PURPOSE: The aim of this study was to evaluate the usefulness of computer-aided detection (CAD) in diagnosing early colorectal cancer using computed tomography colonography (CTC). MATERIALS AND METHODS: A total of 30 CTC data sets for 30 early colorectal cancers in 30 patients were retrospectively reviewed by three radiologists. After primary evaluation, a second reading was performed using CAD findings. The readers evaluated each colorectal segment for the presence or absence of colorectal cancer using five confidence rating levels. To compare the assessment results, the sensitivity and specificity with and without CAD were calculated on the basis of the confidence rating, and differences in these variables were analyzed by receiver operating characteristic (ROC) analysis. RESULTS: The average sensitivities for the detection without and with CAD for the three readers were 81.6% and 75.6%, respectively. Among the three readers, only one reader improved sensitivity with CAD compared to that without. CAD decreased specificity in all three readers. CAD detected 100% of protruding lesions but only 69.2% of flat lesions. On ROC analysis, the diagnostic performance of all three readers was decreased by use of CAD. CONCLUSION: Currently available CAD with CTC does not improve diagnostic performance for detecting early colorectal cancer. An improved CAD algorithm is required for detecting flat lesions and reducing the false-positive rate.
PURPOSE: The aim of this study was to evaluate the usefulness of computer-aided detection (CAD) in diagnosing early colorectal cancer using computed tomography colonography (CTC). MATERIALS AND METHODS: A total of 30 CTC data sets for 30 early colorectal cancers in 30 patients were retrospectively reviewed by three radiologists. After primary evaluation, a second reading was performed using CAD findings. The readers evaluated each colorectal segment for the presence or absence of colorectal cancer using five confidence rating levels. To compare the assessment results, the sensitivity and specificity with and without CAD were calculated on the basis of the confidence rating, and differences in these variables were analyzed by receiver operating characteristic (ROC) analysis. RESULTS: The average sensitivities for the detection without and with CAD for the three readers were 81.6% and 75.6%, respectively. Among the three readers, only one reader improved sensitivity with CAD compared to that without. CAD decreased specificity in all three readers. CAD detected 100% of protruding lesions but only 69.2% of flat lesions. On ROC analysis, the diagnostic performance of all three readers was decreased by use of CAD. CONCLUSION: Currently available CAD with CTC does not improve diagnostic performance for detecting early colorectal cancer. An improved CAD algorithm is required for detecting flat lesions and reducing the false-positive rate.
Authors: Perry J Pickhardt; J Richard Choi; Inku Hwang; James A Butler; Michael L Puckett; Hans A Hildebrandt; Roy K Wong; Pamela A Nugent; Pauline A Mysliwiec; William R Schindler Journal: N Engl J Med Date: 2003-12-01 Impact factor: 91.245
Authors: Ronald M Summers; Jianhua Yao; Perry J Pickhardt; Marek Franaszek; Ingmar Bitter; Daniel Brickman; Vamsi Krishna; J Richard Choi Journal: Gastroenterology Date: 2005-12 Impact factor: 22.682
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Authors: Se Hyung Kim; Jeong Min Lee; Joon-Goo Lee; Jong Hyo Kim; Philippe A Lefere; Joon Koo Han; Byung Ihn Choi Journal: AJR Am J Roentgenol Date: 2007-07 Impact factor: 3.959
Authors: Benoit C Pineau; Electra D Paskett; G John Chen; Mark A Espeland; Kim Phillips; James P Han; Claudia Mikulaninec; David J Vining Journal: Gastroenterology Date: 2003-08 Impact factor: 22.682
Authors: Jacob Sosna; Martina M Morrin; Jonathan B Kruskal; Philip T Lavin; Max P Rosen; Vassilios Raptopoulos Journal: AJR Am J Roentgenol Date: 2003-12 Impact factor: 3.959