[Show abstract][Hide abstract] ABSTRACT: To compare full-field digital mammography (FFDM) using computer-aided diagnosis (CAD) with screen-film mammography (SFM) in a population-based breast cancer screening program for initial and subsequent screening examinations.
The study was approved by the regional medical ethics review board. Informed consent was not required. In a breast cancer screening facility, two of seven conventional mammography units were replaced with FFDM units. Digital mammograms were interpreted by using soft-copy reading with CAD. The same team of radiologists was involved in the double reading of FFDM and SFM images, with differences of opinion resolved in consensus. After 5 years, screening outcomes obtained with both modalities were compared for initial and subsequent screening examination findings.
A total of 367,600 screening examinations were performed, of which 56,518 were digital. Breast cancer was detected in 1927 women (317 with FFDM). At initial screenings, the cancer detection rate was .77% with FFDM and .62% with SFM. At subsequent screenings, detection rates were .55% and .49%, respectively. Differences were not statistically significant. Recalls based on microcalcifications alone doubled with FFDM. A significant increase in the detection of ductal carcinoma in situ was found with FFDM (P < .01). The fraction of invasive cancers with microcalcifications as the only sign of malignancy increased significantly, from 8.1% to 15.8% (P < .001). Recall rates were significantly higher with FFDM in the initial round (4.4% vs 2.3%, P < .001) and in the subsequent round (1.7% vs 1.2%, P < .001).
With the FFDM-CAD combination, detection performance is at least as good as that with SFM. The detection of ductal carcinoma in situ and microcalcification clusters improved with FFDM using CAD, while the recall rate increased.
[Show abstract][Hide abstract] ABSTRACT: PURPOSE
Conversion of an ongoing screening program to digital mammography is studied in a pilot project. The purpose of this paper is to compare screening outcomes of digital and conventional screenings in the first year of the project.
METHOD AND MATERIALS
In a breast cancer screening center that carries out 70,000 screenings each year digital mammography was introcuced to study practical implications and quality issues related to digitization. A digital environment was set up that included a Full Field Digital Mammography (FFDM) system (Lorad Selenia), a dedicated mammographic review station (MeVis), a PACS with an archive and a technician workstation for viewing of current and prior mammograms (Rogan-Delft), and a CAD system with the capability of archiving digitized priors (R2 Technology). Women who were invited for a digital exam were randomly selected based on availability of the systems in use. In the first phase of the project only initial screenings were performed with FFDM. In the second phase also subsequent screenings were carried out digitally. Prior mammograms of one previous screening round were routinely digitized and archived for all participants on the day before they attended screening. These were viewed using automatic hanging protocols by the radiologists and by the technicians, as in the conventional screening protocol. Radiologists had CAD available. All cases were double read and in each reading at least one of a team of two experienced readers was involved. Five other radiologists took part in the double reading.
In the first year of the project 3959 women were screened with FFDM. Detection with FFDM was similar to detection with film. The referral rate for first screenings was significantly higher with FFDM than with film in the first phase of the project (0.58% vs 0.26%, p<0.01), but decreased to a normal level (0.27%) in the second phase. Also for subsequent screenings we found a significant increase in referral rate in the initial period (2.4% vs 1.2%). Comparison with prior mammograms was more difficult due to the way FFDM was processed.
Introduction of digital mammography had no significant effect on detection but initially resulted in a higher referral rate.
N.K.: Is shareholder and has received grant support from R2 Technology