OBJECTIVES: To evaluate the impact of a computer-aided detection (CAD) system on the ability of a junior and senior radiologist to detect breast cancers on mammograms, and to determine the potential of CAD as a teaching tool in mammography. METHODS: Hundred biopsy-proven cancers and 100 normal mammograms were randomly analyzed by a CAD system. The sensitivity (Se) and specificity (Sp) of the CAD system were calculated. In the second phase, to simulate daily practice, 110 mammograms (97 normal or with benign lesions, and 13 cancers) were examined independently by a junior and a senior radiologist, with and without CAD. Interpretations were standardized according to BI-RADS classification. Sensitivity, Specificity, positive and negative predictive values (PPV, NPV) were calculated for each session. RESULTS: For the senior radiologist, Se slightly improved from 76.9 to 84.6% after CAD analysis (NS) (one case of clustered microcalcifications case overlooked by the senior radiologist was detected by CAD). Sp, PPV and PNV did not change significantly. For the junior radiologist, Se improved from 61.9 to 84.6% (significant change). Three cancers overlooked by the junior radiologist were detected by CAD. Sp was unchanged. CONCLUSION: CAD mammography proved more useful for the junior than for the senior radiologist, improving sensitivity. The CAD system may represent a useful educational tool for mammography.
OBJECTIVES: To evaluate the impact of a computer-aided detection (CAD) system on the ability of a junior and senior radiologist to detect breast cancers on mammograms, and to determine the potential of CAD as a teaching tool in mammography. METHODS: Hundred biopsy-proven cancers and 100 normal mammograms were randomly analyzed by a CAD system. The sensitivity (Se) and specificity (Sp) of the CAD system were calculated. In the second phase, to simulate daily practice, 110 mammograms (97 normal or with benign lesions, and 13 cancers) were examined independently by a junior and a senior radiologist, with and without CAD. Interpretations were standardized according to BI-RADS classification. Sensitivity, Specificity, positive and negative predictive values (PPV, NPV) were calculated for each session. RESULTS: For the senior radiologist, Se slightly improved from 76.9 to 84.6% after CAD analysis (NS) (one case of clustered microcalcifications case overlooked by the senior radiologist was detected by CAD). Sp, PPV and PNV did not change significantly. For the junior radiologist, Se improved from 61.9 to 84.6% (significant change). Three cancers overlooked by the junior radiologist were detected by CAD. Sp was unchanged. CONCLUSION: CAD mammography proved more useful for the junior than for the senior radiologist, improving sensitivity. The CAD system may represent a useful educational tool for mammography.
Authors: Trafton Drew; Avi M Aizenman; Matthew B Thompson; Mark D Kovacs; Michael Trambert; Murray A Reicher; Jeremy M Wolfe Journal: J Med Imaging (Bellingham) Date: 2015-10-12
Authors: Elodia B Cole; Zheng Zhang; Helga S Marques; Robert M Nishikawa; R Edward Hendrick; Martin J Yaffe; Wittaya Padungchaichote; Cherie Kuzmiak; Jatuporn Chayakulkheeree; Emily F Conant; Laurie L Fajardo; Janet Baum; Constantine Gatsonis; Etta Pisano Journal: AJR Am J Roentgenol Date: 2012-09 Impact factor: 3.959
Authors: Elodia B Cole; Zheng Zhang; Helga S Marques; R Edward Hendrick; Martin J Yaffe; Etta D Pisano Journal: AJR Am J Roentgenol Date: 2014-10 Impact factor: 3.959
Authors: Akshay S Chaudhari; Christopher M Sandino; Elizabeth K Cole; David B Larson; Garry E Gold; Shreyas S Vasanawala; Matthew P Lungren; Brian A Hargreaves; Curtis P Langlotz Journal: J Magn Reson Imaging Date: 2020-08-24 Impact factor: 5.119