Can Radiomics of Dynamic PET Imaging with 11C-methionine Predict EGFR Amplification Status in Glioblastoma?

Introduction: Epidermal growth factor receptor (EGFR) amplification predicts poor survival in patients with brain gliomas. Purpose: This study aimed to evaluate whether EGFR amplification status can be predicted using radiomics data from dynamic PET scanning with 11C-methionine. Materials and Metho...

Full description

Bibliographic Details
Published in:	Applied Medical Informatics
Main Authors:	Gleb DANILOV, Andrey POSTNOV, Diana KALAEVA, Nina VIKHROVA, Tatyana KOBYAKOVA
Format:	Article
Language:	English
Published:	Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca 2024-11-01
Subjects:	Glioblastoma Radiomics Positron Emission Tomography Computed Tomography Artificial Intelligence Epidermal growth factor receptor
Online Access:	https://ami.info.umfcluj.ro/index.php/AMI/article/view/1072

Similar Items

Resection of positive tissue on methionine‐PET is associated with improved survival in glioblastomas
by: Kazufumi Ohmura, et al.
Published: (2023-12-01)

Transfer learning–based PET/CT three-dimensional convolutional neural network fusion of image and clinical information for prediction of EGFR mutation in lung adenocarcinoma
by: Xiaonan Shao, et al.
Published: (2024-03-01)

New research progress on 18F-FDG PET/CT radiomics for EGFR mutation prediction in lung adenocarcinoma: a review
by: Xinyu Ge, et al.
Published: (2023-11-01)

Current status and prospect of PET-related imaging radiomics in lung cancer
by: Xin Tang, et al.
Published: (2023-12-01)

18F-FDG PET/CT-based radiomics nomogram could predict bone marrow involvement in pediatric neuroblastoma
by: Lijuan Feng, et al.
Published: (2022-09-01)

Value of 18F-FDG PET/CT-Based Radiomics Nomogram to Predict Survival Outcomes and Guide Personalized Targeted Therapy in Lung Adenocarcinoma With EGFR Mutations
by: Bin Yang, et al.
Published: (2020-11-01)

Value of 18F-FDG-PET/CT radiomics combined with clinical variables in the differential diagnosis of malignant and benign vertebral compression fractures
by: Xun Wang, et al.
Published: (2023-10-01)

Imaging phenotyping using 18F-FDG PET/CT radiomics to predict micropapillary and solid pattern in lung adenocarcinoma
by: Linyi Zhou, et al.
Published: (2024-01-01)

[18F]FDG PET-Based Radiomics and Machine Learning for the Assessment of Gliomas and Glioblastomas: A Systematic Review
by: Francesco Dondi, et al.
Published: (2025-01-01)

CT texture analysis of lung adenocarcinoma: can Radiomic features be surrogate biomarkers for EGFR mutation statuses
by: Dongdong Mei, et al.
Published: (2018-12-01)

Gastro-Esophageal Cancer: Can Radiomic Parameters from Baseline <sup>18</sup>F-FDG-PET/CT Predict the Development of Distant Metastatic Disease?
by: Ricarda Hinzpeter, et al.
Published: (2024-06-01)

Interobserver ground-truth variability limits performance of automated glioblastoma segmentation on [18F]FET PET
by: Selene De Sutter, et al.
Published: (2025-06-01)

Development and External Validation of [18F]FDG PET-CT-Derived Radiomic Models for Prediction of Abdominal Aortic Aneurysm Growth Rate
by: Simran Singh Dhesi, et al.
Published: (2025-02-01)

18F-FDG PET/CT radiomics for prediction of lymphovascular invasion in patients with early stage non-small cell lung cancer
by: Jie Wang, et al.
Published: (2023-07-01)

An Automated Method for Artifical Intelligence Assisted Diagnosis of Active Aortitis Using Radiomic Analysis of FDG PET-CT Images
by: Lisa M. Duff, et al.
Published: (2023-02-01)

Can we skip invasive biopsy of sentinel lymph nodes? A preliminary investigation to predict sentinel lymph node status using PET/CT-based radiomics
by: Liping Yang, et al.
Published: (2024-10-01)

[68Ga]Ga‑PSMA‑617 PET-based radiomics model to identify candidates for active surveillance amongst patients with GGG 1–2 prostate cancer at biopsy
by: Jinhui Yang, et al.
Published: (2024-07-01)

Value of PET radiomic features for diagnosis and reccurence prediction of newly diagnosed oral squamous cell carcinoma
by: Elisabeth Pfaehler, et al.
Published: (2025-05-01)

Feasibility on the Use of Radiomics Features of 11[C]-MET PET/CT in Central Nervous System Tumours: Preliminary Results on Potential Grading Discrimination Using a Machine Learning Model
by: Giorgio Russo, et al.
Published: (2021-12-01)

Artificial Intelligence Applications on Restaging [<sup>18</sup>F]FDG PET/CT in Metastatic Colorectal Cancer: A Preliminary Report of Morpho-Functional Radiomics Classification for Prediction of Disease Outcome
by: Pierpaolo Alongi, et al.
Published: (2022-03-01)

Advances in the application of 18F-FDG PET/CT radiomics for diagnosis, treatment and prognosis prediction of lymphoma
by: CHENG Ran, et al.
Published: (2023-06-01)

Comparison of Radiomics and conventional SUVr methods for Alzheimer’s disease classification using AV45 PET imaging
by: Haiyan Gao, et al.
Published: (2025-08-01)

Exploratory analysis of radiomic as prognostic biomarkers in 18F-FDG PET/CT scan in uterine cervical cancer
by: Nadja Rolim Gonçalves de Alencar, et al.
Published: (2022-12-01)

18F-FDG PET/CT-based radiomics nomogram for the preoperative prediction of lymph node metastasis in gastric cancer
by: Xiu-qing Xue, et al.
Published: (2022-08-01)

A positron emission tomography radiomic signature for distant metastases risk in oropharyngeal cancer patients treated with definitive chemoradiotherapy
by: N. Patrik Brodin, et al.
Published: (2022-01-01)

Patterns of intersectional tumor volumes in T2-weighted MRI and [18F]FET PET in adult glioma: a prospective, observational study
by: Jonathan Weller, et al.
Published: (2024-10-01)

18F-FDG PET/CT radiomics signature and clinical parameters predict progression-free survival in breast cancer patients: A preliminary study
by: Xiaojun Xu, et al.
Published: (2023-03-01)

Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics
by: Virginia Liberini, et al.
Published: (2022-06-01)

11C-methionine in the diagnostics and management of glioblastoma patients with rapid early progression: nonrandomized, open label, prospective clinical trial (GlioMET)
by: Radek Lakomý, et al.
Published: (2024-06-01)

Robustness of PET Radiomics Features: Impact of Co-Registration with MRI
by: Alessandro Stefano, et al.
Published: (2021-10-01)

A Retrospective Comparative Study of Sodium Fluoride (NaF-18)-PET/CT and Fluorocholine (F-18-CH) PET/CT in the Evaluation of Skeletal Metastases in Metastatic Prostate Cancer Using a Volumetric 3-D Radiomics Analysis
by: Kalevi Kairemo, et al.
Published: (2020-12-01)

The Role of EGFR Amplification in Deep Venous Thrombosis Occurrence in IDH Wild-Type Glioblastoma
by: Brandon Kaye, et al.
Published: (2023-05-01)

Conventional and novel [18F]FDG PET/CT features as predictors of CAR-T cell therapy outcome in large B-cell lymphoma
by: Doris Leithner, et al.
Published: (2024-04-01)

Development and validation of a machine learning-based 18F-fluorodeoxyglucose PET/CT radiomics signature for predicting gastric cancer survival
by: Huaiqing Zhi, et al.
Published: (2024-07-01)

A Novel Deep Learning Radiomics Model to Discriminate AD, MCI and NC: An Exploratory Study Based on Tau PET Scans from ADNI
by: Yan Zhao, et al.
Published: (2022-08-01)

Survival Outcome Prediction in Glioblastoma: Insights from MRI Radiomics
by: Effrosyni I. Styliara, et al.
Published: (2024-04-01)

Prediction of lymph node metastasis in lung adenocarcinoma using a PET/CT radiomics-based ensemble learning model and its pathological basis
by: Shulin Li, et al.
Published: (2025-08-01)

Two-grade metabolic tumour tissue assessment using positron emission tomography in prediction of overall survival in glioblastoma patients
by: Lučić Silvija, et al.
Published: (2021-01-01)

Deep learning-based tumor segmentation and radiogenomic model for predicting EGFR amplification and assessing intratumoural heterogeneity in glioblastoma
by: Jianpeng Liu, et al.
Published: (2025-07-01)

Correction: Prediction of lymph node metastasis in lung adenocarcinoma using a PET/CT radiomics-based ensemble learning model and its pathological basis
by: Shulin Li, et al.
Published: (2025-10-01)