Influence of imaging source and panel position uncertainties on the accuracy of 2D∕3D image registration of cranial images.

PURPOSE To determine the effects of imager source and panel positioning uncertainties on the accuracy of dual intensity-based 2D∕3D image registration of cranial images. METHODS An open source 2D∕3D image registration algorithm has been developed for registration of two orthogonal x-rays to a 3D volumetric image. The initialization files of the algorithm allow for nine degrees of freedom system calibration including x, y, z positions of the source and panel, and three rotational degrees of freedom of the panel about each of the three translational axes. A baseline system calibration was established and a baseline 2D∕3D registration between two orthogonal x-rays and the volumetric image was determined. The calibration file was manipulated to insert errors into each of the nine calibration variables of both imager geometries. Rigid six degrees of freedom registrations were iterated for each panel or source positional error over a range of predetermined calibration errors to determine the resulting error in the registration versus the baseline registration due to the manipulated error of the panel or source calibration. RESULTS Panel and source translational errors orthogonal to the imager∕panel axis introduced the greatest errors in the registration accuracy (4.0 mm geometric error results in up to 2.7 mm registration error). Panel rotation about the imaging direction also resulted in errors of the registration (2.0° geometric error results in up to 1.7° registration error). Differences in magnification and panel tilt and roll, i.e., source and∕or panel translation along the imaging direction and panel rotations about the orthogonal axes had minimal effects on the registration accuracy (below 0.3 mm and 0.2° registration error). CONCLUSIONS While five of the nine imaging system variables were found to have a considerable effect on 2D∕3D registration accuracy of cranial images, the other four variables showed minimal effects. Vendors typically provide simplified calibration procedures which aim to remove encountered geometric uncertainties by accounting for two panel translations. This study shows that at least the five relevant positional variables should be separately calibrated, if accurate alignment is required for 2D∕3D registration.

[1]  David A Jaffray,et al.  The stability of mechanical calibration for a kV cone beam computed tomography system integrated with linear accelerator. , 2005, Medical physics.

[2]  Xinhua Li,et al.  A generic geometric calibration method for tomographic imaging systems with flat-panel detectors--a detailed implementation guide. , 2010, Medical physics.

[3]  David A Jaffray,et al.  Accurate technique for complete geometric calibration of cone-beam computed tomography systems. , 2005, Medical physics.

[4]  Geoffrey G. Zhang,et al.  Comparing dose in the build‐up region between compensator‐ and MLC‐based IMRT , 2012, Journal of applied clinical medical physics.

[5]  Daniel A Low,et al.  Linac mechanic QA using a cylindrical phantom , 2008, Physics in medicine and biology.

[6]  John A. Nelder,et al.  A Simplex Method for Function Minimization , 1965, Comput. J..

[7]  Gabor Fichtinger,et al.  Monitoring tumor motion by real time 2D/3D registration during radiotherapy , 2012, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[8]  J R Sykes,et al.  Investigation of uncertainties in image registration of cone beam CT to CT on an image-guided radiotherapy system , 2009, Physics in medicine and biology.

[9]  David A. Jaffray,et al.  Quality assurance for the geometric accuracy of cone-beam CT guidance in radiation therapy. , 2008, International journal of radiation oncology, biology, physics.

[10]  Ehsan Samei,et al.  Kilovoltage cone-beam CT: comparative dose and image quality evaluations in partial and full-angle scan protocols. , 2010, Medical physics.

[11]  Stine Korreman,et al.  The European Society of Therapeutic Radiology and Oncology-European Institute of Radiotherapy (ESTRO-EIR) report on 3D CT-based in-room image guidance systems: a practical and technical review and guide. , 2010, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[12]  Jean Pouliot,et al.  Physical performance and image optimization of megavoltage cone-beam CT. , 2009, Medical physics.

[13]  Imad Ali,et al.  Evaluation of the effects of sagging shifts on isocenter accuracy and image quality of cone‐beam CT from kV on‐board imagers * , 2009, Journal of applied clinical medical physics.

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

[15]  Douglas R Wyman,et al.  Analysis of mechanical sources of patient alignment errors in radiation therapy. , 2002, Medical physics.

[16]  Bostjan Likar,et al.  A review of 3D/2D registration methods for image-guided interventions , 2012, Medical Image Anal..

[17]  Lei Xing,et al.  Development of a QA phantom and automated analysis tool for geometric quality assurance of on-board MV and kV x-ray imaging systems. , 2008, Medical physics.

[18]  M. Viergever,et al.  Robust initialization of 2D-3D image registration using the projection-slice theorem and phase correlation. , 2010, Medical physics.

[19]  G C Sharp,et al.  Auto-masked 2D/3D image registration and its validation with clinical cone-beam computed tomography. , 2012, Physics in medicine and biology.

[20]  P Price,et al.  Developments in and experience of kilovoltage X-ray cone beam image-guided radiotherapy. , 2006, The British journal of radiology.

[21]  G J Budgell,et al.  Use of an amorphous silicon EPID for measuring MLC calibration at varying gantry angle. , 2008, Physics in medicine and biology.

[22]  Bernhard Erich Hermann Claus,et al.  Geometry calibration phantom design for 3D imaging , 2006, SPIE Medical Imaging.

[23]  Uwe Stilla,et al.  Geometry calibration for x-ray equipment in radiation treatment devices and estimation of remaining patient alignment errors , 2008, SPIE Medical Imaging.

[24]  Minho Kim,et al.  Evaluation of similarity measures for use in the intensity-based rigid 2D-3D registration for patient positioning in radiotherapy. , 2009, Medical physics.

[25]  D. Kwong,et al.  Evaluation of radiation dose and image quality for the Varian cone beam computed tomography system. , 2011, International journal of radiation oncology, biology, physics.

[26]  B. Fei,et al.  Automatic 3D-to-2D registration for CT and dual-energy digital radiography for calcification detection. , 2007, Medical physics.

[27]  Moyed Miften,et al.  Commissioning and clinical implementation of a mega-voltage cone beam CT system for treatment localization. , 2007, Medical physics.

[28]  Evangelos Matsinos,et al.  The geometric calibration of cone-beam imaging and delivery systems in radiation therapy , 2006 .

[29]  J. Kettenbach,et al.  Rigid 2D/3D slice-to-volume registration and its application on fluoroscopic CT images. , 2006, Medical physics.

[30]  Brian Winey,et al.  Immobilization precision of a modified GTC frame , 2012, Journal of applied clinical medical physics.

[31]  J H Siewerdsen,et al.  Geometric calibration of a mobile C-arm for intraoperative cone-beam CT. , 2008, Medical physics.