Detection Of Breast Cancer In Women Research Articles

Breast Cancer Tumour Masks Segmentation Using Modified U-Net with Channel Attention

Abstract: A modified U-Net for biomedical image segmentation with channel attention is developed for breast cancer image segmentation. A unique step in biomedical image analysis is segmentation because it determines the accuracy of image analysis algorithms. Algorithms for accurate and early breast cancer detection in women using mammograms depend highly on the accuracy of the segmentation stage. In this thesis, in order to improve on the segmentation ability of the traditional UNet architecture, it was modified by varying the fixed kernel sizes that it was originally designed for. In this model, progressively increasing kernel sizes of 3x3, 5x5, 7x7, 9x9 and 11x11 were used, which is different from the architecture of UNet that depended on fixed 3x3 kernel sizes for all convolutional layers. The first Convolutional block of the proposed model contains two Conv2D layers with 3x3 kernel sizes, ReLU (Rectified Linear Unit) activation function, and 16 channel dimensions. A maxpooling2D layer with pool size of (2x2) was placed to downsample the image size before feeding to the next convolutional block which used the same activation function, with 32 channel dimension and 5x5 kernel size. The next convolutional block used 64 channel dimensions with 7x7 kernel size, then a 9x9 kernel size Conv2D block with 128 channel dimensions was placed before the Conv2D with upsampling. The squeeze and excitation block was placed after this convolutional layer and in-between the two convolutional blocks with 11x11 kernel sizes, to reallocate the weight of the essential features to ensure that more discriminate features are learnt from the breast cancer images to improve the overall representational strength of the network through the performance of dynamic feature recalibration of the image channels. This significantly improved the performance of the segmentation by explicitly modeling the interdependencies between channels in the convolutional layers. The increasing kernel sizes enables the model to learn more discriminate features from the images. Jaccard similarity index, F1 score, Recall, Precision, F2 score, and accuracy results were used to compare the result of the proposed model with other models such as U-Net model and Baseline model. The results shows a better performance of 0.88 for Jaccard similarity index, 0.94 for F1 score, 0.93 for recall, 0.92 for precision, 0.92 for F2 score, and an accuracy score of 0.98%. The model is good for biomedical image segmentation.

Addition of Contrast-enhanced Mammography to Tomosynthesis for Breast Cancer Detection in Women with a Personal History of Breast Cancer: Prospective TOCEM Trial Interim Analysis.

Background Digital breast tomosynthesis (DBT) is often inadequate for screening women with a personal history of breast cancer (PHBC). The ongoing prospective Tomosynthesis or Contrast-Enhanced Mammography, or TOCEM, trial includes three annual screenings with both DBT and contrast-enhanced mammography (CEM). Purpose To perform interim assessment of cancer yield, stage, and recall rate when CEM is added to DBT in women with PHBC. Materials and Methods From October 2019 to December 2022, two radiologists interpreted both examinations: Observer 1 reviewed DBT first and then CEM, and observer 2 reviewed CEM first and then DBT. Effects of adding CEM to DBT on incremental cancer detection rate (ICDR), cancer type and node status, recall rate, and other performance characteristics of the primary radiologist decisions were assessed. Results Among the participants (mean age at entry, 63.6 years ± 9.6 [SD]), 1273, 819, and 227 women with PHBC completed year 1, 2, and 3 screening, respectively. For observer 1, year 1 cancer yield was 20 of 1273 (15.7 per 1000 screenings) for DBT and 29 of 1273 (22.8 per 1000 screenings; ICDR, 7.1 per 1000 screenings [95% CI: 3.2, 13.4]) for DBT plus CEM (P < .001). Year 2 plus 3 cancer yield was four of 1046 (3.8 per 1000 screenings) for DBT and eight of 1046 (7.6 per 1000 screenings; ICDR, 3.8 per 1000 screenings [95% CI: 1.0, 7.6]) for DBT plus CEM (P = .001). Year 1 recall rate for observer 1 was 103 of 1273 (8.1%) for (incidence) DBT alone and 187 of 1273 (14.7%) for DBT plus CEM (difference = 84 of 1273, 6.6% [95% CI: 5.3, 8.1]; P < .001). Year 2 plus 3 recall rate was 40 of 1046 (3.8%) for DBT and 92 of 1046 (8.8%) for DBT plus CEM (difference = 52 of 1046, 5.0% [95% CI: 3.7, 6.3]; P < .001). In 18 breasts with cancer detected only at CEM after integration of both observers, 13 (72%) cancers were invasive (median tumor size, 0.6 cm) and eight of nine (88%) with staging were N0. Among 1883 screenings with adequate reference standard, there were three interval cancers (one at the scar, two in axillae). Conclusion CEM added to DBT increased early breast cancer detection each year in women with PHBC, with an accompanying approximately 5.0%-6.6% recall rate increase. Clinical trial registration no. NCT04085510 © RSNA, 2024 Supplemental material is available for this article.

Automated 3D Ultrasound as an Adjunct to Screening Mammography Programs in Dense Breast: Literature Review and Metanalysis.

Purpose: The purpose of this meta-analysis is to investigate the effectiveness of supplementing screening mammography with three-dimensional automated breast ultrasonography (3D ABUS) in improving breast cancer detection rates in asymptomatic women with dense breasts. Materials and Methods: We conducted a thorough review of scientific publications comparing 3D ABUS and mammography. Articles for inclusion were sourced from peer-reviewed journal databases, namely MEDLINE (PubMed) and Scopus, based on an initial screening of their titles and abstracts. To ensure a sufficient sample size for meaningful analysis, only studies evaluating a minimum of 20 patients were retained. Eligibility for evaluation was further limited to articles written in English. Additionally, selected studies were required to have participants aged 18 or above at the time of the study. We analyzed 25 studies published between 2000 and 2021, which included a total of 31,549 women with dense breasts. Among these women, 229 underwent mammography alone, while 347 underwent mammography in combination with 3D ABUS. The average age of the women was 50.86 years (±10 years standard deviation), with a range of 40-56 years. In our efforts to address and reduce bias, we applied a range of statistical analyses. These included assessing study variation through heterogeneity assessment, accounting for potential study variability using a random-effects model, exploring sources of bias via meta-regression analysis, and checking for publication bias through funnel plots and the Egger test. These methods ensured the reliability of our study findings. Results: According to the 25 studies included in this metanalysis, out of the total number of women, 27,495 were diagnosed with breast cancer. Of these, 211 were diagnosed through mammography alone, while an additional 329 women were diagnosed through the combination of full-field digital mammography (FFDSM) and 3D ABUS. This represents an increase of 51.5%. The rate of cancers detected per 1000 women screened was 23.25‱ (95% confidence interval [CI]: 21.20, 25.60; p < 0.001) with mammography alone. In contrast, the addition of 3D ABUS to mammography increased the number of tumors detected to 20.95‱ (95% confidence interval [CI]: 18.50, 23; p < 0.001) per 1000 women screened. Discussion: Even though variability in study results, lack of long-term outcomes, and selection bias may be present, this systematic review and meta-analysis confirms that supplementing mammography with 3D ABUS increases the accuracy of breast cancer detection in women with ACR3 to ACR4 breasts. Our findings suggest that the combination of mammography and 3D ABUS should be considered for screening women with dense breasts. Conclusions: Our research confirms that adding 3D automated breast ultrasound to mammography-only screening in patients with dense breasts (ACR3 and ACR4) significantly (p < 0.05) increases the cancer detection rate.

Association between breast diseases and symptomatic uterine fibroids by using South Korean National Health Insurance database

Both the uterus and breasts have sex hormone dependence, yet there are few studies on the association between breast disease and uterine fibroids (UFs). The purpose of this study was to investigate the incidence of benign breast disease (BBD), carcinoma in situ (CIS), and breast cancer (BC) in women treated for UFs compared to women who were not treated for UFs. This retrospective cohort study used national health insurance data from January 1st, 2011, to December 31st, 2020. We selected women between 20 and 50 years old who (1) were treated for UFs (UF group) or (2) visited medical institutions for personal health screening tests without UFs (control group). We analyzed independent variables such as age, socioeconomic status (SES), region, Charlson comorbidity index (CCI), delivery status, menopausal status, menopausal hormone therapy (MHT), endometriosis, hypertension (HTN), diabetes mellitus (DM), and dyslipidemia based on the first date of uterine myomectomy in the UF group and the first visiting date for health screening in the non-UF group. There were 190,583 and 439,940 participants in the UF and control groups, respectively. Compared with those of the control group, the RRs of BBD, CIS, and BC were increased in the UF group. The hazard ratios (HRs) of BBD, CIS, and BC in the UF group were 1.335 (95% confidence interval (CI) 1.299–1.372), 1.796 (95% CI 1.542–2.092), and 1.3 (95% CI 1.198–1.41), respectively. When we analyzed the risk of BC according to age at inclusion, UFs group had the increased risk of BCs in all age groups in comparison with control group. Women with low SES (HR 0.514, 95% CI 0.36–0.734) and living in rural areas (HR 0.889, 95% CI 0.822–0.962) had a lower risk of BC. Our study showed that women with UFs had a higher risk of BBD, CIS, and BC than those without UFs. This result suggests that women with UFs should be more conscious of BC than those without UFs. Therefore, doctors should consider recommending regular breast self-exams, mammography, or ultrasound for the early detection of BC in women with UFs.

Incidence round screening performance among women with dense breasts undergoing abbreviated breast MRI and digital breast tomosynthesis (ECOG-ACRIN EA1141).

10502 Background: The sensitivity of mammography, including digital breast tomosynthesis (DBT), is limited by breast density. Abbreviated breast MRI (AB-MR) significantly increases breast cancer detection in women with dense breasts. In the prevalence (baseline) screening round of the EA1141 trial, AB-MR offered a 2.45-fold higher cancer detection rate (CDR) than DBT. Here we report the CDR and diagnostic accuracies of AB-MR and DBT during the EA1141 incidence screening round and the overall interval cancer rate. Methods: Informed consent was obtained from all participants. Asymptomatic average risk women aged 40-75 years with mammographically dense breasts scheduled for routine screening with DBT were enrolled. All women underwent DBT and AB-MR at baseline (prevalence) and year 1 (incidence) screens which were interpreted independently by 2 different radiologists blinded to the other modality. Women were contacted 11-13 months after the year 1 screen to assess for a subsequent breast cancer diagnosis. Pathology of biopsy was the reference standard for CDR and positive predictive value of biopsy (PPV3). Interval cancers reported during 11-13 months of follow-up until the next annual screening were included in the reference standard for sensitivity and specificity. A post hoc adjustment was made for multiple testing using the Bonferroni method; p-values are reported for comparisons which met the adjusted significance threshold (0.05/5 = 0.01). Reported 95% confidence intervals were not adjusted for multiplicity. Results: Of 1516 enrolled subjects, 1444 completed the baseline and 1291 also the incidence screen. During the latter, 9 women were diagnosed with breast cancer. DBT detected cancer in 5 women (3 DCIS, 2 invasive) for a CDR of 3.9/1000 (5/1291, CI 1.7, 9.0). AB-MR detected cancer in 6 women (0 DCIS, 6 invasive), 4 of which were not detected on DBT, for a CDR of 4.6/1000 (6/1291, CI 2.1, 10.1). The additional imaging (subject-level) rate for DBT was 7.9% (102/1291, CI 6.6%, 9.5%) vs 3.7% (48/1291, CI 2.8%, 4.9%) for AB-MR (p &lt; 0.001). The PPV3 (lesion-level) for DBT was 29.4% (5/17, CI 13.5%, 52.6%) and 15.0% (6/40, CI 6.9%, 29.6%) for AB-MR. During the 2 years of study screening (baseline and year 1), there was 1 interval cancer (palpable lump 348 days after year 1 screen), for an overall interval cancer rate of 0.37/1000 person-years (1/2677 person-years, CI 0.05, 2.65). Sensitivity and specificity were 50.0% (5/10, CI 23.7%, 76.3%) and 98.5% (1261/1280, CI 97.7%, 99.0%) for DBT vs 60% (6/10, CI 31.3%, 83.2%) and 93.3% (1193/1278, CI 91.8%, 94.6%, p &lt; 0.001) for AB-MR. Conclusions: On the incidence screening round, AB-MR detected additional invasive breast cancers not seen on DBT. In addition, a low overall interval cancer rate was observed with combined screening. Although the need for additional imaging was lower for AB-MR, specificity was higher for DBT. Clinical trial information: NCT02933489 .

The conundrum of breast density; guidance for healthcare providers.

A finding of dense breasts on mammogram decreases the sensitivity of mammogram and increases a woman's risk of breast cancer. Supplemental screening can increase breast cancer detection in women with dense breasts, but caries a risk of increased false-positive test results. There are currently no clear guidelines for providers or patients on recommendations for supplemental screening after a mammogram finding of heterogeneously or extremely dense breasts on mammography. In addition, there is currently great variation in communication and management of breast density amongst physicians and other licensed providers. Women at higher risk for developing breast cancer would benefit most from supplemental screening. Standardizing recommendations and implementation of risk-based decision-making using a validated calculator would allow for earlier detection of breast cancer, clear guidance for providers, and ensure equitable care for patients.

Annual Mammographic Screening Reduces the Risk of Interval or Higher Stage Invasive Breast Cancers Among Postmenopausal Women in the Ontario Breast Screening Program.

Purpose: In the Ontario Breast Screening Program (OBSP) annual screening improved breast cancer detection for women 50-74 years with a family/personal history compared to biennial, while detection was equivalent for women screened annually for mammographic density ≥75%. This study compares the risk of interval or higher stage invasive cancers among postmenopausal women screened annually vs biennially by age and estrogen use. Methods: A retrospective design identified 4247 invasive breast cancers diagnosed among concurrent cohorts of women 50-74 screened in the OBSP with digital mammography between 2011 and 2014, followed until 2016. Polytomous logistic regression estimated the risk of interval or higher stage breast cancers by age and estrogen use between women screened annually because of first-degree relative with breast or ovarian cancer or personal history of ovarian cancer, or mammographic density ≥75%, and those screened biennially. Results: The risk of interval vs screen-detected cancers was significantly reduced in women screened annually for family/personal history (OR=.64; 95%CI:0.51-.80), particularly those 60-74 years (OR=.59; 95%CI:0.45-.77) or not currently using estrogen (OR=.66; 95%CI:0.52-.83) compared to those screened biennially. The risk of stage II-IV vs stage I tumors was also lower in women 60-74 years screened annually for family/personal history (OR=.79; 95%CI:0.64-.97) and in those screened annually for mammographic density ≥75% currently using estrogen (OR=.51; 95%CI:0.26-1.01) compared to women screened biennially. Conclusion: Postmenopausal women at increased risk screened annually had equivalent or reduced risks of interval or higher stage invasive breast cancers than those screened biennially, further supporting risk-based screening in this population.

Health Policy Challenge for Breast Cancer Prevention: A Case Report

Breast cancer early diagnosis increases treatment chances, and self-examination is one of the commonest screening methods employed by women. The case of a 24-year-old Iranian woman with a history of mild mental retardation and chest pain was reported. A large lump was detected in the breast during visitation to the surgical clinic. The parents stated the lump was noticed due to a shape change in the clothes covering the patient's chest area. Therefore, the patient had mastectomy surgery after a biopsy and a malignant breast lump was confirmed. The registration and identification of people with mental disorder histories or various mental retardation degrees in each region's health centers to periodically assess their breast health tend to reduce the risk of late breast cancer detection in women.

A novel generalized logistic dependent model to predict the presence of breast cancer based on biomarkers

SummaryBreast cancer is the second most common cancer in women in the United States. With the revolution of the machine learning era, many researchers currently aim to find pathways and develop tools that may help to detect breast cancer early on in its development. We propose a novel generalized logistic dependent model with considerations of the dependence among selected biomarkers for breast cancer detection based on a set of nine biomarker predictors such as age, glucose, BMI, resistin, HOMA, MCP‐1, leptin, insulin, and adiponectin. Our research findings demonstrate that the proposed model has the potential to predict breast cancer in women just based on five biomarkers, ie, glucose, age, BMI, resistin, and MCP‐1. We also compare our model results to several other machine‐learning modeling approaches including SVM, logistic regression, random forest, and multiple regression analyses using various training data sets (60%, 70%, 80% of all data) and all the dataset. It shows that the inclusion of the dependence among those five predictors in the proposed model is worth the extra model complexity and effort for achieving a significant accuracy prediction level of breast cancer detection in women. Further work in broader validation of the conclusion of our study and exploring the ability for artificial intelligence (AI) to be able to bolster these predictions based on biomarkers are also discussed.

Does three-dimensional functional infrared imaging improve breast cancer detection based on digital mammography in women with dense breasts?

PurposeWe aimed to estimate the incremental cancer detection rate achieved by adding three-dimensional functional infrared imaging (3DIRI) to digital mammography in women with dense breasts.Materials and methodsIn this prospective study conducted between December 2014 and April 2016, 1727 women (median age 56) with percentage volumetric breast density > 6% were recruited at routine screening mammography to undergo additional 3DIRI. The 3DIRI findings were classified as negative or positive. Women with a negative mammography but positive 3DIRI were referred to dynamic contrast-enhanced MRI, whereas all other women underwent routine follow-up based on the mammography finding. Diagnosis of breast cancer was verified by histopathologic examination. The number of women diagnosed with a malignancy formed the basis of our statistical analysis.ResultsMammography detected 7 cancers in 7 women. Of 1692 women with negative mammography, 222 women (13%) had a positive 3DIRI of which 219 underwent MRI. An additional 6 cancers were identified in 5 women, increasing the diagnostic yield from 7 of 1727 (0.41%) to 12 of 1727 (0.69%). The incremental cancer detection rate associated with using 3DIRI to select women for MRI was 5 of 222 (22.5 additional cancers per 1000).ConclusionThe use of 3DIRI to select women for an additional MRI can result in the detection of additional cancers in women with dense breasts, but at the expense of additional false positives and considerably lower positive predictive value of the combined examinations. Additional studies are necessary to evaluate the role of 3DIRI as an adjunct to mammography.Key Points• Use of three-dimensional functional infrared imaging to select women for an MRI in addition to screening mammography has the potential to improve breast cancer detection in women with dense breasts.

Supplemental ultrasound screening in patients with a history of lobular neoplasia.

To investigate the role of ultrasound (US) screening as an adjunct to annual mammography (M) in breast cancer detection in women with a history of lobular neoplasia (LN) diagnosed following core needle or excisional biopsy. A retrospective review of our database was performed between 11/2006 and 11/2011 to identify patients diagnosed with LN, and underwent annual screening. Patients with a lifetime risk >20% per risk modeling were excluded. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and cancer detection rate (CDR) of each screening test were identified. Cancer type and detection modality were recorded. A total of 100 patients who had M and/or US screening were included. Mean patient age was 54.7years (range 33-83). All 100 patients underwent a mean of 3.9 rounds of screening M and 93 (93%) received US screening (mean 3.3 rounds). Of 93 patients who received both M and US screening, 12 (13%) were diagnosed with breast cancer. Mammographic CDR was 4%. Incremental US CDR was 6.5%. The sensitivity, specificity, and NPV for M screening alone was 33% (10%, 65%), 77% (67%, 85%), and 89% (80%, 95%), respectively. US and mammography screening had a combined sensitivity: 83% (52%, 98%), Specificity: 72% (62%, 81%), NPV: 97% (89%, 100%). Supplemental US screening resulted in a significant increase in sensitivity, yielding 6.5% incremental CDR in this high-risk patient subgroup that does not fulfill ACS high-risk MRI screening criteria.

A multicenter hospital-based diagnosis study of automated breast ultrasound system in detecting breast cancer among Chinese women.

The automated breast ultrasound system (ABUS) is a potential method for breast cancer detection; however, its diagnostic performance remains unclear. We conducted a hospital-based multicenter diagnostic study to evaluate the clinical performance of the ABUS for breast cancer detection by comparing it to handheld ultrasound (HHUS) and mammography (MG). Eligible participants underwent HHUS and ABUS testing; women aged 40-69 years additionally underwent MG. Images were interpreted using the Breast Imaging Reporting and Data System (BI-RADS). Women in the BI-RADS categories 1-2 were considered negative. Women classified as BI-RADS 3 underwent magnetic resonance imaging to distinguish true- and false-negative results. Core aspiration or surgical biopsy was performed in women classified as BI-RADS 4-5, followed by a pathological diagnosis. Kappa values and agreement rates were calculated between ABUS, HHUS and MG. A total of 1,973 women were included in the final analysis. Of these, 1,353 (68.6%) and 620 (31.4%) were classified as BI-RADS categories 1-3 and 4-5, respectively. In the older age group, the agreement rate and Kappa value between the ABUS and HHUS were 94.0% and 0.860 (P<0.001), respectively; they were 89.2% and 0.735 (P<0.001) between the ABUS and MG, respectively. Regarding consistency between imaging and pathology results, 78.6% of women classified as BI-RADS 4-5 based on the ABUS were diagnosed with precancerous lesions or cancer; which was 7.2% higher than that of women based on HHUS. For BI-RADS 1-2, the false-negative rates of the ABUS and HHUS were almost identical and were much lower than those of MG. We observed a good diagnostic reliability for the ABUS. Considering its performance for breast cancer detection in women with high-density breasts and its lower operator dependence, the ABUS is a promising option for breast cancer detection in China.

Prognostic impact of interval breast cancer detection in women with pT1a N0M0 breast cancer with HER2-positive status: Results from a multicentre population-based cancer registry study

BackgroundAlthough human epidermal growth factor receptor 2 (HER2) overexpression is associated with poor prognosis, patients (pts) with pT1a N0M0 breast cancers (BCs) have an excellent outcome across all subtypes. Interval cancers (ICs) have poorer survival than screen-detected (SD) tumours, and an association has been reported between ICs and HER2 overexpression. We aimed to determine, in a general population of pT1a N0M0 BCs with known screening status, whether HER2-positive ICs have a poorer outcome than HER2-positive SD cancers. MethodsWe evaluated all incident pT1a N0M0 BCs (n = 874) collected in the Emilia-Romagna region (Italy) from 2003 to 2009 and diagnosed in women aged 50–69. Pts unexposed to screening, with unknown HER2 status and/or treated with adjuvant trastuzumab were excluded from analysis. ResultsSixty-one percent of the BCs were SD, whereas 19% were ICs. BCs with high histologic grade, hormone receptor–negative or HER2-positive status (odds ratio=1.7; 95% confidence interval [CI]: 1.1–2.7) were more likely ICs. Median follow-up was 115 months. The 10-year invasive disease-free survival (iDFS) for HER2-positive ICs was lower than that for HER2-positive SD cancers: 75.0% (95% CI: 55.5%–94.5%) versus 93.8% (95% CI: 86.5%–100%). An interaction between ICs and HER2-positive status was found for poorer iDFS after adjusting for prognostic variables (HR = 5.3; 95% CI: 1.6–16.7). ConclusionsIC detection may identify pts with HER2-positive pT1a N0M0 tumours in whom the rate of recurrence justifies consideration for conventional, anti-HER2, adjuvant treatment.

Abstract PD3-01: Automated, low-cost palpable breast lump triage for economically-developing countries

Abstract Background: According to GLOBOCAN, 1.7 million women were diagnosed with breast cancer and 445,000 died from the disease in 2012. Breast cancer is the most common cause of cancer death among women worldwide and the numbers are disproportionately high for women in developing countries. Furthermore, breast cancer is more common in young women (age 44 and under) in these countries than in industrialized countries. Shifts in lifestyle typical of industrialized societies are thought to be causing a rise in breast cancer incidence while technical advances in detection, diagnosis, and treatment are not reaching these areas of the world. In developing countries, breast cancer commonly presents in women as a palpable mass and a low-cost solution for breast cancer triage would be beneficial. Ultrasound has been shown to perform very well on palpable masses, is non-ionizing, and affordable, portable systems are available. In the ACRIN 6666 clinical study of asymptomatic women, adding screening ultrasound to mammography significantly increased breast cancer detection in women with elevated cancer risk and dense breasts, and more invasive cancers were seen by ultrasound alone than by mammography alone. Method: We propose a novel computer-aided diagnosis (CADx) tool for breast cancer triage using a low-cost ultrasound imaging device that will automatically distinguish among (1) suspicious lesions to be sent for biopsy, (2) benign findings that need no additional follow-up and (3) probably benign findings with recommended 6-month follow-up. A validation study at USC Norris Cancer Center and Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center was performed in order to assess the performance of the triage software compared to the standard-of-care and biopsy-confirmed cancers and false positives. The Study machine was the GE Logiq e ultrasound imaging device, which is FDA-approved for small body parts. Lesions that were assessed as BI-RADS 2 by radiologists were determined to be benign while any lesion assessed as BI-RADS 4a or higher was sent for biopsy. This study cohort included women 61 years of age or younger with a palpable mass. The triage software was compared to the performance by radiologists using conventional standard-of-care for palpable masses. Results: The original milestone for this study was to achieve a sensitivity of 85% while reducing the number of benign lesions going to biopsy by 40%. The validation study showed an actual sensitivity of 100% while reducing the number of benign lesions going to biopsy by 69%. To date, the images collected during the validation study include 152 lesions in total, 22 biopsy-proven cancers and 130 benign lesions; 63 benign lesions were categorized as BI-RADS 4a or higher by a radiologist and sent for biopsy. Conclusions: The validation study showed that adding automated breast cancer triage software to a low-cost portable ultrasound imaging device is a realistic approach for regions of the world with limited access to highly trained radiologists and diagnostic equipment. Funding: NIH Grant #UH2EB019889. Citation Format: Love SM, Berg WA, Podilchuk C, Hovanessian-Larsen LJ, Dauphine C, Jairaj A, Barinov L, Hulbert W, Cen S, Eshraghi L, Mammone R. Automated, low-cost palpable breast lump triage for economically-developing countries [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr PD3-01.

151PD - Prognostic impact of interval breast cancer detection in women with pT1aN0M0 breast cancer with HER2-positive status: results from a multicenter population-based cancer registry study

151PD - Prognostic impact of interval breast cancer detection in women with pT1aN0M0 breast cancer with HER2-positive status: results from a multicenter population-based cancer registry study

F09 - Prognostic Impact of Interval Breast Cancer Detection in Women with pT1aN0M0 Breast Cancer with HER2-positive Status: Results from a Multicenter Population-based Cancer Registry Study

F09 - Prognostic Impact of Interval Breast Cancer Detection in Women with pT1aN0M0 Breast Cancer with HER2-positive Status: Results from a Multicenter Population-based Cancer Registry Study

Abstract P4-09-16: A monoclonal antibody with exceptional specificity across major breast cancer subtypes

Abstract Background: Breast cancer (BC) remains the second leading cause of cancer-related deaths for women in the United States and is recognized to be a heterogeneous disease. Advances in technologies such as whole genome sequencing are leading the way to precision medicine and the leading researchers are envisioning personalized therapies in the not too distant future. However, given the diversity of cancer cell populations, that remains a challenging task at best. The tumor form of MUC1 (designated tMUC1), a transmembrane glycoprotein, is aberrantly glycosylated and overexpressed in ∼95% of BC. We have developed an antibody (TAB004) that specifically recognizes tMUC1 across all major subtypes of BC and importantly does not recognize normal breast epithelia. This is a significant development in light of the challenges faced in treating triple negative BC. Methods: A panel of thirty BC cell lines was obtained from ATCC. The following techniques were used to assess the specificity of TAB 004 to the major subtypes based on ER, PR and Her2 expression: 1) Flow cytometry to quantify membrane bound expression of tMUC1 using Cy7-conjugated TAB004; 2) Western blotting to detect molecular weight patterns of tMUC1 in whole cell lysate; 3) A TAB004 based GMP-grade ELISA kit to measure shed tMUC1 in the supernatant and 4) In vivo imaging of tumors in mice using TAB 004 conjugated to Indocyanine Green (ICG). Specificity and sensitivity was further confirmed using primary human serum and tissue samples from all major BC subtypes obtained from bio-repositories at Duke University Cancer Center, Fox Chase Cancer Center and Carolinas Health Care System. Shed tMUC1 in serum samples were tested using the TAB 004 ELISA kit and tissue sections were analyzed using immunohistochemical (IHC) staining with TAB 004 conjugated to HRP. Results: 1) Flow cytometry data shows that TAB 004 recognized tMUC1 on all major BC subtypes: 25 out of 30 BC cell lines tested had higher expression than a normal epithelial breast cell line; 2) Western blotting also detected tMUC1 on all BC subtypes with distinct molecular weight patterns; 3) ELISA showed high levels of shed tMUC1 by most BC cells and correlated with bound/cytoplasmic levels. 4) In vivo imaging shows clear localization of TAB004-ICG to the tumors expressing tMUC1. Primary human breast cancer patient data shows that shed tMUC1 was detected in the serum obtained from all major BC subtypes and showed statistically significant differentiation from normal/benign. IHC results show strong tMUC1 expression in malignant tissue with excellent differentiation from adjacent normal tissue. Conclusion: TAB004 antibody's extraordinary specificity across major BC subtypes has been confirmed with flow cytometry, western blotting, ELISA and Immunohistochemistry. A number of clinical applications are under development: (a) An ELISA test as a supplement to mammography for the early detection of BC in women with dense breasts; (b) serum monitoring during treatment and to detect disease recurrence; and, (c) targeted antibody-drug/antibody-imaging agent based therapies and imaging modalities particularly for triple negative BC. Citation Format: Das Roy L, Zhou R, Dillon L, Moore LJ, Puri R, Marks JR, Lyerly HK, Mukherjee P. A monoclonal antibody with exceptional specificity across major breast cancer subtypes. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P4-09-16.

Breast-Specific γ-Imaging for the Detection of Mammographically Occult Breast Cancer in Women at Increased Risk.

Breast-specific γ-imaging (BSGI) is a physiologic imaging modality that can detect subcentimeter and mammographically occult breast cancer, with a sensitivity and specificity comparable to MRI. The purpose of this study was to determine the incremental increase in breast cancer detection when BSGI is used as an adjunct to mammography in women at increased risk for breast cancer. All patients undergoing BSGI from April 2010 through January 2014 were retrospectively reviewed. Eligible patients were identified as women at increased risk for breast cancer and whose most recent mammogram was benign. Examinations exhibiting focally increased radiotracer uptake were considered positive. Incremental increase in cancer detection was calculated as the percentage of mammographically occult BSGI-detected breast cancer and the number of mammographically occult breast cancers detected per 1,000 women screened. Included in this study were 849 patients in whom 14 BSGI examinations detected mammographically occult breast cancer. Patients ranged in age from 26 to 83 y, with a mean age of 57 y. Eleven of 14 cancers were detected in women with dense breasts. The addition of BSGI to the annual breast screen of asymptomatic women at increased risk for breast cancer yields 16.5 cancers per 1,000 women screened. When high-risk lesions and cancers were combined, BSGI detected 33.0 high-risk lesions and cancers per 1,000 women screened. BSGI is a reliable adjunct modality to screening mammography that increases breast cancer detection by 1.7% (14/849) in women at increased risk for breast cancer, comparable to results reported for breast MRI. BSGI is beneficial in breast cancer detection in women at increased risk, particularly in those with dense breasts.

The Effect of Breast Implants on Mammogram Outcomes

Breast cancer detection in women with implants has been questioned. We sought to evaluate the impact of breast implants on mammographic outcomes. A retrospective review of women undergoing mammography between March 1 and October 30, 2013 was performed. Demographic characteristics and mammogram results were compared between women with and without breast implants. Overall, 4.8 per cent of 1863 women identified during the study period had breast implants. Median age was 59 years (26-93). Women with implants were younger (53.9 vs 59.2 years, P < 0.0001), had lower body mass index (25.4 vs 28.9, P < 0.0001), and were more likely to have dense breast tissue (72.1% vs 56.4%, P = 0.004) than those without. There were no statistically significant differences with regards to Breast Imaging Recording and Data System 0 score (13.3% with implants vs 21.4% without), call back exam (18.9% with vs 24.1% without), time to resolution of abnormal imaging (58.6 days with vs 43.3 without), or cancer detection rate (0% with implants vs 1.0% without). Because implants did not significantly affect mammogram results, women with implants should be reassured that mammography remains useful in detecting cancer. However, future research is required to determine whether lower call back rates and longer time to resolution of imaging findings contribute to delays in diagnosis in patients with implants.

Survival benefit in women with BRCA1 mutation or familial risk in the MRI screening study (MRISC).

Adding MRI to annual mammography screening improves early breast cancer detection in women with familial risk or BRCA1/2 mutation, but breast cancer specific metastasis free survival (MFS) remains unknown. We compared MFS of patients from the largest prospective MRI Screening Study (MRISC) with 1:1 matched controls. Controls, unscreened if<50 years, and screened with biennial mammography if ≥50 years, were matched on risk category (BRCA1, BRCA2, familial risk), year and age of diagnosis. Of 2,308 MRISC participants, breast cancer was detected in 93 (97 breast cancers), who received MRI <2 years before breast cancer diagnosis; 33 BRCA1 mutation carriers, 18 BRCA2 mutation carriers, and 42 with familial risk. MRISC patients had smaller (87% vs. 52% <T2, p < 0.001), more often node negative (69% vs. 44%, p = 0.001) tumors and received less chemotherapy (39% vs. 77%, p < 0.001) and hormonal therapy (14% vs. 47%, p < 0.001) than controls. Median follow-up time was 9 years (range 0-14). Breast cancer metastasized in 9% (8/93) of MRISC patients and in 23% (21/93) of controls (p = 0.009). MFS was better in MRISC patients overall (log-rank p = 0.008, HR 0.36, 95% CI 0.16-0.80), with familial risk (log-rank p = 0.024, HR: 0.21, 95% CI 0.04-0.95), and in BRCA1 mutation carriers (log-rank p = 0.055, HR 0.30, 95% CI 0.08-1.13). MFS remained better in MRISC patients after lead time correction (log-rank p = 0.020, HR 0.40, 95% CI 0.18-0.90). Overall survival was non-significantly better in MRISC patients (log-rank p = 0.064, HR 0.51, CI 0.24-1.06). Annual screening with MRI and mammography improves metastasis free survival in women with BRCA1 mutation or familial predisposition.