title: Effect of a computer-aided diagnosis system on clinicians' performance in detection of small acute intracranial hemorrhage on computed tomography.
abstract: OBJECTIVE
  To analyze the effect of a computer-aided diagnosis (CAD) system on clinicians' performance in detection of small acute intracranial hemorrhage (AIH) on computed tomography (CT).
  
  
  METHODS
  The authors have developed a CAD scheme that used both image processing techniques and anatomic knowledge based classification system to improve diagnosis of small AIH on CT. A multiple-reader, multiple-case receiver operating characteristic (ROC) study was performed. Twenty clinicians, including seven emergency physicians, seven radiology residents, and six radiology specialists were recruited as readers of 60 sets of brain CT, including 30 cases that show AIH smaller than 1 cm, and 30 controls. Each reader read the same 60 cases twice, first without, then with the prompts produced by the CAD system. The clinicians ranked their confidence in diagnosing a case of showing AIH, which produced the ROC curves.
  
  
  RESULTS
  Significantly improved performance is observed in emergency physicians, average area under the ROC curve (Az) increased from 0.8422 to 0.9294 (P = .0107) when they make the diagnosis without and with the support of CAD. Az for radiology residents increased from 0.9371 to 0.9762 (P = .0088). Az for radiology specialists increased from 0.9742 to 0.9868, but was statistically insignificant (P = .1755).
  
  
  CONCLUSIONS
  CAD can improve the clinicians' performance in detecting AIH on CT. In particular, emergency physicians can benefit most from the CAD and improve their performance to a level approaching that of the average radiology residents.
authors.affiliation: Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong. taochan@hkcr.org
authors.forename: Tao
authors.initials: T
authors.lastname: Chan
authors.forename: H K
authors.initials: HK
authors.lastname: Huang
mesh_terms: D000208:Acute Disease; D000465:Algorithms; D019540:Area Under Curve; D002983:Clinical Competence; D003936:Diagnosis, Computer-Assisted; D004635:Emergency Medicine; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007091:Image Processing, Computer-Assisted / Q000379:methods; D007396:Internship and Residency; D020300:Intracranial Hemorrhages / Q000000981:diagnostic imaging*; D051188:Knowledge Bases; D015588:Observer Variation; D012372:ROC Curve; D011871:Radiology / Q000193:education; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*