Trends in Recall, Biopsy, and Positive Biopsy Rates for Screening Mammography in an Academic Practice

Hospital costs and cosmetic outcome of benign and high-risk breast lesions managed by vacuum-assisted excision versus surgical excision

Objectives:

Although vacuum-assisted excision (VAE) is a safe and effective alternative to surgical excision (SE), the latter is most commonly used for the management of benign and high-risk breast lesions. To evaluate the healthcare benefit of VAE, hospital costs and cosmetic outcome after VAE were compared to SE. Additionally, the impact of VAE implementation on hospital costs was investigated.

Methods:

This was a single-centre retrospective cohort study with two cohorts: “VAE” and “SE”. All patients with a benign or high-risk lesion excised by VAE or SE from January 2016 up to December 2019 were included. Cosmetic outcome was measured with the BCTOS-cosmetic subscale, and hospital costs were presented as mean (SD) and median (IQR).

Results:

During the study period, 258 patients with 295 excised lesions were included. The initial procedure was VAE in 102 patients and SE in 156 patients. Hospital costs after (median € 2324) were significantly lower than before (median € 3,144) implementation of VAE (mean difference € 1,004, p < 0.001), most likely attributable to the lower costs for patients treated with VAE (mean difference € 1,979, p < 0.001). Mean cosmetic outcome was comparable between VAE (median 1.35) and SE (median 1.44, p = 0.802).

Conclusions:

Implementing VAE as an alternative treatment option for benign and high-risk breast lesions resulted in a large decrease in hospital costs but a cosmetic benefit of VAE could not be demonstrated in this retrospective study.

Advances in knowledge:

Costs associated with the complete patient pathway were included and not only VAE was compared to SE but also the before cohort was compared to the after cohort to demonstrate the benefit of VAE implementation in clinical practice. Additionally, cosmetic outcome was compared between VAE and SE using patient reported outcome measures.

Patient reported cosmetic outcome after vacuum assisted excision of benign breast lesions: a cross-sectional study

OBJECTIVE

Better cosmetic outcome after vacuum assisted excision (VAE) compared to surgical excision of benign breast lesions is suggested in previous studies but has never been evaluated with validated outcome measures. In this study, patient reported cosmetic outcome after VAE was evaluated.

METHODS

Patients who underwent VAE between July 2017 and December 2018 were invited to complete the cosmetic subscale of the Dutch Breast Cancer Treatment Outcome Scale, comparing the treated with the untreated breast. Response mode ranged from 1 (no difference) to 4 (large difference) and cosmetic outcome was calculated as the unweighted mean. Clinical outcomes included: tumor size, number of cores, complications, residual lesions and recurrences.

RESULTS

Response rate was 73.4% (47 of 64 patients). Median tumor size was 15 mm (range 5-51 mm) and median number of cores 6.5 (range 1-85), complete excision was confirmed in all but two patients. Mean cosmetic outcome was good (mean score ≤1.75) in 74% of patients and no patients reported a poor cosmetic outcome (mean score >3.25). A hematoma occurred in five patients (one needed aspiration) and a skin rash in one patient, no patients developed an infection or seroma.

CONCLUSION

In this study VAE is safe and effective for tumors up to 5 cm and patient reported cosmetic outcome was good. Patients with benign lesions could benefit from VAE as an alternative for surgical excision.

ADVANCES IN KNOWLEDGE

A formal quantitative measurement of cosmetic outcome after vacuum assisted excision for benign breast lesions was still lacking. This study shows that this cosmetic outcome is overall good in benign lesions up to 5 cm.

An analysis of 11.3 million screening tests examining the association between needle biopsy rates and cancer detection rates in the English NHS Breast Cancer Screening Programme

AIM

To examine the association between recall, needle biopsy, and cancer detection rates to inform the setting of target ranges to optimise the benefit to harm ratio of breast screening programmes.

MATERIALS AND METHODS

Annual screening programme information from 2009/10 to 2015/16 for the 80 screening units of the English National Health Service Breast Screening Programme (totalling 11.3 million screening tests) was obtained from annual (KC62) returns. Linear regression models were used to examine the association between needle biopsy rates and recall rates and non-linear regression models to examine the association between cancer detection rates and needle biopsy rates.

RESULTS

The models show and quantify the diminishing returns for prevalent screens with increasing biopsy rates. A biopsy rate increase from 10 to 20 per 1,000 increases the cancer detection rate by 2.13 per 1,000 with four extra biopsies per extra cancer detected. Increasing the biopsy rate from 40 to 50 per 1,000, increases the cancer detection rate by only 0.25 per 1,000, with 40 extra biopsies per extra cancer detected. Although diminishing returns are also seen at incident screens, screening is generally more efficient.

CONCLUSIONS

Increasing needle biopsy rates leads to rapidly diminishing returns in cancer detection and a marked increase in non-malignant/benign needle biopsies. Much of the harms associated with screening in terms of false-positive recall rates and non-cancer biopsies occur at prevalent screens with much lower rates at incident screens. Needle biopsy rate targets should be considered together with recall rate targets to maximise benefit and minimise harm.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

The Science of Quality Improvement

Scientific rigor should be consistently applied to quality improvement (QI) research to ensure that healthcare interventions improve quality and patient safety before widespread implementation. This article provides an overview of the various study designs that can be used for QI research depending on the stage of investigation, scope of the QI intervention, constraints on the researchers and intervention being studied, and evidence needed to support widespread implementation. The most commonly used designs in QI studies are quasi-experimental designs. Randomized controlled trials and cluster randomized trials are typically reserved for large-scale research projects evaluating the effectiveness of QI interventions that may be implemented broadly, have more than a minimal impact on patients, or are costly. Systematic reviews of QI studies will play an important role in providing overviews of evidence supporting particular QI interventions or methods of achieving change. We also review the general requirements for developing quality measures for reimbursement, public reporting, and pay-for-performance initiatives. A critical part of the testing process for quality measures includes assessment of feasibility, reliability, validity, and unintended consequences. Finally, publication and critical appraisal of QI work is discussed as an essential component to generating evidence supporting QI initiatives in radiology.

Differential diagnosis of idiopathic granulomatous mastitis and breast cancer using acoustic radiation force impulse imaging

PURPOSE

Differentiation of idiopathic granulomatous mastitis (IGM) from carcinoma with routine imaging methods, such as ultrasonography (US) and mammography, is difficult. Therefore, we evaluated the value of a newly developed noninvasive technique called acoustic radiation force impulse imaging in differentiating IGM versus malignant lesions in the breast.

METHODS

Four hundred and eighty-six patients, who were referred to us with a presumptive diagnosis of a mass, underwent Virtual Touch tissue imaging (VTI; Siemens) and Virtual Touch tissue quantification (VTQ; Siemens) after conventional gray-scale US. US-guided percutaneous needle biopsy was then performed on 276 lesions with clinically and radiologically suspicious features. Malignant lesions (n = 122) and IGM (n = 48) were included in the final study group.

RESULTS

There was a statistically significant difference in shear wave velocity marginal and internal values between the IGM and malignant lesions. The median marginal velocity for IGM and malignant lesions was 3.19 m/s (minimum-maximum 2.49-5.82) and 5.05 m/s (minimum-maximum 2.09-8.46), respectively (p < 0.001). The median internal velocity for IGM and malignant lesions was 2.76 m/s (minimum-maximum 1.14-4.12) and 4.79 m/s (minimum-maximum 2.12-8.02), respectively (p < 0.001).

CONCLUSION

The combination of VTI and VTQ as a complement to conventional US provides viscoelastic properties of tissues, and thus has the potential to increase the specificity of US.

The Use of Ultrasound in Breast Cancer Screening of Asymptomatic Women with Dense Breast Tissue: A Narrative Review

INTRODUCTION

Mammography is the standard screening modality for breast cancer; however, sensitivity reduces with increasing breast density, resulting in the potential for masking of cancer. Ultrasound is a potential supplemental screening tool, but its routine use is controversial.

METHODS

A database search was performed with keywords "ultrasound" and "breast density and screening", including variations. Articles were included if they assessed the use of hand-held ultrasound as a supplemental screening modality in women with dense breasts.

DISCUSSION

Twelve articles were identified. No high-level evidence articles were identified. Cancer detection rates increased with the addition of ultrasound-to-mammography screening protocols. However, this was associated with increased costs per cancer detected, an increased biopsy rate, and a low positive predictive value. The survival benefit, cost versus benefit, and psychological impact of the addition of ultrasound is unknown.

CONCLUSIONS

The addition of ultrasound to a screening program in an asymptomatic population of women with dense breast tissue detects additional cancers compared with mammography alone. Knowledge regarding a survival or cost benefit associated with increased cancer detection, and the psychological impact of the addition of ultrasound is unknown. Further research is needed to assess whether the addition of ultrasound is cost-effective with respect to clinical outcome and survival.

Is the false-positive rate in mammography in North America too high?

The practice of investigating pathological abnormalities in the breasts of females who are asymptomatic is primarily employed using X-ray mammography. The importance of breast screening is reflected in the mortality-based benefits observed among females who are found to possess invasive breast carcinoma prior to the manifestation of clinical symptoms. It is estimated that population-based screening constitutes a 17% reduction in the breast cancer mortality rate among females affected by invasive breast carcinoma. In spite of the significant utility that screening confers in those affected by invasive cancer, limitations associated with screening manifest as potential harms affecting individuals who are free of invasive disease. Disease-free and benign tumour-bearing individuals who are subjected to diagnostic work-up following a screening examination constitute a population of cases referred to as false positives (FPs). This article discusses factors contributing to the FP rate in mammography and extends the discussion to an assessment of the consequences associated with FP reporting. We conclude that the mammography FP rate in North America is in excess based upon the observation of overtreatment of in situ lesions and the disproportionate distribution of detriment and benefit among the population of individuals recalled for diagnostic work-up subsequent to screening. To address the excessive incidence of FPs in mammography, we investigate solutions that may be employed to remediate the current status of the FP rate. Subsequently, it can be suggested that improvements in the breast-screening protocol, medical litigation risk, image interpretation software and the implementation of image acquisition modalities that overcome superimposition effects are promising solutions.

Step-by-step of ultrasound-guided core-needle biopsy of the breast: review and technique

Ultrasound-guided core-needle biopsy has high sensitivity in the diagnosis of breast cancer. The present study is aimed at detailing the main steps of such procedure, including indications, advantages, limitations, follow-up and description of the technique, besides presenting a checklist including the critical steps required for an appropriate practice of the technique. In the recent years, an increasing number of patients have required breast biopsy, indicating the necessity of a proportional increase in the number of skilled professionals to carry out the procedures and histological diagnoses. A multidisciplinary approach involving the tripod clinical practice-radiology-pathology is responsible for the highest rate of accuracy of the technique and must always be adopted.

Inference based on diagnostic measures from studies of new imaging devices

RATIONALE AND OBJECTIVES

Before using a new diagnostic imaging device regularly in a clinic, it should be studied using patients and radiologists. Often such studies report diagnostic performance in terms of sensitivity, specificity, area under the receiver operating characteristic curve (AUC), or differences thereof. In this report we look at how these studies differ from actual future clinical practice and how those differences may affect reported performance measures.

MATERIALS AND METHODS

We review signal detection (receiver operating characteristic) theory and decision theory. We compare diagnostic measures from several published studies in medical imaging and examine how they relate to theory and each other.

RESULTS

We see that clinical decisions can be modeled using signal detection and decision theories. Sensitivity and specificity are inextricably linked with clinical factors, such as prevalence and costs. Imaging devices are used in many different ways in clinical practice, so that sensitivities, specificities, and AUCs measured in studies of new diagnostic imaging devices will differ from those in actual future clinical use.

CONCLUSIONS

Measured sensitivities, specificities, and the directions of changes thereof are not necessarily consistent or reproducible across studies of new diagnostic devices. A change in the AUC, which should be independent of clinical costs or prevalence, is a consistent measure across similar studies, and a positive change in AUC is indicative of additional diagnostic information that will be available to radiologists in a future clinical environment.

Analysis of shear strain imaging for classifying breast masses: finite element and phantom results

PURPOSE

Features extracted from axial-shear strain images of breast masses have been previously utilized to differentiate and classify benign from malignant breast masses. In this paper, we compare shear strain patterns exhibited by both the full-shear (axial and lateral component) versus only the axial-shear strain component for differentiating between bound masses (malignant) when compared to unbound masses (benign).

METHODS

We examine different breast mass characteristics such as mass shape, asymmetric location of masses, stiffness variations, and mass bonding characteristics to background tissue to assess their impact on shear strain patterns generated due to a uniaxial applied deformation. Two-dimensional finite element simulations of both circular and elliptical inclusions embedded within a uniform background were utilized. Different degrees of bonding were characterized using friction coefficient values ranging from 0.01 to 100 denoting loosely bound to firmly bound masses. Single-inclusion tissue-mimicking phantoms mimicking firmly bound and loosely bound ellipsoidal masses oriented at four different angles to the applied deformation were studied to corroborate the mass differentiation performance.

RESULTS

Our results indicate that the normalized axial-shear strain and full-shear strain area features are larger for bound when compared to unbound masses. A higher stiffness ratio or contrast between the inclusion and background also improves differentiation. Larger applied deformations reduce the discrimination performance for masses with friction coefficients lower than 0.4, due to increased mass slippage with applied deformations. Potential errors with the use of these features would occur for unbound inclusions at larger applied deformations and for asymmetric mass positions within the background normal tissue.

CONCLUSIONS

Finite element and tissue-mimicking phantom results demonstrate the feasibility of utilizing both the normalized axial-shear and full-shear strain area features to classify breast masses. Differentiation between bound or unbound masses was not affected by the mass size or shape for masses where the applied deformation is normal to the mass surface. Shear strain patterns vary significantly especially within unbound masses, when the mass surface is not normal to the applied deformation. Discrimination performance for unbound masses was improved by utilizing only the normalized shear strain area patterns located outside the mass as illustrated in this paper.

Breast cancer risk estimation with artificial neural networks revisited: discrimination and calibration

BACKGROUND

Discriminating malignant breast lesions from benign ones and accurately predicting the risk of breast cancer for individual patients are crucial to successful clinical decisions. In the past, several artificial neural network (ANN) models have been developed for breast cancer-risk prediction. All studies have reported discrimination performance, but not one has assessed calibration, which is an equivalently important measure for accurate risk prediction. In this study, the authors have evaluated whether an artificial neural network (ANN) trained on a large prospectively collected dataset of consecutive mammography findings can discriminate between benign and malignant disease and accurately predict the probability of breast cancer for individual patients.

METHODS

Our dataset consisted of 62,219 consecutively collected mammography findings matched with the Wisconsin State Cancer Reporting System. The authors built a 3-layer feedforward ANN with 1000 hidden-layer nodes. The authors trained and tested their ANN by using 10-fold cross-validation to predict the risk of breast cancer. The authors used area the under the receiver-operating characteristic curve (AUC), sensitivity, and specificity to evaluate discriminative performance of the radiologists and their ANN. The authors assessed the accuracy of risk prediction (ie, calibration) of their ANN by using the Hosmer-Lemeshow (H-L) goodness-of-fit test.

RESULTS

Their ANN demonstrated superior discrimination (AUC, 0.965) compared with the radiologists (AUC, 0.939; P<.001). The authors' ANN was also well calibrated as shown by an H-L goodness of fit P-value of .13.

CONCLUSIONS

The authors' ANN can effectively discriminate malignant abnormalities from benign ones and accurately predict the risk of breast cancer for individual abnormalities.

Early-stage invasive breast cancers: potential role of optical tomography with US localization in assisting diagnosis

PURPOSE

To investigate the potential role of optical tomography in the near-infrared (NIR) spectrum with ultrasonographic (US) localization as a means of differentiating early-stage cancers from benign lesions of the breast.

MATERIALS AND METHODS

The protocol was approved by the institutional review boards and was HIPAA compliant; all participants signed an informed consent. One hundred seventy-eight consecutive women (mean age, 52 years; range, 21-89 years) who underwent US-guided biopsy were imaged with a hand-held probe consisting of a coregistered US transducer and an NIR imager. The lesion location provided by coregistered US was used to guide optical imaging. Light absorption was measured at two optical wavelengths. From this measurement, tumor angiogenesis was assessed on the basis of calculated total hemoglobin concentration (tHb) and was correlated with core biopsy results. For patients diagnosed with carcinomas and followed up with subsequent excision, the tHb was correlated with pathologic parameters.

RESULTS

There were two in situ carcinomas (Tis), 35 T1 carcinomas, 24 T2-T4 carcinomas, and 114 benign lesions. The mean maximum and mean average tHb of the Tis-T1 group were 102.0 micromol/L +/- 28.5 (standard deviation) and 71.9 micromol/L +/- 18.8, and those of the T2-T4 group were 100.3 micromol/L +/- 26.4 and 67.0 micromol/L +/- 18.3, respectively. The mean maximum and mean average tHb of the benign group were 55.1 micromol/L +/- 22.7 and 39.1 micromol/L +/- 14.9, respectively. Both mean maximum and mean average tHb levels were significantly higher in the malignant groups than they were in the benign group (P < .001). The sensitivity, specificity, positive predictive value, and negative predictive value for Tis-T1 cancers were 92%, 93%, 81%, and 97%. The corresponding values for T2-T4 tumors were 75%, 93%, 69%, and 95%.

CONCLUSION

The angiogenesis (tHb) contrast imaged by using the NIR technique with US holds promise as an adjunct to mammography and US for distinguishing early-stage invasive breast cancers from benign lesions.

Time trends in radiologists' interpretive performance at screening mammography from the community-based Breast Cancer Surveillance Consortium, 1996-2004

PURPOSE

To examine time trends in radiologists' interpretive performance at screening mammography between 1996 and 2004.

MATERIALS AND METHODS

All study procedures were institutional review board approved and HIPAA compliant. Data were collected on subsequent screening mammograms obtained from 1996 to 2004 in women aged 40-79 years who were followed up for 1 year for breast cancer. Recall rate, sensitivity, and specificity were examined annually. Generalized estimating equation (GEE) and random-effects models were used to test for linear trend. The area under the receiver operating characteristic curve (AUC), tumor histologic findings, and size of the largest dimension or diameter of the tumor were also examined.

RESULTS

Data on 2,542,049 subsequent screening mammograms and 12,498 cancers diagnosed in the follow-up period were included in this study. Recall rate increased from 6.7% to 8.6%, sensitivity increased from 71.4% to 83.8%, and specificity decreased from 93.6% to 91.7%. In GEE models, adjusted odds ratios per calendar year were 1.04 (95% confidence interval [CI]: 1.02, 1.05) for recall rate, 1.09 (95% CI: 1.07. 1.12) for sensitivity, and 0.96 (95% CI: 0.95, 0.98) for specificity (P < .001 for all). Random-effects model results were similar. The AUC increased over time: 0.869 (95% CI: 0.861, 0.877) for 1996-1998, 0.884 (95% CI: 0.879, 0.890) for 1999-2001, and 0.891 (95% CI: 0.885, 0.896) for 2002-2004 (P < .001). Tumor histologic findings and size remained constant.

CONCLUSION

Recall rate and sensitivity for screening mammograms increased, whereas specificity decreased from 1996 to 2004 among women with a prior mammogram. This trend remained after accounting for risk factors. The net effect was an improvement in overall discrimination, a measure of the probability that a mammogram with cancer in the follow-up period has a higher Breast Imaging Reporting and Data System assessment category than does a mammogram without cancer in the follow-up period.

Differentiation of benign and malignant breast lesions by mechanical imaging

Mechanical imaging yields tissue elasticity map and provides quantitative characterization of a detected pathology. The changes in the surface stress patterns as a function of applied load provide information about the elastic composition and geometry of the underlying tissue structures. The objective of this study is the clinical evaluation of breast mechanical imager for breast lesion characterization and differentiation between benign and malignant lesions. The breast mechanical imager includes a probe with pressure sensor array, an electronic unit providing data acquisition from the pressure sensors and communication with a touch-screen laptop computer. We have developed an examination procedure and algorithms to provide assessment of breast lesion features such as hardness related parameters, mobility, and shape. A statistical Bayesian classifier was constructed to distinguish between benign and malignant lesions by utilizing all the listed features as the input. Clinical results for 179 cases, collected at four different clinical sites, have demonstrated that the breast mechanical imager provides a reliable image formation of breast tissue abnormalities and calculation of lesion features. Malignant breast lesions (histologically confirmed) demonstrated increased hardness and strain hardening as well as decreased mobility and longer boundary length in comparison with benign lesions. Statistical analysis of differentiation capability for 147 benign and 32 malignant lesions revealed an average sensitivity of 91.4% and specificity of 86.8% with a standard deviation of +/-6.1%. The area under the receiver operating characteristic curve characterizing benign and malignant lesion discrimination is 86.1% with the confidence interval ranging from 80.3 to 90.9%, with a significance level of P = 0.0001 (area = 50%). The multisite clinical study demonstrated the capability of mechanical imaging for characterization and differentiation of benign and malignant breast lesions. We hypothesize that the breast mechanical imager has the potential to be used as a cost effective device for cancer diagnostics that could reduce the benign biopsy rate, serve as an adjunct to mammography and to be utilized as a screening device for breast cancer detection.

Multi-modality CADx: ROC study of the effect on radiologists' accuracy in characterizing breast masses on mammograms and 3D ultrasound images

RATIONALE AND OBJECTIVES

To investigate the effect of a computer-aided diagnosis (CADx) system on radiologists' performance in discriminating malignant and benign masses on mammograms and three-dimensional (3D) ultrasound (US) images.

MATERIALS AND METHODS

Our dataset contained mammograms and 3D US volumes from 67 women (median age, 51; range: 27-86) with 67 biopsy-proven breast masses (32 benign and 35 malignant). A CADx system was designed to automatically delineate the mass boundaries on mammograms and the US volumes, extract features, and merge the extracted features into a multi-modality malignancy score. Ten experienced readers (subspecialty academic breast imaging radiologists) first viewed the mammograms alone, and provided likelihood of malignancy (LM) ratings and Breast Imaging and Reporting System assessments. Subsequently, the reader viewed the US images with the mammograms, and provided LM and action category ratings. Finally, the CADx score was shown and the reader had the opportunity to revise the ratings. The LM ratings were analyzed using receiver-operating characteristic (ROC) methodology, and the action category ratings were used to determine the sensitivity and specificity of cancer diagnosis.

RESULTS

Without CADx, readers' average area under the ROC curve, A(z), was 0.93 (range, 0.86-0.96) for combined assessment of the mass on both the US volume and mammograms. With CADx, their average A(z) increased to 0.95 (range, 0.91-0.98), which was borderline significant (P = .05). The average sensitivity of the readers increased from 98% to 99% with CADx, while the average specificity increased from 27% to 29%. The change in sensitivity with CADx did not achieve statistical significance for the individual radiologists, and the change in specificity was statistically significant for one of the radiologists.

CONCLUSIONS

A well-trained CADx system that combines features extracted from mammograms and US images may have the potential to improve radiologists' performance in distinguishing malignant from benign breast masses and making decisions about biopsies.

Probabilistic computer model developed from clinical data in national mammography database format to classify mammographic findings

PURPOSE

To determine whether a Bayesian network trained on a large database of patient demographic risk factors and radiologist-observed findings from consecutive clinical mammography examinations can exceed radiologist performance in the classification of mammographic findings as benign or malignant.

MATERIALS AND METHODS

The institutional review board exempted this HIPAA-compliant retrospective study from requiring informed consent. Structured reports from 48 744 consecutive pooled screening and diagnostic mammography examinations in 18 269 patients from April 5, 1999 to February 9, 2004 were collected. Mammographic findings were matched with a state cancer registry, which served as the reference standard. By using 10-fold cross validation, the Bayesian network was tested and trained to estimate breast cancer risk by using demographic risk factors (age, family and personal history of breast cancer, and use of hormone replacement therapy) and mammographic findings recorded in the Breast Imaging Reporting and Data System lexicon. The performance of radiologists compared with the Bayesian network was evaluated by using area under the receiver operating characteristic curve (AUC), sensitivity, and specificity.

RESULTS

The Bayesian network significantly exceeded the performance of interpreting radiologists in terms of AUC (0.960 vs 0.939, P = .002), sensitivity (90.0% vs 85.3%, P < .001), and specificity (93.0% vs 88.1%, P < .001).

CONCLUSION

On the basis of prospectively collected variables, the evaluated Bayesian network can predict the probability of breast cancer and exceed interpreting radiologist performance. Bayesian networks may help radiologists improve mammographic interpretation.

What is the point: will screening mammography save my life?

BACKGROUND

We analyzed the claim "mammography saves lives" by calculating the life-saving absolute benefit of screening mammography in reducing breast cancer mortality in women ages 40 to 65.

METHODS

To calculate the absolute benefit, we first estimated the screen-free absolute death risk from breast cancer by adjusting the Surveillance, Epidemiology and End Results Program 15-year cumulative breast cancer mortality to account for the separate effects of screening mammography and improved therapy. We calculated the absolute risk reduction (reduction in absolute death risk), the number needed to screen assuming repeated screening, and the survival percentages without and with screening. We varied the relative risk reduction from 10%-30% based on the randomized trials of screening mammography. We developed additional variations of the absolute risk reduction for a screening intervention, including the average benefit of a single screen, as well as the life-saving proportion among patients with earlier cancer detection.

RESULTS

Because the screen-free absolute death risk is approximately 1% overall but rises with age, the relative risk reduction from repeated screening mammography is about 100 times the absolute risk reduction between the starting ages of 50 and 60. Assuming a base case 20% relative risk reduction, repeated screening starting at age 50 saves about 1.8 (overall range, 0.9-2.7) lives over 15 years for every 1000 women screened. The number needed to screen repeatedly is 1000/1.8, or 570. The survival percentage is 99.12% without and 99.29% with screening. The average benefit of a single screening mammogram is 0.034%, or 2970 women must be screened once to save one life. Mammography saves 4.3% of screen-detectable cancer patients' lives starting at age 50. This means 23 cancers must be found starting at age 50, or 27 cancers at age 40 and 21 cancers at age 65, to save one life.

CONCLUSION

The life-saving absolute benefit of screening mammography increases with age as the absolute death risk increases. The number of events needed to save one life varies depending on the prospective screening subset or reference class. Less than 5% of women with screen-detectable cancers have their lives saved.

How does age affect baseline screening mammography performance measures? A decision model

Background

In order to promote consumer-oriented informed medical decision-making regarding screening mammography, we created a decision model to predict the age dependence of the cancer detection rate, the recall rate and the secondary performance measures (positive predictive values, total intervention rate, and positive biopsy fraction) for a baseline mammogram.

Methods

We constructed a decision tree to model the possible outcomes of a baseline screening mammogram in women ages 35 to 65. We compared the single baseline screening mammogram decision with the no screening alternative. We used the Surveillance Epidemiology and End Results national cancer database as the primary input to estimate cancer prevalence. For other probabilities, the model used population-based estimates for screening mammography accuracy and diagnostic mammography outcomes specific to baseline exams. We varied radiologist performance for screening accuracy.

Results

The cancer detection rate increases from 1.9/1000 at age 40 to 7.2/1000 at age 50 to 15.1/1000 at age 60. The recall rate remains relatively stable at 142–157/1000, which varies from 73–236/1000 at age 50 depending on radiologist performance. The positive predictive value of a screening mammogram increases from 1.3% at age 40 to 9.8% at age 60, while the positive predictive value of a diagnostic mammogram varies from 2.9% at age 40 to 19.2% at age 60. The model predicts the total intervention rate = 0.013*AGE² - 0.67*AGE + 40, or 34/1000 at age 40 to 47/1000 at age 60. Therefore, the positive biopsy (intervention) fraction varies from 6% at age 40 to 32% at age 60.

Conclusion

Breast cancer prevalence, the cancer detection rate, and all secondary screening mammography performance measures increase substantially with age.

Cost-effective screening for breast cancer worldwide: current state and future directions

Affordability of healthcare is highly limited by its skyrocketing cost. Access to screening and diagnostic medical equipment and medicine in developing countries is inadequate for the majority of the population. There is a tremendous worldwide need to detect breast cancer at its earliest stage. These needs must be balanced by the ability of countries to provide breast cancer screening technology to their populations. We reviewed the diagnostic accuracy, procedure cost and cost-effectiveness of currently available technique for breast screening and diagnosis including clinical breast examination, mammography, ultrasound, magnetic resonance imaging, biopsy and a new modality for cancer diagnostics termed elasticity imaging that has emerged in the last decade. Clinical results demonstrate that elasticity imaging even in its simplest and least sophisticated versions, like tactile imaging, has significant diagnostic potential comparable and exceeding that of conventional imaging techniques. In view of many countries with limited resources, effective yet less expensive modes of screening must be considered worldwide. The tactile imaging is one method that has the potential to provide cost-effective breast cancer screening and diagnostics.

Bayesian network to predict breast cancer risk of mammographic microcalcifications and reduce number of benign biopsy results: initial experience

PURPOSE

To retrospectively determine whether a Bayesian network (BN) computer model can accurately predict the probability of breast cancer on the basis of risk factors and mammographic appearance of microcalcifications, to improve the positive predictive value (PPV) of biopsy, with pathologic examination and follow-up as reference standards.

MATERIALS AND METHODS

The institutional review board approved this HIPAA-compliant study; informed consent was not required. Results of 111 consecutive image-guided breast biopsies performed for microcalcifications deemed suspicious by radiologists were analyzed. Mammograms obtained before biopsy were analyzed in a blinded manner by a breast imager who recorded Breast Imaging Reporting and Data System (BI-RADS) descriptors and provided a probability of malignancy. The BN uses probabilistic relationships between breast disease and mammography findings to estimate the risk of malignancy. Probability estimates from the radiologist and the BN were used to create receiver operating characteristic (ROC) curves, and area under the ROC curve (A(z)) values were compared. PPV of biopsy was also evaluated on the basis of these probability estimates.

RESULTS

The BN and the radiologist achieved A(z) values of 0.919 and 0.916, respectively, which were not significantly different. If the 34 patients estimated by the BN to have less than a 10% probability of malignancy had not undergone biopsy, the PPV of biopsy would have increased from 21.6% to 31.2% without missing a breast cancer (P < .001). At this level, the radiologist's probability estimation improved the PPV to 30.0% (P < .001).

CONCLUSION

A probabilistic model that includes BI-RADS descriptors for microcalcifications can distinguish between benign and malignant abnormalities at mammography as well as a breast imaging specialist can and may be able to improve the PPV of image-guided breast biopsy.

Improving radiologists' recommendations with computer-aided diagnosis for management of small nodules detected by CT

RATIONALE AND OBJECTIVES

To evaluate how computer-aided diagnosis (CAD) can improve radiologists' recommendations for management of possible early lung cancers on CT.

MATERIALS AND METHODS

Twenty-eight lung cancers and 28 benign lesions were employed. Each group of 28 lesions was classified into subgroups of two sizes (9 between 6 and 10 mm and 19 between 11 and 20 mm) and three patterns (8 with pure ground glass opacity [GGO], 12 with mixed GGO and 8 solid lesions). Sixteen radiologists participated in the observer study, first without and then with CAD. Radiologists' recommendations, including (1) follow-up in 12 months, (2) in 6 months, (3) in 3 months, or (4) biopsy, were compared at three levels of their malignancy probability ratings (low: 1%-33%; medium: 34%-66%; high: 67%-99%) for 896 observations (56 lesions by the 16 radiologists) in the two size subgroups and three patterns.

RESULTS

The number of recommendations changed by radiologists by use of CAD was 163 (18%) among all 896 observations. Among these changed recommendations, the fraction showing a beneficial effect from CAD was 68% (111/163), and the fraction showing a beneficial effect regarding biopsy recommendations was 69% (48/70). With CAD, the radiologists' performance regarding biopsy recommendations was significantly improved for 43 lung cancers (31 changed to biopsy versus 12 changed away from biopsy; P = .003) and was also improved for 27 benign lesions (10 changed to biopsy versus 17 changed away from biopsy; P = .18). Most of the cancers with improved recommendations were solid lesions or mixed GGO and relatively large.

CONCLUSION

CAD has the potential to improve the appropriateness of radiologists' recommendations for small malignant and benign lesions on CT scans.

Ultrasound elasticity imaging

Before the advent of diagnostic imaging, palpation was one of the main methods of clinical investigation for the evaluation of tumours. Malignant tumours feel harder that benign ones and this physical property is related to their coefficient of elasticity. Direct comparison of tissue images before and after application of a force is too crude a measure of elasticity except at extremes of differences in elasticity. Analysis of the raw imaging data, which contains very much more information than can be displayed for visual perception, can detect very much smaller differences in elasticity.

The radio frequency data of returning ultrasound echoes contain much more data than appears in an ultrasound image. Comparison, of the datasets of uncompressed tissue with compressed tissue, of a region of interest allows production of a strain (elasticity) image of that same region of interest. Change in tissue which is not visible on B-mode (greyscale) imaging can now be detected with real time strain imaging which is beginning to be developed on commercial ultrasound equipment. The information obtained with strain/elasticity imaging is now showing potential in influencing management of patients with breast problems.