Incorporation of pre‐therapy 18F‐FDG uptake data with CT texture features into a radiomics model for radiation pneumonitis diagnosis
暂无分享,去创建一个
Thomas Guerrero | Samuel G. Armato | Richard Castillo | S. Armato | R. Castillo | T. Guerrero | A. Cunliffe | N. Pham | H. Al-Hallaq | Gregory J Anthony | Ngoc Pham | Gregory J. Anthony | Alexandra Cunliffe | Hania A. Al‐Hallaq
[1] A. Giobbie-Hurder,et al. Incidence of Programmed Cell Death 1 Inhibitor-Related Pneumonitis in Patients With Advanced Cancer: A Systematic Review and Meta-analysis. , 2016, JAMA oncology.
[2] 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.
[3] Samuel G Armato,et al. Lung texture in serial thoracic CT scans: assessment of change introduced by image registration. , 2012, Medical physics.
[4] R. Castillo,et al. Pre-Radiation Therapy Fluorine 18 Fluorodeoxyglucose PET Helps Identify Patients with Esophageal Cancer at High Risk for Radiation Pneumonitis. , 2015, Radiology.
[5] H. Vesselle,et al. Correlation of Functional Lung Heterogeneity and Dosimetry to Radiation Pneumonitis using Perfusion SPECT/CT and FDG PET/CT Imaging. , 2018, International journal of radiation oncology, biology, physics.
[6] D. Hansell,et al. Obstructive lung diseases: texture classification for differentiation at CT. , 2003, Radiology.
[7] R. Abratt,et al. Lung toxicity following chest irradiation in patients with lung cancer. , 2002, Lung cancer.
[8] M. Martel,et al. Radiation dose-volume effects in the lung. , 2010, International journal of radiation oncology, biology, physics.
[9] S. McDonald,et al. A perpetual cascade of cytokines postirradiation leads to pulmonary fibrosis. , 1995, International journal of radiation oncology, biology, physics.
[10] Lubomir M. Hadjiiski,et al. Classifier performance prediction for computer-aided diagnosis using a limited dataset. , 2008, Medical physics.
[11] N. Saijo,et al. Radiation pneumonitis in lung cancer patients: a retrospective study of risk factors and the long-term prognosis. , 2001, International journal of radiation oncology, biology, physics.
[12] Zixiang Xiong,et al. Optimal number of features as a function of sample size for various classification rules , 2005, Bioinform..
[13] Drew A. Torigian,et al. A prospective study of the feasibility of FDG-PET/CT imaging to quantify radiation-induced lung inflammation in locally advanced non-small cell lung cancer patients receiving proton or photon radiotherapy , 2018, European Journal of Nuclear Medicine and Molecular Imaging.
[14] R. Castillo,et al. Pre-radiotherapy FDG PET predicts radiation pneumonitis in lung cancer , 2014, Radiation oncology.
[15] Issam El-Naqa,et al. Exploring feature-based approaches in PET images for predicting cancer treatment outcomes , 2009, Pattern Recognit..
[16] C. Simone,et al. First Clinical Report of Proton Beam Therapy for Postoperative Radiotherapy for Non–Small‐Cell Lung Cancer , 2017, Clinical lung cancer.
[17] J. Deasy,et al. Investigating Alpha-2-Macroglobulin and Its Dosimetric Interactions for Predicting Radiation Pneumonitis , 2011 .
[18] A. Berman,et al. Radiation Pneumonitis: Old Problem, New Tricks , 2018, Cancers.
[19] Hugo J. W. L. Aerts,et al. Relationship between the Temporal Changes in Positron-Emission-Tomography-Imaging-Based Textural Features and Pathologic Response and Survival in Esophageal Cancer Patients , 2016, Front. Oncol..
[20] Jeffrey D Bradley,et al. Predicting radiation pneumonitis after chemoradiation therapy for lung cancer: an international individual patient data meta-analysis. , 2013, International journal of radiation oncology, biology, physics.
[21] J. Deasy,et al. Quantitative Mass Spectroscopy and the Identification of Alpha2macroglobulin as a Potential Biomarker for Radiation Pneumonitis , 2010 .
[22] Joseph O Deasy,et al. A bioinformatics approach for biomarker identification in radiation-induced lung inflammation from limited proteomics data. , 2011, Journal of proteome research.
[23] Michael Lock,et al. Prediction of radiation pneumonitis by dose - volume histogram parameters in lung cancer--a systematic review. , 2004, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[24] E. Yorke,et al. Simple Factors Associated With Radiation-Induced Lung Toxicity After Stereotactic Body Radiation Therapy of the Thorax: A Pooled Analysis of 88 Studies. , 2016, International journal of radiation oncology, biology, physics.
[25] Paul Kinahan,et al. Radiomics: Images Are More than Pictures, They Are Data , 2015, Radiology.
[26] S. Armato,et al. Lung texture in serial thoracic computed tomography scans: correlation of radiomics-based features with radiation therapy dose and radiation pneumonitis development. , 2015, International journal of radiation oncology, biology, physics.
[27] J. Bradley,et al. Combined PET/CT image characteristics for radiotherapy tumor response in lung cancer. , 2012, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[28] Aaron D Ward,et al. Early prediction of tumor recurrence based on CT texture changes after stereotactic ablative radiotherapy (SABR) for lung cancer. , 2014, Medical physics.