PET/CT Radiomics in Lung Cancer: An Overview

Radiomics in Pulmonary Lesion Imaging

(2019) Cameron Hassani et al.   AMERICAN JOURNAL OF ROENTGENOLOGY

Texture Analysis on [18F]FDG PET/CT in Non-Small-Cell Lung Cancer: Correlations Between PET Features, CT Features, and Histological Types

(2019) Francesco Bianconi et al.   MOLECULAR IMAGING AND BIOLOGY

Comparison of prediction models with radiological semantic features and radiomics in lung cancer diagnosis of the pulmonary nodules: a case-control study

(2019) Wei Wu et al.   EUROPEAN RADIOLOGY

Early survival prediction in non-small cell lung cancer from PET/CT images using an intra-tumor partitioning method

(2019) Mehdi Astaraki et al.   Physica Medica-European Journal of Medical Physics

Classification of benign and malignant lung nodules from CT images based on hybrid features

(2019) Guobin Zhang et al.   PHYSICS IN MEDICINE AND BIOLOGY

Classification of Pulmonary CT Images by Using Hybrid 3D-Deep Convolutional Neural Network Architecture

(2019) Huseyin Polat et al.   Applied Sciences-Basel

The Challenges of Diagnostic Imaging in the Era of Big Data

(2019) Marco Aiello et al.   Journal of Clinical Medicine

Quantitative Imaging features Improve Discrimination of Malignancy in Pulmonary nodules

(2019) Yoganand Balagurunathan et al.   Scientific Reports

Comparing the diagnostic value of 18F-FDG-PET/CT versus CT for differentiating benign and malignant solitary pulmonary nodules: a meta-analysis

(2019) Yuzhu Jia et al.   Journal of Thoracic Disease

A review of feature selection methods in medical applications

(2019) Beatriz Remeseiro et al.   COMPUTERS IN BIOLOGY AND MEDICINE

The dark side of radiomics: on the paramount importance of publishing negative results

(2019) Irene Buvat et al.   JOURNAL OF NUCLEAR MEDICINE

Exploring Tumor Heterogeneity Using PET Imaging: The Big Picture

(2019) Clément Bailly et al.   Cancers

Heterogeneity in tumours: Validating the use of radiomic features on 18F-FDG PET/CT scans of lung cancer patients as a prognostic tool

(2019) Marie Manon Krebs Krarup et al.   RADIOTHERAPY AND ONCOLOGY

A review on radiomics and the future of theranostics for patient selection in precision medicine

(2018) Simon A Keek et al.   BRITISH JOURNAL OF RADIOLOGY

Computer-assisted subtyping and prognosis for non-small cell lung cancer patients with unresectable tumor

(2018) Maliazurina Saad et al.   COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

Ability of FDG PET and CT radiomics features to differentiate between primary and metastatic lung lesions

(2018) Margarita Kirienko et al.   EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING

Repeatability and reproducibility of radiomic features: A systematic review

(2018) Alberto Traverso et al.   INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS

Radiomics and radiogenomics in lung cancer: A review for the clinician

(2018) Rajat Thawani et al.   LUNG CANCER

Radiomics analysis at PET/CT contributes to prognosis of recurrence and survival in lung cancer treated with stereotactic body radiotherapy

(2018) Anastasia Oikonomou et al.   Scientific Reports

The role of deep learning and radiomic feature extraction in cancer-specific predictive modelling: a review

(2018) Alanna Vial et al.   Translational Cancer Research

18F-FDG PET/CT diagnostic performance in solitary and multiple pulmonary nodules detected in patients with previous cancer history: reports of 182 nodules

(2018) Silvia Taralli et al.   EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING

Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study

(2018) Ahmed Hosny et al.   PLOS MEDICINE

Tumour functional sphericity from PET images: prognostic value in NSCLC and impact of delineation method

(2017) Mathieu Hatt et al.   EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING

Prediction of disease-free survival by the PET/CT radiomic signature in non-small cell lung cancer patients undergoing surgery

(2017) Margarita Kirienko et al.   EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING

Radiomics and its emerging role in lung cancer research, imaging biomarkers and clinical management: State of the art

(2017) Geewon Lee et al.   EUROPEAN JOURNAL OF RADIOLOGY

Characterization of Pulmonary Nodules Based on Features of Margin Sharpness and Texture

(2017) José Raniery Ferreira et al.   JOURNAL OF DIGITAL IMAGING

Application of the 3D slicer chest imaging platform segmentation algorithm for large lung nodule delineation

(2017) Stephen S. F. Yip et al.   PLoS One

Development and clinical application of radiomics in lung cancer

(2017) Bojiang Chen et al.   Radiation Oncology

Diagnostic performance of 18F-FDG PET/CT in solitary pulmonary nodules of non-smokers

(2017) Sevda Sağlampınar Karyağar   Turk Gogus Kalp Damar Cerrahisi Dergisi-Turkish Journal of Thoracic and Cardiovascular Surgery

Diagnostic classification of solitary pulmonary nodules using dual time 18F-FDG PET/CT image texture features in granuloma-endemic regions

(2017) Song Chen et al.   Scientific Reports

PET Radiomics in NSCLC: state of the art and a proposal for harmonization of methodology

(2017) M. Sollini et al.   Scientific Reports

Assessment of Heterogeneity Difference Between Edge and Core by Using Texture Analysis

(2016) Shiteng Suo et al.   ACADEMIC RADIOLOGY

Imaging Heterogeneity in Lung Cancer: Techniques, Applications, and Challenges

(2016) Usman Bashir et al.   AMERICAN JOURNAL OF ROENTGENOLOGY

A Combination of Shape and Texture Features for Classification of Pulmonary Nodules in Lung CT Images

(2016) Ashis Kumar Dhara et al.   JOURNAL OF DIGITAL IMAGING

Predicting Malignant Nodules from Screening CT Scans

(2016) Samuel Hawkins et al.   Journal of Thoracic Oncology

Repeatability of Radiomic Features in Non-Small-Cell Lung Cancer [18F]FDG-PET/CT Studies: Impact of Reconstruction and Delineation

(2016) Floris H. P. van Velden et al.   MOLECULAR IMAGING AND BIOLOGY

Radiomics Signature: A Potential Biomarker for the Prediction of Disease-Free Survival in Early-Stage (I or II) Non—Small Cell Lung Cancer

(2016) Yanqi Huang et al.   RADIOLOGY

Radiomics: Images Are More than Pictures, They Are Data

(2016) Robert J. Gillies et al.   RADIOLOGY

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

Exploratory Study to Identify Radiomics Classifiers for Lung Cancer Histology

(2016) Weimiao Wu et al.   Frontiers in Oncology

Non-small cell lung cancer: quantitative phenotypic analysis of CT images as a potential marker of prognosis

(2016) Jiangdian Song et al.   Scientific Reports

Prevalence of incidental pulmonary nodules on computed tomography of the thorax in trauma patients

(2015) G. Hammerschlag et al.   INTERNAL MEDICINE JOURNAL

Deep learning

(2015) Yann LeCun et al.   NATURE

Textural features in pre-treatment [F18]-FDG-PET/CT are correlated with risk of local recurrence and disease-specific survival in early stage NSCLC patients receiving primary stereotactic radiation therapy

(2015) Thomas Pyka et al.   Radiation Oncology

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

(2015) Anastasia Chalkidou et al.   PLoS One

Imaging Intratumor Heterogeneity: Role in Therapy Response, Resistance, and Clinical Outcome

(2014) J. P. B. O'Connor et al.   CLINICAL CANCER RESEARCH

FDG uptake heterogeneity evaluated by fractal analysis improves the differential diagnosis of pulmonary nodules

(2014) Kenta Miwa et al.   EUROPEAN JOURNAL OF RADIOLOGY

Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

(2014) Hugo J. W. L. Aerts et al.   Nature Communications

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

Texture analysis of advanced non-small cell lung cancer (NSCLC) on contrast-enhanced computed tomography: prediction of the response to the first-line chemotherapy

(2013) Marco Ravanelli et al.   EUROPEAN RADIOLOGY

Probability of Cancer in Pulmonary Nodules Detected on First Screening CT

(2013) Annette McWilliams et al.   NEW ENGLAND JOURNAL OF MEDICINE

Studio comparativo con esame TC contrastografico e con PET-TC del tumore polmonare non a piccole cellule

(2013) Luca Brunese et al.   MEDICAL SCIENCE MONITOR

Publication bias: What are the challenges and can they be overcome?

(2012) Ridha Joober et al.   JOURNAL OF PSYCHIATRY & NEUROSCIENCE

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

Primary vs Metastatic Pulmonary Adenocarcinoma

(2010) Dani S. Zander   CHEST

An open-source toolkit for the volumetric measurement of CT lung lesions

(2010) Karthik Krishnan et al.   OPTICS EXPRESS

Incidentally detected small pulmonary nodules on CT

(2009) A.J. Edey et al.   CLINICAL RADIOLOGY