Delta-radiomics features for the prediction of patient outcomes in non–small cell lung cancer

Early variation of FDG-PET radiomics features in NSCLC is related to overall survival - the “delta radiomics” concept

(2016) S. Carvalho et al.   RADIOTHERAPY AND ONCOLOGY

Radiomic phenotype features predict pathological response in non-small cell lung cancer

(2016) Thibaud P. Coroller et al.   RADIOTHERAPY AND ONCOLOGY

How to use CT texture analysis for prognostication of non-small cell lung cancer

(2016) Kenneth A. Miles   CANCER IMAGING

Impact of image preprocessing on the volume dependence and prognostic potential of radiomics features in non-small cell lung cancer

(2016) Xenia Fave et al.   Translational Cancer Research

Preliminary investigation into sources of uncertainty in quantitative imaging features

(2015) Xenia Fave et al.   COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

Lung Texture in Serial Thoracic Computed Tomography Scans: Correlation of Radiomics-based Features With Radiation Therapy Dose and Radiation Pneumonitis Development

(2015) Alexandra Cunliffe et al.   INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS

Measuring Computed Tomography Scanner Variability of Radiomics Features

(2015) Dennis Mackin et al.   INVESTIGATIVE RADIOLOGY

Fitting Linear Mixed-Effects Models Usinglme4

(2015) Douglas Bates et al.   Journal of Statistical Software

ibex: An open infrastructure software platform to facilitate collaborative work in radiomics

(2015) Lifei Zhang et al.   MEDICAL PHYSICS

CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma

(2015) Thibaud P. Coroller et al.   RADIOTHERAPY AND ONCOLOGY

Radiomic feature clusters and Prognostic Signatures specific for Lung and Head & Neck cancer

(2015) Chintan Parmar et al.   Scientific Reports

CT texture analysis in colorectal liver metastases: A better way than size and volume measurements to assess response to chemotherapy?

(2015) Sheng-Xiang Rao et al.   United European Gastroenterology Journal

False Discovery Rates in PET and CT Studies with Texture Features: A Systematic Review

(2015) Anastasia Chalkidou et al.   PLoS One

Response assessment to neoadjuvant therapy in soft tissue sarcomas: using CT texture analysis in comparison to tumor size, density, and perfusion

(2014) Fang Tian et al.   ABDOMINAL IMAGING

Prognostic Value and Reproducibility of Pretreatment CT Texture Features in Stage III Non-Small Cell Lung Cancer

(2014) David V. Fried et al.   INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS

Noninvasive Image Texture Analysis Differentiates K-ras Mutation from Pan-Wildtype NSCLC and Is Prognostic

(2014) Glen J. Weiss et al.   PLoS One

Reproducibility and Prognosis of Quantitative Features Extracted from CT Images

(2014) Yoganand Balagurunathan et al.   Translational Oncology

Tumor Heterogeneity and Permeability as Measured on the CT Component of PET/CT Predict Survival in Patients with Non-Small Cell Lung Cancer

(2013) T. Win et al.   CLINICAL CANCER RESEARCH

Radiomics: Extracting more information from medical images using advanced feature analysis

(2012) Philippe Lambin et al.   EUROPEAN JOURNAL OF CANCER

Radiomics: the process and the challenges

(2012) Virendra Kumar et al.   MAGNETIC RESONANCE IMAGING

Non-Small Cell Lung Cancer: Epidemiology, Risk Factors, Treatment, and Survivorship

(2012) Julian R. Molina et al.   MAYO CLINIC PROCEEDINGS

Non–Small Cell Lung Cancer: Identifying Prognostic Imaging Biomarkers by Leveraging Public Gene Expression Microarray Data—Methods and Preliminary Results

(2012) Olivier Gevaert et al.   RADIOLOGY

Using cross-validation to evaluate predictive accuracy of survival risk classifiers based on high-dimensional data

(2011) R. M. Simon et al.   BRIEFINGS IN BIOINFORMATICS

Landmark Analysis at the 25-Year Landmark Point

(2011) Urania Dafni  

Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival

(2011) Balaji Ganeshan et al.   EUROPEAN RADIOLOGY

Assessment of Response to Tyrosine Kinase Inhibitors in Metastatic Renal Cell Cancer: CT Texture as a Predictive Biomarker

(2011) Vicky Goh et al.   RADIOLOGY

Texture analysis of non-small cell lung cancer on unenhanced computed tomography: initial evidence for a relationship with tumour glucose metabolism and stage

(2011) Balaji Ganeshan et al.   CANCER IMAGING

New Response Evaluation Criteria in Solid Tumors (RECIST) Guidelines for Advanced Non–Small Cell Lung Cancer: Comparison With Original RECIST and Impact on Assessment of Tumor Response to Targeted Therapy

(2010) Mizuki Nishino et al.   AMERICAN JOURNAL OF ROENTGENOLOGY

Multilevel binomial logistic prediction model for malignant pulmonary nodules based on texture features of CT image

(2009) Huan Wang et al.   EUROPEAN JOURNAL OF RADIOLOGY

Estimation of prediction error by using K-fold cross-validation

(2009) Tadayoshi Fushiki   STATISTICS AND COMPUTING

New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1)

(2008) E.A. Eisenhauer et al.   EUROPEAN JOURNAL OF CANCER