The efficacy of using computer-aided detection (CAD) for detection of breast cancer in mammography screening: a systematic review
Research output: Contribution to journal › Review › Research › peer-review
Emilie L Henriksen, Jonathan F Carlsen, Ilse MM Vejborg, Michael B Nielsen, Carsten A Lauridsen
BACKGROUND: Early detection of breast cancer (BC) is crucial in lowering the mortality.
PURPOSE: To present an overview of studies concerning computer-aided detection (CAD) in screening mammography for early detection of BC and compare diagnostic accuracy and recall rates (RR) of single reading (SR) with SR + CAD and double reading (DR) with SR + CAD.
MATERIAL AND METHODS: PRISMA guidelines were used as a review protocol. Articles on clinical trials concerning CAD for detection of BC in a screening population were included. The literature search resulted in 1522 records. A total of 1491 records were excluded by abstract and 18 were excluded by full text reading. A total of 13 articles were included.
RESULTS: All but two studies from the SR vs. SR + CAD group showed an increased sensitivity and/or cancer detection rate (CDR) when adding CAD. The DR vs. SR + CAD group showed no significant differences in sensitivity and CDR. Adding CAD to SR increased the RR and decreased the specificity in all but one study. For the DR vs. SR + CAD group only one study reported a significant difference in RR.
CONCLUSION: All but two studies showed an increase in RR, sensitivity and CDR when adding CAD to SR. Compared to DR no statistically significant differences in sensitivity or CDR were reported. Additional studies based on organized population-based screening programs, with longer follow-up time, high-volume readers, and digital mammography are needed to evaluate the efficacy of CAD.
|Number of pages||6|
|Publication status||Published - 2019|
- Breast/diagnostic imaging, Breast Neoplasms/diagnostic imaging, Early Detection of Cancer/methods, Female, Humans, Mammography/methods, Radiographic Image Interpretation, Computer-Assisted/methods, Reproducibility of Results, Sensitivity and Specificity