The Use of Quantitative Imaging in Radiation Oncology: A Quantitative Imaging Network (QIN) Perspective.
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Paul Kinahan | P. Lambin | D. Mankoff | L. Schwartz | J. Buatti | J. Mountz | R. Wahl | H. Linden | N. Hylton | R. Nordstrom | D. Rubin | B. Vikram | M. Jacobs | D. Jaffray | H. Shu | B. Kurland | T. Dilling | E. Gerstner | K. Kurdziel | H. Shim | M. Holdhoff | E. Jones | L. Hadjiiski | Lori Henderson | R. Press | Edward Taylor | E. Taylor
[1] H. Zaidi,et al. Local recurrence of squamous cell carcinoma of the head and neck after radio(chemo)therapy: Diagnostic performance of FDG-PET/MRI with diffusion-weighted sequences , 2017, European Radiology.
[2] Yue Cao,et al. Investigation of the diffusion abnormality index as a new imaging biomarker for early assessment of brain tumor response to radiation therapy. , 2014, Neuro-oncology.
[3] Robert J. Gillies,et al. The effect of SUV discretization in quantitative FDG-PET Radiomics: the need for standardized methodology in tumor texture analysis , 2015, Scientific Reports.
[4] Isabelle Berry,et al. Proton magnetic resonance spectroscopic imaging in newly diagnosed glioblastoma: predictive value for the site of postradiotherapy relapse in a prospective longitudinal study. , 2008, International journal of radiation oncology, biology, physics.
[5] Anant Madabhushi,et al. Radiomics based targeted radiotherapy planning (Rad-TRaP): a computational framework for prostate cancer treatment planning with MRI , 2016, Radiation Oncology.
[6] J. Muratet,et al. Use of Metabolic Parameters as Prognostic Factors During Concomitant Chemoradiotherapy for Locally Advanced Cervical Cancer , 2017, American journal of clinical oncology.
[7] D. Hedley,et al. Analysis of the intra- and intertumoral heterogeneity of hypoxia in pancreatic cancer patients receiving the nitroimidazole tracer pimonidazole , 2015, British Journal of Cancer.
[8] Vincent Magnotta,et al. 3-Dimensional magnetic resonance spectroscopic imaging at 3 Tesla for early response assessment of glioblastoma patients during external beam radiation therapy. , 2014, International journal of radiation oncology, biology, physics.
[9] Raymond H Mak,et al. CT-based radiomic analysis of stereotactic body radiation therapy patients with lung cancer. , 2016, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[10] Timothy D Johnson,et al. Parametric response map as an imaging biomarker to distinguish progression from pseudoprogression in high-grade glioma. , 2010, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[11] Philippe Lambin,et al. Preclinical evaluation and validation of [18F]HX4, a promising hypoxia marker for PET imaging , 2011, Proceedings of the National Academy of Sciences.
[12] D. Jaffray,et al. Quantifying hypoxia in human cancers using static PET imaging , 2016, Physics in medicine and biology.
[13] Brian J Smith,et al. A Bayesian framework for performance assessment and comparison of imaging biomarker quantification methods , 2019, Statistical methods in medical research.
[14] Martin A Lodge,et al. Noise Considerations for PET Quantification Using Maximum and Peak Standardized Uptake Value , 2012, The Journal of Nuclear Medicine.
[15] Ilwoo Park,et al. Patterns of recurrence analysis in newly diagnosed glioblastoma multiforme after three-dimensional conformal radiation therapy with respect to pre-radiation therapy magnetic resonance spectroscopic findings. , 2007, International journal of radiation oncology, biology, physics.
[16] M. Baumann,et al. Early FDG PET at 10 or 20 Gy under chemoradiotherapy is prognostic for locoregional control and overall survival in patients with head and neck cancer , 2011, European Journal of Nuclear Medicine and Molecular Imaging.
[17] Brian J. Smith,et al. Using FLT PET to quantify and reduce hematologic toxicity due tochemoradiation therapy for pelvic cancer patients , 2016 .
[18] R. Wahl,et al. From RECIST to PERCIST: Evolving Considerations for PET Response Criteria in Solid Tumors , 2009, Journal of Nuclear Medicine.
[19] C. Faivre-Finn,et al. Early reduction in tumour [18F]fluorothymidine (FLT) uptake in patients with non-small cell lung cancer (NSCLC) treated with radiotherapy alone , 2014, European Journal of Nuclear Medicine and Molecular Imaging.
[20] P. Lambin,et al. Defining the biological basis of radiomic phenotypes in lung cancer , 2017, eLife.
[21] S. Woo,et al. Head-To-Head Comparison Between High- and Standard-b-Value DWI for Detecting Prostate Cancer: A Systematic Review and Meta-Analysis. , 2018, AJR. American journal of roentgenology.
[22] H. Kohrt,et al. Ablative Tumor Radiation Can Change the Tumor Immune Cell Microenvironment to Induce Durable Complete Remissions , 2015, Clinical Cancer Research.
[23] W. Frankel,et al. Initial results of CALGB 80803 (Alliance): A randomized phase II trial of PET scan-directed combined modality therapy for esophageal cancer. , 2017 .
[24] Yohann Tschudi,et al. Prostate cancer radiomics and the promise of radiogenomics. , 2016, Translational cancer research.
[25] Wengui Xu,et al. Consequences of additional use of contrast-enhanced 18F-FDG PET/CT in target volume delineation and dose distribution for pancreatic cancer , 2015, The British journal of radiology.
[26] Peng Wang,et al. An approach to identify, from DCE MRI, significant subvolumes of tumors related to outcomes in advanced head-and-neck cancer. , 2012, Medical physics.
[27] Dimitris Visvikis,et al. Prediction of outcome using pretreatment 18F-FDG PET/CT and MRI radiomics in locally advanced cervical cancer treated with chemoradiotherapy , 2018, European Journal of Nuclear Medicine and Molecular Imaging.
[28] P. Lambin,et al. CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma. , 2015, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[29] Do selective radiation dose escalation and tumour hypoxia status impact the loco-regional tumour control after radio-chemotherapy of head & neck tumours? The ESCALOX protocol , 2017, Radiation oncology.
[30] H. Thoeny,et al. Diffusion-weighted MR imaging including bi-exponential fitting for the detection of recurrent or residual tumour after (chemo)radiotherapy for laryngeal and hypopharyngeal cancers , 2013, European Radiology.
[31] Benjamin M Ellingson,et al. Longitudinal DSC-MRI for Distinguishing Tumor Recurrence From Pseudoprogression in Patients With a High-grade Glioma , 2017, American journal of clinical oncology.
[32] C. Roehrborn,et al. Quantitative diffusion‐weighted imaging and dynamic contrast‐enhanced characterization of the index lesion with multiparametric MRI in prostate cancer patients , 2017, Journal of magnetic resonance imaging : JMRI.
[33] A. Ng,et al. Modern radiation therapy for nodal non-Hodgkin lymphoma-target definition and dose guidelines from the International Lymphoma Radiation Oncology Group. , 2014, International journal of radiation oncology, biology, physics.
[34] Eric J. W. Visser,et al. FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0 , 2014, European Journal of Nuclear Medicine and Molecular Imaging.
[35] P. Lambin,et al. Evaluation of early metabolic responses in rectal cancer during combined radiochemotherapy or radiotherapy alone: sequential FDG-PET-CT findings. , 2010, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[36] Benjamin Haibe-Kains,et al. Radiomic feature clusters and Prognostic Signatures specific for Lung and Head & Neck cancer , 2015, Scientific Reports.
[37] D. Dearnaley,et al. Diffusion-weighted MRI for locally recurrent prostate cancer after external beam radiotherapy. , 2012, AJR. American journal of roentgenology.
[38] Thomas E. Yankeelov,et al. Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network , 2017, Journal of medical imaging.
[39] Thomas Filleron,et al. Evaluation of the lactate-to-N-acetyl-aspartate ratio defined with magnetic resonance spectroscopic imaging before radiation therapy as a new predictive marker of the site of relapse in patients with glioblastoma multiforme. , 2014, International journal of radiation oncology, biology, physics.
[40] Y. Yamada,et al. Long-term outcome of magnetic resonance spectroscopic image-directed dose escalation for prostate brachytherapy. , 2016, Brachytherapy.
[41] Catherine M. Lockhart,et al. Quantifying and Reducing the Effect of Calibration Error on Variability of PET/CT Standardized Uptake Value Measurements , 2011, The Journal of Nuclear Medicine.
[42] D. Hedley,et al. Tumor hypoxia has independent predictor impact only in patients with node-negative cervix cancer. , 2002, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[43] Samuel H. Hawkins,et al. Reproducibility and Prognosis of Quantitative Features Extracted from CT Images. , 2014, Translational oncology.
[44] Andrea Lupi,et al. The effect of 18F-FDG-PET/CT respiratory gating on detected metabolic activity in lung lesions , 2009, Annals of nuclear medicine.
[45] Ender Konukoglu,et al. Post-radiochemotherapy PET radiomics in head and neck cancer - The influence of radiomics implementation on the reproducibility of local control tumor models. , 2017, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[46] M. Milette,et al. Ultrasound-planned high-dose-rate prostate brachytherapy: dose painting to the dominant intraprostatic lesion. , 2014, Brachytherapy.
[47] J. Kurhanewicz,et al. The role of metabolic imaging in radiation therapy of prostate cancer , 2014, NMR in biomedicine.
[48] P. Grigsby,et al. Changes in cervical cancer FDG uptake during chemoradiation and association with response. , 2013, International journal of radiation oncology, biology, physics.
[49] P. Carroll,et al. Does local recurrence of prostate cancer after radiation therapy occur at the site of primary tumor? Results of a longitudinal MRI and MRSI study. , 2012, International journal of radiation oncology, biology, physics.
[50] N. Wu,et al. DCE-MRI Perfusion and Permeability Parameters as predictors of tumor response to CCRT in Patients with locally advanced NSCLC , 2016, Scientific Reports.
[51] V. Goh,et al. Primary colorectal cancer: use of kinetic modeling of dynamic contrast-enhanced CT data to predict clinical outcome. , 2013, Radiology.
[52] R L Wahl,et al. Lung cancer: reproducibility of quantitative measurements for evaluating 2-[F-18]-fluoro-2-deoxy-D-glucose uptake at PET. , 1995, Radiology.
[53] S. Nour,et al. The Potential Role of Magnetic Resonance Spectroscopy in Image-Guided Radiotherapy , 2014, Front. Oncol..
[54] E. M. Pedersen,et al. Dynamic Contrast-Enhanced Computed Tomography as a Potential Biomarker in Patients With Metastatic Renal Cell Carcinoma: Preliminary Results From the Danish Renal Cancer Group Study-1 , 2014, Investigative radiology.
[55] Werner Vach,et al. Serial [18F]-fluoromisonidazole PET during radiochemotherapy for locally advanced head and neck cancer and its correlation with outcome. , 2015, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[56] Yue Cao,et al. SU‐E‐J‐241: Wavelet‐Based Temporal Feature Extraction From DCE‐MRI to Identify Sub‐Volumes of Low Blood Volume in Head‐And‐Neck Cancer , 2015 .
[57] Sabine Van Huffel,et al. Multiproject–multicenter evaluation of automatic brain tumor classification by magnetic resonance spectroscopy , 2008, Magnetic Resonance Materials in Physics, Biology and Medicine.
[58] Eduard Schreibmann,et al. Simulating the Effect of Spectroscopic MRI as a Metric for Radiation Therapy Planning in Patients with Glioblastoma , 2016, Tomography.
[59] S. Fanti,et al. Early 18F‐2‐fluoro‐2‐deoxy‐d‐glucose positron emission tomography may identify a subset of patients with estrogen receptor‐positive breast cancer who will not respond optimally to preoperative chemotherapy , 2010, Cancer.
[60] Thomas Bachelot,et al. Use of [(18)F]-FDG PET to predict response to neoadjuvant trastuzumab and docetaxel in patients with HER2-positive breast cancer, and addition of bevacizumab to neoadjuvant trastuzumab and docetaxel in [(18)F]-FDG PET-predicted non-responders (AVATAXHER): an open-label, randomised phase 2 trial. , 2014, The Lancet. Oncology.
[61] T. Smith,et al. Accuracy of high b-value diffusion-weighted MRI for prostate cancer detection: a meta-analysis , 2018, Acta radiologica.
[62] Lubomir M. Hadjiiski,et al. Radiomics of Lung Nodules: A Multi-Institutional Study of Robustness and Agreement of Quantitative Imaging Features , 2016, Tomography.
[63] Raymond H Mak,et al. Radiomic phenotype features predict pathological response in non-small cell lung cancer. , 2016, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[64] Steffen Greilich,et al. Experimental verification of ion stopping power prediction from dual energy CT data in tissue surrogates , 2014, Physics in medicine and biology.
[65] G. Beets,et al. Value of DCE-MRI for staging and response evaluation in rectal cancer: A systematic review. , 2017, European journal of radiology.
[66] R L Wahl,et al. In vitro assessment of 2-fluoro-2-deoxy-D-glucose, L-methionine and thymidine as agents to monitor the early response of a human adenocarcinoma cell line to radiotherapy. , 1993, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[67] H. Asamura,et al. Prognostic significance of hypoxic PET using (18)F-FAZA and (62)Cu-ATSM in non-small-cell lung cancer. , 2016, Lung cancer.
[68] Catherine Coolens,et al. Comparison of Voxel-Wise Tumor Perfusion Changes Measured With Dynamic Contrast-Enhanced (DCE) MRI and Volumetric DCE CT in Patients With Metastatic Brain Cancer Treated with Radiosurgery , 2016, Tomography.
[69] Sung-Bae Kim,et al. 18F‐fluorodeoxyglucose uptake predicts pathological complete response after neoadjuvant chemotherapy for breast cancer: A retrospective cohort study , 2013, Journal of surgical oncology.
[70] Ghassan Hamarneh,et al. Multi‐site quality and variability analysis of 3D FDG PET segmentations based on phantom and clinical image data , 2017, Medical physics.
[71] K. Sugimura,et al. Do apparent diffusion coefficient (ADC) values obtained using high b-values with a 3-T MRI correlate better than a transrectal ultrasound (TRUS)-guided biopsy with true Gleason scores obtained from radical prostatectomy specimens for patients with prostate cancer? , 2013, European journal of radiology.
[72] H. Groen,et al. Hypoxia imaging using Positron Emission Tomography in non-small cell lung cancer: implications for radiotherapy. , 2012, Cancer treatment reviews.
[73] Robert J. Gillies,et al. A Comparison of Lung Nodule Segmentation Algorithms: Methods and Results from a Multi-institutional Study , 2016, Journal of Digital Imaging.
[74] N. Shah,et al. Radiation injury vs. recurrent brain metastasis: combining textural feature radiomics analysis and standard parameters may increase 18F-FET PET accuracy without dynamic scans , 2017, European Radiology.
[75] C. Kim,et al. High-b-value diffusion-weighted imaging at 3 T to detect prostate cancer: comparisons between b values of 1,000 and 2,000 s/mm2. , 2010, AJR. American journal of roentgenology.
[76] Peter Balter,et al. Delta-radiomics features for the prediction of patient outcomes in non–small cell lung cancer , 2017, Scientific Reports.
[77] Martin A. Lodge,et al. Impact of PET/CT system, reconstruction protocol, data analysis method, and repositioning on PET/CT precision: An experimental evaluation using an oncology and brain phantom , 2017, Medical physics.
[78] Philippe Lambin,et al. Time trends in the maximal uptake of FDG on PET scan during thoracic radiotherapy. A prospective study in locally advanced non-small cell lung cancer (NSCLC) patients. , 2007, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[79] John M Buatti,et al. Automated model‐based quantitative analysis of phantoms with spherical inserts in FDG PET scans , 2018, Medical physics.
[80] S. Strober,et al. Disruption of evasive immune cell microenvironment in tumors reflects immunity induced by radiation therapy , 2016, Oncoimmunology.
[81] Robert Jeraj,et al. Molecular Imaging to Plan Radiotherapy and Evaluate Its Efficacy , 2015, The Journal of Nuclear Medicine.
[82] Thomas E. Yankeelov,et al. The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge , 2016, Tomography.
[83] M. Muzi,et al. Imaging Hypoxia with 18F-Fluoromisonidazole: Challenges in Moving to a More Complicated Analysis , 2016, The Journal of Nuclear Medicine.
[84] 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.
[85] Aswin L Hoffmann,et al. Comparison of five segmentation tools for 18F-fluoro-deoxy-glucose-positron emission tomography-based target volume definition in head and neck cancer. , 2007, International journal of radiation oncology, biology, physics.
[86] Jing Li,et al. A predictive model for distinguishing radiation necrosis from tumour progression after gamma knife radiosurgery based on radiomic features from MR images , 2018, European Radiology.
[87] N. Lee,et al. Postoperative PET/CT and target delineation before adjuvant radiotherapy in patients with oral cavity squamous cell carcinoma , 2016, Head & neck.
[88] P Tiwari,et al. Computer-Extracted Texture Features to Distinguish Cerebral Radionecrosis from Recurrent Brain Tumors on Multiparametric MRI: A Feasibility Study , 2016, American Journal of Neuroradiology.
[89] Ning Wu,et al. Tumor response in patients with advanced non-small cell lung cancer: perfusion CT evaluation of chemotherapy and radiation therapy. , 2009, AJR. American journal of roentgenology.
[90] J. Humm,et al. Multiparametric Imaging of Tumor Hypoxia and Perfusion with 18F-Fluoromisonidazole Dynamic PET in Head and Neck Cancer , 2017, The Journal of Nuclear Medicine.
[91] 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.
[92] Peter Jezzard,et al. Noninvasive Quantification of 2-Hydroxyglutarate in Human Gliomas with IDH1 and IDH2 Mutations. , 2016, Cancer research.
[93] J. Dai,et al. Diffusion-weighted MRI in early assessment of tumour response to radiotherapy in high-risk prostate cancer. , 2014, The British journal of radiology.
[94] David T. W. Jones,et al. Radiomic subtyping improves disease stratification beyond key molecular, clinical, and standard imaging characteristics in patients with glioblastoma , 2018, Neuro-oncology.
[95] Pamela Catton,et al. Polarographic electrode study of tumor oxygenation in clinically localized prostate cancer. , 2004, International journal of radiation oncology, biology, physics.
[96] Indrin J Chetty,et al. A pilot study of [18F]fluorodeoxyglucose positron emission tomography scans during and after radiation-based therapy in patients with non small-cell lung cancer. , 2007, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[97] Janet S. Reddin,et al. Qualification of National Cancer Institute–Designated Cancer Centers for Quantitative PET/CT Imaging in Clinical Trials , 2017, The Journal of Nuclear Medicine.
[98] Philippe Lambin,et al. Response Assessment Using 18F-FDG PET Early in the Course of Radiotherapy Correlates with Survival in Advanced-Stage Non–Small Cell Lung Cancer , 2012, The Journal of Nuclear Medicine.
[99] Randall K Ten Haken,et al. Effect of Midtreatment PET/CT-Adapted Radiation Therapy With Concurrent Chemotherapy in Patients With Locally Advanced Non–Small-Cell Lung Cancer: A Phase 2 Clinical Trial , 2017, JAMA oncology.
[100] S. Blinder,et al. Performance Assessment of a Preclinical PET Scanner with Pinhole Collimation by Comparison to a Coincidence-Based Small-Animal PET Scanner , 2014, The Journal of Nuclear Medicine.
[101] R. Bristow,et al. Hypoxia and Predicting Radiation Response. , 2015, Seminars in radiation oncology.
[102] Yuka Yamamoto,et al. Usefulness of 3′-Deoxy-3′-18F-Fluorothymidine PET for Predicting Early Response to Chemoradiotherapy in Head and Neck Cancer , 2012, The Journal of Nuclear Medicine.
[103] Raymond Y Huang,et al. Residual Convolutional Neural Network for the Determination of IDH Status in Low- and High-Grade Gliomas from MR Imaging , 2017, Clinical Cancer Research.
[104] Daniel L. Rubin,et al. Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions , 2017, Journal of Digital Imaging.
[105] M. Baumann,et al. Usefulness of dynamic contrast enhanced computed tomography in patients with non-small-cell lung cancer scheduled for radiation therapy. , 2010, Lung cancer.
[106] R. Wahl,et al. A comparison of FLT to FDG PET/CT in the early assessment of chemotherapy response in stages IB–IIIA resectable NSCLC , 2017, EJNMMI Research.
[107] Paul Kinahan,et al. Quantitative Imaging in Cancer Clinical Trials , 2016, Clinical Cancer Research.
[108] Martin A Lodge,et al. Repeatability of 18F-FLT PET in a Multicenter Study of Patients with High-Grade Glioma , 2017, The Journal of Nuclear Medicine.
[109] Z. Bhujwalla,et al. Choline phospholipid metabolism: A target in cancer cells? , 2003, Journal of cellular biochemistry.
[110] B. Hoeben,et al. 18F-FLT PET During Radiotherapy or Chemoradiotherapy in Head and Neck Squamous Cell Carcinoma Is an Early Predictor of Outcome , 2013, The Journal of Nuclear Medicine.
[111] O. Brustugun. Hypoxia as a cause of treatment failure in non-small cell carcinoma of the lung. , 2015, Seminars in radiation oncology.
[112] J. Metz,et al. Clinical utility of integrated positron emission tomography/computed tomography imaging in the clinical management and radiation treatment planning of locally advanced rectal cancer. , 2014, Practical radiation oncology.
[113] P. Vaupel,et al. Tumor tissue oxygenation as evaluated by computerized-pO2-histography. , 1990, International journal of radiation oncology, biology, physics.
[114] John Quackenbush,et al. Somatic Mutations Drive Distinct Imaging Phenotypes in Lung Cancer. , 2017, Cancer research.
[115] K. Murase,et al. Radiotherapy treatment planning with contrast-enhanced computed tomography: feasibility of dual-energy virtual unenhanced imaging for improved dose calculations , 2014, Radiation oncology.
[116] Wolfgang A Weber,et al. PET to assess early metabolic response and to guide treatment of adenocarcinoma of the oesophagogastric junction: the MUNICON phase II trial. , 2007, The Lancet. Oncology.
[117] Reubendra Jeganathan,et al. Does pre-operative estimation of oesophageal tumour metabolic length using 18F-fluorodeoxyglucose PET/CT images compare with surgical pathology length? , 2011, European Journal of Nuclear Medicine and Molecular Imaging.
[118] Robert J. Gillies,et al. Association of multiparametric MRI quantitative imaging features with prostate cancer gene expression in MRI-targeted prostate biopsies , 2016, Oncotarget.
[119] Milan Sonka,et al. Automated measurement of uptake in cerebellum, liver, and aortic arch in full-body FDG PET/CT scans. , 2012, Medical physics.
[120] Patrick Granton,et al. Radiomics: extracting more information from medical images using advanced feature analysis. , 2012, European journal of cancer.
[121] A Gregory Sorensen,et al. Dynamic susceptibility contrast MRI measures of relative cerebral blood volume as a prognostic marker for overall survival in recurrent glioblastoma: results from the ACRIN 6677/RTOG 0625 multicenter trial. , 2015, Neuro-oncology.
[122] P. Lambin,et al. Selective nodal irradiation on basis of (18)FDG-PET scans in limited-disease small-cell lung cancer: a prospective study. , 2010, International journal of radiation oncology, biology, physics.
[123] Eugene Wong,et al. Dynamic contrast enhanced CT aiding gross tumor volume delineation of liver tumors: an interobserver variability study. , 2014, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[124] M. Scherr,et al. Proton MR spectroscopy of the prostate. , 2007, European journal of radiology.
[125] Marianne Patt,et al. [18F]Fluoroazomycinarabinofuranoside (18FAZA) and [18F]Fluoromisonidazole (18FMISO): a comparative study of their selective uptake in hypoxic cells and PET imaging in experimental rat tumors. , 2003, Nuclear medicine and biology.
[126] John P. Muzi,et al. 18F-Fluoromisonidazole Quantification of Hypoxia in Human Cancer Patients Using Image-Derived Blood Surrogate Tissue Reference Regions , 2015, The Journal of Nuclear Medicine.
[127] R. Wahl,et al. Optimum Lean Body Formulation for Correction of Standardized Uptake Value in PET Imaging , 2014, The Journal of Nuclear Medicine.
[128] Habib Zaidi,et al. Classification and evaluation strategies of auto‐segmentation approaches for PET: Report of AAPM task group No. 211 , 2017, Medical physics.
[129] 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.
[130] P. Fumoleau,et al. Changes in 18F-FDG tumor metabolism after a first course of neoadjuvant chemotherapy in breast cancer: influence of tumor subtypes. , 2012, Annals of oncology : official journal of the European Society for Medical Oncology.
[131] F DuBois Bowman,et al. Initial experience with the radiotracer anti-1-amino-3-18F-fluorocyclobutane-1-carboxylic acid with PET/CT in prostate carcinoma. , 2007, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[132] Jason A Koutcher,et al. Dynamic contrast-enhanced magnetic resonance imaging as a predictor of outcome in head-and-neck squamous cell carcinoma patients with nodal metastases. , 2012, International journal of radiation oncology, biology, physics.
[133] G. Weinstein,et al. Prediction of Response to Chemoradiation Therapy in Squamous Cell Carcinomas of the Head and Neck Using Dynamic Contrast-Enhanced MR Imaging , 2010, American Journal of Neuroradiology.
[134] D. Mankoff,et al. ACRIN 6684: Assessment of Tumor Hypoxia in Newly Diagnosed Glioblastoma Using 18F-FMISO PET and MRI , 2016, Clinical Cancer Research.
[135] F. Sedlmayer,et al. Assessment of response to neoadjuvant radiochemotherapy with F-18 FLT and F-18 FDG PET/CT in patients with rectal cancer , 2014, Annals of Nuclear Medicine.
[136] P. Lambin,et al. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach , 2014, Nature Communications.
[137] Kujtim Latifi,et al. CT imaging features associated with recurrence in non-small cell lung cancer patients after stereotactic body radiotherapy , 2017, Radiation Oncology.
[138] T. Sone,et al. Incremental value of high b value diffusion-weighted magnetic resonance imaging at 3-T for prediction of extracapsular extension in patients with prostate cancer: preliminary experience , 2017, La radiologia medica.
[139] Milan Sonka,et al. Semiautomated segmentation of head and neck cancers in 18F-FDG PET scans: A just-enough-interaction approach , 2016, Medical physics.
[140] Avraham Eisbruch,et al. Early prediction of outcome in advanced head-and-neck cancer based on tumor blood volume alterations during therapy: a prospective study. , 2008, International journal of radiation oncology, biology, physics.
[141] Brian J. Smith,et al. Using [(18)F]Fluorothymidine Imaged With Positron Emission Tomography to Quantify and Reduce Hematologic Toxicity Due to Chemoradiation Therapy for Pelvic Cancer Patients. , 2016, International journal of radiation oncology, biology, physics.
[142] Susan M. Chang,et al. Survival analysis in patients with newly diagnosed glioblastoma using pre- and postradiotherapy MR spectroscopic imaging. , 2013, Neuro-oncology.
[143] C. Roy,et al. Comparative sensitivities of functional MRI sequences in detection of local recurrence of prostate carcinoma after radical prostatectomy or external-beam radiotherapy. , 2013, AJR. American journal of roentgenology.
[144] Carlo Catalano,et al. Whole-tumor perfusion CT in patients with advanced lung adenocarcinoma treated with conventional and antiangiogenetic chemotherapy: initial experience. , 2011, Radiology.
[145] David Jaffray,et al. Automated voxel-based analysis of volumetric dynamic contrast-enhanced CT data improves measurement of serial changes in tumor vascular biomarkers. , 2015, International journal of radiation oncology, biology, physics.
[146] V. Clementi,et al. Clinical Investigation : Genitourinary Cancer Locally Advanced Prostate Cancer : Three-Dimensional Magnetic Resonance Spectroscopy to Monitor Prostate Response to Therapy , 2022 .
[147] R. Fisher,et al. Prognostic significance of [18F]-misonidazole positron emission tomography-detected tumor hypoxia in patients with advanced head and neck cancer randomly assigned to chemoradiation with or without tirapazamine: a substudy of Trans-Tasman Radiation Oncology Group Study 98.02. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[148] Xavier Franceries,et al. Plate-based transfection and culturing technique for genetic manipulation of Plasmodium falciparum , 2012, Malaria Journal.
[149] Sean S. Park,et al. Differentiation between intra-axial metastatic tumor progression and radiation injury following fractionated radiation therapy or stereotactic radiosurgery using MR spectroscopy, perfusion MR imaging or volume progression modeling. , 2011, Magnetic resonance imaging.
[150] L. Wiens,et al. Validation of FLT uptake as a measure of thymidine kinase-1 activity in A549 carcinoma cells. , 2002, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[151] P. Lambin,et al. Time trends in the maximal uptake of FDG on PET scan during thoracic radiotherapy. A prospective study in locally advanced non-small cell lung cancer (NSCLC) patients , 2007 .
[152] H. Aerts. The Potential of Radiomic-Based Phenotyping in Precision Medicine: A Review. , 2016, JAMA oncology.
[153] J. Pruvo,et al. Dynamic contrast-enhanced MR imaging pharmacokinetic parameters as predictors of treatment response of brain metastases in patients with lung cancer , 2017, European Radiology.
[154] Gisela Mir Arnau,et al. The Transcriptional Landscape of Radiation-Treated Human Prostate Cancer: Analysis of a Prospective Tissue Cohort. , 2018, International journal of radiation oncology, biology, physics.
[155] D. Jaffray,et al. Impact of tissue transport on PET hypoxia quantification in pancreatic tumours , 2017, EJNMMI Research.
[156] K. Ahn,et al. DCE and DSC MR perfusion imaging in the differentiation of recurrent tumour from treatment-related changes in patients with glioma. , 2014, Clinical radiology.
[157] Boris Sepesi,et al. Development and Validation of a Predictive Radiomics Model for Clinical Outcomes in Stage I Non-small Cell Lung Cancer. , 2017, International journal of radiation oncology, biology, physics.
[158] Ron Kikinis,et al. Volumetric CT-based segmentation of NSCLC using 3D-Slicer , 2013, Scientific Reports.
[159] A. Markoe,et al. Volumetric spectroscopic imaging of glioblastoma multiforme radiation treatment volumes. , 2014, International journal of radiation oncology, biology, physics.
[160] Sandra Nuyts,et al. Detection of head and neck squamous cell carcinoma with diffusion weighted MRI after (chemo)radiotherapy: correlation between radiologic and histopathologic findings. , 2007, International journal of radiation oncology, biology, physics.
[161] P. Albertsson,et al. Positron emission tomography and computed tomographic imaging (PET/CT) for dose planning purposes of thoracic radiation with curative intent in lung cancer patients: A systematic review and meta-analysis. , 2017, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[162] Hugo J. W. L. Aerts,et al. Radiomic‐Based Pathological Response Prediction from Primary Tumors and Lymph Nodes in NSCLC , 2017, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.
[163] Michael Baumann,et al. Exploratory prospective trial of hypoxia-specific PET imaging during radiochemotherapy in patients with locally advanced head-and-neck cancer. , 2012, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[164] C. Ménard,et al. Tumor Hypoxia Predicts Biochemical Failure following Radiotherapy for Clinically Localized Prostate Cancer , 2012, Clinical Cancer Research.
[165] J. Kalpathy-Cramer,et al. Repeatability of Standardized and Normalized Relative CBV in Patients with Newly Diagnosed Glioblastoma , 2015, American Journal of Neuroradiology.
[166] T. Kron,et al. Prospective Study of Serial Imaging Comparing Fluorodeoxyglucose Positron Emission Tomography (PET) and Fluorothymidine PET During Radical Chemoradiation for Non-Small Cell Lung Cancer: Reduction of Detectable Proliferation Associated With Worse Survival. , 2017, International journal of radiation oncology, biology, physics.
[167] M. Mix,et al. Exploratory geographical analysis of hypoxic subvolumes using 18F-MISO-PET imaging in patients with head and neck cancer in the course of primary chemoradiotherapy. , 2013, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[168] F. O’Sullivan,et al. Regional Hypoxia in Glioblastoma Multiforme Quantified with [18F]Fluoromisonidazole Positron Emission Tomography before Radiotherapy: Correlation with Time to Progression and Survival , 2008, Clinical Cancer Research.
[169] K. Krohn,et al. Characterization of radiolabeled fluoromisonidazole as a probe for hypoxic cells. , 1987, Radiation research.
[170] Eduard Schreibmann,et al. Quantitative tumor segmentation for evaluation of extent of glioblastoma resection to facilitate multisite clinical trials. , 2014, Translational oncology.
[171] R. Timmerman,et al. Role of interim 18F-FDG-PET/CT for the early prediction of clinical outcomes of Non-Small Cell Lung Cancer (NSCLC) during radiotherapy or chemo-radiotherapy. A systematic review , 2017, European Journal of Nuclear Medicine and Molecular Imaging.
[172] Paul Kinahan,et al. Radiomics: Images Are More than Pictures, They Are Data , 2015, Radiology.
[173] Adelin Albert,et al. FDG PET/CT radiomics for predicting the outcome of locally advanced rectal cancer , 2017, European Journal of Nuclear Medicine and Molecular Imaging.
[174] D. Rubin,et al. Automated tracking of quantitative assessments of tumor burden in clinical trials. , 2014, Translational oncology.
[175] M. Brambilla,et al. FDG-PET/CT imaging for staging and target volume delineation in conformal radiotherapy of anal carcinoma , 2010, Radiation oncology.
[176] T. Johnson,et al. Dual-energy CT: general principles. , 2012, AJR. American journal of roentgenology.
[177] K. Brock,et al. Use of image registration and fusion algorithms and techniques in radiotherapy: Report of the AAPM Radiation Therapy Committee Task Group No. 132 , 2017, Medical physics.
[178] S. Choi,et al. Dynamic contrast-enhanced MR imaging in predicting progression of enhancing lesions persisting after standard treatment in glioblastoma patients: a prospective study , 2017, European Radiology.
[179] Catherine Coolens,et al. Feasibility of 4D perfusion CT imaging for the assessment of liver treatment response following SBRT and sorafenib , 2016, Advances in radiation oncology.
[180] V. Edeline,et al. Role of FDG-PET in the implementation of involved-node radiation therapy for Hodgkin lymphoma patients. , 2014, International journal of radiation oncology, biology, physics.
[181] J. Petersen,et al. Imaging hypoxia to improve radiotherapy outcome , 2012, Nature Reviews Clinical Oncology.
[182] K. Herholz,et al. Measurement of clinical and subclinical tumour response using [18F]-fluorodeoxyglucose and positron emission tomography: review and 1999 EORTC recommendations. European Organization for Research and Treatment of Cancer (EORTC) PET Study Group. , 1999, European journal of cancer.
[183] Paul Kinahan,et al. Multicenter clinical trials using 18 F-FDG PET to measure early response to oncologic therapy , 2016 .
[184] S. Ko,et al. Monitoring the effects of anti-angiogenesis on the radiation sensitivity of pancreatic cancer xenografts using dynamic contrast-enhanced computed tomography. , 2014, International journal of radiation oncology, biology, physics.
[185] Sean D. McGarry,et al. Magnetic Resonance Imaging-Based Radiomic Profiles Predict Patient Prognosis in Newly Diagnosed Glioblastoma Before Therapy , 2016, Tomography.
[186] C. McCulloch,et al. Locally recurrent prostate cancer after external beam radiation therapy: diagnostic performance of 1.5-T endorectal MR imaging and MR spectroscopic imaging for detection. , 2010, Radiology.
[187] Catherine Coolens,et al. Quantitative Imaging in Radiation Oncology: An Emerging Science and Clinical Service. , 2015, Seminars in radiation oncology.
[188] P. Stricker,et al. 68Ga‐PSMA has a high detection rate of prostate cancer recurrence outside the prostatic fossa in patients being considered for salvage radiation treatment , 2016, BJU international.
[189] N. Nickols,et al. The Utility of PET/CT in the Planning of External Radiation Therapy for Prostate Cancer , 2018, The Journal of Nuclear Medicine.
[190] M J Welch,et al. Evaluation of 64Cu-ATSM in vitro and in vivo in a hypoxic tumor model. , 1999, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[191] S. Sheikhbahaei,et al. Use of 18F-Fludeoxyglucose-Positron Emission Tomography/Computed Tomography for Patient Management and Outcome in Oropharyngeal Squamous Cell Carcinoma: A Review. , 2016, JAMA otolaryngology-- head & neck surgery.
[192] Michael A Jacobs,et al. Integrated radiomic framework for breast cancer and tumor biology using advanced machine learning and multiparametric MRI , 2017, npj Breast Cancer.
[193] M. Knopp,et al. Estimating kinetic parameters from dynamic contrast‐enhanced t1‐weighted MRI of a diffusable tracer: Standardized quantities and symbols , 1999, Journal of magnetic resonance imaging : JMRI.
[194] F. Verhaegen,et al. Dual-energy CT-based material extraction for tissue segmentation in Monte Carlo dose calculations , 2008, Physics in medicine and biology.
[195] 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.
[196] K. Peck,et al. A prospective trial of dynamic contrast-enhanced MRI perfusion and fluorine-18 FDG PET-CT in differentiating brain tumor progression from radiation injury after cranial irradiation. , 2016, Neuro-oncology.