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12 May 2004 ROC study of the effects of computer-aided interval change analysis on radiologists' characterization of breast masses in two-view serial mammograms
Lubomir M. Hadjiiski, Mark A. Helvie, Berkman Sahiner, Heang-Ping Chan, Marilyn A. Roubidoux, Alexis Nees, Nicholas Petrick, Caroline Blane, Chintana Paramagul, Janet E. Bailey, Stephanie Patterson, Katherine Klein, Dorit Adler, Michelle Foster, Joseph Shen
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Proceedings Volume 5370, Medical Imaging 2004: Image Processing; (2004) https://doi.org/10.1117/12.535892
Event: Medical Imaging 2004, 2004, San Diego, California, United States
Abstract
We have previously evaluated the effects of computer-aided diagnosis (CAD) on radiologists' characterization of malignant and benign breast masses in single-view serial mammograms. In this study, we conducted observer performance experiments with ROC methodology in which the radiologists read the serial mammograms in two-views (CC and MLO) without and with CAD. 47 temporal pairs of two-view serial mammograms (27 malignant and 20 benign) containing masses were chosen from 39 patient files and digitized. The corresponding masses on each temporal pair were analyzed by the CAD program. For this data set, the computer classifier achieved a test Az value of 0.90. Five MQSA radiologists assessed the two-view temporal pairs and provided estimates of the likelihood of malignancy without and then with CAD. For the five radiologists, the average Az was 0.81 (range: 0.72-0.88) without CAD and improved to 0.88 (range: 0.86-0.90) with CAD. The improvement was statistically significant (p=0.038). In comparison, the test Az value of the computer classifier for single view analysis was 0.87. The average Az of the radiologists for reading the single view temporal pairs without CAD was 0.78 (range: 0.73-0.83) and was improved significantly (p=0.002) to 0.84 (range: 0.77-0.88) with CAD. CAD using interval change analysis can significantly improve radiologists' accuracy in classification of masses. Classification based on information from two-views is more accurate than that based on single view for both the radiologists and the computer classifier. CAD can further improve radiologists' performance even in two-view reading.
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Lubomir M. Hadjiiski, Mark A. Helvie, Berkman Sahiner, Heang-Ping Chan, Marilyn A. Roubidoux, Alexis Nees, Nicholas Petrick, Caroline Blane, Chintana Paramagul, Janet E. Bailey, Stephanie Patterson, Katherine Klein, Dorit Adler, Michelle Foster, and Joseph Shen "ROC study of the effects of computer-aided interval change analysis on radiologists' characterization of breast masses in two-view serial mammograms", Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); https://doi.org/10.1117/12.535892
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KEYWORDS
Computer aided diagnosis and therapy
Mammography
Breast
Biopsy
CAD systems
Breast cancer
Computer aided design
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