Sensitivity Of Mammograms Research Articles

"Artificial intelligence Reading Digital Mammogram: Enhancing Detection and Differentiation of Suspicious Microcalcifications".

To investigate the impact of artificial intelligence (AI) on enhancing the sensitivity of digital mammograms in the detection and specification of grouped microcalcifications. The study is a retrospective analysis of grouped microcalcifications for 447 patients. Grouped microcalcifications detected were correlated with AI, which was applied to the initial mammograms. AI provided a heat map, demarcation, and quantitative evaluation for abnormalities according to the degree of suspicion of malignancy. Histopathology was the standard for confirmation of malignancy. AI showed a high correlation percentage of 67.5% between the red color of the color hue bar and malignant microcalcifications (p value <0.001). The scoring of probable cancer was suggested (ie, more than 50% abnormality scoring) in 39.5% of true cancer lesions. The diagnostic performance of mammography for grouped microcalcifications revealed a sensitivity of 94.7% and a negative predictive value of 82.1%. False negatives were only 12 out of 228 that proved malignant calcifications. The agreement of cancer probability between standard mammograms and examinations read by AI presented a Kappa value of -0.094 and a p value of < 0.001. The used AI system enhanced the sensitivity of mammograms in detecting suspicious microcalcifications, yet an expert human reader is required for proper specification. Grouped calcifications could be early breast cancer on a mammogram. The morphology and distribution are correlated with the nature of breast diseases. AI is a potential decision support for the detection and classification of grouped microcalcifications and thus positively affects the control of breast cancer.

Breast density and risk of breast cancer: masking and detection bias.

Breast density is associated with risk of breast cancer (BC) diagnosis, impacting risk prediction tools and patient notification policies. Density affects mammography sensitivity and may influence screening intensity. Therefore, the observed association between density and BC diagnosis may not reflect the relationship between density and disease risk. We investigate the association between breast density and BC risk using data sourced from 33,542 women in the Breast Cancer Surveillance Consortium, 2000-2018. We estimated mammogram sensitivity and rates of screening mammography among dense (BI-RADS c, d) and non-dense (BI-RADS a, b) breasts. We used Kaplan-Meier estimates to summarize the relative risks of BC diagnosis (RRdx) by density and fit a natural history model to estimate the relative risks of BC onset (RRonset) given density-specific sensitivities. RRdx for dense versus non-dense breasts was 1.80 (95% CI 1.46 to 2.57). Based on estimated screening sensitivities of 0.88 and .78 for non-dense and dense breasts, respectively, RRonset was 1.73 (95% CI 1.43 to 2.25). Sensitivity analyses suggested higher breast density is robustly associated with increased risk of BC onset, similar in magnitude to the increased risk of BC diagnosis. These finding support laws requiring notifications to women with dense breasts of their increased BC risk.

Comparison of Sonographic Findings with Diagnostic Mammography.

Breast cancer is the leading female cancer worldwide with a high mortality rate. Early detection of the suspicious lesion is crucial for better prognosis. Higher breast density decreases the sensitivity of mammogram. Ultrasound can differentiate between cystic and solid masses and further characterize these as benign or possibly malignant. Our objective was to compare the findings of sonography with diagnostic mammography. This was a cross sectional study including 125 females who underwent diagnostic mammogram in a tertiary care center. The mammograms were evaluated and the patients were scanned by ultrasound and categorized as per ACR- BIRADS category. The findings of diagnostic mammography were compared with that of ultrasonography using SPSS version 25. The heterogeneously dense breast in diagnostic mammography corresponded to the heterogenous- fibroglandular breast in ultrasonography. In majority, ultrasound increased the BIRADS category for the lesion than designated by the diagnostic mammography. It was particularly useful for category 0 and 3 lesions which were indeterminate and required further imaging. Ultrasound was useful in evaluation of dense breasts with ACR-BIRADS 0 and 3 in diagnostic mammogram. For category 3 and 4 in diagnostic mammogram, ultrasound showed category 1 or 2 lesions which aided to alleviate patient anxiety and avoid unnecessary biopsies. With emerging technological advances in ultrasound, it can used as a powerful tool for breast lesion detection and patient management.

Abstract P1-05-32: Outcomes of diagnostic breast imaging in young women (less than 50 years old)

Abstract INTRODUCTION The incidence of breast cancer is on the rise in the younger population, with 23 percent of all breast cancer diagnoses occurring in those under the age of 50. In Canada, screening mammography in women at average risk of breast cancer is recommended after the age of 50. Breast cancer in younger women is biologically more aggressive with greater rates of recurrence and metastatic disease. The sensitivity of mammograms to detect clinical breast abnormalities may be reduced due to increased breast density in this age group, leading to potential delayed diagnosis and poor outcomes. The frequency of false-negative diagnostic mammograms in young women is unknown. The purpose of this study is to describe the outcomes of diagnostic breast imaging in young women undergoing investigations for abnormal clinical breast findings and the frequency of delayed breast cancer diagnosis (more than 6 months after initial diagnostic mammography). METHODS We conducted a retrospective electronic chart review in women at average risk of breast cancer, aged between 30 and 50, who underwent diagnostic mammograms and/or breast ultrasounds (US) at our institution between 2018 to 2019 for symptomatic clinical presentations (breast pain, palpable mass, nipple discharge or breast skin changes). Patients undergoing routine screening mammograms were excluded. We collected demographics, findings of initial and follow-up breast imaging (using the Breast Imaging Reporting and Data System (BI-RADS) &amp; breast density), and breast cancer diagnosis timelines where applicable. The primary outcome measure was the frequency of delayed breast cancer diagnosis defined as &amp;gt; 6 months from initial diagnostic imaging. Secondary outcomes included completion of recommended follow-up investigations and their outcomes, total number of breast cancer diagnoses and stage. The study was approved by the local research ethics board and the results were summarized using descriptive analysis. RESULTS We reviewed 400 electronic charts and identified 171 eligible patients. Mean age was 38 years; initial breast imaging included both diagnostic mammogram and US in 168 (87%), US alone in 20 (12%) and mammogram alone in 3 (2%) patients. Breast density was not routinely reported during this time frame. Ninety patients (53%) had benign findings (BIRADS 1 and 2), 41 (24%) had probable benign findings requiring short-term follow-up (BIRADS 3) while 30 (18%) patients had findings suspicious of malignancy (BIRADS 4&amp;5) with biopsy recommended for diagnosis. In the BIRADS 3 group, 93% had recommended follow-up at a median of 7.6 months. Breast US alone was the most common subsequent investigation of which 15 % were benign lesions (BIRADS 1 &amp; 2) and 68% remained in the BIRADS 3 category, while none were scored BIRADS 4 or 5. Among patients with BIRADS 4 &amp; 5 scores, 83% underwent recommended biopsy at a median time of 3 weeks. Ten (6%) out of all 171 patients were diagnosed with breast cancer, all of which had BIRADS 4 or 5 on initial diagnostic imaging. Stage distribution was as follows: stage 0 - 2 patients, stage 1- 7 patients and stage 2 - 1 patients with no locally advanced or metastatic disease. The mean time from initial imaging to breast cancer diagnosis was 1.5 weeks (range 1 to 22 weeks). None of the patients had delayed breast cancer diagnosis in our cohort. CONCLUSION More than half of patients with clinical breast findings in our cohort had benign findings on diagnostic mammogram and/or US (BIRADS 1&amp;2) with no subsequent breast diagnosis. Majority of patients requiring further investigations (BIRADS 0, 3, 4 and 5) underwent recommended follow-up (imaging or biopsy). Ultimately, a total of 10 patients were diagnosed with breast cancer at a median time of 1.5 weeks from original diagnostic imaging with no delayed breast cancer diagnosis. We, therefore, conclude that diagnostic mammograms and US are appropriate diagnostic investigations for clinical breast concerns in women between 30-50 years. Citation Format: Navdeep Dehar, Joseph N. Samuel, Doris Jabs, Wilma Hopman, Mihaela Mates. Outcomes of diagnostic breast imaging in young women (less than 50 years old) [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P1-05-32.

Abstract P4-03-03: Elevated Risk of Breast Cancer Diagnosis in Women with Dense Breasts reflects a similarly Elevated Risk of Breast Cancer Onset that is Robust to the Effect of Density on Mammography Sensitivity

Abstract Dense breasts are associated with a higher risk of breast cancer diagnosis, which has impacted risk prediction tools and patient notification policies. However, given that mammography is less sensitive for women with dense breasts and these women may be subject to different confirmation testing pathways, the true association between breast density and cancer risk is unknown. We investigated the relationship between breast density and onset using a natural history model that accounts for differential sensitivity and rates of exams by breast density. Data consisted of Breast Cancer Surveillance Consortium mammogram and cancer outcomes among women aged 40-54 with a first digital mammogram between 2000-2018 (N=33,542). Of these, 15,092 had non-dense (almost entirely fatty or scattered fibroglandular densities) and18,450 had dense (heterogeneously dense or extremely dense) breasts. We estimated the empirical sensitivity of mammograms in dense and non-dense breasts (fraction of diagnosed cancers that were screen detected) and examined rates of mammograms by density. We estimated the relative risk of breast cancer diagnosis five years after the first exam using Kaplan Meier methods and the relative risk of breast cancer onset from a natural history model, assuming density-specific sensitivity was equal to the empirical sensitivity. Empirical sensitivity was .88 in women with non-dense and .78 in women with dense breasts. Mammogram utilization was somewhat higher in women with dense breasts (HR for subsequent mammograms 1.10 (95% CI [1.07, 1.12]). The relative risk of diagnosis for dense versus non-dense breasts was 1.80 (95% CI [1.46,2.57]); based on the natural history model the relative risk of onset was 1.73 [1.43,2.25]. The estimated relative risk of onset ranged from 1.67 to 2.03 under assumptions that the relative sensitivity of the screening episode for dense versus non-dense breasts was 1.0 to 0.4. In conclusion, the association of risk of breast cancer onset with breast density is robust to assumptions about the relative sensitivity in dense and non-dense breasts. Citation Format: Jane M. Lange, Charlotte Gard, Ellen O’meara, Ruth Etzioni. Elevated Risk of Breast Cancer Diagnosis in Women with Dense Breasts reflects a similarly Elevated Risk of Breast Cancer Onset that is Robust to the Effect of Density on Mammography Sensitivity [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P4-03-03.

The Dense Breast Clinic: Initial Experience of a Patient-Centered Breast Imaging Clinic.

Establish a radiologist-run consultation clinic to review breast density and supplemental screening exams (SSEs) directly with patients in response to breast density reporting laws. Breast radiologists opened and staffed a clinic for formal patient consultations regarding breast density and SSEs. An IRB-approved questionnaire assessed patient knowledge of breast density, SSEs, and encounter satisfaction. Comparative statistical analyses were performed on knowledge-based questions. From February 2019 to February 2021, 294 reimbursable consultations were performed with 215 patients completing pre- and post-consultation questionnaires (survey response rate, 73%). Median patient age was 58 years (range, 34-86 years) and 9% (19/210) had a personal history of breast cancer. An increase in patient knowledge of breast density and SSEs was observed as follows: breast density categories (9% correct pre-consultation (20/215), 86% correct post-consultation (185/215), P < 0.001), dense breast effects on cancer risk (39% correct pre-consultation (83/215), 84% post-consultation (180/215)), mammogram sensitivity (90% correct pre-consultation (193/215), 94% post-consultation (201/215)), and increased cancer detection with SSEs (82% correct pre-consultation (177/215), 95% post-consultation (205/215)) (P < 0.001). Post-consultation, 96% (200/209) were satisfied with the usefulness of information, 89% (186/209) strongly agreed they had sufficient knowledge of SSEs, and 81% (167/205) agreed they would like future opportunities to meet with a breast radiologist. A consultation clinic staffed by breast radiologists focused on breast density and supplemental breast cancer screening can provide personalized patient counseling, engage patients in shared decision making, assist referring clinicians, and support high quality patient-centered care.

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.

Automated breast ultrasound: A comparison study with handheld ultrasound in detection and characterization of lesions in mammographically dense breast

Background: Although mammography is a powerful screening tool in detection of early breast cancer, it is imperfect, particularly for women with dense breast, which have a higher risk to develop cancer and decrease the sensitivity of mammogram, Automated breast ultrasound is a recently introduced ultrasonography technique, developed with the purpose to standardize breast ultrasonography and overcome some limitations of handheld ultrasound, this study aims to evaluate the diagnostic efficacy of Automated breast ultrasound and compare it with handheld ultrasound in the detection and characterization of breast lesions in women with dense breasts. Objectives: To evaluate the diagnostic efficacy of Automated breast ultrasound and compare it with hand held ultrasound in detection and characterization of breast lesions in women with dense breast. Subjects and Methods: A prospective observational study conducted at Oncology Teaching Hospital during the period of ten months from 1st of February till 1st of December 2020. Included 62 women with dense breasts on diagnostic mammograms. All women underwent technician performed automated breast ultrasound and radiologist performed handheld ultrasound for both breasts. All suspicious lesions with selected probably benign lesions underwent biopsy, handheld ultrasound detected 48 masses (67.6%), 15 of them (21.1%) were cystic, automated breast ultrasound detected 54 masses (76.1%); 20 of them (28.2%) were cystic. The sensitivity of handheld ultrasound was=87.5%, Specificity=58.8%, the sensitivity of automated breast ultrasound was=93.8%, Specificity=70.6%. Conclusion: Automated breast ultrasound is an effective modality to detect occult breast lesion in women with dense breasts, automated breast ultrasound and handheld ultrasound have a reliable agreement in detection and characterization of breast lesions with higher accuracy of automated breast ultrasound in the evaluation of malignant lesions.

The study of role of mammography and fine needle aspiration cytology in the diagnosis of early breast carcinoma

Background: Epidemiologically breast cancer is the most common form of cancer among women. Prevalence rate of breast cancer is higher in urban women of middle age group. Early diagnosis of breast carcinoma is required for effective treatment else it may lead to mortality if advanced to stage 3 or 4. At present, there are different diagnosis modalities for early stage breast carcinoma. Currently triple diagnostic assessment including clinical, radiological and pathological examinations with 99% sensitivity is used in diagnosing all palpable breast lumps. The aim of the study was to determine the sensitivity and specificity of mammogram and Fine needle aspiration cytology (FNAC) in diagnosing breast cancer.Methods: A cross sectional study was conducted on total 80 female patients above 30 years of age with a palpable breast lump. Patients were sent for mammography, fine needle aspiration cytology and histopathological examinations. Results of mammography, FNAC and HPR were compared and statistically correlated.Results: Sensitivity of mammogram diagnosis was observed to be 92.857%, specificity as 86.842%, positive and negative predictive values to be 88.636% and 91.667% respectively. Therefore, current study findings revealed accuracy of mammogram to be 90.000%. Sensitivity of FNAC diagnosis was observed to be 92.857% and specificity to be 100%, positive and negative predictive values were observed to be 100% and 92.683% respectively. The study results revealed that FNAC diagnosis exhibited accuracy of 96.250%.Conclusions: Current investigation findings revealed that FNAC has more accuracy in predicting breast cancer than mammogram. Also, it was concluded that there is a significant association between FNAC and mammogram diagnosis.

Is axillary imaging for invasive lobular carcinoma accurate in determining clinical node staging?

Preoperative evaluation of clinical N-stage (cN) is difficult in breast cancer patients with invasive lobular carcinoma (ILC). Our goal was to assess the predictive value of axillary imaging in ILC by comparing imaging cN and pathologic N-stage (pN). A single-institution retrospective review was performed for newly diagnosed stage I-III ILC patients undergoing preoperative breast imaging from 2011 to 2016. Clinicopathologic factors; mammogram, MRI, and ultrasound findings; and surgical pathology data were reviewed. Sub-analysis for pN2-N3 patients was performed to determine imaging sensitivity for patients with a larger nodal disease burden. Statistical analysis included sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of each imaging modality. Of the total 349 patients included, 70.5% were cN0, and 62% were pN0 (p = 0.03). For all patients, mammogram sensitivity was 7%, specificity 97%, PPV 50%, NPV 72%; ultrasound sensitivity was 26%, specificity 86%, PPV 52%, NPV 67%; MRI sensitivity was 7%, specificity 98%, PPV 80%, NPV 51%. For pN2/N3 patients, 38% were identified as cN0. Mammogram sensitivity was 10%; ultrasound 42%; MRI 65%. Pathology evaluation of N2/N3 patients indicated LN were replaced with ILC but maintained normal architecture. The average largest pathologic tumor deposit (1.5 ± 0.8cm) correlated with average largest imaging LN size (1.4 ± 0.6cm) (p = 0.58). A statistically significant difference between clinical and pathologic N-stage exists for ILC patients. MRI was most sensitive for identification of pN2-N3 patients and should be considered part of routine axillary imaging evaluation for ILC patients.

Defining clinicopathological and radiological features of breast cancer in women under the age of 35: an epidemiological study.

Breast cancer is the most commonly diagnosed female cancer. Diagnosis in younger women (under 35years) is different to their older counterparts, and mammography is not considered as sensitive in this cohort. Consequentially, younger patients may present later with more advanced disease. This is a retrospective analysis of a prospectively updated database containing consecutive patients who presented to the symptomatic breast unit of Galway University Hospital between 2009 and 2015. Patient clinicopathologic factors, clinical examination features, diagnostic radiological modalities and Bi-RADS score were all assessed. Data was analysed using Statistical Package for the Social Sciences version 25. One thousand eight hundred thirty-six patients were diagnosed with breast cancer, and of these, 51 (2.8%) patients were < 35years. Invasive ductal carcinoma made up 90% of diagnosis, and 42% had an associated ductal carcinoma in situ. Fifty-four percent were high-grade tumours and 52% presented with stage III disease or greater. The main radiological tool used was ultrasound, which had a sensitivity of 87.50% (95% confidence interval [CI] 74.75 to 95.27%). Mammogram sensitivity was 86.84% (95% CI 71.91 to 95.59%). Magnetic resonance imaging was used in 29% of cases, with a sensitivity of 100.00% (95% CI 78.20 to 100.00%). Females under 35 tend to be diagnosed with aggressive, advanced stage tumours. Ultrasound remains the radiological test of choice, although diagnosis using mammography demonstrated a relatively high sensitivity compared with previous reports. This study emphasises the varying epidemiology of breast cancer in younger patients and the potential role of mammography in making radiological diagnosis in those who are symptomatic.

Machine Learning Approach towards Mammographic Breast Density Measurement for Breast Cancer Risk Prediction: An Overview

“Mammographic breast density” is significant biomarker which has strong association with the occurrence of breast cancer. Generally, in dense breast the tissues of breast cancer get hidden and hence the sensitivity of mammogram reduces significantly. It also increases the risk of false positive diagnosis in computer detection system. Development in the cutting-edge technology has the ability to improve the breast density measurement standards, and lead to early prediction of breast cancer by overcoming the restriction of subjective analysis of breast density measurement. In spite of development of different techniques for automatic breast density measurement, very few tools are practically available for breast cancer risk prediction. Basic objective behind this article is to provide an organized overview of selective research articles having specific application of machine learning approach for mammographic breast density measurement. We have selected research articles which follows the pipe-line of image processing with machine learning. Accuracy and computational complexity of selected methods are highlighted in order to decide the best possible future guidelines of research in this area. Hence the modification in preprocessing algorithms to remove pectoral muscle, refining of segmentation as well as feature extraction algorithms in terms of computational complexity and accuracy, selection of more accurate machine learning algorithm can make a positive impact on accuracy enhancement of breast density measurement.

Screening Sensitivity According to Breast Cancer Location

PurposeTo examine the relation between breast cancer location and screening mammogram sensitivity, and assess whether this association is modified by body mass index (BMI) or breast density. MethodsThis study is based on all interval cancers (n = 481) and a random sample of screen-detected cancers (n = 481) diagnosed in Quebec Breast Cancer Screening Program participants in 2007. Film-screening mammograms, diagnostic mammograms, and ultrasound reports (when available) were requested for these cases. The breast cancer was then localised in mediolateral oblique (MLO) and craniocaudal (CC) projections of the breast by 1 experienced radiologist. The association between cancer location and screening sensitivity was assessed by logistic regression. Adjusted sensitivity and sensitivity ratios were obtained by marginal standardisation. ResultsA total of 369 screen-detected and 268 interval cancers could be localised in MLO and/or CC projections. The 2-year sensitivity reached 68%. Overall, sensitivity was not statistically associated with location of the cancer. However, sensitivity seems lower in MLO posterior inferior area for women with BMI ≥ 25 kg/m2 compared to sensitivity in central area for women with lower BMI (adjusted sensitivity ratio: 0.58, 95% confidence interval [CI]: 0.17–0.98). Lower sensitivity was also observed in subareolar areas for women with breast density ≥ 50% compared to the central areas for women with lower breast density (for MLO and CC projections, adjusted sensitivity ratio and 95% CI of, respectively, 0.54 [0.13–0.96] and 0.46 [0.01–0.93]). ConclusionsScreening sensitivity seems lower in MLO posterior inferior area in women with higher BMI and in subareolar areas in women with higher breast density. When interpreting screening mammograms, radiologists need to pay special attention to these areas.

Retrospective analysis of breast cancer patients in an Asian-majority community clinic.

e12502 Background: Incidence of breast cancer in Asian countries is about one third to one half of that of the US. Asian immigrants have a higher risk of developing breast cancer in the US presumably by adopting more westernized lifestyles. We conduct a retrospective analysis of breast cancer patients (pts) in an Asian-majority community in Southern California. Methods: Unselected consecutive female breast cancer pts were studied. Clinical data were review and statistical analysis was conducted by SPSS 16.0. Results: 501 pts, 334 Asians (incl. Chinese 84%) and 167 non-Asians (incl. Caucasian 47% and Hispanic 45%) were studied. Conclusions: This study raised several intriguing findings: 1. Asian pts are significantly younger and have lower BMI than non-Asians. 2. Asian pts are more likely to undergo mastectomy than breast conserving surgery. 3. Asian pts tend to have denser breasts which may potentially limit the sensitivity of mammogram. Since the ratio of DCIS to invasive cancer is comparable between Asian and non-Asian pts in this study, mammogram is probably effective in detecting early cancer in Asians. 4. Significantly fewer Asian pts are diagnosed by screening mammogram. It is probably due to lower utilization of mammogram in the Asian population. 5. BRCA1/2 mutation is not significantly different between Asians and non-Asians. Due to inherent limitations of retrospective study, these findings need to be confirmed in a larger prospective study. [Table: see text]

Prospective Study of the Efficacy of Breast Magnetic Resonance Imaging and Mammographic Screening in Survivors of Hodgkin Lymphoma

Current guidelines recommend breast magnetic resonance imaging (MRI) as an adjunct to mammography for breast cancer screening in female cancer survivors treated with chest irradiation at a young age, beginning 8 to 10 years after treatment. Prospective data evaluating its efficacy in female cancer survivors are lacking. This study sought to compare the sensitivity and specificity of breast MRI with those of mammography in women who received chest irradiation for Hodgkin lymphoma (HL). We enrolled 148 women treated with chest irradiation for HL at age ≤ 35 years who were > 8 years beyond treatment. Yearly breast MRI and mammogram were performed over a 3-year period. Sensitivity and specificity of the two screening modalities were compared. With the screening, 63 biopsies were performed in 45 women; 18 (29%) showed a malignancy. All but one of the screen-detected malignancies were preinvasive or subcentimeter node-negative breast cancers. After excluding first-screen MRI and mammogram, mammogram sensitivity was 68% as compared with 67% for MRI (P = 1.0). Sensitivity increased to 94% using both screening modalities. The specificities of mammogram alone, MRI alone, and both were 93%, 94%, and 90%, respectively. In contrast to women with genetic or familial risk, in HL survivors breast MRI was not more sensitive than mammogram for breast cancer detection. However, the two screening modalities complement each other in the detection of early cases of disease. Early diagnosis is particularly important in these patients, given the breast cancer treatment challenges in patients who have received prior cancer therapy.

Mammographic Breast Density: Effect on Imaging and Breast Cancer Risk

Mammographic breast density has been studied for more than 30 years. Greater breast density not only is related to decreased sensitivity of mammograms because of a masking effect but also is a major independent risk factor for breast cancer. This article defines breast density and reviews literature on quantification of mammographic density that is key to future clinical and research protocols. Important influences on breast density are addressed, including age, menopausal status, exogenous hormones, and genetics of density. Young women with dense breasts benefit from digital mammographic technique. The potential use of supplemental MRI and ultrasound screening techniques in high-risk women and women with dense breasts is explored, as are potential risk reduction strategies.

Use of hormone therapy and risk of breast cancer detected at screening and between mammographic screens

Postmenopausal hormone therapy (HT) is associated with increased risk of breast cancer, but in women undergoing breast cancer screening it is not clear whether use of HT is associated with increased risk of breast cancer detected at screening or between screens (interval cancer). Further, it is unclear whether the use of the HTs that have been common in Scandinavia is associated with higher risk of breast cancer than the HTs used in other countries. Our study was based on data from 296,651 women aged 50-69 years, who participated in the Norwegian Breast Cancer Screening Program during 1995-2004. After a mean enrollment time of 3.8 years, 1,512 women were diagnosed with invasive screen detected breast cancer, and 814 with invasive interval breast cancer. Cox regression models were used to estimate hazard ratios (HRs) of breast cancer associated with HT use, after adjusting for confounders. Ever users of HT had a 58% increased risk of breast cancer, compared to never users. The HRs associated with HT use were 1.45 (95% confidence interval (CI) = 1.29-1.63) for screen detected and 1.89 (95% CI = 1.61-2.23) for interval cancer. The difference between screen detected and interval cancer was statistically significant (p = 0.011). The HR of breast cancer increased with duration of HT use, but significantly more so for interval than for screen detected cancer (use of HT for 5 or more years compared to never use; HR = 2.91, 95% CI = 2.10-4.04 and HR = 1.94, 95% CI = 1.51-2.50, respectively; p = 0.002). The population attributable fraction of breast cancer due to HT use was 19.8% overall. Ever users of HT tended to develop a cancer of lower grade. No other differences in histological tumor characteristics were observed between ever and never users of HT among screen detected or interval cancers. The estimated risks of either breast cancer overall with HT use are higher in Norway than reported in similar studies from the U.S. HT-use is a stronger risk factor for interval cancer than for screen detected cancer. The increased risk of interval cancer, which may partly be due to decreased sensitivity of mammograms in HT users, remains a challenge in breast cancer screening programs.

Mammographic features and correlation with biopsy findings using 11-gauge stereotactic vacuum-assisted breast biopsy (SVABB)

Mammograms are assigned a BI-RADS (Breast Imaging Reporting and Data System) category, which indicates the level of suspicion for cancer. (i) To evaluate the use of BI-RADS categories in a non-academic radiology practice based in a community hospital compared with local radiology private offices; (ii) to determine positive predictive value (PPV), sensitivity and specificity of mammograms; and (iii) to explore the correlation of BI-RAD 3-5 and lesion description with diagnosis of cancer. We performed 947 SVABBs (stereotactic vacuum-assisted breast biopsies) on 911 patients with BI-RADS 3-5. Lesions were classified as: 1=microcalcifications; 2=asymmetric density; 3=circumscribed mass; and 4=spiculated mass. BI-RADS category correlated with diagnosis of breast cancer (atypia excluded): category 3=4%; category 4=15%; and category 5=79%. The PPV of BI-RADS 4 and 5 for breast cancer or atypia was 20%, in contrast to 5% for BI-RADS 3. Sensitivity and specificity were 95% and 19%, respectively. For BI-RADS 3 without microcalcifications only 3% were positive, in contrast to 8% for remainder. First, there is a stepwise increase in cancer for each of the BI-RADS categories 3-5. Secondly, in BI-RADS 3 with microcalcifications, a biopsy is indicated according to our findings. Finally, the sensitivity of mammograms is 95% but the specificity is 19%.

Improving the accuracy of mammography: volume and outcome relationships.

Countries with centralized, high-volume mammography screening programs, such as the U.K. and Sweden, emphasize high specificity (low percentage of false positives) and high sensitivity (high percentage of true positives). By contrast, the United States does not have centralized, high-volume screening programs, emphasizes high sensitivity, and has lower average specificity. We investigated whether high sensitivity can be achieved in the context of high specificity and whether the number of mammograms read per radiologist (reader volume) drives both sensitivity and specificity. The U.K.'s National Health Service Breast Screening Programme uses the PERFORMS 2 test as a teaching and assessment tool for radiologists. The same 60-film PERFORMS 2 test was given to 194 high-volume U.K. radiologists and to 60 U.S. radiologists, who were assigned to low-, medium-, or high-volume groups on the basis of the number of mammograms read per month. The standard binormal receiver-operating characteristic (ROC) model was fitted to the data of individual readers. Detection accuracy was measured by the sensitivity at specificity = 0.90, and differences among sensitivities were determined by analysis of variance. The average sensitivity at specificity = 0.90 was 0.785 for U.K. radiologists, 0.756 for high-volume U.S. radiologists, 0.702 for medium-volume U.S. radiologists, and 0.648 for low-volume U.S. radiologists. At this specificity, low-volume U.S. radiologists had statistically significantly lower sensitivity than either high-volume U.S. radiologists or U.K. radiologists, and medium-volume U.S. radiologists had statistically significantly lower sensitivity than U.K. radiologists (P<.001, for all comparisons). Reader volume is an important determinant of mammogram sensitivity and specificity. High sensitivity (high cancer detection rate) can be achieved with high specificity (low false-positive rate) in high-volume centers. This study suggests that there is great potential for optimizing mammography screening.