Abstract Purpose After the implementation of mobile units, the screened population increased from 3.9% to 40% of all women from 2004 to 2019 in Taiwan’s Breast Cancer Screening Program. There are limited studies comparing mobile units to hospital units. This study evaluated and compared the performance of the biennial mammography breast cancer screening in mobile units to hospital units in Taiwan over the past decade. Methods A cohort of 3 062 190 women aged 40 to 69 years who underwent biennial breast cancer mammography screenings from 2010 to 2020 was conducted, and data were obtained from the Health Promotion Administration, Ministry of Health and Welfare of Taiwan. Comparing participation of screened women mobile units and hospital units across national screening. Performance measures were determined as percentages and 95% confidence intervals (CIs) using the Wald asymptotic method. Results Among 3 062 190 women who underwent 7 444 450 examinations in the study population, the screened population by mobile units accounted for approximately 45.45 % of total examinations. The volume of screening mammograms performed in the mobile unit increased the number of people reached by this program. Since 2015, screenings performed in the mobile units have outnumbered those performed at brick-and-mortar hospitals: they comprised 480 456 of the 859 221 examinations (55.9%) performed in 2019. During the 10-year periods, the screen-detected cancers were 12 000 and 18 370 for mobile units and hospital units, respectively. Young women preferred screening in hospitals, resulting in a greater proportion of screen-detected cancers among those attending hospitals (49.4%) compared to the mobile unit (34.3%). The mean recall rate was higher in the hospitals at 8.95% (95% CI, 8.93%-8.99%) than in the mobile units at 7.27% (95% CI, 7.25%-7.32%). Conclusion Implementing mobile units increased the coverage of the screening program across the population. Hospital units had a younger patient population and higher recall rate than those mobile units. We can enhance mammography screening rates and follow-up among these groups by identifying these features, which can use to develop programs and materials fitting populations' specific requirements. Summary statement In Taiwan, the development of breast cancer screening has shown beneficial outcomes, especially with the deployment of mobile unit services to increase screened women. Our results could serve as an informative reference for other nations. Keywords: Breast cancer; screening; mobile units; hospital units. Table 1. Clinical Demographics for Mammographic Screening Examinations Table 2. Performance Measures of Digital Mammographic Screenings for Breast Cancer Citation Format: Vy Vu, Amy Ming-Fang Yen, Melissa Min-Szu Yao, Wing P. Chan. The Performance Of Mobile Units Versus Hospital Units In National Breast Cancer Screening Program In Taiwan, 2010-2020 [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-10-09.

BI-RADS Category Assignments by GPT-3.5, GPT-4, and Google Bard: A Multilanguage Study.

Background The performance of publicly available large language models (LLMs) remains unclear for complex clinical tasks. Purpose To evaluate the agreement between human readers and LLMs for Breast Imaging Reporting and Data System (BI-RADS) categories assigned based on breast imaging reports written in three languages and to assess the impact of discordant category assignments on clinical management. Materials and Methods This retrospective study included reports for women who underwent MRI, mammography, and/or US for breast cancer screening or diagnostic purposes at three referral centers. Reports with findings categorized as BI-RADS 1-5 and written in Italian, English, or Dutch were collected between January 2000 and October 2023. Board-certified breast radiologists and the LLMs GPT-3.5 and GPT-4 (OpenAI) and Bard, now called Gemini (Google), assigned BI-RADS categories using only the findings described by the original radiologists. Agreement between human readers and LLMs for BI-RADS categories was assessed using the Gwet agreement coefficient (AC1 value). Frequencies were calculated for changes in BI-RADS category assignments that would affect clinical management (ie, BI-RADS 0 vs BI-RADS 1 or 2 vs BI-RADS 3 vs BI-RADS 4 or 5) and compared using the McNemar test. Results Across 2400 reports, agreement between the original and reviewing radiologists was almost perfect (AC1 = 0.91), while agreement between the original radiologists and GPT-4, GPT-3.5, and Bard was moderate (AC1 = 0.52, 0.48, and 0.42, respectively). Across human readers and LLMs, differences were observed in the frequency of BI-RADS category upgrades or downgrades that would result in changed clinical management (118 of 2400 [4.9%] for human readers, 611 of 2400 [25.5%] for Bard, 573 of 2400 [23.9%] for GPT-3.5, and 435 of 2400 [18.1%] for GPT-4; P < .001) and that would negatively impact clinical management (37 of 2400 [1.5%] for human readers, 435 of 2400 [18.1%] for Bard, 344 of 2400 [14.3%] for GPT-3.5, and 255 of 2400 [10.6%] for GPT-4; P < .001). Conclusion LLMs achieved moderate agreement with human reader-assigned BI-RADS categories across reports written in three languages but also yielded a high percentage of discordant BI-RADS categories that would negatively impact clinical management. © RSNA, 2024 Supplemental material is available for this article.

RADIATION EXPOSURE IN ROUTINE MAMMOGRAPHY SCREENING: A LARGE OBSERVATIONAL CROSS-SECTIONAL STUDY IN MOROCCO

This observational cross-sectional study aimed to assess radiation exposure during mammography for breast cancer screening in Morocco and highlight the importance of dose optimization.&#x0D; Patient data from 1100 mammographic examinations conducted in five units in the Rabat-Salé-Zemmour-Zaër region were collected. The mean glandular dose (MGD) and technical parameters, such as exposure factors and breast thickness, were analyzed. The data were compared with international studies to provide context.&#x0D; The overall mean MGD was 1.34 ± 0.36 mGy for craniocaudal (CC) and 1.48 ± 0.38 mGy for mediolateral oblique (MLO) incidences. The MGD varied among different units and anode/filter combinations. The Rh/Rh anode/filter combination was most commonly used, resulting in the lowest radiation dose. The study findings also highlighted the relationship between MGD and breast thickness, with higher doses observed for thicker breasts.&#x0D; This study provides valuable insights into radiation exposure during mammography breast cancer screening in Morocco. The results underscore the importance of dose optimization strategies to ensure patient safety without compromising diagnostic image quality. Implementing optimized technical parameters, conducting regular quality assurance programs, and promoting education and awareness are essential in achieving dose reduction and minimizing radiation risks. Collaboration among healthcare professionals, regulatory bodies, and international organizations is crucial for sharing best practices and advancing radiation dose optimization in mammography.&#x0D;

Application of Artificial Intelligence (AI) System in Opportunistic Screening and Diagnostic Population in a Middle-income Nation.

This study evaluates the effectiveness of artificial intelligence (AI) in mammography in a diverse population from a middle-income nation and compares it to traditional methods. A retrospective study was conducted on 543 mammograms of 467 Malays, 48 Chinese, and 28 Indians in a middle-income nation. Three breast radiologists interpreted the examinations independently in two reading sessions (with and without AI support). Breast density and BI-RADS categories were assessed, comparing the accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) results. Of 543 mammograms, 69.2% had lesions detected. Biopsies were performed on 25%(n=136), with 66(48.5%) benign and 70(51.5%) malignant. Substantial agreement in density assessment between the radiologist and AI software (κ =0.606, p < 0.001) and the BI-RADS category with and without AI (κ =0.74, p < 0.001). The performance of the AI software was comparable to the traditional methods. The sensitivity, specificity, PPV, and NPV or radiologists alone, radiologist + AI, and AI alone were 81.9%,90.4%,56.0%, and 97.1%; 81.0%, 93.1%,55.5%, and 97.0%; and 90.0%,76.5%,36.2%, and 98.1%, respectively. AI software enhances the accuracy of lesion diagnosis and reduces unnecessary biopsies, particularly for BI-RADS 4 lesions. The AI software results for synthetic were almost similar to the original 2D mammography, with AUC of 0.925 and 0.871, respectively. AI software may assist in the accurate diagnosis of breast lesions, enhancing the efficiency of breast lesion diagnosis in a mixed population of opportunistic screening and diagnostic patients. • The use of artificial intelligence (AI) in mammography for population-based breast cancer screening has been validated in high-income nations, with reported improved diagnostic performance. Our study evaluated the usage of an AI tool in an opportunistic screening setting in a multi-ethnic and middle-income nation. • The application of AI in mammography enhances diagnostic accuracy, potentially leading to reduced unnecessary biopsies. • AI integration into the workflow did not disrupt the performance of trained breast radiologists, as there is a substantial inter-reader agreement for BI-RADS category assessment and breast density.

A multi-task fusion model based on a residual–Multi-layer perceptron network for mammographic breast cancer screening

Background and objectiveDeep learning approaches are being increasingly applied for medical computer-aided diagnosis (CAD). However, these methods generally target only specific image-processing tasks, such as lesion segmentation or benign state prediction. For the breast cancer screening task, single feature extraction models are generally used, which directly extract only those potential features from the input mammogram that are relevant to the target task. This can lead to the neglect of other important morphological features of the lesion as well as other auxiliary information from the internal breast tissue. To obtain more comprehensive and objective diagnostic results, in this study, we developed a multi-task fusion model that combines multiple specific tasks for CAD of mammograms. MethodsWe first trained a set of separate, task-specific models, including a density classification model, a mass segmentation model, and a lesion benignity–malignancy classification model, and then developed a multi-task fusion model that incorporates all of the mammographic features from these different tasks to yield comprehensive and refined prediction results for breast cancer diagnosis. ResultsThe experimental results showed that our proposed multi-task fusion model outperformed other related state-of-the-art models in both breast cancer screening tasks in the publicly available datasets CBIS-DDSM and INbreast, achieving a competitive screening performance with area-under-the-curve scores of 0.92 and 0.95, respectively. ConclusionsOur model not only allows an overall assessment of lesion types in mammography but also provides intermediate results related to radiological features and potential cancer risk factors, indicating its potential to offer comprehensive workflow support to radiologists.

Distant migration of copolyamide breast filler following mammography: a case report

Copolyamide fillers, such as Aquafilling, have been used off-label for breast augmentation in many countries, including Korea. However, safety concerns have arisen due to reported complications, including induration, masses, mastalgia, firmness, asymmetry, migration, infection, and dimpling. We report the case of a 33-year-old woman who presented with distant migration of copolyamide breast filler to the left lower abdomen and inguinal area following mammography for breast cancer screening. This case highlights the potential risks associated with the migration of copolyamide breast fillers, particularly in the context of cancer screening procedures, and emphasizes the importance of awareness and vigilance among clinicians and patients.

Harms and benefits of mammographic screening for breast cancer in Brazil.

In the absence of evidence on the effect of mammographic screening on overall mortality, comparing the number of deaths avoided with the number of deaths caused by screening would be ideal, but the only existing models of this type adopt a very narrow definition of harms. The objective of the present study was to estimate the number of deaths prevented and induced by various mammography screening protocols in Brazil. A simulation study of cohorts of Brazilian women screened, considering various age groups and screening interval protocols, was performed based on life tables. The number of deaths avoided and caused by screening was estimated, as was the absolute risk reduction, the number needed to invite for screening-NNS, the net benefit of screening, and the ratio of "lives saved" to "lives lost". Nine possible combinations of balances between benefits and harms were performed for each protocol, in addition to other sensitivity analyses. The most efficient protocol was biennial screening from 60 to 69 years of age, with almost three times more deaths avoided than biennial screening from 50 to 59 years of age, with a similar number of deaths avoided by biennial screening from 50 to 69 years of age and with the greatest net benefit. Compared with the best scenario of annual screening from 40 to 49 years of age, the NNS of the protocol with biennial screening from 60 to 69 years of age was three-fold lower. Even in its best scenario, the addition of annual screening from 40 to 49 years of age to biennial screening from 50 to 69 years of age results in a decreased net benefit. However, even in the 50-69 year age group, the estimated reduction in breast cancer mortality for Brazil was half that estimated for the United Kingdom.

Cost-Effectiveness Analysis of Digital Breast Tomosynthesis Added to Synthetic Mammography in Breast Cancer Screening in Brazil.

Literature meta-analysis results show that digital breast tomosynthesis (DBT) combined with synthesized two-dimensional (s2D) mammograms can reduce recalls and improve breast cancer detection. Uncertainty regarding the screening of patients with breast cancer presents a health economic challenge, both in terms of healthcare resource use and quality of life impact on patients. This study aims to estimate the cost effectiveness of DBT + s2D versus digital mammography (DM) used in a biennial breast cancer screening setting of women aged 40-69 years with scattered areas of fibroglandular breast density and heterogeneous dense breasts in the Brazilian supplementary health system. A cost-effectiveness analysis was performed on the basis of clinical data obtained from a systematic review with meta-analysis performed to evaluate the analytical validity and clinical utility of DBT + s2D compared with DM. The search was conducted in the PubMed, Cochrane Library and Embase databases, with the main descriptors of the technology, a comparator, and the clinical condition in question, on 9 June 2022. The hybrid economic model (decision tree plus Markov model) simulated costs and outcomes over a lifetime for women aged 40-69 years with scattered areas of fibroglandular breast density and heterogeneous dense breasts. We analyzed incremental cost-effectiveness ratio (ICER) to measure the incremental cost difference per quality-adjusted life year (QALY) of adding DBT + s2D to breast cancer screening. DBT + s2D incurred a cost saving of € 954.02 per patient, in the time horizon of 30 years, compared with DM, and gained 5.1989 QALYs, which would be considered a dominant intervention. These results were confirmed in sensitivity analyses. Switching from DM to biennial DBT + s2D was cost effective. Furthermore, reductions in false-positive recall rates should also be considered in decision making.

Protocol to measure validity and reliability of colorectal, breast, cervical and lung cancer screening questions from the 2021 National Health Interview Survey: Methodology and design.

Previous studies demonstrate that self-reports of mammography screening for breast cancer and colonoscopy screening for colorectal cancer demonstrate concordance, based on adherence to screening guidelines, with electronic medical records (EMRs) in over 90% of those interviewed, as well as high sensitivity and specificity, and can be used for monitoring our Healthy People goals. However, for screening tests for cervical and lung cancers, and for various sub-populations, concordance between self-report and EMRs has been noticeably lower with poor sensitivity or specificity. This study aims to test the validity and reliability of lung, colorectal, cervical, and breast cancer screening questions from the 2021 and 2022 National Health Interview Survey (NHIS). We present the protocol for a study designed to measure the validity and reliability of the NHIS cancer screening questions compared to EMRs from four US-based healthcare systems. We planned a randomized trial of a phone- vs web-based survey with NHIS questions that were previously revised based on extensive cognitive interviewing. Our planned sample size will be 1576 validity interviews, and 1260 interviews randomly assigned at 1 or 3 months after the initial interview. We are enrolling people eligible for cancer screening based on age, sex, and smoking history per US Preventive Services Task Force recommendations. We will evaluate question validity using concordance, sensitivity, specificity, positive predictive value, negative predictive value, and report-to-records ratio. We further are randomizing participants to complete a second survey 1 vs 3 months later to assess question reliability. We suggest that typical measures of concordance may need to be reconsidered in evaluating cancer screening questions.

Artificial Intelligence in the Detection of Breast Cancer

Breast carcinoma, the prevalently existing malignancy and the primary cause of disease mortality among females worldwide. Breast cancer is determined by a multitude of elements, including ageing, genetic history, specific alterations and genetic variations, a record of fecundity and menopause, a sedentary lifestyle, alcohol use, adiposity, nutrition, race and pectoral radiation treatment. Since the previous two decades, various researches on breast cancer has enabled significant advancements in our understanding of the condition, leading to more effective and non-toxic treatments. Increased scanning and public awareness have enabled early detection at stages amenable to full surgical intervention and curative therapy. Breast cancer screening mammography tries to detect the illness at an early stage when therapy would be more effective. Because mammography are such high-resolution images, researchers have thought of putting AI technology to use. They've trained the AI to examine minute patches and create a map of the most dangerous areas. The research shows that AI can recognize differences that are unnoticeable and recognizes breast tumors exactly like a skilled radiologist, providing the most accurate data. As a result, the incidence of this disease has dramatically increased,especially among juveniles. In this article, there are discussions about several causes, medical signs, non-drug treatments (such as radiation and surgery), and drugs (such as chemotherapy, and gene therapy) and thus, its detection by AI.In clinical medicine, AI can aid in establishing diagnoses and predicting the progression of disease in the future. AI jobs go beyond the computer-aided detection that is already used. AI's automated capabilities have the potential to advance medical professionals' diagnostic abilities in fields including exact tumor volume delineation, cancer phenotype extraction, translation of tumoral phenotypic characteristics to clinical genotype ramifications, and risk prediction. In breast cancer, the value of integrating image-specific data with underlying biological,pathologic, and clinical traits is growing.

Exploring&amp;nbsp; the Awareness of Mammographic Screening for Breast Cancer and Identifying Barriers to Refrain from Screening:&amp;nbsp; Mini Review of the Literature

One of the most important factors to be addressed regarding breast cancer (BC) mortality and morbidity is the identification of BC at a late stage due to a lack of awareness of early detection methods of BC. Mammography can be emphasized as a foremost vital facet in the early detection of breast cancer as a screening tool. A mini review of the literature was performed to explore the concepts of awareness of screening mammography for breast cancer under three main aspects. There, the knowledge, attitude, and practice of women in mammographic screening were focused meanwhile identifying the common barriers for women to refrain from undergoing mammographic screening for breast cancer. The studies included various categories of participants especially subcategorized under their personal history or demographic characteristics. Therefore, the correlation of these factors with their awareness level has also been focused. Further, the barriers to screening mammography encountered by women were included. Therefore, this mini-review highlights the different levels of awareness of mammographic screening among females and the common reasons for avoiding screening. It concludes the benefit of bringing the knowledge of females to a considerably positive juncture by utilizing escalating awareness programs, hence minimizing the common causes of refraining from screening mammography.

Emotions and Narrative Reappraisal Strategies of Users of Breast Cancer Screening: Reconstructing the Past, Passing Through the Present, and Predicting Emotions.

Emotional forecasting, meaning how a person anticipates feeling as a consequence of their choices, drives healthcare decision-making. Research, however, suggests that people often do not fully anticipate or otherwise grasp the future emotional impacts of their decisions. Emotional reappraisal strategies, such as putting emotions into words and sharing emotions with others, may mitigate potential undesirable effects of emotions on decision-making. The use of such strategies is important for consequential decisions, such as obtaining timely mammography screening for breast cancer, whereby earlier diagnosis may impact the success of treatment. In this study, we explored the use of emotional reappraisal strategies for decision-making regarding breast cancer screening attendance among women aged 50-69years. Data were collected through semi-structured interviews following mammography with a reflexive thematic methodological approach employed for analysis. Results shed light on how participants' emotional response narratives were reconstructed before the mammography, felt during the mammography, and forecasted while awaiting the results. Future research should consider how individuals experience and manage their emotions as they access breast screening services.

Performance measures of 8,169,869 examinations in the National Breast Cancer Screening Program in Taiwan, 2004–2020

BackgroundThe benefits of mammographic screening have been shown to include a decrease in mortality due to breast cancer. Taiwan’s Breast Cancer Screening Program is a national screening program that has offered biennial mammographic breast cancer screening for women aged 50–69 years since 2004 and for those aged 45–69 years since 2009, with the implementation of mobile units in 2010. The purpose of this study was to compare the performance results of the program with changes in the previous (2004–2009) and latter (2010–2020) periods.MethodsA cohort of 3,665,078 women who underwent biennial breast cancer mammography screenings from 2004 to 2020 was conducted, and data were obtained from the Health Promotion Administration, Ministry of Health and Welfare of Taiwan. We compared the participation of screened women and survival rates from breast cancer in the earlier and latter periods across national breast cancer screening programs.ResultsAmong 3,665,078 women who underwent 8,169,869 examinations in the study population, the screened population increased from 3.9% in 2004 to 40% in 2019. The mean cancer detection rate was 4.76 and 4.08 cancers per 1000 screening mammograms in the earlier (2004–2009) and latter (2010–2020) periods, respectively. The 10-year survival rate increased from 89.68% in the early period to 97.33% in the latter period. The mean recall rate was 9.90% (95% CI: 9.83–9.97%) in the early period and decreased to 8.15% (95%CI, 8.13–8.17%) in the latter period.ConclusionsThe evolution of breast cancer screening in Taiwan has yielded favorable outcomes by increasing the screening population, increasing the 10-year survival rate, and reducing the recall rate through the participation of young women, the implementation of a mobile unit service and quality assurance program, thereby providing historical evidence to policy makers to plan future needs.

Predictive factors of breast cancer mammography screening among Iranian women.

Understanding the factors that influence women's cancer screening behavior is crucial in reducing cancer mortality through early detection. Therefore, the objective of this study was to examine the status of mammography and related factors among women who presented to the health centers of Khorasan Razavi province, Iran. For this study, a sample of 251,011 women who visited healthcare centers affiliated with Mashhad University of Medical Sciences was selected. The study examined several variables, including sociodemographic information, current smoking, nutrition status, and physical exercise. All analyses were performed using Python programming language and SPSS software. Furthermore, to handle imbalanced data, we used SMOTE balancing method that is an oversampling method and produce synthetic samples from the minority class. The factors of age, education, being employed, having children, family history of cancer, physical activity, smoking status, and diet were all predictors of mammography screening. Moreover, findings showed that age and family history of breast cancer were most important variables to predict mammography status, respectively. By examining various variables such as dietary habits, exercise, smoking, and demographic properties, it sheds light on the relationships between these factors and mammography screening. This provides valuable insights into the associations between breast cancer screening behavior and preventive lifestyle behaviors. By targeting both preventive lifestyle choices and breast cancer screening behaviors, interventions can effectively promote positive changes in behavior and ultimately reduce the incidence and impact of breast cancer.

Efficiency of mammography for breast cancer screening

Efficiency of mammography for breast cancer screening

Mammography Breast Cancer Screening Triage Using Deep Learning: A UK Retrospective Study.

Background Breast screening enables early detection of cancers; however, most women have normal mammograms, resulting in repetitive and resource-intensive reading tasks. Purpose To investigate if deep learning (DL) algorithms can be used to triage mammograms by identifying normal results to reduce workload or flag cancers that may be overlooked. Materials and Methods In this retrospective study, three commercial DL algorithms were investigated using consecutive mammograms from two UK Breast Screening Program sites from January 2015 to December 2017 and January 2017 to December 2018 on devices from two mammography vendors. Normal mammograms with a 3-year follow-up and histopathologically proven cancer detected at screening, the subsequent round, or in the 3-year interval were included. Two algorithm thresholds were set: in scenario A, 99.0% sensitivity for rule-out triage to a lone reader, and in scenario B, approximately 1.0% additional recall providing a rule-in triage for further assessment. Both thresholds were then applied to the screening workflow in scenario C. The sensitivity and specificity were used to assess the overall predictive performance of each DL algorithm. Results The data set comprised 78 849 patients (median age, 59 years [IQR, 53-63 years]) and 887 screening-detected, 439 interval, and 688 subsequent screening round-detected cancers. In scenario A (rule-out triage), models DL-1, DL-2, and DL-3 triaged 35.0% (27 565 of 78 849), 53.2% (41 937 of 78 849), and 55.6% (43 869 of 78 849) of mammograms, respectively, with 0.0% (0 of 887) to 0.1% (one of 887) of screening-detected cancers undetected. In scenario B, DL algorithms triaged in 4.6% (20 of 439) to 8.2% (36 of 439) of interval and 5.2% (36 of 688) to 6.1% (42 of 688) of subsequent-round cancers when applied after the routine double-reading workflow. Combining both approaches in scenario C resulted in an overall noninferior specificity (difference, -0.9%; P < .001) and superior sensitivity (difference, 2.7%; P < .001) for the adaptive workflow compared with routine double reading for all three algorithms. Conclusion Rule-out and rule-in DL-adapted triage workflows can improve the efficiency and efficacy of mammography breast cancer screening. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Nishikawa and Lu in this issue.

Impact of breast density on diagnostic accuracy in digital breast tomosynthesis versus digital mammography: results from a European screening trial

BackgroundThe diagnostic accuracy of digital breast tomosynthesis (DBT) and digital mammography (DM) in breast cancer screening may vary per breast density subgroup. The purpose of this study was to evaluate which women, based on automatically assessed breast density subgroups, have the greatest benefit of DBT compared with DM in the prospective Malmö Breast Tomosynthesis Screening Trial.Materials and methodsThe prospective European, Malmö Breast Tomosynthesis Screening Trial (n = 14,848, Jan. 27, 2010–Feb. 13, 2015) compared one-view DBT and two-view DM, with consensus meeting before recall. Breast density was assessed in this secondary analysis with the automatic software Laboratory for Individualized Breast Radiodensity Assessment. DBT and DM’s diagnostic accuracies were compared by breast density quintiles of breast percent density (PD) and absolute dense area (DA) with confidence intervals (CI) and McNemar’s test. The association between breast density and cancer detection was analyzed with logistic regression, adjusted for ages < 55 and ≥ 55 years and previous screening participation.ResultsIn total, 14,730 women (median age: 58 years; inter-quartile range = 16) were included in the analysis. Sensitivity was higher and specificity lower for DBT compared with DM for all density subgroups. The highest breast PD quintile showed the largest difference in sensitivity and specificity at 81.1% (95% CI 65.8–90.5) versus 43.2% (95% CI 28.7–59.1), p < .001 and 95.5% (95% CI 94.7–96.2) versus 97.2% (95% CI 96.6–97.8), p < 0.001, respectively. Breast PD quintile was also positively associated with cancer detected via DBT at odds ratio 1.24 (95% CI 1.09–1.42, p = 0.001).ConclusionWomen with the highest breast density had the greatest benefit from digital breast tomosynthesis compared with digital mammography with increased sensitivity at the cost of slightly lower specificity. These results may influence digital breast tomosynthesis’s use in an individualized screening program stratified by, for instance, breast density.Trial registration. Trial registration at https://www.ClinicalTrials.gov: NCT01091545, registered March 24, 2010.