PURPOSE To determine if the radiomic features on CT can predict progression-free survival (PFS) in epidermal growth factor receptor (EGFR) mutant adenocarcinoma patients treated with first-line EGFR tyrosine kinase inhibitors (TKIs) and to identify the incremental value of radiomic features over conventional clinical factors in PFS prediction. METHODS In this institutional review board-approv...

Objectives We evaluate the feasibility of treatment response prediction using MRI-based pre-, post-, and delta-radiomic features for locally advanced rectal cancer (LARC) patients treated by neoadjuvant chemoradiation therapy (nCRT). Materials Methods This retrospective study included 53 LARC divided into a training set (Center#1, n = 36) external validation (Center#2, 17). T2-weighted (T2W) MR...

The present study proposed a computer-aided diagnosis system based on radiomic features extracted through magnetic resonance imaging to determine the isocitrate dehydrogenase status in glioblastomas. Magnetic resonance imaging data were obtained from 32 patients with wild-typeisocitrate dehydrogenase and 7 patients with mutant isocitrate dehydrogenase in glioblastomas. Radiomic features, namely...

Abstract Background and Aims Prediction of future graft failure with non-invasive investigations is a relevant objective for transplant clinicians. We previously demonstrated promising discrimination capacity interstitial fibrosis / tubular atrophy (IFTA) >50% in kidney biopsy machine learning (ML) based magnetic resonance imaging (MRI) radiomic algorithm. Aim the present study to evalua...

We aimed to compare quantitative radiomic parameters from dual-energy computed tomography (DECT) of lung adenocarcinoma and pathologic complexity.A total 89 tumors with clinical stage I/II lung adenocarcinoma were prospectively included. Fifty one radiomic features were assessed both from iodine images and non-contrast images of DECT datasets. Comprehensive histologic subtyping was evaluated wi...

Objectives New markers are required to predict chemoradiation response in oropharyngeal squamous cell carcinoma (OPSCC) patients. This study evaluated the ability of magnetic resonance (MR) radiomics locoregional control (LRC) and overall survival (OS) after aimed determine whether this has added value traditional clinical outcome predictors. Methods 177 OPSCC patients were eligible for study. ...

Radiomics (radiogenomics) characterizes tumor phenotypes based on quantitative image features derived from routine radiologic imaging to improve cancer diagnosis, prognosis, prediction and response to therapy. Although radiomic features must be reproducible to qualify as biomarkers for clinical care, little is known about how routine imaging acquisition techniques/parameters affect reproducibil...

Radiomics focuses on extracting a large number of quantitative imaging features and testing both their correlation with clinical characteristics prognostic predictive values. We propose radiomic approach using magnetic resonance (MRI) to decode tumor phenotype local recurrence in oropharyngeal squamous cell carcinoma (OPSCC). The contrast-enhanced T1-weighted sequences from baseline MRI examina...