1₈ f-fdg pet/ct habitat radiomics predicts outcome of patients with cervical cancer treated with chemoradiotherapy

Purpose: To determine if quantitative features extracted from pretherapy fluorine 18 fluorodeoxyglucose (¹⁸F-FDG) PET/CT estimate prognosis in patients with locally advanced cervical cancer treated with chemoradiotherapy. Materials and Methods: In this retrospective study, PET/CT images and outcomes were curated from 154 patients with locally advanced cervical cancer, who underwent chemoradiotherapy from two institutions between March 2008 and June 2016, separated into independent training (n = 78; mean age, 51 years 6 13 [standard deviation]) and testing (n = 76; mean age, 50 years 6 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: The radiomics nomograms constructed with T stage, lymph node status, and radiomics signatures resulted in significantly better performance for the estimation of PFS (Harrell concordance index [C-index], 0.85 for training and 0.82 for test) and OS (C-index, 0.86 for training and 0.82 for test) compared with International Federation of Gynecology and Obstetrics staging system (C-index for PFS, 0.70 for training [P = .001] and 0.70 for test [P = .002]; C-index for OS, 0.73 for training [P, .001] and 0.70 for test [P, .001]), respectively. Conclusion: Prognostic models were generated and validated from quantitative analysis of¹⁸F-FDG PET/CT habitat images and clinical data, and may have the potential to identify the patients who need more aggressive treatment in clinical practice, pending further validation with larger prospective cohorts.