Potentials and challenges of diffusion-weighted magnetic resonance imaging in radiotherapy

[1]  Y. Li,et al.  Differentiation between radiation-induced brain injury and glioma recurrence using 3D pCASL and dynamic susceptibility contrast-enhanced perfusion-weighted imaging. , 2018, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[2]  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.

[3]  Kyle M. L. Jones,et al.  Emerging Magnetic Resonance Imaging Technologies for Radiation Therapy Planning and Response Assessment. , 2018, International journal of radiation oncology, biology, physics.

[4]  H. Lyng,et al.  Combined MR Imaging of Oxygen Consumption and Supply Reveals Tumor Hypoxia and Aggressiveness in Prostate Cancer Patients. , 2018, Cancer research.

[5]  Daniela Thorwarth,et al.  Quantitative Imaging for Radiation Oncology. , 2018, International journal of radiation oncology, biology, physics.

[6]  Karin Haustermans,et al.  Contouring of prostate tumors on multiparametric MRI: Evaluation of clinical delineations in a multicenter radiotherapy trial. , 2018, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[7]  A. Priest,et al.  Role of PROPELLER-DWI of the prostate in reducing distortion and artefact from total hip replacement metalwork. , 2018, European journal of radiology.

[8]  D. Hu,et al.  Comparison of reduced field‐of‐view diffusion‐weighted imaging (DWI) and conventional DWI techniques in the assessment of rectal carcinoma at 3.0T: Image quality and histological T staging , 2018, Journal of magnetic resonance imaging : JMRI.

[9]  K. Haustermans,et al.  Standard whole prostate gland radiotherapy with and without lesion boost in prostate cancer: Toxicity in the FLAME randomized controlled trial. , 2018, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[10]  J. E. Park,et al.  Comparison of DWI Methods in the Pediatric Brain: PROPELLER Turbo Spin-Echo Imaging Versus Readout-Segmented Echo-Planar Imaging Versus Single-Shot Echo-Planar Imaging. , 2018, AJR. American journal of roentgenology.

[11]  A. Ahnesjö,et al.  Dose painting of prostate cancer based on Gleason score correlations with apparent diffusion coefficients , 2017, Acta oncologica.

[12]  P. Georg,et al.  Impact of hybrid PET/MR technology on multiparametric imaging and treatment response assessment of cervix cancer. , 2017, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[13]  A N T J Kotte,et al.  First patients treated with a 1.5 T MRI-Linac: clinical proof of concept of a high-precision, high-field MRI guided radiotherapy treatment , 2017, Physics in Medicine and Biology.

[14]  Justin M Ream,et al.  Reduced Field-of-View Diffusion-Weighted Magnetic Resonance Imaging of the Prostate at 3 Tesla: Comparison With Standard Echo-Planar Imaging Technique for Image Quality and Tumor Assessment , 2017, Journal of computer assisted tomography.

[15]  K. Nikolaou,et al.  Combination of integrated dynamic shimming and readout-segmented echo planar imaging for diffusion weighted MRI of the head and neck region at 3Tesla. , 2017, Magnetic resonance imaging.

[16]  N. Schwenzer,et al.  Distortion correction of diffusion-weighted magnetic resonance imaging of the head and neck in radiotherapy position , 2017, Acta oncologica.

[17]  Zhengyang Zhou,et al.  Predictive and prognostic value of intravoxel incoherent motion (IVIM) MR imaging in patients with advanced cervical cancers undergoing concurrent chemo-radiotherapy , 2017, Scientific Reports.

[18]  S. Lukacova,et al.  Diffusion tensor magnetic resonance imaging driven growth modeling for radiotherapy target definition in glioblastoma , 2017, Acta oncologica.

[19]  C. Haie-meder,et al.  Diffusion-weighted MRI in image-guided adaptive brachytherapy: Tumor delineation feasibility study and comparison with GEC-ESTRO guidelines. , 2017, Brachytherapy.

[20]  Olivier Gevaert,et al.  Quantitative imaging outperforms molecular markers when predicting response to chemoradiotherapy for rectal cancer. , 2017, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[21]  J. Kassubek,et al.  Cerebral Microstructural Alterations after Radiation Therapy in High-Grade Glioma: A Diffusion Tensor Imaging-Based Study , 2017, Front. Neurol..

[22]  M. Alber,et al.  Prognostic value of dynamic hypoxia PET in head and neck cancer: Results from a planned interim analysis of a randomized phase II hypoxia-image guided dose escalation trial. , 2017, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[23]  Vikas Gulani,et al.  Development of a Combined MR Fingerprinting and Diffusion Examination for Prostate Cancer. , 2017, Radiology.

[24]  B. Kiefer,et al.  Diffusion-weighted echo planar MR imaging of the neck at 3 T using integrated shimming: comparison of MR sequence techniques for reducing artifacts caused by magnetic-field inhomogeneities , 2017, Magnetic Resonance Materials in Physics, Biology and Medicine.

[25]  M. Iori,et al.  Feasibility of voxel-based Dose Painting for recurrent Glioblastoma guided by ADC values of Diffusion-Weighted MR imaging. , 2016, 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.

[26]  Cem Onal,et al.  Treatment response evaluation using the mean apparent diffusion coefficient in cervical cancer patients treated with definitive chemoradiotherapy , 2016, Journal of magnetic resonance imaging : JMRI.

[27]  Zhenyu Zhou,et al.  Intravoxel incoherent motion diffusion weighted MRI of cervical cancer - Correlated with tumor differentiation and perfusion. , 2016, Magnetic resonance imaging.

[28]  Dan Wang,et al.  Diffusion kurtosis imaging study on temporal lobe after nasopharyngeal carcinoma radiotherapy , 2016, Brain Research.

[29]  A. King,et al.  Functional MRI for the prediction of treatment response in head and neck squamous cell carcinoma: potential and limitations , 2016, Cancer Imaging.

[30]  F. Lucchesi,et al.  Pre-treatment MRI minimum apparent diffusion coefficient value is a potential prognostic imaging biomarker in cervical cancer patients treated with definitive chemoradiation , 2016, BMC Cancer.

[31]  O. Sabri,et al.  Simultaneous (18)F-FDG-PET/MRI: Associations between diffusion, glucose metabolism and histopathological parameters in patients with head and neck squamous cell carcinoma. , 2016, Oral oncology.

[32]  Georgios C. Manikis,et al.  Diffusion-weighted MR imaging of pancreatic cancer: A comparison of mono-exponential, bi-exponential and non-Gaussian kurtosis models , 2016, European journal of radiology open.

[33]  A. Fyles,et al.  Association of Apparent Diffusion Coefficient with Disease Recurrence in Patients with Locally Advanced Cervical Cancer Treated with Radical Chemotherapy and Radiation Therapy. , 2016, Radiology.

[34]  N. Schwenzer,et al.  Analysis of pairwise correlations in multi-parametric PET/MR data for biological tumor characterization and treatment individualization strategies , 2016, European Journal of Nuclear Medicine and Molecular Imaging.

[35]  Fridtjof Nüsslin,et al.  Individualized radiotherapy by combining high-end irradiation and magnetic resonance imaging , 2016, Strahlentherapie und Onkologie.

[36]  Tianyu Zhao,et al.  Online Magnetic Resonance Image Guided Adaptive Radiation Therapy: First Clinical Applications. , 2016, International journal of radiation oncology, biology, physics.

[37]  W. Oyen,et al.  Imaging-Based Treatment Adaptation in Radiation Oncology , 2015, The Journal of Nuclear Medicine.

[38]  C. Ménard,et al.  Readout-segmented echo-planar diffusion-weighted imaging improves geometric performance for image-guided radiation therapy of pelvic tumors. , 2015, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[39]  V. Jeyaseelan,et al.  Role of conventional and diffusion weighted MRI in predicting treatment response after low dose radiation and chemotherapy in locally advanced carcinoma cervix. , 2015, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[40]  H. Kauczor,et al.  Correlation of Histological Vessel Characteristics and Diffusion-Weighted Imaging Intravoxel Incoherent Motion–Derived Parameters in Pancreatic Ductal Adenocarcinomas and Pancreatic Neuroendocrine Tumors , 2015, Investigative radiology.

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

[42]  Geoffrey D. Hugo,et al.  Estimation of optimal b-value sets for obtaining apparent diffusion coefficient free from perfusion in non-small cell lung cancer , 2015, Physics in medicine and biology.

[43]  J. Stoker,et al.  Monitoring treatment response in patients undergoing chemoradiotherapy for locally advanced uterine cervical cancer by additional diffusion‐weighted imaging: A systematic review , 2015, Journal of magnetic resonance imaging : JMRI.

[44]  E. Hui,et al.  Relationship between intravoxel incoherent motion diffusion‐weighted MRI and dynamic contrast‐enhanced MRI in tissue perfusion of cervical cancers , 2015, Journal of magnetic resonance imaging : JMRI.

[45]  E. M. Pedersen,et al.  Diffusion-weighted magnetic resonance imaging during radiotherapy of locally advanced cervical cancer – treatment response assessment using different segmentation methods , 2015, Acta oncologica.

[46]  P. Hahn,et al.  Body MR Imaging: Artifacts, k-Space, and Solutions. , 2015, Radiographics : a review publication of the Radiological Society of North America, Inc.

[47]  Yue Cao,et al.  Hypercellularity Components of Glioblastoma Identified by High b-Value Diffusion-Weighted Imaging. , 2015, International journal of radiation oncology, biology, physics.

[48]  J. Lagendijk,et al.  Diffusion-weighted magnetic resonance imaging for the prediction of pathologic response to neoadjuvant chemoradiotherapy in esophageal cancer. , 2015, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[49]  D. Moses,et al.  Quantitative evaluation of diffusion-weighted imaging techniques for the purposes of radiotherapy planning in the prostate. , 2015, The British journal of radiology.

[50]  L. Marucci,et al.  Early radiation‐induced changes evaluated by intravoxel incoherent motion in the major salivary glands , 2015, Journal of magnetic resonance imaging : JMRI.

[51]  Wen-Chau Wu,et al.  Caveat of measuring perfusion indexes using intravoxel incoherent motion magnetic resonance imaging in the human brain , 2015, European Radiology.

[52]  D. Le Bihan,et al.  The clinical utility of reduced-distortion readout-segmented echo-planar imaging in the head and neck region: initial experience , 2014, European Radiology.

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

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

[55]  Dong Soo Lee,et al.  Prognostic Value of Metabolic Tumor Volume and Total Lesion Glycolysis in Head and Neck Cancer: A Systematic Review and Meta-Analysis , 2014, The Journal of Nuclear Medicine.

[56]  N. Langkilde,et al.  MRI target delineation may reduce long-term toxicity after prostate radiotherapy , 2014, Acta oncologica.

[57]  B. van Calster,et al.  Integrating pretreatment diffusion weighted MRI into a multivariable prognostic model for head and neck squamous cell carcinoma. , 2014, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[58]  Eisaku Ito,et al.  Apparent diffusion coefficient value as a biomarker reflecting morphological and biological features of prostate cancer , 2014, International Urology and Nephrology.

[59]  H. Kauczor,et al.  Multimodal Imaging for Early Functional Response Assessment of 90Y-/177Lu-DOTATOC Peptide Receptor Targeted Radiotherapy with DW-MRI and 68Ga-DOTATOC-PET/CT , 2014, Molecular Imaging and Biology.

[60]  Tae Min Kim,et al.  Differentiation of true progression from pseudoprogression in glioblastoma treated with radiation therapy and concomitant temozolomide: comparison study of standard and high-b-value diffusion-weighted imaging. , 2013, Radiology.

[61]  J. Hoogduin,et al.  Diffusion weighted MRI in head-and-neck cancer: geometrical accuracy. , 2013, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[62]  A. Wetter,et al.  Hybrid [¹⁸F]-FDG PET/MRI including non-Gaussian diffusion-weighted imaging (DWI): preliminary results in non-small cell lung cancer (NSCLC). , 2013, European journal of radiology.

[63]  Y. Jeong,et al.  Pre-Treatment Diffusion-Weighted MR Imaging for Predicting Tumor Recurrence in Uterine Cervical Cancer Treated with Concurrent Chemoradiation: Value of Histogram Analysis of Apparent Diffusion Coefficients , 2013, Korean journal of radiology.

[64]  Joe Y. Chang,et al.  Improved longitudinal length accuracy of gross tumor volume delineation with diffusion weighted magnetic resonance imaging for esophageal squamous cell carcinoma , 2013, Radiation oncology.

[65]  H. Schild,et al.  Intravoxel incoherent motion model-based liver lesion characterisation from three b-value diffusion-weighted MRI , 2013, European Radiology.

[66]  A Kopp-Schneider,et al.  Diffusion-weighted imaging in rectal carcinoma patients without and after chemoradiotherapy: a comparative study with histology. , 2013, European journal of radiology.

[67]  Bram Stieltjes,et al.  Characterization and therapy monitoring of head and neck carcinomas using diffusion-imaging-based intravoxel incoherent motion parameters—preliminary results , 2013, Neuroradiology.

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

[69]  Jing Yuan,et al.  Head and neck squamous cell carcinoma: diagnostic performance of diffusion-weighted MR imaging for the prediction of treatment response. , 2013, Radiology.

[70]  Philippe Lambin,et al.  Functional MRI for radiotherapy dose painting. , 2012, Magnetic resonance imaging.

[71]  Steen Jakobsen,et al.  FAZA PET/CT hypoxia imaging in patients with squamous cell carcinoma of the head and neck treated with radiotherapy: results from the DAHANCA 24 trial. , 2012, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[72]  A. King,et al.  Diffusion-weighted MR imaging in the head and neck. , 2012, Radiology.

[73]  Heidi Lyng,et al.  Pharmacokinetic parameters derived from dynamic contrast enhanced MRI of cervical cancers predict chemoradiotherapy outcome. , 2012, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[74]  Maaike R Moman,et al.  Pathologic validation of a model based on diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging for tumor delineation in the prostate peripheral zone. , 2012, International journal of radiation oncology, biology, physics.

[75]  Sandra Nuyts,et al.  Diffusion-weighted magnetic resonance imaging early after chemoradiotherapy to monitor treatment response in head-and-neck squamous cell carcinoma. , 2012, International journal of radiation oncology, biology, physics.

[76]  J. Fütterer,et al.  ESUR prostate MR guidelines 2012 , 2012, European Radiology.

[77]  Karin Haustermans,et al.  Value of diffusion-weighted magnetic resonance imaging for prediction and early assessment of response to neoadjuvant radiochemotherapy in rectal cancer: preliminary results. , 2012, International journal of radiation oncology, biology, physics.

[78]  Y. Jeong,et al.  Predicting response to neoadjuvant chemoradiation therapy in locally advanced rectal cancer: Diffusion‐weighted 3 tesla MR imaging , 2012, Journal of magnetic resonance imaging : JMRI.

[79]  K. Haustermans,et al.  Single blind randomized Phase III trial to investigate the benefit of a focal lesion ablative microboost in prostate cancer ( FLAME-trial ) : study protocol for a randomized controlled trial , 2012 .

[80]  T. Yoshiura,et al.  Apparent Diffusion Coefficient Calculated with Relatively High b-Values Correlates with Local Failure of Head and Neck Squamous Cell Carcinoma Treated with Radiotherapy , 2011, American Journal of Neuroradiology.

[81]  D. Collins,et al.  Intravoxel incoherent motion in body diffusion-weighted MRI: reality and challenges. , 2011, AJR. American journal of roentgenology.

[82]  Mark Jenkinson,et al.  Reducing distortions in diffusion‐weighted echo planar imaging with a dual‐echo blip‐reversed sequence , 2010, Magnetic resonance in medicine.

[83]  Brian D Ross,et al.  Predicting and monitoring cancer treatment response with diffusion‐weighted MRI , 2010, Journal of magnetic resonance imaging : JMRI.

[84]  Y. Liu,et al.  Diffusion-Weighted Magnetic Resonance Imaging of Uterine Cervical Cancer , 2009, Journal of computer assisted tomography.

[85]  A. Evans,et al.  Prostate cancer detection with multi‐parametric MRI: Logistic regression analysis of quantitative T2, diffusion‐weighted imaging, and dynamic contrast‐enhanced MRI , 2009, Journal of magnetic resonance imaging : JMRI.

[86]  Sigrid Stroobants,et al.  Dose Painting in Radiotherapy for Head and Neck Squamous Cell Carcinoma: Value of Repeated Functional Imaging with 18F-FDG PET, 18F-Fluoromisonidazole PET, Diffusion-Weighted MRI, and Dynamic Contrast-Enhanced MRI , 2009, Journal of Nuclear Medicine.

[87]  Gerda M Verduijn,et al.  Magnetic resonance imaging protocol optimization for delineation of gross tumor volume in hypopharyngeal and laryngeal tumors. , 2009, International journal of radiation oncology, biology, physics.

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

[89]  David J Collins,et al.  Technology Insight: water diffusion MRI—a potential new biomarker of response to cancer therapy , 2008, Nature Clinical Practice Oncology.

[90]  Yue Cao,et al.  Radiation-induced changes in normal-appearing white matter in patients with cerebral tumors: a diffusion tensor imaging study. , 2008, International journal of radiation oncology, biology, physics.

[91]  Stefan Skare,et al.  Clinical multishot DW‐EPI through parallel imaging with considerations of susceptibility, motion, and noise , 2007, Magnetic resonance in medicine.

[92]  Daniela Thorwarth,et al.  Hypoxia dose painting by numbers: a planning study. , 2007, International journal of radiation oncology, biology, physics.

[93]  D. Le Bihan,et al.  Artifacts and pitfalls in diffusion MRI , 2006, Journal of magnetic resonance imaging : JMRI.

[94]  Daniela Thorwarth,et al.  Kinetic analysis of dynamic 18F-fluoromisonidazole PET correlates with radiation treatment outcome in head-and-neck cancer , 2005, BMC Cancer.

[95]  J. Helpern,et al.  Diffusional kurtosis imaging: The quantification of non‐gaussian water diffusion by means of magnetic resonance imaging , 2005, Magnetic resonance in medicine.

[96]  D. Le Bihan,et al.  Diffusion tensor imaging: Concepts and applications , 2001, Journal of magnetic resonance imaging : JMRI.

[97]  D. Le Bihan,et al.  Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. , 1988, Radiology.

[98]  E. Stejskal.  Use of Spin Echoes in a Pulsed Magnetic‐Field Gradient to Study Anisotropic, Restricted Diffusion and Flow , 1965 .

[99]  D. Knol,et al.  Predictive value of diffusion-weighted imaging without and with including contrast-enhanced magnetic resonance imaging in image analysis of head and neck squamous cell carcinoma. , 2015, European journal of radiology.

[100]  J. Dimopoulos,et al.  The Use of Sectional Imaging with CT and MRI for Image-Guided Therapy , 2011 .

[101]  P. Basser,et al.  Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. , 1996, Journal of magnetic resonance. Series B.