Monte Carlo study of the effects of system geometry and antiscatter grids on cone-beam CT scatter distributions.

PURPOSE The proliferation of cone-beam CT (CBCT) has created interest in performance optimization, with x-ray scatter identified among the main limitations to image quality. CBCT often contends with elevated scatter, but the wide variety of imaging geometry in different CBCT configurations suggests that not all configurations are affected to the same extent. Graphics processing unit (GPU) accelerated Monte Carlo (MC) simulations are employed over a range of imaging geometries to elucidate the factors governing scatter characteristics, efficacy of antiscatter grids, guide system design, and augment development of scatter correction. METHODS A MC x-ray simulator implemented on GPU was accelerated by inclusion of variance reduction techniques (interaction splitting, forced scattering, and forced detection) and extended to include x-ray spectra and analytical models of antiscatter grids and flat-panel detectors. The simulator was applied to small animal (SA), musculoskeletal (MSK) extremity, otolaryngology (Head), breast, interventional C-arm, and on-board (kilovoltage) linear accelerator (Linac) imaging, with an axis-to-detector distance (ADD) of 5, 12, 22, 32, 60, and 50 cm, respectively. Each configuration was modeled with and without an antiscatter grid and with (i) an elliptical cylinder varying 70-280 mm in major axis; and (ii) digital murine and anthropomorphic models. The effects of scatter were evaluated in terms of the angular distribution of scatter incident upon the detector, scatter-to-primary ratio (SPR), artifact magnitude, contrast, contrast-to-noise ratio (CNR), and visual assessment. RESULTS Variance reduction yielded improvements in MC simulation efficiency ranging from ∼17-fold (for SA CBCT) to ∼35-fold (for Head and C-arm), with the most significant acceleration due to interaction splitting (∼6 to ∼10-fold increase in efficiency). The benefit of a more extended geometry was evident by virtue of a larger air gap-e.g., for a 16 cm diameter object, the SPR reduced from 1.5 for ADD = 12 cm (MSK geometry) to 1.1 for ADD = 22 cm (Head) and to 0.5 for ADD = 60 cm (C-arm). Grid efficiency was higher for configurations with shorter air gap due to a broader angular distribution of scattered photons-e.g., scatter rejection factor ∼0.8 for MSK geometry versus ∼0.65 for C-arm. Grids reduced cupping for all configurations but had limited improvement on scatter-induced streaks and resulted in a loss of CNR for the SA, Breast, and C-arm. Relative contribution of forward-directed scatter increased with a grid (e.g., Rayleigh scatter fraction increasing from ∼0.15 without a grid to ∼0.25 with a grid for the MSK configuration), resulting in scatter distributions with greater spatial variation (the form of which depended on grid orientation). CONCLUSIONS A fast MC simulator combining GPU acceleration with variance reduction provided a systematic examination of a range of CBCT configurations in relation to scatter, highlighting the magnitude and spatial uniformity of individual scatter components, illustrating tradeoffs in CNR and artifacts and identifying the system geometries for which grids are more beneficial (e.g., MSK) from those in which an extended geometry is the better defense (e.g., C-arm head imaging). Compact geometries with an antiscatter grid challenge assumptions of slowly varying scatter distributions due to increased contribution of Rayleigh scatter.

[1]  J A Seibert,et al.  X-ray scatter removal by deconvolution. , 1988, Medical physics.

[2]  J H Siewerdsen,et al.  Spektr: a computational tool for x-ray spectral analysis and imaging system optimization. , 2004, Medical physics.

[3]  S. Richard,et al.  A simple, direct method for x-ray scatter estimation and correction in digital radiography and cone-beam CT. , 2005, Medical physics.

[4]  P M Joseph,et al.  The effects of scatter in x-ray computed tomography. , 1982, Medical physics.

[5]  Matthias Bertram,et al.  Potential of software-based scatter corrections in cone-beam volume CT , 2005, SPIE Medical Imaging.

[6]  Ruola Ning,et al.  X-ray scatter correction algorithm for cone beam CT imaging. , 2004, Medical physics.

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

[8]  Dong Yang,et al.  Dose and scatter characteristics of a novel cone beam CT system for musculoskeletal extremities , 2012, Medical Imaging.

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

[10]  TU-D-I-611-07: A Scanning Sampled Measurement (SSM) Technique for Scatter Measurement and Correction in Cone Beam Breast CT , 2005 .

[11]  J A Rowlands,et al.  Absorption and noise in cesium iodide x-ray image intensifiers. , 1983, Medical physics.

[12]  Selin Carkaci,et al.  Dedicated cone-beam breast CT: feasibility study with surgical mastectomy specimens. , 2007, AJR. American journal of roentgenology.

[13]  R. Lebowitz,et al.  Flat Panel Cone Beam Computed Tomography of the Sinuses , 2008 .

[14]  G Kleinszig,et al.  Antiscatter grids in mobile C-arm cone-beam CT: effect on image quality and dose. , 2011, Medical physics.

[15]  D. Jaffray,et al.  The influence of bowtie filtration on cone-beam CT image quality , 2008 .

[16]  Freek J. Beekman,et al.  Accelerated simulation of cone beam X-ray scatter projections , 2004, IEEE Transactions on Medical Imaging.

[17]  D M Cunha,et al.  Evaluation of scatter-to-primary ratio, grid performance and normalized average glandular dose in mammography by Monte Carlo simulation including interference and energy broadening effects , 2010, Physics in medicine and biology.

[18]  Lei Zhu,et al.  Scatter correction for cone-beam CT in radiation therapy. , 2009 .

[19]  J. Boone,et al.  Evaluation of x-ray scatter properties in a dedicated cone-beam breast CT scanner. , 2005, Medical physics.

[20]  J. Sempau,et al.  PENELOPE-2006: A Code System for Monte Carlo Simulation of Electron and Photon Transport , 2009 .

[21]  A Taibi,et al.  Updating of form factor tabulations for coherent scattering of photons in tissues. , 2002, Physics in medicine and biology.

[22]  Aldo Badano,et al.  SU-E-I-68: Fast and Accurate Estimation of Organ Doses in Medical Imaging Using a GPU-Accelerated Monte Carlo Simulation Code , 2011 .

[23]  J F Williamson,et al.  Monte Carlo evaluation of kerma at a point for photon transport problems. , 1987, Medical physics.

[24]  John M. Boone,et al.  An object-specific and dose-sparing scatter correction approach for a dedicated cone-beam breast CT system using a parallel-hole collimator , 2012, Medical Imaging.

[25]  Aldo Badano,et al.  Accelerating Monte Carlo simulations of photon transport in a voxelized geometry using a massively parallel graphics processing unit. , 2009, Medical physics.

[26]  B. Wilson,et al.  Volume CT with a flat-panel detector on a mobile, isocentric C-arm: pre-clinical investigation in guidance of minimally invasive surgery. , 2005, Medical physics.

[27]  M. Endo,et al.  Effect of scattered radiation on image noise in cone beam CT. , 2001, Medical physics.

[28]  Frank Verhaegen,et al.  Characterization of scattered radiation in kV CBCT images using Monte Carlo simulations. , 2006, Medical physics.

[29]  V.R. Bom,et al.  Monte Carlo modeling of coherent scattering: influence of interference , 1995, 1995 IEEE Nuclear Science Symposium and Medical Imaging Conference Record.

[30]  Freek J. Beekman,et al.  Efficient Monte Carlo based scatter artifact reduction in cone-beam micro-CT , 2006, IEEE Transactions on Medical Imaging.

[31]  S. Koskinen,et al.  CT arthrography of the wrist using a novel, mobile, dedicated extremity cone-beam CT (CBCT) , 2013, Skeletal Radiology.

[32]  D. Jaffray,et al.  The influence of bowtie filtration on cone-beam CT image quality. , 2007, Medical physics.

[33]  Lei Zhu,et al.  X-ray scatter correction for cone-beam CT using moving blocker array , 2005, SPIE Medical Imaging.

[34]  F J Beekman,et al.  Experimental validation of a rapid Monte Carlo based micro-CT simulator. , 2004, Physics in medicine and biology.

[35]  R. Leahy,et al.  Digimouse: a 3D whole body mouse atlas from CT and cryosection data , 2007, Physics in medicine and biology.

[36]  I. Kyprianou,et al.  Computational high-resolution heart phantoms for medical imaging and dosimetry simulations , 2011, Physics in medicine and biology.

[37]  J H Siewerdsen,et al.  Generalized DQE analysis of radiographic and dual-energy imaging using flat-panel detectors. , 2005, Medical physics.

[38]  W. Kalender,et al.  Combining deterministic and Monte Carlo calculations for fast estimation of scatter intensities in CT , 2006, Physics in medicine and biology.

[39]  Gary H. Glover,et al.  Compton scatter effects in CT reconstructions , 1982 .

[40]  J. Boone,et al.  Evaluation of x-ray scatter properties in a dedicated cone-beam breast CT scanner. , 2005, Medical physics.

[41]  M. H. Kalos,et al.  On the Estimation of Flux at a Point by Monte Carlo , 1963 .

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

[43]  Lei Zhu,et al.  Scatter Correction Method for X-Ray CT Using Primary Modulation: Theory and Preliminary Results , 2006, IEEE Transactions on Medical Imaging.

[44]  J. Siewerdsen,et al.  Technical assessment of a cone-beam CT scanner for otolaryngology imaging: image quality, dose, and technique protocols. , 2012, Medical physics.

[45]  D. Yang,et al.  A dedicated cone-beam CT system for musculoskeletal extremities imaging: design, optimization, and initial performance characterization. , 2011, Medical physics.

[46]  J. Star-Lack,et al.  Improved scatter correction using adaptive scatter kernel superposition , 2010, Physics in medicine and biology.

[47]  Jeffrey F Williamson,et al.  Monte Carlo evaluation of scatter mitigation strategies in cone-beam CT. , 2010, Medical physics.

[48]  Iwan Kawrakow,et al.  Variance reduction techniques for fast Monte Carlo CBCT scatter correction calculations , 2010, Physics in medicine and biology.

[49]  Alexander Sasov Ultrafast micro-CT for in vivo small animal imaging and industrial applications , 2004, SPIE Optics + Photonics.

[50]  H H Barrett,et al.  Statistical limitations in transaxial tomography. , 1976, Computers in biology and medicine.

[51]  John M Boone,et al.  Development of a patient-specific two-compartment anthropomorphic breast phantom. , 2012, Physics in medicine and biology.

[52]  D R Dance,et al.  X-ray transmission formula for antiscatter grids. , 1983, Physics in medicine and biology.

[53]  W. Kalender,et al.  Efficiency of antiscatter grids for flat-detector CT , 2007, Physics in medicine and biology.

[54]  W. Kalender,et al.  Flat-detector computed tomography (FD-CT) , 2007, European Radiology.

[55]  Alastair J. Walker,et al.  An Efficient Method for Generating Discrete Random Variables with General Distributions , 1977, TOMS.

[56]  R. Kruger,et al.  Scatter estimation for a digital radiographic system using convolution filtering. , 1987, Medical physics.

[57]  Alexander Sasov Ultra-fast microCT for industrial applications and in-vivo small animal imaging , 2003 .

[58]  P. C. Johns,et al.  Scattered radiation in fan beam imaging systems. , 1982, Medical physics.

[59]  D. R. White,et al.  The composition of body tissues. , 1986, The British journal of radiology.

[60]  D. Jaffray,et al.  Optimization of x-ray imaging geometry (with specific application to flat-panel cone-beam computed tomography). , 2000, Medical physics.

[61]  Jonathan S. Maltz,et al.  Algorithm for X-ray Scatter, Beam-Hardening, and Beam Profile Correction in Diagnostic (Kilovoltage) and Treatment (Megavoltage) Cone Beam CT , 2008, IEEE Transactions on Medical Imaging.

[62]  SU-F-BRCD-04: Efficient Scatter Distribution Estimation and Correction in CBCT Using Concurrent Monte Carlo Fitting. , 2012, Medical physics.

[63]  S. Webb,et al.  Rayleigh scatter in kilovoltage x-ray imaging: is the independent atom approximation good enough? , 2009, Physics in medicine and biology.

[64]  Cynthia H McCollough,et al.  Dose and image quality evaluation of a dedicated cone-beam CT system for high-contrast neurologic applications. , 2010, AJR. American journal of roentgenology.

[65]  Geoffrey Hugo,et al.  Image-guided radiotherapy via daily online cone-beam CT substantially reduces margin requirements for stereotactic lung radiotherapy. , 2007, International journal of radiation oncology, biology, physics.

[66]  K. Hoffmann,et al.  Generalizing the MTF and DQE to include x-ray scatter and focal spot unsharpness: application to a new microangiographic system. , 2005, Medical physics.

[67]  Frank Verhaegen,et al.  Scatter correction for kilovoltage cone-beam computed tomography (CBCT) images using Monte Carlo simulations , 2006, SPIE Medical Imaging.

[68]  C.W.E. van Eijk,et al.  Monte Carlo modeling of coherent scattering: influence of interference , 1995 .

[69]  J. Boone,et al.  Dedicated breast CT: radiation dose and image quality evaluation. , 2001, Radiology.

[70]  D. Jaffray,et al.  Cone-beam computed tomography with a flat-panel imager: magnitude and effects of x-ray scatter. , 2001, Medical physics.

[71]  D. Jaffray,et al.  The influence of antiscatter grids on soft-tissue detectability in cone-beam computed tomography with flat-panel detectors. , 2004, Medical physics.

[72]  M. Desco,et al.  Assessment of a New High-Performance Small-Animal X-Ray Tomograph , 2008, IEEE Transactions on Nuclear Science.

[73]  M J Yaffe,et al.  Coherent scatter in diagnostic radiology. , 1983, Medical physics.

[74]  U Neitzel,et al.  Grids or air gaps for scatter reduction in digital radiography: a model calculation. , 1992, Medical physics.

[75]  J. Boone,et al.  An accurate method for computer-generating tungsten anode x-ray spectra from 30 to 140 kV. , 1997, Medical physics.

[76]  Rebecca Fahrig,et al.  Dose and image quality for a cone-beam C-arm CT system. , 2006, Medical physics.

[77]  J. Boone,et al.  Evaluation of the spatial resolution characteristics of a cone-beam breast CT scanner. , 2006, Medical physics.

[78]  S Webb,et al.  An efficient Monte Carlo-based algorithm for scatter correction in keV cone-beam CT , 2009, Physics in medicine and biology.