Computer-aided detection in full-field digital mammography in a clinical population: performance of radiologist and technologists

• Published in: Breast cancer research and treatment 2010-04, Vol.120 (2), p.499-506
• Main Authors: van den Biggelaar, Frank J. H. M, Kessels, Alphons G. H, van Engelshoven, Jos M. A, Boetes, Carla, Flobbe, Karin
• Format: Article
• Language: English
• Subjects: Adult; Aged; Aged, 80 and over; Biological and medical sciences; Breast cancer; Breast Neoplasms - diagnostic imaging; CAD; Cancer research; Computer aided design; Epidemiology; False Positive Reactions; Female; Gynecology. Andrology. Obstetrics; Health Personnel - standards; Humans; Mammary gland diseases; Mammography; Mammography - methods; Mammography - standards; Medical sciences; Medicine; Medicine & Public Health; Middle Aged; Oncology; Radiographic Image Interpretation, Computer-Assisted - methods; Radiology - methods; Radiology - standards; Sensitivity and Specificity; Software; Tumors; Young Adult
• ISSN: 0167-6806; 1573-7217
• DOI: 10.1007/s10549-009-0409-y

The purpose of the study was to evaluate the impact of a computer-aided detection (CAD) system on the performance of mammogram readers in interpreting digital mammograms in a clinical population. Furthermore, the ability of a CAD system to detect breast cancer in digital mammography was studied in comparison to the performance of radiologists and technologists as mammogram readers. Digital mammograms of 1,048 consecutive patients were evaluated by a radiologist and three technologists. Abnormalities were recorded and an imaging conclusion was given as a BI-RADS score before and after CAD analysis. Pathology results during 12 months follow up were used as a reference standard for breast cancer. Fifty-one malignancies were found in 50 patients. Sensitivity and specificity were computed before and after CAD analysis and provided with 95% CIs. In order to assess the detection rate of malignancies by CAD and the observers, the pathological locations of these 51 breast cancers were matched with the locations of the CAD marks and the mammographic locations that were considered to be suspicious by the observers. For all observers, the sensitivity rates did not change after application of CAD. A mean sensitivity of 92% was found for all technologists and 84% for the radiologist. For two technologists, the specificity decreased (from 84 to 83% and from 77 to 75%). For the radiologist and one technologist, the application of CAD did not have any impact on the specificity rates (95 and 83%, respectively). CAD detected 78% of all malignancies. Five malignancies were indicated by CAD without being noticed as suspicious by the observers. In conclusion, the results show that systematic application of CAD in a clinical patient population failed to improve the overall sensitivity of mammogram interpretation by the readers and was associated with an increase in false-positive results. However, CAD marked five malignancies that were missed by the different readers.