Patient and Radiologist Characteristics Associated With Accuracy of Two Types of Diagnostic Mammograms

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.

Do Reader Characteristics Affect Diagnostic Efficacy in Screening Mammography? A Systematic Review

To examine reader characteristics associated with diagnostic efficacy in the interpretation of screening mammograms. A systematic search of the literature was conducted using databases such as Cochrane, Scopus, Medline, Embase, Web of Science, and PubMed. Search terms were combined with "AND" or "OR" and included: "Radiologist's characteristics AND performance"; "radiologist experience AND screening mammography"; "annual volume read AND diagnostic efficacy"; "screening mammography performance OR diagnostic efficacy". Studies were included if they assessed reader performance in screening mammography interpretation, breast readers, used a reference standard to assess the performance, and were published in the English language. Twenty-eight studies were reviewed. Increasing reader's age was associated with lower false positive rates. No association was found between gender and performance. Half of the studies showed no association between years of reading mammograms and performance. Most studies showed that high reading volume was more likely to be associated with increased sensitivity, cancer detection rates (CDR), lower recall rate, and lower false positive rates. Inconsistent associations were found between fellowship training in breast imaging and reader performance. Specialization in breast imaging was associated with better CDR, sensitivity, and specificity. Limited studies were available to establish the association between performance and factors such as time spent in breast imaging (n = 2), screening focus (n = 1), formal rotation in mammography (n = 1), owner of practice (n = 1), and practice type (n = 1). No individual characteristics is associated with versatility in diagnostic efficacy, albeit reading volume and specialization in breast imaging appear to be associated with with increased sensitivity and CDR without significantly affecting other performance metrics.

A machine learning model based on readers' characteristics to predict their performances in reading screening mammograms

OBJECTIVES

Proposing a machine learning model to predict readers' performances, as measured by the area under the receiver operating characteristics curve (AUC) and lesion sensitivity, using the readers' characteristics.

METHODS

Data were collected from 905 radiologists and breast physicians who completed at least one case-set of 60 mammographic images containing 40 normal and 20 biopsy-proven cancer cases. Nine different case-sets were available. Using a questionnaire, we collected radiologists' demographic details, such as reading volume and years of experience. These characteristics along with a case set difficulty measure were fed into two ensemble of regression trees to predict the readers' AUCs and lesion sensitivities. We calculated the Pearson correlation coefficient between the predicted values by the model and the actual AUC and lesion sensitivity. The usefulness of the model to categorize readers as low and high performers based on different criteria was also evaluated. The performances of the models were evaluated using leave-one-out cross-validation.

RESULTS

The Pearson correlation coefficient between the predicted AUC and actual one was 0.60 (p < 0.001). The model's performance for differentiating the reader in the first and fourth quartile based on the AUC values was 0.86 (95% CI 0.83-0.89). The model reached an AUC of 0.91 (95% CI 0.88-0.93) for distinguishing the readers in the first quartile from the fourth one based on the lesion sensitivity.

CONCLUSION

A machine learning model can be used to categorize readers as high- or low-performing. Such model could be useful for screening programs for designing a targeted quality assurance and optimizing the double reading practice.

Diagnostic Accuracy of Digital Breast Tomosynthesis in the Evaluation of Palpable Breast Abnormalities

RATIONALE AND OBJECTIVES

The role of digital breast tomosynthesis (DBT) in evaluating palpable abnormalities has not been evaluated and its accuracy compared to 2D mammography is unknown. The purpose of this study was to evaluate combined 2D mammography, DBT, and ultrasound (US) at palpable sites.

MATERIALS AND METHODS

Two breast imagers reviewed blinded consecutive cases with combined 2D mammograms and DBT examinations performed for palpable complaints. By consensus, 2D and DBT findings were recorded and compared to US. Patient characteristics, demographics, subsequent workup, and outcome were recorded.

RESULTS

A total of 229 sites in 188 patients were included, with 50 biopsies performed identifying 18 cancers. All 18 cancers were identified on 2D and US, whereas 17 cancers were identified on DBT. Cancer detection sensitivities for 2D, DBT, and US were 100.0%, 94.4%, and 100.0%. The negative predictive value, when combined with US, was 100% for both. The sensitivity and the specificity for both benign and malignant findings with 2D and DBT were 70.5% versus 75.4% (P = 0.07) and 95.3% versus 99.1% (P = 0.125). Palpable findings not identified by 2D and DBT were smaller than those identified (11.5 ± 8.3 mm vs 23.9 ± 12.8 mm, P < 0.001). Patients with dense breasts were more likely to have mammographically occult findings than patients with nondense breasts (27.4% vs 8.3%).

CONCLUSIONS

DBT did not improve cancer detection over 2D or US. Both mammographic modalities failed to identify sonographically confirmed findings primarily in dense breasts. The diagnostic use of DBT at palpable sites provided limited benefit over combined 2D and US. When utilizing DBT, US should be performed to adequately characterize palpable sites.

Errors in Mammography Cannot be Solved Through Technology Alone

Mammography has been the frontline screening tool for breast cancer for decades. However, high error rates in the form of false negatives (FNs) and false positives (FPs) have persisted despite technological improvements. Radiologists still miss between 10% and 30% of cancers while 80% of woman recalled for additional views have normal outcomes, with 40% of biopsied lesions being benign. Research show that the majority of cancers missed is actually visible and looked at, but either go unnoticed or are deemed to be benign. Causal agents for these errors include human related characteristics resulting in contributory search, perception and decision-making behaviours. Technical, patient and lesion factors are also important relating to positioning, compression, patient size, breast density and presence of breast implants as well as the nature and subtype of the cancer itself, where features such as architectural distortion and triple-negative cancers remain challenging to detect on screening. A better understanding of these causal agents as well as the adoption of technological and educational interventions, which audits reader performance and provide immediate perceptual feedback, should help. This paper reviews the current status of our knowledge around error rates in mammography and explores the factors impacting it. It also presents potential solutions for maximizing diagnostic efficacy thus benefiting the millions of women who undergo this procedure each year.

ACR BI-RADS Assessment Category 4 Subdivisions in Diagnostic Mammography: Utilization and Outcomes in the National Mammography Database

Purpose To determine the utilization and positive predictive value (PPV) of the American College of Radiology (ACR) Breast Imaging Data and Reporting System (BI-RADS) category 4 subdivisions in diagnostic mammography in the National Mammography Database (NMD). Materials and Methods This study involved retrospective review of diagnostic mammography data submitted to the NMD from January 1, 2008 to December 30, 2014. Utilization rates of BI-RADS category 4 subdivisions were compared by year, facility (type, location, census region), and examination (indication, finding type) characteristics. PPV3 (positive predictive value for biopsies performed) was calculated overall and according to category 4 subdivision. The χ² test was used to test for significant associations. Results Of 1 309 950 diagnostic mammograms, 125 447 (9.6%) were category 4, of which 33.3% (41 841 of 125 447) were subdivided. Subdivision utilization rates were higher (P < .001) in practices that were community, suburban, or in the West; for examination indication of prior history of breast cancer; and for the imaging finding of architectural distortion. Of 41 841 category 4 subdivided examinations, 4A constituted 55.6% (23 258 of 41 841) of the examinations; 4B, 31.8% (13 302 of 41 841) of the examinations; and 4C, 12.6% (5281 of 41 841) of the examinations. Pathologic outcomes were available in 91 563 examinations, and overall category 4 PPV3 was 21.1% (19 285 of 91 563). There was a statistically significant difference in PPV3 according to category 4 subdivision (P < .001): The PPV of 4A was 7.6% (1274 of 16 784), that of 4B was 22% (2317 of 10 408), and that of 4C was 69.3% (2839 of 4099). Conclusion Although BI-RADS suggests their use, subdivisions were utilized in the minority (33.3% [41 841 of 125 447]) of category 4 diagnostic mammograms, with variability based on facility and examination characteristics. When subdivisions were used, PPV3s were in BI-RADS-specified malignancy ranges. This analysis supports the use of subdivisions in broad practice and, given benefits for patient care, should motivate increased utilization. ^© RSNA, 2018 Online supplemental material is available for this article.

Performance of a subsidised mammographic screening programme in Malaysia, a middle-income Asian country

BACKGROUND

The incidence of breast cancer in Asia is increasing because of urbanization and lifestyle changes. In the developing countries in Asia, women present at late stages, and mortality is high. Mammographic screening is the only evidence-based screening modality that reduces breast cancer mortality. To date, only opportunistic screening is offered in the majority of Asian countries because of the lack of justification and funding. Nevertheless, there have been few reports on the effectiveness of such programmes. In this study, we describe the cancer detection rate and challenges experienced in an opportunistic mammographic screening programme in Malaysia.

METHODS

From October 2011 to June 2015, 1,778 asymptomatic women, aged 40-74 years, underwent subsidised mammographic screening. All patients had a clinical breast examination before mammographic screening, and women with mammographic abnormalities were referred to a surgeon. The cancer detection rate and variables associated with a recommendation for adjunct ultrasonography were determined.

RESULTS

The mean age for screening was 50.8 years and seven cancers (0.39%) were detected. The detection rate was 0.64% in women aged 50 years and above, and 0.12% in women below 50 years old. Adjunct ultrasonography was recommended in 30.7% of women, and was significantly associated with age, menopausal status, mammographic density and radiologist's experience. The main reasons cited for recommendation of an adjunct ultrasound was dense breasts and mammographic abnormalities.

DISCUSSION

The cancer detection rate is similar to population-based screening mammography programmes in high-income Asian countries. Unlike population-based screening programmes in Caucasian populations where the adjunct ultrasonography rate is 2-4%, we report that 3 out of 10 women attending screening mammography were recommended for adjunct ultrasonography. This could be because Asian women attending screening are likely premenopausal and hence have denser breasts. Radiologists who reported more than 360 mammograms were more confident in reporting a mammogram as normal without adjunct ultrasonography compared to those who reported less than 180 mammograms.

CONCLUSION

Our subsidised opportunistic mammographic screening programme is able to provide equivalent cancer detection rates but the high recall for adjunct ultrasonography would make screening less cost-effective.

How Many of the Biopsy Decisions Taken at Inexperienced Breast Radiology Units Were Correct?

OBJECTIVE

In this study, we aimed to determine the need for biopsy in patients referred from other clinics for the performance of biopsy with the suspicion of breast cancer.

MATERIALS AND METHODS

112 patients were included in the study. It was decided that their biopsies be performed following examinations in other clinics and they presented to the breast radiology unit of our hospital for a second opinion. The demographic characteristics, diagnostic studies completed in the other centers, properties of lesions, decision made as a result of examinations and BI-RADS (Breast Imaging Reporting and Data Systems) categorizations were recorded on the registration forms of the study patients. In addition, the quality of examinations, reasons of repeat tests, additional tests features and the last decision of our clinic were documented. The obtained data were analyzed in terms of re-examination, additional tests and change in the biopsy decision. Changes in the biopsy decisions for patients were specifically inquired.

RESULTS

The biopsy decisions were cancelled in our breast radiology unit for 63 out of 112 patients (56.3%) whose biopsy decisions were made at an external institute. For 42 patients, examinations made by the other clinics were deemed adequate, yet there was no need for biopsy in 22 of them. The biopsy decisions were cancelled for 27 out of 47 patients (57.4%) with repeat examination and 18 out of 28 patients (64.3%) with additional tests because of the insufficient test quality.

CONCLUSION

Incorrect, inadequate breast screening and false positivity were higher at inexperienced institutes.