Comparison of breast cancer detection and depiction between planar and rotating synthetic mammography generated from breast tomosynthesis

Abstract

Purpose: To compare breast cancer detection and depiction between planar synthetic mammography (SM) and rotating synthetic mammography (RM) generated from digital breast tomosynthesis (DBT).

Materials and methods: In a fully-crossed multi-reader multi-case (MRMC) study, three radiologists retrospectively reviewed 190 cases (27 malignant, 31 benign, 132 normal), once with SM alone and once with RM alone, the DBT stack of slices was not reviewed. Lesions were scored using BI-RADS® and level of suspiciousness (1-10). Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were computed using MRMC Analysis of Variance using the open-access software iMRMC. Additionally, readers were asked to make a visual grading analysis (VGA) on visibility of calcifications and soft tissue lesions (1-5 scale with 5 = Excellent visualization). The VGA scores were analyzed using the visual grading characteristics (VGC) method.

Results: On average, the AUC was similar between SM and RM (0.66 versus 0.67, P = 0.818). The sensitivity was equivalent (0.62 versus 0.60, P = 0.794), while specificity was significantly lower in SM than in RM (0.66 versus 0.72, P = 0.028). Radiologists significantly (P < 0.05) preferred the display of all types of lesions in RM over SM. The average reading time per case was higher for RM than for SM (30 s versus 23 s, P < 0.05).

Conclusion: Radiologists achieve similar cancer detection with RM as with SM. They prefer the 3D-like rotating representation of soft tissue lesions and calcifications in comparison to the 2D visualization, which might improve their specificity, but at the expense of longer reading time.

Keywords: Artificial intelligence; Breast cancer detection; Digital breast tomosynthesis; Rotating mammography; Synthetic mammography.