Lorraine Tucker

The TOMMY trial: a comparison of TOMosynthesis with digital MammographY in the UK NHS Breast Screening Programme--a multicentre retrospective reading study comparing the diagnostic performance of digital breast tomosynthesis and digital mammography with digital mammography alone.

BACKGROUND Digital breast tomosynthesis (DBT) is a three-dimensional mammography technique with the potential to improve accuracy by improving differentiation between malignant and non-malignant lesions. OBJECTIVES The objectives of the study were to compare the diagnostic accuracy of DBT in conjunction with two-dimensional (2D) mammography or synthetic 2D mammography, against standard 2D mammography and to determine if DBT improves the accuracy of detection of different types of lesions. STUDY POPULATION Women (aged 47-73 years) recalled for further assessment after routine breast screening and women (aged 40-49 years) with moderate/high of risk of developing breast cancer attending annual mammography screening were recruited after giving written informed consent. INTERVENTION All participants underwent a two-view 2D mammography of both breasts and two-view DBT imaging. Image-processing software generated a synthetic 2D mammogram from the DBT data sets. RETROSPECTIVE READING STUDY In an independent blinded retrospective study, readers reviewed (1) 2D or (2) 2D + DBT or (3) synthetic 2D + DBT images for each case without access to original screening mammograms or prior examinations. Sensitivities and specificities were calculated for each reading arm and by subgroup analyses. RESULTS Data were available for 7060 subjects comprising 6020 (1158 cancers) assessment cases and 1040 (two cancers) family history screening cases. Overall sensitivity was 87% [95% confidence interval (CI) 85% to 89%] for 2D only, 89% (95% CI 87% to 91%) for 2D + DBT and 88% (95% CI 86% to 90%) for synthetic 2D + DBT. The difference in sensitivity between 2D and 2D + DBT was of borderline significance (p = 0.07) and for synthetic 2D + DBT there was no significant difference (p = 0.6). Specificity was 58% (95% CI 56% to 60%) for 2D, 69% (95% CI 67% to 71%) for 2D + DBT and 71% (95% CI 69% to 73%) for synthetic 2D + DBT. Specificity was significantly higher in both DBT reading arms for all subgroups of age, density and dominant radiological feature (p < 0.001 all cases). In all reading arms, specificity tended to be lower for microcalcifications and higher for distortion/asymmetry. Comparing 2D + DBT to 2D alone, sensitivity was significantly higher: 93% versus 86% (p < 0.001) for invasive tumours of size 11-20 mm. Similarly, for breast density 50% or more, sensitivities were 93% versus 86% (p = 0.03); for grade 2 invasive tumours, sensitivities were 91% versus 87% (p = 0.01); where the dominant radiological feature was a mass, sensitivities were 92% and 89% (p = 0.04) For synthetic 2D + DBT, there was significantly (p = 0.006) higher sensitivity than 2D alone in invasive cancers of size 11-20 mm, with a sensitivity of 91%. CONCLUSIONS The specificity of DBT and 2D was better than 2D alone but there was only marginal improvement in sensitivity. The performance of synthetic 2D appeared to be comparable to standard 2D. If these results were observed with screening cases, DBT and 2D mammography could benefit to the screening programme by reducing the number of women recalled unnecessarily, especially if a synthetic 2D mammogram were used to minimise radiation exposure. Further research is required into the feasibility of implementing DBT in a screening setting, prognostic modelling on outcomes and mortality, and comparison of 2D and synthetic 2D for different lesion types. STUDY REGISTRATION Current Controlled Trials ISRCTN73467396. FUNDING This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 19, No. 4. See the HTA programme website for further project information.

Accuracy of Digital Breast Tomosynthesis for Depicting Breast Cancer Subgroups in a UK Retrospective Reading Study (TOMMY Trial)

PURPOSE To compare the diagnostic performance of two-dimensional (2D) mammography, 2D mammography plus digital breast tomosynthesis (DBT), and synthetic 2D mammography plus DBT in depicting malignant radiographic features. MATERIALS AND METHODS In this multicenter, multireader, retrospective reading study (the TOMMY trial), after written informed consent was obtained, 8869 women (age range, 29-85 years; mean, 56 years) were recruited from July 2011 to March 2013 in an ethically approved study. From these women, a reading dataset of 7060 cases was randomly allocated for independent blinded review of (a) 2D mammography images, (b) 2D mammography plus DBT images, and (c) synthetic 2D mammography plus DBT images. Reviewers had no access to results of previous examinations. Overall sensitivities and specificities were calculated for younger women and those with dense breasts. RESULTS Overall sensitivity was 87% for 2D mammography, 89% for 2D mammography plus DBT, and 88% for synthetic 2D mammography plus DBT. The addition of DBT was associated with a 34% increase in the odds of depicting cancer (odds ratio [OR] = 1.34, P = .06); however, this level did not achieve significance. For patients aged 50-59 years old, sensitivity was significantly higher (P = .01) for 2D mammography plus DBT than it was for 2D mammography. For those with breast density of 50% or more, sensitivity was 86% for 2D mammography compared with 93% for 2D mammography plus DBT (P = .03). Specificity was 57% for 2D mammography, 70% for 2D mammography plus DBT, and 72% for synthetic 2D mammography plusmDBT. Specificity was significantly higher than 2D mammography (P < .001in both cases) and was observed for all subgroups (P < .001 for all cases). CONCLUSION The addition of DBT increased the sensitivity of 2D mammography in patients with dense breasts and the specificity of 2D mammography for all subgroups. The use of synthetic 2D DBT demonstrated performance similar to that of standard 2D mammography with DBT. DBT is of potential benefit to screening programs, particularly in younger women with dense breasts. (©) RSNA, 2015.

Digital breast tomosynthesis (DBT): a review of the evidence for use as a screening tool

Breast screening with full-field digital mammography (FFDM) fails to detect 15-30% of cancers. This figure is higher for women with dense breasts. A new tomographic technique in mammography has been developed--digital breast tomosynthesis (DBT)--which allows images to be viewed in sections through the breast and has the potential to improve cancer detection rates. Results from retrospective reading studies comparing DBT with FFDM have been largely favourable with improvement in sensitivity and specificity. Increases in diagnostic accuracy have been reported as being independent of breast density; however there are mixed reports regarding the detection of microcalcification. Prospective screening studies using DBT with FFDM have demonstrated increased rates in cancer detection compared with FFDM alone. A reduction in false-positive recall rates has also been shown. Screening with the addition of DBT would approximately double radiation dose; however a simulated FFDM image can be generated from a DBT scan. The combination of simulated FFDM images and DBT is being evaluated within several studies and some positive results have been published. Interval cancer rates for the UK National Health Service Breast Screening Programme (NHSBSP) demonstrate the limited sensitivity of FFDM in cancer detection. DBT has the potential to increase sensitivity and decrease false-positive recall rates. It has approval for screening and diagnostics in several countries; however, there are issues with DBT as a screening tool including additional reading time, IT storage and connectivity, over-diagnosis, and cost effectiveness. Feasibility and cost-effectiveness trials are needed before the implementation of DBT in NHSBSP can be considered.

Mammographic breast density: comparison of methods for quantitative evaluation.

PURPOSE To evaluate the results from two software tools for measurement of mammographic breast density and compare them with observer-based scores in a large cohort of women. MATERIALS AND METHODS Following written informed consent, a data set of 36 281 mammograms from 8867 women were collected from six United Kingdom centers in an ethically approved trial. Breast density was assessed by one of 26 readers on a visual analog scale and with two automated density tools. Mean differences were calculated as the mean of all the individual percentage differences between each measurement for each case (woman). Agreement in total breast volume, fibroglandular volume, and percentage density was assessed with the Bland-Altman method. Association with observers scores was calculated by using the Pearson correlation coefficient (r). RESULTS Correlation between the Quantra and Volpara outputs for total breast volume was r = 0.97 (P < .001), with a mean difference of 43.5 cm(3) for all cases representing 5.0% of the mean total breast volume. Correlation of the two measures was lower for fibroglandular volume (r = 0.86, P < .001). The mean difference was 30.3 cm(3) for all cases representing 21.2% of the mean fibroglandular tissue volume result. Quantra gave the larger value and the difference tended to increase with volume. For the two measures of percentage volume density, the mean difference was 1.61 percentage points (r = 0.78, P < .001). Comparison of observers scores with the area-based density given by Quantra yielded a low correlation (r = 0.55, P < .001). Correlations of observers scores with the volumetric density results gave r values of 0.60 (P < .001) and 0.63 (P < .001) for Quantra and Volpara, respectively. CONCLUSION Automated techniques for measuring breast density show good correlation, but these are poorly correlated with observers scores. However automated techniques do give different results that should be considered when informing patient personalized imaging. (©) RSNA, 2015 Clinical trial registration no. ISRCTN 73467396.

Does Reader Performance with Digital Breast Tomosynthesis Vary according to Experience with Two-dimensional Mammography?

Purpose To assess whether individual reader performance with digital breast tomosynthesis (DBT) and two-dimensional (2D) mammography varies with number of years of experience or volume of 2D mammograms read. Materials and Methods After written informed consent was obtained, 8869 women (age range, 29-85 years; mean age, 56 years) were recruited into the TOMMY trial (A Comparison of Tomosynthesis with Digital Mammography in the UK National Health Service Breast Screening Program), an ethically approved, multicenter, multireader, retrospective reading study, between July 2011 and March 2013. Each case was read prospectively for clinical assessment and to establish ground truth. A retrospective reading data set of 7060 cases was created and randomly allocated for independent blinded review of (a) 2D mammograms, (b) DBT images and 2D mammograms, and (c) synthetic 2D mammograms and DBT images, without access to previous examinations. Readers (19 radiologists, three advanced practitioner radiographers, and two breast clinicians) who had 3-25 (median, 10) years of experience in the U.K. National Health Service Breast Screening Program and read 5000-13 000 (median, 8000) cases per annum were included in this study. Specificity was analyzed according to reader type and years and volume of experience, and then both specificity and sensitivity were analyzed by matched inference. The median duration of experience (10 years) was used as the cutoff point for comparison of reader performance. Results Specificity improved with the addition of DBT for all readers. This was significant for all staff groups (56% vs 68% and 49% vs 67% [P < .0001] for radiologists and advanced practitioner radiographers, respectively; 46% vs 55% [P = .02] for breast clinicians). Sensitivity was improved for 19 of 24 (79%) readers and was significantly higher for those with less than 10 years of experience (91% vs 86%; P = .03) and those with total mammographic experience of fewer than 80 000 cases (88% vs 86%; P = .03). Conclusion The addition of DBT to conventional 2D screening mammography improved specificity for all readers, but the gain in sensitivity was greater for readers with less than 10 years of experience.

Patient Specific Dose Calculation Using Volumetric Breast Density for Mammography and Tomosynthesis

Minimising the mean glandular dose (MGD) received by the patient whilst maximising image contrast during mammographic imaging is of paramount importance due to the widespread use of the modality for screening, where subjects are for the most part healthy. The advent of digital mammography brought about a general reduction in MGD, however the introduction of tomosynthesis, particularly when used in combination with conventional projection mammography has the potential for unwanted and often unnecessary MGD increases. We describe a method to calculate the patient-specific MGD using a representation of the patient’s volumetric breast density to derive the breast glandularity. This personalises the MGD to the individual woman, rather than assuming a constant value, or one that depends solely on compressed breast thickness. The calculated patient specific MGDs are compared to those reported by the manufacturer for a database of 2D mammograms. Though agreement is generally good for dense breasts, we have found that the MGD is underestimated in fatty breasts. A separate database of 2D mammogram and 3D tomosynthesis acquisitions acquired in “combo” is also analysed. In general, the MGDs are approximately equal for dense (VDG 3 and 4) breasts, but fatty (VDG 1 and 2) breasts exhibited significant differences with tomosynthesis MGDs being higher than mammogram MGDs for these cases.

Diagnostic implications of digital breast tomosynthesis in symptomatic patients

The purpose of this study was to assess the diagnostic performance/utility of digital breast tomosynthesis (DBT) in symptomatic patients in a multidisciplinary clinical setting.

Mammographic density and breast cancer risk in breast screening assessment cases and women with a family history of breast cancer.

Background Mammographic density has been shown to be a strong independent predictor of breast cancer and a causative factor in reducing the sensitivity of mammography. There remain questions as to the use of mammographic density information in the context of screening and risk management, and of the association with cancer in populations known to be at increased risk of breast cancer. Aim To assess the association of breast density with presence of cancer by measuring mammographic density visually as a percentage, and with two automated volumetric methods, Quantra™ and VolparaDensity™. Methods The TOMosynthesis with digital MammographY (TOMMY) study of digital breast tomosynthesis in the Breast Screening Programme of the National Health Service (NHS) of the United Kingdom (UK) included 6020 breast screening assessment cases (of whom 1158 had breast cancer) and 1040 screened women with a family history of breast cancer (of whom two had breast cancer). We assessed the association of each measure with breast cancer risk in these populations at enhanced risk, using logistic regression adjusted for age and total breast volume as a surrogate for body mass index (BMI). Results All density measures showed a positive association with presence of cancer and all declined with age. The strongest effect was seen with Volpara absolute density, with a significant 3% (95% CI 1–5%) increase in risk per 10 cm3 of dense tissue. The effect of Volpara volumetric density on risk was stronger for large and grade 3 tumours. Conclusions Automated absolute breast density is a predictor of breast cancer risk in populations at enhanced risk due to either positive mammographic findings or family history. In the screening context, density could be a trigger for more intensive imaging.

Does reader performance with digital breast tomosynthesis (DBT) vary with experience of 2D mammography

This work was funded by the National Institute for Health Research’s Health Technology Assessment Programme.