Prognostic value of 18F-FDG PET/CT-based radiomics combining dosiomics and dose volume histogram for head and neck cancer
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Lijun Lu | Wenbing Lv | Xianling Dong | Aihui Wang | Xiaolei Zhang | Shuyan Li | Jinghua Liu | Zhongxiao Wang | Zhendong Cao | Bingzhen Wang | Xiaotian Wu
[1] Yun Qin,et al. Review of Radiomics- and Dosiomics-based Predicting Models for Rectal Cancer , 2022, Frontiers in Oncology.
[2] R. Mohan,et al. On the interplay between dosiomics and genomics in radiation-induced lymphopenia of lung cancer patients. , 2021, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[3] F. Xue,et al. A wavelet features derived radiomics nomogram for prediction of malignant and benign early-stage lung nodules , 2021, Scientific Reports.
[4] R. Gatta,et al. Role of 18F-FDG PET/CT Radiomics Features in the Differential Diagnosis of Solitary Pulmonary Nodules: Diagnostic Accuracy and Comparison between Two Different PET/CT Scanners , 2021, Journal of clinical medicine.
[5] J. Dai,et al. Dosiomics-based prediction of radiation-induced hypothyroidism in nasopharyngeal carcinoma patients. , 2021, 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.
[6] P. Lambin,et al. A Prospectively Validated Prognostic Model for Patients with Locally Advanced Squamous Cell Carcinoma of the Head and Neck Based on Radiomics of Computed Tomography Images , 2021, Cancers.
[7] D. Kondziolka,et al. Hippocampal sparing in patients receiving radiosurgery for ≥ 25 brain metastases. , 2021, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[8] Naveed Iqbal,et al. Gray level co-occurrence matrix (GLCM) texture based crop classification using low altitude remote sensing platforms , 2021, PeerJ Comput. Sci..
[9] S. Halligan,et al. Why did European Radiology reject my radiomic biomarker paper? How to correctly evaluate imaging biomarkers in a clinical setting , 2021, European Radiology.
[10] Svetlana K. Eden,et al. Nonparametric estimation of Spearman's rank correlation with bivariate survival data , 2021, Biometrics.
[11] A. Alfouzan. Radiation therapy in head and neck cancer , 2021, Saudi medical journal.
[12] F. Valvo,et al. Radiomics and Dosiomics for Predicting Local Control after Carbon-Ion Radiotherapy in Skull-Base Chordoma , 2021, Cancers.
[13] Hongzan Sun,et al. Prediction of lymphovascular space invasion using a combination of tenascin-C, cox-2, and PET/CT radiomics in patients with early-stage cervical squamous cell carcinoma , 2020, BMC Cancer.
[14] Nikos Paragios,et al. Standardization of brain MR images across machines and protocols: bridging the gap for MRI-based radiomics , 2020, Scientific Reports.
[15] Zheran Liu,et al. Radiomics-based prediction of survival in patients with head and neck squamous cell carcinoma based on pre- and post-treatment 18F-PET/CT , 2020, Aging.
[16] Liyuan Chen,et al. A multi-objective radiomics model for the prediction of locoregional recurrence in head and neck squamous cell cancers. , 2020, Medical physics.
[17] Junghoon Lee,et al. Multi-view radiomics and dosiomics analysis with machine learning for predicting acute-phase weight loss in lung cancer patients treated with radiotherapy , 2020, Physics in medicine and biology.
[18] Yongbao Li,et al. Dosiomics improves prediction of locoregional recurrence for intensity modulated radiotherapy treated head and neck cancer cases. , 2020, Oral oncology.
[19] Jianhua Ma,et al. Multi-Level Multi-Modality Fusion Radiomics: Application to PET and CT Imaging for Prognostication of Head and Neck Cancer , 2019, IEEE Journal of Biomedical and Health Informatics.
[20] Guangjun Li,et al. A multidimensional nomogram combining overall stage, dose volume histogram parameters and radiomics to predict progression-free survival in patients with locoregionally advanced nasopharyngeal carcinoma. , 2019, Oral oncology.
[21] Jianhua Ma,et al. Subregional Radiomics Analysis of PET/CT Imaging with Intratumor Partitioning: Application to Prognosis for Nasopharyngeal Carcinoma , 2019, Molecular Imaging and Biology.
[22] Y. Choi,et al. Spearman’s hypothesis tested comparing Korean young adults with various other groups of young adults on the items of the Advanced Progressive Matrices - Erratum , 2019, Journal of Biosocial Science.
[23] R. Orecchia,et al. Modern radiotherapy for head and neck cancer. , 2019, Seminars in oncology.
[24] Y. Choi,et al. Spearman’s hypothesis tested comparing Korean young adults with various other groups of young adults on the items of the Advanced Progressive Matrices , 2019, Journal of Biosocial Science.
[25] D. Ferrari,et al. Chemotherapy and immunotherapy for recurrent and metastatic head and neck cancer: a systematic review , 2018, Medical Oncology.
[26] Andriy Fedorov,et al. Computational Radiomics System to Decode the Radiographic Phenotype. , 2017, Cancer research.
[27] M. Mareel,et al. Distant metastases in head and neck cancer , 2017, Head & neck.
[28] Léo Jean Perrin,et al. Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer , 2017, Scientific Reports.
[29] Issam El-Naqa,et al. Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer , 2017, Scientific Reports.
[30] M. Wagenmann,et al. Radiomics in Head and Neck Cancer: Extracting Valuable Information from Data beyond Recognition , 2017, ORL.
[31] M. Götz,et al. Radiomic Profiling of Glioblastoma: Identifying an Imaging Predictor of Patient Survival with Improved Performance over Established Clinical and Radiologic Risk Models. , 2016, Radiology.
[32] Paul Kinahan,et al. Radiomics: Images Are More than Pictures, They Are Data , 2015, Radiology.
[33] Philippe Lambin,et al. Is there a causal relationship between genetic changes and radiomics-based image features? An in vivo preclinical experiment with doxycycline inducible GADD34 tumor cells. , 2015, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[34] Benjamin Haibe-Kains,et al. Radiomic feature clusters and Prognostic Signatures specific for Lung and Head & Neck cancer , 2015, Scientific Reports.
[35] 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.
[36] P. Lambin,et al. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach , 2014, Nature Communications.
[37] Patrick Granton,et al. Radiomics: extracting more information from medical images using advanced feature analysis. , 2012, European journal of cancer.
[38] J. Neely,et al. A practical guide to understanding Kaplan-Meier curves , 2010, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.
[39] H. Brenner,et al. Changes in survival in head and neck cancers in the late 20th and early 21st century: a period analysis. , 2010, The oncologist.
[40] G. Raj,et al. How to build and interpret a nomogram for cancer prognosis. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[41] H. Kato,et al. A randomized trial of adjuvant chemotherapy with uracil-tegafur for adenocarcinoma of the lung. , 2004, The New England journal of medicine.
[42] J. Ridge. Squamous cancer of the head and neck: surgical treatment of local and regional recurrence. , 1993, Seminars in oncology.
[43] William G. Wee,et al. Neighboring gray level dependence matrix for texture classification , 1982, Comput. Graph. Image Process..
[44] Mary M. Galloway,et al. Texture analysis using gray level run lengths , 1974 .
[45] Bernard Fertil,et al. Texture indexes and gray level size zone matrix. Application to cell nuclei classification , 2009 .
[46] Hilde van der Togt,et al. Publisher's Note , 2003, J. Netw. Comput. Appl..
[47] S. Taylor. Head and neck cancer. , 1991, Cancer chemotherapy and biological response modifiers.
[48] Robert King,et al. Textural features corresponding to textural properties , 1989, IEEE Trans. Syst. Man Cybern..