Cargando…

Assessing radiomic feature robustness to interpolation in (18)F-FDG PET imaging

Radiomic studies link quantitative imaging features to patient outcomes in an effort to personalise treatment in oncology. To be clinically useful, a radiomic feature must be robust to image processing steps, which has made robustness testing a necessity for many technical aspects of feature extract...

Descripción completa

Detalles Bibliográficos
Autores principales:	Whybra, Philip, Parkinson, Craig, Foley, Kieran, Staffurth, John, Spezi, Emiliano
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Nature Publishing Group UK 2019
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6609613/ https://www.ncbi.nlm.nih.gov/pubmed/31273242 http://dx.doi.org/10.1038/s41598-019-46030-0

Ejemplares similares

Evaluation of prognostic models developed using standardised image features from different PET automated segmentation methods
por: Parkinson, Craig, et al.
Publicado: (2018)

Discovery of stable and prognostic CT-based radiomic features independent of contrast administration and dimensionality in oesophageal cancer
por: Piazzese, Concetta, et al.
Publicado: (2019)

Sensitivity of standardised radiomics algorithms to mask generation across different software platforms
por: Whybra, Philip, et al.
Publicado: (2023)

Radiomic Features of (18)F-FDG PET in Hodgkin Lymphoma Are Predictive of Outcomes
por: Zhou, Yeye, et al.
Publicado: (2021)

Quantitative accuracy of radiomic features of low-dose (18)F-FDG PET imaging
por: Gao, Xin, et al.
Publicado: (2020)

The Influence of the Exclusion of Central Necrosis on [(18)F]FDG PET Radiomic Analysis
por: Noortman, Wyanne A., et al.
Publicado: (2021)

Influence of age on radiomic features in (18)F-FDG PET in normal breast tissue and in breast cancer tumors
por: Boughdad, Sarah, et al.
Publicado: (2018)

Ability of (18)F-FDG PET/CT Radiomic Features to Distinguish Breast Carcinoma from Breast Lymphoma
por: Ou, Xuejin, et al.
Publicado: (2019)

Predicting EGFR mutation subtypes in lung adenocarcinoma using (18)F-FDG PET/CT radiomic features
por: Liu, Qiufang, et al.
Publicado: (2020)

The impact of baseline (18)F-FDG PET-CT on the management and outcome of patients with gastric cancer
por: Foley, Kieran G, et al.
Publicado: (2022)

Quantitative classification and radiomics of [(18)F]FDG-PET/CT in indeterminate thyroid nodules
por: de Koster, Elizabeth J., et al.
Publicado: (2022)

[(18)F]FDG-PET/CT radiomics for the identification of genetic clusters in pheochromocytomas and paragangliomas
por: Noortman, Wyanne A., et al.
Publicado: (2022)

Radiomics–clinical nomogram based on pretreatment 18F-FDG PET-CT radiomics features for individualized prediction of local failure in nasopharyngeal carcinoma
por: Ding, Jianming, et al.
Publicado: (2023)

(18)F-FDG-PET-based radiomics features to distinguish primary central nervous system lymphoma from glioblastoma
por: Kong, Ziren, et al.
Publicado: (2019)

Prognostic Value of Baseline Radiomic Features of (18)F-FDG PET in Patients with Diffuse Large B-Cell Lymphoma
por: Lue, Kun-Han, et al.
Publicado: (2020)

Impact of Aggregation Methods for Texture Features on Their Robustness Performance: Application to Nasopharyngeal (18)F-FDG PET/CT
por: Peng, Lihong, et al.
Publicado: (2023)

Robustness of magnetic resonance radiomic features to pixel size resampling and interpolation in patients with cervical cancer
por: Park, Shin-Hyung, et al.
Publicado: (2021)

(18)F-FDG Pet Parameters and Radiomics Features Analysis in Advanced Nsclc Treated with Immunotherapy as Predictors of Therapy Response and Survival
por: Polverari, Giulia, et al.
Publicado: (2020)

Incorporating radiomic feature of pretreatment (18)F-FDG PET improves survival stratification in patients with EGFR-mutated lung adenocarcinoma
por: Chen, Yu-Hung, et al.
Publicado: (2020)

(18)F-FDG PET baseline radiomics features improve the prediction of treatment outcome in diffuse large B-cell lymphoma
por: Eertink, Jakoba J., et al.
Publicado: (2021)

The prognostic value of radiomic features from pre- and post-treatment (18)F-FDG PET imaging in patients with nasopharyngeal carcinoma
por: Kim, Soo Jeong, et al.
Publicado: (2023)

Radiomic assessment of oesophageal adenocarcinoma: a critical review of 18F-FDG PET/CT, PET/MRI and CT
por: O’Shea, Robert J., et al.
Publicado: (2022)

Impact of respiratory motion on (18)F‐FDG PET radiomics stability: Clinical evaluation with a digital PET scanner
por: Chen, Yu‐Hung, et al.
Publicado: (2023)

Radiomic analysis for predicting prognosis of colorectal cancer from preoperative (18)F-FDG PET/CT
por: Lv, Lilang, et al.
Publicado: (2022)

Frontiers and hotspots of (18)F-FDG PET/CT radiomics: A bibliometric analysis of the published literature
por: Liu, Xinghai, et al.
Publicado: (2022)

Repeatability of Radiomic Features in Non-Small-Cell Lung Cancer [(18)F]FDG-PET/CT Studies: Impact of Reconstruction and Delineation
por: van Velden, Floris H. P., et al.
Publicado: (2016)

Reproducibility of F18‐FDG PET radiomic features for different cervical tumor segmentation methods, gray‐level discretization, and reconstruction algorithms
por: Altazi, Baderaldeen A., et al.
Publicado: (2017)

Diagnostic Performance of Machine Learning Models Based on (18)F-FDG PET/CT Radiomic Features in the Classification of Solitary Pulmonary Nodules
por: Salihoğlu, Yavuz Sami, et al.
Publicado: (2022)

Comparison of Conventional and Radiomic Features between (18)F-FBPA PET/CT and PET/MR
por: Liao, Chien-Yi, et al.
Publicado: (2021)

Prognostic (18)F-FDG Radiomic Features in Advanced High-Grade Serous Ovarian Cancer
por: Travaglio Morales, Daniela, et al.
Publicado: (2023)

External Validation of Radiation-Induced Dyspnea Models on Esophageal Cancer Radiotherapy Patients
por: Shi, Zhenwei, et al.
Publicado: (2019)

Case report of (18)F-FDG PET/CT features of hypoglycemic encephalopathy
por: Shen, Xun-Ze, et al.
Publicado: (2023)

PET probes beyond (18)F-FDG
por: Jiang, Lei, et al.
Publicado: (2014)

A novel iterative modified bicubic interpolation method enables high-contrast and high-resolution image generation for F-18 FDG-PET
por: Okizaki, Atsutaka, et al.
Publicado: (2017)

Repeatability of (18)F‐FDG PET radiomic features: A phantom study to explore sensitivity to image reconstruction settings, noise, and delineation method
por: Pfaehler, Elisabeth, et al.
Publicado: (2018)

Can (18)F-FDG PET/CT Radiomics Features Predict Clinical Outcomes in Patients with Locally Advanced Esophageal Squamous Cell Carcinoma?
por: Jayaprakasam, Vetri Sudar, et al.
Publicado: (2022)

Measurement Repeatability of (18)F-FDG PET/CT Versus (18)F-FDG PET/MRI in Solid Tumors of the Pelvis
por: Fraum, Tyler J., et al.
Publicado: (2019)

Radiomic Profiling of Head and Neck Cancer: (18)F-FDG PET Texture Analysis as Predictor of Patient Survival
por: Feliciani, G., et al.
Publicado: (2018)

Preoperative prediction of pathological grade in pancreatic ductal adenocarcinoma based on (18)F-FDG PET/CT radiomics
por: Xing, Haiqun, et al.
Publicado: (2021)

Breast Tumor Characterization Using [(18)F]FDG-PET/CT Imaging Combined with Data Preprocessing and Radiomics
por: Krajnc, Denis, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_nlh2aa1o0m477i3go5b89haeol