RESUMEN
INTRODUCTION: The objective of this study is to compare different methods for measuring breast density, both visual assessments and automated volumetric density, in a breast cancer screening setting. These measures could potentially be implemented in future screening programmes, in the context of personalised screening or screening evaluation. MATERIALS AND METHODS: Digital mammographic exams (N = 992) of women participating in the Dutch breast cancer screening programme (age 50-75y) in 2013 were included. Breast density was measured in three different ways: BI-RADS density (5th edition) and with two commercially available automated software programs (Quantra and Volpara volumetric density). BI-RADS density (ordinal scale) was assessed by three radiologists. Quantra (v1.3) and Volpara (v1.5.0) provide continuous estimates. Different comparison methods were used, including Bland-Altman plots and correlation coefficients (e.g., intraclass correlation coefficient [ICC]). RESULTS: Based on the BI-RADS classification, 40.8% of the women had 'heterogeneously or extremely dense' breasts. The median volumetric percent density was 12.1% (IQR: 9.6-16.5) for Quantra, which was higher than the Volpara estimate (median 6.6%, IQR: 4.4-10.9). The mean difference between Quantra and Volpara was 5.19% (95% CI: 5.04-5.34) (ICC: 0.64). There was a clear increase in volumetric percent dense volume as BI-RADS density increased. The highest accuracy for predicting the presence of BI-RADS c+d (heterogeneously or extremely dense) was observed with a cut-off value of 8.0% for Volpara and 13.8% for Quantra. CONCLUSION: Although there was no perfect agreement, there appeared to be a strong association between all three measures. Both volumetric density measures seem to be usable in breast cancer screening programmes, provided that the required data flow can be realized.
Asunto(s)
Automatización , Neoplasias de la Mama/diagnóstico por imagen , Mama/anatomía & histología , Programas Informáticos , Anciano , Estudios Transversales , Femenino , Humanos , Persona de Mediana Edad , Países Bajos , RadiografíaRESUMEN
OBJECTIVES: To determine the influence of local contrast optimisation on diagnostic accuracy and perceived suspiciousness of digital screening mammograms. METHODS: Data were collected from a screening region in the Netherlands and consisted of 263 digital screening cases (153 recalled,110 normal). Each case was available twice, once processed with a tissue equalisation (TE) algorithm and once with local contrast optimisation (PV). All cases had digitised previous mammograms. For both algorithms, the probability of malignancy of each finding was scored independently by six screening radiologists. Perceived case suspiciousness was defined as the highest probability of malignancy of all findings of a radiologist within a case. Differences in diagnostic accuracy of the processing algorithms were analysed by comparing the areas under the receiver operating characteristic curves (A(z)). Differences in perceived case suspiciousness were analysed using sign tests. RESULTS: There was no significant difference in A(z) (TE: 0.909, PV 0.917, P = 0.46). For all radiologists, perceived case suspiciousness using PV was higher than using TE more often than vice versa (ratio: 1.14-2.12). This was significant (P <0.0083) for four radiologists. CONCLUSIONS: Optimisation of local contrast by image processing may increase perceived case suspiciousness, while diagnostic accuracy may remain similar. KEY POINTS: Variations among different image processing algorithms for digital screening mammography are large. Current algorithms still aim for optimal local contrast with a low dynamic range. Although optimisation of contrast may increase sensitivity, diagnostic accuracy is probably unchanged. Increased local contrast may render both normal and abnormal structures more conspicuous.