title: Examination of a deformable motion model for respiratory movements and 4D dose calculations using different driving surrogates.
abstract: OBJECTIVE
  The aim of this study was to evaluate a surrogate-driven motion model based on four-dimensional computed tomography that is able to predict CT volumes corresponding to arbitrary respiratory phases. Furthermore, the comparison of three different driving surrogates is examined and the feasibility of using the model for 4D dose re-calculation will be discussed.
  
  
  METHODS
  The study is based on repeated 4DCTs of twenty patients treated for bronchial carcinoma and metastasis. The motion model was estimated from the planning 4DCT through deformable image registration. To predict a certain phase of a follow-up 4DCT, the model considers inter-fractional variations (baseline correction) and intra-fractional respiratory parameters (amplitude and phase) derived from surrogates. The estimated volumes resulting from the model were compared to ground-truth clinical 4DCTs using absolute HU differences in the lung region and landmarks localized using the Scale Invariant Feature Transform. Finally, the γ-index was used to evaluate the dosimetric effects of the intensity differences measured between the estimated and the ground-truth CT volumes.
  
  
  RESULTS
  The results show absolute HU differences between estimated and ground-truth images with median value (± standard deviation) of (61.3 ± 16.7) HU. Median 3D distances, measured on about 400 matching landmarks in each volume, were (2.9 ± 3.0) mm. 3D errors up to 28.2 mm were found for CT images with artifacts or reduced quality. Pass rates for all surrogate approaches were above 98.9% with a γ-criterion of 2%/2 mm.
  
  
  CONCLUSIONS
  The results depend mainly on the image quality of the initial 4DCT and the deformable image registration. All investigated surrogates can be used to estimate follow-up 4DCT phases, however, uncertainties decrease for volumetric approaches. Application of the model for 4D dose calculations is feasible.
authors.affiliation: Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91054, Erlangen, Germany.
authors.forename: Jens
authors.initials: J
authors.lastname: Wölfelschneider
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133, Milan, Italy.
authors.forename: Matteo
authors.initials: M
authors.lastname: Seregni
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133, Milan, Italy.
authors.forename: Aurora
authors.initials: A
authors.lastname: Fassi
authors.affiliation: Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91054, Erlangen, Germany.
authors.forename: Marc
authors.initials: M
authors.lastname: Ziegler
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133, Milan, Italy.
authors.forename: Guido
authors.initials: G
authors.lastname: Baroni
authors.affiliation: Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91054, Erlangen, Germany.
authors.forename: Rainer
authors.initials: R
authors.lastname: Fietkau
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133, Milan, Italy.
authors.forename: Marco
authors.initials: M
authors.lastname: Riboldi
authors.affiliation: Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91054, Erlangen, Germany.
authors.forename: Christoph
authors.initials: C
authors.lastname: Bert
mesh_terms: D016477:Artifacts; D056973:Four-Dimensional Computed Tomography; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D009038:Motion; D011874:Radiometry; D011880:Radiotherapy Planning, Computer-Assisted; D012119:Respiration
keywords: 4D dose reconstruction; 4DCT; respiratory motion model; scale invariant feature transform; surrogates