MRI-Related Geometric Distortions in Stereotactic Radiotherapy Treatment Planning: Evaluation and Dosimetric Impact

In view of their superior soft tissue contrast compared to computed tomography, magnetic resonance images are commonly involved in stereotactic radiosurgery/radiotherapy applications for target delineation purposes. It is known, however, that magnetic resonance images are geometrically distorted, thus deteriorating dose delivery accuracy. The present work focuses on the assessment of geometric distortion inherent in magnetic resonance images used in stereotactic radiosurgery/radiotherapy treatment planning and attempts to quantitively evaluate the consequent impact on dose delivery. The geometric distortions for 3 clinical magnetic resonance protocols (at both 1.5 and 3.0 T) used for stereotactic radiosurgery/radiotherapy treatment planning were evaluated using a recently proposed phantom and methodology. Areas of increased distortion were identified at the edges of the imaged volume which was comparable to a brain scan. Although mean absolute distortion did not exceed 0.5 mm on any spatial axis, maximum detected control point disposition reached 2 mm. In an effort to establish what could be considered as acceptable geometric uncertainty, highly conformal plans were utilized to irradiate targets of different diameters (5-50 mm). The targets were mispositioned by 0.5 up to 3 mm, and dose–volume histograms and plan quality indices clinically used for plan evaluation and acceptance were derived and used to investigate the effect of geometrical uncertainty (distortion) on dose delivery accuracy and plan quality. The latter was found to be strongly dependent on target size. For targets less than 20 mm in diameter, a spatial disposition of the order of 1 mm could significantly affect (>5%) plan acceptance/quality indices. For targets with diameter greater than 2 cm, the corresponding disposition was found greater than 1.5 mm. Overall results of this work suggest that efficacy of stereotactic radiosurgery/radiotherapy applications could be compromised in case of very small targets lying distant from the scanner’s isocenter (eg, the periphery of the brain).

[1]  P. Jursinic,et al.  Distortion of Magnetic Resonance Images Used in Gamma Knife Radiosurgery Treatment Planning: Implications for Acoustic Neuroma Outcomes , 2005, Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology.

[2]  Jean L. Peng,et al.  Comparison of radiation dose spillage from the Gamma Knife Perfexion with that from volumetric modulated arc radiosurgery during treatment of multiple brain metastases in a single fraction. , 2014, Journal of neurosurgery.

[3]  Maria A Schmidt,et al.  Radiotherapy planning using MRI , 2015, Physics in medicine and biology.

[4]  Juha I Peltonen,et al.  MRI quality assurance using the ACR phantom in a multi-unit imaging center , 2011, Acta oncologica.

[5]  Deming Wang,et al.  A novel phantom and method for comprehensive 3-dimensional measurement and correction of geometric distortion in magnetic resonance imaging. , 2004, Magnetic resonance imaging.

[6]  S. Reeder,et al.  Fat and water magnetic resonance imaging , 2010, Journal of magnetic resonance imaging : JMRI.

[7]  B Gino Fallone,et al.  A two-step scheme for distortion rectification of magnetic resonance images. , 2009, Medical physics.

[8]  A Ertl,et al.  Quality assurance for the Leksell gamma unit: considering magnetic resonance image-distortion and delineation failure in the targeting of the internal auditory canal. , 1999, Medical physics.

[9]  D A Jaffray,et al.  Development of a geometrically accurate imaging protocol at 3 Tesla MRI for stereotactic radiosurgery treatment planning , 2010, Physics in medicine and biology.

[10]  D. Jaffray,et al.  Harmonic analysis for the characterization and correction of geometric distortion in MRI. , 2014, Medical physics.

[11]  Ho-Ling Liu,et al.  Quality Assurance of Clinical MRI Scanners Using ACR MRI Phantom: Preliminary Results , 2004, Journal of Digital Imaging.

[12]  I. Paddick,et al.  A simple scoring ratio to index the conformity of radiosurgical treatment plans , 2001 .

[13]  A. Muacevic,et al.  Quality Assurance in Stereotactic Radiosurgery/Radiotherapy according to DIN 6875-1 , 2005, Stereotactic and Functional Neurosurgery.

[14]  M. Torrens,et al.  A simple and efficient methodology to improve geometric accuracy in gamma knife radiation surgery: implementation in multiple brain metastases. , 2014, International journal of radiation oncology, biology, physics.

[15]  Bernhard Heck,et al.  Accuracy and stability of positioning in radiosurgery: long-term results of the Gamma Knife system. , 2007, Medical physics.

[16]  Martin O Leach,et al.  A complete distortion correction for MR images: I. Gradient warp correction , 2005, Physics in medicine and biology.

[17]  D A Jaffray,et al.  Characterization of tissue magnetic susceptibility-induced distortions for MRIgRT. , 2012, Medical physics.

[18]  Keith Wachowicz,et al.  Investigation of a 3D system distortion correction method for MR images , 2010, Journal of applied clinical medical physics.

[19]  E. Fonoff,et al.  An image correction protocol to reduce distortion for 3-T stereotactic MRI. , 2014, Neurosurgery.

[20]  Manabu Tamura,et al.  RADIOSURGERY WITH THE WORLD'S FIRST FULLY ROBOTIZED LEKSELL GAMMA KNIFE PERFEXION IN CLINICAL USE: A 200‐PATIENT PROSPECTIVE, RANDOMIZED, CONTROLLED COMPARISON WITH THE GAMMA KNIFE 4C , 2009, Neurosurgery.

[21]  Peter Metcalfe,et al.  Continuous table acquisition MRI for radiotherapy treatment planning: distortion assessment with a new extended 3D volumetric phantom. , 2015, Medical physics.

[22]  Christian P Karger,et al.  Accuracy of device-specific 2D and 3D image distortion correction algorithms for magnetic resonance imaging of the head provided by a manufacturer , 2006, Physics in medicine and biology.

[23]  B Gino Fallone,et al.  Characterization, prediction, and correction of geometric distortion in 3 T MR images. , 2007, Medical physics.

[24]  M. Torrens,et al.  Assessment and characterization of the total geometric uncertainty in Gamma Knife radiosurgery using polymer gels. , 2013, Medical physics.

[25]  P. Jursinic,et al.  Effect of image uncertainty on the dosimetry of trigeminal neuralgia irradiation. , 2005, International journal of radiation oncology, biology, physics.

[26]  Niko Papanikolaou,et al.  A Systematic Analysis of 2 Monoisocentric Techniques for the Treatment of Multiple Brain Metastases , 2017, Technology in cancer research & treatment.

[27]  I. Paddick A simple scoring ratio to index the conformity of radiosurgical treatment plans. Technical note. , 2000, Journal of neurosurgery.

[28]  J. Palta,et al.  Comprehensive QA for radiation oncology: report of AAPM Radiation Therapy Committee Task Group 40. , 1994, Medical physics.

[29]  Norbert Schuff,et al.  Measurement of MRI scanner performance with the ADNI phantom. , 2009, Medical physics.

[30]  A Moutsatsos,et al.  Characterization of system-related geometric distortions in MR images employed in Gamma Knife radiosurgery applications , 2016, Physics in medicine and biology.

[31]  Yue Cao,et al.  Phantom-based characterization of distortion on a magnetic resonance imaging simulator for radiation oncology , 2016, Physics in medicine and biology.

[32]  F. Zanella,et al.  Analyzing 3-tesla magnetic resonance imaging units for implementation in radiosurgery. , 2005, Journal of neurosurgery.

[33]  J. Michael Fitzpatrick,et al.  A technique for accurate magnetic resonance imaging in the presence of field inhomogeneities , 1992, IEEE Trans. Medical Imaging.

[34]  Zbigniew Petrovich,et al.  An image fusion study of the geometric accuracy of magnetic resonance imaging with the Leksell stereotactic localization system1 , 2001, Journal of applied clinical medical physics.

[35]  Joshua Kim,et al.  Technical Note: Characterization and correction of gradient nonlinearity induced distortion on a 1.0 T open bore MR-SIM. , 2015, Medical physics.

[36]  Anders M. Dale,et al.  Reliability in multi-site structural MRI studies: Effects of gradient non-linearity correction on phantom and human data , 2006, NeuroImage.

[37]  Rabih Hammoud,et al.  Development and validation of a novel large field of view phantom and a software module for the quality assurance of geometric distortion in magnetic resonance imaging. , 2015, Magnetic resonance imaging.

[38]  Ken-Pin Hwang,et al.  Spatial Precision in Magnetic Resonance Imaging-Guided Radiation Therapy: The Role of Geometric Distortion. , 2016, International journal of radiation oncology, biology, physics.

[39]  R. Pellegrini,et al.  Feasibility of single-isocenter, multi-arc non-coplanar volumetric modulated arc therapy for multiple brain tumors using a linear accelerator with a 160-leaf multileaf collimator: a phantom study , 2014, Journal of radiation research.

[40]  D P Dearnaley,et al.  Radiotherapy planning of the pelvis using distortion corrected MR images: the removal of system distortions. , 2000, Physics in medicine and biology.

[41]  Alessandra Bolsi,et al.  Radiotherapy of small intracranial tumours with different advanced techniques using photon and proton beams: a treatment planning study. , 2003, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[42]  S P M Crijns,et al.  Towards inherently distortion-free MR images for image-guided radiotherapy on an MRI accelerator , 2012, Physics in medicine and biology.

[43]  S. Ryu,et al.  Evaluation of volumetric modulated arc therapy for cranial radiosurgery using multiple noncoplanar arcs. , 2011, Medical physics.