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Can Computer-aided Detection with Double Reading of Screening Mammograms Help Decrease the False-Negative Rate? Initial Experience

2004·122 Zitationen·Radiology
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122

Zitationen

6

Autoren

2004

Jahr

Abstract

PURPOSE: To retrospectively evaluate the role of computer-aided detection (CAD) in reducing the rate of false-negative (FN) findings on screening mammograms considered normal at initial double reading. MATERIALS AND METHODS: At the authors' institution, independent prospective double readings in which the second reader is not blinded to results of the first reading are performed routinely for all mammograms. When cancer is diagnosed, prior mammograms also are reviewed with double reading to determine cancer visibility. Findings are categorized as (a) no evidence of cancer on any prior screening mammogram and patient presents more than 1 year after prior screening, (b) no evidence of cancer on any prior screening mammogram and patient presents with symptoms within 1 year after prior screening (year-interval occult false-negative), or (c) cancer visible. The clinical director separately evaluates each case in the same way. In 2000, 519 histologically proved breast cancers were diagnosed, including 132 for which patients sought a second opinion and FN findings were not tracked. Prior screening mammograms were available in 318 of the other 387 cases. Five radiologists in two reading sessions independently reviewed current and prior mammograms to categorize visible cancers as either threshold or actionable FN findings. Visible cancers deemed actionable by at least three of five readers were analyzed with a commercially available CAD system. FN rates were calculated prior to and after CAD analysis. RESULTS: Twenty-seven occult and 71 visible cancers were found (total FN findings, 98). Three of five readers considered 52 (73%) of 71 visible cancers actionable. The CAD system correctly marked 37 (71%) of these 52 on prior screening mammograms (19 [65%] of 29 masses, seven [88%] of eight microcalcifications, seven [78%] of nine architectural distortions, and four [67%] of six masses with microcalcifications). The FN rate was 98 (31%) of 318 before CAD and 61 (19%) of 318 after CAD. CONCLUSION: In this retrospective review of this small subset of cancers, it appears that CAD has the potential to decrease the FN rate at double reading by more than one-third (from 31% to 19%). The CAD system correctly marked 37 (71%) of 52 actionable findings read as negative in previous screening years.

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AI in cancer detectionBreast Lesions and CarcinomasGlobal Cancer Incidence and Screening
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