Importance of Comparison of Current and Prior Mammograms in Breast Cancer Screening

Revolutionizing Breast Cancer Detection With Artificial Intelligence (AI) in Radiology and Radiation Oncology: A Systematic Review

The number one cause of cancer in women worldwide is breast cancer. Over the last three decades, the use of traditional screen-film mammography has increased, but in recent years, digital mammography and 3D tomosynthesis have become standard procedures for breast cancer screening. With the advancement of technology, the interpretation of images using automated algorithms has become a subject of interest. Initially, computer-aided detection (CAD) was introduced; however, it did not show any long-term benefit in clinical practice. With recent advances in artificial intelligence (AI) methods, these technologies are showing promising potential for more accurate and efficient automated breast cancer detection and treatment. While AI promises widespread integration in breast cancer detection and treatment, challenges such as data quality, regulatory, ethical implications, and algorithm validation are crucial. Addressing these is essential for fully realizing AI's potential in enhancing early diagnosis and improving patient outcomes in breast cancer management. In this review article, we aim to provide an overview of the latest developments and applications of AI in breast cancer screening and treatment. While the existing literature primarily consists of retrospective studies, ongoing and future prospective research is poised to offer deeper insights. Artificial intelligence is on the verge of widespread integration into breast cancer detection and treatment, holding the potential to enhance early diagnosis and improve patient outcomes.

A CNN Hyperparameters Optimization Based on Particle Swarm Optimization for Mammography Breast Cancer Classification

Breast cancer is considered one of the most-common types of cancers among females in the world, with a high mortality rate. Medical imaging is still one of the most-reliable tools to detect breast cancer. Unfortunately, manual image detection takes much time. This paper proposes a new deep learning method based on Convolutional Neural Networks (CNNs). Convolutional Neural Networks are widely used for image classification. However, the determination process for accurate hyperparameters and architectures is still a challenging task. In this work, a highly accurate CNN model to detect breast cancer by mammography was developed. The proposed method is based on the Particle Swarm Optimization (PSO) algorithm in order to look for suitable hyperparameters and the architecture for the CNN model. The CNN model using PSO achieved success rates of 98.23% and 97.98% on the DDSM and MIAS datasets, respectively. The experimental results proved that the proposed CNN model gave the best accuracy values in comparison with other studies in the field. As a result, CNN models for mammography classification can now be created automatically. The proposed method can be considered as a powerful technique for breast cancer prediction.

Does the availability of prior mammograms improve radiologists' observer performance?-a scoping review

Objective

The objective of this review was to examine the impact of previous mammogram availability on radiologists' performance from screening populations and experimental studies.

Materials and Methods

A search of the literature was conducted using five databases: MEDLINE, PubMed, Web of Science, ScienceDirect, and CINAHL as well as Google and reference lists of articles. Keywords were combined with "AND" or "OR" or "WITH" and included "prior mammograms, diagnostic performance, initial images, diagnostic efficacy, subsequent images, previous imaging, and radiologist's performance". Studies that assessed the impact of previous mammogram availability on radiologists' performance were reviewed. The Standard for Reporting Diagnostic Accuracy guidelines was used to critically appraise individual sources of evidence.

Results

A total of 15 articles were reviewed. The sample of mammogram cases used across these studies varied from 36 to 1,208,051. Prior mammograms did not affect sensitivity [with priors: 62-86% (mean = 73.3%); without priors: 69.4-87.4% (mean = 75.8%)] and cancer detection rate, but increased specificity [with priors: 72-96% (mean = 87.5%); without priors: 63-87% (mean = 80.5%)] and reduced false-positive rates [with priors: 3.7 to 36% (mean = 19.9%); without priors 13.3-49% (mean = 31.4%)], recall rates [with priors: 3.8-57% (mean = 26.6%); without priors: [4.9%-67.5% (mean = 37.9%)], and abnormal interpretation rate decreased by 4% with priors. Evidence for the associations between the availability of prior mammograms and positive-predictive value, area under the curve (AUC) from the receiver operating characteristic curve (ROC) and localisation ROC AUC, and positive-predictive value of recall is limited and unclear.

Conclusion

Availability of prior mammograms reduces recall rates, false-positive rates, abnormal interpretation rates, and increases specificity without affecting sensitivity and cancer detection rate.

The dilemma of recalling well-circumscribed masses in a screening population: A narrative literature review and exploration of Dutch screening practice

BACKGROUND

In Dutch breast cancer screening, solitary, new or growing well-circumscribed masses should be recalled for further assessment. This results in cancers detected but also in false positive recalls, especially at initial screening. The aim of this study was to determine characteristics of well-circumscribed masses at mammography and identify potential methods to improve the recall strategy.

METHODS

A systematic literature search was performed using PubMed. In addition, follow-up data were retrieved on all 8860 recalled women in a Dutch screening region from 2014 to 2019.

RESULTS

Based on 15 articles identified in the literature search, we found that probably benign well-circumscribed masses that were kept under surveillance had a positive predictive value (PPV) of 0-2%. New or enlarging solitary well-circumscribed masses had a PPV of 10-12%. In general the detected carcinomas had a favorable prognosis. In our exploration of screening practice, 25% of recalls (2133/8860) were triggered by a well-circumscribed mass. Those recalls had a PPV of 2.0% for initial and 10.6% for subsequent screening. Most detected carcinomas had a favorable prognosis as well.

CONCLUSION

To recognize malignancies presenting as well-circumscribed masses, identifying solitary, new or growing lesions is key. This information is missing at initial screening since prior examinations are not available, leading to a low PPV. Access to prior clinical examinations may therefore improve this PPV. In addition, given the generally favorable prognosis of screen-detected malignant well-circumscribed masses, one may opt to recall these lesions at subsequent screening, if grown, rather than at initial screening.

Identification of factors associated with diagnostic performance variation in reporting of mammograms: A review

OBJECTIVES

This narrative review aims to identify what factors are linked to diagnostic performance variation for those who interpret mammograms. Identification of influential factors has potential to contribute to the optimisation of breast cancer diagnosis. PubMed, ScienceDirect and Google Scholar databases were searched using the following terms: 'Radiology', 'Radiologist', 'Radiographer', 'Radiography', 'Mammography', 'Interpret', 'read', 'observe' 'report', 'screen', 'image', 'performance' and 'characteristics.' Exclusion criteria included articles published prior to 2000 as digital mammography was introduced at this time. Non-English articles language were also excluded. 38 of 2542 studies identified were analysed.

KEY FINDINGS

Influencing factors included, new technology, volume of reads, experience and training, availability of prior images, social networking, fatigue and time-of-day of interpretation. Advancements in breast imaging such as digital breast tomosynthesis and volume of mammograms are primary factors that affect performance as well as tiredness, time-of-day when images are interpreted, stages of training and years of experience. Recent studies emphasised the importance of social networking and knowledge sharing if breast cancer diagnosis is to be optimised.

CONCLUSION

It was demonstrated that data on radiologist performance variability is widely available but there is a paucity of data on radiographers who interpret mammographic images.

IMPLICATIONS FOR PRACTICE

This scarcity of research needs to be addressed in order to optimise radiography-led reporting and set baseline values for diagnostic efficacy.

The Impact of Prior Mammograms on the Diagnostic Performance of Radiologists in Early Breast Cancer Detection: A Focus on Breast Density, Lesion Features and Vendors Using Wholly Digital Screening Cases

BACKGROUND

This study aims to investigate the diagnostic efficacy of radiologists when reading screening mammograms in the absence of previous images, and with the presence of prior images from the same and different vendors.

METHODS

612 radiologists' readings across 9 test sets, consisting of 540 screening mammograms (361-normal and 179-cancer) with 245 cases having prior images obtained from same vendor as current images, 129 from a different vendor and 166 cases having no prior images, were retrospectively analysed. True positive (sensitivity), true negative (specificity) and area under ROC curve (AUC) values of radiologists were calculated for three groups of cases (without prior images (NP), with prior images from same vendor (SP), and with prior images from different vendor (DP)). Logistic regression was used to estimate the odds ratio (OR) of true positive, true negative and true cancer localization among case groups with different levels of breast density and lesion characteristics.

RESULTS

Radiologists obtained 12.8% and 10.3% higher sensitivity in NP and DP than SP (0.803-and-0.785 vs. 0.712; p < 0.0001). Specificity in NP and DP cases were 4.8% and 2.0% lower than SP cases (0.749 and 0.771 vs. 0.787). The AUC values for NP and DP were significantly higher than SP cases across different levels of breast density (0.814-and-0.820 vs. 0.782; p < 0.0001). The odds ratio (OR) of true positive for NP relative to SP was 1.6 (p < 0.0001) and DP relative to SP was 1.5 (p < 0.0001). Radiologists were more like to detect architectural distortion in DP than SP cases (OR = 3.2; p < 0.0001), whilst the OR for abnormal calcifications was 2.85 (p < 0.0001).

CONCLUSIONS

Cases without previous mammograms or with prior mammograms obtained from different vendors were more likely to benefit radiologists in cancer detection, whilst prior mammograms undertaken from the same vendor were more useful for radiologists in evaluating normal cases.

Automatic Breast Mass Segmentation and Classification Using Subtraction of Temporally Sequential Digital Mammograms

OBJECTIVE

Cancer remains a major cause of morbidity and mortality globally, with 1 in 5 of all new cancers arising in the breast. The introduction of mammography for the radiological diagnosis of breast abnormalities, significantly decreased their mortality rates. Accurate detection and classification of breast masses in mammograms is especially challenging for various reasons, including low contrast and the normal variations of breast tissue density. Various Computer-Aided Diagnosis (CAD) systems are being developed to assist radiologists with the accurate classification of breast abnormalities.

METHODS

In this study, subtraction of temporally sequential digital mammograms and machine learning are proposed for the automatic segmentation and classification of masses. The performance of the algorithm was evaluated on a dataset created especially for the purposes of this study, with 320 images from 80 patients (two time points and two views of each breast) with precisely annotated mass locations by two radiologists.

RESULTS

Ninety-six features were extracted and ten classifiers were tested in a leave-one-patient-out and k-fold cross-validation process. Using Neural Networks, the detection of masses was 99.9% accurate. The classification accuracy of the masses as benign or suspicious increased from 92.6%, using the state-of-the-art temporal analysis, to 98%, using the proposed methodology. The improvement was statistically significant (p-value < 0.05).

CONCLUSION

These results demonstrate the effectiveness of the subtraction of temporally consecutive mammograms for the diagnosis of breast masses. Clinical and Translational Impact Statement: The proposed algorithm has the potential to substantially contribute to the development of automated breast cancer Computer-Aided Diagnosis systems with significant impact on patient prognosis.

Comparison of Outcomes for One-View Asymmetries Recalled From Digital Breast Tomosynthesis Versus Full-Field Digital Mammography Screening Examinations

BACKGROUND. Recall rates are lower for digital breast tomosynthesis (DBT) than for full-field digital mammography (FFDM). This difference could have important implications with respect to one-view asymmetries given that missed cancers are often visible on one view. OBJECTIVE. The purpose of this study is to compare the outcomes of one-view asymmetries recalled from DBT versus FFDM screening examinations and to determine predictors of malignancy among recalled asymmetries. METHODS. This retrospective study first determined recall rates associated with one-view asymmetries for screening mammography performed using DBT and FFDM from July 14, 2016, through July 14, 2020. Further analyses included patients recalled for a one-view asymmetry who completed subsequent diagnostic workup and all recommended follow-up. Patient and cancer characteristics were extracted from the electronic health record. RESULTS. The recall rate associated with asymmetries was lower for DBT screening (2.5% [3169/128,755]) than for FFDM screening (3.4% [815/23,898]) (p < .001). Further analyses of patients who completed diagnostic workup and subsequent follow-up included 3119 patients (mean age, 57 years) for DBT screening and 811 patients (mean age, 56 years) for FFDM screening. Distribution of final BI-RADS categories from subsequent diagnostic workup was not different between the two modalities (p > .99). The frequency of malignancy was not different between asymmetries recalled from DBT (1.7% [54/3119]) and FFDM (1.7% [14/811]) (p > .99). Malignant asymmetries identified on FFDM versus DBT were more frequently associated with architectural distortion on diagnostic workup (35.7% [5/14] vs 9.3% [5/54]) (p < .001) and were more commonly invasive ductal carcinoma (92.9% vs 57.4%) and less commonly invasive lobular carcinoma (0.0% vs 24.1%) (p = .05). In multivariable analysis, independent predictors of malignancy among recalled asymmetries from DBT were age (for 55-69 years, odds ratio [OR] = 2.40 [p = .04]; for ≥ 70 years, OR = 7.93 [p < .001]; reference, < 55 years) and breast density (not dense, OR = 2.47 [p = .001]; reference, dense breasts). CONCLUSION. Recalled asymmetries were less frequent for DBT than for FFDM. The malignancy rate was low for both modalities (1.7%). Age 55 years old and older and lower breast density predicted malignancy for DBT-recalled asymmetries. CLINICAL IMPACT. Our results support the use of DBT to reduce unnecessary recalls without altering PPV for asymmetry-associated malignancies. Patient factors should be considered when assessing whether a potential asymmetry on DBT screening represents overlapping fibroglandular tissue or a suspicious finding that requires diagnostic workup.

Know your way around acute unenhanced CT during global iodinated contrast crisis: a refresher to ED radiologists

Due to a contrast shortage crisis resulting from the decreased supply of iodinated contrast agents, the American College of Radiology (ACR) has issued a guidance statement followed by memoranda from various hospitals to preserve and prioritize the limited supply of contrast. The vast majority of iodinated contrast is used by CT, with a minority used by vascular and intervention radiology, fluoroscopy, and other services. A direct consequence is a paradigm shift to large volume unenhanced CT scans being utilized for acute and post traumatic patients in EDs, an uncharted territory for most radiologists and trainees. This article provides radiological diagnostic guidance and a pictorial example through systematic review of common unenhanced CT findings in the acute setting.

The Need for Medical Artificial Intelligence That Incorporates Prior Images

The use of artificial intelligence (AI) has grown dramatically in the past few years in the United States and worldwide, with more than 300 AI-enabled devices approved by the U.S. Food and Drug Administration (FDA). Most of these AI-enabled applications focus on helping radiologists with detection, triage, and prioritization of tasks by using data from a single point, but clinical practice often encompasses a dynamic scenario wherein physicians make decisions on the basis of longitudinal information. Unfortunately, benchmark data sets incorporating clinical and radiologic data from several points are scarce, and, therefore, the machine learning community has not focused on developing methods and architectures suitable for these tasks. Current AI algorithms are not suited to tackle key image interpretation tasks that require comparisons to previous examinations. Focusing on the curation of data sets and algorithm development that allow for comparisons at different points will be required to advance the range of relevant tasks covered by future AI-enabled FDA-cleared devices.

Benefits and harms of annual, biennial, or triennial breast cancer mammography screening for women at average risk of breast cancer: a systematic review for the European Commission Initiative on Breast Cancer (ECIBC)

BACKGROUND

Although mammography screening is recommended in most European countries, the balance between the benefits and harms of different screening intervals is still a matter of debate. This review informed the European Commission Initiative on Breast Cancer (BC) recommendations.

METHODS

We searched PubMed, EMBASE, and the Cochrane Library to identify RCTs, observational or modelling studies, comparing desirable (BC deaths averted, QALYs, BC stage, interval cancer) and undesirable (overdiagnosis, false positive related, radiation related) effects from annual, biennial, or triennial mammography screening in women of average risk for BC. We assessed the certainty of the evidence using the GRADE approach.

RESULTS

We included one RCT, 13 observational, and 11 modelling studies. In women 50-69, annual compared to biennial screening may have small additional benefits but an important increase in false positive results; triennial compared to biennial screening may have smaller benefits while avoiding some harms. In younger women (aged 45-49), annual compared to biennial screening had a smaller gain in benefits and larger harms, showing a less favourable balance in this age group than in women 50-69. In women 70-74, there were fewer additional harms and similar benefits with shorter screening intervals. The overall certainty of the evidence for each of these comparisons was very low.

CONCLUSIONS

In women of average BC risk, screening intervals have different trade-offs for each age group. The balance probably favours biennial screening in women 50-69. In younger women, annual screening may have a less favourable balance, while in women aged 70-74 years longer screening intervals may be more favourable.

The Effect of Clinical History on Diagnostic Imaging Interpretation - A Systematic Review

RATIONALE AND OBJECTIVES

To provide updated information on the effect of clinical history on diagnostic image interpretation and to provide study methodology and design recommendations for future studies assessing the effect of clinical history on diagnostic image performance.

MATERIALS AND METHODS

A literature search of Medline, Embase, Scopus, Web of Science, and the Cochrane Central Register of Controlled Trials (CENTRAL) databases was conducted from database inception to July 21, 2020. Studies comparing diagnostic imaging performance with and without clinical history, using observers reading images under both conditions that used an independent reference standard were included.

RESULTS

Twenty-two studies met the inclusion criteria, with 15 showing clinical history improved diagnostic performance. One study reported a decrease in diagnostic performance with clinical history and the remaining six studies found no significant change in performance. Two studies used the free response paradigm with both reporting clinical history increased location sensitivity, decreased specificity and had no overall change in diagnostic performance. The disease spectrum of included cases was largely unreported and a balanced reading design was not used in 19 studies.

CONCLUSION

Most published studies found that clinical history improved diagnostic performance. More recent studies accounting for abnormality location and multiple abnormalities showed an increase in false positives and no significant change in overall diagnostic performance with clinical history.

Perspective: in pursuit of a learning culture

Transitioning from peer review to peer learning is an important step forward in developing a learning culture. Additional measures are going to be required to meet this goal. Ideas toward establishing a learning culture are detailed in this perspective.

Digital subtraction of temporally sequential mammograms for improved detection and classification of microcalcifications

Background

Our aim was to demonstrate that automated detection and classification of breast microcalcifications, according to Breast Imaging Reporting and Data System (BI-RADS) categorisation, can be improved with the subtraction of sequential mammograms as opposed to using the most recent image only.

Methods

One hundred pairs of mammograms were retrospectively collected from two temporally sequential rounds. Fifty percent of the images included no (BI-RADS 1) or benign (BI-RADS 2) microcalcifications. The remaining exhibited suspicious findings (BI-RADS 4-5) in the recent image. Mammograms cannot be directly subtracted, due to tissue changes over time and breast deformation during mammography. To overcome this challenge, optimised preprocessing, image registration, and postprocessing procedures were developed. Machine learning techniques were employed to eliminate false positives (normal tissue misclassified as microcalcifications) and to classify the true microcalcifications as BI-RADS benign or suspicious. Ninety-six features were extracted and nine classifiers were evaluated with and without temporal subtraction. The performance was assessed by measuring sensitivity, specificity, accuracy, and area under the curve (AUC) at receiver operator characteristics analysis.

Results

Using temporal subtraction, the contrast ratio improved ~ 57 times compared to the most recent mammograms, enhancing the detection of the radiologic changes. Classifying as BI-RADS benign versus suspicious microcalcifications, resulted in 90.3% accuracy and 0.87 AUC, compared to 82.7% and 0.81 using just the most recent mammogram (p = 0.003).

Conclusion

Compared to using the most recent mammogram alone, temporal subtraction is more effective in the microcalcifications detection and classification and may play a role in automated diagnosis systems.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41747-021-00238-w.

Does mammographic density remain a radiological challenge in the digital era?

BACKGROUND

The low subject contrast between cancerous and fibroglandular tissue could obscure breast abnormalities.

PURPOSE

To investigate radiologists' performance for detection of breast cancer in low and high mammographic density (MD) when cases are digitally acquired.

MATERIAL AND METHODS

A test set of 60 digital mammography cases, of which 20 were cancerous, were examined by 17 radiologists. Mammograms were categorized as low (≤50%) or high (>50%) MD and rated for suspicion of malignancy using the Royal Australian and New Zealand College of Radiology (RANZCR) classification system. Radiologist demographics including cases read per year, age, subspecialty, and years of reporting were recorded. Radiologist performance was analyzed by the following metrics: sensitivity; specificity; area under the receiver operating characteristic (ROC) curve (AUC), location sensitivity, and jackknife free-response ROC (JAFROC) figure of merit (FOM).

RESULTS

Comparing high to low MD cases, radiologists showed a significantly higher sensitivity (P = 0.015), AUC (P = 0.003), location sensitivity (P = 0.002), and JAFROC FOM (P = 0.001). In high compared to low MD cases, radiologists with <1000 annual reads and radiologists with no mammographic subspecialty had significantly higher AUC, location sensitivity, and JAFROC FOM. Radiologists with ≥1000 annual reads and radiologists with mammography subspecialty demonstrated a significant increase in location sensitivity in high compared to low MD cases.

CONCLUSION

In this experimental situation, radiologists' performance was higher when reading cases with high compared to low MD. Experienced radiologists were able to precisely localize lesions in breasts with higher MD. Further studies in unselected screening materials are needed to verify the results.

Convolutional neural networks for breast cancer detection in mammography: A survey

Despite its proven record as a breast cancer screening tool, mammography remains labor-intensive and has recognized limitations, including low sensitivity in women with dense breast tissue. In the last ten years, Neural Network advances have been applied to mammography to help radiologists increase their efficiency and accuracy. This survey aims to present, in an organized and structured manner, the current knowledge base of convolutional neural networks (CNNs) in mammography. The survey first discusses traditional Computer Assisted Detection (CAD) and more recently developed CNN-based models for computer vision in mammography. It then presents and discusses the literature on available mammography training datasets. The survey then presents and discusses current literature on CNNs for four distinct mammography tasks: (1) breast density classification, (2) breast asymmetry detection and classification, (3) calcification detection and classification, and (4) mass detection and classification, including presenting and comparing the reported quantitative results for each task and the pros and cons of the different CNN-based approaches. Then, it offers real-world applications of CNN CAD algorithms by discussing current Food and Drug Administration (FDA) approved models. Finally, this survey highlights the potential opportunities for future work in this field. The material presented and discussed in this survey could serve as a road map for developing CNN-based solutions to improve mammographic detection of breast cancer further.

Left-right breast asymmetry and risk of screen-detected and interval cancers in a large population-based screening population

OBJECTIVES

To assess the associations between automated volumetric estimates of mammographic asymmetry and breast cancers detected at the same ("contemporaneous") screen, at subsequent screens, or in between (interval cancers).

METHODS

Automated measurements from mammographic images (N = 79,731) were used to estimate absolute asymmetry in breast volume (BV) and dense volume (DV) in a large ethnically diverse population of attendees of a UK breast screening programme. Logistic regression models were fitted to assess asymmetry associations with the odds of a breast cancer detected at contemporaneous screen (767 cases), adjusted for relevant confounders.Nested case-control investigations were designed to examine associations between asymmetry and the odds of: (a) interval cancer (numbers of cases/age-matched controls: 153/646) and (b) subsequent screen-detected cancer (345/1438), via conditional logistic regression.

RESULTS

DV, but not BV, asymmetry was positively associated with the odds of contemporaneous breast cancer (P-for-linear-trend (Pt) = 0.018). This association was stronger for first (prevalent) screens (Pt = 0.012). Both DV and BV asymmetry were positively associated with the odds of an interval cancer diagnosis (Pt = 0.060 and 0.030, respectively). Neither BV nor DV asymmetry were associated with the odds of having a subsequent screen-detected cancer.

CONCLUSIONS

Increased DV asymmetry was associated with the risk of a breast cancer diagnosis at a contemporaneous screen or as an interval cancer. BV asymmetry was positively associated with the risk of an interval cancer diagnosis.

ADVANCES IN KNOWLEDGE

The findings suggest that DV and BV asymmetry may provide additional signals for detecting contemporaneous cancers and assessing the likelihood of interval cancers in population-based screening programmes.

Artificial intelligence for breast cancer detection in mammography and digital breast tomosynthesis: State of the art

Screening for breast cancer with mammography has been introduced in various countries over the last 30 years, initially using analog screen-film-based systems and, over the last 20 years, transitioning to the use of fully digital systems. With the introduction of digitization, the computer interpretation of images has been a subject of intense interest, resulting in the introduction of computer-aided detection (CADe) and diagnosis (CADx) algorithms in the early 2000's. Although they were introduced with high expectations, the potential improvement in the clinical realm failed to materialize, mostly due to the high number of false positive marks per analyzed image. In the last five years, the artificial intelligence (AI) revolution in computing, driven mostly by deep learning and convolutional neural networks, has also pervaded the field of automated breast cancer detection in digital mammography and digital breast tomosynthesis. Research in this area first involved comparison of its capabilities to that of conventional CADe/CADx methods, which quickly demonstrated the potential of this new technology. In the last couple of years, more mature and some commercial products have been developed, and studies of their performance compared to that of experienced breast radiologists are showing that these algorithms are on par with human-performance levels in retrospective data sets. Although additional studies, especially prospective evaluations performed in the real screening environment, are needed, it is becoming clear that AI will have an important role in the future breast cancer screening realm. Exactly how this new player will shape this field remains to be determined, but recent studies are already evaluating different options for implementation of this technology. The aim of this review is to provide an overview of the basic concepts and developments in the field AI for breast cancer detection in digital mammography and digital breast tomosynthesis. The pitfalls of conventional methods, and how these are, for the most part, avoided by this new technology, will be discussed. Importantly, studies that have evaluated the current capabilities of AI and proposals for how these capabilities should be leveraged in the clinical realm will be reviewed, while the questions that need to be answered before this vision becomes a reality are posed.

The Effect of Prior Comparison MRI on Interpretive Performance of Screening Breast MRI

OBJECTIVE

To evaluate the effect of prior comparison MRI on interpretive performance of screening breast MRI.

METHODS

After institutional review board approval, all screening breast MRI examinations performed from January 2011 through December 2014 were retrospectively reviewed. Screening performance metrics were estimated and compared for exams with and without a prior comparison MRI, using logistic regression models to adjust for age and screening indication (BRCA mutation or thoracic radiation versus breast cancer history versus high-risk lesion history versus breast cancer family history).

RESULTS

Most exams, 4509 (87%), had a prior comparison MRI (incidence round), while 661 (13%) did not (prevalence round). Abnormal interpretation rate (6% vs 20%, P < 0.01), biopsy rate (3% vs 9%, P < 0.01), and false-positive biopsy recommendation rate per 1000 exams (21 vs 71, P < 0.01) were significantly lower in the incidence rounds compared to the prevalence rounds, while specificity was significantly higher (95% vs 81%, P < 0.01). There was no difference in cancer detection rate (CDR) per 1000 exams (12 vs 20, P = 0.1), positive predictive value of biopsies performed (PPV3) (35% vs 23%, P = 0.1), or sensitivity (86% vs 76%, P = 0.4).

CONCLUSION

Presence of a prior comparison significantly improves incidence round screening breast MRI examination performance compared with prevalence round screening. Consideration should be given to updating the BI-RADS breast MRI screening benchmarks and auditing prevalence and incidence round examinations separately.

Risk-Based Screening Mammography for Women Aged <40: Outcomes From the National Mammography Database

OBJECTIVE

There is insufficient large-scale evidence for screening mammography in women <40 years at elevated risk. This study compares risk-based screening of women aged 30 to 39 with risk factors versus women aged 40 to 49 without risk factors in the National Mammography Database (NMD).

METHODS

This retrospective, HIPAA-compliant, institutional review board-exempt study analyzed data from 150 NMD mammography facilities in 31 states. Patients were stratified by 5-year age intervals, availability of prior mammograms, and specific risk factors for breast cancer: family history of breast cancer, personal history of breast cancer, and dense breasts. Four screening performance metrics were calculated for each age and risk group: recall rate (RR), cancer detection rate (CDR), and positive predictive values for biopsy recommended (PPV₂) and biopsy performed (PPV₃).

RESULTS

Data from 5,986,131 screening mammograms performed between January 2008 and December 2015 in 2,647,315 women were evaluated. Overall, mean CDR was 3.69 of 1,000 (95% confidence interval: 3.64-3.74), RR was 9.89% (9.87%-9.92%), PPV₂ was 20.1% (19.9%-20.4%), and PPV₃ was 28.2% (27.0%-28.5%). Women aged 30 to 34 and 35 to 39 had similar CDR, RR, and PPVs, with the presence of the three evaluated risk factors associated with significantly higher CDR. Moreover, compared with a population currently recommended for screening mammography in the United States (aged 40-49 at average risk), incidence screening (at least one prior screening examination) of women aged 30 to 39 with the three evaluated risk factors has similar cancer detection rates and recall rates.

DISCUSSION

Women with one or more of these three specific risk factors likely benefit from screening commencing at age 30 instead of age 40.

Specialized Second Opinion Review of Breast MRI Impacts Management and Increases Cancer Detection

OBJECTIVE

The aim of our study is to determine MRI review discrepancy frequency and the subsequent impact on patient management for patients pursuing breast imaging second opinions.

METHODS

A retrospective chart review was conducted on 1,000 consecutive patients with second opinion radiology interpretations performed by subspecialty-trained breast radiologists at a dedicated cancer center July 1 through December 31, 2016. Of these, 205 included review of outside breast MRI. Outside imaging reports were compared with second opinion reports to categorize breast MRI review discrepancies. These included relevant BI-RADS category changes or identification of additional extent of disease >4 cm. The discrepancy frequency, relevant alterations in patient management, and incremental cancer detection were measured. Statistical analyses were performed using Fisher's exact test.

RESULTS

Discrepant second opinion breast MRI review was seen in 36 of 205 patients (18%). Additional cancer was detected through image-guided biopsy in 3 of these 36 patients and through excision in 2 (5 of 205, 2%). Additionally, five biopsies yielded high-risk pathologic results without upstage on excision. Findings suspicious for additional extent of disease >4 cm were noted in five patients (2%) treated with mastectomies. Finally, five patients had BI-RADS category downgrades. Ultimately, completion of second opinion MRI review recommendations resulted in altered management in 10% of patients (20 of 205). The absence of prior imaging studies for comparison was associated with increased discrepancy frequency (P = .005).

CONCLUSION

Second opinion breast MRI review by subspecialized breast imaging radiologists increases cancer detection and results in clinically relevant changes in patient management.

Baseline Mammography: What Is It and Why Is It Important? A Cross-Sectional Survey of Women Undergoing Screening Mammography

OBJECTIVES

Studies have shown that having a baseline mammogram, the first screening mammogram, available for comparison at the time of interpreting a subsequent mammogram significantly decreases the potential of a false-positive examination. Our aim was to evaluate knowledge of and perception about the significance of baseline mammograms in those women undergoing screening mammography.

MATERIALS AND METHODS

A cross-sectional prospective survey study was conducted in women without a history of breast cancer presenting for their screening mammogram. Respondents were surveyed anonymously between March and April 2017. The questionnaire was developed by primary care providers and radiologists and pretested for readability and clarity.

RESULTS

In all, 401 women (87% white, 93% educated beyond high school) completed surveys in which 77% of women reported having yearly mammograms, 31% reported having a history of an abnormal mammogram, and 45% had not heard the term baseline mammogram. Of those who had heard the term, the most commonly reported source was their primary care provider (31%). Although 74% chose the correct definition of a baseline mammogram, 67% did not think that a baseline mammogram was important for decreasing associated cost, time, and discomfort due to the number of mammograms incorrectly read as abnormal.

CONCLUSION

In a group of educated women who routinely get mammograms, almost one-half had not heard the term baseline mammogram. Furthermore, most women did not think baseline mammography was important for decreasing associated cost, time, and discomfort due to mammograms incorrectly read as abnormal. This study suggests that efforts to improve women's understanding of baseline mammograms and their importance are warranted, with greatest opportunity for health care providers and radiologists.

Availability of prior mammograms affects incomplete report rates in mobile screening mammography

PURPOSE

Mobile mammography can improve access to screening mammography in rural areas and underserved populations. We evaluated the frequency of incomplete reports in mobile mammography screening and the relationships between prior mammograms and recall rates.

METHODS

The frequency of incomplete mammogram reports, the subgroups of those needing prior comparison mammograms, recalls for additional imaging, and availability of prior mammograms of a mobile screening mammography unit were compared with fixed site mammography from January 1, 2007 through December 31, 2009. All mobile unit mammograms were full field digital mammography (FFDM). Differences between rates of recall, incomplete reports, and availability of prior mammograms were calculated using the Chi-Square statistic.

RESULTS

Of 2640 mobile mammography cases, 21.9% (578) reports were incomplete, versus 15.2% (7653) (p ≤ 0.001) of 50325 fixed site reports. Of incomplete cases, recall for additional imaging occurred among 8.3% (218) of mobile mammography reports versus 11.3% (5708) (p ≤ 0.001) of fixed site reports. Prior mammograms were needed among 13.6% (360) of mobile mammography versus 3.9% (1945) (p ≤ 0.001) of fixed site reports. Mobile mammography recall rate varied with availability of prior mammograms: 16.0% (54) when no prior mammograms, 7.6% (127) when prior mammograms were elsewhere but unavailable and 5.9% (37) when prior FFDM were immediately available (p ≤ 0.001).

CONCLUSIONS

Incomplete reports were more frequent in mobile mammography than the fixed site. The availability of prior comparison mammograms at time of interpretation decreased the rate of incomplete mammogram reports. Recall rates were higher without prior comparison mammograms and lowest when comparison FFDM mammograms were available.

Classifying symmetrical differences and temporal change for the detection of malignant masses in mammography using deep neural networks

We investigate the addition of symmetry and temporal context information to a deep convolutional neural network (CNN) with the purpose of detecting malignant soft tissue lesions in mammography. We employ a simple linear mapping that takes the location of a mass candidate and maps it to either the contralateral or prior mammogram, and regions of interest (ROIs) are extracted around each location. Two different architectures are subsequently explored: (1) a fusion model employing two datastreams where both ROIs are fed to the network during training and testing and (2) a stagewise approach where a single ROI CNN is trained on the primary image and subsequently used as a feature extractor for both primary and contralateral or prior ROIs. A "shallow" gradient boosted tree classifier is then trained on the concatenation of these features and used to classify the joint representation. The baseline yielded an AUC of 0.87 with confidence interval [0.853, 0.893]. For the analysis of symmetrical differences, the first architecture where both primary and contralateral patches are presented during training obtained an AUC of 0.895 with confidence interval [0.877, 0.913], and the second architecture where a new classifier is retrained on the concatenation an AUC of 0.88 with confidence interval [0.859, 0.9]. We found a significant difference between the first architecture and the baseline at high specificity with [Formula: see text]. When using the same architectures to analyze temporal change, we yielded an AUC of 0.884 with confidence interval [0.865, 0.902] for the first architecture and an AUC of 0.879 with confidence interval [0.858, 0.898] in the second setting. Although improvements for temporal analysis were consistent, they were not found to be significant. The results show our proposed method is promising and we suspect performance can greatly be improved when more temporal data become available.

Analysis of Participant Factors That Affect the Diagnostic Performance of Screening Mammography: A Report of the Alliance for Breast Cancer Screening in Korea

OBJECTIVE

To analyze participant factors that affect the diagnostic performance of screening mammography.

MATERIALS AND METHODS

We enrolled 128756 cases from 10 hospitals between 2005 and 2010. We analyzed recall rate, cancer detection rate (CDR) per 1000 examinations, positive predictive value (PPV), sensitivity, specificity, false positive rate (FPR), and interval cancer rate (ICR) per 1000 negative examinations according to participant factors including age, breast density, and number of visit to the same institution, and adjusted for confounding variables.

RESULTS

Increasing age improved recall rates (27.4% in 40's, 17.5% in 50's, 11.1% in 60's, and 8.6% in 70's), CDR (2.7, 3.2, 2.0, and 2.4), PPV (1.0, 1.8, 1.8, and 2.8%), sensitivity (81.3, 88.8, 90.3, and 94.7%), specificity (72.7, 82.7, 89.0, and 91.7%), and FPR (27.3, 17.3, 11.0, and 8.4%) (p < 0.05). Higher breast density impaired recall rates (4.0% in P1, 9.0% in P2, 28.9% in P3, and 27.8% in P4), PPV (3.3, 2.3, 1.2, and 1.3%), specificity (96.1, 91.2, 71.4, and 72.5%), and FPR (3.9, 8.9, 28.6, and 27.6%) (p < 0.001). It also increased CDR (1.3, 2.1, 3.3, and 3.6) and ICR (0.2, 0.3, 0.6, and 1.6) (p < 0.05). Successive visits to the same institution improved recall rates (20.9% for one visit, 10.7% for two visits, 7.7% for more than three visits), PPV (1.6, 2.8, and 2.7%), specificity (79.4, 89.6, and 92.5%), and FPR (20.6, 10.4, and 7.5%) (p < 0.001).

CONCLUSION

Young age and dense breasts negatively affected diagnostic performance in mammography screening, whereas successive visits to the same institution had a positive effect. Examinee education for successive visits to the same institution would improve the diagnostic performance.

Image Sharing in Radiology-A Primer

By virtue of its information technology-oriented infrastructure, the specialty of radiology is uniquely positioned to be at the forefront of efforts to promote data sharing across the healthcare enterprise, including particularly image sharing. The potential benefits of image sharing for clinical, research, and educational applications in radiology are immense. In this work, our group-the Association of University Radiologists (AUR) Radiology Research Alliance Task Force on Image Sharing-reviews the benefits of implementing image sharing capability, introduces current image sharing platforms and details their unique requirements, and presents emerging platforms that may see greater adoption in the future. By understanding this complex ecosystem of image sharing solutions, radiologists can become important advocates for the successful implementation of these powerful image sharing resources.

Impact of prior mammograms on combined reading of digital mammography and digital breast tomosynthesis

Background Although digital breast tomosynthesis (DBT) is an emerging technique yielding higher sensitivity and specificity compared to digital mammography (DM) alone, relative contribution of prior mammograms on the interpretation of DBT combined with DM has not been investigated. Purpose To retrospectively compare the diagnostic performances of DM, DM + DBT, and DM + DBT with prior mammograms. Material and Methods Three breast radiologists independently reviewed images of 116 patients with 24 cancers in the sequential order of DM, DM + DBT, and DM + DBT with prior mammograms using Breast Imaging Reporting and Data System (BI-RADS) assessment categories. Results The average areas under the receiver operating characteristic curve (AUC) of DM, DM + DBT, and DM + DBT with prior mammograms were 0.712, 0.777, and 0.816, respectively. Adding prior mammograms did not significantly affect the AUC of DM + DBT ( P = 0.108), whereas adding DBT significantly increased the AUC of DM ( P = 0.009). Sensitivity for DM, DM + DBT, and DM + DBT with prior mammograms was 58.3%, 69.4%, and 69.4%, and specificities were 84.1%, 85.9%, and 93.8%, respectively. Addition of DBT significantly increased the sensitivity ( P = 0.0090) of DM. Prior mammograms significantly improved the specificity of DM + DBT ( P = 0.0004), whereas adding prior mammogram did not affect sensitivity of DM + DBT ( P = 1.000). Conclusion DBT significantly increases the overall sensitivity and diagnostic performance of DM. Prior mammograms significantly increase the specificity of DM + DBT but have no significant effect on sensitivity and overall diagnostic performance.

Synchronized navigation of current and prior studies using image registration improves radiologist's efficiency

PURPOSE

The purpose of this study was to investigate how the use of multi-modal rigid image registration integrated within a standard picture archiving and communication system affects the efficiency of a radiologist while performing routine interpretations of cases including prior examinations.

METHODS

Six radiologists were recruited to read a set of cases (either 16 neuroradiology or 14 musculoskeletal cases) during two crossover reading sessions. Each radiologist read each case twice, one time with synchronized navigation, which enables spatial synchronization across examinations from different study dates, and one time without. Efficiency was evaluated based upon time to read a case and amount of scrolling while browsing a case using Wilcoxon signed rank test.

RESULTS

Significant improvements in efficiency were found considering either all radiologists simultaneously, the two sections separately and the majority of individual radiologists for time to read and for amount of scrolling. The relative improvement for each individual radiologist ranged from 4 to 32% for time to read and from 14 to 38% for amount of scrolling.

CONCLUSION

Image registration providing synchronized navigation across examinations from different study dates provides a tool that enables radiologists to work more efficiently while reading cases with one or more prior examinations.

The Economic and Social Value of an Image Exchange Network: A Case for the Cloud

As the health care environment continually changes, radiologists look to the ACR's Imaging 3.0^® initiative to guide the search for value. By leveraging new technology, a cloud-based image exchange network could provide secure universal access to prior images, which were previously siloed, to facilitate accurate interpretation, improved outcomes, and reduced costs. The breast imaging department represents a viable starting point given the robust data supporting the benefit of access to prior imaging studies, existing infrastructure for image sharing, and the current workflow reliance on prior images. This concept is scalable not only to the remainder of the radiology department but also to the broader medical record.

Cost-Effectiveness of Double Reading versus Single Reading of Mammograms in a Breast Cancer Screening Programme

OBJECTIVES

The usual practice in breast cancer screening programmes for mammogram interpretation is to perform double reading. However, little is known about its cost-effectiveness in the context of digital mammography. Our purpose was to evaluate the cost-effectiveness of double reading versus single reading of digital mammograms in a population-based breast cancer screening programme.

METHODS

Data from 28,636 screened women was used to establish a decision-tree model and to compare three strategies: 1) double reading; 2) double reading for women in their first participation and single reading for women in their subsequent participations; and 3) single reading. We calculated the incremental cost-effectiveness ratio (ICER), which was defined as the expected cost per one additionally detected cancer. We performed a deterministic sensitivity analysis to test the robustness of the ICER.

RESULTS

The detection rate of double reading (5.17‰) was similar to that of single reading (4.78‰; P = .768). The mean cost of each detected cancer was €8,912 for double reading and €8,287 for single reading. The ICER of double reading versus single reading was €16,684. The sensitivity analysis showed variations in the ICER according to the sensitivity of reading strategies. The strategy that combines double reading in first participation with single reading in subsequent participations was ruled out due to extended dominance.

CONCLUSIONS

From our results, double reading appears not to be a cost-effective strategy in the context of digital mammography. Double reading would eventually be challenged in screening programmes, as single reading might entail important net savings without significantly changing the cancer detection rate. These results are not conclusive and should be confirmed in prospective studies that investigate long-term outcomes like quality adjusted life years (QALYs).

Improving Screening Mammography Outcomes Through Comparison With Multiple Prior Mammograms

OBJECTIVE

The objective of the present study is to evaluate the effect of comparison with multiple prior mammograms on the outcomes of screening mammography relative to comparison with a single prior mammogram.

MATERIALS AND METHODS

We retrospectively analyzed 46,288 consecutive screening mammograms performed at our institution for 22,792 women. We divided these examinations into three groups: those interpreted without comparison with prior mammograms, those interpreted in comparison with one prior examination, and those interpreted in comparison with two or more prior examinations. For each group, we determined the rate of examination recall. We also calculated the positive predictive value of recall (i.e., positive predictive value level 1 [PPV1]) and the cancer detection rate (CDR) for both the group of examinations compared with a single prior mammogram and the group compared with multiple prior mammograms. Generalized estimating equations with the logistic link function were used to determine the relative odds ratio of recall as a function of the number of comparisons, with adjustment made for age as a confounding variable. The Fisher exact test was performed to compare the PPV1 and the CDR in the different cohorts.

RESULTS

The recall rate for mammograms interpreted without comparison with prior examinations was 16.6%, whereas that for mammograms compared with one prior examination was 7.8% and that for mammograms compared with two or more prior examinations was 6.3%. After adjustment was made for age, the odds ratio of recall for the group with multiple prior examinations relative to the group with a single prior examination was 0.864 (95% CI, 0.776-0.962; p = 0.0074). Statistically significant increases in the PPV1 of 0.05 (p = 0.0009) and in the CDR of 2.3 cases per 1000 examinations (p = 0.0481) were also noted for mammograms compared with multiple prior examinations relative to those compared with a single prior examination.

CONCLUSION

Comparison with two or more prior mammograms resulted in a statistically significant reduction in the screening mammography recall rate and increases in the CDR and PPV1 relative to comparison with a single prior mammogram.

Consequences Validity Evidence: Evaluating the Impact of Educational Assessments

Because tests that do not alter management (i.e., influence decisions and actions) should not be performed, data on the consequences of assessment constitute a critical source of validity evidence. Consequences validity evidence is challenging for many educators to understand, perhaps because it has no counterpart in the older framework of content, criterion, and construct validity. The authors' purpose is to explain consequences validity evidence and propose a framework for organizing its collection and interpretation.Both clinical and educational assessments can be viewed as interventions. The act of administering or taking a test, the interpretation of scores, and the ensuing decisions and actions influence those being assessed (e.g., patients or students) and other people and systems (e.g., physicians, teachers, hospitals, schools). Consequences validity evidence examines such impacts of assessments. Despite its importance, consequences evidence is reported infrequently in health professions education (range 5%-20% of studies in recent systematic reviews) and is typically limited in scope and rigor.Consequences validity evidence can derive from evaluations of the impact on examinees, educators, schools, or the end target of practice (e.g., patients or health care systems); and the downstream impact of classifications (e.g., different score cut points and labels). Impact can result from the uses of scores or from the assessment activity itself, and can be intended or unintended and beneficial or harmful. Both quantitative and qualitative research methods are useful. The type, quantity, and rigor of consequences evidence required will vary depending on the assessment and the claims for its use.

Missed Breast Cancer: What Can We Learn?

Multiple studies have shown that screening mammography helps to reduce mortality and morbidity from advanced breast cancer. However mammography does have its own limitations, and unfortunately, there are a fair number of false-negative mammograms. We are all aware that the sensitivity of mammography is inversely proportional to the breast density. With many states passing mandatory breast density reporting legislation, there has been an emphasis on using additional and alternative screening methods such as whole breast ultrasound and screening magnetic resonance imaging. Many cancers are simply not detected on mammography, even in retrospect. However, many of the breast cancers are actually visible retrospectively on the prior mammogram. It is these small and often subtle cancers that are perceptible but often missed, that provide a valuable learning opportunity. Studying the imaging findings of cancers that went undetected is a good learning exercise for the radiologist to identify common patterns and mistakes that lead to a missed cancer. This allows the radiologist to improve mammographic sensitivity and overall diagnostic accuracy. This article discusses some of the limitations of mammography, common sources of error which may lead to an undetected cancer, and also discuss a few pearls to prevent these common errors.

False positives in breast cancer screening with one-view breast tomosynthesis: An analysis of findings leading to recall, work-up and biopsy rates in the Malmö Breast Tomosynthesis Screening Trial

Objectives

To analyse false positives (FPs) in breast cancer screening with tomosynthesis (BT) vs. mammography (DM).

Methods

The Malmö Breast Tomosynthesis Screening Trial (MBTST) is a prospective population-based study comparing one-view BT to DM in screening. This study is based on the first half of the MBTST population (n = 7,500). Differences in FP recall rate, findings leading to recall, work-up and biopsy rate between cases recalled on BT alone, DM alone and BT+DM were analysed.

Results

The FP recall rate was 1.7 % for BT alone (n = 131), 0.9 % for DM alone (n = 69) and 1.1 % for BT + DM (n = 81). The FP recall rate for BT alone was halved after the initial phase of the trial, stabilising at 1.5 %. BT doubled the recall of stellate distortions compared to DM (n = 64 vs. n = 33). There were fewer fibroadenomas and cysts, and the biopsy rate was slightly lower for FP recalled on BT alone compared to DM alone (15.3 % vs. 27.6 %: p = 0.037 and 33.8 % vs. 36.2 %; p = 0.641, respectively).

Conclusions

FPs increased with BT screening mainly due to the recall of stellate distortions. The FP recall rate was still well within the European guidelines and showed evidence of a learning curve. Characterisation of rounded lesions was improved with BT.

Key Points

• Tomosynthesis screening gave a higher false-positive recall rate than mammography

• There was a decline in the false-positive recall rate for tomosynthesis

• The recall due to stellate distortions simulating malignancy was doubled with tomosynthesis

• Tomosynthesis found more radial and postoperative scar tissue than mammography

• Tomosynthesis is better at characterising rounded lesions

Breast cancer screening in England and the United States: a comparison of provision and utilisation

OBJECTIVES

Comparing breast cancer screening across countries within the context of some of the benefits and harms offers the opportunity to improve effectiveness through mutual learning.

METHODS

This paper describes the provision of breast cancer screening in England and the United States. The various recommendations for accessing breast cancer screening in the two countries are set out and the organisation of services including quality assurance, incentives and performance mechanisms considered.

RESULTS

In the United States, younger women are routinely screened; they are less likely to benefit and more likely to be harmed. The utilisation of breast cancer screening amongst eligible women is broadly comparable in the two countries. However, there are differences in technical performance; the reasons for these including radiological reading procedures and cultural factors are explored.

CONCLUSIONS

Despite a well-functioning screening programme, breast cancer mortality and survival in England are poor relative to other countries. Emphasis for American improvement should be on reducing false-positive recall rates, while the English NHS could supplement existing efforts to understand and improve comparatively poor survival and mortality.

Racial differences in false-positive mammogram rates: results from the ACRIN Digital Mammographic Imaging Screening Trial (DMIST)

BACKGROUND

Mammography screening reduces breast cancer mortality, but false-positive tests are common. Few studies have assessed racial differences in false-positive rates.

OBJECTIVES

We compared false-positive mammography rates for black and white women, and the effect of patient and facility characteristics on false positives.

RESEARCH DESIGN AND SUBJECTS

A prospective cohort study. From a sample of the American College of Radiology Imaging Network (ACRIN) Digital Mammographic Imaging Screening Trial (DMIST), we identified black/African American (N=3176) or white (N=26,446) women with no prior breast surgery or breast cancer.

MEASURES

Race, demographics, and breast cancer risk factors were self-reported. Results of initial digital and film mammograms were assessed. False positives were defined as a positive mammogram (Breast Imaging Reporting and Data System category 0, 4, 5) with no cancer diagnosis within 15 months.

RESULTS

The false-positive rate for digital mammograms was 9.2% for black women compared with 7.8% for white women (P=0.009). After adjusting for age, black women had 17% increased odds of false-positive digital mammogram compared with whites (OR=1.17; 95% CI, 1.01-1.35; P=0.033). This association was attenuated after adjusting for patient factors, prior films, and study site (OR=1.04; 95% CI, 0.91-1.20; P=0.561). There was no difference in the occurrence of false positives by race for film mammography.

CONCLUSIONS

Black women had higher frequency of false-positive digital mammograms explained by lack of prior films and study site.The variation in the disparity between the established technique (film) and the new technology (digital) raises the possibility that racial differences in screening quality may be greatest for new technologies.

Effect of the Availability of Prior Full-Field Digital Mammography and Digital Breast Tomosynthesis Images on the Interpretation of Mammograms

PURPOSE

To assess the effect of and interaction between the availability of prior images and digital breast tomosynthesis (DBT) images in decisions to recall women during mammogram interpretation.

MATERIALS AND METHODS

Verbal informed consent was obtained for this HIPAA-compliant institutional review board-approved protocol. Eight radiologists independently interpreted twice deidentified mammograms obtained in 153 women (age range, 37-83 years; mean age, 53.7 years ± 9.3 [standard deviation]) in a mode by reader by case-balanced fully crossed study. Each study consisted of current and prior full-field digital mammography (FFDM) images and DBT images that were acquired in our facility between June 2009 and January 2013. For one reading, sequential ratings were provided by using (a) current FFDM images only, (b) current FFDM and DBT images, and (c) current FFDM, DBT, and prior FFDM images. The other reading consisted of (a) current FFDM images only, (b) current and prior FFDM images, and (c) current FFDM, prior FFDM, and DBT images. Fifty verified cancer cases, 60 negative and benign cases (clinically not recalled), and 43 benign cases (clinically recalled) were included. Recall recommendations and interaction between the effect of prior FFDM and DBT images were assessed by using a generalized linear model accounting for case and reader variability.

RESULTS

Average recall rates in noncancer cases were significantly reduced with the addition of prior FFDM images by 34% (145 of 421) and 32% (106 of 333) without and with DBT images, respectively (P < .001). However, this recall reduction was achieved at the cost of a corresponding 7% (23 of 345) and 4% (14 of 353) reduction in sensitivity (P = .006). In contrast, availability of DBT images resulted in a smaller reduction in recall rates (false-positive interpretations) of 19% (76 of 409) and 26% (71 of 276) without and with prior FFDM images, respectively (P = .001). Availability of DBT images resulted in 4% (15 of 338) and 8% (25 of 322) increases in sensitivity, respectively (P = .007). The effects of the availability of prior FFDM images or DBT images did not significantly change regardless of the sequence in presentation (P = .81 and P = .47 for specificity and sensitivity, respectively).

CONCLUSION

The availability of prior FFDM or DBT images is a largely independent contributing factor in reducing recall recommendations during mammographic interpretation.

Impact of and interaction between the availability of prior examinations and DBT on the interpretation of negative and benign mammograms

RATIONALE AND OBJECTIVES

To assess the interaction between the availability of prior examinations and digital breast tomosynthesis (DBT) in decisions to recall a woman during interpretation of mammograms.

MATERIALS AND METHODS

Eight radiologists independently interpreted twice 36 mammography examinations, each of which had current and prior full-field digital mammography images (FFDM) and DBT under a Health Insurance Portability and Accountability Act-compliant, institutional review board-approved protocol (written consent waived). During the first reading, three sequential ratings were provided using FFDM only, followed by FFDM + DBT, and then followed by FFDM + DBT + priors. The second reading included FFDM only, then FFDM + priors, and then FFDM + priors + DBT. Twenty-two benign cases clinically recalled, 12 negative/benign examinations (not recalled), and two verified cancer cases were included. Recall recommendations and interaction between the effect of priors and DBT on decisions were assessed (P = .05 significance level) using generalized linear model (PROC GLIMMIX, SAS, version 9.3; SAS Institute, Cary, NC) accounting for case and reader variability.

RESULTS

Average recall rates in noncancer cases were significantly reduced (51%; P < .001) with the addition of DBT and with addition of priors (23%; P = .01). In absolute terms, the addition of DBT to FFDM reduced the recall rates from 0.67 to 0.42 and from 0.54 to 0.27 when DBT was available before and after priors, respectively. Recall reductions were from 0.64 to 0.54 and from 0.42 to 0.33 when priors were available before and after DBT, respectively. Regardless of the sequence in presentation, there were no statistically significant interactions between the effect of availability of DBT and priors (P = .80).

CONCLUSIONS

Availability of both priors and DBT are independent primary factors in reducing recall recommendations during mammographic interpretations.

Mammography test sets: reading location and prior images do not affect group performance

AIM

To examine how the location where reading takes place and the availability of prior images can affect performance in breast test-set reading.

MATERIALS AND METHODS

Under optimized viewing conditions, 10 expert screen readers each interpreted a reader-specific set of images containing 200 mammographic cases. Readers, randomly divided into two groups read images under one of two pairs of conditions: clinical read with prior images and laboratory read with prior images; laboratory read with prior images and laboratory read without prior images. Region-of-interest (ROI) figure-of-merit (FOM) was analysed using JAFROC software. Breast side-specific sensitivity and specificity were tested using Wilcoxon matched-pairs signed rank tests. Agreement between pairs of readings was measured using Kendall's coefficient of concordance.

RESULTS

Group performances between test-set readings demonstrated similar ROI FOMs, sensitivity and specificity median values, and acceptable levels of agreement between pairs of readings were shown (W = 0.75-0.79, p < 0.001) for both pairs of reading conditions. On an individual reader level, two readers demonstrated significant decreases (p < 0.05) in ROI FOMs when prior images were unavailable. Reading location had an inconsistent impact on individual performance.

CONCLUSION

Reading location and availability of prior images did not significantly alter group performance.

Benefit of semiannual ipsilateral mammographic surveillance following breast conservation therapy

PURPOSE

To compare cancer recurrence outcomes on the basis of compliant semiannual versus noncompliant annual ipsilateral mammographic surveillance following breast conservation therapy (BCT).

MATERIALS AND METHODS

A HIPAA-compliant retrospective review was performed of post-BCT examinations from 1997 through 2008 by using a deidentified database. The Committee on Human Research did not require institutional review board approval for this study, which was considered quality assurance. Groups were classified according to compliance with institutional post-BCT protocol, which recommends semiannual mammographic examinations of the ipsilateral breast for 5 years. A compliant semiannual examination was defined as an examination with an interval of 0-9 months, although no examination had intervals less than 3 months. A noncompliant annual examination was defined as an examination with an interval of 9-18 months. Cancer recurrence outcomes were compared on the basis of the last examination interval leading to diagnosis.

RESULTS

Initially, a total of 10 750 post-BCT examinations among 2329 asymptomatic patients were identified. Excluding initial mammographic follow-up, there were 8234 examinations. Of these, 7169 examinations were semiannual with 94 recurrences detected and 1065 examinations were annual with 15 recurrences detected. There were no differences in demographic risk factors or biopsy rates. Recurrences identified at semiannual intervals were significantly less advanced than those identified at annual intervals (stage I vs stage II, P = .04; stage 0 + stage I vs stage II, P = .03). Nonsignificant findings associated with semiannual versus annual intervals included smaller tumor size (mean, 11.7 vs 15.3 mm; P = .15) and node negativity (98% vs 91%, P = .28).

CONCLUSION

Results suggest that a semiannual interval is preferable for ipsilateral mammographic surveillance, allowing detection of a significantly higher proportion of cancer recurrences at an earlier stage than noncompliant annual surveillance.

Increase in perceived case suspiciousness due to local contrast optimisation in digital screening mammography

Objectives

To determine the influence of local contrast optimisation on diagnostic accuracy and perceived suspiciousness of digital screening mammograms.

Methods

Data were collected from a screening region in the Netherlands and consisted of 263 digital screening cases (153 recalled,110 normal). Each case was available twice, once processed with a tissue equalisation (TE) algorithm and once with local contrast optimisation (PV). All cases had digitised previous mammograms. For both algorithms, the probability of malignancy of each finding was scored independently by six screening radiologists. Perceived case suspiciousness was defined as the highest probability of malignancy of all findings of a radiologist within a case. Differences in diagnostic accuracy of the processing algorithms were analysed by comparing the areas under the receiver operating characteristic curves (A_z). Differences in perceived case suspiciousness were analysed using sign tests.

Results

There was no significant difference in A_z (TE: 0.909, PV 0.917, P = 0.46). For all radiologists, perceived case suspiciousness using PV was higher than using TE more often than vice versa (ratio: 1.14–2.12). This was significant (P <0.0083) for four radiologists.

Conclusions

Optimisation of local contrast by image processing may increase perceived case suspiciousness, while diagnostic accuracy may remain similar.

Key Points

• Variations among different image processing algorithms for digital screening mammography are large.

• Current algorithms still aim for optimal local contrast with a low dynamic range.

• Although optimisation of contrast may increase sensitivity, diagnostic accuracy is probably unchanged.

• Increased local contrast may render both normal and abnormal structures more conspicuous.

Effect of observing change from comparison mammograms on performance of screening mammography in a large community-based population

PURPOSE

To evaluate the effect of comparison mammograms on accuracy, sensitivity, specificity, positive predictive value (PPV(1)), and cancer detection rate (CDR) of screening mammography to determine the role played by identification of change on comparison mammograms.

MATERIALS AND METHODS

This HIPAA-compliant and institutional review board-approved prospective study was performed with waiver of patient informed consent. A total of 1,157,980 screening mammograms obtained between 1994 and 2008 in 435,183 women aged at least 40 years were included. Radiologists recorded presence of comparison mammograms and change, if seen. Women were followed for 1 year to monitor cancer occurrence. Performance measurements were calculated for screening with comparison mammograms versus screening without comparison mammograms and for screening with comparison mammograms that showed a change versus screening with comparison mammograms that did not show a change while controlling for age, breast density, and data clustering.

RESULTS

Comparison mammograms were available in 93% of examinations. For screening with comparison mammograms versus screening without comparison mammograms, CDR per 1000 women was 3.7 versus 7.1; recall rate, 6.9% versus 14.9%; sensitivity, 78.9% versus 87.4%; specificity, 93.5% versus 85.7%; and PPV(1), 5.4% versus 4.8%. For screening with comparison mammograms that showed a change versus screening with comparison mammograms that did not show a change, CDR per 1000 women was 25.4 versus 0.8; recall rate, 41.4% versus 2.0%; sensitivity, 96.6% versus 43.5%; specificity, 60.4% versus 98.1%; and PPV(1), 6.0% versus 3.9%. Detected cancers with change were 21.1% ductal carcinoma in situ and 78.9% invasive carcinoma. Detected cancers with no change were 19.3% ductal carcinoma in situ and 80.7% invasive carcinoma.

CONCLUSION

Performance is affected when change from comparison mammograms is noted. Without change, sensitivity is low and specificity is high. With change, sensitivity is high, with a high false-positive rate (low specificity). Further work is needed to appreciate changes that might indicate cancer and to identify changes that are likely not indicative of cancer.

Use of prior mammograms in the transition to digital mammography: a performance and cost analysis

Breast screening in Europe is gradually changing from film to digital imaging and reporting of cases. In the transition period prior mammograms (from the preceding screening round) are films thereby potentially causing difficulties in comparison to current digital mammograms. To examine this breast screening performance was measured at a digital mammography workstation with prior mammograms displayed in different formats, and the associated costs calculated. 160 selected difficult cases (41% malignant) were read by eight UK qualified mammography readers in three conditions: with film prior mammograms; with digitised prior mammograms; or without prior mammograms. Lesion location and probability of malignancy were recorded, alongside a decision of whether to recall each case for further tests. JAFROC analysis showed a difference between conditions (p=.006); performance with prior mammograms in either film or digitised formats was superior to that without prior mammograms (p<.05). There was no difference in the performance when the prior mammograms were presented in film or digitised form. The number of benign or normal cases recalled was 26% higher without prior mammograms than with digitised or film prior mammograms (p<.05). This would correspond to an increase in recall rate at the study hospital from 4.3% to 5.5% with no associated increase in cancer detection rate. The cost of this increase was estimated to be £11,581 (€13,666) per 10,000 women screened, which is higher than the cost of digitised (£11,114/€13,115), or film display (£6451/€7612) of the prior mammograms. It is recommended that, where available, prior mammograms are used in the transition to digital breast screening.

Consequences of digital mammography in population-based breast cancer screening: initial changes and long-term impact on referral rates

Objectives:

To investigate the referral pattern after the transition to full-field digital mammography (FFDM) in a population-based breast cancer screening programme.

Methods:

Preceding the nationwide digitalisation of the Dutch screening programme, an FFDM feasibility study was conducted. Detection and referral rates for FFDM and screen-film mammography (SFM) were compared for first and subsequent screens. Furthermore, radiological characteristics of referrals in digital screening were assessed.

Results:

A total of 312,414 screening mammograms were performed (43,913 digital and 268,501 conventional), with 4,473 consecutive referrals (966 following FFDM). Initially the FFDM referral rate peaked, and many false-positive results were noted as a consequence of pseudolesions and increased detection of (benign) microcalcifications. A higher overall referral rate was observed in FFDM screening in both first and subsequent examinations (p < .001), with a significant increase in cancer detection (p = .010).

Conclusion:

As a result of initial inexperience with digital screening images implementing FFDM in a population-based breast cancer screening programme may lead to a strong, but temporary increase in referral. Dedicated training in digital screening for radiographers and screening radiologists is therefore recommended. Referral rates decrease and stabilise (learning curve effect) at a higher level than in conventional screening, yet with significantly enhanced cancer detection.