MRI-only treatment planning: benefits and challenges

Over the past decade, the application of magnetic resonance imaging (MRI) has increased, and there is growing evidence to suggest that improvements in the accuracy of target delineation in MRI-guided radiation therapy may improve clinical outcomes in a variety of cancer types. However, some considerations should be recognized including patient motion during image acquisition and geometric accuracy of images. Moreover, MR-compatible immobilization devices need to be used when acquiring images in the treatment position while minimizing patient motion during the scan time. Finally, synthetic CT images (i.e. electron density maps) and digitally reconstructed radiograph images should be generated from MRI images for dose calculation and image guidance prior to treatment. A short review of the concepts and techniques that have been developed for implementation of MRI-only workflows in radiation therapy is provided in this document.

[1]  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.

[2]  John M Pauly,et al.  Slice encoding for metal artifact correction with noise reduction , 2011, Magnetic resonance in medicine.

[3]  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.

[4]  D. Johnston,et al.  Optimization of prostate biopsy strategy using computer based analysis. , 1997, The Journal of urology.

[5]  Kenneth Ulin,et al.  Results of a multi-institutional benchmark test for cranial CT/MR image registration. , 2010, International journal of radiation oncology, biology, physics.

[6]  M Thelen,et al.  MRI-assisted radiation therapy planning of brain tumors--clinical experiences in 17 patients. , 1991, Magnetic resonance imaging.

[7]  Erik Kouwenhoven,et al.  MRI- versus CT-based volume delineation of lumpectomy cavity in supine position in breast-conserving therapy: an exploratory study. , 2012, International journal of radiation oncology, biology, physics.

[8]  Marcel van Herk,et al.  Errors and margins in radiotherapy. , 2004, Seminars in radiation oncology.

[9]  Carri Glide-Hurst,et al.  High-quality t2-weighted 4-dimensional magnetic resonance imaging for radiation therapy applications. , 2015, International journal of radiation oncology, biology, physics.

[10]  Adam Johansson,et al.  CT substitute derived from MRI sequences with ultrashort echo time. , 2011, Medical physics.

[11]  Rabih Hammoud,et al.  Characterization of 3D geometric distortion of magnetic resonance imaging scanners commissioned for radiation therapy planning. , 2016, Magnetic resonance imaging.

[12]  John M Pauly,et al.  SEMAC: Slice encoding for metal artifact correction in MRI , 2009, Magnetic resonance in medicine.

[13]  Wei Luo,et al.  Magnetic resonance-based treatment planning for prostate intensity-modulated radiotherapy: creation of digitally reconstructed radiographs. , 2007, International journal of radiation oncology, biology, physics.

[14]  Xiao Han,et al.  MR‐based synthetic CT generation using a deep convolutional neural network method , 2017, Medical physics.

[15]  S. Vandenberghe,et al.  MRI-Based Attenuation Correction for PET/MRI Using Ultrashort Echo Time Sequences , 2010, Journal of Nuclear Medicine.

[16]  Matthias Fenchel,et al.  Dosimetric evaluation of synthetic CT for magnetic resonance-only based radiotherapy planning of lung cancer , 2017, Radiation oncology.

[17]  Jeffrey A Fessler,et al.  Female pelvic synthetic CT generation based on joint intensity and shape analysis. , 2017, Physics in medicine and biology.

[18]  Jurgen Fripp,et al.  MRI-alone radiation therapy planning for prostate cancer: Automatic fiducial marker detection. , 2016, Medical physics.

[19]  Ansgar Malich,et al.  Definition of the CTV Prostate in CT and MRI by Using CT–MRI Image Fusion in IMRT Planning for Prostate Cancer , 2011, Strahlentherapie und Onkologie.

[20]  Masoom A Haider,et al.  Dynamic contrast-enhanced magnetic resonance imaging for localization of recurrent prostate cancer after external beam radiotherapy. , 2008, International journal of radiation oncology, biology, physics.

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

[22]  Issam El Naqa,et al.  Pelvic normal tissue contouring guidelines for radiation therapy: a Radiation Therapy Oncology Group consensus panel atlas. , 2012, International journal of radiation oncology, biology, physics.

[23]  David M. Doddrell,et al.  Geometric Distortion in Structural Magnetic Resonance Imaging , 2005 .

[24]  Patrick W McLaughlin,et al.  Vessel-sparing prostate radiotherapy: dose limitation to critical erectile vascular structures (internal pudendal artery and corpus cavernosum) defined by MRI. , 2005, International journal of radiation oncology, biology, physics.

[25]  A. D'Amico,et al.  DEFINITIVE EXTERNAL-BEAM IRRADIATION IN STAGE T1 AND T2 PROSTATE CANCER , 2013 .

[26]  G. Liney,et al.  Repeatability of functional MRI for conformal avoidance radiotherapy planning , 2006, Journal of magnetic resonance imaging : JMRI.

[27]  Soumya Ghose,et al.  Regression and statistical shape model based substitute CT generation for MRI alone external beam radiation therapy from standard clinical MRI sequences , 2017, Physics in medicine and biology.

[28]  Olivier Salvado,et al.  A magnetic resonance imaging‐based workflow for planning radiation therapy for prostate cancer , 2011, The Medical journal of Australia.

[29]  Yue Cao,et al.  Clinical applications for diffusion magnetic resonance imaging in radiotherapy. , 2014, Seminars in radiation oncology.

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

[31]  Weitian Chen,et al.  Imaging near metal with a MAVRIC‐SEMAC hybrid , 2011, Magnetic resonance in medicine.

[32]  Steve Webb,et al.  Radiotherapy treatment planning of prostate cancer using magnetic resonance imaging alone. , 2003, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[33]  Jurgen Fripp,et al.  Robust inverse-consistent affine CT-MR registration in MRI-assisted and MRI-alone prostate radiation therapy , 2015, Medical Image Anal..

[34]  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.

[35]  Michael Bremer,et al.  The delineation of target volumes for radiotherapy of lung cancer patients. , 2009, Radiotherapy and Oncology.

[36]  Carsten Brink,et al.  Magnetic resonance only workflow and validation of dose calculations for radiotherapy of prostate cancer , 2017, Acta oncologica.

[37]  C. Hess,et al.  The Impact of Gross Tumor Volume (GTV) and Clinical Target Volume (CTV) Definition on the Total Accuracy in Radiotherapy , 2003, Strahlentherapie und Onkologie.

[38]  Ninon Burgos,et al.  Attenuation Correction Synthesis for Hybrid PET-MR Scanners , 2013, MICCAI.

[39]  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.

[40]  Jason A Dowling,et al.  Investigating the generalisation of an atlas-based synthetic-CT algorithm to another centre and MR scanner for prostate MR-only radiotherapy. , 2017, Physics in medicine and biology.

[41]  Christian Kirisits,et al.  Recommendations from Gynaecological (GYN) GEC-ESTRO Working Group: considerations and pitfalls in commissioning and applicator reconstruction in 3D image-based treatment planning of cervix cancer brachytherapy. , 2010, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[42]  M. Bernstein,et al.  MRI in radiation oncology: Underserved needs , 2016, Magnetic resonance in medicine.

[43]  Thomas Krauss,et al.  Conformal radiotherapy planning of cervix carcinoma: differences in the delineation of the clinical target volume. A comparison between gynaecologic and radiation oncologists. , 2003, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[44]  R. Steenbakkers,et al.  Reduction of dose delivered to the rectum and bulb of the penis using MRI delineation for radiotherapy of the prostate. , 2003, International journal of radiation oncology, biology, physics.

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

[46]  Melanie Traughber,et al.  Evaluating organ delineation, dose calculation and daily localization in an open-MRI simulation workflow for prostate cancer patients , 2015, Radiation Oncology.

[47]  D. Louis Collins,et al.  Gradient distortions in MRI: Characterizing and correcting for their effects on SIENA-generated measures of brain volume change , 2010, NeuroImage.

[48]  C. Njeh,et al.  Tumor delineation: The weakest link in the search for accuracy in radiotherapy , 2008, Journal of medical physics.

[49]  Kim Butts,et al.  Reduction of blurring in view angle tilting MRI , 2005, Magnetic resonance in medicine.

[50]  M van Herk,et al.  Definition of the prostate in CT and MRI: a multi-observer study. , 1999, International journal of radiation oncology, biology, physics.

[51]  Jidi Sun,et al.  MRI simulation: end-to-end testing for prostate radiation therapy using geometric pelvic MRI phantoms. , 2015, Physics in medicine and biology.

[52]  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.

[53]  J. Schenck The role of magnetic susceptibility in magnetic resonance imaging: MRI magnetic compatibility of the first and second kinds. , 1996, Medical physics.

[54]  Lei Xing,et al.  Robust Estimation of Electron Density From Anatomic Magnetic Resonance Imaging of the Brain Using a Unifying Multi-Atlas Approach. , 2017, International journal of radiation oncology, biology, physics.

[55]  B. Erickson,et al.  Comprehensive MRI simulation methodology using a dedicated MRI scanner in radiation oncology for external beam radiation treatment planning. , 2014, Medical physics.

[56]  Harini Veeraraghavan,et al.  Multiatlas approach with local registration goodness weighting for MRI‐based electron density mapping of head and neck anatomy† , 2017, Medical physics.

[57]  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.

[58]  B. Zackrisson,et al.  Dedicated magnetic resonance imaging in the radiotherapy clinic. , 2009, International journal of radiation oncology, biology, physics.

[59]  Bernhard Schölkopf,et al.  MRI-Based Attenuation Correction for PET/MRI: A Novel Approach Combining Pattern Recognition and Atlas Registration , 2008, Journal of Nuclear Medicine.

[60]  B. Gino Fallone,et al.  3T MR-based treatment planning for radiotherapy of brain lesions , 2006 .

[61]  J. Dimopoulos,et al.  Recommendations from gynaecological (GYN) GEC ESTRO working group (II): concepts and terms in 3D image-based treatment planning in cervix cancer brachytherapy-3D dose volume parameters and aspects of 3D image-based anatomy, radiation physics, radiobiology. , 2006, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[62]  H. Kooy,et al.  Automatic three-dimensional correlation of CT-CT, CT-MRI, and CT-SPECT using chamfer matching. , 1994, Medical physics.

[63]  I. Repa,et al.  Integrating functional MRI information into conventional 3D radiotherapy planning of CNS tumors. Is it worth it? , 2011, Journal of Neuro-Oncology.

[64]  Timothy D Johnson,et al.  Functional diffusion map as an early imaging biomarker for high-grade glioma: correlation with conventional radiologic response and overall survival. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[65]  C. Kirisits,et al.  Magnetic resonance image guided brachytherapy. , 2014, Seminars in radiation oncology.

[66]  Carri Glide-Hurst,et al.  Image Guided Radiation Therapy Using Synthetic Computed Tomography Images in Brain Cancer. , 2016, International journal of radiation oncology, biology, physics.

[67]  Frank Zijlstra,et al.  Evaluation of an automatic MR-based gold fiducial marker localisation method for MR-only prostate radiotherapy , 2017, Physics in medicine and biology.

[68]  Aliaksandr Karotki,et al.  Comparison of bulk electron density and voxel‐based electron density treatment planning , 2011, Journal of applied clinical medical physics.

[69]  Maximilien Vermandel,et al.  MRI alone simulation for conformal radiation therapy of prostate cancer: technical aspects , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[70]  T. Nyholm,et al.  A review of substitute CT generation for MRI-only radiation therapy , 2017, Radiation oncology.

[71]  John M Pauly,et al.  Metal-induced artifacts in MRI. , 2011, AJR. American journal of roentgenology.

[72]  R. S. Hinks,et al.  A multispectral three‐dimensional acquisition technique for imaging near metal implants , 2009, Magnetic resonance in medicine.

[73]  Tetsuya Yuasa,et al.  Improved volumetric measurement of brain structure with a distortion correction procedure using an ADNI phantom. , 2013, Medical physics.

[74]  Huawei Zhao,et al.  Use of spherical harmonic deconvolution methods to compensate for nonlinear gradient effects on MRI images , 2004, Magnetic resonance in medicine.

[75]  J. Edmund,et al.  A criterion for the reliable use of MRI-only radiotherapy , 2014, Radiation oncology.

[76]  Corine van Vliet-Vroegindeweij,et al.  Multiinstitutional study on target volume delineation variation in breast radiotherapy in the presence of guidelines. , 2010, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[77]  Ciprian Catana,et al.  Toward Implementing an MRI-Based PET Attenuation-Correction Method for Neurologic Studies on the MR-PET Brain Prototype , 2010, The Journal of Nuclear Medicine.

[78]  Fang-Fang Yin,et al.  Investigation of sagittal image acquisition for 4D-MRI with body area as respiratory surrogate. , 2014, Medical physics.

[79]  Alan Pollack,et al.  MRI-based treatment planning for radiotherapy: dosimetric verification for prostate IMRT. , 2004, International journal of radiation oncology, biology, physics.

[80]  Margie Hunt,et al.  Dosimetric and workflow evaluation of first commercial synthetic CT software for clinical use in pelvis , 2017, Physics in medicine and biology.

[81]  Leonard Wee,et al.  Intensity-based dual model method for generation of synthetic CT images from standard T2-weighted MR images - Generalized technique for four different MR scanners. , 2017, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[82]  I. Trop,et al.  Localization of the surgical bed using supine magnetic resonance and computed tomography scan fusion for planification of breast interstitial brachytherapy. , 2011, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[83]  S. Spencer,et al.  Conventional four-field pelvic radiotherapy technique without CT treatment planning in cancer of the cervix: potential geographic miss. , 1994, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[84]  Ersin Bayram,et al.  Optimization of a novel large field of view distortion phantom for MR‐only treatment planning , 2017, Journal of applied clinical medical physics.

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

[86]  J. Jonsson,et al.  Counterpoint: Opportunities and challenges of a magnetic resonance imaging-only radiotherapy work flow. , 2014, Seminars in radiation oncology.

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

[88]  E Bellon,et al.  The contribution of magnetic resonance imaging to the three-dimensional treatment planning of localized prostate cancer. , 1999, International journal of radiation oncology, biology, physics.

[89]  S. Spencer,et al.  Conventional four-field pelvic radiotherapy technique without computed tomography-treatment planning in cancer of the cervix: potential geographic miss and its impact on pelvic control. , 1995, International journal of radiation oncology, biology, physics.

[90]  Indrin J Chetty,et al.  Four dimensional magnetic resonance imaging optimization and implementation for magnetic resonance imaging simulation. , 2015, Practical radiation oncology.

[91]  M. Nittka,et al.  Metal artefact reduction in MRI at both 1.5 and 3.0 T using slice encoding for metal artefact correction and view angle tilting. , 2015, The British journal of radiology.

[92]  C R Ramsey,et al.  Magnetic resonance imaging based digitally reconstructed radiographs, virtual simulation, and three-dimensional treatment planning for brain neoplasms. , 1998, Medical physics.

[93]  Masoom A. Haider,et al.  Diffusion-weighted MRI in cervical cancer , 2008, European Radiology.

[94]  Stephan E Maier,et al.  Early detection of response to radiation therapy in patients with brain malignancies using conventional and high b-value diffusion-weighted magnetic resonance imaging. , 2003, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[95]  P. Choyke,et al.  Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. , 2009, Neoplasia.

[96]  Shiao Y. Woo,et al.  Evaluation of peritumoral edema in the delineation of radiotherapy clinical target volumes for glioblastoma. , 2007, International journal of radiation oncology, biology, physics.

[97]  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.

[98]  Marcel van Herk,et al.  Target definition in prostate, head, and neck. , 2005, Seminars in radiation oncology.

[99]  H. Zaidi,et al.  Magnetic resonance imaging-guided attenuation and scatter corrections in three-dimensional brain positron emission tomography. , 2003, Medical physics.

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

[101]  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.

[102]  Minsong Cao,et al.  Accuracy of UTE-MRI-based patient setup for brain cancer radiation therapy. , 2016, Medical physics.

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

[104]  A W Beavis,et al.  Radiotherapy treatment planning of brain tumours using MRI alone. , 1998, The British journal of radiology.

[105]  Srinivasan Vijayakumar,et al.  Marginal misses after postoperative intensity-modulated radiotherapy for head and neck cancer. , 2011, International journal of radiation oncology, biology, physics.

[106]  Jurgen Fripp,et al.  Automatic Substitute Computed Tomography Generation and Contouring for Magnetic Resonance Imaging (MRI)-Alone External Beam Radiation Therapy From Standard MRI Sequences. , 2015, International journal of radiation oncology, biology, physics.

[107]  Fredrik Nordström,et al.  MR-OPERA: A Multicenter/Multivendor Validation of Magnetic Resonance Imaging-Only Prostate Treatment Planning Using Synthetic Computed Tomography Images. , 2017, International journal of radiation oncology, biology, physics.

[108]  Slobodan Devic,et al.  MRI simulation for radiotherapy treatment planning. , 2012, Medical physics.

[109]  Benjamin Movsas,et al.  Initial clinical experience with a radiation oncology dedicated open 1.0T MR‐simulation , 2015, Journal of applied clinical medical physics.

[110]  C. Kirisits,et al.  Review of clinical brachytherapy uncertainties: Analysis guidelines of GEC-ESTRO and the AAPM☆ , 2014, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[111]  Christian Kirisits,et al.  Uncertainties in image guided adaptive cervix cancer brachytherapy: impact on planning and prescription. , 2013, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[112]  H. Kjer,et al.  A voxel-based investigation for MRI-only radiotherapy of the brain using ultra short echo times , 2014, Physics in medicine and biology.

[113]  Mary Feng,et al.  Synthetic CT for MRI-based liver stereotactic body radiotherapy treatment planning. , 2017, Physics in medicine and biology.

[114]  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.

[115]  Juha Korhonen,et al.  Dosimetric characterization of MRI-only treatment planning for brain tumors in atlas-based pseudo-CT images generated from standard T1-weighted MR images. , 2016, Medical physics.

[116]  Soumya Ghose,et al.  Substitute CT generation from a single ultra short time echo MRI sequence: preliminary study , 2017, Physics in medicine and biology.

[117]  B. Hargreaves,et al.  Metal artifact reduction with MAVRIC SL at 3-T MRI in patients with hip arthroplasty. , 2015, AJR. American journal of roentgenology.

[118]  Stephan G Nekolla,et al.  Attenuation correction for PET/MR: problems, novel approaches and practical solutions. , 2012, Zeitschrift fur medizinische Physik.

[119]  Tiina Seppälä,et al.  A dual model HU conversion from MRI intensity values within and outside of bone segment for MRI-based radiotherapy treatment planning of prostate cancer. , 2013, Medical physics.

[120]  L Chen,et al.  Dosimetric evaluation of MRI-based treatment planning for prostate cancer , 2004, Physics in medicine and biology.

[121]  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.

[122]  Cyrus Chargari,et al.  Accuracy of diffusion-weighted echo-planar MR imaging and ADC mapping in the evaluation of residual cervical carcinoma after radiation therapy. , 2011, Gynecologic oncology.

[123]  Koen Van Leemput,et al.  A patch-based pseudo-CT approach for MRI-only radiotherapy in the pelvis. , 2016, Medical physics.

[124]  Snehashis Roy,et al.  Synthesizing CT from Ultrashort Echo-Time MR Images via Convolutional Neural Networks , 2017, SASHIMI@MICCAI.

[125]  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.

[126]  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.

[127]  H. G. van der Poel,et al.  Repeatability of dose painting by numbers treatment planning in prostate cancer radiotherapy based on multiparametric magnetic resonance imaging , 2017, Physics in medicine and biology.

[128]  T. Brown,et al.  Noninvasive phosphorus magnetic resonance spectroscopic imaging predicts outcome to first-line chemotherapy in newly diagnosed patients with diffuse large B-cell lymphoma. , 2013, Academic Radiology.

[129]  Arne Skretting,et al.  A simulation of MRI based dose calculations on the basis of radiotherapy planning CT images , 2008, Acta oncologica.

[130]  Jonathan J Wyatt,et al.  Systematic Review of Synthetic Computed Tomography Generation Methodologies for Use in Magnetic Resonance Imaging-Only Radiation Therapy. , 2018, International journal of radiation oncology, biology, physics.

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

[132]  C. Caldwell,et al.  Toward magnetic resonance-only simulation: segmentation of bone in MR for radiation therapy verification of the head. , 2014, International journal of radiation oncology, biology, physics.

[133]  Richard L Ehman,et al.  MR elastography derived shear stiffness—a new imaging biomarker for the assessment of early tumor response to chemotherapy , 2014, Magnetic resonance in medicine.

[134]  T. Bock,et al.  Interobserver Comparison of CT and MRI-Based Prostate Apex Definition Clinical Relevance for Conformal Radiotherapy Treatment Planning , 2002, Strahlentherapie und Onkologie.

[135]  Jelmer M. Wolterink,et al.  Deep MR to CT Synthesis Using Unpaired Data , 2017, SASHIMI@MICCAI.

[136]  Mika Kapanen,et al.  T1/T2*-weighted MRI provides clinically relevant pseudo-CT density data for the pelvic bones in MRI-only based radiotherapy treatment planning , 2013, Acta oncologica.

[137]  Adam Johansson,et al.  Improved quality of computed tomography substitute derived from magnetic resonance (MR) data by incorporation of spatial information – potential application for MR-only radiotherapy and attenuation correction in positron emission tomography , 2013, Acta oncologica.

[138]  Christian Kirisits,et al.  Clinical impact of MRI assisted dose volume adaptation and dose escalation in brachytherapy of locally advanced cervix cancer. , 2007, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[139]  Mark Bydder,et al.  Magnetic Resonance: An Introduction to Ultrashort TE (UTE) Imaging , 2003, Journal of computer assisted tomography.

[140]  V S Khoo,et al.  New developments in MRI for target volume delineation in radiotherapy. , 2006, The British journal of radiology.

[141]  Hiroshi Fujita,et al.  K-means Clustering for Classifying Unlabelled MRI Data , 2007, 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA 2007).

[142]  Christian Kirisits,et al.  Consequences of random and systematic reconstruction uncertainties in 3D image based brachytherapy in cervical cancer. , 2008, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[143]  Z. Bhujwalla,et al.  Choline metabolism in malignant transformation , 2011, Nature Reviews Cancer.

[144]  Jun Yu,et al.  Voxel-wise uncertainty in CT substitute derived from MRI. , 2012, Medical physics.

[145]  Martin O. Leach,et al.  T2-Weighted 4D Magnetic Resonance Imaging for Application in Magnetic Resonance–Guided Radiotherapy Treatment Planning , 2017, Investigative radiology.

[146]  T. Helbich,et al.  Molecular imaging of cancer: MR spectroscopy and beyond. , 2012, European journal of radiology.

[147]  Jinsoo Uh,et al.  MRI-based treatment planning with pseudo CT generated through atlas registration. , 2014, Medical physics.

[148]  Olivier Salvado,et al.  MRI-guided prostate radiation therapy planning: Investigation of dosimetric accuracy of MRI-based dose planning. , 2011, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[149]  Fiona J Gilbert,et al.  Use of new imaging techniques to predict tumour response to therapy. , 2010, The Lancet. Oncology.