Which phantom is better for assessing the image quality in full-field digital mammography?: American College of Radiology Accreditation phantom versus digital mammography accreditation phantom

哪种体模更适合评估全视野数字乳腺摄影的图像质量?:美国放射学会认证体模与数字乳腺摄影认证体模

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Abstract

OBJECTIVE: To compare between the American College of Radiology (ACR) accreditation phantom and digital mammography accreditation phantom in assessing the image quality in full-field digital mammography (FFDM). MATERIALS AND METHODS: In each week throughout the 42-week study, we obtained phantom images using both the ACR accreditation phantom and the digital mammography accreditation phantom, and a total of 42 pairs of images were included in this study. We assessed the signal-to-noise ratio (SNR) in each phantom image. A radiologist drew a square-shaped region of interest on the phantom and then the mean value of the SNR and the standard deviation were automatically provided on a monitor. SNR was calculated by an equation, measured mean value of SNR-constant coefficient of FFDM/standard deviation. Two breast radiologists scored visible objects (fibers, specks, and masses) with soft-copy images and calculated the visible rate (number of visible objects/total number of objects). We compared SNR and the visible rate of objects between the two phantoms and calculated the k-coefficient for interobserver agreement. RESULTS: The SNR of the ACR accreditation phantom ranged from 42.0 to 52.9 (Mean, 47.3 ± 2.79) and that of Digital Phantom ranged from 24.8 to 54.0 (Mean, 44.1 ± 9.93) (p = 0.028). The visible rates of all three types of objects were much higher in the ACR accreditation phantom than those in the digital mammography accreditation phantom (p < 0.05). Interobserver agreement for visible rates of objects on phantom images was fair to moderate agreement (k-coefficients: 0.34-0.57). CONCLUSION: The ACR accreditation phantom is superior to the digital mammography accreditation phantom in terms of SNR and visibility of phantom objects. Thus, ACR accreditation phantom appears to be satisfactory for assessing the image quality in FFDM.

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