Increase in perceived case suspiciousness due to local contrast optimisation in digital screening mammography.

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.

Breast cancer screening results 5 years after introduction of digital mammography in a population-based screening program.

PURPOSE: To compare full-field digital mammography (FFDM) using computer-aided diagnosis (CAD) with screen-film mammography (SFM) in a population-based breast cancer screening program for initial and subsequent screening examinations. MATERIALS AND METHODS: The study was approved by the regional medical ethics review board. Informed consent was not required. In a breast cancer screening facility, two of seven conventional mammography units were replaced with FFDM units. Digital mammograms were interpreted by using soft-copy reading with CAD. The same team of radiologists was involved in the double reading of FFDM and SFM images, with differences of opinion resolved in consensus. After 5 years, screening outcomes obtained with both modalities were compared for initial and subsequent screening examination findings. RESULTS: A total of 367,600 screening examinations were performed, of which 56,518 were digital. Breast cancer was detected in 1927 women (317 with FFDM). At initial screenings, the cancer detection rate was .77% with FFDM and .62% with SFM. At subsequent screenings, detection rates were .55% and .49%, respectively. Differences were not statistically significant. Recalls based on microcalcifications alone doubled with FFDM. A significant increase in the detection of ductal carcinoma in situ was found with FFDM (P < .01). The fraction of invasive cancers with microcalcifications as the only sign of malignancy increased significantly, from 8.1% to 15.8% (P < .001). Recall rates were significantly higher with FFDM in the initial round (4.4% vs 2.3%, P < .001) and in the subsequent round (1.7% vs 1.2%, P < .001). CONCLUSION: With the FFDM-CAD combination, detection performance is at least as good as that with SFM. The detection of ductal carcinoma in situ and microcalcification clusters improved with FFDM using CAD, while the recall rate increased.