A Novel Markerless Technique to Evaluate Daily Lung Tumor Motion Based on Conventional Cone-Beam CT Projection Data

Department of Computer Science, University of Texas at Dallas, Richardson, TX, USA.
International journal of radiation oncology, biology, physics (Impact Factor: 4.26). 02/2012; 82(5):e749-56. DOI: 10.1016/j.ijrobp.2011.11.035
Source: PubMed


In this study, we present a novel markerless technique, based on cone beam computed tomography (CBCT) raw projection data, to evaluate lung tumor daily motion.
The markerless technique, which uses raw CBCT projection data and locates tumors directly on every projection, consists of three steps. First, the tumor contour on the planning CT is used to create digitally reconstructed radiographs (DRRs) at every projection angle. Two sets of DRRs are created: one showing only the tumor, and another with the complete anatomy without the tumor. Second, a rigid two-dimensional image registration is performed to register the DRR set without the tumor to the CBCT projections. After the registration, the projections are subtracted from the DRRs, resulting in a projection dataset containing primarily tumor. Finally, a second registration is performed between the subtracted projection and tumor-only DRR. The methodology was evaluated using a chest phantom containing a moving tumor, and retrospectively in 4 lung cancer patients treated by stereotactic body radiation therapy. Tumors detected on projection images were compared with those from three-dimensional (3D) and four-dimensional (4D) CBCT reconstruction results.
Results in both static and moving phantoms demonstrate that the accuracy is within 1 mm. The subsequent application to 22 sets of CBCT scan raw projection data of 4 lung cancer patients includes about 11,000 projections, with the detected tumor locations consistent with 3D and 4D CBCT reconstruction results. This technique reveals detailed lung tumor motion and provides additional information than conventional 4D images.
This technique is capable of accurately characterizing lung tumor motion on a daily basis based on a conventional CBCT scan. It provides daily verification of the tumor motion to ensure that these motions are within prior estimation and covered by the treatment planning volume.

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    • "Template matching usually involves 2D–2D matching (Berbeco et al 2005, Cui et al 2007, Lin et al 2009, Xu et al 2008) or 2D–3D matching (Gendrin et al 2012, Hugo et al 2010, Lewis et al 2010, Rohlfing et al 2005, Schweikard et al 2005, Yang et al 2012), and is usually performed over all breathing phases to identify the best match. This process can be called 2D/4D matching, and has been used to track tumors for both planar fluoroscopy (Berbeco et al 2005, Cui et al 2007, Lin et al 2009, Xu et al 2008) and rotational cone beam computed tomography (CBCT) projections (Gendrin et al 2012, Hugo et al 2010, Lewis et al 2010, Rohlfing et al 2005, Schweikard et al 2005, Yang et al 2012). "
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    ABSTRACT: Tumor motion caused by respiration is an important issue in image-guided radiotherapy. A 2D/4D matching method between 4D volumes derived from cone beam computed tomography (CBCT) and 2D fluoroscopic images was implemented to track the tumor motion without the use of implanted markers. In this method, firstly, 3DCBCT and phase-rebinned 4DCBCT are reconstructed from cone beam acquisition. Secondly, 4DCBCT volumes and a streak-free 3DCBCT volume are combined to improve the image quality of the digitally reconstructed radiographs (DRRs). Finally, the 2D/4D matching problem is converted into a 2D/2D matching between incoming projections and DRR images from each phase of the 4DCBCT. The diaphragm is used as a target surrogate for matching instead of using the tumor position directly. This relies on the assumption that if a patient has the same breathing phase and diaphragm position as the reference 4DCBCT, then the tumor position is the same. From the matching results, the phase information, diaphragm position and tumor position at the time of each incoming projection acquisition can be derived. The accuracy of this method was verified using 16 candidate datasets, representing lung and liver applications and one-minute and two-minute acquisitions. The criteria for the eligibility of datasets were described: 11 eligible datasets were selected to verify the accuracy of diaphragm tracking, and one eligible dataset was chosen to verify the accuracy of tumor tracking. The diaphragm matching accuracy was 1.88 ± 1.35 mm in the isocenter plane and the 2D tumor tracking accuracy was 2.13 ± 1.26 mm in the isocenter plane. These features make this method feasible for real-time marker-free tumor motion tracking purposes.
    Physics in Medicine and Biology 04/2014; 59(9):2219-2233. DOI:10.1088/0031-9155/59/9/2219 · 2.76 Impact Factor
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    • "In their methods, only MV images were used without the use of kV images. Mao et al used raw cone beam CT (CBCT) projection data and located tumors directly on every projection (Yang et al 2012). First, the tumor contour on the planning CT was used to create digitally reconstructed radiographs (DRRs) at every projection angle. "
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    Physics in Medicine and Biology 05/2013; 58(11):3615-3630. DOI:10.1088/0031-9155/58/11/3615 · 2.76 Impact Factor
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    International journal of radiation oncology, biology, physics 10/2012; 84(2):304; author reply 304-5. DOI:10.1016/j.ijrobp.2012.05.025 · 4.26 Impact Factor
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