Breast Cancer Screening Modalities Research Articles

The Association of Mammographic Breast Density and Breast Cancer Biology Among Breast Cancer Women in Jordan

Background: A breast mammogram is considered the gold standard modality for breast cancer screening. The sensitivity of breast mammograms is highly linked to mammographic breast density (MBD) which is strongly linked to women's age, ethnicity, and other factors. Higher breast density is considered one of the risk factors for breast cancer development and it can be associated with different pathological and biological features of breast cancer. Methods: This is a retrospective review of 97 women with a diagnosis of breast cancer in a tertiary hospital in Jordan who were diagnosed in the period between 2018 and 2020. We compared patients with a positive status for estrogen (ER) or progesterone (PR) receptors (ER+/PR+) and others with negative receptors (ER-/PR-), in terms of their correlation with MBD. Results: The analysis has included 97 patients. Of which, 87.6% had either a PR+ or an ER+, and 38.1% of patients were positive for HER2/neu protein. The sample mean age was 56.4 and most patients were obese (56.7%). MBD of our cohort was 30.9% (30/97) fatty, 29.9% (29/97) scattered, 23.7% (23/97) heterogeneously dense, and 15.5% (15/97) dense. The ER+/PR+ group was more associated with fatty (35.3% vs 0.0%) and scattered (31.8% vs 25.0%) MBD types than the ER-/PR- group, and less associated with the dense type (9.4% vs 58.3%), and the association was statistically significant (P < 0.001). However, no statistically significant correlation was found between MBD and the HER2/neu protein status. Conclusion: According to our results, ER+/PR+ group patients tend to have fatty and scattered MBD types than the ER-/PR- patients. Larger randomized cohorts should investigate the association between breast cancer biological subtypes and MBD.

Automated Breast Ultrasound With Remote Reading for Primary Breast Cancer Screening: A Prospective Study Involving 46 Community Health Centers in China.

Background: China has faced barriers to implementation of a population-based mammographic screening program. Breast ultrasound provides an alternative screening modality to mammography in low-resource settings. Objective: To evaluate the performance of ABUS with remote reading as the primary screening modality for breast cancer. Methods: This prospective study enrolled asymptomatic women 35-69 years old from 46 community health centers across 18 provinces representing all six regions of China from January 2021 to December 2021. Participants underwent screening ABUS as the sole breast cancer screening modality, with images acquired by a technologist at the community health center. The 3D volumetric data were transferred via cloud-based software to a single remote reading center, where examinations were interpreted independently in batches by two subspecialized breast radiologists using BI-RADS; a third radiologist at the remote reader center resolved discrepancies. Diagnostic reports were returned to the community centers, and patients sought follow-up care at local hospitals. The reference standard incorporated a combination of histopathology and 24-month follow-up. Outcomes measures included cancer detection rate, abnormal interpretation rate (AIR), sensitivity, specificity, biopsy rate, and PPV. Results: The final analysis included 5978 enrolled participants (median age, 46 years [IQR 40-52 years]) who underwent screening ABUS at the community health centers with subsequent remote reading. A total of 24 ABUS-detected cancers and two interval cancers were diagnosed. The cancer detection rate was 4.0 per 1000 women (95% CI: 2.7-5.9), and the AIR was 11.9% (95% CI: 11.1-12.7). A total of 95.8% (23/24) of ABUS-detected cancers were invasive. The 23 invasive cancers had a median diameter of 10.0 mm; 73.9% (17/23) were node-negative. Sensitivity was 92.3% (95% CI: 75.9-97.9), and specificity was 88.4% (95% CI: 87.6-89.2). The biopsy rate was 1.7% (95% CI: 1.4-2.0), and the PPV of biopsy was 24.0% (95% CI: 16.7-33.2). Conclusion: ABUS screening with remote reading met benchmark performance for cancer detection in comparison to mammography, with infrequent interval cancers. Clinical Impact: ABUS with remote reading holds promise in enhancing access to breast cancer screening and early detection in low-resource settings or underserved regions where mammographic screening is not established.

Effectiveness of Breast Ultrasound for Breast Cancer Screening : A Systematic Review

Breast cancer is the most common cancer in Indonesia and has the highest mortality rate in women. Nowadays, the primary prevention is not clear yet to prevent the breast cancer. Secondary prevention with radiological modality is the only option to decrease the mortality of breast cancer. This study aims to identify ultrasound effectiveness and accuracy as a screening modality for early detection of breast cancer. Methods: A systematic review was analyzed using PRISMA without a meta-analysis method on articles published in 2014-2024. Articles searches were conducted using PubMed, Science Direct, and Google Scholar Database. Result: Based on the search results, seven eligible articles met the criteria for analysis. We found consistent evidence in 5 studies that breast cancer screening using ultrasound has high sensitivity (range sensitivity 68.9%-100%) and accuracy (range accuracy 0.687-0.999) compared to mammography alone. Breast ultrasound specificity is lower than mammography, ranging from 22% to 99.9%. The positive predictive value ranges from 4.3%-70%, and the negative predictive value of breast ultrasound ranges from 61.2%-100%. Conclusion: Breast Ultrasound can be an option as a breast cancer screening modality, especially in young women with dense breasts. It can be used in health facilities where mammography is unavailable.

Ultra-Low Frequency Transmitted Ultrasound Breast Imaging vs DBT (Digital Breast Tomosynthesis): A Patient-Reported Outcome Study.

Breast cancer screening remains a challenge in the United States. Many women do not get a mammogram because of pain associated with the exam, radiation exposure, false-positive results, and additional costs. Others who may benefit from annual screening do not qualify because of young age and radiation risk. We hypothesize that a novel volumetric transmitted breast ultrasound, Quantitative Transmission (QT) Scan may encourage more women to have annual breast cancer screening. Assessing results from patient-reported outcomes (PROs) may predict the value of newer, more desirable screening technologies. Pre- and post-menopausal women who qualified for breast cancer screening were enrolled in a prospective trial of Quantitative Transmission (QT Scan) vs traditional mammography via Digital Breast Tomosynthesis (DBT) Clinical Trials.gov NCT03052166. These women completed questionnaires to assess their experiences with QT Scan and DBT. Associations between QT Scan or DBT and differences in PRO scores were examined. A total of 430 subjects completed the PRO instrument analyzed. A total of 36 questions were asked, 34 were paired for both QT and DBT and two were asked regarding exclusively the QT Scan. Physical discomfort, perceptions of safety and low efficacy, false-positive results and additional out-of-pocket expenses were concerns identified as highest risk for opting out of screening mammography (differences between 2.1 and 2.9 indicate significant differences between means and standard deviations using the Cohen's d statistic). Student's T-test shows a significance level of <10 -10. Statistically significant differences in PROs between QT Scan and DBT were observed by 14 of the 17 paired experience questions (p<0.001). Significant differences in PROs were found between QT scan and DBT, indicating women have significantly more negative experiences with traditional mammography via DBT and are less inclined to undergo screening mammography. Identification of PRO differences could be used to help identify a more desirable breast cancer screening modality.

Comparing Personal Risk Communication with Generic Information on Breast Cancer Screening Attendance: A Randomized Controlled Trial

Objective: This study sought to discern the differential impacts of communicating individualized breast cancer risk versus disseminating generic breast cancer information on women's proclivity towards breast cancer screenings. Method: A structured experimental design was used, including 300 female volunteers aged between 40-69, who had not previously been diagnosed with breast cancer, in Erzincan. Data collection entailed a face-to-face administration of a 22-item questionnaire complemented by the ASSISTS scale. Participants were randomized into two conditions: one receiving a standardized briefing on breast cancer screening modalities, and the other being apprised of their lifetime risk of breast cancer development based on the modified Gail model. Results: Post-intervention, 55.8% (n=72) of the risk-informed cohort and 40.5% (n=41) of the generic information cohort expressed a willingness to undergo screening (p=0.022). Notably, the group informed of their personalized risk exhibited a more pronounced uptick in requests for breast self-examination, clinical breast examination, and mammography screening compared to their counterparts. Conclusion: The communication of personalized breast cancer risk proves to be a more efficacious and time-efficient strategy than generic information dissemination in bolstering screening participation rates.

Automated Breast Tumor Detection and Segmentation Using the Threshold Density Algorithm with Logistic Regression on Microwave Images

Context: Breast cancer remains a major health burden worldwide, necessitating improved screening modalities for early detection. However, existing techniques such as mammography and MRI exhibit limitations regarding sensitivity and specificity. Microwave imaging has recently emerged as a promising technology for breast cancer diagnosis, exploiting the dielectric contrast between normal and malignant tissues. Objectives: This study proposes a novel computational framework integrating thresholding, edge segmentation, and logistic regression to enhance microwave image-based breast tumor delineation. Methodology: The employed algorithm selects optimal features using logistic regression to mitigate the class imbalance between tumor and healthy tissues. Localized density thresholds are applied to identify tumor regions, followed by edge segmentation methods to precisely localize the detected lesions. Results: When evaluated on a dataset of microwave breast images, our approach demonstrated high accuracy for detecting and segmenting malignant tissues. Density thresholds ranging from 0.1 to 0.8 showcase the highest accuracy in detecting breast tumors from these images. Conclusions: The results highlight the potential of the proposed segmentation algorithm to improve the reliability of microwave imaging as an adjunct modality for breast cancer screening. This could promote earlier diagnosis and better clinical outcomes. The proposed framework represents a significant advance in developing robust image processing techniques tailored to emerging medical imaging modalities challenged by class imbalance and low intrinsic contrast.

SIFT-DBT: SELF-SUPERVISED INITIALIZATION AND FINE-TUNING FOR IMBALANCED DIGITAL BREAST TOMOSYNTHESIS IMAGE CLASSIFICATION.

Digital Breast Tomosynthesis (DBT) is a widely used medical imaging modality for breast cancer screening and diagnosis, offering higher spatial resolution and greater detail through its 3D-like breast volume imaging capability. However, the increased data volume also introduces pronounced data imbalance challenges, where only a small fraction of the volume contains suspicious tissue. This further exacerbates the data imbalance due to the case-level distribution in real-world data and leads to learning a trivial classification model that only predicts the majority class. To address this, we propose a novel method using view-level contrastive Self-supervised Initialization and Fine-Tuning for identifying abnormal DBT images, namely SIFT-DBT. We further introduce a patch-level multi-instance learning method to preserve spatial resolution. The proposed method achieves 92.69% volume-wise AUC on an evaluation of 970 unique studies.

Abstract 6078: Circulating tumor cell-based early detection of breast cancer

Abstract Although mammograms have been a useful tool since the first half of the 20th century and have an acceptable sensitivity (87%) in the general population, that drops to &amp;lt;50% in women with dense breasts making it an ineffective screening tool in this population. Cell free DNA (cfDNA) has proven to be an inadequate alternative in this population, and while MRI is acceptable, it is expensive. Astrin Biosciences has developed a blood-based assay that detects circulating tumor cells (CTCs) at a high sensitivity to serve as an alternative screening method to mammography in breast cancer early detection, specifically in women with high-density breasts. Astrin’s technology integrates holographic imaging, machine learning, and microfluidics to identify CTCs in the blood stream. Omics analysis can then be performed on the collected cells to further differentiate patients with cancer from matched healthy controls. Astrin has initiated a small cohort study to investigate the sensitivity and specificity of CTC detection in women with early-stage breast cancer. Astrin’s small cohort study, including patients with ductal carcinoma in situ, stage 1, and stage 2 breast cancer patients, demonstrated &amp;gt; 85% sensitivity and specificity. A large cohort study is being conducted to validate these preliminary results. The small cohort study demonstrates the ability of Astrin Bioscience’s platform to detect cancer cells at an early stage, particularly in breast cancer. This technology will drastically increase the effectiveness of breast cancer screening modalities available to patients. Additionally, since it is a blood-based assay, it can be performed at shorter intervals in high-risk populations than mammograms which require a full patient appointment. Citation Format: Justin M. Drake, Kaylee J. Kamalanathan, Catalina Galeano-Garces, Nathaniel Bristow, Nicholas Heller, Mahdi Ahmadi, Olivia Hedeen, Alexa Hesch, Grant Schaap, Joel Hapke, Jeff Miller, Ivo Babris, Tuan Le, Tony Clacko, Jiarong Hong, Badri Konety, Jayant Parthasarathy. Circulating tumor cell-based early detection of breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6078.

Case Presentation where MRI shows Superiority as A Modality for Breast Cancer Screening

Background: Common modalities for breast cancer screening include regular clinical breast exams (73%), annual breast sonograms (73%) for high-risk groups, and mammograms (71.5%) recommended every 3 years for high-risk groups. Despite a higher sensitivity of 89.4%, MRI is underutilized, especially among high-risk groups with the means for the test. Kenyan guidelines recommend mammography for normal-risk populations, omitting MRI for routine screening in average-risk populations. This study explores an intriguing case of a 60-year-old post-menopausal lady, with no hormone replacement history, three parities, and a smoking habit. She presented with a left-sided benign cyst but revealed an ominous, undetected lesion on the right breast, emphasizing the limitations of conventional screening modalities. Method: The patient was admitted for abdominal pain due to gastroenteritis and a breast lump on the left breast for 3 months with a strong family history of breast cancer, so she requested screening for the same. In the process, we found axillary and mediastinal lymph nodes, but the left breast showed a simple harmless cystic lesion. The right breast confirmed a lesion with irregular borders that looked suspicious, and a biopsy confirmed ductal carcinoma of the right breast. Results: The right breast that had no symptoms or signs, and no abnormality on mammogram, ultrasound, or CT scan, had a grade 3a Ductal Cancer in its initial stage that was seen on a simultaneous MRI. Conclusion: MRI could be a better choice for screening early breast cancer in high-risk groups and in those who can afford the test.

Evaluating Clinical Efficacy of Thermalytix as a Breast Cancer Screening Tool in Young Women

Abstract Objective: Breast cancer remains a significant health challenge worldwide, particularly among women under 45 years of age who often present with dense breast tissue. Mammography, the current gold standard for breast cancer screening, is less effective in this demographic due to reduced sensitivity in detecting malignancies within dense breast tissue. This study evaluates the efficacy of Thermalytix, an artificial intelligence-driven, noninvasive, and radiation-free thermal imaging tool, as a screening modality for breast cancer in young women through a meta-analysis of published studies. Materials and Methods: This meta-analysis aggregated the data from three clinical studies involving a total of 1187 women who first underwent a Thermalytix test followed by reference standard of care (SoC) tests, which included one or more mammography, ultrasound, and biopsy. Among these women, 463 were under 45 years of age and were eligible for this study. Thermalytix analyzed high-resolution thermal images of the breast, utilizing novel radiomic features such as hotspots, vascular patterns, and areolar characteristics to predict malignancy. The performance of Thermalytix was evaluated by computing its sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), with 95% confidence intervals (95% CIs), in both the overall population and the younger cohort by aggregating the data from all studies. Results: Among the 463 young women under 45 years, 43 were diagnosed with breast cancer as per SoC. When raw data were aggregated from this young women cohort, Thermalytix resulted in a sensitivity of 90.7% (95% CI: 82.0%–99.4%), a specificity of 82.1% (95% CI: 78.5%–85.8%), a PPV of 34.2% (95% CI: 25.5%–42.9%), and an NPV of 98.9% (95% CI: 97.7%–100%). The pooled sensitivity and specificity of Thermalytix using the random-effects model were estimated to be 96.0% (95% CI: 88.9%–100%) and 82.3% (95% CI: 78.6%–85.9%), respectively. Further, in the entire population of 1187, Thermalytix showed an aggregated sensitivity of 88.3% (95% CI: 83.3%–93.2%), specificity of 84.7% (95% CI: 82.5%–86.9%), PPV of 47.7% (95% CI: 42.0%–53.3%), and NPV 97.9% (95% CI: 96.9%–98.8%). Conclusions: Thermalytix demonstrated high sensitivity and NPV in women under 45 years of age, suggesting its potential as an effective screening modality for younger women who face challenges with conventional screening methods due to dense breast tissue.

DOTnet 2.0: Deep learning network for diffuse optical tomography image reconstruction

Breast cancer is the most common cancer worldwide. The standard imaging modality for breast cancer screening is X-ray mammography, which suffers from low sensitivities in women with dense breasts and can potentially cause cancers despite a low radiation dosage. Diffuse Optical Tomography (DOT) is a noninvasive imaging technique that can potentially be employed to improve breast cancer early detection. However, conventional model-based algorithms for reconstructing DOT images usually produce low-quality images with limited resolution and low reconstruction accuracy. We propose to integrate deep neural networks (DNNs) with the conventional DOT reconstruction methods. This hybrid framework significantly enhances image quality. The DNNs have been trained and tested with sample data derived from clinically relevant breast models. The sample dataset contains blood vessel structures from breast structures and artificially created vessels using the Lindenmayer-system algorithm. By comparing the hybrid reconstruction with the ground truth image, we demonstrated a multi scale - structural similarity index measure (MS-SSIM) score of 0.80–0.90. Whereas using conventional reconstruction, MS-SSIM provided a much inferior score of 0.36–0.59. In terms of DOT image quality, both qualitative and quantitative assessments of the reconstructed images signify that the hybrid approach is superior to conventional methods. This improvement suggests that DOT can potentially become a viable alternative to breast cancer screening, providing a step towards the next-generation device for optical mammography.

PCOS Detection and Breast Cancer Detection

Polycystic Ovary Syndrome (PCOS) is a prevalent endocrine disorder that affects people with ovaries, typically during their reproductive years. Detecting PCOS is crucial for timely intervention and management. PCOS detection involves a multifaceted approach, encompassing both clinical and laboratory methods. Clinical assessment of PCOS often begins with a comprehensive medical history, physical examination, and evaluation of symptoms, such as irregular menstruation, excess hair growth, and acne. Transvaginal ultrasound is commonly employed to visualize the ovaries and identify the characteristic cysts. Blood tests, measuring hormone levels like testosterone, luteinizing hormone (LH), and follicle-stimulating hormone (FSH), aid in the diagnosis. Additionally, insulin resistance and glucose tolerance tests may be conducted, as PCOS is frequently associated with metabolic disturbances. Breast Cancer Detection: Breast cancer is a significant global health concern, and early detection is essential for improved prognosis and survival rates. Various techniques are employed for breast cancer detection, combining clinical assessment, imaging, and biopsy procedures. Clinical breast examination involves a physical assessment by a healthcare professional to identify any palpable lumps, changes in breast shape, or skin abnormalities. Mammography, a low-dose X-ray, is a primary imaging modality for breast cancer screening. Other imaging techniques, such as ultrasound and magnetic resonance imaging (MRI), are used for supplemental evaluation. In cases where abnormalities are detected, a biopsy is performed to confirm the presence of cancer cells. Biopsies may include fine-needle aspiration, core needle biopsy, or surgical biopsy, providing definitive evidence of malignancy. Advances in technology, such as digital mammography and the development of artificial intelligence algorithms for image analysis, continue to enhance the precision and efficiency of breast cancer detection, thereby contributing to early diagnosis and effective treatment.

3-D breast nodule detection on automated breast ultrasound using faster region-based convolutional neural networks and U-Net

Mammography is currently the most commonly used modality for breast cancer screening. However, its sensitivity is relatively low in women with dense breasts. Dense breast tissues show a relatively high rate of interval cancers and are at high risk for developing breast cancer. As a supplemental screening tool, ultrasonography is a widely adopted imaging modality to standard mammography, especially for dense breasts. Lately, automated breast ultrasound imaging has gained attention due to its advantages over hand-held ultrasound imaging. However, automated breast ultrasound imaging requires considerable time and effort for reading because of the lengthy data. Hence, developing a computer-aided nodule detection system for automated breast ultrasound is invaluable and impactful practically. This study proposes a three-dimensional breast nodule detection system based on a simple two-dimensional deep-learning model exploiting automated breast ultrasound. Additionally, we provide several postprocessing steps to reduce false positives. In our experiments using the in-house automated breast ultrasound datasets, a sensitivity of 93.65%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$93.65\\%$$\\end{document} with 8.6 false positives is achieved on unseen test data at best.

Microwave Breast Sensing via Deep Learning for Tumor Spatial Localization by Probability Maps.

microwave imaging (MWI) has emerged as a promising modality for breast cancer screening, offering cost-effective, rapid, safe and comfortable exams. However, the practical application of MWI for tumor detection and localization is hampered by its inherent low resolution and low detection capability. this study aims to generate an accurate tumor probability map directly from the scattering matrix. This direct conversion makes the probability map independent of specific image formation techniques and thus potentially complementary to any image formation technique. An approach based on a convolutional neural network (CNN) is used to convert the scattering matrix into a tumor probability map. The proposed deep learning model is trained using a large realistic numerical dataset of two-dimensional (2D) breast slices. The performance of the model is assessed through visual inspection and quantitative measures to assess the predictive quality at various levels of detail. the results demonstrate a remarkably high accuracy (0.9995) in classifying profiles as healthy or diseased, and exhibit the model's ability to accurately locate the core of a single tumor (within 0.9 cm for most cases). overall, this research demonstrates that an approach based on neural networks (NN) for direct conversion from scattering matrices to tumor probability maps holds promise in advancing state-of-the-art tumor detection algorithms in the MWI domain.

Breast Cancer After Reduction Mammoplasty: A Population-Based Analysis of Incidence, Treatment and Screening Patterns.

The risk of breast cancer may be decreased in women who undergo reduction mammoplasty. The purpose of this study was to describe the incidence and treatment of breast cancer after reduction mammoplasty and to better understand the use of breast cancer screening modalities in these patients. This population-based retrospective analysis utilized the Discharge Abstract Database held by the Canadian Institute for Health Information and the National Ambulatory Care Reporting System to identify all women aged 20 years or older who underwent reduction mammoplasty in Alberta, Canada. The incidence and treatment of breast cancer were compared among patients who underwent reduction mammoplasty and age-sex-matched controls. Imaging utilization, including the use of mammography, ultrasound, and breast biopsy, was also compared. Between 2003 and 2007, 8021 patients over 20 years old underwent reduction mammoplasty in Alberta. Patients were followed for an average of 12.6 years. Eighty-nine (1.1%) patients who underwent reduction mammoplasty developed breast cancer after surgery, compared to 453 (1.9%) controls (P < 0.0001). Among patients diagnosed with breast cancer, there was no difference in patient and tumor characteristics. Women who underwent reduction mammoplasty were more likely to undergo mastectomy for cancer (41.6% vs 1.5%; P < 0.0001) and were more likely to undergo mammography (66.7% vs 58.7%; P < 0.0001), ultrasound (29.2% vs 26.2%; P < 0.0001) and biopsy for benign disease (7.2% vs 6%, P < 0.0001) compared to controls. Despite an increased frequency of breast cancer screening, the incidence of breast cancer is lower after reduction mammoplasty compared with women who did not undergo breast reduction. After a diagnosis of breast cancer, surgical treatment patterns differ between groups, whereby mastectomy is more common after reduction mammoplasty.

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

ObjectiveTo 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).MethodsClinical 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.ResultsCompared 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.ConclusionsWhile 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.

Barriers to breast cancer screening in a developing middle eastern country: A nationwide survey.

e22517 Background: Breast cancer imposes a significant global health burden not only due to being constantly ranked as the leading malignancy in females, but also due to the immense resulting morbidity and mortality. Despite the presence of screening modalities, the uptake is relatively low due to unidentified barriers in many countries and regions. The Identification of these barriers towards screening is of paramount importance to tackle the health burden imposed by breast cancer, especially in countries like Jordan, a developing middle eastern country. Methods: A self-reporting survey consisting of comprehensive questions regarding the participant’s demographics, medical history, knowledge about breast cancer and the screening modalities was distributed to females aged 25 years and above with no prior history of breast cancer who are residing across the different regions of Jordan. The first consecutive 790 participants were enrolled, and data analysis was performed to identify the key barriers. Results: The mean age of the enrolled study population was 41 ± 9 years old with the majority being married (82.8%), have underwent a higher level of education (86.5%), are non-smokers (75.2%), and are medically insured (72.4%). 209 participants (26.5%) had reported a family history of breast cancer, while 83.4% of the participants reported awareness about breast cancer screening modalities with breast self-examination being the most commonly known modality of screening in 39.2% of the participants. Only 22.4% of the participants were aware of the 3 available screening methods. The majority of the participants (57.1%) did not undergo previous screening. When the participants who did not undergo previous breast cancer screening were compared with those who did, the participants without prior screening were more likely to report the lack of knowledge towards screening modalities (27.7% vs 8.0%) (p-value &lt; 0.001), fear of the results (22.6% vs 13.9%) (p-value = 0.002), fear of pain during or after from the test (10.4% vs 5.9%) (p-value = 0.024), and feeling of embarrassment provoked by the screening test (15.7% vs 6.5%) (p-value &lt; 0.001) as key barriers. On the contrary, there was no statistically significant difference between the two groups when assessing financial aspect of screening uptake as a potential barrier (p-value = 0.860). Conclusions: Despite the considerably high percentage of participants being aware of breast cancer screening modalities, an alarmingly low rate of screening uptake was witnessed due to several barriers. The collective identification of lack of knowledge towards screening modalities and the nature of the available tests, in addition to the fear of the results and pain following the test, and feeling of embarrassment undoubtedly mandates the formulation of comprehensive awareness campaigns that effectively tackle these barriers.

The usefulness of addition of breast-specific gamma imaging to mammography in women with dense breast

BackgroundMammography (MG) has been adopted as a screening modality for breast cancer. However, the diagnostic yield was reported to decrease in women with dense breasts in MG. Several modalities have been introduced to improve the drawbacks. Breast-specific gamma imaging (BSGI) is a new technique in nuclear medicine imaging that could support breast cancer diagnosis. The aim of this study was to evaluate whether the addition of BSGI according to MG category could improve the accuracy of diagnosis and reduce unnecessary studies or biopsies.ResultsFrom February 2013 to December 2018, 548 patients with 628 breast lesions were enrolled in this retrospective study. The performances of BSGI and MG were evaluated for detecting breast cancer. We classified subgroups by adding the results of BSGI for BI-RADS category 0 and 4a lesions on MG. For each subgroup, diagnostic performance was calculated in overall and dense/non-dense. Factors associated with false-negative BSGI were evaluated. The sensitivity of BSGI (88.26%) was comparable to that of MG (87.95%) (P > 0.05). Specificity (81.44%) and AUC (0.85) of BSGI were significantly superior to those of MG (66.83% and 0.77, respectively). In the subgroup analysis of BSGI plus MG, the sensitivity of BSGI + MG0 and BSGI + MG4a were 95.98% and 94.64%, respectively. And specificities were 69.80% and 77.23%, respectively. Sensitivity and AUC of subgroups increased significantly compared to those of MG alone in overall and dense breasts. A nodule ≤ 10 mm and a low Ki-67 showed significant association with the false negativity of BSGI.ConclusionsApplying BSGI to MG, notably for breast lesions with BI-RADS category 0 or 4a, could improve the diagnostic performance, even in dense breasts.

Meta-Analysis of Supplemental Breast Cancer Screening Modalities in Women with Dense Breasts and Negative Mammography.

HomeRadiology: Imaging CancerVol. 5, No. 3 PreviousNext Research HighlightsMeta-Analysis of Supplemental Breast Cancer Screening Modalities in Women with Dense Breasts and Negative MammographyEvelyn Tran, Kimberly RayEvelyn Tran, Kimberly RayEvelyn TranKimberly RayPublished Online:May 5 2023https://doi.org/10.1148/rycan.239012MoreSectionsFull textPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In Highlighted ArticleHussein H, Abbas E, Keshavarzi S, et al. Supplemental breast cancer screening in women with dense breasts and negative mammography: a systematic review and meta-analysis. Radiology 2023;306(3):e221785. Link, Google ScholarArticle HistoryPublished online: May 05 2023 FiguresReferencesRelatedDetailsRecommended Articles RSNA Education Exhibits RSNA Case Collection Vol. 5, No. 3 Metrics Altmetric Score PDF download

Abstract 3029: Barriers to optimal breast cancer screening modalities for high-risk patients in the primary care setting

Abstract Background: Annual screening breast MRIs are endorsed by current breast cancer screening guidelines as an adjunctive screening modality for high-risk patients (defined by more than 20% lifetime risk) in addition to a screening mammogram. Recent studies showed screening breast MRI remained underutilized despite the current recommendations. On the other hand, validated breast cancer risk models for identifying high-risk patients also remained under-recognized among primary care providers. This study aims to identify the potential barriers for primary care providers (PCPs) to using breast cancer risk models and referring high-risk patients to breast MRI for screening. Methods: An anonymous survey was distributed via email to the PCPs and OB/GYN providers in the network of Mount Auburn Hospital, a community teaching hospital affiliated with Harvard Medical School in Cambridge, Massachusetts. The survey included questions regarding breast cancer screening in average-risk and high-risk patients, providers’ understanding of breast cancer risk models, and current referral status of breast MRIs and high-risk/genetic clinics. Results: The survey was sent to 104 providers, and 43 responses were received. When asked about performing breast cancer risk assessments, 58% reported “Always (91-100%)” and 33% said “Often (71-90%)”. For factors to consider when performing risk assessments, most of the providers considered personal medical history (98%), family history (100%), genetic syndrome history (86%), and previous breast biopsy results (90%). When asked about breast cancer risk models, 58% of the providers had not heard of or used one. 33% of the providers have used the Gail model, and 26% have used the Tyrer-Cuzick model. 51% of the providers correctly identified high-risk as lifetime risk &amp;gt;20%. 56% correctly answered annual mammograms with MRI for breast cancer screening for high-risk patients. The majority of the providers (84%) would prefer to refer patients to the high-risk clinic for risk assessment and screening management. For barriers to referring to MRI, the insurance approval process (49%) was reported to be the largest barrier. 72% of the providers prefer not ordering it and defer to the high-risk/genetic clinic for ordering the test. Conclusions: Our survey has shown different barriers to breast cancer screening in high-risk patients in the primary care setting, including knowledge and logistic barriers. Further education for PCPs is needed for correctly identifying high-risk patients, utilizing risk models, and referring high-risk patients for breast MRI screening. Citation Format: Yu Jen Jan, Prudence B. Lam. Barriers to optimal breast cancer screening modalities for high-risk patients in the primary care setting [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3029.