CT-based radiomics for preoperative prediction of early recurrent hepatocellular carcinoma: Technical reproducibility of acquisition and scanners

H Hu, Q Shan, S Chen, B Li, S Feng, E Xu, X Li… - La radiologia …, 2020 - Springer
Purpose To test the technical reproducibility of acquisition and scanners of CT image-based
radiomics model for early recurrent hepatocellular carcinoma (HCC). Methods We included …

Development of a radiomics nomogram based on the 2D and 3D CT features to predict the survival of non-small cell lung cancer patients

L Yang, J Yang, X Zhou, L Huang, W Zhao, T Wang… - European …, 2019 - Springer
Objectives The aim of this study was to develop a radiomics nomogram by combining the
optimized radiomics signatures extracted from 2D and/or 3D CT images and clinical …

[HTML][HTML] Incorporating radiomics into clinical trials: expert consensus endorsed by the European Society of Radiology on considerations for data-driven compared to …

L Fournier, L Costaridou, L Bidaut, N Michoux… - European …, 2021 - Springer
Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue
characteristics and follow a well-understood path of technical, biological and clinical …

[HTML][HTML] Applications of radiomics in precision diagnosis, prognostication and treatment planning of head and neck squamous cell carcinomas

SP Haider, B Burtness, WG Yarbrough… - Cancers of the head & …, 2020 - Springer
Recent advancements in computational power, machine learning, and artificial intelligence
technology have enabled automated evaluation of medical images to generate quantitative …

[HTML][HTML] Independent and reproducible hippocampal radiomic biomarkers for multisite Alzheimer's disease: diagnosis, longitudinal progress and biological basis

K Zhao, Y Ding, Y Han, Y Fan, AF Alexander-Bloch… - Science Bulletin, 2020 - Elsevier
Hippocampal morphological change is one of the main hallmarks of Alzheimer's disease
(AD). However, whether hippocampal radiomic features are robust as predictors of …

[HTML][HTML] Radiomics for classification of bone mineral loss: a machine learning study

S Rastegar, M Vaziri, Y Qasempour, MR Akhash… - Diagnostic and …, 2020 - Elsevier
Purpose The purpose of this study was to develop predictive models to classify
osteoporosis, osteopenia and normal patients using radiomics and machine learning …

Radiomic analysis of soft tissues sarcomas can distinguish intermediate from high‐grade lesions

VDA Corino, E Montin, A Messina… - Journal of Magnetic …, 2018 - Wiley Online Library
Purpose To assess the feasibility of grading soft tissue sarcomas (STSs) using MRI features
(radiomics). Materials and Methods MRI (echo planar SE, 1.5 T) from 19 patients with STSs …

Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer

H Abdollahi, B Mofid, I Shiri, A Razzaghdoust… - La radiologia …, 2019 - Springer
Objective To develop different radiomic models based on the magnetic resonance imaging
(MRI) radiomic features and machine learning methods to predict early intensity-modulated …

[HTML][HTML] Radiomics in head and neck cancer: from exploration to application

AJ Wong, A Kanwar, AS Mohamed… - Translational cancer …, 2016 - ncbi.nlm.nih.gov
In the context of clinical oncology, a fundamental goal of radiomics is the extraction of large
amounts of quantitative features whose subsequent analysis can be used for decision …

Radiomics in medical imaging: pitfalls and challenges in clinical management

R Fusco, V Granata, G Grazzini, S Pradella… - Japanese journal of …, 2022 - Springer
Background Radiomics and radiogenomics are two words that recur often in language of
radiologists, nuclear doctors and medical physicists especially in oncology field. Radiomics …