title: Simulated lesion, human observer performance comparison between thin-section dedicated breast CT images versus computed thick-section simulated projection images of the breast.
abstract: The objective of this study was to compare the lesion detection performance of human observers between thin-section computed tomography images of the breast, with thick-section (>40 mm) simulated projection images of the breast. Three radiologists and six physicists each executed a two alterative force choice (2AFC) study involving simulated spherical lesions placed mathematically into breast images produced on a prototype dedicated breast CT scanner. The breast image data sets from 88 patients were used to create 352 pairs of image data. Spherical lesions with diameters of 1, 2, 3, 5, and 11 mm were simulated and adaptively positioned into 3D breast CT image data sets; the native thin section (0.33 mm) images were averaged to produce images with different slice thicknesses; average section thicknesses of 0.33, 0.71, 1.5 and 2.9 mm were representative of breast CT; the average 43 mm slice thickness served to simulate simulated projection images of the breast.The percent correct of the human observer's responses were evaluated in the 2AFC experiments. Radiologists lesion detection performance was significantly (p < 0.05) better in the case of thin-section images, compared to thick section images similar to mammography, for all but the 1 mm lesion diameter lesions. For example, the average of three radiologist's performance for 3 mm diameter lesions was 92% correct for thin section breast CT images while it was 67% for the simulated projection images. A gradual reduction in observer performance was observed as the section thickness increased beyond about 1 mm. While a performance difference based on breast density was seen in both breast CT and the projection image results, the average radiologist performance using breast CT images in dense breasts outperformed the performance using simulated projection images in fatty breasts for all lesion diameters except 11 mm. The average radiologist performance outperformed that of the average physicist observer, however trends in performance were similar. Human observers demonstrate significantly better mass-lesion detection performance on thin-section CT images of the breast, compared to thick-section simulated projection images of the breast.
authors.affiliation: Department of Radiology, University of California, Davis, CA, USA.
authors.forename: L
authors.initials: L
authors.lastname: Chen
authors.forename: J M
authors.initials: JM
authors.lastname: Boone
authors.forename: C K
authors.initials: CK
authors.lastname: Abbey
authors.forename: J
authors.initials: J
authors.lastname: Hargreaves
authors.forename: C
authors.initials: C
authors.lastname: Bateni
authors.forename: K K
authors.initials: KK
authors.lastname: Lindfors
authors.forename: K
authors.initials: K
authors.lastname: Yang
authors.forename: A
authors.initials: A
authors.lastname: Nosratieh
authors.forename: A
authors.initials: A
authors.lastname: Hernandez
authors.forename: P
authors.initials: P
authors.lastname: Gazi
mesh_terms: D000328:Adult; D000368:Aged; D001940:Breast / Q000473:pathology*; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D003198:Computer Simulation; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D008327:Mammography / Q000379:methods*; D008875:Middle Aged; D015588:Observer Variation; D010364:Pattern Recognition, Visual; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D013647:Task Performance and Analysis; D014057:Tomography, X-Ray Computed / Q000379:methods*
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