Evaluation of three types of reference image data for external beam radiotherapy target localization using digital tomosynthesis (DTS).

Digital tomosynthesis (DTS) is a fast, low-dose three-dimensional (3D) imaging approach which yields slice images with excellent in-plane resolution, though low plane-to-plane resolution. A stack of DTS slices can be reconstructed from a single limited-angle scan, with typical scan angles ranging from 10 degrees to 40 degrees and acquisition times of less than 10 s. The resulting DTS slices show soft tissue contrast approaching that of full cone-beam CT. External beam radiotherapy target localization using DTS requires the registration of on-board DTS images with corresponding reference image data. This study evaluates three types of reference volume: original reference CT, exact reference DTS (RDTS), and a more computationally efficient approximate reference DTS (RDTSapprox), as well as three different DTS scan angles (22 degrees, 44 degrees, and 65 degrees) for the DTS target localization task. Three-dimensional mutual information (MI) shared between reference and onboard DTS volumes was computed in a region surrounding the spine of a chest phantom, as translations spanning +/-5 mm and rotations spanning +/-5 degrees were simulated along each dimension in the reference volumes. The locations of the MI maxima were used as surrogates for registration accuracy, and the width of the MI peaks were used to characterize the registration robustness. The results show that conventional treatment planning CT volumes are inadequate reference volumes for direct registration with on-board DTS data. The efficient RDTSapprox method also appears insufficient for MI-based registration without further refinement of the technique, though it may be suitable for manual registration performed by a human observer. The exact RDTS volumes, on the other hand, delivered a 3D DTS localization accuracy of 0.5 mm and 0.50 along each axis, using only a single 44 degrees coronal on-board DTS scan of the chest phantom.

[1]  B. G. Ziedses des Plantes,et al.  Eine Neue Methode Zur Differenzierung in der Rontgenographie (Planigraphies) , 1932 .

[2]  Fang-Fang Yin,et al.  TH‐C‐330A‐05: Analysis of the Point Spread Function of Isocentric Digital Tomosynthesis (DTS) , 2006 .

[3]  Z. Kolitsi,et al.  Volume imaging for treatment optimisation in radiotherapy , 1995 .

[4]  James T. Dobbins,et al.  Initial application of digital tomosynthesis with on-board imaging in radiation oncology , 2005, SPIE Medical Imaging.

[5]  D. Kopans,et al.  Digital tomosynthesis in breast imaging. , 1997, Radiology.

[6]  D. Godfrey,et al.  Optimization of the matrix inversion tomosynthesis (MITS) impulse response and modulation transfer function characteristics for chest imaging. , 2006, Medical physics.

[7]  C. Beaulieu,et al.  Circular tomosynthesis: potential in imaging of breast and upper cervical spine--preliminary phantom and in vitro study. , 2003, Radiology.

[8]  James T Dobbins,et al.  Digital x-ray tomosynthesis: current state of the art and clinical potential. , 2003, Physics in medicine and biology.

[9]  J H Siewerdsen,et al.  Cone-beam computed tomography with a flat-panel imager: initial performance characterization. , 2000, Medical physics.

[10]  J. Valentin,et al.  Abstract: Avoidance of radiation injuries from medical interventional procedures, ICRP Publication 85 , 2000 .

[11]  J. Wong,et al.  Flat-panel cone-beam computed tomography for image-guided radiation therapy. , 2002, International journal of radiation oncology, biology, physics.

[12]  N Pallikarakis,et al.  Three-dimensional localisation based on projectional and tomographic image correlation: an application for digital tomosynthesis. , 1999, Medical engineering & physics.

[13]  L. Feldkamp,et al.  Practical cone-beam algorithm , 1984 .

[14]  M. Oldham,et al.  Digital tomosynthesis with an on-board kilovoltage imaging device. , 2006, International journal of radiation oncology, biology, physics.

[15]  Jinkoo Kim,et al.  Effects of x-ray and CT image enhancements on the robustness and accuracy of a rigid 3D/2D image registration. , 2005, Medical physics.

[16]  Ismail B. Tutar,et al.  Tomosynthesis-based localization of radioactive seeds in prostate brachytherapy. , 2003, Medical physics.

[17]  Guy Marchal,et al.  Multimodality image registration by maximization of mutual information , 1997, IEEE Transactions on Medical Imaging.

[18]  Timothy M. Persons Three‐dimensional tomosynthetic image restoration for brachytherapy source localization , 2001 .

[19]  Z. Kolitsi,et al.  427A localization tool on the basis of digital tomosynthesis , 1996 .

[20]  J A Rowlands,et al.  Just-in-time tomography (JiTT): a new concept for image-guided radiation therapy. , 2005, Physics in medicine and biology.

[21]  Berthold K. P. Horn,et al.  Closed-form solution of absolute orientation using orthonormal matrices , 1988 .

[22]  Hui Yan,et al.  SU‐CC‐ValA‐01: Automatic Comparison Between Reference and On Board Digital Tomosynthesis for Target Localization , 2006 .

[23]  David A Jaffray,et al.  Patient dose from kilovoltage cone beam computed tomography imaging in radiation therapy. , 2006, Medical physics.

[24]  D. Kopans,et al.  Tomographic mammography using a limited number of low-dose cone-beam projection images. , 2003, Medical physics.

[25]  Mark Oldham,et al.  Cone-beam-CT guided radiation therapy: A model for on-line application. , 2005, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[26]  D. G. Grant Tomosynthesis: a three-dimensional radiographic imaging technique. , 1972, IEEE transactions on bio-medical engineering.

[27]  M. Oldham,et al.  Cone-beam-CT guided radiation therapy: technical implementation. , 2005, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.