False-negative Mammograms Research Articles

Lessons Learnt from Imaging Review of Interval Breast Cancers in a Single Center in the UK National Breast Screening Program.

False-negative mammograms are a part of any screening program and the National Breast Screening Program in the United Kingdom is no exception. Every year, 2.5 million women have screening mammograms in the United Kingdom. Around 8 per 1,000 women screened are diagnosed with a breast cancer and 3 per 1,000 women will present with an interval breast cancer following a negative screening mammogram and before their next mammogram. Robust quality standards have to be adhered to at every stage in the screening pathway in order to maintain the fine balance between detecting cancers early and avoiding unnecessary false-positive results. As part of this process, there is a mandatory requirement for screening units to review all breast cancers. We present a pictorial illustration of the lessons learnt from such a review in this essay. The cases described here are from one large breast screening unit in the North of England. In this unit, 30,000 to 40,000 women have a screening mammogram each year and these are all double read by human readers. All cases requiring recall and those where there is a disagreement between the first and second human reader go through a consensus/arbitration process involving a minimum of two human readers. Interval cancers are identified through a consistent process outlined by the screening program and are then subjected to a review by a minimum of two reviewers. In this process, the reviewers have access to the false-negative mammograms along with all priors that were available at the time of initial read. The reviewers make a decision on whether the initial mammogram is normal or abnormal without seeing the diagnostic mammogram with the interval cancer. They also categorize the density of the breast and describe the mammographic abnormality if there is any on a standardized interval cancer data collection form. Finally, they categorize the interval cancer into one of three types-"satisfactory," "satisfactory with learning points," or "unsatisfactory."

Abstract C118: Racial disparities in insurance coverage for supplemental breast cancer screening

Abstract Introduction and Purpose: Women with dense breasts have increased risk both for developing breast cancer and false-negative mammograms. Supplemental screening with breast MRI has been shown to shown to significantly increase cancer detection among women with dense breasts. In May 2023, Pennsylvania (PA) mandated insurance coverage of one supplemental screening study (breast MRI or ultrasound ) annually for women with dense breasts. Prior research suggests that Black women have lower breast density on average than white women based on subjective grading from the American College of Radiology Breast Imaging and Reporting Data System (BI-RADS), partially due to larger average breast size and higher body mass index (BMI) than white women. The purpose of this study was to estimate the potential impact of this supplemental screening law on different patient populations in a large health system. Methods: Women without prior breast cancer or known BRCA1/2 mutations who underwent mammographic screening at a large PA health system from April 2015-December 2017and completed a risk factor questionnaire were included (N=83,579). Under PA law, women must have either heterogeneously dense breasts plus >20% lifetime risk of breast cancer or extremely dense breasts to be eligible for insurance coverage for supplemental screening, both of which involve subjectively graded breast measurements. Breast cancer risk for each patient was estimated using the Gail model. The cancer detection rate (CDR) for mammographic screening was calculated as the number of cancers diagnosed within one year of a positive mammographic screen; the interval cancer rate was calculated as the number of cancers diagnosed within one year of a non-actionable screening mammogram per 1000 women. Logistic regression was used to calculate the odds of eligibility adjusted for age and BMI. Results: Black women were less likely to have extremely or heterogeneously dense breasts than white women (23.7% vs. 45.0%, p<0.001). Under PA law, 2.5% of Black women and 9.9% of white women would qualify for insurance coverage for supplemental screening (p<0.001). Only 0.2% of Black women and 2.3% of white women had heterogeneously dense breasts and >20% lifetime risk. Black women were more likely to have triple-negative breast cancer (TNBC) than white women (p<0.001). After adjusting for age and BMI, Black women remained 54% less likely to be eligible for supplemental screening than white women (OR=0.46, 95% 0.42-0.51, p<0.001).Conclusions: Black women are less likely to qualify for insurance coverage for supplemental breast cancer screening than white women under PA law. Given that Black women have lower prevalence of subjectively graded dense breasts and higher prevalence of TNBC, the new supplemental screening law is unlikely to meaningfully reduce racial disparities in breast cancer mortality. Methods to better assess breast cancer risk among Black women, particularly the risk of TNBC, are urgently needed to identify Black women that may benefit from supplemental screening. Citation Format: Mattia A. Mahmoud, Sarah Ehsan, Oluwadamilola M. Fayanju, Susan M. Domchek, Katherine L. Nathanson, Despina Kontos, Emily F. Conant, Anne Marie McCarthy. Racial disparities in insurance coverage for supplemental breast cancer screening [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr C118.

Circulating tumor biomarkers in early-stage breast cancer: characteristics, detection, and clinical developments.

Breast cancer is the most common form of cancer in women, contributing to high rates of morbidity and mortality owing to the ability of these tumors to metastasize via the vascular system even in the early stages of progression. While ultrasonography and mammography have enabled the more reliable detection of early-stage breast cancer, these approaches entail high rates of false positive and false negative results Mammograms also expose patients to radiation, raising clinical concerns. As such, there is substantial interest in the development of more accurate and efficacious approaches to diagnosing breast cancer in its early stages when patients are more likely to benefit from curative treatment efforts. Blood-based biomarkers derived from the tumor microenvironment (TME) have frequently been studied as candidate targets that can enable tumor detection when used for patient screening. Through these efforts, many promising biomarkers including tumor antigens, circulating tumor cell clusters, microRNAs, extracellular vesicles, circulating tumor DNA, metabolites, and lipids have emerged as targets that may enable the detection of breast tumors at various stages of progression. This review provides a systematic overview of the TME characteristics of early breast cancer, together with details on current approaches to detecting blood-based biomarkers in affected patients. The limitations, challenges, and prospects associated with different experimental and clinical platforms employed in this context are also discussed at length.

Rethinking screening mammography in Japan: next-generation breast cancer screening through breast awareness and supplemental ultrasonography.

Breast cancer mortality has not been reduced in Japan despite more than 20years of population-based screening mammography. Screening mammography might not be suitable for Japanese women who often have dense breasts, thus decreasing mammography sensitivity because of masking. The J-START study showed that breast ultrasonography increases the sensitivity and the detection rate for early invasive cancers and lowers the rate of interval cancers for Japanese women in their 40s. Breast awareness and breast cancer survival are directly correlated; however, breast awareness is not widely known in Japan. Next-generation breast cancer screening in Japan should consist of breast awareness campaigns for improving breast cancer literacy and supplemental breast ultrasonography to address the problem of false-negative mammograms attributable to dense breasts.

Educational programs and campaigns for breast awareness is a right measure against false-negative mammogram issues due to dense breasts in Japan

Educational programs and campaigns for breast awareness is a right measure against false-negative mammogram issues due to dense breasts in Japan

Utility of Diagnostic Mammography as the Primary Imaging Modality for Palpable Lumps in Women With Almost Entirely Fatty Breasts.

OBJECTIVE. The purpose of this study was to assess the performance of diagnostic mammography alone for evaluation of palpable symptoms in women with almost entirely fatty breast composition. MATERIALS AND METHODS. All diagnostic mammograms performed for palpable symptoms in women who had been assigned a breast density of "almost entirely fatty" over an 8-year period (2009-2017) at an academic breast center were retrospectively identified. Each symptomatic breast was considered a separate case and analyses were performed at the case level. Clinical, imaging, and pathologic results were reviewed. Descriptive statistics and 2 × 2 contingency table analyses were performed. RESULTS. The study cohort included 323 cases evaluated with mammography. Of these, 294 (91%) had undergone targeted ultrasound. At mammography, 240 (74%) had no correlate to the palpable lump; 38 (12%), a benign correlate; and 45 (14%), a suspicious correlate. Three cases had incidental suspicious mammographic findings, for a total of 48 positive mammography cases. Twenty-seven (8%) cases were malignant. Mammography alone detected all but one cancer, which was detected by ultrasound. In retrospect, the woman from whom this single false-negative mammogram was obtained did not have almost entirely fatty breast density. Mammography alone yielded a negative predictive value of 99.6%, percentage of diagnostic examinations recommended for biopsy that resulted in a tissue diagnosis of malignancy within 1 year of 54%, sensitivity of 96%, and specificity of 93%. Adjunct ultrasound contributed to 11 false-positives but also identified benign correlates in eight cases with no mammographic finding. CONCLUSION. In patients with almost entirely fatty breast tissue presenting with palpable symptoms, mammography alone had a high sensitivity and specificity. Our results support that mammography alone may be sufficient for evaluation of palpable symptoms in these women as long as density criteria are strictly applied.

Improved Cancer Detection Using Artificial Intelligence: a Retrospective Evaluation of Missed Cancers on Mammography

To determine whether cmAssist™, an artificial intelligence-based computer-aided detection (AI-CAD) algorithm, can be used to improve radiologists’ sensitivity in breast cancer screening and detection. A blinded retrospective study was performed with a panel of seven radiologists using a cancer-enriched data set from 122 patients that included 90 false-negative mammograms obtained up to 5.8 years prior to diagnosis and 32 BIRADS 1 and 2 patients with a 2-year follow-up of negative diagnosis. The mammograms were performed between February 7, 2008 (earliest) and January 8, 2016 (latest), and were all originally interpreted as negative in conjunction with R2 ImageChecker CAD, version 10.0. In this study, the readers analyzed the 122 studies before and after review of cmAssist™, an AI-CAD software for mammography. The statistical significance of our findings was evaluated using Student’s t test and bootstrap statistical analysis. There was a substantial and significant improvement in radiologist accuracy with use of cmAssist, as demonstrated in the 7.2% increase in the area-under-the-curve (AUC) of the receiver operating characteristic (ROC) curve with two-sided p value < 0.01 for the reader group. All radiologists showed a significant improvement in their cancer detection rate (CDR) with the use of cmAssist (two-sided p value = 0.030, confidence interval = 95%). The readers detected between 25 and 71% (mean 51%) of the early cancers without assistance. With cmAssist, the overall reader CDR was 41 to 76% (mean 62%). The percentage increase in CDR for the reader panel was significant, ranging from 6 to 64% (mean 27%) with the use of cmAssist. There was less than 1% increase in the readers’ false-positive recalls with use of cmAssist. With the use of cmAssist TM, there was a substantial and statistically significant improvement in radiologists’ accuracy and sensitivity for detection of cancers that were originally missed. The percentage increase in CDR for the radiologists in the reader panel ranged from 6 to 64% (mean 27%) with the use of cmAssist, with negligible increase in false-positive recalls.

Abstract 2585: Mammography screening adherence after a false positive test result

Abstract Mammography screening has been shown to be effective in reducing breast cancer mortality, but it also generates a significant number of false positive test results. We sought to compare mammography guideline adherence after a false positive versus a true negative screening mammogram, looking for differences by age, race, family history of breast cancer, time since prior mammogram, and mammographic breast density. Linked data from the Carolina Mammography Registry and privately insured beneficiaries in North Carolina from 2004-2009 were used to evaluate screening adherence among 14,071 women aged 40 to 64 years who had a screening mammogram with a false positive or true negative result. Women were classified as being adherent to mammography screening guidelines if they obtained a screening mammogram in the 9 to 24 months after their index screening mammogram. We compared characteristics of women with a false positive versus true negative screening mammogram result using the chi-square test. To determine if the index mammogram result (false positive or true negative) was predictive of subsequent adherence to screening mammography, we employed a random effects logistic regression, adjusting for age, race, menopausal status, first-degree family history of breast cancer, personal history of breast biopsy, mammographic breast density, time since prior mammogram, and comorbidities. We tested for interactions of these characteristics with the index mammogram result using backwards selection and considered interaction terms with p-values &amp;lt;0.05 significant. Of the 14,071 screening mammograms 92.1% were true negative and 7.9% were false positive. Women with a false positive were more likely to be younger, pre-menopausal, have dense breasts, and have had their last mammogram 3 or more years ago. Women with a false positive result were also less adherent to screening mammography in the subsequent 24 months compared to women with a true negative result (81.8% vs. 84.2%, p-value = 0.031). Women with a prior mammogram within 1 to 3 years and a false positive result were less likely to be adherent (adjusted odds ratio (OR) = 0.77, 95% CI: 0.64-0.94) than women with a true negative result. In contrast, for women who had a prior mammogram 3 or more years ago, those with a false positive result were more likely to be adherent (adjusted OR = 1.80, 95% CI: 1.13-2.87) than those with a true negative result. Our findings suggest that a false positive screening mammogram may reduce the likelihood of a woman returning for her next planned screening mammogram if her prior mammogram was within 1 to 3 years, but it may increase her likelihood to return if her prior mammogram was more than 3 years prior. Future studies should expand beyond observational data to incorporate qualitative interview data with women to better understand the psychological distress experienced after a false positive screening mammogram result. Citation Format: Mary W. Marsh, Thad Benefield, Mikael Anne Greenwood-Hickman, Laura Jones, Anne Marie Meyer, Louise M. Henderson. Mammography screening adherence after a false positive test result. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2585.

Abstract B74: Examining racial/ethnic disparities in mammography screening performance in a single, large healthcare organization

Abstract Introduction: Screening mammography for early detection of breast cancer is subject to both false positive and false negative results. False positive mammograms subject women to unnecessary diagnostic imaging and biopsies that create a burden to the patient and costs to the health care system. False negative mammograms, on the other hand, result in the diagnosis of an “interval” cancer following symptoms and typically at a later stage than if discovered on the prior screen. Prior studies conducted in metropolitan Chicago suggested that differences in both mammogram image quality and quality of the interpretation of the mammogram might contribute to higher false negative rates (FNR) and higher false positive rates (FPR) for ethnic minority patients. We sought to examine predictors of FNR and FPR, and whether ethnic disparities might exist in these outcomes within a single, large healthcare organization. Methods: Screening mammograms during 2001-2009 were linked to incident breast cancer cases for the period 2001-2010 from the Illinois State Cancer Registry (ISCR) using probabilistic linkage methods. Screening mammograms were scored by the interpreting radiologist using the American College of Radiology Breast Imaging Reporting and Data System (BIRADS) and each mammogram was defined as negative (BIRADS 1,2) or positive (BIRADS 0,4,5); BIRADS 3 mammograms were excluded from these analyses. A false positive (FP) mammogram was defined as a screening mammogram with an abnormal interpretation which nonetheless did not result in a breast cancer diagnosis in the subsequent 12 months. A false negative (FN) mammogram was defined as a screening mammogram with a normal interpretation in a woman who nonetheless was diagnosed with breast cancer (“interval cancer”) in the subsequent 12 months. We examined patient factors (race/ethnicity, age at diagnosis, and breast density) and tumor characteristics including hormone (estrogen and progesterone) receptor (ER/PR) status, tumor grade, and behavior (in-situ vs. malignant) and their association with FNR and FPR. Results: A total of 669,222 screens were included in this analysis and 4,058 breast cancer cases were diagnosed in the 12 months subsequent to each screening mammogram (3,071 screen-detected and 988 interval cancers). Overall, the false negative rate was 24.3%. As expected, the FNR decreased with increasing age, and increased with increasing breast density. Also as expected, FNR was higher for ER-/PR- breast cancer than other forms (31% vs. 25%, p=0.01), was higher for high grade/undifferentiated tumors and was higher for malignant than in situ tumors (27% vs. 19%, p &amp;lt;0.001). Contrary to expectation, however, FNR was higher in White than African Americans patients (26% vs. 20%, p&amp;lt;0.001); and FNR was higher for digital than analog mammograms (27% vs. 23%, p=0.001). With regards to false positive rate (FPR), FPR was 12.6% overall. As hypothesized, FPR was slightly higher in African Americans compared to Whites (14% vs. 11%, p=0.014), and higher for mammograms performed on women with heterogeneously/extremely dense versus less dense breasts (14% vs. 11%, p&amp;lt;0.0001). Conclusion: Contrary to expectation, we did not find a racial disparity in the probability of a false negative mammogram, though we did find a modestly increased false positive rate in ethnic minorities. Radiologists in this organization are provided feedback on the quality of their screening interpretations on a regular basis, and this quality control program may be responsible for leveling the quality of screening mammography by race/ethnicity. Citation Format: Firas M. Dabbous, Garth Rauscher, Terry Macarol, Jenna Khan, Therese Dolecek, Sally Friedewald, Teena Francois, Tom Summerfelt. Examining racial/ethnic disparities in mammography screening performance in a single, large healthcare organization. [abstract]. In: Proceedings of the Sixth AACR Conference: The Science of Cancer Health Disparities; Dec 6–9, 2013; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2014;23(11 Suppl):Abstract nr B74. doi:10.1158/1538-7755.DISP13-B74

Breast Cancer Diagnosis by CAD

ABSTRACT Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death of female worldwide. Mammogram is one of the most excellent technologies currently being used for diagnosing breast cancer. Computer aided diagnosis helps the radiologists to detect abnormalities earlier than traditional procedures. In this paper, we suggested to use some of features selected to distinguish the benign and malignant breast cancer. Tumor segmented and denoising prior to classification. The accuracy of proposed system was 100%. General Terms Image processing, Pattern recognition, Medical image processing. Keywords Breast Cancer, Mammography, Denoising, Diagnosis, Image Features. 1. INTRODUCTION The uncontrolled division of one cell may cause to emerge mass called tumor. Tumor can be benign or malignant. Benign tumor cannot spread or invade to other parts of the body while malignant tumor grows rapidly and invades its surrounding tissues through causing their damage. Breast cancer is a malignant tissue beginning to grow in the breast. The abnormalities like existence of a breast mass change in shape and dimension of breast, differences in the color of breast skin, breast aches, etc. are the symptoms of breast cancer [1]. Breast cancer is a disease of humans and other mammals; while the overwhelming majority of cases in humans are women, men can also develop breast cancer. Mammography is the most used screening tool for abnormality detection, because it allows an easy way to identify the cancer. The goal of mammography is the early detection of breast cancer, typically through detection of characteristic masses and/or micro-calcifications. Radiologists interpret the mammograms and attempt to identify areas of potential abnormalities. Therefore, the expert radiologist’s is the corner stones of diagnosis the breast cancer; the screening process depends on the radiologist’s ability to detect areas of subtle irregular abnormalities. It is estimated that between 10-30% of women diagnosed with breast cancer have false-negative mammograms [2]. Most of the false-negative cases can be attributed to the radiologist's failure to detect a cancer which could be due to misinterpretation, or simply that the radiologist overlooked the area. It has been demonstrated that an independent second reading can significantly improve the detection rate and decrease the number of false positive cases. Computerized aided can help the physicians, and radiologist’s to detecting and diagnosing the breast cancer; it is a tools to processing and analyzing images as secondary reading. The first step for CAD is the ability to identify the abnormal masses in the breast, while the second step is to diagnosis the masses detected in the first step. Before these two steps implementing a really important preprocessing step has to take place which is the detection or segmentation of the breast region from the background. The analysis of mammogram image can assist the radiologist for early detection of tumor and diagnosis the breast cancer effectively [3]. Computer aided can classify into two main groups: computer-aided detection (CADe) and computer-aided diagnosis (CADx). The first group CADe works with medical images to detect and localize the lesions in the image. While CADx works directly on the lesions to classify them to benign and malignant, it is diagnosis process [4].

Dilemma of False Negative Mammograms in Breast Cancer Patients

Background: Breast cancer is the most common cancer in women and the second cause of mortality after lung cancer. Mammography is an effective tool in detecting both clinically occult and palpable breast cancers. However, a good number of breast carcinomas may not appear on the mammogram. The false negative rate for conventional mammography worldwide is 10% 30% 1 . There are very few studies addressing the results of mammography in Bahrain.

A computer aided detection framework for mammographic images using fisher linear discriminant and nearest neighbor classifier

Today, mammography is the best method for early detection of breast cancer. Radiologists failed to detect evident cancerous signs in approximately 20% of false negative mammograms. False negatives have been identified as the inability of the radiologist to detect the abnormalities due to several reasons such as poor image quality, image noise, or eye fatigue. This paper presents a framework for a computer aided detection system that integrates Principal Component Analysis (PCA), Fisher Linear Discriminant (FLD), and Nearest Neighbor Classifier (KNN) algorithms for the detection of abnormalities in mammograms. Using normal and abnormal mammograms from the MIAS database, the integrated algorithm achieved 93.06% classification accuracy. Also in this paper, we present an analysis of the integrated algorithm’s parameters and suggest selection criteria.

PCN152 Can Breast Cancer Risk Prediction Reduce the Risks of False Negative and False Positive Screening Mammograms?

PCN152 Can Breast Cancer Risk Prediction Reduce the Risks of False Negative and False Positive Screening Mammograms?

A Method For Improve Preprocessing Images Mammography

A great volume of mammography images have dark background, these parts are not important in processing of mammography images. We can decrease the picture size and increase the processing speed by deleting these parts. Some parts of images have some notes and labels which consist of information like name, family, hospital's seal, date and…. It is better to omit these labels before processing since they are bright; the same as gray level of some breast tissues and have the same gray level. In the other way it is better to limit processing to the breast region and omit excessive parts. Previous studies over breast tissues show that if the considered region has not been marked clearly, it will influence characteristics and will not give the desired result. For obtaining this aim first find the main breast region, and then omit excessive parts to obtain processing result accurately and rapidly. The work that we do in this paper is introduced in three phases. The first phase is omitting the excessive image parts which are in the two sides of the image; we do this work by the usage of the pixels brightness. The second phase is the distinction of the breast direction and put all images in one direction; we do this work by the usage of threshold limit of gray level of the two halves of the image. The third phase is the breast region segmentation from the background; we do this work by the usage of series of point operations and the growing region method and the result has been reported to 99%. false negative mammograms (28). It has been shown that an independent second reading of mammograms improves the sensitivity of mammography by as much as 15% (29). Computerized analysis of mammograms has been envisaged as a means of providing a emulated secon- opinion (30), improving consistency by providing a standardized approach lo mammogram interpretation, and increasing detection sensitivity. Computer- Aided Detection (CADe) is the process of identifying potential abnormalities withm a mammogram, classifying regions of a mammogram as positive or negative. CADe systems use image processing algorithms to analyze mammograms for possible abnormalities including masses, microcalcifications, distortions in breast architecture, and symmetric densities. AAer an initial examination of the mammographic images, a radiologist reviews suspicious regions prompted by the CADe system and determines whether they warrant further follow-up. The CADe system assists the radiologist by confirming the detection of suspicious regions or identifying those that might otherwise have been missed. The precise segmentation of the breast region in mammograms is an essential preprocessing step in the computerized analysis of mammograms. It allows the search for abnormalities to be limited to the region of the breast without undue influence from the background of the mammogram. It also facilitates enhancements to techniques such as comparative analysis, which includes the automated comparison of corresponding mammograms. The breast boundary contains significant information relating to the deformation between two mammograms and is the source of information for relating the position of the nipple relative to the skin surface.

Zur Leistungsfähigkeit des Record-Linkage zwischen epidemiologischen Krebsregistern und dem Mammographie-Screening

The evaluation of the German Mammography Screening Program requires record linkage with data from cancer registries in order to measure the number of false-negative mammograms and interval cancers. This study aims at evaluating the performance of the established linkage method based on identifiers encrypted by the standard procedure of the German cancer registries. In addition, the results are compared with an alternative method based on plain text identifiers. A total of 16,572 records from the Bremen Mammography Screening Pilot Study were linked with data from the Bremen Cancer Registry. Based on a gold standard set of matching record pairs, homonym and synonym errors were determined. Given the customary threshold value in cancer registries, the plain text method showed a lower rate of synonym errors (2.1-5.1%) and a lower rate of homonym errors (0.01-0.15%). As 10.4 million women are invited to take part biennially in screening, the corresponding figures would be 3,237 homonym errors for the standard procedure and 294 using the plain text method provided equivalent conditions. The 11-fold increase in the homonym error rate documents the trade-off for better data protection using encrypted data.

Can Peer Review Contribute to Earlier Detection of Breast Cancer? A Quality Initiative to Learn from False-Negative Mammograms

Although Mammography Quality Standards Act requires tracking true positives, tracking false negatives is not required. We describe a peer review process implemented at Lahey Clinic to identify false-negative mammograms. We defined a false-negative mammogram as one which was read as negative within 12 months of a cancer diagnosis, and in which two of three radiologists correctly identified the site of cancer. Reviewing radiologists were blinded to each other and to computer-aided design (CAD), but were aware that somewhere in the mammogram was cancer. 25/64, 983, or 0.038% were classified as misses. The false-negative rate of any one radiologist averaged <0.1% without outliers. Of the false negatives, 60% were in heterogeneously dense tissue, 72% were asymmetries or masses rather than calcifications, and 24% were correctly identified by CAD in two views. We use these data for quality assurance, educational purposes, and to help identify patterns of undetected cancers to aid in earlier and improved detection of breast cancers.

TU‐D‐342‐01: Advances in Breast Imaging

Over the last decade, there have been tremendous advances in breast imaging. As many facilities make the transition from film screen to digital mammography, it is appropriate to examine the accomplishments of the past and to acknowledge current technological limitations. In addition, we should carefully study evolving technologies in breast imaging with the goal of developing highly sensitive and highly specific techniques. This presentation will examine recent progress in digital mammography, including contrast‐enhanced imaging, tomosynthesis, and breast CT, from a breast imager's perspective.Randomized clinical trials and meta‐analyses have shown that screening mammography results in a decrease in breast cancer mortality. Although mammography is efficacious in most women, we know that mammography is not a perfect test, epecially in women with radiographically dense breasts. Furthermore, false positive and false negative mammograms are difficult to eliminate. As digital mammography replaces film screen mammography in many practice settings, cancer detection rates may rise slightly and call back rates may decrease slightly.Overlapping densities and areas of dense tissue often make interpretation of film screen mammograms difficult. Overlapping parenchyma and dense tissue hinder digital mammography less than film screen mammography, but these overlying structures are not eliminated with digital mammography. Major efforts have been made in digital tomosynthesis and breast CT in order to advance beyond projection imaging. Tomosynthesis involves the acquisition of tomographic images in the digital mammography unit, while breast CT is based on a volumetric acquisition with the patient positioned prone in a machine that is similar to a unit used for stereotactic biopsies.Conventional digital mammography, digital tomosynthesis, and breast CT may be combined with the injection of iodinated contrast material in order to visualize tumor vascularity and increase the conspicuity of breast tumors. These techniques may also be used to monitor response to neoadjuvant chemotherapy.Over the next decade, tomosynthesis and breast CT will transition from research applications to clinical realities. Further studies are needed in order to determine how to use these emerging tools in an effective, efficacious manner.Educational Objectives:1. To review advances in breast imaging over the last decade.2. To understand the strengths and weaknesses of film screen and digital mammography.3. To appreciate the potential roles of digital tomosynthesis and breast CT.4. To understand the application of iodinated contrast material in digital mammography, tomosynthesis, and breast CT.

Imaging Findings of Missed Breast Cancer: Retrospective Analysis

Screening mammography has been proved to be an effective tool to detect early breast cancers and to decrease mortality. However, the rate of false-negative mammograms has been reported to be still high as 10~30%. Missed breast cancers are cancers that are visible at previous mammograms only retrospectively and can be classified as three types; interval cancers, subsequent screen-detected cancers, and alternative imaging-detected cancers. In a small group, screen-detected abnormalities recalled for further evaluation may be dismissed due to false negative diagnostic assessment, leading to delays in breast cancer diagnosis. Possible causes for missing include perception errors, interpretation errors, and technical errors. Furthermore, every diagnostic examination has inherent limitations. Perception errors are often attributed to combined multiple factors; peripheral lesions, single view abnormalities, subtle findings, distracting lesions, and dense parenchyma obscuring a lesion. To decrease the false negative rate, radiologists should be alert to take additional mammograms and ultrasonography, and should try to improve the image quality and interpretation techniques comparing with the previous imaging, considering the use of computer-aided detection or double reading.

The Effect of Silicone Implants on the Diagnosis, Prognosis, and Treatment of Breast Cancer

Because of the prevalence of breast cancer, many augmented women eventually will develop the disease. This article reviews what is known about the effect of implants on the detection, prognosis, and treatment of carcinoma of the breast. Observations were made on 4082 breast cancer patients (3953 nonaugmented and 129 augmented) treated over a 23-year time span. Findings in the two groups were compared and differences analyzed statistically. Mammograms of all women with palpable lesions were reviewed to assess mammographic sensitivity in patients with and without implants. Cosmetic outcomes in augmented patients treated with breast conservation therapy were reviewed. Augmented patients presented more frequently with palpable lesions, invasive tumors, axillary nodal metastases, and false-negative mammograms. However, there was no significant difference in stage of disease, tumor size, recurrence rates, or survival between the two groups. Augmented patients treated with breast conservation therapy often experienced poor cosmetic results and frequently required reoperation. Despite the diminished sensitivity of mammography in women with implants, augmented and nonaugmented patients are diagnosed at a similar stage of disease and have a comparable prognosis. Implants may impair mammography but appear to facilitate tumor detection on physical examination. Magnetic resonance imaging and breast ultrasound may be useful adjuncts, but conventional mammography remains the most reliable tool for diagnosing early breast cancer in augmented patients. Breast implants do not interfere with mastectomy or breast reconstruction but may compromise the outcome of breast conservation therapy.

Analysis of patients with false negative mammography and symptomatic breast carcinoma

False-negative mammograms may result in a delay in breast carcinoma diagnosis and have important implications for patient care. In this study, the characteristics of symptomatic patients with false-negative mammograms were analysed. Patients with symptomatic breast carcinoma were identified over a 10-year period (1994-2004). One hundred and twenty-four patients had false-negative preoperative mammograms and 1241 patients had abnormal preoperative mammograms. Clinical presentation, diagnostic methods and pathology were analysed. False-negative mammograms were reviewed by a specialist breast radiologist. Following retrospective review, 42% of false-negative mammograms were re-categorised as suspicious. The most commonly misinterpreted lesion was architectural distortion/asymmetrical density. Adjuvant ultrasound, where performed (n = 27), raised the level of suspicion in 93% of cases. Patients with false-negative mammograms were more likely to be younger (P < 0.0001), present with nipple discharge (P = 0.002) and have smaller tumours (P < 0.0001). Their tumours were more frequently located outside the upper outer quadrant (P = 0.002). False-negative mammography led to a delay in diagnosis of >2 months in 12 patients. Symptomatic patients with false-negative mammograms often demonstrate definite abnormalities on imaging, the most common of which is architectural distortion/asymmetrical density. Those at particular risk were younger patients, those with nipple discharge, and patients with lesions located outside the upper outer quadrant.