title: A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging.
abstract: OBJECTIVE
  4D cone beam CT (4D-CBCT) has been utilized in radiation therapy to provide 4D image guidance in lung and upper abdomen area. However, clinical application of 4D-CBCT is currently limited due to the long scan time and low image quality. The purpose of this paper is to develop a new 4D-CBCT reconstruction method that restores volumetric images based on the 1-min scan data acquired with a standard 3D-CBCT protocol.
  
  
  METHODS
  The model optimizes a deformation vector field that deforms a patient-specific planning CT (p-CT), so that the calculated 4D-CBCT projections match measurements. A forward-backward splitting (FBS) method is invented to solve the optimization problem. It splits the original problem into two well-studied subproblems, i.e., image reconstruction and deformable image registration. By iteratively solving the two subproblems, FBS gradually yields correct deformation information, while maintaining high image quality. The whole workflow is implemented on a graphic-processing-unit to improve efficiency. Comprehensive evaluations have been conducted on a moving phantom and three real patient cases regarding the accuracy and quality of the reconstructed images, as well as the algorithm robustness and efficiency.
  
  
  RESULTS
  The proposed algorithm reconstructs 4D-CBCT images from highly under-sampled projection data acquired with 1-min scans. Regarding the anatomical structure location accuracy, 0.204 mm average differences and 0.484 mm maximum difference are found for the phantom case, and the maximum differences of 0.3-0.5 mm for patients 1-3 are observed. As for the image quality, intensity errors below 5 and 20 HU compared to the planning CT are achieved for the phantom and the patient cases, respectively. Signal-noise-ratio values are improved by 12.74 and 5.12 times compared to results from FDK algorithm using the 1-min data and 4-min data, respectively. The computation time of the algorithm on a NVIDIA GTX590 card is 1-1.5 min per phase.
  
  
  CONCLUSIONS
  High-quality 4D-CBCT imaging based on the clinically standard 1-min 3D CBCT scanning protocol is feasible via the proposed hybrid reconstruction algorithm.
authors.affiliation: Department of Radiation Oncology, The University of Texas, Southwestern Medical Center, Dallas, Texas 75390.
authors.forename: Hao
authors.initials: H
authors.lastname: Yan
authors.affiliation: Department of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong 510515, China.
authors.forename: Xin
authors.initials: X
authors.lastname: Zhen
authors.affiliation: Department of Radiation Oncology, The University of Texas, Southwestern Medical Center, Dallas, Texas 75390.
authors.forename: Michael
authors.initials: M
authors.lastname: Folkerts
authors.affiliation: Department of Radiation Oncology, The University of Texas, Southwestern Medical Center, Dallas, Texas 75390 and Department of Engineering Physics, Tsinghua University, Beijing 100084, China.
authors.forename: Yongbao
authors.initials: Y
authors.lastname: Li
authors.affiliation: Department of Imaging Physics, The University of Texas, MD Anderson Cancer Center, Houston, Texas 77030.
authors.forename: Tinsu
authors.initials: T
authors.lastname: Pan
authors.affiliation: Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California 92093.
authors.forename: Laura
authors.initials: L
authors.lastname: Cervino
authors.affiliation: Department of Radiation Oncology, The University of Texas, Southwestern Medical Center, Dallas, Texas 75390.
authors.forename: Steve B
authors.initials: SB
authors.lastname: Jiang
authors.affiliation: Department of Radiation Oncology, The University of Texas, Southwestern Medical Center, Dallas, Texas 75390.
authors.forename: Xun
authors.initials: X
authors.lastname: Jia
mesh_terms: D000465:Algorithms; D003201:Computers; D054893:Cone-Beam Computed Tomography / Q000295:instrumentation / Q000379:methods*; D005240:Feasibility Studies; D056973:Four-Dimensional Computed Tomography / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D008962:Models, Theoretical; D009038:Motion; D019047:Phantoms, Imaging; D013997:Time Factors