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

Radiomics provides a comprehensive quantification of tumor phenotypes by extracting and mining large number of quantitative image features. To reduce the redundancy and compare the prognostic characteristics of radiomic features across cancer types, we investigated cancer-specific radiomic feature clusters in four independent Lung and Head & Neck (H&N) cancer cohorts (in total 878 patients). Radiomic features were extracted from the pre-treatment computed tomography (CT) images. Consensus clustering resulted in eleven and thirteen stable radiomic feature clusters for Lung and H&N cancer, respectively. These clusters were validated in independent external validation cohorts using rand statistic (Lung RS = 0.92, p < 0.001, H&N RS = 0.92, p < 0.001). Our analysis indicated both common as well as cancer-specific clustering and clinical associations of radiomic features. Strongest associations with clinical parameters: Prognosis Lung CI = 0.60 ± 0.01, Prognosis H&N CI = 0.68 ± 0.01; Lung histology AUC = 0.56 ± 0.03, Lung stage AUC = 0.61 ± 0.01, H&N HPV AUC = 0.58 ± 0.03, H&N stage AUC = 0.77 ± 0.02. Full utilization of these cancer-specific characteristics of image features may further improve radiomic biomarkers, providing a non-invasive way of quantifying and monitoring tumor phenotypic characteristics in clinical practice.

• Publication year

  2015

• Venue

  Scientific Reports

• Publication date

  2015-06-05

• Fields of study

  Medicine

• Identifiers
  DOI 10.1038/srep11044PMID 26251068PMCID 4937496
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Addition of MR imaging features and genetic biomarkers strengthens glioblastoma survival prediction in TCGA patients.

  2015cited by this paper
• Reproducibility and Prognosis of Quantitative Features Extracted from CT Images.

  2014cited by this paper
• Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

  2014cited by this paper
• Corrigendum: Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

  2014cited by this paper
• Non-small cell lung cancer: histopathologic correlates for texture parameters at CT.

  2013cited by this paper
• Predicting outcomes in radiation oncology—multifactorial decision support systems

  2013cited by this paper
• Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival

  2012cited by this paper
• Radiomics: extracting more information from medical images using advanced feature analysis.

  2012cited by this paper
• Combined PET/CT image characteristics for radiotherapy tumor response in lung cancer.

  2012cited by this paper
• Promise and pitfalls of quantitative imaging in oncology clinical trials.

  2012cited by this paper
• Radiomics: the process and the challenges.

  2012cited by this paper
• A collaborative enterprise for multi-stakeholder participation in the advancement of quantitative imaging.

  2011cited by this paper
• Intratumor Heterogeneity Characterized by Textural Features on Baseline 18F-FDG PET Images Predicts Response to Concomitant Radiochemotherapy in Esophageal Cancer

  2011cited by this paper
• Radiogenomic Mapping of Edema/Cellular Invasion MRI-Phenotypes in Glioblastoma Multiforme

  2011cited by this paper
• pROC: an open-source package for R and S+ to analyze and compare ROC curves

  2011cited by this paper
• Intra-tumor heterogeneity on baseline 18F-FDG PET images characterized by textural features predicts response to concomitant radio-chemotherapy in esophageal cancer

  2011cited by this paper
• Quantitative imaging test approval and biomarker qualification: interrelated but distinct activities.

  2011cited by this paper
• Early changes in tumor size in patients treated for advanced stage nonsmall cell lung cancer do not correlate with survival

  2010cited by this paper
• Texture analysis of non-small cell lung cancer on unenhanced computed tomography: initial evidence for a relationship with tumour glucose metabolism and stage

  2010cited by this paper
• ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking

  2010cited by this paper
• The VGAM Package for Categorical Data Analysis

  2010cited by this paper
• A Pilot Study of Volume Measurement as a Method of Tumor Response Evaluation to Aid Biomarker Development

  2010cited by this paper
• Exploring feature-based approaches in PET images for predicting cancer treatment outcomes

  2009cited by this paper
• Early changes in tumor size in patients treated for advanced stage nonsmall cell lung cancer do not correlate with survival

  2009cited by this paper
• Decoding global gene expression programs in liver cancer by noninvasive imaging

  2007cited by this paper
• Genomics and proteomics: emerging technologies in clinical cancer research.

  2007cited by this paper
• Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis

  2003cited by this paper
• Consensus Clustering: A Resampling-Based Method for Class Discovery and Visualization of Gene Expression Microarray Data

  2003cited by this paper
• CERR: a computational environment for radiotherapy research.

  2003cited by this paper
• A resampling-based method for class discovery and visualization of gene expression microarray data

  2003cited by this paper
• A Simple Generalisation of the Area Under the ROC Curve for Multiple Class Classification Problems

  2001cited by this paper
• Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis

  2001cited by this paper
• Texture analysis using gray level run lengths

  1974cited by this paper
• Textural Features for Image Classification

  1973cited by this paper
• Bioinformatics Applications Note Gene Expression Survcomp: an R/bioconductor Package for Performance Assessment and Comparison of Survival Models

  year unknowncited by this paper

• Characterization of Intratumoral Heterogeneity via MRI‐Based Radiomic Habitats in Osteosarcoma

  2026cites this paper
• Diagnostic Accuracy of Artificial Intelligence Models for Differentiation of Squamous Cell Carcinoma and Adenocarcinoma of Lung—A Systematic Review

  2026cites this paper
• Impact of harmonization on predicting complications in head and neck cancer after radiotherapy using MRI radiomics and machine learning techniques

  2025cites this paper
• Prognostic power of radiomics in head and neck cancers: Insights from a meta-analysis

  2025cites this paper
• Survival prediction using CT-based radiomic features in patients of pancreatic cancer treated with chemotherapy followed by SBRT.

  2025cites this paper
• Development of a radiomics and clinical feature-based nomogram for preoperative prediction of pathological grade in bladder cancer

  2025cites this paper
• Radiomic Cardiac MRI Signatures for Predicting Ventricular Arrhythmias in Patients With Nonischemic Dilated Cardiomyopathy

  2025cites this paper
• Unsupervised Clustering Successfully Predicts Prognosis in NSCLC Brain Metastasis Cohorts

  2025cites this paper
• Predictors of Radiation Resistance and Novel Radiation Sensitizers in Head and Neck Cancers: Advancing Radiotherapy Efficacy.

  2025cites this paper
• Prognostic modeling in head and neck cancer: deep learning or handcrafted radiomics?

  2025cites this paper
• Artificial intelligence-powered oocyte evaluation: Correlating cytoplasmic features with blastocyst development.

  2025cites this paper
• Improved Cancer Detection method using AI

  2025cites this paper
• Multimodal Positron Emission Tomography/Computed Tomography Radiomics Combined with a Clinical Model for Preoperative Prediction of Invasive Pulmonary Adenocarcinoma in Ground-Glass Nodules.

  2025cites this paper
• CT-based deep learning radiomics analysis for preoperative Lauren classification in gastric cancer and explore the tumor microenvironment

  2025cites this paper
• Integrative machine learning analysis of radiomics for the non-invasive prediction of non-small cell lung cancer subtypes

  2025cites this paper
• Performance of MRI-based radiomics for prediction of residual disease status in patients with nasopharyngeal carcinoma after radical radiotherapy

  2025cites this paper
• Cardiovascular magnetic resonance radiologic-pathologic correlation in radiomic analysis of myocardium in non-ischemic dilated cardiomyopathy

  2025cites this paper
• Machine Learning and Deep Learning Hybrid Approach Based on Muscle Imaging Features for Diagnosis of Esophageal Cancer

  2025cites this paper
• Quantitative Imaging Biomarkers in Lung Cancer: Current Trends and Future Directions.

  2025cites this paper
• Predicting chemotherapy response in pediatric lymphoma using pre-treatment contrast-enhanced CT radiomics: A hypothesis-generating study.

  2025cites this paper
• The potential of radiomics features in the detection of hepatocellular carcinoma (HCC) in 2D liver MRI images by using machine learning methods

  2025cites this paper
• Glioma Multimodal MRI Analysis System for Tumor Layered Diagnosis via Multi-task Semi-supervised Learning

  2025cites this paper
• Relating Macroscopic PET Radiomics Features to Microscopic Tumor Phenotypes Using a Stochastic Mathematical Model of Cellular Metabolism and Proliferation

  2024cites this paper
• Correction: Deep learning based automated epidermal growth factor receptor and anaplastic lymphoma kinase status prediction of brain metastasis in non-small cell lung cancer

  2024cites this paper
• Disparities in the diagnostic efficacy of radiomics models in predicting various degrees of cognitive impairment in patients with cerebral small vessel disease

  2024cites this paper
• Deep-Learning-Based Predictive Imaging Biomarker Model for EGFR Mutation Status in Non-Small Cell Lung Cancer from CT Imaging

  2024cites this paper
• Research on multi-model imaging machine learning for distinguishing early hepatocellular carcinoma

  2024cites this paper
• Uncovering the Diagnostic Power of Radiomic Feature Significance in Automated Lung Cancer Detection: An Integrative Analysis of Texture, Shape, and Intensity Contributions

  2024cites this paper
• Enhanced Efficiency in Lung Cancer Classification via Deep Learning Ensembles

  2024cites this paper
• A Hybrid CNN-Transformer Model for Predicting N Staging and Survival in Non-Small Cell Lung Cancer Patients Based on CT-Scan

  2024influential citation
• Segmentation of Variants of Nuclei on Whole Slide Images by Using Radiomic Features

  2024cites this paper
• Performance of Handcrafted Radiomics versus Deep Learning for Prognosticating Head and Neck Squamous Cell Carcinoma: A Systematic Review with Critical Appraisal of Quantitative Imaging Studies

  2024cites this paper
• Design of MATLAB-based Radiomics Classifier Training Simulator Powered by Pyradiomics

  2024cites this paper
• Machine Learning and Computed Tomography Radiomics to Predict Disease Progression to Upfront Pembrolizumab Monotherapy in Advanced Non-Small-Cell Lung Cancer: A Pilot Study

  2024cites this paper
• Pretreatment Spatially Aware Magnetic Resonance Imaging Radiomics Can Predict Distant Brain Metastases (DBMs) After Stereotactic Radiosurgery/Radiation Therapy (SRS/SRT)

  2024cites this paper
• Critères d’évaluation de la TEP au 18F-FDG au cours de l’immunothérapie

  2024cites this paper
• Development of a CT-Based radiomics-clinical model to diagnose acute pancreatitis on nonobvious findings on CT in children with pancreaticobiliary maljunction.

  2024cites this paper
• Decoding Radiomics: A Step-by-Step Guide to Machine Learning Workflow in Hand-Crafted and Deep Learning Radiomics Studies

  2024cites this paper
• The impact of radiomics libraries and gray level discretization on the discovery of immunotherapy biomarkers in NSCLC patients.

  2024cites this paper
• Value of radiomics-based automatic grading of muscle edema in polymyositis/dermatomyositis based on MRI fat-suppressed T2-weighted images

  2024cites this paper
• Significance of MRI-based radiomics in predicting pathological complete response to neoadjuvant chemoradiotherapy of locally advanced rectal cancer: A narrative review.

  2024cites this paper
• KEMORADYOTERAPİ İLE TEDAVİ EDİLEN BAŞ VE BOYUN SKUAMÖZ HÜCRELİ KANSERİNDE BİLGİSAYARLI TOMOGRAFİ HİSTOGRAM ANALİZİNİN SAĞKALIM SÜRESİ VE LOKAL KONTROL SÜRESİ İLE İLİŞKİSİNİN ARAŞTIRILMASI

  2023cites this paper
• PET/CT May Assist in Avoiding Pointless Thyroidectomy in Indeterminate Thyroid Nodules: A Narrative Review

  2023cites this paper
• Multimodality radiomics analysis based on [^18F]FDG PET/CT imaging and multisequence MRI: application to nasopharyngeal carcinoma prognosis

  2023cites this paper
• Radiomics Analysis of Gray-Scale Ultrasonographic Images of Papillary Thyroid Carcinoma > 1 cm: Potential Biomarker for the Prediction of Lymph Node Metastasis

  2023cites this paper
• T1 Map-Based Radiomics for Prediction of Left Ventricular Reverse Remodeling in Patients With Nonischemic Dilated Cardiomyopathy

  2023cites this paper
• Predictive value of clinical and radiomic features for radiation therapy response in patients with lymph node‐positive head and neck cancer

  2023cites this paper
• Machine learning predictive performance evaluation of conventional and fuzzy radiomics in clinical cancer imaging cohorts

  2023cites this paper
• A machine learning approach for preoperatively assessing pulmonary function with computed tomography in patients with lung cancer

  2023cites this paper
• Computed tomography-based radiomics machine learning models for prediction of histological invasiveness with sub-centimeter subsolid pulmonary nodules: a retrospective study

  2023cites this paper
• An Individualized Prognostic Model in Patients with Locoregionally Advanced Nasopharyngeal Carcinoma Based on Serum Metabolomic Profiling

  2023cites this paper
• BAŞ VE BOYUN SKUAMÖZ HÜCRELİ KANSERİNDE TÜMÖR VE LENFADENOPATİ BT HİSTOGRAM PARAMETRELERİ İLE TÜMÖR EVRESİ VE HPV DURUMU ARASINDAKİ İLİŞKİ

  2023cites this paper
• A multi-objective based radiomics feature selection method for response prediction following radiotherapy

  2023cites this paper
• Medical imaging and multimodal artificial intelligence models for streamlining and enhancing cancer care: opportunities and challenges

  2023cites this paper
• A Radiomics Approach to Identify Immunologically Active Tumor in Patients with Head and Neck Squamous Cell Carcinomas

  2023cites this paper
• Imaging Analytics using Artificial Intelligence in Oncology: A Comprehensive Review.

  2023cites this paper
• Identifying radiomics signatures in body composition imaging for the prediction of outcome following pancreatic cancer resection

  2023cites this paper
• Prognostic value of 18F-FDG PET/CT-based radiomics combining dosiomics and dose volume histogram for head and neck cancer

  2023cites this paper
• Immunotherapy Efficacy Prediction for Non-Small Cell Lung Cancer Using Multi-View Adaptive Weighted Graph Convolutional Networks

  2023cites this paper
• Advanced Techniques in Head and Neck Cancer Imaging: Guide to Precision Cancer Management.

  2023cites this paper
• Radiomics and Artificial Intelligence for Precision Medicine in Lung Cancer Treatment.

  2023cites this paper
• Radiomics Based Diagnosis with Medical Imaging: A Comprehensive Study

  2023cites this paper
• Multi-centre radiomics for prediction of recurrence following radical radiotherapy for head and neck cancers: Consequences of feature selection, machine learning classifiers and batch-effect harmonization

  2023cites this paper
• Magnetic Resonance Imaging Patterns of Intracranial Meningiomas in Erbil City

  2023cites this paper
• Spatially-aware clustering improves AJCC-8 risk stratification performance in oropharyngeal carcinomas.

  2023cites this paper
• Artificial intelligence-driven radiomics study in cancer: the role of feature engineering and modeling

  2023cites this paper
• Application of radiomics in diagnosis and treatment of lung cancer

  2023cites this paper
• Spatial assessments in texture analysis: what the radiologist needs to know

  2023cites this paper
• Deep learning based automated epidermal growth factor receptor and anaplastic lymphoma kinase status prediction of brain metastasis in non-small cell lung cancer

  2023cites this paper
• Preoperative prediction of pancreatic neuroendocrine tumor grade based on 68Ga-DOTATATE PET/CT

  2023influential citation
• Deep learning attention-guided radiomics for COVID-19 chest radiograph classification

  2022cites this paper
• Transferability of radiomic signatures from experimental to human interstitial lung disease

  2022cites this paper
• DECT-CLUST: Dual-Energy CT Image Clustering and Application to Head and Neck Squamous Cell Carcinoma Segmentation

  2022cites this paper
• Development of a novel nomogram-based model incorporating 3D radiomic signatures and lung CT radiological features for differentiating invasive adenocarcinoma from adenocarcinoma in situ and minimally invasive adenocarcinoma

  2022cites this paper
• Machine Learning Based Approach for Automated Cervical Dysplasia Detection Using Multi-Resolution Transform Domain Features

  2022cites this paper
• Predicting the radiotherapeutic treatment response of non-small cell lung cancer

  2022cites this paper
• Radiomics Signature to Predict Prognosis in Early-Stage Lung Adenocarcinoma (≤3 cm) Patients with No Lymph Node Metastasis

  2022cites this paper
• Investigation of the added value of CT-based radiomics in predicting the development of brain metastases in patients with radically treated stage III NSCLC

  2022cites this paper
• Prediction of early recurrence of HCC after hepatectomy by contrast-enhanced ultrasound-based deep learning radiomics

  2022cites this paper
• Nasopharyngeal Carcinoma Radiomic Evaluation with Serial PET/CT: Exploring Features Predictive of Survival in Patients with Long-Term Follow-Up

  2022cites this paper
• Combined whole-lesion radiomic and iodine analysis for differentiation of pulmonary tumors

  2022cites this paper
• A triple-classification for the evaluation of lung nodules manifesting as pure ground-glass sign: a CT-based radiomic analysis

  2022cites this paper
• Using Machine Learning for Precision Prognostics in Head and Neck Cancer Images

  2022cites this paper
• Development and Validation of a DeepSurv Nomogram to Predict Survival Outcomes and Guide Personalized Adjuvant Chemotherapy in Non-Small Cell Lung Cancer

  2022cites this paper
• Radiomics in medical imaging: pitfalls and challenges in clinical management

  2022cites this paper
• Radiomics/Radiogenomics in Lung Cancer: Basic Principles and Initial Clinical Results

  2022cites this paper
• Classification of anatomic structures in head and neck by CT-based radiomics

  2022cites this paper
• A novel methodology for head and neck carcinoma treatment stage detection by means of model checking

  2022cites this paper
• Noninvasive Method for Predicting the Expression of Ki67 and Prognosis in Non-Small-Cell Lung Cancer Patients: Radiomics

  2022cites this paper
• Radiomic Analysis of Pulmonary Nodules for Distinguishing Malignancy From Benignancy: The Value of Using Iodine Maps From Dual-Energy Computed Tomography

  2022cites this paper
• A CT-Based Radiomics Nomogram in Predicting the Postoperative Prognosis of Colorectal Cancer: A Two-center Study.

  2022cites this paper
• Radiomics and deep learning methods for the prediction of 2-year overall survival in LUNG1 dataset

  2022cites this paper
• Deep Learning with Multimodal Integration for Predicting Recurrence in Patients with Non-Small Cell Lung Cancer

  2022cites this paper
• Towards reliable head and neck cancers locoregional recurrence prediction using delta‐radiomics and learning with rejection option

  2022influential citation
• A review on advances in 18F-FDG PET/CT radiomics standardisation and application in lung disease management

  2022cites this paper
• A Handcrafted Radiomics-Based Model for the Diagnosis of Usual Interstitial Pneumonia in Patients with Idiopathic Pulmonary Fibrosis

  2022cites this paper
• Combined model of radiomics, clinical, and imaging features for differentiating focal pneumonia-like lung cancer from pulmonary inflammatory lesions: an exploratory study

  2022cites this paper
• Conventional Machine Learning Methods

  2022cites this paper
• Cleaning radiotherapy contours for radiomics studies, is it worth it? A head and neck cancer study

  2022cites this paper
• Classification of Benign and Malignant Features of Glioma and Prediction of Early Metastasis and Recurrence Based on Enhanced MRI Imaging

  2022cites this paper