PURPOSE To evaluate the accuracy of a visually lossless, image-adaptive, wavelet-based compression method for achievement of high compression rates at mammography. MATERIALS AND METHODS The study was approved by the institutional review board of the University of South Florida as a research study with existing medical records and was exempt from individual patient consent requirements. Patient identifiers were obliterated from all images. The study was HIPAA compliant. An algorithm based on scale-specific quantization of biorthogonal wavelet coefficients was developed for the compression of digitized mammograms with high spatial and dynamic resolution. The method was applied to 500 normal and abnormal mammograms from 278 patients who were 32-85 years old, 85 of whom had biopsy-proved cancer. Film images were digitized with a charge-coupled device-based digitizer. The original and compressed reconstructed images were evaluated in a localization response operating characteristic experiment involving three radiologists with 2-10 years of experience in reading mammograms. RESULTS Compression rates in the range of 14:1 to 2051:1 were achieved, and the rates were dependent on the degree of parenchymal density and the type of breast structure. Ranges of the area under the receiver operating characteristic curve were 0.70-0.83 and 0.72-0.86 for original and compressed reconstructed mammograms, respectively. Ranges of the area under the localization response operating characteristic curve were 0.39-0.65 and 0.43-0.71 for original and compressed reconstructed mammograms, respectively. The localization accuracy increased an average of 6% (0.04 of 0.67) with the compressed mammograms. Localization performance differences were statistically significant with P = .05 and favored interpretation with the wavelet-compressed reconstructed images. CONCLUSION The tested wavelet-based compression method proved to be an accurate approach for digitized mammography and yielded visually lossless high-rate compression and improved tumor localization.

The purpose of this study was to determine the impact of default image display, presentation protocol, and workstation configuration on the softcopy interpretation of mammograms. Results from ROC studies that compared film to softcopy mammography were analyzed for this purpose. On average, no difference in performance was observed between the two modalities. However, differences were identified in individual observer performance and the qualitative evaluation of the two platforms that were related to the system’s speed, the default grayscale display of the images, and possibly the CRT phosphor. Speed and default display were ranked as the top two impact factors on softcopy reading.

The purpose of this study was to evaluate the frequency and reasons of disagreement between film and full-field digital mammography (FFDM) interpretations observed in a prospective clinical trial performed with the GE Senographe 2000D system. The data from 643 mammography examinations comprising both digital and film mammograms were analyzed for this purpose. Reports indicated that 455 findings were identified on the digital softcopy reading and 457 findings on the standard film mammography with 408 discrepancies. Findings with discrepancies were matched and analyzed. A reason was identified and a relative conspicuity score of 0 to 10 was assigned to each finding at the time of resolution; 0 corresponded to a finding highly conspicuous on digital, 10 to a finding highly conspicuous on film, and 5 denoted equal visibility on both. After review, agreement was established between the two modalities in 73.3% of the findings; 13.5% of findings were seen better on digital and 13.2% of the findings were seen better on film. Approximately 63% of the discrepancies occurred due to variability in the reporting style of the radiologists and/or unavailability of prior films for comparison. Three cancer cases were identified in this study; two were seen on both modalities and one only on film. In conclusion, no statistically significant differences were observed between digital and film mammography, a result that despite the small size of our dataset is in agreement with previous reports. Interobserver variability, display differences, and presentation disagreements are the main reasons for interpretation differences that are primarily identified in the classification and BIRADS assignment.

Rationale and Objectives. The authors developed and evaluated a method for the simulation of calcification clusters based on the guidelines of the Breast Imaging Reporting and Data System of the American College of Radiology. They aimed to reproduce accurately the relative and absolute Size, shape. location. number, and intensity of real calcifications associated with both benign and malignant disease.Materials and Methods. Thirty calcification clusters were simulated by using the proposed model and were superimposed on real. negative mammograms digitized at M pm and 16 bits per pixel. The accuracy of the simulation was evaluated by three radiologists in a blinded study.Results. No statistically significant difference was observed in the observers' evaluation of the simulated clusters and the real clusters. The observers' classification of the-cluster types seemed to be a good approximation of the intended types from the simulation design.Conclusion. This model can provide Simulated calcification clusters with well-defined morphologic, distributional, and contrast characteristics for a variety of applications in digital mammography.