title: Low-dose preview for patient-specific, task-specific technique selection in cone-beam CT.
abstract: OBJECTIVE
  A method is presented for generating simulated low-dose cone-beam CT (CBCT) preview images from which patient- and task-specific minimum-dose protocols can be confidently selected prospectively in clinical scenarios involving repeat scans.
  
  
  METHODS
  In clinical scenarios involving a series of CBCT images, the low-dose preview (LDP) method operates upon the first scan to create a projection dataset that accurately simulates the effects of dose reduction in subsequent scans by injecting noise of proper magnitude and correlation, including both quantum and electronic readout noise as important components of image noise in flat-panel detector CBCT. Experiments were conducted to validate the LDP method in both a head phantom and a cadaveric torso by performing CBCT acquisitions spanning a wide dose range (head: 0.8-13.2 mGy, body: 0.8-12.4 mGy) with a prototype mobile C-arm system. After injecting correlated noise to simulate dose reduction, the projections were reconstructed using both conventional filtered backprojection (FBP) and an iterative, model-based image reconstruction method (MBIR). The LDP images were then compared to real CBCT images in terms of noise magnitude, noise-power spectrum (NPS), spatial resolution, contrast, and artifacts.
  
  
  RESULTS
  For both FBP and MBIR, the LDP images exhibited accurate levels of spatial resolution and contrast that were unaffected by the correlated noise injection, as expected. Furthermore, the LDP image noise magnitude and NPS were in strong agreement with real CBCT images acquired at the corresponding, reduced dose level across the entire dose range considered. The noise magnitude agreed within 7% for both the head phantom and cadaveric torso, and the NPS showed a similar level of agreement up to the Nyquist frequency. Therefore, the LDP images were highly representative of real image quality across a broad range of dose and reconstruction methods. On the other hand, naïve injection ofuncorrelated noise resulted in strong underestimation of the true noise, which would lead to overly optimistic predictions of dose reduction.
  
  
  CONCLUSIONS
  Correlated noise injection is essential to accurate simulation of CBCT image quality at reduced dose. With the proposed LDP method, the user can prospectively select patient-specific, minimum-dose protocols (viz., acquisition technique and reconstruction method) suitable to a particular imaging task and to the user's own observer preferences for CBCT scans following the first acquisition. The method could provide dose reduction in common clinical scenarios involving multiple CBCT scans, such as image-guided surgery and radiotherapy.
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205.
authors.forename: Adam S
authors.initials: AS
authors.lastname: Wang
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205.
authors.forename: J Webster
authors.initials: JW
authors.lastname: Stayman
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205.
authors.forename: Yoshito
authors.initials: Y
authors.lastname: Otake
authors.affiliation: Siemens Healthcare XP Division, Erlangen 91052, Germany.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Vogt
authors.affiliation: Siemens Healthcare XP Division, Erlangen 91052, Germany.
authors.forename: Gerhard
authors.initials: G
authors.lastname: Kleinszig
authors.affiliation: Department of Orthopaedic Surgery, Johns Hopkins University, Baltimore, Maryland 21205.
authors.forename: A Jay
authors.initials: AJ
authors.lastname: Khanna
authors.affiliation: Department of Neurosurgery, Johns Hopkins University, Baltimore, Maryland 21205.
authors.forename: Gary L
authors.initials: GL
authors.lastname: Gallia
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205.
authors.forename: Jeffrey H
authors.initials: JH
authors.lastname: Siewerdsen
mesh_terms: D000465:Algorithms; D016477:Artifacts; D002138:Calibration; D003198:Computer Simulation; D054893:Cone-Beam Computed Tomography / Q000295:instrumentation / Q000379:methods*; D006257:Head / Q000000981:diagnostic imaging; D006801:Humans; D008954:Models, Biological; D019047:Phantoms, Imaging; D011829:Radiation Dosage; D060726:Torso / Q000000981:diagnostic imaging