4D-CT Lung Registration and its Application for Lung Radiation Therapy

Radiation therapy has been successful in treating lung cancer patients, but its efficacy is limited by the inability to account for the respiratory motion during treatment planning and radiation dose delivery. Physics-based lung deformation models facilitate the motion computation of both tumor and local lung tissue during radiation therapy. In this dissertation, a novel method is discussed to accurately register 3D lungs across the respiratory phases from 4D-CT datasets, which facilitates the estimation of the volumetric lung deformation models. This method uses multi-level and multi-resolution optical flow registration coupled with thin plate splines (TPS), to address registration issue of inconsistent intensity across respiratory phases. It achieves higher accuracy as compared to multi-resolution optical flow registration and other commonly used registration methods. Results of validation show that the lung registration is computed with 3 mm Target Registration Error (TRE) and approximately 3 mm Inverse Consistency Error (ICE). This registration method is further implemented in GPU based real time dose delivery simulation to assist radiation therapy planning.

[1]  A. Lunde,et al.  Health in the United States , 1968, Nature.

[2]  John F. Nunn,et al.  Respiratory Physiology—the essentials , 1975 .

[3]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[4]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[5]  E. Mok,et al.  A photon dose distribution model employing convolution calculations. , 1985, Medical physics.

[6]  R. Siddon.  Fast calculation of the exact radiological path for a three-dimensional CT array. , 1985, Medical physics.

[7]  J. Battista,et al.  A convolution method of calculating dose for 15-MV x rays. , 1985, Medical physics.

[8]  John A. H. Lee.  Health: United States , 1986 .

[9]  Gerald Farin,et al.  Geometric modeling : algorithms and new trends , 1987 .

[10]  J J Battista,et al.  Generation of photon energy deposition kernels using the EGS Monte Carlo code. , 1988, Physics in medicine and biology.

[11]  A. Boyer,et al.  Fast Fourier transform convolution calculations of x-ray isodose distributions in homogeneous media. , 1989, Medical physics.

[12]  N Papanikolaou,et al.  Investigation of the convolution method for polyenergetic spectra. , 1993, Medical physics.

[13]  C. Rubin,et al.  Systematic Reviews: Synthesis of Best Evidence for Health Care Decisions , 1998, Annals of Internal Medicine.

[14]  Thomas Ertl,et al.  Accelerating 3D convolution using graphics hardware , 1999, Proceedings Visualization '99 (Cat. No.99CB37067).

[15]  James S. Duncan,et al.  Rigid point feature registration using mutual information , 1999, Medical Image Anal..

[16]  Li Fan,et al.  3D warping and registration from lung images , 1999, Medical Imaging.

[17]  Gary E. Christensen,et al.  Landmark and Intensity-Based, Consistent Thin-Plate Spline Image Registration , 2001, IPMI.

[18]  Margrit Betke,et al.  Automatic 3D Registration of Lung Surfaces in Computed Tomography Scans , 2001, MICCAI.

[19]  Gary E. Christensen,et al.  Consistent landmark and intensity-based image registration , 2002, IEEE Transactions on Medical Imaging.

[20]  Margrit Betke,et al.  Landmark detection in the chest and registration of lung surfaces with an application to nodule registration , 2003, Medical Image Anal..

[21]  Geoffrey G. Zhang,et al.  Intrathoracic tumour motion estimation from CT imaging using the 3D optical flow method. , 2004, Physics in medicine and biology.

[22]  Shinichi Shimizu,et al.  Intrafractional tumor motion: lung and liver. , 2004, Seminars in radiation oncology.

[23]  R. Jeraj,et al.  Treatment plan optimization incorporating respiratory motion. , 2004, Medical physics.

[24]  D. Hawkes,et al.  Modelling Respiratory Motion for Optimisation of Lung Cancer Radiotherapy Using Fast MR Imaging and Intensity-Based Image Registration , 2004 .

[25]  Geoffrey McLennan,et al.  Estimation of regional lung expansion via 3D image registration , 2005, SPIE Medical Imaging.

[26]  Markus Hadwiger,et al.  Real-time volume graphics , 2006, Eurographics.

[27]  Tinsu Pan,et al.  Dynamic ventilation imaging from four-dimensional computed tomography , 2006, Physics in medicine and biology.

[28]  J. McClelland,et al.  A continuous 4D motion model from multiple respiratory cycles for use in lung radiotherapy. , 2006, Medical physics.

[29]  Wei Lu,et al.  Tracking lung tissue motion and expansion/compression with inverse consistent image registration and spirometry. , 2007, Medical physics.

[30]  D. Brenner,et al.  Computed tomography--an increasing source of radiation exposure. , 2007, The New England journal of medicine.

[31]  Anna Hilsmann,et al.  Deformable 4DCT lung registration with vessel bifurcations , 2007 .

[32]  Cristian Lorenz,et al.  4DCT image-based lung motion field extraction and analysis , 2008, SPIE Medical Imaging.

[33]  Geoffrey G. Zhang,et al.  Use of three‐dimensional (3D) optical flow method in mapping 3D anatomic structure and tumor contours across four‐dimensional computed tomography data , 2008, Journal of applied clinical medical physics.

[34]  B. Aggarwal,et al.  Cancer is a Preventable Disease that Requires Major Lifestyle Changes , 2008, Pharmaceutical Research.

[35]  Deshan Yang,et al.  A fast inverse consistent deformable image registration method based on symmetric optical flow computation , 2008, 2008 42nd Asilomar Conference on Signals, Systems and Computers.

[36]  Patrick A Kupelian,et al.  Observations on real-time prostate gland motion using electromagnetic tracking. , 2008, International journal of radiation oncology, biology, physics.

[37]  F. Mastik,et al.  A study of coronary artery rotational motion with dense scale-space optical flow in intravascular ultrasound , 2009, Physics in medicine and biology.

[38]  Cancer Facts & Figures 2021 , 2010 .

[39]  Yugang Min,et al.  A GPU-based framework for modeling real-time 3D lung tumor conformal dosimetry with subject-specific lung tumor motion. , 2010, Physics in medicine and biology.

[40]  D. Makuc,et al.  Health, United States, 2010; with special feature on death and dying , 2011 .

[41]  Sasa Mutic,et al.  Technical note: DIRART--A software suite for deformable image registration and adaptive radiotherapy research. , 2011, Medical physics.