title: Primary three-dimensional analysis with perspective-filet view versus primary two-dimensional analysis: evaluation of lesion detection by inexperienced readers at computed tomographic colonography in symptomatic patients.
abstract: BACKGROUND
  "Perspective-filet view" is a novel three-dimensional (3D) viewing technique for computed tomography colonography (CTC). Studies with experienced readers have shown a sensitivity for perspective-filet view similar to that of 2D or 3D endoluminal fly-through in detection of colorectal lesions. It is not known whether perspective-filet view, compared to axial images, improves lesion detection by inexperienced readers.
  
  
  OBJECTIVE
  To compare primary 3D analysis using perspective-filet view (3D Filet) with primary 2D analysis, as used by inexperienced CTC readers. Secondary aims were to compare lesion detection by 3D Filet when used by experienced and inexperienced readers, and to evaluate the effect of combined 3D Filet + 2D analysis.
  
  
  METHODS
  Fifty symptomatic patients were prospectively enrolled. An experienced reader performed 3D Filet analysis followed by complete 2D analysis (3D Filet + 2D), before colonoscopy with segmental unblinding. Two inexperienced readers (readers 2 and 3), blinded to CTC and colonoscopy findings, retrospectively performed 3D Filet analysis and, after 5 weeks, 2D analysis. True positives >or=6 mm detected by the inexperienced readers with 3D Filet and/or 2D were combined to obtain 3D Filet + 2D.
  
  
  RESULTS
  Colonoscopy revealed 116 lesions: 16 lesions >or=10 mm, 19 lesions 6-9 mm, and 81 lesions <or=5 mm. For the experienced reader, sensitivities for lesions >or=6 mm with 3D Filet and 3D Filet + 2D were 77% and 83%, respectively. For the inexperienced readers, sensitivities for lesions >or=6 mm with 3D Filet and 2D were 51% and 57% (reader 2) and 40% and 43% (reader 3), respectively. There was no significant difference between 3D Filet and 2D regarding sensitivity and reading time. For lesions >or=6 mm, 3D Filet + 2D improved the sensitivity of reader 2 to 63% and of reader 3 to 51%.
  
  
  CONCLUSIONS
  Lesion detection by inexperienced readers using perspective-filet view is comparable to that obtained by 2D. Lesion detection improves by combining 3D Filet + 2D, but not to the level of an experienced reader.
authors.affiliation: Department of Radiology, Sahlgrenska University Hospital and Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. valeria.fisichella@vgregion.se
authors.forename: V A
authors.initials: VA
authors.lastname: Fisichella
authors.forename: F
authors.initials: F
authors.lastname: Jäderling
authors.forename: S
authors.initials: S
authors.lastname: Horvath
authors.forename: P-O
authors.initials: PO
authors.lastname: Stotzer
authors.forename: A
authors.initials: A
authors.lastname: Kilander
authors.forename: M
authors.initials: M
authors.lastname: Hellström
mesh_terms: D000230:Adenocarcinoma / Q000000981:diagnostic imaging* / Q000453:epidemiology; D000236:Adenoma / Q000000981:diagnostic imaging* / Q000453:epidemiology*; D000368:Aged; D000369:Aged, 80 and over; D002983:Clinical Competence; D003111:Colonic Polyps / Q000000981:diagnostic imaging* / Q000453:epidemiology*; D023881:Colonography, Computed Tomographic / Q000379:methods* / Q000706:statistics & numerical data*; D003113:Colonoscopy; D015179:Colorectal Neoplasms / Q000000981:diagnostic imaging* / Q000453:epidemiology*; D003287:Contrast Media / Q000008:administration & dosage; D004502:Education, Medical, Continuing; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods* / Q000706:statistics & numerical data*; D021621:Imaging, Three-Dimensional / Q000379:methods* / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D011871:Radiology / Q000193:education*; D012680:Sensitivity and Specificity; D012984:Software; D013996:Time and Motion Studies; D014283:Triiodobenzoic Acids
chemical_list: D003287:Contrast Media; D014283:Triiodobenzoic Acids; C044834:iodixanol