Feasibility of Multiparametric Positron Emission Tomography/Magnetic Resonance Imaging as a One-Stop Shop for Radiation Therapy Planning for Patients with Head and Neck Cancer

[1]  Liselotte Højgaard,et al.  AI-driven attenuation correction for brain PET/MRI: Clinical evaluation of a dementia cohort and importance of the training group size , 2020, NeuroImage.

[2]  Frank Zijlstra,et al.  Dosimetric evaluation of synthetic CT for head and neck radiotherapy generated by a patch-based 3D convolutional neural network. , 2019, Medical physics.

[3]  T. Beyer,et al.  Preparing data for multiparametric PET/MR imaging: Influence of PET point spread function modelling and EPI distortion correction on the spatial correlation of [18F]FDG-PET and diffusion-weighted MRI in head and neck cancer. , 2019, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

[4]  Josef A. Lundman,et al.  Dosimetric Impact of MRI Distortions: A Study on Head and Neck Cancers. , 2019, International journal of radiation oncology, biology, physics.

[5]  Carl Landwher,et al.  2018 , 2019, Communications of the ACM.

[6]  L. Marner,et al.  Deep Learning Based Attenuation Correction of PET/MRI in Pediatric Brain Tumor Patients: Evaluation in a Clinical Setting , 2019, Front. Neurosci..

[7]  Berkman Sahiner,et al.  Deep learning in medical imaging and radiation therapy. , 2018, Medical physics.

[8]  Jelmer M. Wolterink,et al.  MR-Only Brain Radiation Therapy: Dosimetric Evaluation of Synthetic CTs Generated by a Dilated Convolutional Neural Network. , 2018, International journal of radiation oncology, biology, physics.

[9]  Ninon Burgos,et al.  Comparative study of algorithms for synthetic CT generation from MRI: Consequences for MRI‐guided radiation planning in the pelvic region , 2018, Medical physics.

[10]  N. Schwenzer,et al.  Assessment of image quality of a radiotherapy-specific hardware solution for PET/MRI in head and neck cancer patients , 2018, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[11]  J. Axelsson,et al.  Technical Note: Adapting a GE SIGNA PET/MR scanner for radiotherapy , 2018, Medical physics.

[12]  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.

[13]  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.

[14]  Minsong Cao,et al.  Characterization of spatial distortion in a 0.35 T MRI-guided radiotherapy system , 2017, Physics in medicine and biology.

[15]  S. Ourselin,et al.  Evaluation of a multi-atlas CT synthesis approach for MRI-only radiotherapy treatment planning , 2017, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

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

[17]  Ninon Burgos,et al.  A multi-centre evaluation of eleven clinically feasible brain PET/MRI attenuation correction techniques using a large cohort of patients , 2016, NeuroImage.

[18]  Mark Oehmigen,et al.  Whole-body hybrid imaging concept for the integration of PET/MR into radiation therapy treatment planning , 2016, Physics in medicine and biology.

[19]  Indrin J Chetty,et al.  Technology for Innovation in Radiation Oncology. , 2015, International journal of radiation oncology, biology, physics.

[20]  Thomas Brox,et al.  U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.

[21]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[22]  Harald H Quick,et al.  Towards integration of PET/MR hybrid imaging into radiation therapy treatment planning. , 2014, Medical physics.

[23]  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.

[24]  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.

[25]  Daniela Thorwarth,et al.  Potential role of PET/MRI in radiotherapy treatment planning , 2013, Clinical and Translational Imaging.

[26]  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.

[27]  N. Lee,et al.  Target volume delineation in oropharyngeal cancer: impact of PET, MRI, and physical examination. , 2010, International journal of radiation oncology, biology, physics.

[28]  Sébastien Ourselin,et al.  Fast free-form deformation using graphics processing units , 2010, Comput. Methods Programs Biomed..

[29]  Tufve Nyholm,et al.  Systematisation of spatial uncertainties for comparison between a MR and a CT-based radiotherapy workflow for prostate treatments , 2009, Radiation oncology.

[30]  M. Karamouzis,et al.  Head and neck cancer , 2008, The Lancet.

[31]  Alicia Y Toledano,et al.  An evaluation of the variability of tumor-shape definition derived by experienced observers from CT images of supraglottic carcinomas (ACRIN protocol 6658). , 2007, International journal of radiation oncology, biology, physics.

[32]  D. Townsend,et al.  Method for transforming CT images for attenuation correction in PET/CT imaging. , 2006, Medical physics.

[33]  Søren M Bentzen,et al.  Radiation therapy: intensity modulated, image guided, biologically optimized and evidence based. , 2005, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

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

[35]  C. Snyderman,et al.  Head and neck malignancy: is PET/CT more accurate than PET or CT alone? , 2005, Radiology.

[36]  Søren M Bentzen,et al.  Theragnostic imaging for radiation oncology: dose-painting by numbers. , 2005, The Lancet. Oncology.

[37]  L. Ting,et al.  Impact of magnetic resonance imaging versus CT on nasopharyngeal carcinoma: primary tumor target delineation for radiotherapy , 2004, Head & neck.

[38]  Anne Bol,et al.  Evaluation of a multimodality image (CT, MRI and PET) coregistration procedure on phantom and head and neck cancer patients: accuracy, reproducibility and consistency. , 2003, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[39]  C C Ling,et al.  Towards multidimensional radiotherapy (MD-CRT): biological imaging and biological conformality. , 2000, International journal of radiation oncology, biology, physics.

[40]  M van Herk,et al.  The potential impact of CT-MRI matching on tumor volume delineation in advanced head and neck cancer. , 1997, International journal of radiation oncology, biology, physics.