Rationale and Objectives
The aim of this study was to evaluate the breast cancer diagnostic capability of “dual-side readout” computed radiography–based mammography (DRCRM) with a 50-μm pixel size compared to that of conventional film-screen mammography (FSM).
Materials and Methods
Thirty patients who were scheduled for surgical treatment for breast cancer and 10 normal volunteers were enrolled. All 30 patients underwent surgical treatment, and breast cancer was proved histopathologically. Twenty-eight patients had 35 invasive carcinomas, and the remaining two had ductal carcinomas in situ. Each of the 40 women underwent both DRCRM and FSM (with double exposure and the same view, without removing compression). Three observers retrospectively interpreted the mammograms independently and evaluated and rated masses and class categories. The accuracy of the detection of masses was evaluated with alternative free-response receiver-operating characteristic analysis. Sensitivity for the detection of masses and of cancers was also evaluated.
Results
The mean areas under the alternative free-response receiver-operating characteristic curves in the detection of the masses were 0.88 for DRCRM and 0.91 for FSM ( P = .08). The corresponding values for mean sensitivity for the detection of masses were 0.74 and 0.77 ( P = .48) and those for the detection of cancers 0.79 and 0.84 ( P = .20).
Conclusion
No significant differences were observed between DRCRM and FSM for diagnosis of breast cancers.
Over the past decade, various different digital mammographic systems have become available for clinical use . The main advantage of any digital imaging system is the separation of image acquisition, processing, and display, which allows for the optimization of these steps . One such system is a computed radiography (CR)–based mammographic system using photostimulated storage phosphor plates. In recent years, a computed radiographic system dedicated to mammography has been released. This system uses the “dual-side readout” technique, which collects emitted light efficiently from both sides of the storage phosphor plate . Dual-side readout CR-based mammography (DRCRM) allows for higher detective quantum efficiency, with an image sampling rate of 50 μm .
The evaluation of microcalcification findings is essential for the detection of breast cancers and to distinguish cancers from other, benign lesions. However, because the spatial resolution of 100 μm of most digital mammographic systems is inferior to that of conventional film-screen mammography (FSM), diagnosis with conventional digital mammographic systems has been considered to be at a disadvantage for the evaluation of microcalcification findings. However, DRCRM has twice the spatial resolution of other digital systems, which may help overcome the disadvantage of digital mammography for the evaluation of microcalcification findings.
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Materials and methods
Patients
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Mammography
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Image Assessment
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Statistical Analyses
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Results
Detection of Mass Lesions
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Table 1
Area Under the Alternative Free-response Receiver-operating Characteristic Curves in the Detection of Breast Mass Lesions
Modality Reader 1 Reader 2 Reader 3 Mean_P_ All breasts ( n = 40) DRCRM 0.87 0.88 0.89 0.88 FSM 0.88 0.90 0.93 0.91 .08 Breasts with dense parenchyma ( n = 23) DRCRM 0.73 0.87 0.87 0.82 FSM 0.85 0.90 0.93 0.89 .12 Breasts with fatty change ( n = 17) DRCRM 0.98 0.87 0.92 0.92 FSM DD ∗ 0.91 DD ∗ 0.91 N/A
DD, degenerate data; DRCRM, dual-side readout computed radiography–based mammography; FSM, film-screen mammography.
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Table 2
Sensitivities in the Detection of Breast Mass Lesions
Modality Reader 1 Reader 2 Reader 3 Mean_P_ All breasts ( n = 40) DRCRM 0.71 0.77 0.74 0.74 FSM 0.69 0.86 0.77 0.77 .48 Breasts with dense parenchyma ( n = 23) DRCRM 0.67 0.81 0.71 0.73 FSM 0.71 0.81 0.76 0.76 .18 Breasts with fatty change ( n = 17) DRCRM 0.79 0.71 0.79 0.76 FSM 0.64 0.93 0.79 0.79 .84
DRCRM, dual-side readout computed radiography–based mammography; FSM, film-screen mammography.
Table 3
Positive Predictive Values in the Detection of Breast Mass Lesions
Modality Reader 1 Reader 2 Reader 3 Mean_P_ All breasts ( n = 40) DRCRM 0.93 0.82 0.96 0.90 FSM 0.92 0.81 0.93 0.89 .26 Breasts with dense parenchyma ( n = 23) DRCRM 0.88 0.81 0.94 0.87 FSM 0.88 0.81 0.89 0.87 .99 Breasts with fatty change ( n = 17) DRCRM 1.00 0.83 1.00 0.94 FSM 1.00 0.77 1.00 0.92 .42
DRCRM, dual-side readout computed radiography–based mammography; FSM, film-screen mammography.
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Detection of Cancers
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Table 4
Sensitivities in the Detection of Breast Cancers
Modality Reader 1 Reader 2 Reader 3 Mean_P_ All breasts (n = 40) DRCRM 0.77 0.77 0.83 0.79 FSM 0.77 0.83 0.93 0.84 .20 Breasts with dense parenchyma (n = 23) DRCRM 0.81 0.81 0.81 0.81 FSM 0.81 0.88 0.94 0.88 .23 Breasts with fatty change (n = 17) DRCRM 0.71 0.71 0.86 0.76 FSM 0.71 0.79 0.93 0.81 .18
DRCRM, dual-side readout computed radiography–based mammography; FSM, film-screen mammography.
Breast cancers were proved histopathologically in 30 patients.
Table 5
Positive Predictive Values in the Detection of Breast Cancers
Modality Reader 1 Reader 2 Reader 3 Mean_P_ All breasts (n = 40) DRCRM 0.89 0.89 0.89 0.89 FSM 0.96 0.89 0.85 0.90 .75 Breasts with dense parenchyma (n = 23) DRCRM 0.81 0.81 0.87 0.83 FSM 0.93 0.88 0.79 0.86 .62 Breasts with fatty change (n = 17) DRCRM 1.00 1.00 0.92 0.97 FSM 1.00 0.92 0.93 0.95 .46
DRCRM, dual-side readout computed radiography–based mammography; FSM, film-screen mammography.
Breast cancers were proved histopathologically in 30 patients.
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Comparative Study by One-to-One Correspondence
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Table 6
The Imaging Features of Each Finding in Dual-side Readout Computed Radiography–based Mammography Compared to That of Film-screen Mammography
Finding and Feature Comparison Microcalcifications ( n = 18) Size Larger Same Smaller 0 (0%) 18 (100%) 0 (0%) Number More Same Less 1 (6%) 12 (67%) 5 (28%) Shape More angular Same More round 0 (0%) 14 (78%) 4 (22%) Conspicuity Better-defined Same Worse-defined 1 (6%) 11 (61%) 6 (33%) Masses ( n = 26) Size Larger Same Smaller 1 (4%) 24 (92%) 1 (4%) Conspicuity Better-defined Same Worse-defined 5 (19%) 19 (73%) 2 (8%) Stellate signs ( n = 10) Conspicuity More clear Same More obscure 3 (30%) 5 (50%) 2 (20%)
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Inter-reader Variability
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Intrareader Variability
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Discussion
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Acknowledgments
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References
1. James J.J.: The current status of digital mammography. Clin Radiol 2004; 59: pp. 1-10.
2. Pisano E.D., Yaffe M.J., Hemminger B.M., et. al.: Current status of full-field digital mammography. Acad Radiol 2000; 7: pp. 266-280.
3. Lewin J.M., Hendrick R.E., D’Orsi C.J., et. al.: Comparison of full-field digital mammography with screen-film mammography for cancer detection: results of 4,945 paired examinations. Radiology 2001; 218: pp. 873-880.
4. Fetterly K.A., Schueler B.A.: Performance evaluation of a “dual-side read” dedicated mammography computed radiography system. Med Phys 2003; 30: pp. 1843-1854.
5. Yasuda H., Takasu A., Itakura T., Arakawa S.: Development of a high-quality “dual-side read” dedicated mammography Fuji computed radiography system. Fuji Med Rev 2001; 10: pp. 3-12.
6. Schueller G., Riedl C.C., Mallek R., et. al.: Image quality, lesion detection, and diagnostic efficacy in digital mammography: full-field digital mammography versus computed radiography-based mammography using digital storage phosphor plates. Eur J Radiol 2008; 67: pp. 487-496.
7. Bonardi R., Ambrogetti D., Ciatto S., et. al.: Conventional versus digital mammography in the analysis of screen-detected lesions with low positive predictive value. Eur J Radiol 2005; 55: pp. 258-263.
8. Chakraborty D.P., Winter L.H.: Free-response methodology: alternate analysis and a new observer-performance experiment. Radiology 1990; 174: pp. 873-881.
9. Yamada M., Shimura K.: Improvement of diagnostic-image quality by means of Pattern Enhancement Processing for Mammography (PEM). Fuji Med Rev 2001; 10: pp. 13-22.
10. Lewin J.M., Hendrick R.E., Dórci C.J., et. al.: Comparison of full-field digital mammography with screen-film mammography for cancer detection: results of 4945 paired examinations. Radiology 2001; 218: pp. 873-880.