OBJECTIVE: Our objective was to evaluate the impact of a computer-aided diagnostic scheme on radiologists' interpretations of chest radiographs with interstitial opacities by performing an observer test using receiver operating characteristic (ROC) analysis. MATERIALS AND METHODS: Twenty chest radiographs with normal findings and 20 chest radiographs with abnormal findings were used. Each radiograph was divided into four quadrants. One hundred twenty-nine quadrants (80 normal and 49 abnormal quadrants) were used for testing because we excluded 31 equivocal quadrants. Sixteen independent observers (10 residents and six attending radiologists) participated in this study. The radiologists' performance without and with computer assistance, which indicated cases with normal and abnormal findings by various markers, was evaluated by ROC analysis. RESULTS: The diagnostic accuracy of the observers improved by a statistically significant magnitude when computer-aided diagnosis was used. Thus, the values for the area under the ROC curve obtained with and without the computer-aided diagnostic output were .970 and .948 (p = .0002), respectively, for all observers; .969 and .943 (p = .0006), respectively, for the residents' subgroup; and .972 and .960 (p = .162), respectively, for the attending radiologists' subgroup. The value for the area under the ROC curve for the computerized scheme by itself was .943. CONCLUSION: Our computer-aided diagnostic scheme can assist radiologists in the diagnosis or exclusion of interstitial disease on chest radiographs.
OBJECTIVE: Our objective was to evaluate the impact of a computer-aided diagnostic scheme on radiologists' interpretations of chest radiographs with interstitial opacities by performing an observer test using receiver operating characteristic (ROC) analysis. MATERIALS AND METHODS: Twenty chest radiographs with normal findings and 20 chest radiographs with abnormal findings were used. Each radiograph was divided into four quadrants. One hundred twenty-nine quadrants (80 normal and 49 abnormal quadrants) were used for testing because we excluded 31 equivocal quadrants. Sixteen independent observers (10 residents and six attending radiologists) participated in this study. The radiologists' performance without and with computer assistance, which indicated cases with normal and abnormal findings by various markers, was evaluated by ROC analysis. RESULTS: The diagnostic accuracy of the observers improved by a statistically significant magnitude when computer-aided diagnosis was used. Thus, the values for the area under the ROC curve obtained with and without the computer-aided diagnostic output were .970 and .948 (p = .0002), respectively, for all observers; .969 and .943 (p = .0006), respectively, for the residents' subgroup; and .972 and .960 (p = .162), respectively, for the attending radiologists' subgroup. The value for the area under the ROC curve for the computerized scheme by itself was .943. CONCLUSION: Our computer-aided diagnostic scheme can assist radiologists in the diagnosis or exclusion of interstitial disease on chest radiographs.
Authors: Narathip Reamaroon; Michael W Sjoding; Jonathan Gryak; Brian D Athey; Kayvan Najarian; Harm Derksen Journal: Comput Biol Med Date: 2021-05-11 Impact factor: 6.698
Authors: J J Heit; H Coelho; F O Lima; M Granja; A Aghaebrahim; R Hanel; K Kwok; H Haerian; C W Cereda; C Venkatasubramanian; S Dehkharghani; L A Carbonera; J Wiener; K Copeland; F Mont'Alverne Journal: AJNR Am J Neuroradiol Date: 2020-12-24 Impact factor: 3.825
Authors: Dena M Bravata; Vandana Sundaram; Kathryn M McDonald; Wendy M Smith; Herbert Szeto; Mark D Schleinitz; Douglas K Owens Journal: Emerg Infect Dis Date: 2004-01 Impact factor: 6.883