Digital and Screen-Film Mammography: Comparison of Image Acquisition and Interpretation Times

The impact of the BreastScreen NSW transition from film to digital mammography, 2002-2016: a linked population health data analysis

OBJECTIVES

To assess the impact of the transition from film to digital mammography in the Australian national breast cancer screening program.

STUDY DESIGN

Retrospective linked population health data analysis (New South Wales Central Cancer Registry, BreastScreen NSW); interrupted time series analysis.

SETTING

New South Wales, 2002-2016.

PARTICIPANTS

Women aged 40 years or older with breast cancer diagnosed during 2002-2017 who had been screened by BreastScreen NSW and for whom complete follow-up information until the end of the recommended re-screening interval was available.

INTERVENTION

Transition from film to digital mammography; 2009 defined as transition year (digital mammography becomes dominant screening modality).

MAIN OUTCOME MEASURES

Population rates of screen-detected cancer, interval cancer, recalls, and false positive findings.

RESULTS

The study cohort comprised 967 573 women; of the 2 741 555 screens, 1 535 184 used film mammography (2002-2010) and 1 206 371 used digital mammography (2006-2016). The screen-detected cancer rate was 4.86 (95% confidence interval [CI], 4.75-4.97) cases per 1000 screens with film mammography and 6.11 (95% CI, 5.97-6.24) cases per 1000 screens with digital mammography (unadjusted difference, 1.24 [95% CI, 1.06-1.41] cases per 1000 screens). The interval cancer rate was 2.56 (95% CI, 2.48-2.64) cases per 1000 screens with film mammography and 2.84 (95% CI, 2.75-2.94) cases per 1000 screens with digital mammography (unadjusted difference, 0.27 [95% CI, 0.15-0.40] cases per 1000 screens). With the transition to digital mammography, the screen-detected cancer rate increased by 0.07 per 1000 screens, the sum of the decline in the invasive cancer rate (-0.21 cases per 1000 screens) and the rise in the ductal carcinoma in situ detection rate (0.28 cases per 1000 screens); during 2009-2015, it increased by 0.18 cases per 1000 screens per year. With the transition to digital mammography, the interval cancer rate increased by 0.75 cases per 1000 screens (invasive cancer: by 0.69 cases per 1000 screens); during 2009-2015, it declined by 0.13 cases per 1000 screens per year. The recall rate increased by 8.02 per 1000 screens and the false positive rate by 7.16 per 1000 screens following the transition; both rates subsequently declined to pre-transition levels.

CONCLUSIONS

The increased screen-detected cancer rate following the transition to digital mammography was not accompanied by a reduction in interval cancer detection rates.

Considerations for Evaluating the Introduction of New Cancer Screening Technology: Use of Interval Cancers to Assess Potential Benefits and Harms

This framework focuses on the importance of the consideration of the downstream intermediate and long-term health outcomes when a change to a screening program is introduced. The authors present a methodology for utilising the relationship between screen-detected and interval cancer rates to infer the benefits and harms associated with a change to the program. A review of the previous use of these measures in the literature is presented. The framework presents other aspects to consider when utilizing this methodology, and builds upon an existing framework that helps researchers, clinicians, and policy makers to consider the impacts of changes to screening programs on health outcomes. It is hoped that this research will inform future evaluative studies to assess the benefits and harms of changes to screening programs.

Contrast-enhanced mammography: what the radiologist needs to know

Contrast-enhanced mammography (CEM) is a combination of standard mammography and iodinated contrast material administration. During the last decade, CEM has found its place in breast imaging protocols: after i.v. administration of iodinated contrast material, low-energy and high-energy images are retrieved in one acquisition using a dual-energy technique, and a recombined image is constructed enabling visualisation of areas of contrast uptake. The increased incorporation of CEM into everyday clinical practice is reflected in the installation of dedicated equipment worldwide, the (commercial) availability of systems from different vendors, the number of CEM examinations performed, and the number of scientific articles published on the subject. It follows that ever more radiologists will be confronted with this technique, and thus be required to keep up to date with the latest developments in the field. Most importantly, radiologists must have sufficient knowledge on how to interpret CEM images and be acquainted with common artefacts and pitfalls. This comprehensive review provides a practical overview of CEM technique, including CEM-guided biopsy; reading, interpretation and structured reporting of CEM images, including the accompanying learning curve, CEM artefacts and interpretation pitfalls; indications for CEM; disadvantages of CEM; and future developments.

Comparable prediction of breast cancer risk from a glimpse or a first impression of a mammogram

Expert radiologists can discern normal from abnormal mammograms with above-chance accuracy after brief (e.g. 500 ms) exposure. They can even predict cancer risk viewing currently normal images (priors) from women who will later develop cancer. This involves a rapid, global, non-selective process called “gist extraction”. It is not yet known whether prolonged exposure can strengthen the gist signal, or if it is available solely in the early exposure. This is of particular interest for the priors that do not contain any localizable signal of abnormality. The current study compared performance with brief (500 ms) or unlimited exposure for four types of mammograms (normal, abnormal, contralateral, priors). Groups of expert radiologists and untrained observers were tested. As expected, radiologists outperformed naïve participants. Replicating prior work, they exceeded chance performance though the gist signal was weak. However, we found no consistent performance differences in radiologists or naïves between timing conditions. Exposure time neither increased nor decreased ability to identify the gist of abnormality or predict cancer risk. If gist signals are to have a place in cancer risk assessments, more efforts should be made to strengthen the signal.

Improved Screening Mammogram Workflow by Maximizing PACS Streamlining Capabilities in an Academic Breast Center

The aim of this study was to perform an operational improvement project targeted at the breast imaging reading workflow of mammography examinations at an academic medical center with its associated breast centers and satellite sites. Through careful analysis of the current workflow, two major issues were identified: stockpiling of paperwork and multiple worklists. Both issues were considered to cause significant delays to the start of interpreting screening mammograms. Four workflow changes were suggested (scanning of paperwork, worklist consolidation, use of chat functionality, and tracking of case distribution among trainees) and implemented in July 2015. Timestamp data was collected 2 months before (May-Jun) and after (Aug-Sep) the implemented changes. Generalized linear models were used to analyze the data. The results showed significant improvements for the interpretation of screening mammograms. The average time elapsed for time to open a case reduced from 70 to 28 min (60 % decrease, p < 0.001), report turn-around time with preliminary signature decreased from 151 to 107 min (29 % decrease, p < 0.001), and report turn-around time final signature from 153 to 139 min (9 % decrease, p = 0.002). These improvements were achieved while keeping the efficiency of the workflow for diagnostic mammograms at large unaltered even with increased volume of mammography examinations (31 % increase of 4344 examinations for May-Jun to 5678 examinations for Aug-Sep). In conclusion, targeted efforts to improve the breast imaging reading workflow for screening mammograms in a teaching environment provided significant performance improvements without affecting the workflow of diagnostic mammograms.

Recent Advances in Breast-Specific Imaging

Background

Imaging the breast is a vital component not only for breast cancer screening, but also for diagnosis, evaluation, treatment, and follow-up of patients with breast cancer.

Methods

The author reviews recent advances and also provides her personal experience in describing the status of digital mammography, computer-aided detection, dedicated magnetic resonance imaging (MRI), and positron-emission mammography for evaluating the breast.

Results

Full-field digital mammography is superior to standard mammography in women under 50 years of age and in those with dense breasts. Computer-aided detection assists inexperienced mammographers and enhances detection of microcalcifications in dense breasts. Breast MRI is useful in preoperative evaluation, clarification of indeterminate mammograms, and follow-up of BRCA mutation carriers. The specificity of MRI remains problematic, however. Positron-emission mammography promises enhanced detection of ductal carcinoma in situ (DCIS), even when not associated with microcalcifications, and should aid surgical planning.

Conclusions

These four significant advances in breast imaging have all improved the sensitivity of detecting breast abnormalities. Cost issues, however, may limit the widespread application of these advances.

Evaluation of the effect of zoom function on lesion detection by soft-copy reading of screening mammograms

INTRODUCTION

This study aims to evaluate the effectiveness of zooming in improving screen-reader performance in reporting digital mammograms.

METHOD

Two experiments were conducted. In the first experiment, 5 readers were asked to report 59 two-view bilateral mammograms retrospectively with zooming function turned off. The second session was similar to the first one except that zooming was enabled. The task of readers was to assess if the mammograms were normal or abnormal and rate the confidence levels for each of the lesion they detected. The reader performances were evaluated via case sensitivity, lesion sensitivity, specificity, receiver operating characteristics (ROC) area under the curve (AUC) and jackknife free-response receiver operating characteristics (JAFROC) figure of merit (FOM).

RESULTS

There was no significant improvement in overall reader performance in detecting abnormalities in zooming condition compared with no zooming in terms of case sensitivity (96% and 87%, P = 0.285) or lesion sensitivity (88% and 81%, P = 0.224). However, differences in ROC AUC and JAFROC FOM (P ≤ 0.05) were found in two readers when they performed the test set with zooming function.

CONCLUSION

The results suggested that the use of the zooming function did improve the performance of some readers in detecting abnormal cases.

Breast peripheral area correction in digital mammograms

Digital mammograms may present an overexposed area in the peripheral part of the breast, which is visually shown as a darker area with lower contrast. This has a direct impact on image quality and affects image visualisation and assessment. This paper presents an automatic method to enhance the overexposed peripheral breast area providing a more homogeneous and improved view of the whole mammogram. The method automatically restores the overexposed area by equalising the image using information from the intensity of non-overexposed neighbour pixels. The correction is based on a multiplicative model and on the computation of the distance map from the breast boundary. A total of 334 digital mammograms were used for evaluation. Mammograms before and after enhancement were evaluated by an expert using visual comparison. In 90.42% of the cases, the enhancement obtained improved visualisation compared to the original image in terms of contrast and detail. Moreover, results show that lesions found in the peripheral area after enhancement presented a more homogeneous intensity distribution. Hence, peripheral enhancement is shown to improve visualisation and will play a role in further development of CAD systems in mammography.

Changes in the availability of screening mammography, 2000-2010

BACKGROUND

Rates of screening mammography have plateaued, and the number of mammography facilities has declined in the past decade. The objective of this study was to assess changes over time and geographic disparities in the availability of mammography services.

METHODS

Using information from the US Food and Drug Administration and the US Census, county-level mammography capacity was defined as the number of mammography machines per 10,000 women aged ≥ 40 years. Cross-sectional variation and longitudinal changes in capacity were examined in relation to county characteristics.

RESULTS

Between 2000 and 2010, the number of mammography facilities declined 10% from 9434 to 8469, the number of mammography machines declined 10% from 13,100 to 11,762, and the median county mammography capacity decreased nearly 20% from 1.77 to 1.42 machines per 10,000 women aged ≥ 40 years. In cross-sectional analysis, counties with greater percentages of uninsured residents, less educated residents, greater population density, and higher managed care penetration had lower mammography capacity. Conversely, counties with more hospital beds per 100,000 population had higher capacity. High initial mammography capacity, growth in both the percentage of the population aged ≥ 65 years and the percentage living in poverty, and increased managed care penetration were all associated with a decrease in mammography capacity between 2000 and 2010. Only the percentage of rural residents was associated with an increase in capacity.

CONCLUSIONS

Geographic variation in mammography capacity and declines in capacity over time are associated with demographic, socioeconomic, and health care market characteristics. Maldistribution of mammography resources may explain geographic disparities in breast cancer screening rates.

Is confidence of mammographic assessment a good predictor of accuracy?

OBJECTIVE

Interpretive accuracy varies among radiologists, especially in mammography. This study examines the relationship between radiologists' confidence in their assessments and their accuracy in interpreting mammograms.

MATERIALS AND METHODS

In this study, 119 community radiologists interpreted 109 expert-defined screening mammography examinations in test sets and rated their confidence in their assessment for each case. They also provided a global assessment of their ability to interpret mammograms. Positive predictive value (PPV) and negative predictive value (NPV) were modeled as functions of self-rated confidence on each examination using log-linear regression estimated with generalized estimating equations. Reference measures were cancer status and expert-defined need for recall. Effect modification by weekly mammography volume was examined.

RESULTS

Radiologists who self-reported higher global interpretive ability tended to interpret more mammograms per week (p = 0.08), were more likely to specialize (p = 0.02) and to have completed a fellowship in breast or women's imaging (p = 0.05), and had a higher PPV for cancer detection (p = 0.01). Examinations for which low-volume radiologists were "very confident" had a PPV of 2.93 times (95% CI, 2.01-4.27) higher than examinations they rated with neutral confidence. Trends of increasing NPVs with increasing confidence were significant for low-volume radiologists relative to noncancers (p = 0.01) and expert nonrecalls (p < 0.001). A trend of significantly increasing NPVs existed for high-volume radiologists relative to expert nonrecall (p = 0.02) but not relative to noncancer status (p = 0.32).

CONCLUSION

Confidence in mammography assessments was associated with better accuracy, especially for low-volume readers. Asking for a second opinion when confidence in an assessment is low may increase accuracy.

Association between time spent interpreting, level of confidence, and accuracy of screening mammography

OBJECTIVE

The objective of this study was to examine the effect of time spent viewing images and level of confidence on a screening mammography test set on interpretive performance.

MATERIALS AND METHODS

Radiologists from six mammography registries participated in this study and were randomized to interpret one of four test sets and complete 12 survey questions. Each test set had 109 cases of digitized four-view screening screen-film mammograms with prior comparison screening views. Viewing time for each case was defined as the cumulative time spent viewing all mammographic images before recording which visible feature, if any, was the "most significant finding." Log-linear regression fit via the generalized estimating equation was used to test the effect of viewing time and level of confidence in the interpretation on test set sensitivity and false-positive rate.

RESULTS

One hundred nineteen radiologists completed a test set and contributed data on 11,484 interpretations. The radiologists spent more time viewing cases that had significant findings or cases for which they had less confidence in their interpretation. Each additional minute of viewing time increased the probability of a true-positive interpretation among cancer cases by 1.12 (95% CI, 1.06-1.19; p < 0.001) regardless of confidence in the assessment. Among the radiologists who were very confident in their assessment, each additional minute of viewing time increased the adjusted risk of a false-positive interpretation among noncancer cases by 1.42 (95% CI, 1.21-1.68), and this viewing-time effect diminished with decreasing confidence.

CONCLUSION

Longer interpretation times and higher levels of confidence in an interpretation are both associated with higher sensitivity and false-positive rates in mammography screening.

An observer study for a computer-aided reading protocol (CARP) in the screening environment for digital mammography

RATIONALE AND OBJECTIVES

The aims of this study were to investigate improving work flow efficiency by shortening the reading time of digital mammograms using a computer-aided reading protocol (CARP) in the screening environment and to increase detection sensitivity using CARP, compared to the current protocol, commonly referred to as the quadrant view (QV).

MATERIALS AND METHODS

A total of 200 cases were selected for a receiver-operating characteristic (ROC) study to evaluate two image display work flows, CARP and QV, in the screening environment. A Web-based tool was developed for scoring, reporting, and statistical analysis. Cases were scored for and stratified by difficulty. A total of six radiologists of differing levels of training ranging from dedicated mammographers to senior radiology residents participated. Each was timed while interpreting the 200 cases in groups of 50, first using QV and then, after a washout period, using CARP. The data were analyzed using ROC and κ analysis. Interpretation times were also assessed.

RESULTS

Using QV, readers' average area under the ROC curve was 0.68 (range, 0.54-0.73). Using CARP, readers' average area under the ROC curve was 0.71 (range, 0.66-0.75). There was no statistically significant difference in reader performance using either work flow. However, there was a statistically significant reduction in the average interpretation time of negative cases from 64.7 seconds using QV to 58.8 seconds using CARP.

CONCLUSIONS

CARP determines the display order of regions of interest depending on computer-aided detection findings. This is a variation of traditional computer-aided detection for digital mammography that has the potential to reduce interpretation times of studies with negative findings without significantly affecting sensitivity, thus allowing improved work flow efficiency in the screening environment, in which, in most settings, the majority of cases are negative.

Detection of microcalcifications on digital screening mammograms using varying degrees of monitor zooming

OBJECTIVE

The American College of Radiology recommends that mammogram images be viewed at 100% resolution (also called one-to-one or full resolution). We tested the effect of this and three other levels of zooming on the ability of radiologists to identify malignant calcifications on screening mammographic views.

MATERIALS AND METHODS

Seven breast imagers viewed 77 mammographic images, 32 with and 45 without malignant microcalcifications, using four different degrees of monitor zooming. The readers indicated whether they thought a cluster of potentially malignant calcifications was present and where the cluster was located. Tested degrees of zooming included fit screen, a size midway between fit screen and 100%, 100%, and a size slightly larger than 100%.

RESULTS

Readers failed to detect 17 clusters of malignant calcifications with fit-screen images, 12 clusters with midway images, 13 clusters with 100% images, and 11 clusters with slightly larger images. When viewing images without malignant microcalcifications, the readers marked false-positive areas on 25 images using fit-screen images, 43 of the midway images, 40 of the 100% images, and 29 of the slightly larger images.

CONCLUSION

All four tested levels of zooming functioned well. There was a trend for the fit-screen images to function slightly less well than the others with regard to sensitivity, so it may not be prudent to rely on those images without other levels of zooming. The 100% resolution images did not function noticeably better than the others.

Is computer aided detection (CAD) cost effective in screening mammography? A model based on the CADET II study

BACKGROUND

Single reading with computer aided detection (CAD) is an alternative to double reading for detecting cancer in screening mammograms. The aim of this study is to investigate whether the use of a single reader with CAD is more cost-effective than double reading.

METHODS

Based on data from the CADET II study, the cost-effectiveness of single reading with CAD versus double reading was measured in terms of cost per cancer detected. Cost (Pound (£), year 2007/08) of single reading with CAD versus double reading was estimated assuming a health and social service perspective and a 7 year time horizon. As the equipment cost varies according to the unit size a separate analysis was conducted for high, average and low volume screening units. One-way sensitivity analyses were performed by varying the reading time, equipment and assessment cost, recall rate and reader qualification.

RESULTS

CAD is cost increasing for all sizes of screening unit. The introduction of CAD is cost-increasing compared to double reading because the cost of CAD equipment, staff training and the higher assessment cost associated with CAD are greater than the saving in reading costs. The introduction of single reading with CAD, in place of double reading, would produce an additional cost of £227 and £253 per 1,000 women screened in high and average volume units respectively. In low volume screening units, the high cost of purchasing the equipment will results in an additional cost of £590 per 1,000 women screened.One-way sensitivity analysis showed that the factors having the greatest effect on the cost-effectiveness of CAD with single reading compared with double reading were the reading time and the reader's professional qualification (radiologist versus advanced practitioner).

CONCLUSIONS

Without improvements in CAD effectiveness (e.g. a decrease in the recall rate) CAD is unlikely to be a cost effective alternative to double reading for mammography screening in UK. This study provides updated estimates of CAD costs in a full-field digital system and assessment cost for women who are re-called after initial screening. However, the model is highly sensitive to various parameters e.g. reading time, reader qualification, and equipment cost.

Cost and cost-effectiveness of digital mammography compared with film-screen mammography in Australia

OBJECTIVE

A systematic review assessed the relative safety and effectiveness of digital mammography compared with film-screen mammography. This study utilised the evidence from the review to examine the economic value of digital compared with film-screen mammography in Australia.

METHODS

A cost-comparison analysis between the two technologies was conducted for the overall population for the purposes of breast cancer screening and diagnosis. In addition, a cost-effectiveness analysis was conducted for the screening subgroups where digital mammography was considered to be more accurate than film-screen mammography.

RESULTS

Digital mammography in a screening setting is $11 more per examination than film-screen mammography, and $36 or $33 more per examination in a diagnostic setting when either digital radiography or computed radiography is used. In both the screening and diagnostic settings, the throughput of the mammography system had the most significant impact on decreasing the incremental cost/examination/year of digital mammography.

CONCLUSION

Digital mammography is more expensive than film-screen mammography. Whether digital mammography represents good value for money depends on the eventual life-years and quality-adjusted life-years gained from the early cancer diagnosis.

IMPLICATIONS

The evidence generated from this study has informed the allocation of public resources for the screening and diagnosis of breast cancer in Australia.

Comparison of image acquisition and radiologist interpretation times in a diagnostic mammography center

RATIONALE AND OBJECTIVES

The purpose of this study was to determine the acquisition and interpretation times of screen-film mammography and soft-copy digital mammography in a diagnostic mammography center.

MATERIALS AND METHODS

The study was conducted in three phases for patients presenting for clinical diagnostic workup to a mammography clinic. In the first phase, technologist acquisition and processing times and radiologist interpretation time were measured for patients imaged with a screen-film mammographic system. During the second phase of the study, times were measured for patients imaged with a direct radiographic digital mammographic system, with interpretation performed on a soft-copy display system. During the third phase, 3 months after installation of the soft-copy display system, times were measured again for patients imaged on the same direct radiographic digital mammographic system, with interpretation with the same soft-copy system. The same four experienced breast imaging radiologists and seven technologists participated in all phases of the study. All data were entered into a database, and statistical analysis was conducted using weighted linear models and logarithmic transformation.

RESULTS

Times were obtained for 295 patients. There were 100 patients each for phases 1 and 2 and 95 patients for phase 3. Diagnostic mammographic acquisition times with processing were 13.02 min/case for screen film (phase 1), 8.16 min/case for digital (phase 2), and 10.66 min/case for digital (phase 3) (P < .001 and P < .0001, respectively). In addition, the radiologist interpretation time for digital mammography in both phases was not significantly different from that for film mammography (P = .2853 and P = .2893, respectively). There was no significant difference between phases 2 and 3 (P = 1.0000). The mean interpretation times were 3.75 min/case for screen film, 2.14 min/case for digital (phase 2), and 2.26 min/case for digital (phase 3).

CONCLUSIONS

Digital mammography significantly shortened the acquisition time for diagnostic mammography. There was no significant difference in interpretation time compared to screen-film mammography in a diagnostic mammography setting.

Conspicuity of microcalcifications on digital screening mammograms using varying degrees of monitor zooming

RATIONALE AND OBJECTIVES

American College of Radiology guidelines suggest that digital screening mammographic images should be viewed at the full resolution at which they were acquired. This slows interpretation speed. The aim of this study was to examine the effect of various levels of zooming on the detection and conspicuity of microcalcifications.

MATERIALS AND METHODS

Six radiologists viewed 40 mammographic images five times in different random orders using five different levels of zooming: full resolution (100%) and 30%, 61%, 88%, and 126% of that size. Thirty-three images contained microcalcifications varying in subtlety, all associated with breast cancer. The clusters were circled. Seven images contained no malignant calcifications but also had randomly placed circles. The radiologists graded the presence or absence and visual conspicuity of any calcifications compared to calcifications in a reference image. They also counted the microcalcifications.

RESULTS

The radiologists saw the microcalcifications in 94% of the images at 30% size and in either 99% or 100% of the other tested levels of zooming. Conspicuity ratings were worst for the 30% size and fairly similar for the others. Using the 30% size, two radiologists failed to see the microcalcifications on either the craniocaudal or mediolateral oblique view taken from one patient. Interobserver agreement regarding the number of calcifications was lowest for the 30% images and second lowest for the 100% images.

CONCLUSIONS

Images at 30% size should not be relied on alone for systematic scanning for microcalcifications. The other four levels of magnification all performed well enough to warrant further testing.

Performance of computer-aided detection applied to full-field digital mammography in detection of breast cancers

OBJECTIVE

The aim of this retrospective study was to evaluate performance of computer-aided detection (CAD) with full-field digital mammography (FFDM) in detection of breast cancers.

MATERIALS AND METHODS

CAD was retrospectively applied to standard mammographic views of 127 cases with biopsy proven breast cancers detected with FFDM (Senographe 2000, GE Medical Systems). CAD sensitivity was assessed in total group of 127 cases and for subgroups based on breast density, mammographic lesion type, mammographic lesion size, histopathology and mode of presentation.

RESULTS

Overall CAD sensitivity was 91% (115 of 127 cases). There were no statistical differences (p > 0.1) in CAD detection of cancers in dense breasts 90% (53/59) versus non-dense breasts 91% (62/68). There was statistical difference (p < 0.05) in CAD detection of cancers that appeared mammographically as microcalcifications only versus other mammographic manifestations. CAD detected 100% (44/44) of cancers manifesting as microcalcifications, 89% (47/53) as no-calcified masses or asymmetries, 88% (14/16) as masses with associated calcifications, and 71% (10/14) as architectural distortions. CAD sensitivity for cancers 1-10mm was 84% (38/45); 11-20mm 93% (55/59); and >20mm 97% (22/23).

CONCLUSION

CAD applied to FFDM showed 100% sensitivity in identifying cancers manifesting as microcalcifications only and high sensitivity 86% (71/83) for other mammographic appearances of cancer. Sensitivity is influenced by lesion size. CAD in FFDM is an adjunct helping radiologist in early detection of breast cancers.

Comparison of soft-copy and hard-copy reading for full-field digital mammography

PURPOSE

To compare radiologists' performance in detecting breast cancer when reading full-field digital mammographic (FFDM) images either displayed on monitors or printed on film.

MATERIALS AND METHODS

This study received investigational review board approval and was HIPAA compliant, with waiver of informed consent. A reader study was conducted in which 26 radiologists read screening FFDM images displayed on high-resolution monitors (soft-copy digital) and printed on film (hard-copy digital). Three hundred thirty-three cases were selected from the Digital Mammography Image Screening Trial screening study (n = 49,528). Of these, 117 were from patients who received a diagnosis of breast cancer within 15 months of undergoing screening mammography. The digital mammograms were displayed on mammographic workstations and printed on film according to the manufacturer's specifications. Readers read both hard-copy and soft-copy images 6 weeks apart. Each radiologist read a subset of the total images. Twenty-two readers were assigned to evaluate images from one of three FFDM systems, and four readers were assigned to evaluate images from two mammographic systems. Each radiologist assigned a malignancy score on the basis of overall impression by using a seven-point scale, where 1 = definitely not malignant and 7 = definitely malignant.

RESULTS

There were no significant differences in the areas under the receiver operating characteristic curves (AUCs) for the primary comparison. The AUCs for soft-copy and hard-copy were 0.75 and 0.76, respectively (95% confidence interval: -0.04, 0.01; P = .36). Secondary analyses showed no significant differences in AUCs on the basis of manufacturer type, lesion type, or breast density.

CONCLUSION

Soft-copy reading does not provide an advantage in the interpretation of digital mammograms. However, the display formats were not optimized and display software remains an evolving process, particularly for soft-copy reading.

Why does it take longer to read digital than film-screen screening mammograms? A partial explanation

Digital screening mammograms (DM) take longer to interpret than film-screen screening mammograms (FSM). We evaluated what part of the process takes long in our reading environment. We selected cases from those for which timed readings had been performed as part of a previous study. Readers were timed as they performed various computer manipulations on groups of DM cases and as they moved the alternator and adjusted lighting and manual shutters for FSM cases. Subtracting manipulation time from the original interpretation times yielded estimated times to reach a decision. Manipulation times for DM ranged from a low of 11 s when four-view DM were simply opened and closed in a 4-on-1 hanging protocol before moving on to the next study to 113.8 s when each view of six-view DM were brought up 1-on-1, enlarged to 100% resolution, and panned through. Manipulation times for groups of FSM ranged from 8.3 to 12.1 s. Estimated decision-making times for DM ranged from 128.0 to 202.2 s, while estimated decision-making time for FSM ranged from 60.9 to 146.3 s. Computer manipulation time partially explains the discrepancy in interaction times between DM and FSM. Radiologists also appear to spend more time looking at DM than at FSM before making a decision.

Timed efficiency of interpretation of digital and film-screen screening mammograms

OBJECTIVE

Our objective was to compare interpretation speeds for digital and film-screen screening mammograms to test whether other variables might affect interpretation times and thus contribute to the apparent difference in interpretation speed between digital mammograms and film-screen mammograms, and to test whether the use of digital rather than film comparison studies might result in significant time savings.

MATERIALS AND METHODS

Four readers were timed in the course of actual clinical interpretation of digital mammograms and film-screen mammograms. Interpretation times were compared for subgroups of studies based on the interpretation of the study by BI-RADS code, the number of images, the presence or absence of comparison studies and the type of comparison study, and whether the radiologist personally selected and hung additional films; the same comparisons were made among individual readers.

RESULTS

For all four readers, mean interpretation times were longer for digital mammograms than for film-screen mammograms, with differences ranging from 76 to 202 seconds. The difference in interpretation speed between digital and film-screen mammograms was independent of other variables. Digital mammogram interpretation times were significantly longer than film-screen mammogram interpretation times regardless of whether the digital mammograms were matched with film or digital comparison studies.

CONCLUSION

In screening mammography interpretation, digital mammograms take longer to read than film-screen mammograms, independent of other variables. Exclusive use of digital comparison studies may not cause interpretation times to drop enough to approach the interpretation time required for film-screen mammograms.

Results of a survey on digital screening mammography: prevalence, efficiency, and use of ancillary diagnostic AIDS

OBJECTIVE

As the use of full-field digital screening mammography grows rapidly, this study was conducted to determine the time required to interpret digital soft-copy (filmless) mammography compared with conventional film-screen screening mammography and to evaluate radiologists' use of ancillary diagnostic aids when interpreting digital mammography (DM) and conventional film-screen mammography (FSM).

MATERIALS AND METHODS

An 18-question survey was sent to 1,703 members of the Society of Breast Imaging, whose e-mail addresses were provided by the society. After subtracting those from whom out-of-office e-mail responses were received and three who wrote back to exclude themselves, there were 1,659 potential participants. Data from the respondents were collected and analyzed by tabulation and cross-tabulation.

RESULTS

In total, 396 members of the Society of Breast Imaging completed and returned surveys, for a 23.9% response rate. Of the respondents, 49.0% said that they had access to and interpreted DM. Their estimated average time to read a single digital mammographic study was 2.6 minutes, compared with 2.0 minutes for reading a single film-screen mammographic study. Therefore, the perceived time difference was 0.6 minutes. Magnification was the main ancillary diagnostic aid used in interpreting both DM and FSM: 74.2% of respondents used computer-based magnification at least half the time in interpreting DM, and 90.9% used optical magnification at least half the time in interpreting FSM. Optical magnification was also used by 28.5% of respondents at least half the time in interpreting DM. The respondents also used computer-aided detection frequently: 91.0% and 76.3% of those who had computer-aided detection available said that they used it at least 75% of the time in interpreting DM and FSM, respectively.

CONCLUSION

Digital mammography takes longer to interpret than FSM. Radiologists use various ancillary diagnostic aids, but magnification and computer-aided detection are the two most commonly used aids.

Issues to consider in converting to digital mammography

This article outlines the reasons that many radiology practices are converting to digital mammography. In addition, it provides basic information about the issues that must be considered in making the transformation. These issues include technical matters regarding image display, storage, and retrieval as well as clinical and ergonomic considerations.

Digital mammography: what do we and what don't we know?

High-quality full-field digital mammography has been available now for several years and is increasingly used for both diagnostic and screening mammography. A number of different detector technologies exist, which all have their specific advantages and disadvantages. Diagnostic accuracy of digital mammography has been shown to be at least equivalent to film-screen mammography in a general screening population. Digital mammography is superior to screen-film mammography in younger women with dense breasts due to its ability to selectively optimize contrast in areas of dense parenchyma. This advantage is especially important in women with a genetic predisposition for breast cancer, where intensified early detection programs may have to start from 25 to 30 years of age. Tailored image processing and computer-aided diagnosis hold the potential to further improve the early detection of breast cancer. However, at present no consensus exists among radiologists on which processing is optimal for digital mammograms. Image processing may also vary significantly among vendors with so far limited interoperability. This review aims to summarize the available information regarding the impact of digital mammography on workflow and breast cancer diagnosis.

How to Transition to Digital Mammography

To date, the transition to digital mammography has been cumbersome and difficult. In part, this is because digital mammography equipment could not be easily integrated into preexisting picture archiving and communication systems (PACS). Until the results of the ACR Imaging Network Digital Mammographic Imaging Screening Trial showed that digital mammography is more accurate than screen-film mammography for some patients, users have been reticent to switch. To make the transition as seamless as possible, several considerations should be made. First, an evaluation of a facility's current screen-film situation, including the condition of the analog units, work flow, patient capacity, staffing, and existing PACS components helps in understanding current status more clearly. After that, the facility's goals for a digital department should be determined. Next, the components of the digital imaging chain, the network infrastructure, and the PACS, as well as what clinical aspects each part of the chain affects, must be understood to avoid unexpected frustrations after the conversion is made. Then, education is required on the different acquisition options, display options, printing options, and archival options to facilitate the choice of equipment that will meet the digital goals set forth previously. Finally, a pace of conversion that is best suited to the facility should be determined.