title: Maximum-Intensity-Projection and Computer-Aided-Detection Algorithms as Stand-Alone Reader Devices in Lung Cancer Screening Using Different Dose Levels and Reconstruction Kernels.
abstract: OBJECTIVE
  The objective of our study was to evaluate lung nodule detection rates on standard and microdose chest CT with two different computer-aided detection systems (SyngoCT-CAD, VA 20, Siemens Healthcare [CAD1]; Lung CAD, IntelliSpace Portal DX Server, Philips Healthcare [CAD2]) as well as maximum-intensity-projection (MIP) images. We also assessed the impact of different reconstruction kernels.
  
  
  METHODS
  Standard and microdose CT using three reconstruction kernels (i30, i50, i70) was performed with an anthropomorphic chest phantom. We placed 133 ground-glass and 133 solid nodules (diameters of 5 mm, 8 mm, 10 mm, and 12 mm) in 55 phantoms. Four blinded readers evaluated the MIP images; one recorded the results of CAD1 and CAD2. Sensitivities for CAD and MIP nodule detection on standard dose and microdose CT were calculated for each reconstruction kernel.
  
  
  RESULTS
  Dose for microdose CT was significantly less than that for standard-dose CT (0.1323 mSv vs 1.65 mSv; p < 0.0001). CAD1 delivered superior results compared with CAD2 for standard-dose and microdose CT (p < 0.0001). At microdose level, the best stand-alone sensitivity (97.6%) was comparable with CAD1 sensitivity (96.0%; p = 0.36; both with i30 reconstruction kernel). Pooled sensitivities for all nodules, doses, and reconstruction kernels on CAD1 ranged from 88.9% to 97.3% versus 49.6% to 73.9% for CAD2. The best sensitivity was achieved with standard-dose CT, i50 kernel, and CAD1 (97.3%) versus 96% with microdose CT, i30 or i50 kernel, and CAD1. MIP images and CAD1 had similar performance at both dose levels (p = 0.1313 and p = 0.48).
  
  
  CONCLUSIONS
  Submillisievert CT is feasible for detecting solid and ground-glass nodules that require soft-tissue kernels for MIP and CAD systems to achieve acceptable sensitivities. MIP reconstructions remain a valuable adjunct to the interpretation of chest CT for increasing sensitivity and have the advantage of significantly lower false-positive rates.
authors.affiliation: 1 Department of Radiology, Duke University Medical Center, Box 3808, Durham, NC 27710.
authors.forename: Lukas
authors.initials: L
authors.lastname: Ebner
authors.affiliation: 1 Department of Radiology, Duke University Medical Center, Box 3808, Durham, NC 27710.
authors.forename: Justus E
authors.initials: JE
authors.lastname: Roos
authors.affiliation: 1 Department of Radiology, Duke University Medical Center, Box 3808, Durham, NC 27710.
authors.forename: Jared D
authors.initials: JD
authors.lastname: Christensen
authors.affiliation: 2 Department of Diagnostic, Interventional and Pediatric Radiology, University Hospital Inselspital, Bern, Switzerland.
authors.forename: Tomas
authors.initials: T
authors.lastname: Dobrocky
authors.affiliation: 2 Department of Diagnostic, Interventional and Pediatric Radiology, University Hospital Inselspital, Bern, Switzerland.
authors.forename: Lars
authors.initials: L
authors.lastname: Leidolt
authors.affiliation: 2 Department of Diagnostic, Interventional and Pediatric Radiology, University Hospital Inselspital, Bern, Switzerland.
authors.forename: Barbara
authors.initials: B
authors.lastname: Brela
authors.affiliation: 2 Department of Diagnostic, Interventional and Pediatric Radiology, University Hospital Inselspital, Bern, Switzerland.
authors.forename: Verena C
authors.initials: VC
authors.lastname: Obmann
authors.affiliation: 2 Department of Diagnostic, Interventional and Pediatric Radiology, University Hospital Inselspital, Bern, Switzerland.
authors.forename: Sonya
authors.initials: S
authors.lastname: Joy
authors.affiliation: 3 Department of Cardiovascular and Interventional Radiology, University Hospital Pitié-Salpêtrière, Paris, France.
authors.forename: Adrian
authors.initials: A
authors.lastname: Huber
authors.affiliation: 2 Department of Diagnostic, Interventional and Pediatric Radiology, University Hospital Inselspital, Bern, Switzerland.
authors.forename: Andreas
authors.initials: A
authors.lastname: Christe
mesh_terms: D000465:Algorithms; D055088:Early Detection of Cancer; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D019047:Phantoms, Imaging; D011829:Radiation Dosage; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012680:Sensitivity and Specificity; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging; D014057:Tomography, X-Ray Computed / Q000379:methods*
keywords: CT; computer-aided detection; maximum intensity projection; radiation dose