Litcius/Paper detail

<sup>18</sup>F-FDG PET/CT Habitat Radiomics Predicts Outcome of Patients with Cervical Cancer Treated with Chemoradiotherapy

Wei Mu, Ying Liang, Lawrence Hall, Yan Tan, Yoganand Balagurunathan, Robert M. Wenham, Ning Wu, Jie Tian, Robert J. Gillies

2020Radiology Artificial Intelligence54 citationsDOIOpen Access PDF

Abstract

PURPOSE: F-FDG) PET/CT estimate prognosis in patients with locally advanced cervical cancer treated with chemoradiotherapy. MATERIALS AND METHODS: = 76; mean age, 50 years ± 10) cohorts. Radiomic features were extracted from PET, CT, and habitat (subregions with different metabolic characteristics) images that were derived by fusing PET and CT images. Parsimonious sets of these features were identified by the least absolute shrinkage and selection operator analysis and used to generate predictive radiomics signatures for progression-free survival (PFS) and overall survival (OS) estimation. Prognostic validation of the radiomic signatures as independent prognostic markers was performed using multivariable Cox regression, which was expressed as nomograms, together with other clinical risk factors. RESULTS: < .001]), respectively. CONCLUSION: © RSNA, 2020.

Topics & Concepts

RadiomicsCervical cancerChemoradiotherapyMedicinePet imagingNuclear medicinePositron emission tomographyCancerOncologyRadiologyInternal medicineRadiomics and Machine Learning in Medical ImagingMedical Imaging Techniques and ApplicationsAdvanced X-ray and CT Imaging