Simulated lesion, human observer performance comparison between thin-section dedicated breast CT images versus computed thick-section simulated projection images of the breast

The objective of this study was to compare the lesion detection performance of human observers between thin-section computed tomography images of the breast, with thick-section (>40 mm) simulated projection images of the breast. Three radiologists and six physicists each executed a two alterative force choice (2AFC) study involving simulated spherical lesions placed mathematically into breast images produced on a prototype dedicated breast CT scanner. The breast image data sets from 88 patients were used to create 352 pairs of image data. Spherical lesions with diameters of 1, 2, 3, 5, and 11 mm were simulated and adaptively positioned into 3D breast CT image data sets; the native thin section (0.33 mm) images were averaged to produce images with different slice thicknesses; average section thicknesses of 0.33, 0.71, 1.5 and 2.9 mm were representative of breast CT; the average 43 mm slice thickness served to simulate simulated projection images of the breast.The percent correct of the human observer's responses were evaluated in the 2AFC experiments. Radiologists lesion detection performance was significantly (p < 0.05) better in the case of thin-section images, compared to thick section images similar to mammography, for all but the 1 mm lesion diameter lesions. For example, the average of three radiologist's performance for 3 mm diameter lesions was 92% correct for thin section breast CT images while it was 67% for the simulated projection images. A gradual reduction in observer performance was observed as the section thickness increased beyond about 1 mm. While a performance difference based on breast density was seen in both breast CT and the projection image results, the average radiologist performance using breast CT images in dense breasts outperformed the performance using simulated projection images in fatty breasts for all lesion diameters except 11 mm. The average radiologist performance outperformed that of the average physicist observer, however trends in performance were similar. Human observers demonstrate significantly better mass-lesion detection performance on thin-section CT images of the breast, compared to thick-section simulated projection images of the breast.

TU-E-217BCD-03: Characterization of Anatomical Noise in Mammography, Tomosynthesis and Breast CT

PURPOSE

The role of breast density in cancer detection has been well characterized, and newer modalities such as breast tomosynthesis and breast CT (bCT) were developed to improve cancer detection in the dense breast by reducing anatomical complexity. Anatomical noise was characterized on a small cohort of patient images and compared across digital mammography, tomosynthesis, and bCT images.

METHODS AND MATERIALS

An IRB-approved and HIPPA-compliant clinical study was performed on women undergoing breast biopsy, and mammography, tomosynthesis, and bCT were performed on both breasts immediately prior to biopsy. A total of 23 women participated in this study, and the unaffected breast (no lesion) was evaluated. A total of 1000 regions of interest were sampled on each image data set, and the 2D noise power spectrum (NPS) was evaluated. This was radially averaged to produce a 1D NPS, and the NPS was fit to a power law: ln{NPS(f)} = alpha+betaxln(f), over an anatomically-relevant range of spatial frequencies. The slope, beta, was averaged across patients and compared between modalities and projections.

RESULTS

The value of beta was determined for bCT data sets, and they were 1.75 (0.424), 1.83 (0.352), and 1.79 (0.397), for the coronal, sagittal and axial views, respectively. For tomosynthesis, beta was 3.06 (0.361) and 3.10 (0.315) for the CC and MLO views, respectively. For mammography, these values were 3.17 (0.226) and 3.30 (0.236), for the CC and MLO views, respectively. The values of beta for breast CT were significantly different than those for tomosynthesis and mammography (p<0.001, all 12 comparisons).

CONCLUSIONS

The results of this investigation demonstrate that the anatomical complexity of the breast, as characterized by the parameter beta, is statistically similar between mammography and tomosynthesis, a somewhat surprising finding. The breast CT image data, however, demonstrate a statistically-significant reduction in beta across all projections. Funded in part by Hologic Corporation and by a grant from the National Institute of Biomedical Imaging and Bioengineering, EB002138.