China Oncology ›› 2025, Vol. 35 ›› Issue (8): 784-791.doi: 10.19401/j.cnki.1007-3639.2025.08.007

• Article • Previous Articles     Next Articles

Analysis of variation coefficient of SNR in phantom-based mammography quality control

SHEN Xigang(), CHAI Qinghuan, JIANG Tingting, SHEN Yue, XIAO Qin, GU Yajia()   

  1. Department of Radiology, Fudan University Shanghai Cancer Center;Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
  • Received:2024-10-24 Revised:2025-03-19 Online:2025-08-30 Published:2025-09-10
  • Contact: GU Yajia
  • Supported by:
    Wu Jieping Medical Foundation Clinical Research Special Fund(320.6750.2022-11-24)

Abstract:

Background and purpose: In the quality control of mammography, the signal-to-noise ratio (SNR) refers to the ratio of the useful signal intensity to the background noise in the image, which is one of the important indicators for measuring the quality of the image. The coefficient of variation (CoV) is a commonly used indicator to describe the consistency and repeatability of SNR. This study aimed to assess the stability and repeatability of mammographic device performance by analyzing the changes in SNR CoV in two-dimensional (2D) images and tomosynthesis images (referred to as Tomo images) under different exposure modes using three mammographic devices from different manufacturers. Methods: A polymethylmethacrylate (PMMA) phantom designed for mammography quality control was used to perform automatic exposure detection at PMMA thicknesses ranging from 20-80 mm, with actual compression thickness equivalent to the average density of the breast compressed to 21-103 mm under full-field digital mammography (FFDM), low-dose mammography and digital breast tomosynthesis (DBT) exposure modes. The CoV of SNR in 2D images and tomosynthesis images was calculated for different mammographic devices under different exposure modes and compression thicknesses. Results: Between the compression thicknesses equivalent to the average density of the breast from 21 mm to 103 mm under FFDM, low-dose mammography, and DBT exposure modes, the differences in SNR CoV of 2D images under different exposure modes among mammographic devices 1, 2, and 3 were statistically significant only in the DBT exposure mode (P=0.003), with SNR CoV ranging from 0.188% to 0.720%, 0.368% to 1.073% and 0.402% to 1.662%, respectively. There were no statistically significant differences in SNR CoV of 2D images among devices 1, 2, and 3 under FFDM and low-dose exposure modes (P=0.060). Under the DBT exposure mode, there were no statistically significant differences in the SNR CoV of the first projection image and the 0° projection image of tomosynthesis among devices 1 (2 angles), 2, and 3 (P=0.373, P=0.742, P=0.225, P=0.693, respectively). Conclusion: The SNR CoV in 2D images and tomosynthesis images varies under different mammographic devices and exposure modes, with no fixed or standard values, but all within the required range for mammographic device quality control. The stability and repeatability of 2D images of mammographic devices are better under FFDM and low-dose exposure modes; the SNR CoV values of the first projection image and the 0° projection image of tomosynthesis under the DBT exposure mode show no statistical differences, indicating good stability of the devices.

Key words: Mammography, Signal-to-noise ratio, Coefficient of variation, Quality control

CLC Number: