Dosimetric evaluation of synthetic CT for magnetic resonance-only based radiotherapy planning of lung cancer

BackgroundInterest in MR-only treatment planning for radiation therapy is growing rapidly with the emergence of integrated MRI/linear accelerator technology. The purpose of this study was to evaluate the feasibility of using synthetic CT images generated from conventional Dixon-based MRI scans for radiation treatment planning of lung cancer.MethodsEleven patients who underwent whole-body PET/MR imaging following a PET/CT exam were randomly selected from an ongoing prospective IRB-approved study. Attenuation maps derived from the Dixon MR Images and atlas-based method was used to create CT data (synCT). Treatment planning for radiation treatment of lung cancer was optimized on the synCT and subsequently copied to the registered CT (planCT) for dose calculation. Planning target volumes (PTVs) with three sizes and four different locations in the lung were planned for irradiation. The dose-volume metrics comparison and 3D gamma analysis were performed to assess agreement between the synCT and CT calculated dose distributions.ResultsMean differences between PTV doses on synCT and CT across all the plans were −0.1% ± 0.4%, 0.1% ± 0.5%, and 0.4% ± 0.5% for D95, D98 and D100, respectively. Difference in dose between the two datasets for organs at risk (OARs) had average differences of −0.14 ± 0.07 Gy, 0.0% ± 0.1%, and −0.1% ± 0.2% for maximum spinal cord, lung V20, and heart V40 respectively. In patient groups based on tumor size and location, no significant differences were observed in the PTV and OARs dose-volume metrics (p > 0.05), except for the maximum spinal-cord dose when the target volumes were located at the lung apex (p = 0.001). Gamma analysis revealed a pass rate of 99.3% ± 1.1% for 2%/2 mm (dose difference/distance to agreement) acceptance criteria in every plan.ConclusionsThe synCT generated from Dixon-based MRI allows for dose calculation of comparable accuracy to the standard CT for lung cancer treatment planning. The dosimetric agreement between synCT and CT calculated doses warrants further development of a MR-only workflow for radiotherapy of lung cancer.

[1]  Chuanyong Bai,et al.  A generalized model for the conversion from CT numbers to linear attenuation coefficients , 2002, 2002 IEEE Nuclear Science Symposium Conference Record.

[2]  H Shirato,et al.  High-speed magnetic resonance imaging for four-dimensional treatment planning of conformal radiotherapy of moving body tumors. , 2000, International journal of radiation oncology, biology, physics.

[3]  J Balter,et al.  Patient-induced susceptibility effect on geometric distortion of clinical brain MRI for radiation treatment planning on a 3T scanner , 2013, Physics in medicine and biology.

[4]  Indrin J Chetty,et al.  Magnetic Resonance-Based Automatic Air Segmentation for Generation of Synthetic Computed Tomography Scans in the Head Region. , 2015, International journal of radiation oncology, biology, physics.

[5]  Chronic Disease Division.  Cancer facts and figures , 2010 .

[6]  B G Fallone,et al.  A study on the magnetic resonance imaging (MRI)-based radiation treatment planning of intracranial lesions , 2008, Physics in medicine and biology.

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

[8]  R. Weichselbaum,et al.  Increasing radiation therapy dose is associated with improved survival in patients undergoing stereotactic body radiation therapy for stage I non-small-cell lung cancer. , 2015, International journal of radiation oncology, biology, physics.

[9]  Mary Feng,et al.  Quantitative characterizations of ultrashort echo (UTE) images for supporting air–bone separation in the head , 2015, Physics in medicine and biology.

[10]  Mitsuhiro Nakamura,et al.  Dosimetric evaluation of the impacts of different heterogeneity correction algorithms on target doses in stereotactic body radiation therapy for lung tumors , 2012, Journal of radiation research.

[11]  Y. Ohno,et al.  Metastases in mediastinal and hilar lymph nodes in patients with non-small cell lung cancer: quantitative and qualitative assessment with STIR turbo spin-echo MR imaging. , 2004, Radiology.

[12]  Tiina Seppälä,et al.  Commissioning of MRI‐only based treatment planning procedure for external beam radiotherapy of prostate , 2013, Magnetic resonance in medicine.

[13]  U. G. Dailey.  Cancer,Facts and Figures about. , 2022, Journal of the National Medical Association.

[14]  Eric S Paulson,et al.  Consensus opinion on MRI simulation for external beam radiation treatment planning. , 2016, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[15]  Indra J. Das,et al.  Correlation between target volume and electron transport effects affecting heterogeneity corrections in stereotactic body radiotherapy for lung cancer , 2014, Journal of radiation research.

[16]  Mary Feng,et al.  Assessing the Dosimetric Accuracy of Magnetic Resonance-Generated Synthetic CT Images for Focal Brain VMAT Radiation Therapy. , 2015, International journal of radiation oncology, biology, physics.

[17]  W. T. Dixon.  Simple proton spectroscopic imaging. , 1984, Radiology.

[18]  D. Low,et al.  A technique for the quantitative evaluation of dose distributions. , 1998, Medical physics.

[19]  G. Hermosillo,et al.  Whole-Body PET/MR Imaging: Quantitative Evaluation of a Novel Model-Based MR Attenuation Correction Method Including Bone , 2015, The Journal of Nuclear Medicine.

[20]  A. Ahnesjö.  Collapsed cone convolution of radiant energy for photon dose calculation in heterogeneous media. , 1989, Medical physics.

[21]  R. Günther,et al.  Automatic, three-segment, MR-based attenuation correction for whole-body PET/MR data , 2010, European Journal of Nuclear Medicine and Molecular Imaging.

[22]  Danny C. Kim,et al.  Free-Breathing Radial 3D Fat-Suppressed T1-Weighted Gradient Echo Sequence: A Viable Alternative for Contrast-Enhanced Liver Imaging in Patients Unable to Suspend Respiration , 2011, Investigative radiology.

[23]  Jan J W Lagendijk,et al.  MRI/linac integration. , 2008, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[24]  Fredrik Nordström,et al.  Technical Note: MRI only prostate radiotherapy planning using the statistical decomposition algorithm. , 2015, Medical physics.

[25]  Mary Feng,et al.  Investigation of a method for generating synthetic CT models from MRI scans of the head and neck for radiation therapy , 2013, Physics in medicine and biology.

[26]  Peter M Jakob,et al.  Ultrashort echo time imaging using pointwise encoding time reduction with radial acquisition (PETRA) , 2012, Magnetic resonance in medicine.

[27]  S. Matsumoto,et al.  Lung Cancer Assessment Using MR Imaging: An Update. , 2015, Magnetic resonance imaging clinics of North America.

[28]  J. Galvin,et al.  Dosimetric evaluation of heterogeneity corrections for RTOG 0236: stereotactic body radiotherapy of inoperable stage I-II non-small-cell lung cancer. , 2007, International journal of radiation oncology, biology, physics.

[29]  J Balter,et al.  Estimation of geometrically undistorted B(0) inhomogeneity maps. , 2014, Physics in medicine and biology.

[30]  Jeffrey A Fessler,et al.  A female pelvic bone shape model for air/bone separation in support of synthetic CT generation for radiation therapy , 2016, Physics in medicine and biology.

[31]  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.

[32]  I. Das,et al.  Computed tomography imaging parameters for inhomogeneity correction in radiation treatment planning , 2016, Journal of medical physics.

[33]  A. Brahme,et al.  Calculation and application of point spread functions for treatment planning with high energy photon beams. , 1987, Acta oncologica.

[34]  J. Galvin,et al.  Dosimetric verification using monte carlo calculations for tissue heterogeneity-corrected conformal treatment plans following RTOG 0813 dosimetric criteria for lung cancer stereotactic body radiotherapy. , 2012, International journal of radiation oncology, biology, physics.

[35]  Fang-Fang Yin,et al.  Four-dimensional magnetic resonance imaging (4D-MRI) using image-based respiratory surrogate: a feasibility study. , 2011, Medical physics.

[36]  Carri Glide-Hurst,et al.  Implementation of a novel algorithm for generating synthetic CT images from magnetic resonance imaging data sets for prostate cancer radiation therapy. , 2015, International journal of radiation oncology, biology, physics.

[37]  Tufve Nyholm,et al.  Treatment planning using MRI data: an analysis of the dose calculation accuracy for different treatment regions , 2010, Radiation oncology.

[38]  Carri Glide-Hurst,et al.  Dosimetric evaluation of synthetic CT relative to bulk density assignment-based magnetic resonance-only approaches for prostate radiotherapy , 2015, Radiation oncology.

[39]  Olivier Salvado,et al.  An atlas-based electron density mapping method for magnetic resonance imaging (MRI)-alone treatment planning and adaptive MRI-based prostate radiation therapy. , 2012, International journal of radiation oncology, biology, physics.