Comparison of recall and cancer detection rates for immediate versus batch interpretation of screening mammograms

Optimizing the Patient Experience in Breast Imaging Facilities: AJR Expert Panel Narrative Review

Breast imaging studies are complex examinations for patients and providers. Breast imaging providers and organizations invest significant resources in educating patients and referring physicians to address variability in changing breast cancer screening recommendations, cultural biases, and socioeconomic barriers for patients. The breast imaging examination frequently involves multiple imaging modalities, including interventional procedures, thus requiring multiple room types. Practices need to consider the variables that affect workflow efficiency throughout the process of examination scheduling, performance, interpretation, and results delivery, as well as options in facilities design for creating inviting yet functional environments for patients. Breast imaging appointments provide an opportunity to capture individual breast cancer risk and to engage patients in health education and breast screening awareness. This AJR Expert Panel Narrative Review discusses ways in which breast imaging facilities can optimize a patient's experience throughout the complex process of a breast imaging examination, based on the authors' observations and opinions informed by private and academic breast imaging experience.

Impact of Interruptions During Screening Mammography on Physician Well-Being and Patient Care

OBJECTIVE

To assess the impact of interruptions on radiologists' efficiency, accuracy, and job satisfaction in interpreting screening mammograms.

METHODS

This institutional review board-approved retrospective reader study recruited nine breast radiologists from a single academic institution [name withheld] to interpret 150 screening mammograms performed between December 1, 2008, and December 31, 2015 under two different reading conditions, as follows: (1) uninterrupted batch reading and (2) interrupted reading. The 150 cases consisted of 125 normal mammograms and 25 mammograms with subtle breast cancers. Cases were divided into two groups of 75 cases each (cohort 1 and cohort 2), with a comparable distribution of cancer cases. Four rounds of 75 cases each were conducted with a 6-week washout period between rounds 2 and 3. After completing each interpretation session, readers completed a seven-question survey, assessing perceptions of mental and physical effort, level of frustration, and performance satisfaction. Clinical performance metrics (reading time, recall rate, sensitivity, specificity, accuracy, and positive predictive value 1) were calculated.

RESULTS

Recall rates were significantly (P = .04) higher during interrupted reading sessions (35.4%) than they were during uninterrupted batch reading sessions (31.4%). Accuracy was significantly (P = .049) worse in the interrupted reading sessions (69.5%), compared with uninterrupted sessions (73.6%). Differences in overall image interpretation times were not statistically significant (P = .065). Compared with uninterrupted batch reading sessions, readers during interrupted sessions reported feeling busier (P < .001), encountered higher levels of cognitive demand (P = .005), experienced elevated levels of physical fatigue (P = .004), and expressed lower levels of satisfaction with their performance (P = .041).

CONCLUSION

Interruptions during interpretation of screening mammography have deleterious effects on physician performance and their sense of well-being.

Feasibility of predicting a screening digital breast tomosynthesis recall using features extracted from the electronic medical record

PURPOSE

Tools to predict a screening mammogram recall at the time of scheduling could improve patient care. We extracted patient demographic and breast care history information within the electronic medical record (EMR) for women undergoing digital breast tomosynthesis (DBT) to identify which factors were associated with a screening recall recommendation.

METHOD

In 2018, 21,543 women aged 40 years or greater who underwent screening DBT at our institution were identified. Demographic information and breast care factors were extracted automatically from the EMR. The primary outcome was a screening recall recommendation of BI-RADS 0. A multivariable logistic regression model was built and included age, race, ethnicity groups, family breast cancer history, personal breast cancer history, surgical breast cancer history, recall history, and days since last available screening mammogram.

RESULTS

Multiple factors were associated with a recall on the multivariable model: history of breast cancer surgery (OR: 2.298, 95% CI: 1.854, 2.836); prior recall within the last five years (vs no prior, OR: 0.768, 95% CI: 0.687, 0.858); prior screening mammogram within 0-18 months (vs no prior, OR: 0.601, 95% CI: 0.520, 0.691), prior screening mammogram within 18-30 months (vs no prior, OR: 0.676, 95% CI: 0.520, 0.691); and age (normalized OR: 0.723, 95% CI: 0.690, 0.758).

CONCLUSIONS

It is feasible to predict a DBT screening recall recommendation using patient demographics and breast care factors that can be extracted automatically from the EMR.

Imaging of breast cancer-beyond the basics

Imaging of breast cancer is the backbone of breast cancer screening, diagnosis, preoperative/treatment assessment and follow-up. The main modalities are mammography, ultrasound and magnetic resonance imaging, each with its own advantages and disadvantages. New emerging technologies have also enabled each modality to improve on their weaknesses. Imaging-guided biopsies have allowed for accurate diagnosis of breast cancer, with low complication rates. The purpose of this article is to review the common modalities for breast cancer imaging in current practice with emphasis on the strengths and potential weaknesses, discuss the selection of the best imaging modality for the specific clinical question or patient population, and explore new technologies / future directions of breast cancer imaging.

Racial Disparities in Breast Imaging Wait Times Before and After the Implementation of a Same-Day Biopsy Program

OBJECTIVE

To examine time from screening to diagnostic workup, biopsy, and surgery for non-Hispanic White (NHW) and Black women following implementation of a same-day biopsy program.

METHODS

All NHW and Black women with BI-RADS category 0 screening mammogram at Duke University Hospital were identified between August 1, 2020, and August 1, 2021. Patient characteristics were recorded. Time between screening mammogram, diagnostic workup, breast biopsy, surgical consultation, and surgery were recorded. Comparisons were made between NHW and Black women using a multivariable regression model. Diagnostic imaging to biopsy time interval was compared to historical averages before same-day biopsy implementation.

RESULTS

There were 2156 women: 69.9% NHW (1508/2156) and 30.1% Black (648/2156). Mean ± standard deviation time from screening to diagnostic imaging overall was 13.5 ± 32.5 days but longer for Black (18.0 ± 48.3 days) than for NHW women (11.5 ± 22.2 days) (P < 0.001). The mean time from diagnostic mammogram to biopsy was 5.9 ± 18.9 days, longer for Black (9.0 ± 27.9 days) than for NHW women (4.4 ± 11.8 days) (P = 0.017). The same-day biopsy program shortened the time from diagnostic imaging to biopsy overall (12.5 ± 12.4 days vs 5.9 ± 18.9 days; P < 0.001), with a significant reduction for NHW women (12.4 ± 11.7 days vs 4.4 ± 11.8 days) (P < 0.001) but not Black women (11.5 ± 9.9 days vs 9.0 ± 27.9 days) (P = 0.527).

CONCLUSION

Disparities exist along the breast imaging pathway. A same-day biopsy program benefited NHW women more than Black women.

Prioritizing Screening Mammograms for Immediate Interpretation and Diagnostic Evaluation on the Basis of Risk for Recall

PURPOSE

The aim of this study was to develop a prioritization strategy for scheduling immediate screening mammographic interpretation and possible diagnostic evaluation.

METHODS

A population-based cohort with screening mammograms performed from 2012 to 2020 at 126 radiology facilities from 7 Breast Cancer Surveillance Consortium registries was identified. Classification trees identified combinations of clinical history (age, BI-RADS® density, time since prior mammogram, history of false-positive recall or biopsy result), screening modality (digital mammography, digital breast tomosynthesis), and facility characteristics (profit status, location, screening volume, practice type, academic affiliation) that grouped screening mammograms by recall rate, with ≥12/100 considered high and ≥16/100 very high. An efficiency ratio was estimated as the percentage of recalls divided by the percentage of mammograms.

RESULTS

The study cohort included 2,674,051 screening mammograms in 925,777 women, with 235,569 recalls. The most important predictor of recall was time since prior mammogram, followed by age, history of false-positive recall, breast density, history of benign biopsy, and screening modality. Recall rates were very high for baseline mammograms (21.3/100; 95% confidence interval, 19.7-23.0) and high for women with ≥5 years since prior mammogram (15.1/100; 95% confidence interval, 14.3-16.1). The 9.2% of mammograms in subgroups with very high and high recall rates accounted for 19.2% of recalls, an efficiency ratio of 2.1 compared with a random approach. Adding women <50 years of age with dense breasts accounted for 20.3% of mammograms and 33.9% of recalls (efficiency ratio = 1.7). Results including facility-level characteristics were similar.

CONCLUSIONS

Prioritizing women with baseline mammograms or ≥5 years since prior mammogram for immediate interpretation and possible diagnostic evaluation could considerably reduce the number of women needing to return for diagnostic imaging at another visit.

Live Mammographic Screening Interpretation Versus Offline Same-Day Screening Interpretation at a Tertiary Cancer Center

OBJECTIVES

The aim of this study was to compare screening mammography performance metrics for immediate (live) interpretation versus offline interpretation at a cancer center.

METHODS

An institutional review board-approved, retrospective comparison of screening mammography metrics at a cancer center for January 1, 2018, to December 31, 2019 (live period), and September 1, 2020, to March 31, 2022 (offline period), was performed. Before July 2020, screening examinations were interpreted while patients waited (live period), and diagnostic workup was performed concurrently. After the coronavirus disease 2019 shutdown from March to mid-June 2020, offline same-day interpretation was instituted. Patients with abnormal screening results returned for separate diagnostic evaluation. Screening metrics of positive predictive value 1 (PPV1), cancer detection rate (CDR), and abnormal interpretation rate (AIR) were compared for 17 radiologists who interpreted during both periods. Statistical significance was assessed using χ² analysis.

RESULTS

In the live period, there were 7,105 screenings, 635 recalls, and 51 screen-detected cancers. In the offline period, there were 7,512 screenings, 586 recalls, and 47 screen-detected cancers. Comparison of live screening metrics versus offline metrics produced the following results: AIR, 8.9% (635 of 7,105) versus 7.8% (586 of 7,512) (P = .01); PPV1, 8.0% (51 of 635) versus 8.0% (47 of 586); and CDR, 7.2/1,000 versus 6.3/1,000 (P = .50). When grouped by >10% AIR or <10% AIR for the live period, the >10% AIR group showed a significant decrease in AIR for offline interpretation (from 12.7% to 9.7%, P < .001), whereas the <10% AIR group showed no significant change (from 7.4% to 6.7%, P = .17).

CONCLUSIONS

Conversion to offline screening interpretation from immediate interpretation at a cancer center was associated with lower AIR and similar CDR and PPV1. This effect was seen largely in radiologists with AIR > 10% in the live setting.

Patient-centered Care and Integrated Practice Units: Embracing the Breast Care Continuum

Patient-centered care is a health care approach optimized for the needs of the patient. As patients have sought more autonomy in recent years, this model has been more frequently adopted. Breast radiologists aspiring to advance patient-centered care should seek greater ownership of the breast diagnostic imaging and intervention workflows, helping their patients navigate the complex breast care landscape with patients' preferences taken into account. Applying this approach to breast radiology will increase patient satisfaction and compliance while also limiting wasted health care dollars, unnecessary diagnostic delays, and overall confusion. Herein, the benefits of patient-centered breast radiology are discussed, and numerous suggestions and case examples are provided to help readers reshape their practice toward the priorities of their patients.

Persistent inter-observer variability of breast density assessment using BI-RADS® 5th edition guidelines

OBJECTIVES

Due to most states' legislation, mammographic density categorization has potentially far-reaching implications, but remains subjective based on BIRADS® guidelines. We aimed to determine 1) effect of BI-RADS® 5th edition (5th-ed) vs 4th-edition (4th-ed) guidelines on reader agreement regarding density assessment; 2) 5th-ed vs 4th-ed density distribution, and visual vs quantitative assessment agreement; 3) agreement between experienced vs less experienced readers.

METHODS

In a retrospective review, six breast imaging radiologists (BIR) (23-30 years' experience) visually assessed density of 200 screening mammograms performed September 2012-January 2013 using 5th-ed guidelines. Results were compared to 2016 data of the same readers evaluating the same mammograms using 4th-ed guidelines after a training module. 5th-ed density categorization by seven junior BIR (1-5 years' experience) was compared to eight experienced BIR. Nelson et al.'s kappas (κ_m, κ_w), Fleiss' κ_F, and Cohen's κ were calculated. Quantitative density using Volpara was compared with reader assessments.

RESULTS

Inter-reader weighted agreement using 5th-ed is moderately strong, 0.73 (κ_w, s.e. = 0.01), similar to 4th-ed, 0.71 (κ_w, s.e. = 0.03). Intra-reader Cohen's κ is 0.23-0.34, similar to 4th-ed. Binary not-dense vs dense categorization, using 5th-ed results in higher dense categorization vs 4th-ed (p < 0.001). 5th-ed density distribution results in higher numbers in categories B/C vs 4th-ed (p < 0.001). Distribution for 5th-ed does not differ based on reader experience (p = 0.09). Reader vs quantitative weighted agreement is similar (5th-ed, Cohen's κ = 0.76-0.85; 4th-ed, Cohen's κ = 0.68-0.83).

CONCLUSION

There is persistent subjectivity of visually assessed mammographic density using 5th-ed guidelines; experience does not correlate with better inter-reader agreement.

Online or Offline: Does It Matter? A Review of Existing Interpretation Approaches and Their Effect on Screening Mammography Metrics, Patient Satisfaction, and Cost

The ideal practice routine for screening mammography would optimize performance metrics and minimize costs, while also maximizing patient satisfaction. The main approaches to screening mammography interpretation include batch offline, non-batch offline, interrupted online, and uninterrupted online reading, each of which has its own advantages and drawbacks. This article reviews the current literature on approaches to screening mammography interpretation, potential effects of newer technologies, and promising artificial intelligence resources that could improve workflow efficiency in the future.

Does it matter for the radiologists' performance whether they read short or long batches in organized mammographic screening?

Objective

To analyze the association between radiologists’ performance and image position within a batch in screen reading of mammograms in Norway.

Method

We described true and false positives and true and false negatives by groups of image positions and batch sizes for 2,937,312 screen readings performed from 2012 to 2018. Mixed-effects models were used to obtain adjusted proportions of true and false positive, true and false negative, sensitivity, and specificity for different image positions. We adjusted for time of day and weekday and included the individual variation between the radiologists as random effects. Time spent reading was included in an additional model to explore a possible mediation effect.

Result

True and false positives were negatively associated with image position within the batch, while the rates of true and false negatives were positively associated. In the adjusted analyses, the rate of true positives was 4.0 per 1000 (95% CI: 3.8–4.2) readings for image position 10 and 3.9 (95% CI: 3.7–4.1) for image position 60. The rate of true negatives was 94.4% (95% CI: 94.0–94.8) for image position 10 and 94.8% (95% CI: 94.4–95.2) for image position 60. Per 1000 readings, the rate of false negative was 0.60 (95% CI: 0.53–0.67) for image position 10 and 0.62 (95% CI: 0.55–0.69) for image position 60.

Conclusion

There was a decrease in the radiologists’ sensitivity throughout the batch, and although this effect was small, our results may be clinically relevant at a population level or when multiplying the differences with the number of screen readings for the individual radiologists.

Key Points

• True and false positive reading scores were negatively associated with image position within a batch.

• A decreasing trend of positive scores indicated a beneficial effect of a certain number of screen readings within a batch.

• False negative scores increased throughout the batch but the association was not statistically significant.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-021-08010-9.

Batch Reading and Interrupted Interpretation of Digital Screening Mammograms Without and With Tomosynthesis

OBJECTIVE

To compare batch reading and interrupted interpretation for modern screening mammography.

METHODS

We retrospectively reviewed digital mammograms without and with tomosynthesis that were originally interpreted with batch reading or interrupted interpretation between January 2015 and June 2017. The following performance metrics were compared: recall rate (per 100 examinations), cancer detection rate (per 1,000 examinations), and positive predictive values for recall and biopsy.

RESULTS

In all, 9,832 digital mammograms were batch read, yielding a recall rate of 9.98%, cancer detection rate of 4.27, and positive predictive values for recall and biopsy of 4.40% and 35.5%, respectively. There were 49,496 digital mammograms that were read with interrupted interpretation, yielding a recall rate of 11.3%, cancer detection rate of 4.44, and positive predictive values for recall and biopsy of 3.92% and 30.1%, respectively. Of the digital mammograms with tomosynthesis, 7,075 were batch read, yielding a recall rate of 6.98%, cancer detection rate of 5.37, and positive predictive values for recall and biopsy of 7.69% and 38.0%, respectively. Of the digital mammograms with tomosynthesis, 24,380 were read with interrupted interpretation, yielding a recall rate of 8.30%, cancer detection rate of 5.41, and positive predictive values for recall and biopsy of 6.52% and 33.3%, respectively. For both digital mammograms without and with tomosynthesis, recall rates improved with batch reading compared with interrupted interpretation (P < .001), but no significant differences were seen for other metrics.

DISCUSSION

Batch reading digital mammograms without and with tomosynthesis improves recall rates while maintaining cancer detection rates and positive predictive values compared with interrupted interpretation.

Effects of time of day on radiological interpretation

Accurate interpretation of radiological images involves a complex visual search that relies on several cognitive processes, including selective attention, working memory, and decision-making. Patient outcomes often depend on the accuracy of image interpretations, and yet research has revealed that conclusions vary significantly from one radiologist to another. A myriad of factors has been shown to contribute to the likelihood of interpretative errors and discrepancies, including the radiologist's level of experience and fatigue, and these factors are well reported elsewhere; however, a potentially important factor that has been given little previous consideration is how radiologists' interpretations might be impacted by the time of day at which the reading takes place, a factor that other disciplines have shown to be a determinant of competency. The available literature shows that while the time of day is known to significantly impact some cognitive functions that likely relate to reading competence, including selective visual attention and visual working memory, little is known about the impact of the time of day on radiology interpretation performance. This review explores the evidence regarding the relationship between time of day and performance, with a particular emphasis on radiological activities.

Deep learning in radiology: An overview of the concepts and a survey of the state of the art with focus on MRI

Deep learning is a branch of artificial intelligence where networks of simple interconnected units are used to extract patterns from data in order to solve complex problems. Deep-learning algorithms have shown groundbreaking performance in a variety of sophisticated tasks, especially those related to images. They have often matched or exceeded human performance. Since the medical field of radiology mainly relies on extracting useful information from images, it is a very natural application area for deep learning, and research in this area has rapidly grown in recent years. In this article, we discuss the general context of radiology and opportunities for application of deep-learning algorithms. We also introduce basic concepts of deep learning, including convolutional neural networks. Then, we present a survey of the research in deep learning applied to radiology. We organize the studies by the types of specific tasks that they attempt to solve and review a broad range of deep-learning algorithms being utilized. Finally, we briefly discuss opportunities and challenges for incorporating deep learning in the radiology practice of the future. Level of Evidence: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:939-954.

Impact of Immediate Interpretation of Screening Tomosynthesis Mammography on Performance Metrics

RATIONALE AND OBJECTIVES

This study aimed to compare performance metrics for immediate and delayed batch interpretation of screening tomosynthesis mammograms.

MATERIALS AND METHODS

This HIPAA compliant study was approved by institutional review board with a waiver of consent. A retrospective analysis of screening performance metrics for tomosynthesis mammograms interpreted in 2015 when mammograms were read immediately was compared to historical controls from 2013 to 2014 when mammograms were batch interpreted after the patient had departed. A total of 5518 screening tomosynthesis mammograms (n = 1212 for batch interpretation and n = 4306 for immediate interpretation) were evaluated. The larger sample size for the latter group reflects a group practice shift to performing tomosynthesis for the majority of patients. Age, breast density, comparison examinations, and high-risk status were compared. An asymptotic proportion test and multivariable analysis were used to compare performance metrics.

RESULTS

There was no statistically significant difference in recall or cancer detection rates for the batch interpretation group compared to immediate interpretation group with respective recall rate of 6.5% vs 5.3% = +1.2% (95% confidence interval -0.3 to 2.7%; P = .101) and cancer detection rate of 6.6 vs 7.2 per thousand = -0.6 (95% confidence interval -5.9 to 4.6; P = .825). There was no statistically significant difference in positive predictive values (PPVs) including PPV1 (screening recall), PPV2 (biopsy recommendation), or PPV 3 (biopsy performed) with batch interpretation (10.1%, 42.1%, and 40.0%, respectively) and immediate interpretation (13.6%, 39.2%, and 39.7%, respectively). After adjusting for age, breast density, high-risk status, and comparison mammogram, there was no difference in the odds of being recalled or cancer detection between the two groups.

CONCLUSIONS

There is no statistically significant difference in interpretation performance metrics for screening tomosynthesis mammograms interpreted immediately compared to those interpreted in a delayed fashion.

Communication Practices of Mammography Facilities and Timely Follow-up of a Screening Mammogram with a BI-RADS 0 Assessment

RATIONALE AND OBJECTIVES

The objective of this study was to evaluate the association of communication practices with timely follow-up of screening mammograms read as Breast Imaging Reporting and Data Systems (BI-RADS) 0 in the Population-based Research Optimizing Screening through Personalized Regimens (PROSPR) consortium.

MATERIALS AND METHODS

A radiology facility survey was conducted in 2015 with responses linked to screening mammograms obtained in 2011-2014. We considered timely follow-up to be within 15 days of the screening mammogram. Generalized estimating equation models were used to evaluate the association between modes of communication with patients and providers and timely follow-up, adjusting for PROSPR site, patient age, and race and ethnicity.

RESULTS

The analysis included 34,680 mammography examinations with a BI-RADS 0 assessment among 28 facilities. Across facilities, 85.6% of examinations had a follow-up within 15 days. Patients in a facility where routine practice was to contact the patient by phone if follow-up imaging was recommended were more likely to have timely follow-up (odds ratio [OR] 4.63, 95% confidence interval [CI] 2.76-7.76), whereas standard use of mail was associated with reduced timely follow-up (OR 0.47, 95% CI 0.30-0.75). Facilities that had standard use of electronic medical records to report the need for follow-up imaging to a provider had less timely follow-up (OR 0.56, 95% CI 0.35-0.90). Facilities that routinely contacted patients by mail if they missed a follow-up imaging visit were more likely to have timely follow-up (OR 1.65, 95% CI 1.02-2.69).

CONCLUSIONS

Our findings support the value of telephone communication to patients in relation to timely follow-up. Future research is needed to evaluate the role of communication in completing the breast cancer screening episode.

Screening organization and recall rate in a regional breast screening programme

Objective To use results on recall rates from a regional non-population-based breast screening programme to inform practice in a planned national population-based programme. Methods We analysed data on rates of recall for further assessment in 27,327 mammographic screening episodes in 2015-2016 in the breast screening programme in the city of Tbilisi, Georgia. Screening was done by two-view digital mammography with double reading in women aged 40-70, and further assessment took place at the same clinic and during the same visit as the initial screening mammogram. Results The recall rates were 46% (3573/7824) in 2015 and 27% (5276/19,503) in 2016. Cancer detection rates were 8 per 1000 in 2015 and 3 per 1000 in 2016. Rates of recall were higher in younger women than in older, whereas the rates of cancer detection were higher in older women. Conclusions The recall rates, while lower in 2016 than in 2015, are still too high to manage in a nationwide population programme. The use of same-visit assessment is likely to be contributing to this. The national programme should consider separate assessment clinics and carry out audit of recalls to date.

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.

Integrating Customer Intimacy Into Radiology to Improve the Patient Perspective: The Case of Breast Cancer Screening

OBJECTIVE

The customer intimacy business model has emerged as a key operational approach for health care organizations as they move toward patient-centered care. The question arises how the customer intimacy approach can be implemented in the clinical setting and whether it can help practitioners address problems and improve quality of care.

CONCLUSION

Breast cancer screening and its emphasis on the patient perspective provides an interesting case study for understanding how the customer intimacy approach can be integrated into radiologic practice to improve the patient experience.

Influences of Radiology Trainees on Screening Mammography Interpretation

PURPOSE

Participation of radiology trainees in screening mammographic interpretation is a critical component of radiology residency and fellowship training. The aim of this study was to investigate and quantify the effects of trainee involvement on screening mammographic interpretation and diagnostic outcomes.

METHODS

Screening mammograms interpreted at an academic medical center by six dedicated breast imagers over a three-year period were identified, with cases interpreted by an attending radiologist alone or in conjunction with a trainee. Trainees included radiology residents, breast imaging fellows, and fellows from other radiology subspecialties during breast imaging rotations. Trainee participation, patient variables, results of diagnostic evaluations, and pathology were recorded.

RESULTS

A total of 47,914 mammograms from 34,867 patients were included, with an overall recall rate for attending radiologists reading alone of 14.7% compared with 18.0% when involving a trainee (P < .0001). Overall cancer detection rate for attending radiologists reading alone was 5.7 per 1,000 compared with 5.2 per 1,000 when reading with a trainee (P = .517). When reading with a trainee, dense breasts represented a greater portion of recalls (P = .0001), and more frequently, greater than one abnormality was described in the breast (P = .013). Detection of ductal carcinoma in situ versus invasive carcinoma or invasive cancer type was not significantly different. The mean size of cancers in patients recalled by attending radiologists alone was smaller, and nodal involvement was less frequent, though not statistically significantly.

CONCLUSIONS

These results demonstrate a significant overall increase in recall rate when interpreting screening mammograms with radiology trainees, with no change in cancer detection rate. Radiology faculty members should be aware of this potentiality and mitigate tendencies toward greater false positives.

Adaptation and visual search in mammographic images

Radiologists face the visually challenging task of detecting suspicious features within the complex and noisy backgrounds characteristic of medical images. We used a search task to examine whether the salience of target features in x-ray mammograms could be enhanced by prior adaptation to the spatial structure of the images. The observers were not radiologists, and thus had no diagnostic training with the images. The stimuli were randomly selected sections from normal mammograms previously classified with BIRADS Density scores of "fatty" versus "dense," corresponding to differences in the relative quantities of fat versus fibroglandular tissue. These categories reflect conspicuous differences in visual texture, with dense tissue being more likely to obscure lesion detection. The targets were simulated masses corresponding to bright Gaussian spots, superimposed by adding the luminance to the background. A single target was randomly added to each image, with contrast varied over five levels so that they varied from difficult to easy to detect. Reaction times were measured for detecting the target location, before or after adapting to a gray field or to random sequences of a different set of dense or fatty images. Observers were faster at detecting the targets in either dense or fatty images after adapting to the specific background type (dense or fatty) that they were searching within. Thus, the adaptation led to a facilitation of search performance that was selective for the background texture. Our results are consistent with the hypothesis that adaptation allows observers to more effectively suppress the specific structure of the background, thereby heightening visual salience and search efficiency.

Diagnostic imaging and biopsy pathways following abnormal screen-film and digital screening mammography

The transition from screen-film to digital mammography may have altered diagnostic evaluation of women following a positive screening examination. This study compared the use and timeliness of diagnostic imaging and biopsy for women screened with screen-film or digital mammography. Data were obtained from 35,321 positive screening mammograms on 32,087 women aged 40-89 years, from 22 breast cancer surveillance consortium facilities in 2005-2008. Diagnostic pathways were classified by their inclusion of diagnostic mammography, ultrasound, magnetic resonance imaging, and biopsy. We compared time to resolution and frequency of diagnostic pathways by patient characteristics, screening exam modality, and radiology facility. Between-facility differences were evaluated by computing the proportion of mammograms receiving follow-up with a particular pathway for each facility and examining variation in these proportions across facilities. Multinomial logistic regression adjusting for age, calendar year, and facility compared odds of follow-up with each pathway. The median time to resolution of a positive screening mammogram was 10 days. Compared to screen-film mammograms, digital mammograms were more frequently followed by only a single diagnostic mammogram (46 vs. 36 %). Pathways following digital screening mammography were also less likely to include biopsy (16 vs. 20 %). However, in adjusted analyses, most differences were not statistically significant (p = 0.857 for mammography only; p = 0.03 for biopsy). Substantial variability in diagnostic pathway frequency was seen across facilities. For instance, the frequency of evaluation with diagnostic mammography alone ranged from 23 to 55 % across facilities. Differences in evaluation of positive digital and screen-film screening mammograms were minor, and appeared to be largely attributable to substantial variation between radiology facilities. To guide health systems in their efforts to eliminate practices that do not contribute to effective care, we need further research to identify the causes of this variation and the best evidence-based approach for follow-up.

Are the CMS hospital outpatient quality measures relevant for rural hospitals?

CONTEXT

Quality measures focused on outpatient settings are of increasing interest to policy makers, but little research has been conducted on hospital outpatient quality measures, especially in rural settings.

PURPOSE

To evaluate the relevance of Centers for Medicare and Medicaid Services' (CMS) outpatient quality measures for rural hospitals, including critical access hospitals.

METHODS

Researchers analyzed Medicare hospital outpatient claims and hospital compare outpatient quality measure data for rural hospitals to assess the volume of conditions addressed by the measures in rural hospitals. A literature review and information from national quality organizations were used to assess the external and internal usefulness of the measures for rural hospitals. A panel of rural hospital quality experts reviewed the measures and provided additional input about their usefulness and data collection issues in rural hospitals.

RESULTS

The rural relevant CMS outpatient measures include most of the emergency department (ED) measures. The outpatient surgical measures are relevant for the majority of rural hospitals providing outpatient surgery. Several measures were not selected as relevant for rural hospitals, including the outpatient imaging and condition-specific measures.

CONCLUSIONS

To increase sample sizes for smaller rural hospitals, CMS could combine data for similar inpatient and outpatient measures, use composite measures by condition, or use a longer time period to calculate measures. A menu of outpatient measures would allow smaller rural hospitals to choose relevant measures depending on the outpatient services they provide. Global measures and care coordination measures would be useful for quality improvement and have sufficient sample size to allow reliable measurement in smaller rural hospitals.

Factors associated with imaging and procedural events used to detect breast cancer after screening mammography

OBJECTIVE

The purpose of this study was to characterize the type and frequency of diagnostic evaluations after screening mammography and to summarize their association with the likelihood of biopsy and subsequent breast cancer diagnosis.

MATERIALS AND METHODS

The data source was 584,470 women with no previous breast cancer from six states in the Breast Cancer Surveillance Consortium. In this observational study, we linked data from 1,207,631 routine screening mammograms performed between January 1, 1996, and December 31, 2002, to data on additional imaging, interventional procedures, and biopsy outcome (benign or malignant). Additional examinations were categorized into diagnostic mammography, sonography, or both. Events were further subdivided by whether they were performed on the same day as the screening examination and whether patients reported breast symptoms. Logistic regression analysis was used to examine the association between additional evaluation performed and the likelihood of biopsy and the likelihood of subsequent breast cancer diagnosis after adjustment for patient and screening mammographic characteristics.

RESULTS

Most (92%) of the screening examinations did not include additional imaging. The probability of biopsy ranged from 0.4% for examinations with no follow-up to 20.1% for those with diagnostic mammography and sonography on the same day as screening among women without symptoms and from 2.1% for those with no follow-up to 18.9% for those with diagnostic mammography and sonography on a day different from screening among women with symptoms. Thirty percent of women without symptoms who underwent biopsy had cancer, whereas 27.1% of women with symptoms who underwent biopsy had cancer. Women who underwent biopsy after screening mammography with diagnostic mammography and sonography on the same day had the highest probability of breast cancer (37.6% among women without symptoms, 36.4% among women with symptoms), whereas those who underwent only sonography performed at a later date had the lowest probability of breast cancer (11.9% among women without symptoms, 17.1% among women with symptoms).

CONCLUSION

Women who undergo screening mammography followed by diagnostic mammography and sonography have a high probability of undergoing biopsy and having the biopsy result of breast cancer when follow-up imaging is performed on the same day as screening mammography whether or not breast symptoms are present. Biopsy performed after sonography in the absence of diagnostic mammography had a low yield of breast cancer.

Diagnostic performance of digital versus film mammography for breast-cancer screening

BACKGROUND

Film mammography has limited sensitivity for the detection of breast cancer in women with radiographically dense breasts. We assessed whether the use of digital mammography would avoid some of these limitations.

METHODS

A total of 49,528 asymptomatic women presenting for screening mammography at 33 sites in the United States and Canada underwent both digital and film mammography. All relevant information was available for 42,760 of these women (86.3 percent). Mammograms were interpreted independently by two radiologists. Breast-cancer status was ascertained on the basis of a breast biopsy done within 15 months after study entry or a follow-up mammogram obtained at least 10 months after study entry. Receiver-operating-characteristic (ROC) analysis was used to evaluate the results.

RESULTS

In the entire population, the diagnostic accuracy of digital and film mammography was similar (difference between methods in the area under the ROC curve, 0.03; 95 percent confidence interval, -0.02 to 0.08; P=0.18). However, the accuracy of digital mammography was significantly higher than that of film mammography among women under the age of 50 years (difference in the area under the curve, 0.15; 95 percent confidence interval, 0.05 to 0.25; P=0.002), women with heterogeneously dense or extremely dense breasts on mammography (difference, 0.11; 95 percent confidence interval, 0.04 to 0.18; P=0.003), and premenopausal or perimenopausal women (difference, 0.15; 95 percent confidence interval, 0.05 to 0.24; P=0.002).

CONCLUSIONS

The overall diagnostic accuracy of digital and film mammography as a means of screening for breast cancer is similar, but digital mammography is more accurate in women under the age of 50 years, women with radiographically dense breasts, and premenopausal or perimenopausal women. (ClinicalTrials.gov number, NCT00008346.)

The Use of Batch Reading to Improve the Performance of Screening Mammography

OBJECTIVE

The objective of our study was to prove that batch reading of screening mammograms can reduce recall rates without sacrificing cancer detection.

MATERIALS AND METHODS

We analyzed recall rate, cancer detection, minimal cancer detection, detection of low-stage cancer, and tumor size from consecutive screening mammography examinations from October 2001 to July 2003. The initial 7,984 mammograms were interpreted in the midst of a busy breast imaging practice. Although these studies were not read online, the interpretations were often interrupted for telephone calls, procedures, and diagnostic mammograms. The remaining 1,538 studies were interpreted after the institution of dedicated uninterrupted batch reading.

RESULTS

Recall rates were 20.1% before and 16.2% after the introduction of batch reading (p < 0.001). Cancer detection rates were not significantly different: 5.6 cancers were detected per 1,000 examinations without and 7.2 were detected per 1,000 with batch reading. Prognostic factors for breast cancers diagnosed between these groups also were not significantly different. Of the screening-detected cancers diagnosed before batch reading, minimal cancers comprised 67% and low-stage cancers accounted for 76%. Of the cancers diagnosed using batch reading, 73% were minimal and 91% were low stage. The mean size of cancers, 11.7 mm without batch reading and 9.1 mm with batch reading, also showed no statistically significant difference.

CONCLUSION

Our experience shows that batch reading can significantly reduce screening mammography recall rates without affecting the cancer detection rate or the proportion of cancers diagnosed with favorable prognostic indicators.