title: Computer-aided detection (CAD) in lung cancer screening at chest MDCT: ROC analysis of CAD versus radiologist performance.
abstract: To evaluate the performance of a computer-aided detection (CAD) algorithm in the detection of pulmonary nodules on high-resolution multidetector row computed tomography images in a large, homogeneous screening population, and to evaluate the effect of the system output on the performance of radiologists, using receiver operating characteristic analysis. Three radiologists with variable experience (1 to 7 y), independently read the 200 computed tomography scans and assigned each nodule candidate a confidence score (1-2-3: unlikely, probably, and definitely a nodule). CAD was applied to all scans; successively readers reevaluated all findings of the CAD, assigning, in consensus, a confidence score (1 to 3). The reference standard was established by the consensus of 2 experienced radiologists with 30 and 15 years of experience. Results were used to generate an free-response receiver operating characteristic analysis. The reference standard showed 125 nodules. Sensitivity for readers I-II-III was 57%, 68%, and 46%. A double reading resulted in an increase in sensitivity up to 75%. With CAD, sensitivity was increased to 94%, 96%, and 94% for readers I, II, and III. The area under the free-response receiver operating characteristic curve (Az) was 0.72, 0.82, 0.55, and 0.84 for readers I, II, III, and the CAD, when considering all nodules. Differences between readers I-II and CAD were not significant (P=0.9). There was a significant difference between reader III and the CAD. For nodules <6-mm Az was 0.40, 0.47, 0.14, and 0.72 for readers I, II, III, and the CAD. Differences between all readers and the CAD were significant (P<0.05). CAD can aid in daily radiologic routine detecting a substantial number of nodules unseen by radiologists. This is true for both board-certified radiologists and for less experienced readers especially in the detection of small nodules.
authors.affiliation: Department of Radiological Sciences, University of Rome La Sapienza, Viale Regina Elena 324, Rome, Italy. Francesco.Fraioli@uniroma1.it
authors.forename: Francesco
authors.initials: F
authors.lastname: Fraioli
authors.forename: Linda
authors.initials: L
authors.lastname: Bertoletti
authors.forename: Alessandro
authors.initials: A
authors.lastname: Napoli
authors.forename: Federica
authors.initials: F
authors.lastname: Pediconi
authors.forename: Francesca Antonella
authors.initials: FA
authors.lastname: Calabrese
authors.forename: Raffaele
authors.initials: R
authors.lastname: Masciangelo
authors.forename: Carlo
authors.initials: C
authors.lastname: Catalano
authors.forename: Roberto
authors.initials: R
authors.lastname: Passariello
mesh_terms: D002983:Clinical Competence; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D016273:Occupational Exposure; D016495:Police; D012372:ROC Curve; D011857:Radiographic Image Interpretation, Computer-Assisted; D013902:Radiography, Thoracic; D012680:Sensitivity and Specificity; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed / Q000379:methods*; D001335:Vehicle Emissions / Q000633:toxicity
chemical_list: D001335:Vehicle Emissions