title: Multiple diagnostic task performance in CT examination of the chest.
abstract: In three experiments, we studied the detection of multiple abnormality types using the satisfaction of search (SOS) paradigm, the provision of a computer-aided detection (CAD) of pulmonary nodules and a focused nodule detection task.
  
  
  
  51 chest CT examinations (24 that demonstrated subtle pulmonary nodules and 27 that demonstrated no pulmonary nodules) were read by 15 radiology residents and fellows under two experimental conditions: (1) when there were no other abnormalities present except test abnormalities in the exams (non-SOS condition), and (2) when other abnormalities were present in the exams (SOS condition). Trials from the two conditions were intermixed. Readers were invited to return for two sessions: one in which the SOS condition was repeated with a simulated CAD; another in which only the non-SOS condition was presented. Detection accuracy was measured using receiver operating characteristic (ROC) analysis.
  
  
  
  An SOS effect (reduced detection accuracy for the test nodules in the presence of the diverse added abnormalities) was not found. Average accuracy was much higher when the CAD prompt was provided, without cost in the detection of the added abnormalities. Accuracy for detecting nodules appearing without intermixed SOS trials was also substantially improved.
  
  
  
  CT interpretation was highly task dependent. Nodule detection was poor in the general search task. Therefore, CAD may offer a greater performance improvement than demonstrated in experiments assessing CAD using focused search. The absence of SOS may be due to limited nodule detection even without other abnormalities. Advances in knowledge CAD prompts of nodules increase the detection accuracy of nodules and decrease the time to detection-without impairing the detection accuracy-of non-nodule abnormalities.
authors.affiliation: Department of Radiology, The University of Iowa , Roy J. and Lucille A. Carver College of Medicine, Iowa City, IA, USA. kevin-schartz@uiowa.edu
authors.forename: K M
authors.initials: KM
authors.lastname: Schartz
authors.forename: K S
authors.initials: KS
authors.lastname: Berbaum
authors.forename: M T
authors.initials: MT
authors.lastname: Madsen
authors.forename: B H
authors.initials: BH
authors.lastname: Thompson
authors.forename: B F
authors.initials: BF
authors.lastname: Mullan
authors.forename: R T
authors.initials: RT
authors.lastname: Caldwell
authors.forename: B
authors.initials: B
authors.lastname: Hammett
authors.forename: A N
authors.initials: AN
authors.lastname: Ellingson
authors.forename: E A
authors.initials: EA
authors.lastname: Franken
mesh_terms: D000465:Algorithms; D005188:False Negative Reactions; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D015588:Observer Variation; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D013902:Radiography, Thoracic / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed / Q000379:methods*