An initial study on the estimation of time‐varying volumetric treatment images and 3D tumor localization from single MV cine EPID images. Issue 8 (30th November 2016)

• Record Type: Journal Article
• Authors: Mishra, Pankaj; Li, Ruijiang; Mak, Raymond H.; Rottmann, Joerg; Bryant, Jonathan H.; Williams, Christopher L.; Berbeco, Ross I.; Lewis, John H.
• Is Part Of: Medical physics. Volume 41:Issue 8(2014)Part 1
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-11-30
• Subjects: Computed tomography -- Biomedical instrumentation and transducers, including micro‐electro‐mechanical systems (MEMS) -- Pneumodyamics, respiration -- Registration -- Reconstruction -- Radiography; biomedical equipment -- computerised tomography -- diagnostic radiography -- eigenvalues and eigenfunctions -- image reconstruction -- image registration -- image representation -- lung -- medical image processing -- patient treatment -- phantoms -- pneumodynamics -- principal component analysis -- tumours; MV imaging -- lung motion model -- cine EPID images -- 4DCT -- treatment verification; Computerised tomographs -- Biological material, e.g. blood, urine; Haemocytometers -- Digital computing or data processing equipment or methods, specially adapted for specific applications -- Image data processing or generation, in general; Cancer -- Image guided radiation therapy -- Lungs -- Eigenvalues -- Digital radiography -- Three dimensional image processing -- Dosimetry -- Linear accelerators; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4889779
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: In this work the authors develop and investigate the feasibility of a method to estimate time‐varying volumetric images from individual MV cine electronic portal image device (EPID) images. Methods: The authors adopt a two‐step approach to time‐varying volumetric image estimation from a single cine EPID image. In the first step, a patient‐specific motion model is constructed from 4DCT. In the second step, parameters in the motion model are tuned according to the information in the EPID image. The patient‐specific motion model is based on a compact representation of lung motion represented in displacement vector fields (DVFs). DVFs are calculated through deformable image registration (DIR) of a reference 4DCT phase image (typically peak‐exhale) to a set of 4DCT images corresponding to different phases of a breathing cycle. The salient characteristics in the DVFs are captured in a compact representation through principal component analysis (PCA). PCA decouples the spatial and temporal components of the DVFs. Spatial information is represented in eigenvectors and the temporal information is represented by eigen‐coefficients. To generate a new volumetric image, the eigen‐coefficients are updated via cost function optimization based on digitally reconstructed radiographs and projection images. The updated eigen‐coefficients are then multiplied with the eigenvectors to obtain updated DVFs that, in turn, give the volumetric image corresponding to the cine EPID image. Results: The algorithm was tested on (1) Eight digital eX tendedCA rdiac‐T orso phantom datasets based on different irregular patient breathing patterns and (2) patient cine EPID images acquired during SBRT treatments. The root‐mean‐squared tumor localization error is (0.73 ± 0.63 mm) for the XCAT data and (0.90 ± 0.65 mm) for the patient data. Conclusions: The authors introduced a novel method of estimating volumetric time‐varying images from single cine EPID images and a PCA‐based lung motion model. This is the first method to estimate volumetric time‐varying images from single MV cine EPID images, and has the potential to provide volumetric information with no additional imaging dose to the patient.